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NURS FPX 6612 Assessment 3 Quality Improvement Proposal

Assessment 3: Patient Discharge Care Planning

Name

Capella University

NURS-FPX6612: Health Care Models Used in Care Coordination

Instructor Name

July, 2024

Patient Discharge Care Planning

To develop a successful patient discharge care plan, assessing some of the major problems affecting the coordination of care and patient outcomes is important (Li et al., 2022). Marta Rodriguez is an 18-year-old freshman attending college in Nevada. She is from Mexico and has multiple primary medical and discharge needs after many surgeries and treatment for a systemic infection at a shock trauma center. This is revealed by Health Information Technology (HIT), which assists in developing a patient-centered care plan that enables her to get through the continuum of her care easily. Appropriate usage of HIT means utilizing the reporting data that focuses on client behaviors to improve care organization (Kwon & Lee, 2024). By merging the data acquired from HIT and EHR, the multi-disciplinary teams can improve the discharge planning and decrease the readmission rates, thus guaranteeing Marta a safe and successful discharge.

Utilization of HIT in Patient-Centered Care Plan

An interprofessional team will use HIT to develop a comprehensive, patient-oriented, ongoing care plan to guide Marta Rodriguez’s discharge planning. Components of HIT like EHR, telehealth, and patient portals will be essential to guarantee continuum and integrated care (Borycki & Kushniruk, 2023). EHRs will help keep records of Marta’s medical history, treatments, development of care plans, and instructions for her and the team members involved and provide detailed overviews of sources. Telehealth services will help to carry out follow-up appointments so that Marta’s progress will be checked, and if there is any problem, it will be identified early. Patient portals can enable patients to receive information on their health, communicate with their care team, and manage their appointments, increasing their compliance with the care plan (Chen et al., 2023).

Preventing Readmission within 48 Hours

To reduce the risk of Marta’s re-admission within the subsequent 48 hours of discharge, the members of the interprofessional group will employ selected HIT components for her recovery. Virtual or remote consults will help Marta to have check-ups and monitor her condition from wherever she is. Besides, related issues can be detected and addressed in real-time (Derecho et al., 2024). This way, her EHR will be designed to hold follow-up alerts for the key areas that ought to be checked fully to prevent possible negligence that may occur in her care. In the same respect, care coordinators can utilize analytical tools embedded in the HIT system to discover patient’s risks and implement preventive measures (Ehsani et al., 2021). Thus, the proactive strategy, backed up by technology, is designed to prevent potential dangers and facilitate recovery to the best of her abilities, of Marta.

Supporting Coordination of Care

The deployment of HIT elements will greatly enhance Marta’s care coordination since the plan allows for the efficient sharing of information and communication between her other care providers. An important benefit of using the EHR system is implementing structured and collected patient information into all caregivers’ databases, including, but not limited to, the surgeon, primary care physician, and rehabilitation specialists (Borycki & Kushniruk, 2023). The shared access shall allow for better decision-making about the treatment plan and overall management of the patient (Holmgren et al., 2023). The patient portals will enable Marta to relate with her caregivers closely, document her evolution, and receive feedback, making her care encompassing. The outlined HIT elements can be integrated to synchronize the efforts of the health care team involved, hence providing Marta with coherent, co-coordinated care in the continuum, leading to enhanced health status of the patient and a positive patient experience. 

Impact of Data Reporting on Care Coordination and Management

The patterns of reports regarding identified client behavior can notably influence the coordination and management of Marta Rodriguez’s care. Marta’s medication compliance and physical therapy attendance record, together with her symptom worsening rate, will be of immense help to a qualified healthcare team to address all her needs comprehensively. Applying this method enables Marta’s health to be modified frequently to suit her recovery process, thus improving her health. In addition, data reporting can discover trends or a possible problem that may not be recognizable, like customers or patients who fail to attend appointments more often or when they have bad effects from taking medicine, thus allowing the team to prevent such issues (Derecho et al., 2024).

