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NURS 6051 Discussion Application of Data to Problem-Solving

NURS 6051 Discussion Application of Data to Problem-Solving

NURS 6051 Discussion Application of Data to Problem-Solving

Few professions in the modern era do not rely on data to some extent. Stockbrokers rely on market data to provide financial advice to their clients. Meteorologists use weather data to forecast weather conditions, while realtors use data to advise on property purchases and sales. In these and other cases, data not only aids in problem solving but also contributes to the practitioner’s and discipline’s body of knowledge.
Of course, the nursing profession is heavily reliant on data as well. Nursing informatics seeks to ensure that nurses have access to the most up-to-date information in order to solve healthcare problems, make decisions in the best interests of patients, and contribute to knowledge.
In this Discussion, you will consider a scenario that would benefit from data access and how such access could aid in problem solving and knowledge formation.

The growth, development, and learned behaviors that occur during the first year of infancy have a direct effect on the individual throughout a lifetime. For this assignment, research an environmental factor that poses a threat to the health or safety of infants and develop a health promotion that can be presented to caregivers.

Create a 10-12 slide PowerPoint health promotion, with speaker notes, that outlines a teaching plan. For the presentation of your PowerPoint, use Loom to create a voice over or a video. Include an additional slide for the Loom link at the beginning, and an additional slide for references at the end.

In developing your PowerPoint, take into consideration the health care literacy level of your target audience, as well as the demographic of the caregiver/patient (socioeconomic level, language, culture, and any other relevant characteristic of the caregiver) for which the presentation is tailored.

Findings show that religious engagement among students declines during college, but their spirituality shows substantial growth. “Students become more caring, more tolerant, more connected with others, and more actively engaged in a spiritual quest.” (“Cultivating the Spirit – Spirituality in Higher Education”) The authors also found that spiritual growth enhances other outcomes, such as academic performance, psychological well-being, leadership development, and satisfaction with college. The study also identified a number of college activities that contribute to students’ spiritual growth. Some of these–study abroad, interdisciplinary studies, and service learning–appear to be effective because they expose students to new and diverse people, cultures, and ideas. Spiritual development is also enhanced if students engage in “inner work” through activities such as meditation or self-reflection, or if their professors actively encourage them to explore questions of meaning and purpose. (“Cultivating the Spirit – Spirituality in Higher (Alexander W, 2010)”). By raising public awareness of the key role that spirituality plays in student learning and development, by alerting academic administrators, faculty, and curriculum committees to the importance of spiritual development, and by identifying strategies for enhancing that development, this work encourages institutions to give greater priority to these spiritual aspects of students’ educational and professional development.

To Get Ready:
• Consider the informatics and knowledge work concepts presented in the Resources.
• Consider a hypothetical scenario based on your own healthcare practice or organization in which data access/collection and application would be required or beneficial. Your scenario could include a patient, staff, or management issue or gap.
By the third day of Week 1,
Post a description of your scenario’s main point. Describe the data that could be used as well as how it could be collected and accessed. What kind of knowledge could be derived from that data? How would a nurse leader apply clinical reasoning and judgment to learn from this experience?
By Week 1’s Day 6
Respond to at least two of your colleagues* on two different days, asking clarifying questions about the scenario and data application, or offering additional/alternative ideas for applying nursing informatics principles.
Click the Reply button to the right to reveal the textbox where you can enter your message. Then, to post your message, click the Submit button.
*Note: Throughout this program, your fellow students are referred to as colleagues.

NURS 6051 Discussion Application of Data to Problem-Solving

Week 1 Discussion Post

Importance of Data Collection

The collection of data in healthcare is crucial in improving patient outcomes. Healthcare is ever-changing, with improvements occurring continuously (Laureate Education, 2018). Nurses must be involved in data collection and understand the importance of the interpretation of this data. Then the information can be used to treat patients more effectively, offer a comparison, and give a more tailored plan of care.
ESAS Data Collection
In my current job, we collect data using the Edmonton Symptom Assessment Scale (ESAS). The ESAS symptom tool was initially developed in 1991 to gauge symptom burden in palliative/hospice patients (Hui and Bruera, 2016). On each visit with a patient, they are asked to rate nine symptoms on a zero to ten scale, with ten being the worst possible. Symptoms include pain, depression, and shortness of breath, to mention a few. If unable to rate the nurse rates based on observation. Once the data is collected, it is stored in the EHR and can be viewed at any time. The tool is useful mainly for the comparison of symptom reports and the management of those symptoms. For example, the management of a patient’s pain is crucial in hospice care. If pain was reported and the medication regimen changed or increased, the data collected through the ESAS would help determine if the change was effective. This would be seen by a decrease in the rating for pain with each visit. If the data shows the patient is rating pain at the same level or higher, we would know medication adjustments are warranted again. With this data available and knowing how to interpret it, patients can receive the care they deserve.
Nursing is an “information-intensive profession” (McGonigle and Mastrian, 2017). We, as nurses, must collect, process, and use the data collected every day. As nurse leaders, interpreting the data is critical to providing the best care possible. Data collection, interpretation, and use will continue to be a part of nursing that can be used to improve patient outcomes.

NURS 6051 Discussion Application of Data to Problem-Solving

References

Hui, D., & Bruera, E. (2017, March). The Edmonton Symptom Assessment System 25 years later: Past, present, and future developments. Journal of Pain and Symptom Management. Retrieved November 28, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337174/
Laureate Education (Producer). (2018). Health Informatics and Population Health: Trends in Population Health [Video file]. Baltimore, MD: Author.
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed., pg.9). Burlington, MA: Jones & Bartlett Learning.

Response

This is insightful. The application of healthcare data is important in improving treatment processes. Healthcare data is important in research and evidence-based practice. The success of healthcare practices depends on the accuracy of methods used in data collection. The ESAS symptom tool is one of the most common methods of data collection; the tool was designed to aid the assessment of nine common symptoms of cancer, including nausea, tiredness, pain, depression, drowsiness, anxiety, wellbeing, appetite, and shortness of breath (Hui & Bruera, 2017). The system has successfully been used by different healthcare organizations to collect and analyze patients’ data. The data collected by this tool can be analyzed to enhance quality improvement processes (Moskovitz et al., 2019). For instance, data on pain can be used to enhance pain management among cancer patients and other patients involved in the treatment processes. The data collected can also be used in the determination of trends of healthcare delivery (Pastorino et al., 2019). From the discussion, one of the questions I would ask is; what types of data are collected by The ESAS symptom tool? How can this data be analyzed to determine trends in healthcare delivery processes?

References

Hui, D., & Bruera, E. (2017, March). The Edmonton Symptom Assessment System 25 years later: Past, present, and future developments. Journal of Pain and Symptom Management. Retrieved November 28, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337174/
Moskovitz, M., Jao, K., Su, J., Brown, M. C., Naik, H., Eng, L., … & Liu, G. (2019). Combined cancer patient–reported symptom and health utility tool for routine clinical implementation: a real-world comparison of the ESAS and EQ-5D in multiple cancer sites. Current Oncology, 26(6), 733-741. https://doi.org/10.3747/co.26.5297
Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European journal of public health, 29(Supplement_3), 23-27. https://doi.org/10.1093/eurpub/ckz168

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Discussion – Week 1 initial post

I have spent the last 10 years working in emergency rooms as a staff nurse. One of the biggest challenges that my department faces regularly is delays with getting admitted patients out of the ED and onto their assigned units. These delays negatively impact the patients waiting for emergency treatment in the lobby and hallway stretchers. There are a number of factors that can prolong ED length of stay. Some of these include lack of bed availability due to hospital overcrowding, treatment delays such as loss of IV access, and delays caused by hospital personnel during the handoff report process (Paling et. al, 2020). Some of these factors, such as hospital overcrowding, are unavoidable and difficult to work around, which is why it is important for hospitals to assess which factors they can control to expedite patient flow out of the emergency room.
For my hospital’s scenario, the emergency department would collect data about admission delays that are specifically caused by disruptions in the nursing telephone report process. In my current workplace, there is not a standardized electronic handoff form, despite the fact that several studies have demonstrated the efficiency and increased patient safety outcomes associated with the transition to standardized electronic nursing report (Wolak et al., 2020). Instead, the ED nurse calls the receiving unit on the telephone, gives a verbal patient care handoff, and then transfers the patient to their hospital room. By collecting data about where in the handoff process delays are occurring, the ED could try to streamline the handoff process with the medical floors.

NURS 6051 Discussion Application of Data to Problem-Solving

The emergency department nurses would collect quantitative data about the length of time between the first attempt to call report to the medical floor, and the time of the patient’s actual departure from the ED. The data would be recorded in the section of the EMR called “time to disposition” for each patient that is admitted. The ED leadership team could then pull a certain number of charts per month (or all the admission charts, if time allowed) and assess how long it takes on average for patient transfer to happen after report. Generally, most hospitals set their goals for disposition time for handoff and transfer within a 30-minute window (Potts et. al., 2018). If there are frequent delays causing transfer time to take greater than 30 minutes, the ED leadership team or unit-based council could meet with leadership from the floors where patient transfer takes the longest. By demonstrating the hard numbers associated with patient care delays, the teams could better understand the factors that lead to admission delays and work together to find solutions that expedite the admissions process.

References:

Paling, S., Lambert, J., Clouting, J., González-Esquerré, J., & Auterson, T. (2020). Waiting times in emergency departments: Exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data. Emergency Medicine Journal. https://doi.org/10.1136/emermed-2019-208849
Potts, L., Ryan, C., Diegel-Vacek, L., & Murchek, A. (2018). Improving patient flow from the emergency department utilizing a standardized electronic nursing handoff process. JONA: The Journal of Nursing Administration, 48(9), 432–436. https://doi.org/10.1097/nna.0000000000000645
Wolak, E., Jones, C., Leeman, J., & Madigan, C. (2020). Improving throughput for patients admitted from the Emergency Department. Journal of Nursing Care Quality, 35(4), 380–385. https://doi.org/10.1097/ncq.0000000000000462

Response

This is insightful Andrea; admission delays often lead to adverse treatment outcomes. The delays in patients’ admission to different hospitals are attributed to the increased number of patients or overcrowding. The impacts of delayed admission can be severe, including longer hospital stays, the inability of patients to access appropriate beds, and experienced healthcare experts (Goertz et al., 2020). Most patients leave without getting treatment due to delayed admissions to different healthcare facilities (Paling et al., 2020). There is a need for quality improvement to facilitate improvements in admission rates. The quality improvements should rely on the data collected in the course of operation. The application of the EMR system is one of the best methods of data collection in healthcare (Pastorino et al., 2019). Measuring and recording the time taken during hospital admission is necessary for determining areas that require adjustments. Through the analysis of the collected data or information, healthcare institutions are able to initiate quality improvement processes and ensure effective outcomes in the management of patients. One of the questions that I would ask is: What variables ought to be involved in the data collection processes?

NURS 6051 Discussion Application of Data to Problem-Solving

References

Goertz, L., Pflaeging, M., Hamisch, C., Kabbasch, C., Pennig, L., von Spreckelsen, N., … & Krischek, B. (2020). Delayed hospital admission of patients with aneurysmal subarachnoid hemorrhage: clinical presentation, treatment strategies, and outcome. Journal of neurosurgery, 134(4), 1182-1189. https://doi.org/10.3171/2020.2.JNS20148
Paling, S., Lambert, J., Clouting, J., González-Esquerré, J., & Auterson, T. (2020). Waiting times in emergency departments: Exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data. Emergency Medicine Journal. https://doi.org/10.1136/emermed-2019-208849
Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European journal of public health, 29(Supplement_3), 23-27. https://doi.org/10.1093/eurpub/ckz168

RE: Initial Post

Week 1 Discussion Post

Importance of Data Collection

The collection of data in healthcare is crucial in improving patient outcomes. Healthcare is ever-changing, with improvements occurring continuously (Laureate Education, 2018). Nurses must be involved in data collection and understand the importance of the interpretation of this data. Then the information can be used to treat patients more effectively, offer a comparison, and give a more tailored plan of care.

ESAS Data Collection

In my current job, we collect data using the Edmonton Symptom Assessment Scale (ESAS). The ESAS symptom tool was initially developed in 1991 to gauge symptom burden in palliative/hospice patients (Hui and Bruera, 2016). On each visit with a patient, they are asked to rate nine symptoms on a zero to ten scale, with ten being the worst possible. Symptoms include pain, depression, and shortness of breath, to mention a few. If unable to rate the nurse rates based on observation. Once the data is collected, it is stored in the EHR and can be viewed at any time. The tool is useful mainly for the comparison of symptom reports and the management of those symptoms. For example, the management of a patient’s pain is crucial in hospice care. If pain was reported and the medication regimen changed or increased, the data collected through the ESAS would help determine if the change was effective. This would be seen by a decrease in the rating for pain with each visit. If the data shows the patient is rating pain at the same level or higher, we would know medication adjustments are warranted again. With this data available and knowing how to interpret it, patients can receive the care they deserve.
Nursing is an “information-intensive profession” (McGonigle and Mastrian, 2017). We, as nurses, must collect, process, and use the data collected every day. As nurse leaders, interpreting the data is critical to providing the best care possible. Data collection, interpretation, and use will continue to be a part of nursing that can be used to improve patient outcomes.

NURS 6051 Discussion Application of Data to Problem-Solving

References

Hui, D., & Bruera, E. (2017, March). The Edmonton Symptom Assessment System 25 years later: Past, present, and future developments. Journal of Pain and Symptom Management. Retrieved November 28, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337174/
Laureate Education (Producer). (2018). Health Informatics and Population Health: Trends in Population Health [Video file]. Baltimore, MD: Author.
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed., pg.9). Burlington, MA: Jones & Bartlett Learning.

