NURS FPX 6612 Assessment 3 Patient Discharge Care Planning

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NURS FPX 6612 Assessment 3 Patient Discharge Care Planning

NURS FPX 6612 Assessment 3 Patient Discharge Care Planning

Name

Capella university

NURS-FPX 6612 Health Care Models Used in Care Coordination

Prof. Name

Date

Patient Discharge Care Planning

This assessment is based on a patient scenario named Marta Rodriguez, who had a car accident in Nevada. As a freshman in the first semester of college, Marta had gained a student health insurance plan and was acquiring care in the nearest shock trauma center for the past four weeks. However, she was recently moved from New Mexico to Nevada to study. Marta underwent several surgeries and antibiotic treatment against systemic infection. The patient’s native language is Spanish, while English is her second language. As a senior care coordinator overseeing Marta’s care treatments, analyzing the key issues that interprofessional team members must delve into to ensure effective discharge care planning for patients is imperative.

Therefore, I will present Marta’s case in an upcoming interprofessional team meeting to discuss the careful discharge plan with a coordinated care approach. This will require meaningful use of Health Information Technologies (HIT) to enable care coordination and continuity of care in the discharge planning. Moreover, the plan will discuss data reporting ways and their impact on care management and clinical efficiency. Lastly, the plan will discuss how the patient-reported health information can enhance the patient’s health outcomes.

 Longitudinal Patient Care Plan

HIT plays a significant role in smooth care transitions and the continuum of care after patient discharge. These innovative technological alternatives to traditional in-person care can promote remote monitoring and virtual follow-up appointments (Abraham et al., 2022). In Marta’s case, interprofessional team members can use Electronic Health Records with multilingual capabilities to create and maintain a concise and thorough digital record of the patient’s medical history and treatment plans. This will include her shock trauma center stay, surgeries, and antibiotic treatment histories (Khoong et al., 2020). The healthcare professionals will use this platform to access real-time data about Marta’s health status. This will facilitate collaborative decision-making and ensure continuity of care across different healthcare settings (Khoong et al., 2020). 

The interprofessional team will integrate telehealth platforms and remote monitoring tools to monitor Marta’s recovery progress post-discharge. This includes virtual follow-up appointments, medication adherence tracking, and vital sign monitoring. Telehealth services with remote monitoring elements will enhance patient engagement and allow the team to address emerging health concerns proactively. These tools will provide real-time data on Marta’s health status post-discharge, enabling early detection and intervention to prevent potential complications (Somsiri et al., 2020).

Furthermore, predictive analysis tools and Clinical Decision Support Systems (CDSS) will be used to assess Marta’s risk of readmission based on several factors, such as post-operative recovery, infection risks, and adherence to treatment plans. Interprofessional teams will use these tools to identify the potential causes before they escalate and allow timely targeted interventions. The decision support systems will assist healthcare providers in making evidence-based decisions for Marta’s specific health needs and minimize the risk of readmission (Oosterhoff et al., 2021).

Logical Implications of HIT in Care Planning  

These HIT elements collectively contribute to a comprehensive and patient-centered care plan, reducing the risk of readmission within 48 hours post-discharge. With the help of real-time data access, continuous monitoring, and virtual consultations, interprofessional team members can promptly identify and address any potential issues with enhanced patient engagement (Srinivasan et al., 2020). Additionally, through EHR use and CDDS, care coordination will be improved due to better communication and collaboration. This will foster a holistic care approach to facilitate a continuum of care for Marta’s post-discharge care. Hence, using HIT tools supports longitudinal and patient-oriented care plans by enhancing interprofessional care coordination and patient empowerment (Somsiri et al., 2020).

Consequences of Using Specific Data and Information

By using specific health-related data and information, such as acknowledging the language barrier and implementing interpretation technology to ensure accurate and clear communication, patient engagement will be enhanced, and adherence to treatment plans in Marta’s case will be facilitated. Moreover, using past medical history data and treatment plans, Marta’s ongoing care will be better aligned, reducing the chances of treatment errors, hospital readmissions, and emergency visits (Abraham et al., 2022). Lastly, using the information on Marta’s health insurance plan, billing processes for Marta’s care will be streamlined, and insurance-relevant delays can be avoided.

Data Reporting Pertinent to Client Behaviors

Reporting health-related data is significant in ensuring smooth care coordination and improving health outcomes. Moreover, data reporting within healthcare settings promotes efficiency in clinical practice and interprofessional innovation in care treatments. Following are the three ways in which data reporting can impact care coordination, clinical efficiency, care management, and interprofessional creative idea development:

  • By analyzing data related to Marta’s behaviors, such as medication adherence and follow-up attendance, the care coordination team can tailor the care coordination approach related to procured information. For example, suppose reported data indicates inconsistent medication adherence (Kumar et al., 2022). In that case, the healthcare team can implement targeted interventions such as medication reminders or educational resources in Spanish to address potential language-related barriers. This tailored approach will improve care coordination and care management by addressing specific challenges Marta faces. The team can allocate resources effectively and ensure tailored interventions suit her unique health needs (Kumar et al., 2022).

