Comparability of family planning quality of care measurement tools in low-and-middle income country settings: a systematic review
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Bibliographic record
Abstract
BACKGROUND: In low-and-middle income countries (LMICs), accurate measures of the elements of quality care provided by a health worker through family planning services (also known as process quality) are required to ensure family's contraceptives needs are being met. There are many tools used to assess family planning process quality of care (QoC) but no one standardized method. Those measuring QoC in LMICs should select an appropriate tool based the program context and financial/logistical parameters, but they require data on how well each tool measures routine clinical care. We aim to synthesize the literature on validity/comparability of family planning process QoC measurement tools through a quantitative systematic review with no meta-analysis. METHODS: We searched six literature databases for studies that compared quality measurements from different tools using quantitative statistics such as sensitivity/specificity, kappa statistic or absolute difference. We extracted the comparative measure along with other relevant study information, organized by quality indicator domain (e.g. counseling and privacy), and then classified the measure by low, medium, and high agreement. RESULTS: We screened 8172 articles and identified eight for analysis. Studies comparing quality measurements from simulated clients, direct observation, client exit interview, provider knowledge quizzes, and medical record review were included. These eight studies were heterogenous in their methods and the measurements compared. There was insufficient data to estimate overall summary measures of validity for the tools. Client exit interviews compared to direct observation or simulated client protocols had the most data and they were a poor proxy of the actual quality care received for many measurements. CONCLUSION: To measure QoC consistently and accurately in LMICs, standardized tools and measures are needed along with an established method of combining them for a comprehensive picture of quality care. Data on how different tools proxy quality client care will inform these guidelines. Despite the small number of studies found during the review, we described important differences on how tools measure quality of care.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it