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Discussion: The Application of Data to Problem-Solving

Discussion: The Application of Data to Problem-Solving

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

Compliance or noncompliance with treatment in behavioral health patients influences the course of treatment and the outcomes of psychiatric disorders (Rao, George, Sudarshan, & Begum, 2017). There are many reasons that patients are non-compliant with the recommended treatment programs. Noncompliance can be due to lack of education, side effects of treatments or medications, lack of transportation, financial issues, religious or personal beliefs. It is noted that noncompliance for all medical disorders within the United States is estimated to be $100 billion dollars yearly (Centorrino et al., 2001). Noncompliance with psychiatric treatment is associated with increased clinical, social, and economic costs, and noncompliance is linked to relapse, rehospitalization, and poor outcomes among patients suffering from psychiatric disorders (Centorrino et al., 2001).

Working in a Behavioral Health Urgent care; nurses must posses the technical skills to mange equipment and preform procedures, the interpersonal skills to interact appropriately with people, and the cognitive skills to observe, recognize, and collect data; and reach a conclusion that is able to form a decision (McGonigle & Mastrian, 2017). The goal in treatment of patients is to increase compliance with treatment which will increase positive outcomes for the patient. Part of the treatment plan for patients to increase compliance with follow-up care is to schedule outpatient appointments with community agencies. Nursing informatics can manage and communicate data to inform the Behavioral Health Urgent Care if patients are completing scheduled follow-up outpatient appointments with the community agencies. If patients are not attending scheduled appointments calls can be made to find the reason that appointment was not attended. Knowledge is defined as the awareness and understanding of information, and ways that the information can be useful to support a specific task or arrive at decision (McGonigle & Mastrian, 2017). Research has showed that 1/3 of behavioral health outpatient appointments are missed which leads to an increased risk of re-hospitalization (Centorrino et al., 2001). The data can be used to find ways to increase compliance with patients attending the scheduled outpatient appointments. Adhering to treatment plans is essential to the treatment of mental health disorders.

Resources

Centorrino, F., Hernán, M. A., Drago-Ferrante, G., Rendall, M., Apicella, A., Längar, G., & Baldessarini, R. J. (2001). Factors Associated with Noncompliance with Psychiatric Outpatient Visits. Psychiatric Services, 52(3), 378–380. https://doi.org/10.1176/appi.ps.52.3.378

McGonigle, D., & Mastrian, K. (2017). Nursing Informatics and the Foundation of Knowledge (4th ed.). Jones & Bartlett Learning.

Rao, K. N., George, J., Sudarshan, C. Y., & Begum, S. (2017). Treatment compliance and noncompliance in psychoses. Indian journal of psychiatry59(1), 69–76. https://doi.org/10.4103/psychiatry.IndianJPsychiatry_24_17

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You raise some excellent concerns about noncompliance in behavioral health patients.  One simple solution to help these patients receive better care would be to take insurance prior authorization for medications out of the healthcare system.  Some medications require authorization from an insurance company prior to being filled by a pharmacy.  For patients without insurance, these medications can be paid for out of pocket.  For patients without insurance, pharmacies will frequently refuse to fill the prescriptions and allow patients to pay out of pocket for them while prior authorization is actively in process.  According to Jones et al. (2019), antidepressants, narcotic analgesics, and hypnotics are among the most frequently prescribed medications which require prior authorization when prescribed.  Many of these medications are frequently used in the behavioral health settings. Blake et al. (2019) describes a study involving pediatric patient in which the process of obtaining prior authorization created barriers in continuity and quality of care.  Another study of dermatology patients found prior authorizations cause a huge burden on providers and lead to delayed, lesser, or abandoned treatment (Petitt et al., 2021).

References

Blake, S. C., Song, M., Gaydos, L., & Cummings, J. R. (2019). Prior Authorization Policies and Preferred Drug Lists in Medicaid Plans: Stakeholder Perspectives on the Implications for Youth with ADHD. Administration and Policy in Mental Health46(5), 580–595. https://doi-org.ezp.waldenulibrary.org/10.1007/s10488-019-00937-y

Jones, L. K., Ladd, I. G., Gregor, C., Evans, M. A., Graham, J., & Gionfriddo, M. R. (2019). Understanding the medication prior-authorization process: A case study of patients and clinical staff from a large rural integrated health delivery system. American Journal of Health-System Pharmacy : AJHP : Official Journal of the American Society of Health-System Pharmacists76(7), 453–459. https://doi-org.ezp.waldenulibrary.org/10.1093/ajhp/zxy083

Petitt, C. E., Kiracofe, E., Adamson, A., & Barbieri, J. S. (2021). Prior authorizations in dermatology and impact on patient care: An updated survey of US dermatology providers and staff by the American Academy of Dermatology. Dermatology Online Journal27(1).