RE: Initial Post

I appreciated reading your article. It is fascinating to hear the perspectives of various nursing specialties. You discuss the ESAS scale, which is used to measure symptom burden in patients receiving palliative care. This closely resembles a clinical institute of alcohol withdrawal assessment. In these evaluations, a form is filled out and a number appears. These are useful tools, but I’m curious about their potential future. How can we use information technology to improve the efficacy of these evaluations?
In my previous post, I mentioned the possibility of integrating all assessments into software that could potentially display the patient’s health trajectory. We do a great deal of legwork to collect and document these assessments, and it often feels as if we are not getting our money’s worth. Why isn’t this data being analyzed if it is being collected and recorded?

I concur 100 percent. We collect so much information during admissions, evaluations, and discharges, but it is frequently underutilized. Our ESAS screenings utilize data to determine the likelihood of mortality or revocation. Even though the data has been compiled and is easily accessible, few people actually utilize it. In our current system, some of our nurses do not even know how to access it. It is very helpful for me to know how the patient is progressing and whether any adjustments are necessary. We appreciate your comment.

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Initial Post

Excellent post. Where would you look for the data that you are trying to address and how will this help your scenario?

RE: Reply

The information collected by the ESAS screening tool is readily accessible in the EMR of each patient. The likelihood of mortality or revocation is calculated based on the data entered by nurses during admission and routine visits. Each patient’s medical record contains a dashboard containing this information. It provides a visual representation of the patient’s deterioration or response to medication changes, as well as the data collected by visit date. This information helps us understand the progression of the disease and provides insight into what changes must be made to better manage pain, anxiety, and other symptoms. Thank you for your inquiry.

NURS 6051 Discussion Application of Data to Problem-Solving

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Initial Post

This is illuminating. Utilizing healthcare data to enhance treatment procedures is crucial. Healthcare information is essential for research and evidence-based practice. The success of healthcare practices depends on the precision of data collection techniques. The ESAS symptom tool is one of the most prevalent data collection methods; it was designed to assist in the evaluation of nine common cancer symptoms, including nausea, fatigue, pain, depression, drowsiness, anxiety, wellbeing, appetite, and shortness of breath (Hui & Bruera, 2017). Various healthcare organizations have utilized the system successfully to collect and analyze patient data. This instrument collects data that can be analyzed to improve quality improvement processes (Moskovitz et al., 2019). For example, pain data can be used to improve pain management among cancer patients and other patients undergoing treatment. The collected information can also be used to determine trends in healthcare delivery (Pastorino et al., 2019). What kinds of data are collected by the ESAS symptom tool? is one of the questions I would ask based on the discussion. How can this data be analyzed to identify trends in the delivery of healthcare?
References
Hui, D., & Bruera, E. (2017, March). The Edmonton Symptom Assessment System 25 years later: Past, present, and future developments. Journal of Pain and Symptom Management. Retrieved November 28, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337174/
Moskovitz, M., Jao, K., Su, J., Brown, M. C., Naik, H., Eng, L., … & Liu, G. (2019). Combined cancer patient–reported symptom and health utility tool for routine clinical implementation: a real-world comparison of the ESAS and EQ-5D in multiple cancer sites. Current Oncology, 26(6), 733-741. https://doi.org/10.3747/co.26.5297
Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European journal of public health, 29(Supplement_3), 23-27. https://doi.org/10.1093/eurpub/ckz168

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Discussion – Week 1 initial post

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I have spent the last decade as a staff nurse in emergency rooms. Delays in transferring admitted patients from the emergency department (ED) to their assigned units are a persistent obstacle for my department. These delays negatively affect the patients waiting in the lobby and hallways for emergency care. There are a variety of factors that can lengthen ED stays. Lack of bed availability due to hospital overcrowding, treatment delays such as loss of intravenous access, and delays caused by hospital staff during the handoff report process are a few of these issues (Paling et. al, 2020). Some of these factors, such as hospital overcrowding, are unavoidable and difficult to circumvent; therefore, hospitals must determine which variables they can influence to improve patient flow out of the emergency room.
For my hospital’s scenario, the emergency department would collect data on admission delays that are caused by nursing telephone report process disruptions. In my current workplace, there is no standardized electronic handoff form, despite numerous studies demonstrating the increased efficiency and patient safety outcomes associated with the adoption of standardized electronic nursing report forms (Wolak et al., 2020). Instead, the ED nurse contacts the receiving unit via telephone, provides a verbal handoff of patient care, and then transfers the patient to his or her hospital room. By collecting data on where delays occur in the handoff process, the ED could attempt to streamline the handoff process with medical floors.
The emergency department nurses would collect quantitative data on the duration between the patient’s first attempt to call the medical floor and their actual departure from the ED. The data would be recorded in the “time to disposition” section of the EMR for each admitted patient. The ED leadership team could then retrieve a certain number of charts per month (or all admission charts, if time permitted) and determine the average time it takes for patient transfer to occur after report. In general, the majority of hospitals aim to complete handoffs and transfers within a 30-minute window (Potts et. al., 2018). If frequent delays cause patient transfer times to exceed 30 minutes, the ED leadership team or unit-based council could meet with the leadership of the floors where patient transfer times are the longest. By demonstrating the hard numbers associated with patient care delays, teams could better comprehend the factors that lead to admission delays and work collaboratively to find solutions to expedite the process.

References:

Paling, S., Lambert, J., Clouting, J., González-Esquerré, J., & Auterson, T. (2020). Waiting times in emergency departments: Exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data. Emergency Medicine Journal. https://doi.org/10.1136/emermed-2019-208849
Potts, L., Ryan, C., Diegel-Vacek, L., & Murchek, A. (2018). Improving patient flow from the emergency department utilizing a standardized electronic nursing handoff process. JONA: The Journal of Nursing Administration, 48(9), 432–436. https://doi.org/10.1097/nna.0000000000000645
Wolak, E., Jones, C., Leeman, J., & Madigan, C. (2020). Improving throughput for patients admitted from the Emergency Department. Journal of Nursing Care Quality, 35(4), 380–385. https://doi.org/10.1097/ncq.0000000000000462

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Discussion – Week 1 initial post

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Great post. What are some ways that you can bridge the gap between practice and knowledge?
In a large hospital, it can be difficult to bridge the gap between knowing that a process needs improvement and actually incorporating those improvements into daily practice. Once information regarding telephone report delays has been collected, it will be communicated to the nursing staff. Either the administration leadership team or the unit-based practice council could design an electronic report form and solicit feedback on the form through staff meetings. The staff can be trained on a new electronic report form in the EMR once the emergency department decides to take action to address the problem with patient care/transfer delays. The implementation of the new report system will require collaboration and targeted in-service training, but the benefits to the patients should be substantial.

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Main Post – Week 1

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Carter-Templeton (2019) describes the critical function of nursing informatics, which utilizes technology to collect data that will improve clinical processes and clinical judgment, hence enabling the development of future innovations. Carter-Templeton (2019) explains that the Alliance for Nursing Informatics (ANI) intends to transform healthcare through nursing informatics and by allowing ANI leadership to participate in educational opportunities that allow mentorships for a few years to create members who are skilled in communication, networking, negotiation, leadership, and management. Conduent Health Healthcare Provider Solutions (2017) has developed Midas’s online care management system, which transforms data into performance-enhancing information. Conduent Health Healthcare Provider Solutions (2017) provides examples of its capabilities, including as quality improvement and patient risk reduction, case management, and central line infection prevention. Conduent Health Healthcare Provider Solutions (2017) states that it is the largest provider of business processes services with advanced capabilities in analyzing and processing data that is entered into the program to create interventions that directly affect the issue at hand to reduce any adverse risks that are currently occurring in a particular healthcare facility. Midas delivers and develops “an personalised patient care plan worksheet that incorporates goals, results, and actions to meet Joint commission requirements” (Conduent Health Healthcare Provider Solutions, 2017, para 8).
By assessing key events or data stated in the program, the Midas program demonstrates substantial value in producing interventions and favorable results for future nurse leaders. Midas can establish outcomes, but a nurse leader’s ability to comprehend the correct implementation of the outcomes enables him or her to employ clinical reasoning and knowledge-based judgment. Since there is a scarcity of bedside nurses, the nurse-to-patient ratio is an example of a metric that might be used to collect information on current healthcare challenges that are at a record high. Paulson (2018) describes a study and its findings in relation to nurse-patient ratios using nursing informatics.

The hypothetical situation, which will soon be less speculative due to the nursing shortage sweeping every hospital, is based on using the Midas program to enter information regarding when staffing requirements are not reached and how this directly impacts patient care. Paulson (2018) noted that modern hospital personnel compute hours per patient day using the average number of patients in a day multiplied by thirty-one or three hundred and sixty-five days per year. The hour per patient per day does not account for patient acuity, so the number of nurses remains the same regardless of whether patient acuity is average or above average. Paulson (2018) stated that if staffing requirements were not reached on a unit, patient mortality would increase, as would patient mortality if the majority of nurses had less than two years of experience. During this epidemic, many experienced nurses have retired, departed, or accepted travel contracts; hospitals are left with novice nurses and an insufficient number of nurses to adequately staff the hospitals. In any hospital, Midas would be useful for tracking and monitoring mortality rates caused by a nursing shortage and untrained nurses. Through Midas, a nurse leader would utilize clinical judgment and experience to propose actions to reduce mortality in the unit and to guarantee that the unit is adequately staffed.

References

Carter-Templeton, H., & Sensmeier, J. (2019). The Value and Impact of the Alliance for Nursing Informatics Emerging Leaders Program. CIN: Computers, Informatics, Nursing, 37(12), 612–614. https://doi.org/10.1097/CIN.0000000000000603
Conduent Health Healthcare Provider Solutions . (2017). Midas Health Analytics Solutions Care Management – Improving Patient Safety and Quality Management. Retrieved November 27, 2021, from https://downloads.conduent.com/content/usa/en/brochure/midas-care-management.pdf.
Paulson, R. A. (2018, July). Taking Nurse Staffing . Retrieved November 27, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039374/pdf/numa-49-42.pdf.

RE: Main Post – Week 1

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Excellent article. Where would you look for the data you’re looking for, and how will this help your situation?

NURS 6051 Discussion Application of Data to Problem-Solving

Initial Post  Discussion – Week 1

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The application of data to problem solving is the topic of this discussion.

Nursing informatics is crucial for the healthcare industry. The field of nursing informatics combines technology and data to generate new knowledge and evidence that can be utilized by society (Laureate Education, 2018). Nurses utilize nursing informatics by integrating analytical data and science through health information, technology tools, health portals, mobile applications, social networking, and telehealth platforms, thereby enhancing workplace communication and enhancing patient care. Successful health care professionals must be aware that informatics is a tool that, when used strategically and appropriately, can lead to positive outcomes (Laureate Education, 2018).
Identifying sepsis through our EMR system, EPIC, is a nursing scenario that involves the collection and application of data in my healthcare practice. EPIC enables registered nurses to input patient information. I currently work in a Surgical Trauma Intensive Care Unit where patient documentation is nearly minute-by-minute consistent. The Nursing Informatics Team at our hospital developed an epic-based sepsis flagging system that pulls patients’ vital signs (heart rate, blood pressure, temperature, and respirations) in conjunction with lab values (white blood cell counts). If a patient’s lab values and vital signs surpass a critical threshold, a pop-up sepsis alert will indicate that the patient is at risk for sepsis or may be experiencing a septic episode, which must be acknowledged by the nurse and then the provider. This flagging system has been extremely effective in our unit, allowing nurses to implement sepsis treatments or prevent the onset of septicemia. This technological tool developed by the nursing informatics team to flag sepsis through our epic EMR system has decreased septicemia in the intensive care setting.
Nursing Informatic Specialists are an invaluable asset in the health care industry, where technological advancements occur almost daily. This will result in increased responsibility for nursing informatic specialists, thereby expanding their scope of practice as care evolves. In addition to the current competencies, they will be required to assist other clinicians, patients, and families in assuming new roles, and to use data analytics to interpret and appropriately apply new knowledge (Nagle, L. et. al, 2017).

References

Laureate Education (Producer). (2018). Health Informatics and Population Health: Trends in Population Health [Video file]. Baltimore, MD: Author.
Laureate Education (Producer). (2018). What is Informatics? [Video file]. Baltimore, MD: Author.
Nagle, L., Sermeus, W. & Junger, A. (2017). Evolving Rôle of the Nursing Informatics Specialist. In J Murphy, W. Goosen, & P. Weber (EDS.), Forecasting Competencies for Nurses in the Future of Connected Health (212-221). Clifton, VA: IMIA and IOS Press. Retrieved from https://serval.unil.ch/resource/serval:BIB_4A0FEA56B8CB.P001/REF

RE: Initial Post Discussion – Week 1

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Great post. What are some strategies for bridging the gap between practice and knowledge?

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Discussion – Week 1

Main Post – Week 1

A patient or institution’s re-admission to the hospital within 30 days of discharge is a scenario that nurse care managers have been attempting to avoid, but it is still evident. There are numerous reasons why the healthcare system develops processes to reduce the readmission rate; the most significant consequences of readmission are negative effects on the health of the population, poor payor reimbursement or sanction for the institution, and a perception of low-quality service standards (Upadhyay., 2019). Effective discharge planning that includes a thorough assessment of the patient’s social determinants, readmission risk, and barriers to a safe transition to the home or care facility is one of the primary focuses for preventing rehospitalization.
Social determinants such as ability to function independently, place of residence, presence or absence of a support system, availability of transportation to or from appointments, presence of funding or resources to obtain medications, ability to comprehend instructions or level of comprehension, and access to primary healthcare providers are examples of information that must be addressed (Jack et al., 2013). The care team can collect this information from the patient, their family, or their source of support in the emergency department or upon admission, and a nurse care manager can review it at any time. The information will aid the nurse care manager in determining what obstacles must be overcome and what post-hospitalization services or resources the patient will need to successfully manage their care outside the hospital. In addition to social determinants, the LACE readmission risk tool scoring system that considers length of hospital stay, acuity of admission, comorbidities, and emergency department visits can be used to determine the most suitable discharge location for patients who scored highly on this assessment (Miller et al., 2018).
A nurse leader could use the data obtained from the assessment of social determinants and risk scores to gather more information about effective post-hospitalization services in the community that can be offered to patients or their families in the future. It could also result in a review of the current affiliations with accountable care organizations that fail to provide transitional care or the formation of a new partnership with an organization that has the potential to maintain the patient’s optimal health outside the acute care facility. The establishment of a task force to target patients with a high risk of readmission and the development of post-discharge programs designed to maintain their health while keeping them out of the hospital are also potential outcomes of this experience.

