Central Healthcare System
Consider the following scenario:
Central Healthcare System (CHS) operates 12 hospital facilities within the service area and manages all of their own administrative, management, and operational functions in-house. Human Resources staff have alerted CHS administrators that there have been higher than usual rates of hospital staff turnover in recent months and that it has been difficult to ensure that all shifts are fully staffed. Several clinical leaders have also mentioned to administrators that the tone of department meetings has grown increasingly negative and that there is a pervasive sense of discouragement and fatigue amongst frontline staff. CHS healthcare administrators are concerned about these developments, but they are unsure which potential action steps will most effectively address them. They resolve to review the literature on employee burnout, examine existing internal data, and collect additional data from frontline staff to develop a comprehensive understanding of the problem that will help them make an evidence-based decision.
In this scenario, CHS administrators are at the beginning of a data-driven decision-making process. They have just learned about a staff-burnout problem and outlined preliminary data collection steps that will provide them with a comprehensive understanding to guide future action. What kinds of data do you think CHS leaders need to fully understand the burnout problem and underlying causes? Where are the various types of needed data located? How should CHS leaders organize the data they collect into a format that provides meaningful context? In this Assignment, you will apply your knowledge of data-driven decision-making to develop a data collection and organization plan for Central Healthcare System leaders to inform their decision-making on staff burnout.
DO:
Draft a 6- to 7-page paper in which you analyze the data collection and organization that the healthcare administration leaders in the scenario could undertake to make a data-driven decision. Within your paper, include the following:
• Describe data collection from the literature:
o Describe the data that need to be collected from the literature to inform the decision and explain how you would collect it.
o Describe how you would approach this type of search of the literature, including your search strategy, databases used, and search terms used.
o Identify 3 or 4 empirical research articles that would support a decision for this scenario (include properly formatted references for each).
o Assess how the literature-search strategy would inform decision-making for the scenario.
• Describing HSO data collection:
o Describe the data (both quantitative and qualitative) that need to be collected from the HSO to inform the decision. These includes data that may be found within administrative records, electronic health records, or other such databases and data that have yet to be collected, such as through surveys or focus groups.
o Describe where each piece of the data is located and explain how you would collect it. Include descriptive information for each piece of data, as well as the best way to collect it (e.g., through surveys or focus groups).
o Assess how the data results would inform decision-making for this scenario. In your explanation, evaluate the strengths and limitations of the data results and implications for decision-making.
• Organizing the data:
o Explain strategies you would use to organize the data from the literature and the different types of HSO data to inform the decision-making process.
Data Collection and Organization Plan for Central Healthcare System (CHS)
Introduction:
Central Healthcare System (CHS) faces a critical issue: rising staff turnover and declining morale, indicative of potential burnout. To address this effectively, CHS administrators must adopt a data-driven decision-making approach. This plan outlines data collection strategies from the literature and internal HSO sources, followed by data organization methods to inform evidence-based decisions.
1. Data Collection from the Literature:
- Data Needed:
- Evidence-based strategies for preventing and mitigating staff burnout in healthcare settings.
- Factors contributing to burnout, including workload, organizational culture, and leadership styles.
- The impact of burnout on patient safety, staff retention, and organizational performance.
- Best practices for improving staff well-being and engagement.
- Collection Approach:
- Search Strategy: A systematic review of relevant databases using a combination of keywords and controlled vocabulary.
- Databases: PubMed, CINAHL, PsycINFO, and Google Scholar.
- Search Terms: "healthcare staff burnout," "nurse burnout," "physician burnout," "employee turnover healthcare," "healthcare workplace stress," "organizational culture healthcare," "staff well-being healthcare," "preventing healthcare burnout," "healthcare employee engagement."
- Combining terms with boolean operators (AND, OR, NOT) to refine search results.
- Using filters for publication date, study design, and population.
- Empirical Research Articles:
- Reference 1: Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual review of psychology, 52(1), 397-422.
- Reference 2: Aiken, L. H., Clarke, S. P., Sloane, D. M., Sochalski, J., & Silber, J. H. (2002). Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA, 288(16), 1987-1993.
