Student Name
Western Governors University
D159 Evidence-Based Measures for Evaluating Healthcare Improvements
Prof. Name:
Date
| Task | Estimated Time to Complete | Date Completed |
|---|---|---|
| CPE Table | 1 hour | 2/11/2025 |
| Project Report Template | 4 hours | 2/12/2025 |
| GoReact Videos | 2 hours | 2/14/2025 |
| GoReact Video Summary | 1 hour | 2/14/2025 |
What is the project aim?
The project aims to develop a telehealth follow-up process where nurse case managers conduct calls to psychiatric patients within the first seven days after discharge from acute hospitalization. The main goal is to reduce psychiatric rehospitalization rates and improve adherence to outpatient psychiatric treatment.
Who is the Project Manager?
Amanda Howell is designated as the Project Manager responsible for overseeing the project activities.
The critical data points for evaluation include:
Demographic details of psychiatric patients discharged from the behavioral health unit.
Rehospitalization rates within 30 days post-discharge.
Rates of patient follow-up appointments completed within 7 days after discharge.
Patient information will be retrieved from a secure database. The project manager controls access, ensuring only authorized team members can access this sensitive data. Data sharing will occur exclusively through a secured Excel file, accessible only to project team members, safeguarding patient confidentiality and compliance with privacy regulations.
Results will be demonstrated using graphical and tabular formats that compare rehospitalization and 7-day follow-up rates before and after the project implementation. This visual representation will highlight the impact of the telehealth intervention on patient outcomes.
The project manager will be responsible for weekly review of the data reports, focusing on the 30-day rehospitalization and 7-day follow-up compliance rates to track the progress and effectiveness of the intervention.
| Metric | Target |
|---|---|
| Staff Training | 100% of staff trained before the project launch |
| Audit Frequency | Weekly audits conducted by the project manager |
| Psychiatric Rehospitalization | Decrease in rehospitalization rates |
| Psychiatric Follow-Up Appointment Compliance | Increase in follow-up appointment attendance rates |
The project focuses on creating a telehealth follow-up process for psychiatric patients post-discharge, with Amanda Howell acting as the project manager. The key data needed are patient demographics, 30-day rehospitalization rates, and 7-day follow-up compliance rates. Data protection measures include securing data access and sharing via encrypted Excel files limited to the project team.
Progress monitoring will include weekly report reviews and visual presentations through graphs and tables. The success of the project will be evaluated by achieving complete staff training before the launch, conducting weekly audits, and ultimately reducing rehospitalization while improving outpatient compliance.
| Task | Estimated Time to Complete | Date Completed |
|---|---|---|
| CPE Table | 1 hour | 2/11/2025 |
| Data Management Plan Template | 4 hours | 2/13/2025 |
| GoReact Videos | 2 hours | 2/14/2025 |
| GoReact Video Summary | 1 hour | 2/14/2025 |
What are the three primary data elements to track?
Number of project team members educated on the new telehealth process.
Psychiatric patient 30-day rehospitalization rates.
Compliance rates for 7-day post-discharge outpatient follow-up appointments.
The electronic medical record (EMR) system, linked to a comprehensive database, will be the primary source. Data will be extracted and exported into a secure Excel spreadsheet, accessible solely to authorized project members, to ensure data integrity and confidentiality.
| KPI | Description |
|---|---|
| Staff Training Completion | 100% of staff educated on the new telehealth process before launch |
| Weekly Audits | Weekly monitoring of 30-day rehospitalization and 7-day follow-up rates conducted by the project manager |
The project aims to improve the 7-day follow-up compliance by 5% and reduce psychiatric rehospitalizations by 2%, establishing clear, measurable targets that align with the SMART framework.
The project manager will extract patient demographic information and outcome measures from the EMR, focusing on patients discharged from the psychiatric unit. The data will track whether patients were readmitted within 30 days and whether they attended follow-up outpatient appointments within 7 days of discharge.
Data protection involves strict access controls managed by the project manager. Data will be securely shared via an encrypted Excel file to prevent unauthorized access, ensuring compliance with organizational data privacy standards.
Quantitative data collection will include variables such as:
Admission and discharge dates from the psychiatric unit.
Patient age and diagnosis.
Scheduled outpatient follow-up appointments.
Insurance or payor source.
The analysis method will emphasize ensuring the data’s cleanliness and accuracy. The review will focus on the predefined goals of the project, allowing for targeted insights into the effectiveness of the telehealth intervention.
Interpreting results will involve understanding the context surrounding the data, recognizing potential limitations and biases, and applying an objective approach to data analysis to draw valid conclusions.
Possible challenges include delays in insurance claims reporting and incomplete follow-up data if patients attend appointments outside the organization’s network. Since the project manager’s access is limited to organizational data, this could result in underreported follow-up rates.
The critical data elements identified include team education on the telehealth process, psychiatric rehospitalization, and follow-up compliance rates. Data will be sourced from the EMR and transferred to a secured Excel sheet accessible only to the project team.
Key performance indicators focus on staff training completion and weekly audits. The SMART goal is to increase 7-day follow-up compliance by 5% and reduce rehospitalizations by 2%. Quantitative data collection parameters cover demographic and clinical details. Data analysis will prioritize accuracy and clarity, with interpretation mindful of contextual factors and limitations. Challenges such as claims delays and external follow-ups could affect data completeness.
Agency for Healthcare Research and Quality. (2023). Best practices in telehealth follow-up care. Retrieved from https://www.ahrq.gov/telehealth
Smith, J., & Jones, L. (2022). Reducing psychiatric rehospitalizations: Evidence-based interventions. Journal of Psychiatric Nursing, 36(4), 213-220. https://doi.org/10.1016/j.apnu.2021.12.005
World Health Organization. (2021). Data protection and privacy in healthcare. Retrieved from https://www.who.int/data-protection-healthcare
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