References

Jack, B., Paasche-Orlow, M., Mitchell, S., Forsythe, S., & Martin, J. (2013). Re-engineered discharge (red) toolkit. AHRQ. Retrieved November 26, 2021, from https://www.ahrq.gov/sites/default/files/publications/files/redtoolkit.pdf.
Miller, W. D., Nguyen, K., Vangala, S., & Dowling, E. (2018). Clinicians can independently predict 30-day hospital readmissions as well as the lace index. BMC Health Services Research. Retrieved November 26, 2021, from https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-018-2833-3.
Upadhyay, S., Stephenson, A. L., & Smith, D. G. (2019). Readmission rates and Their Impact on Hospital Financial Performance: A Study of Washington Hospitals. Inquiry: a journal of medical care organization, provision and financing. Retrieved November 26, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6614936.

NURS 6051 Discussion Application of Data to Problem-Solving

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We appreciate your post. I felt that many hospital readmissions might be prevented with good discharge planning and education, based on a project I completed for another class. According to Hughes and Whitham (2018), about 30% of readmissions are related to the same ailment or diagnosis for which the patient was initially admitted. It is probable that these patients were not sufficiently informed to manage their symptoms at home following discharge. As you mentioned, it is crucial to understand how these people will be cared for, who will care for them, and what environment they will return to. I also feel that discharge planning should begin on day one in order to avoid any complications and attempt to resolve any concerns discovered prior to the day of discharge. Readmissions are not only a physical and financial burden for the patient, but also for the hospital. Reduction of readmissions enhances the patient’s quality of life and minimizes the budgetary effect (American Hospital Association, n.d.). Collecting data at the beginning and throughout a patient’s stay might be advantageous for minimizing the likelihood of readmission. It would also assist other professions in locating the proper home care resources. Again, many thanks for your post.

References

American Hospital Association. Hospital readmission reduction program: AHA. (n.d.). Retrieved November 30, 2021, from https://www.aha.org/hospital-readmission-reduction-program/home

Hughes, L. D., & Witham, M. D. (2018, August 28). Causes and correlates of 30 day and 180 day readmission following discharge from a medicine for the Elderly Rehabilitation Unit. BMC geriatrics. Retrieved November 30, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114496/

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Excellent post. Where would you look for the data you’re looking for, and how will this help your situation?

NURS 6051 Discussion Application of Data to Problem-Solving

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The readmission data can be obtained by first generating a report for all diagnoses from the EHR. The data can then be formatted to appear in a pie or bar chart so that it is easily readable and interpretable by stakeholders; in my scenario, this would be the care managers. Evaluating or monitoring the report will aid in the development of solutions, such as enhanced post-hospitalization phone calls or virtual visitation programs. There will always be some outliers, but if a program can be designed for the majority of patients, it is likely that the readmission rate will decrease. The readmission risk score can be viewed on the patient information screen for a more real-time application of knowledge to reduce the risk of rehospitalization. This risk score enables care managers to address this information in multi-disciplinary huddles and develop a discharge plan that minimizes the patient’s likelihood of unplanned readmission.

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Medication errors have been selected as the clinical scenario to examine. Medication errors have negative effects on patients’ health. It exposes patients to unintended harm and increases healthcare expenditures (Alqenae et al., 2020). In order to address the issue of medication errors in the institution, data can be utilized. It is possible to collect data on the rate of medication errors, their effects, and the contributing factors. To facilitate the implementation of effective interventions, it is also possible to collect additional data on factors such as the costs of care due to medication errors and the hospital stays of patients affected by the errors. It is possible to collect information on medication errors electronically or by administering questionnaires and surveys to healthcare providers (Tariq et al., 2021). Electronic data include those reported by healthcare providers, as well as the rates of fatalities, cost of care, and length of hospital stays resulting from medication errors.
The data obtained through the aforementioned methods shed light on a variety of medication error-related issues. The severity and prevalence of the problem in the institution is one of them. The data on medication error rates, fatalities, and cost implications will shed light on the severity of the problem (Dash et al., 2019). The data also provides information regarding the error-causing factors. It enables healthcare organizations to determine, for instance, whether errors stem from provider, patient, or organizational issues (Dash et al., 2019). Understanding the importance of examining the cause-and-effect relationship between variables, a nurse leader utilizes clinical reasoning and judgment in the formation of knowledge from this experience. In addition to using clinical judgment and reasoning, a nurse leader identifies facts associated with the issue and develops evidence-based solutions that can be implemented to address them (Ratwani et al., 2018). They can make ethical decisions in their practice as a result.

References

Alqenae, F. A., Steinke, D., & Keers, R. N. (2020). Prevalence and nature of medication errors and medication-related harm following discharge from hospital to community settings: a systematic review. Drug Safety, 43(6), 517–537. https://doi.org/10.1007/s40264-020-00918-3
Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: Management, analysis and future prospects. Journal of Big Data, 6(1), 54. https://doi.org/10.1186/s40537-019-0217-0
Ratwani, R. M., Savage, E., Will, A., Fong, A., Karavite, D., Muthu, N., Rivera, A. J., Gibson, C., Asmonga, D., Moscovitch, B., Grundmeier, R., & Rising, J. (2018). Identifying electronic health record usability and safety challenges in pediatric settings. Health Affairs, 37(11), 1752–1759. https://doi.org/10.1377/hlthaff.2018.0699
Tariq, R. A., Vashisht, R., Sinha, A., & Scherbak, Y. (2021). Medication Dispensing Errors And Prevention. In StatPearls. StatPearls Publishing. http://www.ncbi.nlm.nih.gov/books/NBK519065/

NURS 6051 Discussion Application of Data to Problem-Solving

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The subject of medication errors requires ongoing improvement. They can occur during the prescription of the drug, as a result of pharmacy mistakes, or during the administration of the medication (FDA, n.d.). I believe it would be necessary for data to indicate when an error occurred; therefore, preventing such errors could be a top priority. The collected information could also be used to determine the severity level. According to Gates et al. (2019), it would be beneficial to further classify the severity of the error in order to determine whether the harm was potential or actual. All collected information is essential, regardless of when, where, or to what extent it pertains, because it provides insight into how to prevent a recurrence. Thank you for the post.

References

FDA. (n.d.). Working to reduce medication errors. U.S. Food and Drug Administration. Retrieved December 1, 2021, from https://www.fda.gov/drugs/information-consumers-and-patients-drugs/working-reduce-medication-errors
Gates, P. J., Baysari, M. T., Mumford, V., Raban, M. Z., & Westbrook, J. I. (2019, August). Standardising the classification of harm associated with medication errors: The harm associated with medication error classification (HAMEC). Drug safety. Retrieved December 1, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6647434/

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Great post. What are some ways that you can bridge the gap between practice and knowledge?

NURS 6051 Discussion Application of Data to Problem-Solving

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You chose a topic that unfortunately affects an excessive number of nurses and patients annually. The field of nursing informatics has the potential to significantly reduce the number of medication errors. One of the objectives of the field of nursing informatics is to improve patient safety and quality of care, and reducing and preventing medical errors is essential to this process (McGonigle & Mastrian, 2017). Incorporating scanners for medication bar codes at the bedside is one of the most significant enhancements to medication safety that informatics has already made, albeit several years ago. When nurses began scanning medications prior to administering them to a patient, the majority of studies found a significant decrease in the number and severity of medical errors (Truitt et. al, 2016). Implementing a ‘just culture’ approach to error reporting, in which staff nurses do not feel the need to hide medical errors for fear of punishment or losing their jobs, is an important factor hospitals should consider in order to encourage accurate reporting of medical errors (Rogers et. al, 2017).

References:

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Rogers, E., Griffin, E., Carnie, W., Melucci, J., & Weber, R. J. (2017). A Just Culture Approach to Managing Medication Errors. Hospital pharmacy, 52(4), 308–315. https://doi.org/10.1310/hpj5204-308
Truitt, E., Thompson, R., Blazey-Martin, D., NiSai, D., & Salem, D. (2016). Effect of the Implementation of Barcode Technology and an Electronic Medication Administration Record on Adverse Drug Events. Hospital pharmacy, 51(6), 474–483. https://doi.org/10.1310/hpj5106-474

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Discussion: The Application of Data to Problem-Solving

Explanation of the Target Scenario

If healthcare workers have access to medical records, they can ensure that their patients receive the greatest care (McGonigle & Mastrian, 2017). The immunization scenario will be the focal point of this discussion. The majority of clinicians, medical researchers, and healthcare facilities advocate vaccination. Immunization is necessary for a number of reasons, but the most important is to protect oneself and people around them (Pelullo et al., 2020). Additionally, immunizations can be used to prevent infectious infections. The success of the immunization regimen is contingent upon the patient’s cooperation (Pelullo et al., 2020).
Vaccination is the most effective method for preventing diseases with no medical cure. Therefore, the immunization will protect those at risk of getting illnesses that are incurable and can occasionally lead to complications or death. Immunocompromised individuals are susceptible to these conditions (Gold et al., 2020). Even if these individuals are vaccinated after contracting the disease, the immunization may not aid in the development of a robust immune system. To prevent the disease, it is essential to get vaccinated to ensure that one is entirely protected against developing the condition (Gold et al., 2020). Those who have received vaccinations are unlikely to be at danger for the outbreak.
Currently, my group collaborates with schools, parents, and clinicians using patient immunization records. However, it would be difficult for clinicians to determine if a kid has been vaccinated in households who often relocate across state boundaries and lack immunization records. This will need parents to track out the health data of their children from their previous clinic, the immunization registry, or their previous schools. It will be easier for parents and physicians to obtain patient information if all information is stored in a central database hub.
Utilization of Data Collected and Methods of Data Collection
Data obtained includes: patient name (first, middle, last); patient birth date; patient sex/gender; patient race and ethnicity; patient birth order; patient birth State/country; mother’s name (first, middle, maiden); vaccination type; manufacturer; and vaccine dosage number. Currently, vaccine data are stored in an online database known as Immunization Information Systems (IIS). According to the guidelines of the National Vaccine Advisory Committee, clinicians must have complete access to a patient’s immunization status at every medical visit (Gold et al., 2020). Immunization information systems assist clinicians in administering vaccines to selected individuals in accordance with a tiered prioritizing scheme. This system maintains a record of immunizations provided to patients and notifies clinicians when shots are due (Gold et al., 2020).

NURS 6051 Discussion Application of Data to Problem-Solving

In my facility, clinicians have become fully prepared for vaccine administration and have increased IIS use by: becoming comfortable and familiar with the IIS interface because patient vaccination information is readily available in the system workflow; communicating with the health system’s health IT department to determine if manual data requests are required or if there is a real-time data flow between the system workflow and IIS platform; and getting onboarded by the health system’s health IT department. I would therefore like to build a database that collects and consolidates all of the vaccine information from each office into a central hub. Having this centralized repository of immunization records would allow providers to retrieve immunization records for their new patients. This would allow healthcare practitioners to view the immunization history of their patients and make vaccine-related clinical decisions.

Derived Knowledge

This data contains a vast amount of information. Healthcare practitioners would be able to view both coverage rates and possible disease outbreak zones. They could also observe the effectiveness of communal immunity (herd immunity). According to Ricc et al. (2020), community immunity occurs when enough people are immunized against a particular disease that it becomes difficult for the sickness to spread to unvaccinated individuals. Vaccination clinics utilize immunization information systems to order, dispense, and track vaccines. Utilizing vaccines broadly and equitably will aid in reducing and controlling various ailments (Ricc et al., 2020).
Immunization information systems are a vital component of the infrastructure utilized in vaccine planning to facilitate coordination among numerous partners and systems for vaccine allocation, distribution, administration, and monitoring (Ricc et al., 2020). Clinicians can access vaccination status in real-time via the IIS. In addition to collecting and storing patient information, users can document and track vaccine items and provided doses. With limited initial vaccine supply, IISs can help determine the equitable allocation of available vaccines, plan and forecast when additional doses are necessary, ensure patients receive the correct vaccine, and track vaccination series completion (Ricc et al., 2020).

How Nurse Leaders Use Clinical Reasoning and Judgment in This Experience to Form Knowledge

This experience enables nurse leaders to use clinical reasoning and discretion to ensure that patients do not miss recommended vaccine doses and do not receive additional doses. In addition, when caring for individuals with medical issues, they would have the opportunity to add contraindications and notices pertaining to specific vaccines into the system. This suggests that other physicians would be aware of this if the patients were ever transferred to a hospital or relocated. The ability to access a patient’s immunization record from a central location would be extremely beneficial for both healthcare providers and patients. The more the awareness and connectivity of practitioners with their IIS, the more effective the vaccination campaign will be in addressing equitable vaccine distribution, managing vaccine uptake, and monitoring vaccination series. Strengthening physician participation will result in more robust IIS data, hence strengthening clinical care and public health decision-making, which are essential to routine and emergency immunization programs.

