Diabetes Health Services in Sri Lanka: Development of a Quality Index
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus is a major public health issue in Sri Lanka and across the globe. Patients with diabetes mellitus (DM) need long term comprehensive care. Quality of care for DM varies in different settings. Service quality assessment leads to identifying service areas that may benefit from appropriate intervention in order to achieve better health outcomes. The aim of this study was to develop and validate an instrument to measure the quality of services provided for patients with DM attending medical and diabetic clinics in state hospitals of Sri Lanka. METHODS: A ‘Care for DM Quality of services’ (CD QS) instrument comprised of 8 subscales: routine services, glycaemic control, Blood Pressure and lipid control, weight control, annual screening, patient empowerment, recording of information and functional aspects was developed and validated. Trained research assistants collected data from 100 volunteer patients attending four diabetic clinics two each at secondary and tertiary level hospitals. Construct validity was established by multi-trait scaling analysis and known group comparisons. Internal consistency was assessed by item-total correlations and Cronbach’s alpha. Cut off levels to classify the hospital clinic as ‘good’, ‘moderate’ or ‘poor’ performance were determined by the average score in each subscale being above mean + SD (good), between mean + SD (moderate), and below the mean –SD (poor) respectively. RESULTS: Multi-trait scaling analysis of items showed highest correlation with its own subscale compared to the other subscales. Significantly higher mean scores (p<0.05) for all the subscales were observed in tertiary level clinics compared to the secondary level. Internal consistency of ‘CD QS’ was good with Cronbach’s alpha of 0.9. Intra Class Correlation Coefficients were over 0.9 for all subscales with confidence intervals ranging from 0.8 to 2.9 suggestive of good inter-rater reliability. CONCLUSIONS: ‘CD QS’ is a valid and reliable tool to assess both functional and technical quality of follow up care provided for patients with DM. This facilitates regular quality assessment of DM care thus identifying the gaps and improving the service quality. Further implementation and testing for clinical usefulness and acceptability will determine the tools application in the healthcare setting.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".