NURS FPX 6612 Assessment 3 Patient Discharge Care Planning

  •  Data-driven insights from reported data on Marta’s health can also enhance clinical efficiency by analyzing post-operative and post-discharge recovery progress, pain levels, and following rehabilitation exercises. Suppose data suggests slower-than-expected recovery or signs of discomfort. In that case, the healthcare team can adjust the care plan and schedule follow-up appointments to enhance clinical efficiency and provide timely and targeted care (Richards et al., 2020).
  • Analyzing data on communication preferences and engagement with culturally diverse patients can shape interprofessional innovative solutions. By assessing Marta’s communication preferences, patient satisfaction, and engagement with culturally appropriate resources, the interprofessional team can be well-informed about the need for innovation in care delivery (Real et al., 2020). For instance, if data highlights a preference for specific communication channels or indicates gaps in cultural competence, the team can explore innovative solutions such as virtual support groups in Spanish or personalized educational materials for Marta. By leveraging technology, the team can craft innovative interprofessional care solutions to address identified needs from reported data (Real et al., 2020).

Logical Implications of Data Reporting

Data reporting relevant to patients’ health behaviors and patterns facilitates a deeper understanding of the root causes behind certain patients’ behaviors and helps healthcare providers address underlying issues rather than just symptoms  (Provost & Murray, 2022). Additionally, data reporting has another logical implication of Marta’s behavior data, i.e., encouraging a culture of continuous improvement. Continuous improvement promotes refining care processes and strategies based on data-driven insights. Therefore, data reporting specific to client behaviors is a powerful tool that can maximize impact on care coordination, management, clinical efficacy, and multidisciplinary idea development (Provost & Murray, 2022).

Evaluating the Quality of Data

The quality of collected data can be evaluated by ensuring its relevance, accuracy, consistency, and timeliness. If the data collected are aligned with specific goals of care coordination and management for Marta, it shows qualified data. Ignorant and extraneous data can hinder accurate decision-making. Moreover, healthcare professionals can evaluate data accuracy by using data validation techniques and ensuring the patient’s behaviors reflect her health status and actions. Additionally, timely reporting is crucial for decision-making. Therefore, evaluating the timeliness of data ensures that interventions are implemented promptly (Moghaddam et al., 2019). 

Using Client Records to Positively Influence Health Outcomes

The information collected from Marta’s records can positively impact her health outcomes. This can be done by developing personalized care plans based on the patient’s medical history, preferences, and previous intervention responses (Kasula, 2023). These care plans optimize healthcare services and enhance adherence to Marta’s treatment plan. Ultimately, her health improvement is manifested in the form of favorable health outcomes. Additionally, analyzing Marta’s records will help identify health risks and potential complications early. This will enable proactive interventions to prevent the worsening of conditions (Wang et al., 2020). Enhanced sharing of relevant information from client records with patients encourages active participation in care treatments and empowers clients to make informed decisions about their health (Lyles et al., 2020). 

Interprofessional team members can share their findings from records in a unified EHR system to promote care coordination among all team members. EHR promotes a comprehensive view of a patient’s health status (Lyles et al., 2020). Additionally, they can conduct scheduled meetings or virtual conferences that allow team members to discuss their findings, share insights, and coordinate care plans. Efficient communication channels within the HIT system will also facilitate the sharing of real-time updates about Marta’s health status. Moreover, establishing standardized protocols for recording information in Marta’s records ensures uniformity in data collection. This makes it easier for different team members to interpret and build upon each other’s findings (Boussard et al., 2020).

Underlying Assumptions and Well-Reasoned Conclusions

The analysis is based on several assumptions, including that collaboration among interprofessional team members is crucial for smooth care transitions, reduced hospital readmissions, and enhanced continuity of care after discharge. Additionally, it is assumed that HIT enhances coordination by reducing errors, preventing treatment delays, and increasing access to up-to-date information (Abraham et al., 2022). Furthermore, the assumption that data quality in client records is essential is warranted, as accurate or complete health information can lead to incorrect conclusions and negatively impact patient health outcomes (Moghaddam et al., 2019).

Conclusion

Marta, a student of freshman in college, happens to have a car accident and is under care at a trauma shock center. Her care transition for post-discharge care requires an interprofessional approach to reduce the risk of hospital readmission rates. Therefore, as a senior care coordinator, I suggest utilizing HIT to provide a patient-centered care plan that addresses critical issues such as the language barrier. Moreover, we can use client-specific data behaviors in multiple ways to improve care coordination, management, and clinical efficiency. Additionally, we can brainstorm ideas to craft innovative interprofessional approaches to meet patients’ unique health needs by using health information data. This information can improve her health outcomes as a continuum of care is consistently maintained.

