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Operationalizing Well-Being Using Work Determinants of Well-Being: Building a Well-Being Analytics Approach.

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Summary
This summary is machine-generated.

Healthcare systems need to measure Work Determinants of Well-Being (WDOW) to improve staff health. Analyzing data like Paid Time Off (PTO) utilization can reduce burnout and enhance healthcare worker well-being.

Keywords:
paid time offwell-being data analyticswork determinants of well-being

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Area of Science:

  • Healthcare Operations
  • Occupational Health
  • Health Systems Science

Background:

  • Healthcare worker well-being is crucial but hindered by inadequate metrics.
  • Existing metrics do not allow for a systems-level approach to well-being.
  • Addressing well-being requires identifying organizationally attributable Work Determinants of Well-Being (WDOW).

Purpose of the Study:

  • To describe the development of a well-being analytics team and database.
  • To identify WDOW by leveraging existing healthcare data.
  • To illustrate how analyzing WDOW, such as Paid Time Off (PTO) utilization, can improve healthcare worker well-being and reduce burnout.

Main Methods:

  • Established a dedicated well-being analytics team.
  • Built a comprehensive database integrating existing healthcare system data.
  • Analyzed Paid Time Off (PTO) utilization as a case example of a Work Determinant of Well-Being (WDOW).

Main Results:

  • Successfully created a well-being analytics infrastructure.
  • Identified key Work Determinants of Well-Being (WDOW) through data analysis.
  • Demonstrated the potential of PTO utilization analysis to inform interventions for burnout reduction.

Conclusions:

  • A systems approach to healthcare worker well-being is feasible through data analytics.
  • Identifying and measuring WDOW is essential for effective well-being strategies.
  • Analyzing operational data like PTO utilization offers a practical pathway to enhance HCW well-being and mitigate burnout.