RE: Discussion Main Post – Week 1

COLLAPSE

 Technology has had an influx in the last century and healthcare professionals are dependent on it. To bridge the gap between bedside nursing and electronic health records (EMR), we need nursing informatics. Healthcare Informatics is defined as “the integration of health-care sciences, computer science, information science, and cognitive science to assist in the management of healthcare information” (Saba & McCormick, 2015, p. 232).  

According to Berga Congost, et al. (2021), ischemic heart disease is the most significant cause of death in the world today. The most prevailing presentation with the worst clinical outcome is myocardial infarctions (MI). In a recent study, it was found that systematic, well-regulated clinical approaches to timely prompt management of myocardial infarctions had a direct effect on clinical outcomes in patients.  

In my scenario, I am going to discuss a practice that we strive for in the emergency room. According to the (Yiadom et al., 2017), to receive timely diagnosis of a ST elevated myocardial infarction an EKG needs to be completed in less than 10 minutes from arrival. In our emergency room, we closely monitor on a weekly basis the door to EKG time for all patients with any complaint of chest pain. If it is noted that there was a delay in care, the chart is audited, and reasoning must be documented on why the EKG was delayed. Our nurse leader is responsible for auditing the patient charts weekly and recording the average door to EKG time. Last week we were at 11 minutes with 77% competition in less than 10 minutes. Since our door to EKG times are higher than normal, we had a team huddle about it and what we can do to improve these numbers.  

 Refereces:  

Berga Congost, G., Brugaletta, S., Valverde Bernal, J., Márquez López, A., Ruiz Gabalda, J., Garcia-Picart, J., Puig Campmany, M., & Martinez Momblan, M. A. (2021). The importance of organizational variables in treatment time for patients with ST-elevation acute myocardial infarction improve delays in STEMI. Australasian Emergency Care24(2), 141–146. https://doi-org.ezp.waldenulibrary.org/10.1016/j.auec.2020.10.001 

Saba, V. K. & McCormick, K. A. (2015). Essentials of nursing informatics (6th ed.). New York: McGraw-Hill. 

Yiadom, M. Y., Baugh, C. W., McWade, C. M., Liu, X., Song, K. J., Patterson, B. W., Jenkins, C. A., Tanski, M., Mills, A. M., Salazar, G., Wang, T. J., Dittus, R. S., Liu, D., & Storrow, A. B. (2017). Performance of emergency Department screening criteria for an Early ECG to Identify St‐segment Elevation myocardial infarction. Journal of the American Heart Association6(3). https://doi.org/10.1161/jaha.116.003528 

RE: Discussion – Week 1

As a result of the covid-19 pandemic in January of 2020, health care was impacted and forced to create new ways to deliver care. Telehealth services have been a great resource to manage, maintenance and offer multiple benefits for patients and health care professionals. Additionally, it allows nurses and doctors to diagnose,  prevent, treat, monitor, and control illness, especially during a pandemic (Bell et al., 2021). In the scenario, I will discuss the benefits of Telehealth and covid-19

A study conducted in 2020 describes a health system that used telehealth computer programs and four biomedical informatics resources to screen and care for covid-19 patients by using special programs and electronic health record data. The Telehealth modalities used were: continuous virtual monitoring to reduce workforce risk, remote patient monitoring for covid-19 positive patients, virtual urgent care screening, and transition of outpatient care to Telehealth. In addition, the article identifies as a critical factor the ability to link Telehealth with electronic health records to monitor and track patients for optimal health outcomes  (Ford et al., 2020).

My work as a triage nurse can connect telehealth programs with electronic health records to follow specific metrics and track ED visits for illnesses such as congestive heart failure, covid-19, diabetes individually.  Metric data is reviewed daily to meet particular patient needs, such as emergency room f/u office visits. In addition, triage calls meet department and national standards with specific protocols and care to advise. The nurse manager then evaluates the individual productivity to implement new ideas for improvements.

In summary, Telehealth offers valuable opportunities in the process of health care delivery and improving patients outcomes Covid-19 has stimulated telehealth and health informatic services (Ford et al., 2020).

