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The Hidden Workload Study protocol: a national mixed-methods analysis of general practice workload and local
Kirsten Lee1, Selma Audi1, Thomas Brain1,2
1Population Health Research Institute, City St George's, University of London, London, UK.
General practice faces increasing workload, with "hidden" tasks like administration unmeasured. This study quantoys to quantify all clinician activities, revealing workload variations and informing future planning.
Area of Science:
- Primary Care Research
- Health Services Research
- Occupational Health
Background:
- General practice workload is rising, but current data only captures appointment numbers, neglecting crucial administrative and supervisory tasks.
- Existing National Health Service (NHS) data fails to quantify the full spectrum of general practice activities.
- The 'hidden' workload, encompassing non-appointment-based tasks, remains unmeasured and unaddressed.
Purpose of the Study:
- To comprehensively examine the diverse tasks undertaken daily by general practice clinicians.
- To investigate variations in workload based on clinical roles and practice demographics.
- To explore the lived experiences of general practice workload through qualitative interviews.
Main Methods:
- Mixed-methods approach combining quantitative task recording and qualitative interviews.
- Utilizing the Primary Care Academic Collaborative network for participant recruitment across English general practices.
- Data collection via task logs and timers for a full day's activities, supplemented by practice demographic data and semi-structured interviews.
Main Results:
- Quantitative data will detail task distribution (clinical, administrative, supervisory, breaks) by clinician role and practice type.
- Qualitative data will provide in-depth insights into the subjective experience of workload.
- Analysis will identify key drivers of workload variation within general practice.
Conclusions:
- The Hidden Workload Study will offer a holistic view of contemporary general practice workload.
- Findings will illuminate factors contributing to workload disparities.
- Results will inform evidence-based service provision and strategic workforce planning in primary care.
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