Rethinking Health Systems Responsiveness in Low- and Middle-Income Countries: Validation Study
Bibliographic record
Abstract
BACKGROUND: Health systems responsiveness (HSR) is the ability of systems to respond to legitimate non-health expectations of the population. The concept of HSR by the World Health Organization (WHO) includes respect for dignity, individual autonomy, confidentiality, prompt attention to care, availability of basic amenities, choice of provider, access to social support networks, and clarity of communication. The WHO tool is applied globally to assess HSR in low, middle, and high-income countries. OBJECTIVE: We have revised the conceptual framework of HSR following a rigorous systematic review and made it specific for low- and middle-income countries (L&MICs). This study is designed to (1) run the Delphi technique to validate the upgraded conceptual framework of HSR, (2) modify and upgrade the WHO measurement tool for assessing HSR in the context of L&MICs, and (3) determine the validity of the upgraded HSR measurement tool by pilot testing it in Pakistan. METHODS: The Delphi technique will be run by inviting global public health experts to provide suggestions on the domains and subdomains of HSR specific to L&MICs. Cronbach ɑ will be calculated to determine internal consistency among the participants. The upgraded HSR conceptual framework will serve as a beacon to modify the measurement tool by the research team, which will be reviewed by subject experts for refinement. The modified tool will be pilot-tested by administering it to 1128 participants from primary, secondary, and tertiary care hospitals in Rawalpindi district, Pakistan. Additionally, an "observation checklist" of HSR domains and subdomains will be completed to objectively measure the state of HSR across health care facilities. HSR assessment will be further strengthened by incorporating the perspective of hospital managers, service providers, and policy makers (ie, the supply side) as well as community leaders and representatives (ie, the demand side) through qualitative interviews. RESULTS: The study was started in January 2024 and will continue until February 2025. A multidimensional approach will yield significant quantifiable information on HSR from the demand and supply sides of L&MICs. CONCLUSIONS: This study will provide a conceptual understanding of HSR and a corresponding measurement tool specific to L&MICs. It will contribute to global public health literature and provide a snapshot of HSR in Rawalpindi district, Pakistan, with concrete action points for policy makers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59836.
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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 | 0.078 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".