Assignment: Patient Care Efficiencies.
Assignment: Patient Care Efficiencies.
The Influence of Nursing Informatics on Patient Outcomes and Care Efficiencies
You considered the interaction of nurse informaticists with other specialists to ensure successful care in the Discussion for this module. What factors influence success?
One of the primary ways that healthcare success is measured is through patient outcomes and achievement of care goals. Measuring patient outcomes generates data that can be used to improve outcomes. Nursing informatics can play an important role in this process by improving processes, identifying at-risk patients, and increasing efficiency.
To Get Ready:
Examine the technology application concepts presented in the Resources.
Consider how emerging technologies such as artificial intelligence might help to strengthen nursing informatics as a specialty by having a greater impact on patient outcomes or improving patient care efficiencies.
The task at hand: (4-5 pages)
Propose a nursing informatics project for your organization in a 4- to 5-page project proposal written to the leadership of your healthcare organization to improve patient outcomes or patient-care efficiency. The following items should be included in your project proposal:
Describe the proposed project.
Determine the stakeholders who will be impacted by this project.
Explain the patient outcome(s) or patient-care efficiencies that this project aims to improve, as well as how this improvement would take place. Provide specifics and examples.
Identify and explain the technologies required to complete this project.
Identify the project team (by roles) and explain how you plan to include the nurse informaticist.
BY WEEK 3’S DAY 7
Please send in your completed Project Proposal.
Technology has eased nurses’ work by providing easy access to shared resources. Nurses need to accept the role of technology in clinical decisions in order to improve patient outcomes. The purpose of the paper is to describe a nursing informatics project that will help enhance patient-care efficiency.
Proposed Project
The proposed project for our organization is a clinical decision support system (CDSS). CDSS use software tools to provide healthcare workers with evidence-based information and patient-specific data to assist them with clinical decision-making. CDSS is primarily used at the point-of-care, for the clinician to combine their knowledge with information or suggestions provided by the CDSS (Sutton et al., 2020). As a result, itimproves healthcare delivery by enhancing medical decisions from clinical knowledge, patient information, and health information. CDSS use can help in screening, diagnosing, disease management, setting up alarm systems, prescription,drug control and follow-up services.
Stakeholders Impacted by This Project
The use of CDSS will directly impact patients, healthcare providers and the healthcare facility. CDSS will enable healthcare professionals to make well-informed clinical decisions as they are able to gain knowledge based on evidence-based practice. It will also reduce medication errors, thus reducing incidences of morbidity and mortality in hospitals(Sutton et al., 2020). CDSS will further enhance healthcare providers’ knowledge of disease conditions, enabling them to become more reliable for future patient care. It will help improve patient outcomes through enhancing their safety while reducing health care costs (Taheri et al., 2021). Screening services and indicating relevant diagnostic tests can help reduce costs as well as minimize the risk of certain diseases from developing. The use of CDSS helps reduce mortality and morbidity in hospitals, improving the hospital’s reputationand encouraging more patients to visit the facility, increasing revenue for the healthcare facility.
Patient Outcomes the Project Is Aimed at Improving
CDSS can help improve patient outcomes by ensuring their safety. CDSS can be used to create strategies that reduce medication errors. Medication errors, including overdosing and underdosing, have been noted to be a common cause of morbidity and mortality due to the risk of drug toxicity and undertreatment. CDSS has created software that guides drug dosing, duplication of therapies, drug-drug interactions, and allergy detection (Taheri et al., 2021). It can guide clinicians in prescribing, transcribing, dispensing, and administration of drugs to prevent medication errors.Additionally, CDSS also improve patient safety by creating alert and reminder systems for medical events (Sutton et al., 2020). Alert systems can remind healthcare providers when certain measurements need to be taken, such as blood pressure and glucose, ensuring continuous patient monitoring to prevent complications.