Enhancing Clinical Efficiency

Patient care is significantly improved when data concerning the behavioral patterns of the clients are applied in the clinical setting (Ehsani et al., 2021). For example, analyzing data on appointment no-shows or delays will be useful for scheduling and usage of resources. More so, the details of the recovery period of the patients, as well as the treatment results, can help formulate the best approach to treatment and other clinical procedures (Holmgren et al., 2023). Drawing from the observations, healthcare organizations can cut time spent waiting, increase patient flow, and consequently boost the efficiency of clinical processes (Kwon & Lee, 2024).

Fostering Interprofessional Innovation

Reporting data brings in the sense of interprofessional relationship by encouraging the development of the solution and idea (Park & Park, 2023). This is especially the case when different healthcare specialists get close and result-oriented information about the self-organization of patients. For example, telehealth utilization information provides a basis for improving the organization of remote care procedures. This is one of the ways healthcare is delivered smartly for the benefit of patients and to make bottom-up changes in practices. Assessing data quality is critical in ensuring it will give out efficient information (Tsai et al., 2020). Decisions on data assessment depend on the source’s reliability, the data collection’s homogeneity, and the connection between collected data and the clinical questions of interest (Lahijanian & Alvarado, 2021). The data collected should be reliable, relevant, and rich to support the right decisions in healthcare facilities.

Using Client Records to Improve Health Outcomes

Data obtained from clients ‘paper charts is hugely valuable in improving health status as it contains details of a patient’s treatment history and medication reactions. Such information proves valuable for decision-making by caregivers and to give distinctive treatment (Chen et al., 2023). With successful client amalgamation, various healthcare professionals can analyze data, spot the likelihood of future health complications, and develop unique solutions suited to individual needs (Jung et al., 2021). For example, in Marta’s case, all records related to the surgeries, antibiotics, and Marta’s progress in recovery are important to define a safe discharge plan. Ultimately, the combination of data gathered from within the client records provides a well-rounded understanding of Marta’s health condition, enhancing the process of developing her ongoing treatments. Documentation and management of client records are a vital step in improving the population’s health and maintaining their safety, which, in turn, contributes to the Patient-Centered Care approach (Kwon & Lee, 2024).

Positive Influence on Health Outcomes

Clients’ records consist of history, clinical diagnosis, treatments given, medications used, and results of the particular patient (Derecho et al., 2024). This information can reveal the trends of situations and probable causes, which will help implement tactics for early treatment and prevention. In Marta’s case, her surgeries, her treatments, and especially her recovery records are very important in coming up with a safe plan of discharge. Using multiple data improves patient care by creating a comprehensive view of their health, increasing treatment accuracy and patient safety since they are at the center of the treatment process (Lewis et al., 2023). 

Coordination of Findings through HIT

When implemented by different teams, Health Information Technology or electronic HIT expedites the sharing of findings by other interdisciplinary team members (Chen et al., 2023). Everyone can view and update an EHR, which will contain all the information concerning the patient in real time. This means different team members are well aware of what other members are doing in relation to a particular patient, and everybody has an overview of a particular patient’s condition. The HIT is applied in Marta’s case when the care team members discuss Marta’s progress in the rehabilitation process to make interpersonal and well-coordinated decisions. For instance, a pharmacist may check through prescriptions and a nurse’s note about a patient’s allergy to avoid administering fatal doses of medication to the patient (Lahijanian & Alvarado, 2021). It also elevates care quality, facilitates the efficient delivery of health, and enhances the resulting impact on the members of multiple teams. 

NURS FPX 6612 Assessment 3 Quality Improvement Proposal Conclusion 

It is crucial to refer to and utilize Health Information Technology (HIT) and records on the client to create an appropriate Discharge Care Plan (Park & Park, 2023). Automating physical and emotional health status and using data reporting that involves the client’s behavior helps improve the services’ coordination, clinical practice, and interdisciplinary relationships (Marafino et al., 2021). These technological tools help provide detailed knowledge of the patient’s condition and planning of the discharge process to enhance the patient’s recovery and avoid adverse outcomes. Integrating various elements of HIT bridges the gaps in the continuum of care, leading to improved care (Tsai et al., 2020).