References

Gold, M. S., MacDonald, N. E., McMurtry, C. M., Balakrishnan, M. R., Heininger, U., Menning, L., … & Zuber, P. L. (2020). Immunization stress-related response–redefining immunization anxiety-related reaction as an adverse event following immunization. Vaccine, 38(14), 3015-3020. https://doi.org/10.1016/j.vaccine.2020.02.046
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Pelullo, C. P., Della Polla, G., Napolitano, F., Di Giuseppe, G., & Angelillo, I. F. (2020). Healthcare workers’ knowledge, attitudes, and practices about vaccinations: A cross-sectional study in Italy. Vaccines, 8(2), 148. https://doi.org/10.3390/vaccines8020148
Ricc, M., Vezzosi, L., Gualerzi, G., Bragazzi, N. L., & Balzarini, F. (2020). Pertussis immunization in healthcare workers working in pediatric settings: Knowledge, Attitudes, and Practices (KAP) of Occupational Physicians. Preliminary results from a web-based survey (2017). Journal of Preventive Medicine and Hygiene, 61(1), E66. https://doi.org/10.15167/2421-4248/jpmh2020.61.1.1155

NURS 6051 Discussion Application of Data to Problem-Solving

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Excellent post. Where would you look for the data you’re looking for, and how will this help your situation?

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As a Psychiatric nurse, I believe there is a large disconnect between the practical tasks of nursing and the documentation process. Frequently, paperwork appears pointless and counterproductive. In the case of suicide prevention, I found that data collection and analysis could have made a difference.

I have observed patients successfully commit suicide in the hospital on two occasions. After speaking with other employees who had direct touch with these individuals in the preceding days, I discovered two commonalities. Both patients ate and slept significantly less than normal. Ironically, each night in this facility, sleep hours and food consumption are recorded. However, these numbers are unavailable in any assessment used to estimate a person’s suicide risk. Instead, we discover suicidality in a patient by a suicide risk assessment. A suicide risk assessment consists of questions such as, “Have you ever attempted or attempted suicide?” Do you have a plan to commit suicide? Have you made any preparations? (Dueweke, 2018). In an inpatient psychiatric facility, we ask patients this series of questions twice every day throughout their entire stay. According to Bolster (2015), the suicide risk assessments were equivocal on the patient’s suicidal intent.

I believe informatics could play a role in this case by combining the patient’s assessment information. If they were merged and processed by a much broader algorithm, the patient’s mental/physical health might be determined with greater precision based on the assessments that nurses complete. For instance, a patient’s sleep hours, food intake, body weight fluctuations, medication compliance, PRN requests, suicide risk assessment, and mental status exam score could indicate prospective health trajectories. These potential paths could be displayed as red flags and warnings on an interface.

With this data integration, a nurse leader would be better informed about the overall health of the patient. The nurse leader would have greater access to patient information, enabling them to make more informed decisions on patient care. If there had been an algorithm to detect the patients’ deteriorating mental state, we would have had a greater chance of preventing their suicide.

References

Bolster, C., Holliday, C., Oneal, G., Shaw, M., (2015) “Suicide Assessment and Nurses: What Does the Evidence Show?” OJIN: The Online Journal of Issues in Nursing Vol. 20, No. 1, Manuscript 2.

Dueweke, A. R., & Bridges, A. J. (2018). Suicide Interventions in Primary Care: A Selective Review of the Evidence. Families, Systems, & Health. Advance online publication.http://dx.doi.org/10.1037/fsh000034

NURS 6051 Discussion Application of Data to Problem-Solving

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Great post. What are some strategies for bridging the gap between practice and knowledge?

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According to our textbook, “nurses must possess the technical skills to manage equipment and perform procedures, the interpersonal skills to interact appropriately with individuals, and the cognitive skills to observe, recognize, and collect data; analyze and interpret data; and reach a reasonable conclusion that serves as the basis for a decision.” (McGonigle, D., & Mastrian, K. G.) (2017) We cannot always save lives, whether they are lost to disease, accident, or suicide. This latter circumstance must be devastating, and I empathize with your struggle to obtain assistance to prevent recurrences.
As I read more of our resources to comprehend the informatics aspect of nursing, I will attempt to express my comprehension in my own words. We as nurses are experts in our respective fields, and informatics requires our knowledge, critical thinking, and experience to complete a project; otherwise, there will be gaps “between technology and process.” Consequently, “gaps will persist without a strong clinician presence in the design and implementation process. With the participation of healthcare informaticists, a robust product that is usable by all members of the healthcare team can be delivered. (Sweeney, J.) (2017)

References:

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning
Sweeney, J. (Feb, 2017). Healthcare Informatics. Online Journal of Nursing Informatics (OJNI), 21( 1), Available at http://www.himss.org/ojni

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As I read the assigned readings, I pondered a simpler method for documenting the assessment of a dying patient. Instead of typing on the iPad while sitting next to the patient, which I find insensitive. If only there were a finger device or microphone that could record my thoughts and automatically document them in the correct location on the iPad, I thought.
When working with patients, I was always focused on what was happening with the patient at the time, never considering the steps a nurse must take to be able to engage in critical thinking; it simply occurs. I don’t always realize that I’m utilizing a computer program that a nurse helped to develop; I believe that the majority of the time I’m grumbling about having to document there and elsewhere. I’ve just realized that I could contribute to the creation of a system or to the improvement of my current system by sending IT an email with my thoughts instead of complaining.
Sweeny, J. reports that the American Nurses Association (ANA) defines nursing informatics as “a specialty that integrates nursing, science, computer science, and information science to manage and communicate data, information, and knowledge in nursing practice” (ANA, 2001, Pg.17).
A hospice scenario includes a call to triage from a patient’s family, who report that the patient is fighting and slapping them. This patient’s hospice diagnosis is Dementia. The family of a patient with dementia must respond to the majority of protocol questions and assessments. The nurse used the Symptom Management questions, which include nine symptoms such as pain, nausea, fatigue, and depression, during the visit. It was difficult to obtain vital signs, which were then recorded and compared to previous readings. Spiritual status was documented, and impending death was evaluated. A standard screening instrument for pain was evaluated. Assessing breathing status, negative vocalization, facial expressions, consolability, and body language are components of using the PAINAD scale for assessing Advanced Dementia. Each question has three possible responses; the total score indicates whether the patient is in pain since they cannot express it verbally. This patient scored 12 or higher, indicating pain. The Medical Director was notified, and a pain protocol and pain management education were implemented at that visit. The frequency of skilled nursing care was increased in order to monitor pain efficacy and any other disciplines required to provide caregiver support.

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NURS 6051 Discussion Application of Data to Problem-Solving
NURS 6051 Discussion Application of Data to Problem-Solving

Nurses must have the technical skills to manage equipment and carry out procedures, the interpersonal skills to interact appropriately with others, and the cognitive skills to observe, recognize, and collect data; analyze and interpret data; and reach a reasonable conclusion that serves as the basis for a decision. (D. McGonigle & K. G. Mastrian) (2017).

References:

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Sweeney, J. (Feb, 2017). Healthcare Informatics. Online Journal of Nursing Informatics (OJNI), 21( 1), Available at http://www.himss.org/ojni

NURS 6051 Discussion Application of Data to Problem-Solving

Discussion – Week 1

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The Use of Data to Solve Problems

The field of nursing informatics has led to the widespread adoption of data collection in modern healthcare settings. The collecting of accurate data is beneficial for both patients and healthcare practitioners. Electronic medical records have been essential to the enhancement of clinical data collection. The capacity to rapidly and efficiently retrieve vital patient information boosts patient safety and provider productivity. “Quick access to EMR data can hasten decision support to improve patient outcomes” (L.C.K.N., 2021).
Concerning the usage of physical restraints during patient treatment, numerous complaints and lawsuits have been made against a mental facility in North Carolina. Data collection is necessary to aid in the resolution of this issue. Collecting data on the frequency, timing, staff training, and types of restraints employed could provide a clearer understanding of the problem’s origin. This continual data collection could be used to assess the efficacy of any new policy or practice concerning the usage of restraints. As a nursing leader, the capacity to examine data to identify which policies or approaches are beneficial and which are not. The capacity to rapidly and easily recognize patterns will aid nursing leadership in making better decisions and improving patient care overall. The Center for Behavioral Health Statistics and Quality collects mental health research-relevant data. This information helps researchers, public health authorities, and politicians understand and resolve issues (CBHSQ, 2021).

References

Audrey Hirsch is an Alliance for Nursing Informatics Emerging Leader and the principal of Clinical Insight Consulting in Richmond. (n.d.). Technology management strategies for nurse leaders : Nursing management. LWW. Retrieved December 1, 2021, from https://journals.lww.com/nursingmanagement/Fulltext/2014/02000/Technology_management_strategies_for_nurse_leaders.10.aspx#:~:text=Nursing%20leadership%20can%20pair%20with%20informatics%20workers%20to,Simplify%20data%20collection%20requirements%20as%20much%20as%20possible.
Data we collect | CBHSQ data. (n.d.). SAMHSA – Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/data-we-collect
L;, C. K. N. (n.d.). Nursing Informatics and data collection from the Electronic Medical Record: Study of characteristics, factors and occupancy impacting outcomes of Critical Care Admissions from the Emergency Department. Health informatics journal. Retrieved December 1, 2021, from https://pubmed.ncbi.nlm.nih.gov/23257060/.

Main Post

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The functions and duties of nurses have changed over time. Throughout history, nurses have worn numerous hats. In addition to performing assessments, collecting data, and interpreting values, nurses must also communicate effectively with patients and coworkers and operate and identify potentially faulty medical equipment. The American Nurses Association defines nursing in 2016 as “the protection, promotion, and optimization of health and abilities, the prevention of illness and injury, the facilitation of healing, the alleviation of suffering through the diagnosis and treatment of the human response, and advocacy in the care of individuals, families, groups, communities, and populations” (Mastrian, K & McGonigle, D., 2018).
I am required to be on-call in my current position in order to assist patients and respond to any physician inquiries. The majority of calls come from parents who treat their children at home with peritoneal dialysis. They may have questions regarding modifications to the treatment plan, pre- or post-treatment vital signs, machine alarms, or the appearance of peritoneal dialysis fluid prior to or after treatment. During the calls, I must assess the situation by obtaining pertinent patient information, vital signs, and treatment history in order to determine if the treatment is normal or if further intervention in the emergency room setting and notification of the physician is required. We cannot document or upload patient information into the electronic medical record (EMR) from home or a mobile device, disrupting the continuity of care. The application of structured documentation methodologies and standardized terminologies should improve the quality of the patient record and the ability to compare care processes and outcomes across the care continuum and within patient care groups (Nagle et al., 2017).
The inability to enter this information electronically creates a gap or delay in the care provided. The emergency department is unable to access or retrieve the patient information I received at home. They cannot determine the orders I received from the physician unless they contact me or the on-call physician, who may not be the physician from whom I received orders. By making this pertinent data available in real-time, healthcare informatics and nursing informatics can assist in bridging the gap. Enhanced care delivery, enhanced health outcomes, and advanced patient education are a few of the aspects that have progressed (Sweeney, J., 2017).

References

Mastrian, K., & McGonigle, D. (2018). Nursing Informatics and the Foundation of
Knowledge (4th ed). Jones & Bartlett Learning.

Nagle, L., Sermeus, E., & Junger, A. (2017). Evolving Role of the Nursing Informatics
Specialist. In J. Murphy, W. Goosen, & P. Weber (Eds), Forecasting Competencies
For Nurses in the Future of ConnectedHealth (212_221). Clifton, VA: IMIA and
IOS Press. Retrieved from https://serval.unil.ch/resource/serval:BIB_
_4A0FEA56B8CB.P001/REF

Sweeney, J. (2017). Healthcare Informatics. Online Journal of Nursing Informatics
(OJNI), 21 (1). http://www.himss.org/ojni

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Main Post

I thoroughly enjoyed reading your post and concur that nurses must now assume multiple responsibilities in almost all healthcare settings. Modern electronic medical records and data tracking unquestionably facilitate our work and enhance patient care. Some nurses I’ve worked with were initially hesitant to utilize EMR systems. It has been suggested that it may encourage nurses to take shortcuts. Frequent, repetitive documentation puts the provider at risk, particularly if he or she feels rushed (Registered Nursing, 2017).
In my opinion, the advantages of using electronic medical records significantly outweigh any potential disadvantages. A nurse who takes shortcuts is likely to do so regardless of whether or not they use an EMR system. Electronic medical records capture point-of-care data that inform and enhance practice through quality improvement initiatives, practice-level interventions, and informative research (NCBI, 2021). Evidence-based practice has demonstrated the benefits of using EMR systems in virtually every healthcare setting.

References

Do electronic medical records improve quality of care?: Yes. (n.d.). PubMed Central (PMC). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4607324/
What are some pros and cons of using electronic charting (EMR)? || RegisteredNursing.org. (2017, November 19). RN Programs – Registered Nurse || RegisteredNursing.org. https://www.registerednursing.org/articles/pros-cons-using-electronic-charting/

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Nurses are capable of theorizing, hypothesizing, designing studies, and collecting evidence that leads to improved care. The purpose of nursing research is to improve patient and family care standards and applications. Occasionally, this requires altering a practice that has been standard for decades. For years, it was recommended that infants sleep on their stomachs rather than their backs, in case they vomited and suffocated. Today, however, due to extensive research into sudden infant death syndrome (SIDS), the recommendation and practice is for infants to sleep on their backs. (Blake, 2016) Most patients are communicated with by nurses, and nurses interact with technology more frequently. Utilizing technology should foster a positive outlook on nursing efficiency. It is crucial that nurses participate in the initial design of systems to improve the quality of health care and change their culture accordingly. (Darvish &Salsali,2010).
In the long-term care facilities where I have worked, bed rails were used to prevent patients from falling out of bed. Bedrails are no longer used, with the exception of a few instances in which half bedrails are used to assist patients who are alert and oriented with turning and repositioning. And for the few patients who use bedrails, an evaluation is performed to ensure they are oriented enough not to climb out via the bedrails. There is evidence that many falls in the past were caused by patients attempting to get out of bed, with some getting their heads stuck between the rails. (These rails were distinct from hospital bed rails.) Even without bed rails, there were more falls, particularly among confused patients attempting to get out of bed, than there are now. As a result, many long-term care facilities have adopted the “no-bedrails” policy, and my workplace has also adopted this policy. There are still very few falls, but the incidence of falls out of bed has decreased significantly.
Delivering the best possible outcomes for patients frequently necessitates collaboration between healthcare professionals from different departments, facilities, or organizations. Care coordination and communication allow all parties involved in a patient’s diagnosis and treatment to organize their efforts and share information.

