Towards actionable international comparisons of health system performance: expert revision of the OECD framework and quality indicators

Objective To review and update the conceptual framework, indicator content and research priorities of the Organisation for Economic Cooperation and Development's (OECD) Health Care Quality Indicators (HCQI) project, after a decade of collaborative work. Design A structured assessment was carried out using a modified Delphi approach, followed by a consensus meeting, to assess the suite of HCQI for international comparisons, agree on revisions to the original framework and set priorities for research and development. Setting International group of countries participating to OECD projects. Participants Members of the OECD HCQI expert group. Results A reference matrix, based on a revised performance framework, was used to map and assess all seventy HCQI routinely calculated by the OECD expert group. A total of 21 indicators were agreed to be excluded, due to the following concerns: (i) relevance, (ii) international comparability, particularly where heterogeneous coding practices might induce bias, (iii) feasibility, when the number of countries able to report was limited and the added value did not justify sustained effort and (iv) actionability, for indicators that were unlikely to improve on the basis of targeted policy interventions. Conclusions The revised OECD framework for HCQI represents a new milestone of a long-standing international collaboration among a group of countries committed to building common ground for performance measurement. The expert group believes that the continuation of this work is paramount to provide decision makers with a validated toolbox to directly act on quality improvement strategie

SCORE2-Diabetes: 10-year cardiovascular risk estimation in type 2 diabetes in Europe

Aims: To develop and validate a recalibrated prediction model (SCORE2-Diabetes) to estimate the 10-year risk of cardiovascular disease (CVD) in individuals with type 2 diabetes in Europe. Methods and results: SCORE2-Diabetes was developed by extending SCORE2 algorithms using individual-participant data from four large-scale datasets comprising 229 460 participants (43 706 CVD events) with type 2 diabetes and without previous CVD. Sex-specific competing risk-adjusted models were used including conventional risk factors (i.e. age, smoking, systolic blood pressure, total, and HDL-cholesterol), as well as diabetes-related variables (i.e. age at diabetes diagnosis, glycated haemoglobin [HbA1c] and creatinine-based estimated glomerular filtration rate [eGFR]). Models were recalibrated to CVD incidence in four European risk regions. External validation included 217 036 further individuals (38 602 CVD events), and showed good discrimination, and improvement over SCORE2 (C-index change from 0.009 to 0.031). Regional calibration was satisfactory. SCORE2-Diabetes risk predictions varied several-fold, depending on individuals' levels of diabetes-related factors. For example, in the moderate-risk region, the estimated 10-year CVD risk was 11% for a 60-year-old man, non-smoker, with type 2 diabetes, average conventional risk factors, HbA1c of 50 mmol/mol, eGFR of 90 mL/min/1.73 m2, and age at diabetes diagnosis of 60 years. By contrast, the estimated risk was 17% in a similar man, with HbA1c of 70 mmol/mol, eGFR of 60 mL/min/1.73 m2, and age at diabetes diagnosis of 50 years. For a woman with the same characteristics, the risk was 8% and 13%, respectively. Conclusion: SCORE2-Diabetes, a new algorithm developed, calibrated, and validated to predict 10-year risk of CVD in individuals with type 2 diabetes, enhances identification of individuals at higher risk of developing CVD across Europe

Measuring the quality of care in small countries: the empirical analysis of 30-day mortality following acute myocardial infarction and ischaemic stroke in Latvia

The evaluation of quality of care is a complex task that, over the last decades, has been performed using the Donabedian model as its main conceptual framework. Small countries are an ideal setting in which to make innovative, empirical evaluations of the quality of care. In this research, we discussed the challenges and opportunities of assessing hospital performance in Latvia, a small country in the Baltic region of Northern Europe. The study outcomes were 30-day acute myocardial infarction mortality and 30-day ischaemic stroke mortality. We described how indicator specifications, risk-adjustment, data reliability assessment and graphical representations were tailored to the geographic and institutional context of Latvia. By looking at the impact of structural characteristics on hospital performance, we found that cath labs and large caseloads were significantly associated with lower mortality. This approach allows decision-makers at different governance levels to design and implement actions aimed at improving the quality of care. At the health system level, it may help policy-makers adopt proper strategies to tackle poor outcomes; at the hospital level, it may help managers intervene on structural determinants of performance. Because small countries face some relevant issues that have implications for health care, these analyses might be relevant also for larger countries to improve the design of their health-care service

Measuring the quality of care in small countries: the empirical analysis of 30-day mortality following acute myocardial infarction and ischaemic stroke in Latvia

The evaluation of quality of care is a complex task that, over the last decades, has been performed using the Donabedian model as its main conceptual framework. Small countries are an ideal setting in which to make innovative, empirical evaluations of the quality of care. In this research, we discussed the challenges and opportunities of assessing hospital performance in Latvia, a small country in the Baltic region of Northern Europe. The study outcomes were 30-day acute myocardial infarction mortality and 30-day ischaemic stroke mortality. We described how indicator specifications, risk-adjustment, data reliability assessment and graphical representations were tailored to the geographic and institutional context of Latvia. By looking at the impact of structural characteristics on hospital performance, we found that cath labs and large caseloads were significantly associated with lower mortality. This approach allows decision-makers at different governance levels to design and implement actions aimed at improving the quality of care. At the health system level, it may help policy-makers adopt proper strategies to tackle poor outcomes; at the hospital level, it may help managers intervene on structural determinants of performance. Because small countries face some relevant issues that have implications for health care, these analyses might be relevant also for larger countries to improve the design of their health-care service

SCORE2-diabetes : 10-year cardiovascular risk estimation in type 2 diabetes in Europe

Aims To develop and validate a recalibrated prediction model (SCORE2-Diabetes) to estimate the 10-year risk of cardiovascular disease (CVD) in individuals with type 2 diabetes in Europe. Methods and results SCORE2-Diabetes was developed by extending SCORE2 algorithms using individual-participant data from four large-scale datasets comprising 229 460 participants (43 706 CVD events) with type 2 diabetes and without previous CVD. Sex-specific competing risk-adjusted models were used including conventional risk factors (i.e. age, smoking, systolic blood pressure, total, and HDL-cholesterol), as well as diabetes-related variables (i.e. age at diabetes diagnosis, glycated haemoglobin [HbA1c] and creatinine-based estimated glomerular filtration rate [eGFR]). Models were recalibrated to CVD incidence in four European risk regions. External validation included 217 036 further individuals (38 602 CVD events), and showed good discrimination, and improvement over SCORE2 (C-index change from 0.009 to 0.031). Regional calibration was satisfactory. SCORE2-Diabetes risk predictions varied several-fold, depending on individuals' levels of diabetes-related factors. For example, in the moderate-risk region, the estimated 10-year CVD risk was 11% for a 60-year-old man, non-smoker, with type 2 diabetes, average conventional risk factors, HbA1c of 50 mmol/mol, eGFR of 90 mL/min/1.73 m(2), and age at diabetes diagnosis of 60 years. By contrast, the estimated risk was 17% in a similar man, with HbA1c of 70 mmol/mol, eGFR of 60 mL/min/1.73 m(2), and age at diabetes diagnosis of 50 years. For a woman with the same characteristics, the risk was 8% and 13%, respectively. Conclusion SCORE2-Diabetes, a new algorithm developed, calibrated, and validated to predict 10-year risk of CVD in individuals with type 2 diabetes, enhances identification of individuals at higher risk of developing CVD across Europe