Shifting human resources for health in the context of ART provision: qualitative and quantitative findings from the Lablite baseline study
Bibliographic record
Abstract
BACKGROUND: Lablite is an implementation project supporting and studying decentralized antiretroviral therapy (ART) rollout to rural communities in Malawi, Uganda and Zimbabwe. Task shifting is one of the strategies to deal with shortage of health care workers (HCWs) in ART provision. Evaluating Human Resources for Health (HRH) optimization is essential for ensuring access to ART. The Lablite project started with a baseline survey whose aim was to describe and compare national and intercountry delivery of ART services including training, use of laboratories and clinical care. METHODS: A cross-sectional survey was conducted between October 2011 and August 2012 in a sample of 81 health facilities representing different regions, facility levels and experience of ART provision in Malawi, Uganda and Zimbabwe. Using a questionnaire, data were collected on facility characteristics, human resources and service provision. Thirty three (33) focus group discussions were conducted with HCWs in a subset of facilities in Malawi and Zimbabwe. RESULTS: The survey results showed that in Malawi and Uganda, primary care facilities were run by non-physician clinical officers/medical assistants while in Zimbabwe, they were run by nurses/midwives. Across the three countries, turnover of staff was high especially among nurses. Between 10 and 20% of the facilities had at least one clinical officer/medical assistant leave in the 3 months prior to the study. Qualitative results show that HCWs in ART and non-ART facilities perceived a shortage of staff for all services, even prior to the introduction of ART provision. HCWs perceived the introduction of ART as having increased workload. In Malawi, the number of people on ART and hence the workload for HCWs has further increased following the introduction of Option B+ (ART initiation and life-long treatment for HIV positive pregnant and lactating women), resulting in extended working times and concerns that the quality of services have been affected. For some HCWs, perceived low salaries, extended working schedules, lack of training opportunities and inadequate infrastructure for service provision were linked to low job satisfaction and motivation. CONCLUSIONS: ART has been decentralized to lower level facilities in the context of an ongoing HRH crisis and staff shortage, which may compromise the provision of high-quality ART services. Task shifting interventions need adequate resources, relevant training opportunities, and innovative strategies to optimize the operationalization of new WHO treatment guidelines which continue to expand the number of people eligible for ART.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".