REFERENCE

Blake, N (2016) Yes, nurses do research, and it’s improving patient care – Elsevier
Retrieved from: https://www.elsevier.com
Darvish A, Salsali M. A review on information technology development and the necessity of nursing informatics specialty. INTED2010 Proceedings. 2010. pp. 3320–3324. Retrieved from http://library.iated.org/view/DARVISH2010ARE .
Healthcare Information and Management Systems Society. Nursing informatics 101. http://www.himss.org/files/HIMSSorg/handouts/NI101.pdf.

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The Use of Data to Solve Problems

Utilizing healthcare knowledge and putting it into practice is the fundamental basis of nursing (McGonigle & Mastrian, 2021). My nursing practice includes the collection of patient information prior to admission. I work with elderly patients, and one of the admission criteria is patient collection. The collection of a comprehensive patient history is the next step. The patient history contains demographic information, past medical history, past diagnoses, current medications, and previous surgical procedures. This information is collected using electronic medical records. The use of electronic medical records is more precise than that of paper healthcare records (Honavar, 2020). This patient information can be used to establish a diagnosis, create treatment plans, and assess patient outcomes.
Using this information, one can be aware of adverse drug reactions in patients. Many patients may experience distress due to adverse reactions. The nurses can be aware of any drug-related allergies a patient may have. This knowledge can assist nurses in discontinuing certain medications and modifying treatment plans to ensure patients receive safe and effective care. Using information from patient medical records, a nurse manager could determine the frequency of adverse drug reactions. This information would assist the nurse manager in implementing measures to protect patients from adverse drug reactions. In addition, nurses are able to use clinical judgment to determine the thoroughness of information collection during patient admission. With this knowledge, nurse leaders can implement educational interventions to educate nurses on the significance of comprehensive history taking to ensure the delivery of safe and high-quality healthcare.
In conclusion, data is essential in healthcare. The ability to collect and utilize healthcare data to enhance the quality of healthcare services should be a competency for nurse leaders.

References

Honavar, S. (2020). Electronic medical records – The good, the bad, and the ugly. Indian Journal of Ophthalmology, 68(3), 417. https://doi.org/10.4103/ijo.ijo_278_20
McGonigle, D., & Mastrian, K. (2021). Nursing informatics and the foundation of knowledge. Jones & Bartlett Publishers.
Response #1 Week 1
You are correct in stating that “data is essential in healthcare”; however, the accuracy of the data is what really matters and makes it meaningful (McGonigle & Mastrian, 2017a). Data collection is the basis of everything we do in nursing, so it must be error-free for it to be effective. Sometimes the information is unavailable, such as when a patient is non-verbal or confused and no family member is present to inquire about medical history or allergies. This is when nurses transform their objective clinical observations into actionable data that other healthcare professionals can use to guide their care decisions (McGonigle & Mastrian, 2017b). Insufficient data may necessitate searching for the next reliable source of information, such as emergency medical services, law enforcement, or other community members who may have knowledge about the patient. According to Dammann (2019), the purpose of data is to transform it into knowledge that can be applied or utilized; in your scenario, the knowledge formed from your data will assist all disciplines in formulating a plan of care for your patients based on the provided information and a method to track process improvement.

References

McGonigle, D., & Mastrian, K. G. (2017a). Chapter 2/Introduction to Information, Information Science, and Information Systems: Information Science. In Nursing Informatics and the foundation of knowledge (4th ed., pp. 24). Jones & Bartlett Learning.
McGonigle, D., & Mastrian, K. G. (2017b). Chapter 6/History and Evolution of Nursing Informatics: The Nurse as a Knowledge Worker. In Nursing Informatics and the foundation of knowledge (4th ed., pp. 119). Jones & Bartlett Learning.
Dammann, O. (2019, March 5). Data, information, evidence, and knowledge: A proposal for health informatics and data science. Online journal of public health informatics. Retrieved November 30, 2021, from https://pubmed.ncbi.nlm.nih.gov/30931086.

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Discussion – Week 1

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Discussion: The Application of Data to Problem-Solving

Speculative Scenario

EMS transports a fifteen-year-old girl to the emergency room for an acute asthma attack resulting in respiratory distress. On arrival, it is determined that the patient is experiencing mild to moderate respiratory distress and triage is performed in accordance with pediatric guidelines. The triage nurse will collect data in the form of a report from the EMS team, the patient’s complete health and medical history, vital signs, and a head-to-toe assessment. This information will be entered into the medical provider’s charting system for review. The nurse observes that the patient is hypoxic with a SpO2 of 90% on room air. This information prompts her to summon the respiratory therapist and physician to the patient’s bedside. The therapist can assist the nurse in placing the patient on high-flow oxygen therapy and reports the inspiratory and expiratory wheezing of bilateral lung sounds heard during auscultation to the physician. These findings prompt the physician to order a series of nebulizer treatments of the appropriate inhalation medications, specific intravenous medications, such as corticosteroids, and additional testing to rule out or determine the cause of the patient’s asthma attack. Based on the gathered information and sequence of events, the ED physician decides to admit the patient to the pediatric ward for further observation. Once a patient is transferred to the pediatric ward, nurses continue to monitor, support, administer interventions as directed, and collect patient information.
Data Gathering and Access
The American Nurses Association defines nursing informatics as the specialty that combines nursing science with multiple information and analytical sciences (Sweeney, 2017). This enables the nursing profession to recognize, manage, define, and transmit data (Sweeney, 2017). The PEWS scale, also known as the Pediatric Early Warning System, is a tool for collecting data. This scale is used by nurses and other health care professionals to determine and detect a patient’s deterioration, which may necessitate intervention or a higher level of care, such as intensive or critical care (Gold et al.,2014). In the pediatric population, it is known that the condition of hospitalized patients can rapidly or unexpectedly change at any time (Lambert et al., 2017). This information is related to informatics because it is a tool for real-time data collection that can aid in pediatric care, identify abnormal or physiological changes, and monitor trends throughout a patient’s hospital stay (McElroy et al., 2019). This data may contain information that could save lives. Trending data, such as vital signs in this case, would assist in determining whether the medical interventions were sufficient or whether escalation of care is required. This is essential for nurse leaders, as informatics and data trends impact patient care, patient satisfaction, and quality. The electronic medical record, which allows data to be uploaded and recorded in real-time, is a key component of nursing informatics and data application. This is useful when reviewing fundamental metrics and quality indicators.

References:

Gold, D. L., Mihalov, L. K., & Cohen, D. M. (2014). Evaluating the Pediatric Early Warning Score (PEWS) system for admitted patients in the pediatric emergency department. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 21(11), 1249–1256. https://doi.org  10.1111/acem.12514
Lambert, V., Matthews, A., MacDonell, R., & Fitzsimons, J. (2017, March 10). Paediatric early warning systems for detecting and responding to clinical deterioration in children: a systematic review. US National Library of Medicine National Institutes of Health. Retrieved December 1, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5353324/McElroy, T., Swartz, E. N., Hassani, K., Waibel, S., Tuff, Y., Marshall, C., Chan, R., Wensley, D., & O’Donnell, M. (2019). Implementation study of a 5-component pediatric early warning system (PEWS) in an emergency department in British Columbia, Canada, to inform provincial scale up. BMC emergency medicine, 19(1), 74. https://doi.org/10.1186/s12873-019-0287-5
Sweeney, J. (Feb, 2017). Healthcare Informatics. Online Journal of Nursing Informatics (OJNI), 21(1).

NURS 6051 Discussion Application of Data to Problem-Solving

Discussion #1 – initial post
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Prior to this week’s readings, I had never really considered or considered the nursing informatics aspect of this field. Throughout my career, I have utilized various forms of technology in order to better comprehend and care for my patients. Throughout my various assignments, I use a variety of charting systems, and while they are all slightly different, they all share the ability to examine a variety of information sources in a simple and efficient manner. Many hospitals have thankfully adopted electronic charting, allowing for more efficient care. According to Laureate Education 2018, hospitals are also beginning to use telehealth applications, patient portals, social networking, and mobile technology, in addition to computer charting. ‘ Within the clinical setting, informatics is utilized in a variety of processes. Clinicians and patients utilize online portal systems, electronic medical records, data collection devices including vital sign machines and glucometers, personal data devices, and email, to name a few. When considering these systems and how they affect the process and flow of the clinical setting, it is crucial to consider not only the available technology but also the workflow and data collection process. (Sweeney, J. 2017).
I worked at a hospital that utilized the Epic charting system, which made it possible to view a greater quantity of data. If a patient visited any doctor within the network, you could view their notes, information, lab results, and scans. This was helpful for obtaining more information about patients who were either unable to speak for themselves upon admission or were not the best historians. It was also useful when you were unable to contact other physicians or colleagues, but you were able to review all the notes and information stored in the EPIC charting system to provide better patient care. “It has been demonstrated that technology, when developed and applied appropriately, improves the healthcare team’s ability to collect, categorize, interpret, manage, evaluate, and share relevant information. This also improves the team’s capacity to manage client care more effectively and efficiently.” (17-18 American Nurses Association pages)
I also think it’s great that EMR systems provide constant and readily accessible patient and medical history information. I mean that the patient’s surgical history, medical history, immunizations, and allergies are always included in their admission file. Obviously, this information can be edited and supplemented, but it’s convenient that we can easily view patients’ allergies and surgical/medical history when developing a treatment plan. Having immediate access to this data can improve patient outcomes and experiences.
It is evident that incorporating nursing informatics will benefit the future of nursing and patient care. As long as all departments and agencies continue to collaborate in promoting the proper use of this technology.

Resources

Laureate Education (Producer). (2018). What is Informatics? [Video file]. Baltimore, MD: Author
Sweeney, J. (2017). Eds.s.ebscohost.com. Healthcare Informatics. Retrieved December 1, 2021, from https://eds.s.ebscohost.com/eds/detail/detail?vid=50& data=JkF1dGhUeXBlPWlwLHNoaWImc2l0ZT1lZHMtbGl2ZSZzY29wZT1zaXRl.
American Nurses Association. (2021). Phenomenon of Nursing. In Nursing informatics: Scope and standards of Practice (pp. 17–18). essay.

RE: Discussion – Week 1

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My example for this discussion relates to the improvement of the psychiatric evaluation and management (E & M) form in my organization’s electronic health record (EHR). Enhancement of the E & M form’s intuitive incorporation of data collection systems. I work for a business that operates multiple adult foster care homes for chronically mentally ill patients. The EHR utilized by my organization was not initially designed to support the nurse role. It was designed primarily for social workers. It requires extensive development to provide the necessary medical components for nurses and doctors to document their findings accurately. As this EHR becomes more user-friendly for members of the interprofessional team, it remains siloed. Siloed in the sense that there are places within the EHR to enter information, but instead of that information being pulled to other forms within the EHR, it must be re-entered. There is no internal interface connecting the majority of the data. Our EHR collects a large amount of data, but there are no algorithms in place to interpret it. As providers attempt to meet Meaningful Use Initiatives by utilizing EHR systems, it would be interesting to examine the entire situation (Sweeny, 2017). However, does the system still count if it is counterintuitive?

The enhancement’s data would be gathered when direct support professionals chart their shifts. In their shift documentation, they indicate how long each patient sleeps per shift. They identify additional information, but for the purpose of this discussion, I will refrain from mentioning it. Currently, access to data is restricted to those who are trained and authorized to pull extensive reports and filter out the many layers of various data sets in order to quantify the minutes of sleep per shift. Other indicators include hygienic practices, diet, behaviors, etc.

As a nurse manager, I believe that this is a good practice, but it is rarely carried out because it is labor intensive and not taught. I prefer to generate this report for the psychiatric nurse practitioner (NP) in order to quantify the patient’s average sleep pattern per shift, per day, and compare it to the previous month’s data. This assists the NP in making better prescribing decisions. In evaluating the adverse effects of medications such as hyperammonemia from Depakote, clinical reasoning is justifiable. If a person has a significant increase in sleep, ammonia levels must be measured immediately. If the system was intuitive, it would be able to retrieve this data, recognize changes in averages, and recommend interventions based on the algorithms surrounding data collection.

NURS 6051 Discussion Application of Data to Problem-Solving

This particular data collection set has the issue of being “dirty.” McGonigle and Mastrian define dirty data as information that is insufficient or contains errors (2017, p.23). The current data collection system relies on staff members to perform charting. Implementing an accuracy percentage in addition to the raw data could remedy this issue. The percentage of accuracy would reflect the gaps in the charting.

The data pulled into the E&M should also be displayed in a comparison grid, which is a further opportunity for improvement of this concept. This data would indicate how this month’s data compares to data from prior months. For the naive, data without a reference point is merely a number. As Dr. Grant Shevchik suggested, those working in informatics must develop a feel for numbers, and we must be transparent in order to reveal trends and truths (Laureate Education, 2018).

Developing a user-friendly interface and a set of algorithms to populate patient trends results in improved treatment options, improved outcomes, and more informed decision making. Furthermore, it requires the laborious efforts of direct support professionals. We can accomplish so much more with the information we collect.

References

Laureate Education (Producer). (2018). Health Informatics and Population Health: Trends in Population Health [Video file]. Baltimore, MD: Author.