NURS FPX 6612 Assessment 3 Quality Improvement Proposal References

Borycki, E. M., & Kushniruk, A. W. (2023). Health technology, quality and safety in a learning health system. Healthcare Management Forum, 36(2), 79–85. https://doi.org/10.1177/08404704221139383

Chen, Z., Liang, N., Zhang, H., Li, H., Yang, Y., Zong, X., Chen, Y., Wang, Y., & Shi, N. (2023). Harnessing the power of clinical decision support systems: Challenges and opportunities. Open Heart, 10(2), e002432. https://doi.org/10.1136/openhrt-2023-002432  

Derecho, C., Cafino, R., Aquino, L., Isla, A., Esencia, A., Lactuan, J., Maranda, G., & Velasco, P. (2024). Technology adoption of electronic medical records in developing economies: A systematic review on physicians’ perspective. Digital Health, 10, 20552076231224605. https://doi.org/10.1177/20552076231224605 

Ehsani, B., Martin, K., & Queenan, J. A. (2021). Data quality in healthcare: A report of practical experience with the Canadian Primary Care Sentinel Surveillance Network data. Journal of the Health Information Management, 50(1-2), 88–92. https://doi.org/10.1177/1833358319887743 

Holmgren, J., Esdar, M., Hüsers, J., & Coutinho, J. (2023). Health information exchange: Understanding the policy landscape and future of data interoperability. Yearbook of Medical Informatics, 32(1), 184–194. https://doi.org/10.1055/s-0043-1768719 

Jung, S. Y., Hwang, H., Lee, K., Lee, D., Yoo, S., Lim, K., Lee, Y., & Kim, E. (2021). User perspectives on barriers and facilitators to the implementation of electronic health records in behavioral hospitals: Qualitative study. JMIR Formative Research, 5(4), e18764. https://doi.org/10.2196/18764 

Kwon, H., & Lee, D. (2024). Clinical decision support system for clinical nurses’ decision-making on nurse-to-patient assignment: A scoping review protocol. BMJ Open, 14(1), e080208. https://doi.org/10.1136/bmjopen-2023-080208 

Lahijanian, B., & Alvarado, M. (2021). Care strategies for reducing hospital readmissions using stochastic programming. Healthcare, 9(8), 940. https://doi.org/10.3390/healthcare9080940 

Lewis, E., Weiskopf, N., Abrams, B., Foraker, R., Lai, M., Payne, O., & Gupta, A. (2023). Electronic health record data quality assessment and tools: A systematic review. Journal of the American Medical Informatics Association, 30(10), 1730–1740. https://doi.org/10.1093/jamia/ocad120 

Li, E., Clarke, J., Ashrafian, H., Darzi, A., & Neves, L. (2022). The impact of electronic health record interoperability on safety and quality of care in high-income countries: Systematic review. Journal of Medical Internet Research, 24(9), e38144. https://doi.org/10.2196/38144 

Marafino, J., Escobar, J., Baiocchi, T., Liu, X., Plimier, C., & Schuler, A. (2021). Evaluation of an intervention targeted with predictive analytics to prevent readmissions in an integrated health system: Observational study. BMJ, 374, n1747. https://doi.org/10.1136/bmj.n1747 

Park, J., & Park, J. (2023). Identifying the knowledge structure and trends of nursing informatics: A text network analysis. Computers, Informatics, Nursing, 41(1), 8–17. https://doi.org/10.1097/CIN.0000000000000919 

Tsai, H., Eghdam, A., Davoody, N., Wright, G., Flowerday, S., & Koch, S. (2020). Effects of electronic health record implementation and barriers to adoption and use: A scoping review and qualitative content analysis. Life, 10(12), 327. https://doi.org/10.3390/life10120327 

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