References

Abraham, J., Meng, A., Tripathy, S., Kitsiou, S., & Kannampallil, T. (2022). Effect of Health Information Technology (HIT)-based discharge transition interventions on patient readmissions and emergency room visits: A systematic review. Journal of the American Medical Informatics Associationhttps://doi.org/10.1093/jamia/ocac013 

Boussard, T. H., Bozkurt, S., Ioannidis, J. P. A., & Shah, N. H. (2020). MINIMAR (minimum information for medical AI reporting): Developing reporting standards for artificial intelligence in health care. Journal of the American Medical Informatics Associationhttps://doi.org/10.1093/jamia/ocaa088 

Kasula, B. Y. (2023). Harnessing machine learning for personalized patient care. Transactions on Latest Trends in Artificial Intelligence4(4). https://ijsdcs.com/index.php/TLAI/article/view/399 

Khoong, E. C., Rivadeneira, N. A., Hiatt, R. A., & Sarkar, U. (2020). The use of technology for communicating with clinicians or seeking health information in a multilingual urban cohort: Cross-Sectional survey. Journal of Medical Internet Research22(4), e16951. https://doi.org/10.2196/16951 

Kumar, S., Qiu, L., Sen, A., & Sinha, A. P. (2022). Putting analytics into action in care coordination research: Emerging issues and potential solutions. Production and Operations Management31(6). https://doi.org/10.1111/poms.13771 

Lyles, C. R., Nelson, E. C., Frampton, S., Dykes, P. C., Cemballi, A. G., & Sarkar, U. (2020). Using electronic health record portals to improve patient engagement: Research priorities and best practices. Annals of Internal Medicine172(11), 123–129. https://doi.org/10.7326/m19-0876 

NURS FPX 6612 Assessment 3 Patient Discharge Care Planning

Moghaddam, B. E., Martin, K., & Queenan, J. A. (2019). Data quality in healthcare: A report of practical experience with the Canadian primary care sentinel surveillance network data. Health Information Management Journal50(1-2), 183335831988774. https://doi.org/10.1177/1833358319887743 

Oosterhoff, J. H. F., Thio, Q. C. B. S., Groot, O. Q., Bongers, M. E. R., Ghaednia, H., Karhade, A. V., Del Fiol, G., & Kawamoto, K. (2021). Integration of automated predictive analytics into electronic health records: Can spine surgery applications lead the way using SMART on FHIR and CDS hooks? Seminars in Spine Surgery, 100870. https://doi.org/10.1016/j.semss.2021.100870 

Provost, L. P., & Murray, S. K. (2022). The health care data guide: Learning from data for improvement. In Google Books. John Wiley & Sons. https://books.google.com/books?hl=en&lr=&id=5Wh6EAAAQBAJ&oi=fnd&pg=PA17&dq=data+record+of+patient+for+continuous+improvement&ots=G0o17507Hl&sig=lSlgbGmxhB9yq1pnIwy6oOi5BUE 

Real, K., Bell, S., Williams, M. V., Latham, B., Talari, P., & Li, J. (2020). Patient perceptions and real-time observations of bedside rounding team communication: The Interprofessional Teamwork Innovation Model (ITIM). The Joint Commission Journal on Quality and Patient Safety46(7). https://doi.org/10.1016/j.jcjq.2020.04.005 

Richards, H. S., Blazeby, J. M., Portal, A., Harding, R., Reed, T., Lander, T., Chalmers, K. A., Carter, R., Singhal, R., Absolom, K., Velikova, G., & Avery, K. N. L. (2020). A real-time electronic symptom monitoring system for patients after discharge following surgery: A pilot study in cancer-related surgery. BMC Cancer20(1). https://doi.org/10.1186/s12885-020-07027-5 

NURS FPX 6612 Assessment 3 Patient Discharge Care Planning

Somsiri, V., Asdornwised, U., O’Connor, M., Suwanugsorn, S., & Chansatitporn, N. (2020). Effects of a transitional telehealth program on functional status, rehospitalization, and satisfaction with care in thai patients with heart failure. Home Health Care Management & Practice, 108482232096940. https://doi.org/10.1177/1084822320969400 

Srinivasan, M., Jayant, P., Zulman, D., Thadaney, I., Samuel, M., Robert, S., Lance, D. M., Ian, N., Artandi, M., & Sharp, C. (2020). Enhancing patient engagement during virtual care: A conceptual model and rapid implementation at an academic medical center. NEJM Catalysthttps://catalyst.nejm.org/doi/full/10.1056/CAT.20.0262 

Wang, Q. Q., Kaelber, D. C., Xu, R., & Volkow, N. D. (2020). COVID-19 risk and outcomes in patients with substance use disorders: Analyses from electronic health records in the United States. Molecular Psychiatry26(1), 30–39. https://doi.org/10.1038/s41380-020-00880-7 

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