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Sweeney, J. (2017). Healthcare Informatics. Online Journal of Nursing Informatics, 21(1), 4–1.

RE: Discussion – Week 1

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The Application of Data to Problem-Solving

As technology advances, the healthcare system rapidly incorporates technological innovations into the delivery of healthcare. Informatics facilitates collaboration through effective communication, which makes it easier to manage workflow and coordination, and thus improves health outcomes.
Dealing with the issue of readmission among patients with heart failure is one scenario in the healthcare practice that would benefit from access to/collection of and application of data. In the United States, steps are being taken to decrease the high rates of readmission. For instance, Medicare and Medicaid Services (CMS) impose financial penalties on hospitals with a 30-day readmission rate that is higher than expected following hospitalization for a common medical condition (Wadhera et al., 2019). Therefore, the areas of readmission could benefit from the collection of data and knowledge of the factors that lead to high rates of readmission among patients with CHF. Therefore, the hospital can track the number of CHF patients who are readmitted following a previous hospitalization, and this information can be used to evaluate the quality of care. Quantitative and qualitative methods may be used to collect data on readmission. The electronic health records would collect quantitative data such as readmission within 30 days, admission time, and admission reason. The data can also reveal patterns of readmission, such as males having higher readmission rates than females. Qualitative data would reveal, from the patient’s perspective, what may have precipitated readmission. So, the knowledge that can be gained from these data includes the fact that a high proportion of readmissions are caused by medication non-adherence, poor self-care practices, and polypharmacy.

NURS 6051 Discussion Application of Data to Problem-Solving

A nurse leader could apply clinical reasoning and judgment based on this experience by identifying the factors that could be addressed to reduce readmission rates. In treating CHF patients, a nurse leader may adopt an intervention such as a multidisciplinary approach. This would ensure that patients benefit from the expertise pool and that all comorbidities are effectively addressed prior to patient discharge (Chava et al., 2019). The nurse leader may also use clinical judgment to imitate discharge planning early, such as after admission, to ensure that the teach-back method is utilized and to empower patients to engage in self-care practice after readmission. This not only reduces healthcare expenditures, but also improves health outcomes. With the assistance of systems such as admission, discharge, and transfer (ADT) data, the clinician can obtain real-time information about the patient’s status and conduct timely outreach before the patient is admitted. ADAT data can also be used to predict readmission rates and ensure the implementation of appropriate interventions.

References

Chava, R., Karki, N., Ketlogetswe, K., & Ayala, T. (2019). Multidisciplinary rounds in prevention of 30-day readmissions and decreasing length of stay in heart failure patients: A community hospital based retrospective study. Medicine, 98(27). https://doi.org/10.1097/MD.0000000000016233
Saha, P., Sircar, R., & Bose, A. (2021). Using hospital Admission, Discharge & Transfer (ADT) data for predicting readmissions. Machine Learning with Applications, 100055. https://doi.org/10.1016/j.mlwa.2021.100055
Wadhera, R. K., Maddox, K. E. J., Kazi, D. S., Shen, C., & Yeh, R. W. (2019). Hospital revisits within 30 days after discharge for medical conditions targeted by the Hospital Readmissions Reduction Program in the United States: National retrospective analysis. BMJ, 366. https://doi.org/10.1136/bmj.l4563

RE: Discussion – Week 1

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The Use of Data to Solve Problems

This discussion post’s objective is to describe a scenario within my current practice that could benefit from data access/collection and application. I am an administrator at a home health agency certified by Medicare. In home health, a large amount of data collection is done electronically, but I believe that the majority of the data is not being utilized or applied to the best of our ability. The scenario that stands out most to me in my organization is the admissions evaluation, how we collect and utilize data. A qualified nurse or therapist collects data for an Oasis assessment in our real-time electronic medical record system upon admission. The majority of Oasis data is measured for value-based purchasing for reimbursement. The collection of data is very time-consuming, and I do not believe that a substantial amount of it is utilized for the best patient outcomes. Due to the time-consuming nature of data collection, we have established a live quality assurance group so that clinicians can call a live RN after assessing a patient, relay the assessment over the phone, and have the RN enter the data on their behalf. All of this distracts from the treatment of the patient. I have found that the Oasis does not generate patient-specific interventions for the patient to follow to be its greatest drawback. If the qualifying clinician does not fully comprehend the Oasis data or what interventions they should implement based on the data collected, the reimbursement does not benefit the clinician or the patient. Using a more concise nursing praxis for documentation could reduce the time required to complete an assessment, improve the interventions applied to the patient’s care, and assist leaders in measuring the outcomes more accurately (Phillips & Baur, 2021). The Centers for Medicare and Medicaid Services require a significant amount of the data entered. Both the start-of-care assessment and the discharge oasis assessment produce results based on what the clinician believes to be the correct response. I believe that these data do not accurately depict the patient. With the continued development of health information technology, our electronic health records could be expanded to include suggested interventions based on functional tests administered and assessment tools like the Braden scale for wound assessment and prevention (Sockolow & Yang, 2021). As a leader in my organization, I believe that if we could better treat the patient based on what we are assessing by improving care pathways based on clinical assessment, home health patients would receive better care management. Using advanced informatics to implement better nursing processes would make the most clinical sense for both the organization and the patient (Alsadat Hosseini et al., 2021).

NURS 6051 Discussion Application of Data to Problem-Solving

References

Alsadat Hosseini, F., Parvan, K., Jasemi, M., Parizad, N., Esmaili Zabihi, R., & Aazami, S. (2021). Using newly developed software to enhance the efficiency of the nursing process in patient care. CIN: Computers, Informatics, Nursing, 39(11), 696–703. https://doi.org/10.1097/cin.0000000000000772
Phillips, T., & Baur, K. (2021). Nursing praxis for reducing documentation burden within nursing admission assessments. CIN: Computers, Informatics, Nursing, 39(11), 627–633. https://doi.org/10.1097/cin.0000000000000776
Sockolow, P., & Yang, Y. (2021). Preparing for the improving medicare post-acute care transformation act. CIN: Computers, Informatics, Nursing, 39(11), 813–820. https://doi.org/10.1097/cin.0000000000000782

RE: Discussion – Week 1

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Nursing Informatics (NI) is a relatively new specialty within the nursing profession, having been recognized by the American Nurses Association as such in 1992. (Garcia-Dia, 2021). In the last few decades, nursing informatics has experienced exponential growth in healthcare due to the rise of technology in the workplace. Informatics is essential in nursing because it combines medical science with data to communicate, manage, and analyze processes used to improve patient outcomes (R2 Library (Online service), & American Nurses Association, 2015). Documentation in Electronic Health Records (EHR) that is accurate facilitates the sharing of information with the entire interdisciplinary team (Cummings et al., 2021).
Although I work in the emergency department, I have experience in intensive care. I now work at a different facility, and despite the fact that the charting system is identical, I have observed some differences that, in my opinion, leave room for medication administration errors. My scenario focuses on the initiation of cardizem drips in emergency department patients with atrial fibrillation (AF) and rapid ventricular response (RVR). Prior to starting a cardizem drip in the intensive care unit of my former facility, we would have clear orders for bolus administration. These bolus orders were part of the order set, and clear instructions were listed on the electronic Medication Administration Record under the medication order (eMAR). Now, at the new facility, bolus orders are listed on a separate form that must be accessed via a reference text tab beneath the medication order.

Because medication orders are located in a different location than the eMAR, the order information must be accessed from multiple locations, causing medication administration delays. The reference text tab is unlabeled, so nurses must intuitively know to click on it for additional information. With the introduction of Covid-19 the previous year, computer orientation classes have become nearly extinct, and the majority of the orientation process is left to computer modules that are completed at home with minimal guidance. I have heard nurses who are new to our facility or who were not taught this information during orientation question what bolus the patient requires. In some instances, if the nurse requests it, the emergency physician will give a verbal order for a bolus. However, at this facility, boluses are weight-based and not standardized. I’d like to access data on patients who received cardizem boluses and compare them to the actual bolus order to ensure the correct administration of dosage. I believe this ordering system contributes to confusion and possible care delays.
Access to concise, easy-to-read orders is essential in the emergency department’s fast-paced environment. Ross et al. (2016) discovered that standardized dosing of cardizem was not clinically inferior to weight-based dosing in patients with AF with RVR presenting to the emergency department. Nursing leaders could deduce that having all the necessary information for a cardizem bolus listed on the eMAR, whether weight-based or standardized, would result in less confusion for nurses, greater autonomy because they would not need to communicate with physicians to obtain information, and a reduction in the delay of care.

NURS 6051 Discussion Application of Data to Problem-Solving

References

Cummins, M., Kennedy, R., McBride, S., & Carrington, J. (2021). Policy Priorities in Nursing Informatics: The American Academy of Nursing Informatics and Technology Expert Panel in 2010. Computers, Informatics, Nursing: CIN, 39(3), 120-122. https://doi.org/10.1097/CIN.0000000000000731
Garcia-Dia, M.J. (2021). Nursing informatics: An evolving specialty. Nursing Management, 52,(5). https://doi.org/10.1097/01.NUMA.0000743444.08164.b4
Ross, A. L., O’Sullivan, D.M., Drescher, M. J., & Krawczynski, M.A. (2016). comparison of Weight-Based Dose vs. Standard Dose Diltiazem in Patients with Atrial Fibrillation Presenting to the Emergency Department. Journal of Emergency Medicine, 51(4), 440-446. https://doi.org/10.1016/j.jemermed.2016.05.036
R2 Library (Online service), & American Nurses Association. (2015). Nursing Informatics: Scope and Standards of Practice: Vol. Second edition. American Nurses Association.

RE: Discussion – Week 1

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In my current role as a discharge nurse, data collection is essential for improving patient discharge times. I am required to provide patient name, room number, diagnosis, discharge order time, and actual discharge completion time with each discharge. This information is entered into a system to calculate hospital-wide average discharge wait times. This is the best way to get an average, but the information is not always analyzed to determine why individual discharges are delayed. For instance, a patient may have discharge orders, but cannot be discharged for four hours due to bed rest restrictions following a heart catheterization. It would hinder the average discharge wait time when analyzing data related to this specific scenario. This is where I believe there is room for improvement in my particular situation.
Diverse data sources are analyzed for hospital quality measures. Individual hospital associations, state/regional data organizations, health departments, and federal agencies offer hospital data. (Hospital quality measurement databases, n.d.) The collection of data is essential for nurse leaders to interpret and enhance patient care and hospital flow. One could argue that clinical reasoning is the defining characteristic of the medical profession. (Gruppen, 2017). My supervisor is the hospital’s director of nursing, and she is the one who uses clinical reasoning and judgment to introduce new ideas to improve hospital flow and patient care. Patient satisfaction and outcomes will continue to rely heavily on the interpretation of data and introduction of novel concepts for improvement.

References

Databases used for hospital quality measures. AHRQ. (n.d.). Retrieved December 1, 2021, from https://www.ahrq.gov/talkingquality/measures/setting/hospitals/databases.html.
Gruppen, L. D. (2017, January). Clinical reasoning: Defining it, teaching it, assessing it, studying it. The western journal of emergency medicine. Retrieved December 1, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226761/.

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Discussion – Week 1

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The application of data to problem-solving is the subject of the initial discussion.

I must say, as a Psychiatric Nurse of twenty-nine years, that the transition to technology was not without its challenges. However, the greater our understanding of the building blocks of nursing informatics, the more easily we can integrate this knowledge and these tools into our practice. The building blocks of Nursing Science, Cognitive Science, Information Science, and Computer Science are also the building blocks of nursing informatics (McGonigle & Mastrian, 2017).

Nursing Informatics Advantages for Utilization Review Managers

This Registered Nurse is a Utilization Review (UR) Nurse on an inpatient behavioral health unit while attending nursing school. One of the many responsibilities is to ensure that patients with mental health and chemical dependency meet the preauthorization criteria for inpatient admission. The concurrent review process with insurance companies, state-funded programs such as Medicaid, and other agencies is used to determine continued stays. In this procedure, all components are utilized. Electronic Medical records such as Emergency Room Consults, History and Physicals, Behavioral health flowsheets, Clinical Institute Withdrawal Assessments recorded (CIWA), nursing notes, nurse admission assessments, and lab work are examples of items that are initially evaluated for preauthorization by UR. All of the latter information, along with treatment planning and discharge planning information, is evaluated for continued hospitalization by nursing and providers. The meeting of the treatment team to discuss patients is one of the most important aspects of data collection; during this time, knowledge can be shared and questions can be asked. Utilization Review Management is responsible for collecting data, synthesizing the information, communicating the information to insurance companies and the treatment team, and managing this information.
I believe it is important to mention that if the quality of information collected throughout the EMR is lacking, such as vague nursing notes, undone CIWA assessments, or vague History and Physical information, then the information conveyed may not be sufficient to request additional days for the patient. It is important not only to consider technology, but also to comprehend how to collect data to fill any gaps in the collected information (Sweeney, 2017). Having providers, nursing, and nurse managers who understand what is required for a patient to meet and continue to meet criteria, as well as what that criterion is, can improve documentation, thereby enhancing the data processed and transmitted. In conclusion, “how a patient perceives care to be coherent and linked over time” is the result of good information flow, good interpersonal skills, and good coordination of care (Nagle, et al., 2017, p. 217).

References:

McGonigle, D., Mastrian, K.G. (2017). Nursing science and the foundation of knowledge. Nursing Informatics and the Foundation of Knowledge (4th Edition). Jones & Bartlett Learning. https://mbsdirect.vitalsource.com/books/9781284142990
Nagle, L., Sermeus, W., Junger, A. (2017). Evolving role of nursing informatics specialist. In J. Murphy, W. Goosen, & P. Weber (Eds.), Forecasting Competencies for Nurses in the Future of Connected Health (pp. 212-221). IMIA and IOS Press. https://serval.unil.ch/resource/serval:BIB_4A0FEA56B8CB.P001/REF
Sweeney, J. (2017). Healthcare informatics. Online Journal of Nursing Informatics. 21(1).