 

Dee Ford, Jillian B Harvey, James McElligott, Kathryn King, Kit N Simpson, Shawn Valenta, Emily H Warr, Tasia Walsh, Ellen Debenham, Carla Teasdale, Stephane Meystre, Jihad S Obeid, Christopher Metts, Leslie A Lenert, Leveraging health system telehealth and informatics infrastructure to create a continuum of services for COVID-19 screening, testing, and treatment, Journal of the American Medical Informatics Association, Volume 27, Issue 12, December 2020, Pages 1871–1877, https://doi.org/10.1093/jamia/ocaa157

 

Bell, L. C. K., Norris-Grey, C., Luintel, A., Bidwell, G., Lanham, D., Marks, M., Baruah, T., O’Shea, L., Heightman, M., & Logan, S. (2021). Implementation and evaluation of a COVID-19 rapid follow-up service for patients discharged from the emergency department. Clinical Medicine21(1), e57–e62. https://doi-org.ezp.waldenulibrary.org/10.7861/clinmed.2020-0816

            I work in the Electroconvulsion Therapy Department on our Behavioral Health Unit. I often have wondered how many patients with severe depression walk through the doors and based on severity of symptoms, how many treatments are enough to be effective. I have seen as little as 2 treatments completely relieve patient of depression and as many as 17 on a routine basis. Many patients come in for their maintenance therapy but I often wonder about the acute phase of these treatments. Based on the voltage of the shock and the placement of the shock is it possible to cure people of depression faster or ultimately is the safety of the patient at risk by changing the threshold. “The use of informatics is seen in a multitude of processes within the clinical setting. Whether inpatient or outpatient, clinicians and patients utilize online portal systems, electronic medical records, data collection devices such as vital sign machines and glucometers, as well as personal data devices and email, to name a few.” (Sweeney, 2017).

I think it would be important to have a clinical spreadsheet over the course of 12-week intervals documenting the most frequent treatments needed along with the least treatments needed. Understanding factors take place such as age, and second therapy medications to determine if there is any data available to determine if other forms of treatment can aid is resolution of depression faster. “The vast majority of depressed patients referred for ECT will have severe, debilitating illness that has not responded to multiple medications and psychotherapy. The urgency of the clinical situation, often marked by intense suicidal preoccupation and drive, is commonly what compels the recommendation for ECT.” (Kellner, Obbels, & Sienaert, 2020).

As a nurse leader, one can use this information and relay the data on to the psychiatrist to help facility best practice measures along with safety of treatments for patients.

References

Kellner, C. H., Obbels, J., & Sienaert, P. (2020). When to consider electroconvulsive therapy (ECT). Acta Psychiatrica Scandinavica, 141(4), 304-315. doi:https://doi-org.ezp.waldenulibrary.org/10.1111/acps.13134

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

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

The phone rings on a busy Saturday afternoon and the pleasant voice of a registered nurse answers professionally, greeting the caller seeking advice and care. This could be a day for a typical for an ambulatory telephone triage nurse. The concept of telephone triage and consultation can be one of a registered nurse using evidence-based algorithms from electronic databases. The nurses, like most nurses, working in a progressive health care industry are using technology to counsel patients. According to McGonigue & Mastrian, (2022), “For information to be valuable, it must be accessible, accurate, timely, complete, cost-effective, flexible, reliable, relevant, simple, verifiable, and secure.” p.9.

This information could be valuable to many leaders in the healthcare team. Accessibility would be easiest in form of electronic records and telephone recordings. McGonigue & Mastrian (2022), argue, “Computer science offers extremely valuable tools that when used skillfully, can facilitate the acquisition and manipulation of data and information by nurses, who then can synthesize the data into an evolving knowledge and wisdom base ”p. 35). Accurate and timely information could be an interest in nursing quality and control. One argument on how telephone triage could be cost-effective is that paying nurses to man the phone lines is cheaper than using inappropriate resources such as the emergency room to care that can be directed elsewhere. Flexibility, reliability, simple, verifiable and secure would require a more in-depth look into the nature of telephone triage and program development within a system, but the concept of triage nursing seems to be malleable to the interest of how the data would be used.

An additional source of centralized evidence-based algorithm software program could also be used and from my research is being used in assisting the nurses to effectively triage the caller and ensure best practice standards. Documentation done by triage nurses would have data from the callers that are subjective and objective, the nursing assessment, and recommendations based on the call.

From this data collection, multiple departments within healthcare could use this or would have an interest in this data collection. Intradisciplinary teams have an opportunity to look at how to retrieve data from electronic retrieval of health records or from recorded lines if those are being used. An ambulatory nurse manager might be interested in using the data as a system educator of staff development and improvement strategy to support the training needs within their triage staff. A quality nurse might want to use this data to help in creating of protocol development and safety improvements for effective triage and outcomes. Ambulatory providers could use data to see the patient population’s interests and barriers to care and from there use it to modify their practices. Health information technology departments within health care organizations could be supportive of this nursing department in implementing programs in making documentation more time efficient and detailed. Nursing leadership could use this as a cost-effective strategy.

