Task Master/Mining for Data™: an Innovative Strategy for Data Collection Used in a Task Analysis Study in Lesotho

Session: Task Analysis: Adaptation and Application in Africa, Asia and the Caribbean to Gain New Evidence for Health Workforce Strengthening

Presenter: Leah Hart, Jhpiego
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Background: Lesotho’s predominantly rural population faces significant health impacts due to challenges to equitable distribution of the health workforce. Nurses and midwives are the largest health cadres in the country, and need to be adequately prepared to address health priorities in the settings where they work. Data describing their tasks is necessary in order to define education and practice priorities, and the current competence of health workers in task performance. A task analysis study was conducted in 2012-2013 in order to obtain these data.

Method: Nursing and midwifery experts convened to develop and validate a task list which was then used to collect data from 170 currently practicing nurses and midwives from all 10 districts in the country. Task Master: Mining for Data™ was used to collect feedback on the 102-item task list. Participants responded by playing cards that reflected their opinions for each task about frequency conducted, importance to individual or community health, where trained and self-perceived competency. These anonymously numbered cards were collected and recorded, maintaining confidentiality of responses. The study numbers were matched to a biographical data sheet that included workforce location, allowing for analysis of task performance according to geographical area and practice setting.

Results: Diarrheal diseases are a leading cause of young child mortality in Lesotho, yet 22.2% of participants responded that they were not competent at the highly critical task- address diarrheal diseases and associated dehydration with ORS. Other examples include significant gaps in task performance at the community level in TB and HIV related services.

Conclusion: The task analysis in Lesotho provided invaluable data for determining priorities for nursing and midwifery education and practice updates, as well as defining how to improve workforce distribution coverage. Results are being used to prioritize content for in-service training, continuing professional development and pre-service education updates.