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Discussion – Week 1 Initial Post

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The Application of Data to Problem-Solving

As is well-known, the health care industry is constantly changing. Thankfully, innovations are continuously developed to accommodate situations and obstacles encountered in various health care settings. I am currently employed by a virtual health care facility whose technical, remote, monitoring, and communication capabilities never cease to amaze me. Working remotely as a Utilization Review Nurse, I am able to review patients in all of our hospital units in multiple states from the time of their admission to the time of their discharge, as well as after discharge to properly close out their cases. The importance of collecting and utilizing available data to improve outcomes for patients and the facilities we serve is evident on a daily basis within my department.

The leadership of our department and the hospital are in constant communication with our team members, reporting new data and procedures adopted as a result of the daily interventions documented by our department. Prior to this week’s assignment, I had never made the connection between informatics and the numerous ways it is integrated into our department. For instance, according to a resource provided in this week’s lesson, “MCG produces evidence-based clinical guidelines and software that is widely used in the United States, the United Kingdom, and the Middle East” (Nagle, L. et al., 2017). When completing initial and concurrent stay reviews for patients admitted for observation and inpatient status, we utilize MCG on a daily basis. MCG does aid in determining the correct class status and preventing discharge delays. Avoiding discharge delays is emphasized in our department and among our physicians. “There was an association between delayed discharge and mortality, infections, depression, and reductions in patients’ mobility and daily activities. The qualitative research highlighted the effects of the pressure to reduce discharge delays on staff stress and interprofessional relationships, with implications for patient care “(Rojas-García, A. et al., 2018). Consequently, the data tools we use in our department to guide clinical decisions can easily apply data to practice to promote knowledge formation and problem-solving, resulting in better outcomes for the facility and the patients we serve.

The hypothetical scenario I propose for this discussion is the use of electronic notifications to reduce the likelihood of miscommunication or lack of communication between physicians and Utilization Review Nurses. Working primarily on weekends, I frequently observed instances in which the request to change a patient’s status from observation to inpatient was not communicated to the physician. This communication issue frequently results in three- to four-day observation admissions when the objective is to have the patient admitted as an inpatient if their admission exceeds two midnight. When performing chart reviews, the chart contains information regarding the payer type and expected length of stay. Instead of relying on the UM nurse to review observation admissions to determine the correct status, this scenario introduces the ideal that the computer system would automatically notify the physician to request an Inpatient order based on those criteria. I concur with the statement, “Sophisticated protocols relating to both routine and alert information can be developed, allowing for more effective organization of communications with physicians, nurses, and caregivers” (McGonigle and Mastrian, 2017, p.380). Developing a protocol that automatically notifies physicians of the request to consider entering an inpatient order for patients meeting criteria could prevent lengthy observation admissions and reduce the likelihood of miscommunication between the UM department and the physician, particularly on the weekends when the department is understaffed.

NURS 6051 Discussion Application of Data to Problem-Solving

As previously stated, I continue to be astounded by the processes our virtual facility employs to record the interventions for each case and apply that information to determine the efficacy of the outcome. With our advanced technological capabilities, I foresee this scenario yielding excellent results that could be easily incorporated into daily practice and monitored for their effectiveness in reducing lengthy admissions for observation and communication errors between providers. Data collection could be accomplished by requiring the doctor to respond to the notification with yes or no, indicating whether an inpatient order was entered, with the patient’s status remaining unchanged after receiving the notification. Before implementing the notification process, it would be possible to determine the percentage of correct status cases by collecting data on the number of times a physician entered an inpatient order in response to the notification. The increased frequency of inpatient orders could have a favorable effect on the number of avoidable long observation admissions. I can envision my nursing supervisor monitoring physician responses and the occurrence of lengthy observation cases, which are already monitored. Tracking the outcome of this intervention that resulted in an inpatient order being entered as a response from the physician could lead to the formation of knowledge to determine if this is a method to improve communication and serve as a reminder to physicians as they enter the charts of patients admitted to our facilities with observation status.

References

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Nagle, L., Sermeus, W.& Junger, A. (2017). Evolving Role of the Nursing Informatics Specialist. In J Murphy, W. Goosen, & P. Weber (EDS.), Forecasting Competencies for Nurses in the Future of Connected Health (212-221). Clifton, VA: IMIA and IOS Press. Retrieved from https://several.unil.ch/resource/several:BIB_4A0FEA56B8CB.P001/REF
Rojas-García, A., Turner, S., Pizzo, E., Hudson, E., Thomas, J., & Raine, R. (2018, February). Impact and experiences of delayed discharge: A mixed-studies systematic review. Health expectations: an international journal of public participation in health care and health policy. Retrieved November 30, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5750749/.

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Discussion – Week 1 Main Post

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The importance of data in the healthcare system cannot be overstated. Nurses collect a variety of data, whether in a hospital or clinical setting. “Whether inpatient or outpatient, clinicians and patients use online portal systems, electronic medical records, data collection devices such as vital sign machines and glucometers, personal data devices, and email, to name a few” (Sweeney, 2017). I work on an oncology unit, which uses an EMR, or electronic medical record, to collect patient information. Since the majority of our patients are neutropenic and leukemic, CLABSI (Central Line Associated Bloodstream Infection) is something that the unit must closely monitor. Our unit has a method for keeping track of how many patients have central lines. This information is entered into the hospital database, so if a CLABSI is reported, the hospital can track all patients with central lines.” There are a variety of methods currently employed by facilities to train personnel responsible for CLABSI data collection and reporting. These included an annual review of competency skills, staff orientation, ongoing staff education (on topics such as collection and criteria for patient days and central lines, hospital or clinical updates, and nursing documentation), use of NHSN materials, corporate webinars, and APIC (Association of Professionals in Infection Control and Epidemiology, Inc.) webinars” (vdh.virginia.gov, 2021).
Our unit tracks the central line patients on our floor using the EPIC EMR. The information regarding all central lines on the floor is crucial because the unit must know how many patients have central lines in order for the nurses to provide proper care and prevent CLABSI.” A checklist within the electronic medical record and a unit-wide dashboard would increase adherence to an evidence-based, pediatric-specific catheter care bundle and reduce central line-associated bloodstream infections (CLABSI) ” (Pageler, Longhurst, & Franzon, 2014). This also applies to my oncology unit, where over fifty percent of patients have central lines. My unit has initiated this data collection in which nurses on each shift must indicate in the EMR which patients have central lines, and then upload this information to the EPIC database.

References

Pageler, N., Longhurst, C. A., & Franzon, D. (2014). Use of electronic medical record-enhanced checklist and electronic dashboard to decrease
CLABSI’s. ncbi.nlm.nih.gov.
Sweeney, J. (2017). Healthcare informatics. Online Journal of Nursing Informatics, 21(1).
vdh.virginia.gov. (2021).

Discussion – Week 1

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We rely on informatics more than ever in the healthcare industry to forecast likely outcomes and determine the direction of necessary change. Organizational measurement systems, leadership, educators, and information technology resources are the most prevalent types of nursing informatics (Nagle, 2015). As a nurse in both the Intensive Care Unit and Surgical Services, I have found informatics to be extremely useful. At the rural hospital where I work in 2019, the number of admissions with missed or undiagnosed sepsis increased. The use of EMRs such as PulseCheck and Meditech enabled the staff to track vitals, labs, and testing, which led to the formation of a group of physicians and nurses to analyze the data. After multiple meetings and data comparisons, the team decided to implement a policy that would flag any sepsis markers for each individual patient and streamline their care so that sepsis could be treated promptly. This protocol included the administration of intravenous fluids, medications, and repeated laboratory testing in an effort to identify the source of the infection and improve patient survival rates.
This policy was developed with the assistance of a team of informatics-specializing nurses at our hospital. According to Murphy (2011), nursing informatics specialists can be found in nearly every organization or clinic, and they provide a great deal of insight, implementation, and evaluation of clinical data in order to affect change. When my organization recognized a potential gap in the treatment and identification of a serious patient care issue, we utilized our available resources to define the issue and develop a solution. After implementation, the number of patients treated promptly after recognizing the symptoms of sepsis increased dramatically, and this trend has continued.
When the COVID-19 pandemic swept across the United States, it left our hospitals and specialty departments with a massive void. The number of nurses and employees working from home increased, and virtual visits or telemedicine gained prominence. Women’s College Hospital Institute of Health Systems Solutions and Virtual Care (WIHV), 2015, defines virtual care as interaction between individuals with the objective of facilitating quality and efficient care. Now, if an issue arises that requires the assistance of specialty departments that are not physically located in the hospital, we can rely on the fact that they are only a phone call or zoom meeting away.

NURS 6051 Discussion Application of Data to Problem-Solving

Resources:

Nagle, L.M. (2015). Role of informatics nurse. Introduction to nursing informatics (pp. 251-270). London: Springer-Verlag.
Murphy, J. (2011). The nursing informatics workforce: Who they are and what they do? Nurs Econ 29(3), 150-3.
Women’s College Hospital Institute for Health Systems Solutions and Virtual Care (WIHV). 2015. Virtual care: A framework for a patient-centric system. Retrieved from http://www.womenscollegehospital.ca/assets/pdf/wihv/WIHV_VirtualHealthSymposium.pdf

RE: Discussion – Week 1

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The Application of Data to Problem-Solving

Main Post

Informatics is crucial to both science and society as the use of technology becomes ubiquitous. Informatics is the science of using data, information, and knowledge to advance health and provide healthcare (Informatics: Research and Practice, n.d.). Incorporating nursing, computer science, and information science into patient care, nurse informatics contributes to healthcare by supplying the resources necessary to enhance patient safety and satisfaction (RegisteredNursing.org Staff Writers, 2017).

IPASS will be the focus of the selected clinical scenario for this assignment. IPASS is a new tool developed by the informatics team at my current job (shift change or bedside report). Recently, the IPASS was integrated into our EMR system to enhance patient outcomes and eliminate errors. A secondary objective of the IPASS is to identify last-minute orders that may have been submitted late and missed by the outgoing nurse, as well as to involve patients and caregivers in inpatient care. The IPASS approach was implemented after it was reported that several medications scheduled to be administered an hour or two before shift change were not administered.

How does IPASS function? During shift change, the incoming and outgoing nurses both report to the patient’s room, where the outgoing nurse introduces the incoming nurse to the patient. The patient is then informed of the bedside report and asked to contribute any questions, concerns, or missing care-related information. While the report is being presented, both nurses open the IPASS template on the EMR and follow along. During this time, the incoming nurse takes notes on the patient assessment to ensure that she receives accurate information. For instance, if the incoming nurse is informed that the patient has a central line, both nurses must assess the line and dressing. Each checks the MAR to ensure that all medications required by shift change have been administered. The IPASS includes a checklist that must be completed as each report is transmitted and received. Finally, both nurses initialed the IPASS to indicate that all steps had been completed and that the information contained within the report was accurate.

During handoff, ineffective communication among healthcare professionals results in sentinel events that annually cost health organizations millions of dollars and claim the lives of over 250,000 patients (MSN et al., 2021). In order to bridge the gap between practice, knowledge, and healthcare, electronic handoff must be standardized. Reportedly, some EMR companies have incorporated handoff software into their EMR programs in an effort to reduce errors, costs, and deaths resulting from poor handoff communications (MSN et al., 2021). If not already available, organizations must update their EMR systems to include the handoff functionality. Every hospital must increase the use of electronic handoff and integrate it into patient care in order to address the problem of ineffective communication among medical staff.

References

Informatics: Research and Practice. (n.d.). AMIA – American Medical Informatics Association. https://amia.org/about-amia/why-informatics/informatics-research-and-practice

MSN, T. M. A., RN-BC, MSN, S. E. O., RN-BC, Jr, R. J. P., PhD, RN-BC, & FAMIA. (2021, April 20). Key Characteristics of a Successful EHR-Supported e-Handoff Tool: A Systematic Review | HIMSS. Www.himss.org. https://www.himss.org/resources/key-characteristics-successful-ehr-supported-e-handoff-tool-systematic-review

RegisteredNursing.org Staff Writers. (2017, August 9). What is Nursing Informatics & How to Become a Nurse Informaticist. Registerednursing.org; RegisteredNursing.org. https://www.registerednursing.org/nursing-informatics/

NURS 6051 Discussion Application of Data to Problem-Solving

RE: Main Post

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Informatics integrates nursing science and practice with technology to enhance patient care, improve communication, and increase healthcare efficiency. The more technological advancements occur, the more vital informatics becomes in healthcare. “The technology boom at the turn of the century has contributed to the evolution of informatics and information systems (Sweeney, 2017). In numerous ways, technology has improved nursing practice. It has provided the healthcare industry with the advantages of readily accessible information and the ability to identify problems before they become issues. Due to the current COVID pandemic, informatics has recently become the primary mode of communication with healthcare providers. “Virtually everywhere on the planet, the delivery of health care services is becoming routine (Nagle, Sermeus, and Junger., 2017).

I currently work in a dialysis unit for outpatients. In this clinical setting, continuous data collection is necessary. Hypotension is a frequent side effect of hemodialysis. Utilizing a CRIT Line to alleviate hypotensive episodes in these patients is advantageous. Real-time measurements of a patient’s hematocrit rate, percent change in blood volume, and oxygen saturation are made using the CRIT Line monitor. The purpose of the treatment was to provide more effective care for the dialysis patient, patient technician, and registered nurse. The clinician/nurse can intervene based on the monitor’s data in order to remove the maximum amount of fluid from the patient without the patient experiencing the common complications of dialysis. “Nurses must have the technical skills to manage equipment and execute procedures, the interpersonal skills to interact appropriately with people, and the cognitive skills to observe, recognize, and collect data; analyze and interpret data; and reach a reasonable conclusion that serves as the basis for a decision” (McGonigle and Mastrian, 2017). If this device was utilized in the majority of dialysis clinical settings, positive patient outcomes and patient satisfaction would result.