CDSSs can support nurses in managing conditions and creating individualized care plans. CDSS can guide disease-specific assessments based on evidence-based practice to guide their clinical decisions. EBP can provide guidelines that healthcare providers can utilize to provide care for the patients while enhancing care coordination. Furthermore, CDSS can assist with managing patients by creating effective follow-up protocols that alert clinicians to reach out to patients who have yet to follow management plans or are due for follow-up(Sutton et al., 2020). As a result, close monitoring of patients is attained, and proper care is given to them even while they are not admitted. Furthermore, follow-up services have reduced the risk of patients developing complications while they are at home, thus reducing readmission rates.
Technologies Required to Implement CDSS
CDSS often make use of web applications, electronic health records (EHR), computerized provider order entry (CPOE) systems, and artificial intelligence (AI). The use of AI in CDSS has been important as it can schedule appointments for patients, digitization of medical records that can be used for EBP, guide on drug dosage and their adverse effects, and set up reminder calls for healthcare workers and patients for follow-up. CPOE systems can be used to improve prescription documentation to prevent incidences of medication errors (Jungreithmayr et al., 2021). EHR is important as it can keep patients’ health records in a centralized manner (Vos et al., 2020). A well-designed EHR systemcan access patient data and process it to suggest a range of possible diagnoses, thus reducing the time and costs used in diagnostic procedures.
Project Team
Implementing the CDSS project requires two groups of people: the healthcare providers and the information technology (IT) team. The IT team identifies features of CDSS that are critical to improving clinical practice and ensures the CDSS product is met with the desired feature for clinical practice (Hak et al., 2022). Additionally, they ensure that the project program is comprehensible and updated consistently. Healthcare providers are essential in creating the CDSS program as they can evaluate the data provided to them and choose the best that meets EBP. They are able to ensure that the program created by the IT team is easily understandable to other healthcare providers and patients using it (Hak et al., 2022). The nurse informaticist can collaborate with the IT team to create a program that hastens clinical decisions that improve patient safety and outcome. The nurse informaticist can actively engage other healthcare providers by training them on how to use CDSS to improve their patient care. Additionally, they can advise other healthcare providers to publish data that can be used to improve CDSS.
Conclusion
CDSS is an important tool in healthcare practice today. It has enabled the use of EBP to improve patient care, thus improving patient outcomes. A nurse informaticist is an essential member in implementing the program as they can guide the IT team and healthcare team to ensure the program is efficiently used to meet its importance.
References
Amisha, Malik, P., Pathania, M., &Rathaur, V. K. (2019). Overview of artificial intelligence in medicine. Journal of family medicine and primary care, 8(7), 2328–2331. https://doi.org/10.4103/jfmpc.jfmpc_440_19
Hak, F., Guimarães, T., & Santos, M. (2022). Towards effective clinical decision support systems: A systematic review. PloS one, 17(8), e0272846. https://doi.org/10.1371/journal.pone.0272846
Jungreithmayr, V., Meid, A. D., Implementation Team, Haefeli, W. E., &Seidling, H. M. (2021). The impact of a computerized physician order entry system implementation on 20 different criteria of medication documentation-a before-and-after study. BMC medical informatics and decision making, 21(1), 279. https://doi.org/10.1186/s12911-021-01607-6
Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., &Kroeker, K. I. (2020). An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ digital medicine, 3, 17. https://doi.org/10.1038/s41746-020-0221-y
Taheri Moghadam, S., Sadoughi, F., Velayati, F., Ehsanzadeh, S. J., &Poursharif, S. (2021). The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis. BMC medical informatics and decision making, 21(1), 98. https://doi.org/10.1186/s12911-020-01376-8
Vos, J. F. J., Boonstra, A., Kooistra, A., Seelen, M., & van Offenbeek, M. (2020). The influence of electronic health record use on collaboration among medical specialties. BMC health services research, 20(1), 676. https://doi.org/10.1186/s12913-020-05542-6