- Reference 3: West, C. P., Dyrbye, L. N., & Shanafelt, T. D. (2018). Physician burnout: contributors, prevention and treatment. Journal of internal medicine, 283(6), 516-529.
- Reference 4: Panagioti, M., Geraghty, K., Johnson, J., Zhou, A., Panagopoulou, E., Chew-Graham, C. A., ... & Geraghty, R. K. (2018). Association between physician burnout and patient safety, professionalism, and patient satisfaction: a systematic review and meta-analysis. JAMA internal medicine, 178(10), 1317-1331.
- Literature Search Strategy Impact:
- Provides a foundation for understanding the scope and nature of staff burnout.
- Identifies evidence-based interventions and best practices.
- Helps to frame the internal data collection and analysis.
- Allows for comparison of CHS data to findings in other healthcare systems.
2. Describing HSO Data Collection:
- Quantitative Data:
- Staff Turnover Rates:
- Location: HR records.
- Collection: Review monthly turnover reports, analyze trends over time.
- Description: Number of staff departures per month, categorized by department and job role.
- Absenteeism Rates:
- Location: HR records.
- Collection: Analyze attendance records, track sick leave and unscheduled absences.
- Description: Number of unscheduled absences per month, categorized by department.
- Overtime Hours:
- Location: Payroll records.
- Collection: Review overtime reports, track average overtime hours per employee.
- Description: Average overtime hours per month, per department.
- Patient Satisfaction Scores:
- Location: Patient satisfaction surveys.
- Collection: Analyze survey results, look for correlations with staff burnout.
- Description: Average patient satisfaction scores per department.
- Employee Engagement Survey Data:
- Location: Previous employee survey data if available.
- Collection: Analyze previous survey data, and implement new surveys if needed.
- Description: employee responses to questions regarding job satisfaction, and feeling valued.
- Staff Turnover Rates:
- Qualitative Data:
- Focus Groups:
- Location: Conduct focus groups with frontline staff from various departments.
- Collection: Facilitate discussions about workplace stressors, morale, and suggestions for improvement.
- Description: Transcripts and summaries of focus group discussions.
- Individual Interviews:
- Location: Conduct interviews with clinical leaders and HR staff.
- Collection: Gather insights into observed changes in staff behavior and department dynamics.
- Description: Interview notes and summaries.
- Open-Ended Survey Questions:
- Location: Online or paper surveys.
- Collection: Include open ended questions in staff surveys to allow staff to provide narrative responses.
- Description: Narrative responses from staff members.
- Focus Groups:
- Data Results Impact:
- Quantitative data provides objective measures of burnout indicators.
- Qualitative data offers rich insights into the lived experiences of staff.
- Strengths: Provides a very well rounded view of the problem.
- Limitations: Qualitative data can be subjective. Quantitative data can lack context.
- Implications: Combined data will help to identify specific areas of concern and develop targeted interventions.
3. Organizing the Data:
- Data Integration:
- Create a centralized database to store all collected data.
- Use a spreadsheet or database software to organize quantitative data.
- Transcribe and code qualitative data for thematic analysis.
- Data Visualization:
- Develop charts and graphs to visualize trends in turnover, absenteeism, and overtime.
- Create heat maps to identify departments with high burnout rates.
- Use word clouds to summarize common themes from qualitative data.
- Data Analysis:
- Conduct statistical analysis to identify correlations between burnout indicators.
- Use thematic analysis to identify patterns and themes in qualitative data.
- Develop a narrative report that integrates quantitative and qualitative findings.
- Reporting:
- Create reports that clearly display the data, and the findings of the data.
- Use language that is easy to understand.
- Provide clear recommendations based on the data.
- Data Security:
- Ensure all data is stored in compliance with HIPAA and other applicable privacy regulations.
- Limit access to sensitive data to authorized personnel.
By implementing this comprehensive data collection and organization plan, CHS leaders can gain a deep understanding of staff burnout and develop effective, evidence-based interventions.