ArticleHealth research policy and systems2008
The Quality Improvement Demonstration Study: an example of evidence-based policy-making in practice.
Article in Health research policy and systems, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Comparative effectiveness of two disparate policies on child health: experimental evidence from the Philippines.Health policy and planning · 2017Trial
- The impact of performance incentives on child health outcomes: results from a cluster randomized controlled trial in the Philippines.Health policy and planning · 2014Trial
- The health and cost impact of care delay and the experimental impact of insurance on reducing delays.The Journal of pediatrics · 2009Trial
- A novel method for measuring health care system performance: experience from QIDS in the Philippines.Health policy and planning · 2009Trial
- Effects of Health Insurance on Quality of Care in Low-Income Countries: A Systematic Review.Public health reviews · 2023Review
- Large-Scale Evaluation of Quality of Care in 6 Countries of Eastern Europe and Central Asia Using Clinical Performance and Value Vignettes.Global health, science and practice · 2017Article
- Do doctors under-provide, over-provide or do both? Exploring the quality of medical treatment in the Philippines.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2011Article
- Evidence of a causal link between health outcomes, insurance coverage, and a policy to expand access: experimental data from children in the Philippines.Health economics · 2011Article
- Pushing on a String: How policy might encourage private doctors to compete with the public sector on the basis of quality.Economics letters · 2011Article
- Evidence-informed health policy: are we beginning to get there at last?Health research policy and systems · 2009Article
- An evaluation of the cost-effectiveness of policy navigators to improve access to care for the poor in the Philippines.Health policy (Amsterdam, Netherlands) · 2009Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundRandomized trials have long been the gold-standard for evaluating clinical practice. There is growing recognition that rigorous studies are similarly needed to assess the effects of policy. However, these studies are rarely conducted. We report on the Quality Improvement Demonstration Study (QIDS), an example of a large randomized policy experiment, introduced and conducted in a scientific manner to evaluate the impact of large-scale governmental policy interventions.
methodsIn 1999 the Philippine government proposed sweeping reforms in the National Health Sector Reform Agenda. We recognized the unique opportunity to conduct a social experiment. Our ongoing goal has been to generate results that inform health policy. Early on we concentrated on developing a multi-institutional collaborative effort. The QIDS team then developed hypotheses that specifically evaluated the impact of two policy reforms on both the delivery of care and long-term health status in children. We formed an experimental design by randomizing matched blocks of three communities into one of the two policy interventions plus a control group. Based on the reform agenda, one arm of the experiment provided expanded insurance coverage for children; the other introduced performance-based payments to hospitals and physicians. Data were collected in household, hospital-based patient exit, and facility surveys, as well as clinical vignettes, which were used to assess physician practice. Delivery of services and health status were evaluated at baseline and after the interventions were put in place using difference-in-difference estimation.
resultsWe found and addressed numerous challenges conducting this study, namely: formalizing the experimental design using the existing health infrastructure; securing funding to do research coincident with the policy reforms; recognizing biases and designing the study to account for these; putting in place a broad data collection effort to account for unanticipated findings; introducing sustainable policy interventions based on the reform agenda; and providing results in real-time to policy makers through a combination of venues.
conclusionQIDS demonstrates that a large, prospective, randomized controlled policy experiment can be successfully implemented at a national level as part of sectoral reform. While we believe policy experiments should be used to generate evidence-based health policy, to do this requires opportunity and trust, strong collaborative relationships, and timing. This study nurtures the growing attitude that translation of scientific findings from the bedside to the community can be done successfully and that we should raise the bar on project evaluation and the policy-making process.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.