Concordance of care processes between medical records and patient self-administered questionnaires.

BACKGROUND: Despite the increasing use of medical records to measure quality of care, studies have shown that their validity is suboptimal. The objective of this study is to assess the concordance of cardiovascular care processes evaluated through medical record review and patient self-administered questionnaires (SAQs) using ten quality indicators (TRANSIT indicators). These indicators were developed as part of a participatory research program (TRANSIT study) dedicated to TRANSforming InTerprofessional clinical practices to improve cardiovascular disease (CVD) prevention in primary care. METHODS: For every patient participating in the TRANSIT study, the compliance to each indicator (individual scores) as well as the mean compliance to all indicators of a category (subscale scores) and to the complete set of ten indicators (overall scale score) were established. Concordance between results obtained using medical records and patient SAQs was assessed by prevalence-adjusted bias-adjusted kappa (PABAK) coefficients as well as intraclass correlation coefficients (ICCs) and 95% confidence intervals (95% CI). Generalized linear mixed models (GLMM) were used to identify patients' sociodemographic and clinical characteristics associated with agreement between the two data sources. RESULTS: The TRANSIT study was conducted in a primary care setting among patients (n = 759) with multimorbidity, at moderate (16%) and high risk (83%) of cardiovascular diseases. Quality of care, as measured by the TRANSIT indicators, varied substantially between medical records and patient SAQ. Concordance between the two data sources, as measured by ICCs (95% CI), was poor for the subscale (0.18 [0.08-0.27] to 0.46 [0.40-0.52]) and overall (0.46 [0.40-0.53]) compliance scale scores. GLMM showed that agreement was not affected by patients' characteristics. CONCLUSIONS: In quality improvement strategies, researchers must acknowledge that care processes may not be consistently recorded in medical records. They must also be aware that the evaluation of the quality of care may vary depending on the source of information, the clinician responsible of documenting the interventions, and the domain of care.

Lasso Regression for the Prediction of Intermediate Outcomes Related to Cardiovascular Disease Prevention Using the TRANSIT Quality Indicators.

BACKGROUND: Cardiovascular disease morbidity and mortality are largely influenced by poor control of hypertension, dyslipidemia, and diabetes. Process indicators are essential to monitor the effectiveness of quality improvement strategies. However, process indicators should be validated by demonstrating their ability to predict desirable outcomes. The objective of this study is to identify an effective method for building prediction models and to assess the predictive validity of the TRANSIT indicators. METHODS: On the basis of blood pressure readings and laboratory test results at baseline, the TRANSIT study population was divided into 3 overlapping subpopulations: uncontrolled hypertension, uncontrolled dyslipidemia, and uncontrolled diabetes. A classic statistical method, a sparse machine learning technique, and a hybrid method combining both were used to build prediction models for whether a patient reached therapeutic targets for hypertension, dyslipidemia, and diabetes. The final models' performance for predicting these intermediate outcomes was established using cross-validated area under the curves (cvAUC). RESULTS: At baseline, 320, 247, and 303 patients were uncontrolled for hypertension, dyslipidemia, and diabetes, respectively. Among the 3 techniques used to predict reaching therapeutic targets, the hybrid method had a better discriminative capacity (cvAUCs=0.73 for hypertension, 0.64 for dyslipidemia, and 0.79 for diabetes) and succeeded in identifying indicators with a better capacity for predicting intermediate outcomes related to cardiovascular disease prevention. CONCLUSIONS: Even though this study was conducted in a complex population of patients, a set of 5 process indicators were found to have good predictive validity based on the hybrid method.

Psychometric analysis of the TRANSIT quality indicators for cardiovascular disease prevention in primary care.

OBJECTIVE: To assess a selection of psychometric properties of the TRANSIT indicators. DESIGN: Using medical records, indicators were documented retrospectively during the 14 months preceding the end of the TRANSIT study. SETTING: Primary care in Quebec, Canada. PARTICIPANTS: Indicators were documented in a random subsample (n = 123 patients) of the TRANSIT study population (n = 759). INTERVENTIONS: For every patient, the mean compliance to all indicators of a category (subscale score) and to the complete set of indicators (overall scale score) were established. To evaluate test-retest and inter-rater reliabilities, indicators were applied twice, two months apart, by the same evaluator and independently by different evaluators, respectively. To evaluate convergent validity, correlations between TRANSIT indicators, Burge et al. indicators and Institut national d'excellence en santé et en services sociaux (INESSS) indicators were examined. MAIN OUTCOME MEASURES: Test-retest reliability, inter-rater reliability, and convergent validity. RESULTS: Test-retest reliability, as measured by intraclass correlation coefficients (ICCs) was equal to 0.99 (0.99-0.99) for the overall scale score while inter-rater reliability was equal to 0.95 (0.93-0.97) for the overall scale score. Convergent validity, as measured by Pearson's correlation coefficients, was equal to 0.77 (P < 0.001) for the overall scale score when the TRANSIT indicators were compared to Burge et al. indicators and to 0.82 (P < 0.001) for the overall scale score when the TRANSIT indicators were compared to INESSS indicators. CONCLUSIONS: Reliability was excellent except for eleven indicators while convergent validity was strong except for domains related to the management of CVD risk factors.