All departments could build off one another and become temporary team members to gain knowledge and benefit in patient care and satisfaction. Emerging roles could be created as, “Teams are working across boundaries of organizations and will be organized around a particular patient.” (Nagale et al, 2017, p. 215). Within most healthcare systems the mission and visions of these organizations are built on patient outcomes and patient centered care. An informatics nurse specialist could support patients, nurses, providers, and leaders with the interpretation of data analytics and therefore participate in applying new knowledge from data to wisdom. (Nauright et al., 1999)

This hypothetical scenario of a nurse working at a telephone triage call center would benefit immensely from data access, problem-solving and the process of knowledge formation. In a real-time, scenario, I could see how this could impact patient care and outcomes on a global level and be a perfect role for a nurse informatics specialist to pilot.

The scenario I experienced recently involves the hospital readmission rate of my dialysis patients diagnosed with fluid overload. During data gathering, I noticed that at least three patients whose target weights are below 90kg have intradialytic weights of more than 4kg for the last three treatments. They are also less than three months in dialysis, considered new patients. They are also not reaching their dry or target weight on the data. Their blood pressures were also greater than 160/90mmhg before dialysis, even when they reported taking their blood pressure medicine at home. Using my clinical reasoning and judgment, patients with high blood pressure, more than 4kg of intradialytic weight gain, and not reaching their target weight are collecting fluid in their bodies. When they come to treatment and have gained 4kg, we calculate the fluid removal goal of 4kg plus 0.5kg Normal Saline rinse when we start dialysis and return their blood. Removing 4.5 kilograms of liquid in a patient weighing 90kg below is hard on the patient’s heart. There is a high chance they will experience cramping, nausea, vomiting, and hypotension. The data on the three patients showed fluid removal of less than 4kg in every treatment. This showed that patients accumulate extra fluids in their bodies during every therapy. By the end of three treatments, their body can no longer handle the excess fluids which go to their organs, such as the lungs making them short of breath.

When admitted, they are dialyzed daily until the extra fluids in their body are removed. They will get discharged if no other complications are found. They will be back on their routine, which is dialysis treatment three times a week in our facility. Diet counseling is the best plan to help them avoid gaining too much when they return. Since they are new patients, they still struggle with what food is right for them. Together with the dietician, we conducted one-on-one counseling with the patients and allowed family members. While the dietitian counsels them on food, I incorporated my education on organs affected by fluid overloads, such as the heart and the lungs. Education such as limiting fluid intake to 32oz a day, foods low on sodium, and informing them that fruits contain fluids added to the 32oz day limit.

Healthcare is experiencing rapid transformation. Digital technologies are advancing and aiming to make healthcare safer and more effective. Health informatics is one way of assisting healthcare is evolving. Health Informatics “integrates nursing, information and communication technologies, and professional knowledge to improve patient outcomes (Reid et al., 2021).”

References:

Reid, L., Maeder, A., Button, D., Breaden, K., & Brommeyer, M. (2021). Defining Nursing Informatics: A Narrative Review. Studies in health technology and informatics284, 108–112. https://doi.org/10.3233/SHTI210680

 

My current healthcare organization attends to numerous patients diagnosed with chronic illnesses such as cardiovascular diseases, diabetes, and cancer. The risk factors for most of these conditions can be identified early through screening and mitigated or approached taken to reduce the impact of the disease. Healthcare data can be potentially useful in predicting a patient’s risk for a disease such as Type 2 Diabetes, which has been a major concern due to its associated morbidity and mortality. The Electronic Health Record (EHR) can be used to collect a patient’s data including, their past medical history, family, social history, and lifestyle practices (Dash et al., 2019). The data can be collected on the initial contact with a patient, and health providers should be advised to take a comprehensive patient history in the first contact.

The data can be used to predict a patient’s degree of risk to a particular chronic illness such as diabetes. For instance, health providers can identify risk factors for diabetes such as the history of overweight, obesity, or high blood pressure, positive family history of diabetes, sedentary lifestyle, smoking, and excessive alcohol consumption. The data can guide health providers to make data-driven decisions to enhance a patient’s outcomes such as, requesting additional screenings or providing patient education on weight management and adoption of healthy lifestyles (Dash et al., 2019). Furthermore, for patients diagnosed with diabetes, the health provider can access the data in the EHR to monitor their treatment plans and guide on pharmacological management to promote better outcomes.

A nurse leader can use patient data from EHR to strategically plan and lead the healthcare team in developing treatment plans for patients. Nurse leaders can also analyze patients’ data from different demographic groups and identify what factors limit patients from achieving the desired health outcomes (McGonigle & Mastrian, 2017). Furthermore, the data can be used to form knowledge on ways to enhance clinical practice and new ways to provide patient care, to enhance health outcomes.

References

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data6(1), 54. https://doi.org/10.1186/s40537-019-0217-0

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