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Diabetes care quality is highly correlated with patient panel characteristics.

ABSTRACT: INTRODUCTION:Health care reimbursement is increasingly based on quality. Little is known about how clinic-level patient characteristics affect quality, particularly in community health centers (CHCs). METHODS:Using data from electronic health records for 4019 diabetic patients from 23 primary care CHCs in the OCHIN practice-based research network, we calculated correlations between a clinic's patient panel characteristics and rates of delivery of diabetes preventive services in 2007. Using regression models, we estimated the proportion of variability in clinics' preventive services rates associated with the variability in the clinics' patient panel characteristics. We also explored whether clinics' performance rates were affected by how patient panel denominators were defined. RESULTS:Clinic rates of hemoglobin testing, influenza immunizations, and lipid screening were positively associated with the percentage of patients with continuous health insurance coverage and negatively associated with the percentage of uninsured patients. Microalbumin screening rates were positively associated with the percentage of racial minorities in a clinic's panel. Associations remained consistent with different panel denominators. CONCLUSIONS:Clinic variability in delivery rates of preventive services correlates with differences in clinics' patient panel characteristics, particularly the percentage of patients with continuous insurance coverage. Quality scores that do not account for these differences could create disincentives to clinics providing diabetes care for vulnerable patients.

SUBMITTER: Bailey SR

PROVIDER: S-EPMC3922763 | biostudies-literature | 2013 Nov-Dec

REPOSITORIES: biostudies-literature

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Diabetes care quality is highly correlated with patient panel characteristics.

Bailey Steffani R SR O'Malley Jean P JP Gold Rachel R Heintzman John J Likumahuwa Sonja S DeVoe Jennifer E JE

Journal of the American Board of Family Medicine : JABFM 20131101 6

<h4>Introduction</h4>Health care reimbursement is increasingly based on quality. Little is known about how clinic-level patient characteristics affect quality, particularly in community health centers (CHCs).<h4>Methods</h4>Using data from electronic health records for 4019 diabetic patients from 23 primary care CHCs in the OCHIN practice-based research network, we calculated correlations between a clinic's patient panel characteristics and rates of delivery of diabetes preventive services in 20 ...[more]

PMID: 24204063

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Project description:BackgroundThe United States lacks a timely and accurate nationwide surveillance system for acute ischemic stroke (AIS). We use the Get With The Guidelines-Stroke registry to apply poststratification survey weights to generate national assessment of AIS epidemiology, hospital care quality, and in-hospital outcomes.MethodsClinical data from the Get With The Guidelines-Stroke registry were weighted using a Bayesian interpolation method anchored to observations from the national inpatient sample. To generate a US stroke forecast for 2019, we linearized time trend estimates from the national inpatient sample to project anticipated AIS hospital volume, distribution, and race/ethnicity characteristics for the year 2019. Primary measures of AIS epidemiology and clinical care included patient and hospital characteristics, stroke severity, vital and laboratory measures, treatment interventions, performance measures, disposition, and clinical outcomes at discharge.ResultsWe estimate 552 476 patients with AIS were admitted in 2019 to US hospitals. Median age was 71 (interquartile range, 60-81), 48.8% female. Atrial fibrillation was diagnosed in 22.6%, 30.2% had prior stroke/transient ischemic attack, and 36.4% had diabetes. At baseline, 46.4% of patients with AIS were taking antiplatelet agents, 19.2% anticoagulants, and 46.3% cholesterol-reducers. Mortality was 4.4%, and only 52.3% were able to ambulate independently at discharge. Performance nationally on AIS achievement measures were generally higher than 95% for all measures but the use of thrombolytics within 3 hours of early stroke presentations (81.9%). Additional quality measures had lower rates of receipt: dysphagia screening (84.9%), early thrombolytics by 4.5 hours (79.7%), and statin therapy (80.6%).ConclusionsWe provide timely, reliable, and actionable US national AIS surveillance using Bayesian interpolation poststratification weights. These data may facilitate more targeted quality improvement efforts, resource allocation, and national policies to improve AIS care and outcomes.

Project description:BackgroundAccounting for justifiable variance is important for fair comparisons of treatment quality. The variance between general practices in treatment quality of type 2 diabetes (T2DM) patients may be attributed to the underlying patient population and practice characteristics. The objective of this study is to describe the between practice differences in treatment, and identify patient and practice level characteristics that may explain these differences.MethodsThe data of 24,607 T2DM patients from 183 general practices in the Netherlands were used. Treatment variance was assessed in a cross-sectional manner for: glucose-lowering drugs/metformin, lipid-lowering drugs/statins, blood pressure-lowering drugs/ACE-inhibitor or ARB. Patient characteristics tested were age, gender, diabetes duration, comorbidity, comedication. Practice characteristics were number of T2DM patients, practice type, diabetes assistant available. Multilevel logistic regression was used to examine the between practice variance in treatment and the effect of characteristics on this variance.ResultsTreatment rates varied considerably between practices (IQR 9.5-13.9). The variance at practice level was 7.5% for glucose-lowering drugs, 3.6% for metformin, 3.1% for lipid-lowering drugs, 10.3% for statins, 8.6% for blood pressure-lowering drugs, and 3.9% for ACE-inhibitor/ARB. Patient and practice characteristics explained 19.0%, 7.5%, 20%, 6%, 9.9%, and 13.4% of the variance respectively. Age, multiple chronic drugs, and ≥3 glucose-lowering drugs were the most relevant patient characteristics. Number of T2DM patients per practice was the most relevant practice characteristic.DiscussionConsiderable differences exist between practices in treatment rates. Patients' age was identified as characteristic that may account for justifiable differences in especially lipid-lowering treatment. Other patient or practice characteristics either do not explain or do not justify the differences.

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Diabetes care quality is highly correlated with patient panel characteristics.

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Diabetes care quality is highly correlated with patient panel characteristics.

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