The Quality Improvement Demonstration Study: An example of evidence-based policy-making in practice

<p>Abstract</p> <p>Background</p> <p>Randomized 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.</p> <p>Methods</p> <p>In 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.</p> <p>Results</p> <p>We 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.</p> <p>Conclusion</p> <p>QIDS 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.</p

Quality of care and health status in Ukraine

BACKGROUND: We conducted a national level assessment of the quality of clinical care practice in the Ukrainian healthcare system for two important causes of death and chronic disease conditions. We tested two hypotheses: a) quality of care is predicted by physician and facility characteristics and b) health status is predicted by quality of care. METHODS: During 2009–2010 in Ukraine, we collected nationally-representative data from clinical facilities, physicians, Clinical Performance and Value (CPV) vignettes, patient surveys from the facilities, and from the general population. Each physician completed a written CPV vignette—a simulated case scenario of a typical patient visit—for each of two clinical cases, congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD). CPV vignette scores, calculated as a percentage of all care criteria completed by the physician, were used as the measure of clinical quality of care. Self-reported health measures were collected from exit and household survey respondents. Regression models were developed to test the two study hypotheses. RESULTS: 136 hospitals and 125 polyclinics were surveyed; 1,044 physicians were interviewed and completed CPV vignettes. On average physicians scored 47.4% on the vignettes. Younger, female physicians provide a higher quality of care—as well as those that have had recent continuing medical education (CME) in chronic disease or health behaviors. Higher quality was associated with better health outcomes. CONCLUSIONS: As low- and middle-income countries around the world are challenged by non-communicable diseases, higher quality of care provided to these populations may result in better outcomes, such as improved health status and life expectancy, and overcome regional shortfalls. Policy efforts that serially evaluate quality may improve chronic disease care.Keywords: Ukraine, Health policy, Health care delivery, Eastern Europe, Non-communicable diseases, Quality of car

Predictive Modeling Techniques in Prostate Cancer

A number of new predictive modeling techniques have emerged in the past several years. These methods can be used independently or in combination with traditional modeling techniques to produce useful tools for the management of prostate cancer. Investigators should be aware of these techniques and avail themselves of their potentially useful properties. This review outlines selected predictive methods that can be used to develop models that may be useful to patients and clinicians for prostate cancer management.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63147/1/10915360152745812.pd

BMQ

BMQ: Boston Medical Quarterly was published from 1950-1966 by the Boston University School of Medicine and the Massachusetts Memorial Hospitals

Quality of care associated with number of cases seen and self-reports of clinical competence for Japanese physicians-in-training in internal medicine

BACKGROUND: The extent of clinical exposure needed to ensure quality care has not been well determined during internal medicine training. We aimed to determine the association between clinical exposure (number of cases seen), self- reports of clinical competence, and type of institution (predictor variables) and quality of care (outcome variable) as measured by clinical vignettes. METHODS: Cross-sectional study using univariate and multivariate linear analyses in 11 teaching hospitals in Japan. Participants were physicians-in-training in internal medicine departments. Main outcome measure was standardized t-scores (quality of care) derived from responses to five clinical vignettes. RESULTS: Of the 375 eligible participants, 263 (70.1%) completed the vignettes. Most were in their first (57.8%) and second year (28.5%) of training; on average, the participants were 1.8 years (range = 1–8) after graduation. Two thirds of the participants (68.8%) worked in university-affiliated teaching hospitals. The median number of cases seen was 210 (range = 10–11400). Greater exposure to cases (p = 0.0005), higher self-reports of clinical competence (p = 0.0095), and type of institution (p < 0.0001) were significantly associated with higher quality of care, using a multivariate linear model and adjusting for the remaining factors. Quality of care rapidly increased for the first 100 to 200 cases seen and tapered thereafter. CONCLUSION: The amount of clinical exposure and levels of self-reports of clinical competence, not years after graduation, were positively associated with quality of care, adjusting for the remaining factors. The learning curve tapered after about 200 cases

Underutilization of Social Insurance among the Poor: Evidence from the Philippines

Many developing countries promote social health insurance as a means to eliminate unmet health needs. However, this strategy may be ineffective if there are barriers to fully utilizing insurance.We analyzed the utilization of social health insurance in 30 hospital districts in the central regions of the Philippines between 2003 and 2007. Data for the study came from the Quality Improvement Demonstration Study (QIDS) and included detailed patient information from exit interviews of children under 5 years of age conducted in seven waves among public hospital districts located in the four central regions of the Philippines. These data were used to estimate and identify predictors of underutilization of insurance benefits--defined as the likelihood of not filing claims despite having legitimate insurance coverage--using logistic regression.Multivariate analyses using QIDS data from 2004 to 2007 reveal that underutilization averaged about 15% throughout the study period. Underutilization, however, declined over time. Among insured hospitalized children, increasing length of stay in the hospital and mother's education, were associated with less underutilization. Being in a QIDS intervention site was also associated with less underutilization and partially accounts for the downward trend in underutilization over time.The surprisingly high level of insurance underutilization by insured patients in the QIDS sites undermines the potentially positive impact of social health insurance on the health of the marginalized. In the Philippines, where the largest burden of health care spending falls on households, underutilization suggests ineffective distribution of public funds, failing to reach a significant proportion of households which are by and large poor. Interventions that improve benefit awareness may combat the problem of underutilization and should be the focus of further research in this area

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Maternal predictors of infant health outcomes among Hawaiians.

Disaggregated data, vital statistics, and a comprehensive literature review were used to assess the relationship between Hawaiian maternal predictors and infant health outcomes. Despite near universal health care coverage, Hawaiians continue to use less prenatal care, have average rates of low birth weight and the highest infant mortality rates compared to other ethnic groups in Hawaii. Specific investigations and interventions are necessary to reduce the disparity of Hawaiian infant health outcomes