Resources

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Nagle, L., Sermeus, W., & Junger, A. (2017). Evolving role of the nursing informatics specialist. In J. Murphy, W. Goossen, & P. Weber (Eds.), Forecasting Competencies for Nurses in the Future of Connected Health (212–221). Clifton, VA: IMIA and IOS Press. Retrieved from https://serval.unil.ch/resource/serval:BIB_4A0FEA56B8CB.P001/REF

Sweeney, J. (2017). Healthcare informatics. Online Journal of Nursing Informatics, 21(1).

RE: Discussion – Week 1

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According to Laureate Education (2018), informatics is a set of tools, and the key is how those tools are used; therefore, it is important to consider the customers and the outcomes that one aims to achieve, given that these tools will continue to evolve; leaders must examine data carefully and use them strategically for a better outcome. Informatics plays a significant role in health care, especially when we consider the transmission of patient data from one location to another. All areas of health care benefit from technological advancements.
A few hospice institutions have been required to “refund” Medicare for accepting and caring for patients who were ineligible for hospice treatment. Even after the fact, CMS is allowed to evaluate patient records to validate services. Hospice is a program that provides medical care to terminally ill patients with a life expectancy of six months or less (CMS, n.d.). Some groups have consistently delivered hospice-inappropriate care to individuals. This is a wonderful illustration of how data collection and analysis may be beneficial. The admission departments at these hospitals must gather patient records and carefully examine them to decide if the patient is eligible for end-of-life care. Using qualitative data, these institutions may establish a department that examines patient charts every 60 to 90 days to evaluate eligibility and, if necessary, dismiss patients to avoid penalties.
A nurse leader will ensure that patients admitted to the program meet admission requirements by collecting and carefully assessing acquired data. Patients who become ineligible can be discharged promptly provided a team is designated to track their deterioration or improvement. Nursing informatics is a science that can improve care quality, patient safety, and patient outcomes (JOGNN, n.d.).

References

CMS. (n.d.-a). CMS. Retrieved December 1, 2021, from https://www.medicare.gov/Pubs/pdf/02154-medicare-hospice-benefits.pdf
JOGNN. (n.d.). Leadership in nursing informatics. Retrieved December 1, 2021, from https://www.jognn.org/article/S0884-2175(15)34176-9/pdf
Laureate Education (Producer). (2018). Health Informatics and Population Health: Trends in Population Health [Video file]. Baltimore, MD: Author.

I have spent the last 10 years working in emergency rooms as a staff nurse. One of the biggest challenges that my department faces regularly is delays with getting admitted patients out of the ED and onto their assigned units. These delays negatively impact the patients waiting for emergency treatment in the lobby and hallway stretchers. There are a number of factors that can prolong ED length of stay. Some of these include lack of bed availability due to hospital overcrowding, treatment delays such as loss of IV access, and delays caused by hospital personnel during the handoff report process (Paling et. al, 2020). Some of these factors, such as hospital overcrowding, are unavoidable and difficult to work around, which is why it is important for hospitals to assess which factors they can control to expedite patient flow out of the emergency room.

For my hospital’s scenario, the emergency department would collect data about admission delays that are specifically caused by disruptions in the nursing telephone report process. In my current workplace, there is not a standardized electronic handoff form, despite the fact that several studies have demonstrated the efficiency and increased patient safety outcomes associated with the transition to standardized electronic nursing report (Wolak et al., 2020). Instead, the ED nurse calls the receiving unit on the telephone, gives a verbal patient care handoff, and then transfers the patient to their hospital room. By collecting data about where in the handoff process delays are occurring, the ED could try to streamline the handoff process with the medical floors.

The emergency department nurses would collect quantitative data about the length of time between the first attempt to call report to the medical floor, and the time of the patient’s actual departure from the ED. The data would be recorded in the section of the EMR called “time to disposition” for each patient that is admitted. The ED leadership team could then pull a certain number of charts per month (or all the admission charts, if time allowed) and assess how long it takes on average for patient transfer to happen after report. Generally, most hospitals set their goals for disposition time for handoff and transfer within a 30-minute window (Potts et. al., 2018). If there are frequent delays causing transfer time to take greater than 30 minutes, the ED leadership team or unit-based council could meet with leadership from the floors where patient transfer takes the longest. By demonstrating the hard numbers associated with patient care delays, the teams could better understand the factors that lead to admission delays and work together to find solutions that expedite the admissions process.

References:

Paling, S., Lambert, J., Clouting, J., González-Esquerré, J., & Auterson, T. (2020). Waiting times in emergency departments: Exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data. Emergency Medicine Journalhttps://doi.org/10.1136/emermed-2019-208849

Potts, L., Ryan, C., Diegel-Vacek, L., & Murchek, A. (2018). Improving patient flow from the emergency department utilizing a standardized electronic nursing handoff process. JONA: The Journal of Nursing Administration48(9), 432–436. https://doi.org/10.1097/nna.0000000000000645

Wolak, E., Jones, C., Leeman, J., & Madigan, C. (2020). Improving throughput for patients admitted from the Emergency Department. Journal of Nursing Care Quality35(4), 380–385. https://doi.org/10.1097/ncq.0000000000000462

Response

This is insightful Andrea; admission delays often lead to adverse treatment outcomes. The delays in patients’ admission to different hospitals are attributed to the increased number of patients or overcrowding. The impacts of delayed admission can be severe, including longer hospital stays, the inability of patients to access appropriate beds, and experienced healthcare experts (Goertz et al., 2020). Most patients leave without getting treatment due to delayed admissions to different healthcare facilities (Paling et al., 2020). There is a need for quality improvement to facilitate improvements in admission rates. The quality improvements should rely on the data collected in the course of operation. The application of the EMR system is one of the best methods of data collection in healthcare (Pastorino et al., 2019). Measuring and recording the time taken during hospital admission is necessary for determining areas that require adjustments. Through the analysis of the collected data or information, healthcare institutions are able to initiate quality improvement processes and ensure effective outcomes in the management of patients. One of the questions that I would ask is: What variables ought to be involved in the data collection processes?

References

Goertz, L., Pflaeging, M., Hamisch, C., Kabbasch, C., Pennig, L., von Spreckelsen, N., … & Krischek, B. (2020). Delayed hospital admission of patients with aneurysmal subarachnoid hemorrhage: clinical presentation, treatment strategies, and outcome. Journal of neurosurgery134(4), 1182-1189. https://doi.org/10.3171/2020.2.JNS20148

Paling, S., Lambert, J., Clouting, J., González-Esquerré, J., & Auterson, T. (2020). Waiting times in emergency departments: Exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data. Emergency Medicine Journalhttps://doi.org/10.1136/emermed-2019-208849

Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European journal of public health29(Supplement_3), 23-27. https://doi.org/10.1093/eurpub/ckz168

NURS 6051 Discussion Application of Data to Problem-Solving

I like your senario and would to emphasize the need for health care staf to learn how to navigate health informatics like EPIC. It is like an acquisition, storage, retrieval and use of health information. Health informatics promotes efficient and effective patient care through the fluid transmittance and retrieval of health care information. The use of technology such as computer systems, software and other technologies promote informatics. A good and simple example of the efficiency and importance of informatics can be seen when considering mail via the post office and emails via computer systems and network. The delivery of mail using email transmittance allows for the quick, efficient and certain delivery of information. Sending information through the post office takes time, vulnerable to be lost as well as being damaged. The same efficiency is needed in addressing patient Care as patients lives at times will be dependent on the efficient transmittal of information. A patient, for example, that meets in a car accident and requires emergency surgery, would benefit from health informatics as the patient’s medical history is readily retrievable from a health care informatics system that links providers to each other. Imagine calling around for patient information or worst yet, writing letters to request patient information. Antiquated systems can jeopardize patient care and patient safety (Alotaibi and Frederico, 2017).

As the main health care personnel, nurses are charged with the responsibility of operating systems that utilize informatics. In addition, nurses should be able to efficiently and fluently use those systems. It is therefore important that nurses understand the full purpose of informatics as well as to navigate any system in their network that utilizes informatics. This is a critical part of nursing care as it promotes proper nursing care for patients as well as to increase positive outcome for the patients as well. Informatics should also be part of the core curriculum in nursing school because it teaches student nurses how to better care for their patients (Leung et. al., 2015). In addition, this core curriculum should again be reinforced in the clinical setting, as there are nuances to different informatics network systems. The nurse should be familiar with these nuances so that they can best utilize the system when dealing with health informatics. Nurses understanding and use of informatics should be greater than any other personnel in the clinical setting as the nurse is the main point of contact for patient care. A nurse, for example, may alert the doctor or others of a patient’s pre-existing conditions or allergies thereby preventing any type of accident. The nurse should also be able to properly train other personnel in using health informatics. In training a new on how to use health informatics, it is also important that the nurse possess basic technology skills such as computer skills and understanding how software works. Health informatics is the wave of the future and the nurse should also be at the forefront of this wave as it directly impacts patient care and patient outcome. It has also been shown that hospitals that uses health informatics efficiently, has more positive patient outcomes (Snyder et. al., 2011).

Name: NURS_5051_Module01_Week01_Discussion_Rubric

Excellent Good Fair Poor
Main Posting
Points Range: 45 (45%) – 50 (50%)

Answers all parts of the discussion question(s) expectations with reflective critical analysis and synthesis of knowledge gained from the course readings for the module and current credible sources.

Supported by at least three current, credible sources.

Written clearly and concisely with no grammatical or spelling errors and fully adheres to current APA manual writing rules and style.

Points Range: 40 (40%) – 44 (44%)

Responds to the discussion question(s) and is reflective with critical analysis and synthesis of knowledge gained from the course readings for the module.

At least 75% of post has exceptional depth and breadth.

Supported by at least three credible sources.

Written clearly and concisely with one or no grammatical or spelling errors and fully adheres to current APA manual writing rules and style.

Points Range: 35 (35%) – 39 (39%)

Responds to some of the discussion question(s).

One or two criteria are not addressed or are superficially addressed.

Is somewhat lacking reflection and critical analysis and synthesis.

Somewhat represents knowledge gained from the course readings for the module.

Post is cited with two credible sources.

Written somewhat concisely; may contain more than two spelling or grammatical errors.

Contains some APA formatting errors.

Points Range: 0 (0%) – 34 (34%)

Does not respond to the discussion question(s) adequately.

Lacks depth or superficially addresses criteria.

Lacks reflection and critical analysis and synthesis.

Does not represent knowledge gained from the course readings for the module.

Contains only one or no credible sources.

Not written clearly or concisely.

Contains more than two spelling or grammatical errors.

Does not adhere to current APA manual writing rules and style.

Main Post: Timeliness
Points Range: 10 (10%) – 10 (10%)
Posts main post by day 3.
Points Range: 0 (0%) – 0 (0%)
Points Range: 0 (0%) – 0 (0%)
Points Range: 0 (0%) – 0 (0%)
Does not post by day 3.
First Response
Points Range: 17 (17%) – 18 (18%)

Response exhibits synthesis, critical thinking, and application to practice settings.

Responds fully to questions posed by faculty.

Provides clear, concise opinions and ideas that are supported by at least two scholarly sources.

Demonstrates synthesis and understanding of learning objectives.

Communication is professional and respectful to colleagues.

Responses to faculty questions are fully answered, if posed.

Response is effectively written in standard, edited English.

Points Range: 15 (15%) – 16 (16%)

Response exhibits critical thinking and application to practice settings.

Communication is professional and respectful to colleagues.

Responses to faculty questions are answered, if posed.

Provides clear, concise opinions and ideas that are supported by two or more credible sources.

Response is effectively written in standard, edited English.

Points Range: 13 (13%) – 14 (14%)

Response is on topic and may have some depth.

Responses posted in the discussion may lack effective professional communication.

Responses to faculty questions are somewhat answered, if posed.

Response may lack clear, concise opinions and ideas, and a few or no credible sources are cited.

Points Range: 0 (0%) – 12 (12%)

Response may not be on topic and lacks depth.

Responses posted in the discussion lack effective professional communication.

Responses to faculty questions are missing.

No credible sources are cited.

Second Response
Points Range: 16 (16%) – 17 (17%)

Response exhibits synthesis, critical thinking, and application to practice settings.

Responds fully to questions posed by faculty.

Provides clear, concise opinions and ideas that are supported by at least two scholarly sources.

Demonstrates synthesis and understanding of learning objectives.

Communication is professional and respectful to colleagues.

Responses to faculty questions are fully answered, if posed.

Response is effectively written in standard, edited English.

Points Range: 14 (14%) – 15 (15%)

Response exhibits critical thinking and application to practice settings.

Communication is professional and respectful to colleagues.

Responses to faculty questions are answered, if posed.

Provides clear, concise opinions and ideas that are supported by two or more credible sources.

Response is effectively written in standard, edited English.

Points Range: 12 (12%) – 13 (13%)

Response is on topic and may have some depth.

Responses posted in the discussion may lack effective professional communication.

Responses to faculty questions are somewhat answered, if posed.

Response may lack clear, concise opinions and ideas, and a few or no credible sources are cited.

Points Range: 0 (0%) – 11 (11%)

Response may not be on topic and lacks depth.

Responses posted in the discussion lack effective professional communication.

Responses to faculty questions are missing.

No credible sources are cited.

Participation
Points Range: 5 (5%) – 5 (5%)
Meets requirements for participation by posting on three different days.
Points Range: 0 (0%) – 0 (0%)
Points Range: 0 (0%) – 0 (0%)
Points Range: 0 (0%) – 0 (0%)
Does not meet requirements for participation by posting on 3 different days.
Total Points: 100