Validity of the Updated Rx-Risk Index as a Disease Identification and Risk-Adjustment Tool for Use in Observational Health Studies - Widagdo I; Kerr M; Kalisch Ellett L; Schlegel C; Sadeqzadeh E; Wang A; Clarke AL; Pratt N (Clinical Interventions in Aging)
Imaina Widagdo,1 Mhairi Kerr,1 Lisa Kalisch Ellett,1 Clement Schlegel,2 Elham Sadeqzadeh,2 Alvin Wang,2 Allison Louise Clarke,2 Nicole Pratt1 1Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia; 2Data and Analytics Branch, Health Economics and Research Division, Department of Health and Aged Care, Canberra, Australian Capital Territory, AustraliaCorrespondence: Imaina Widagdo, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia, Email imaina.widagdo@unisa.edu.auPurpose: Identifying patient health conditions in observational studies is essential for accurately measuring healthcare practices and planning effective health policy interventions. This analysis evaluates the validity of the Rx-Risk Index, a tool that uses medication dispensing data to identify patient comorbidities and measure overall health. We examined an updated version of the Rx-Risk Index, reflecting changes in treatment practices, to assess its validity as a tool for identifying specific health conditions and as a measure of overall health to aid in risk adjustment in observational studies.Patients and Methods: We conducted a validation study using two Australian linked health datasets, the Person-Level Integrated Data Asset (PLIDA) and the National Health Data Hub (NHDH), from 2010 to 2018, focusing on individuals aged 65 years or older. The sensitivity, specificity, PPV/NPV, Cohen’s kappa, and F1 scores were used to assess agreement between Rx-Risk Index conditions and two reference standards: patient self-reported conditions and hospital diagnosis. The Rx-Risk Index’s predictive validity for one-year mortality was also evaluated using logistic regression, with model fit assessed by AIC and c-statistic.Results: Data were analysed from 3,959 individuals in PLIDA and 157,709 individuals in NHDH. The Rx-Risk Index showed high sensitivity (≥ 75%) for diabetes, chronic airways disease, hyperlipidemia, and epilepsy against both self-reported conditions and hospital diagnoses. However, hyperlipidemia and hypertension showed lower specificity (< 70%). High PPVs (≥ 78%) were observed for diabetes and renal failure. The agreement between the Rx-Risk Index and self-reported conditions was stronger (Cohen’s kappa: 0.41– 0.81 for 7 conditions) than between Rx-Risk Index and ICD10-AM diagnoses (kappa: 0.73 for one condition). The Rx-Risk Index was a strong predictor of one-year mortality, with c-statistic of 0.820 (95% CI: 0.817– 0.825).Conclusion: Selected Rx-Risk Index conditions are reasonable proxies for identifying specific conditions, particularly those requiring pharmacological management. The Rx-Risk Index was a strong predictor of one-year mortality, suggesting it is a valid measure of overall health. This study demonstrates the Rx-Risk Index’s potential to enhance disease classification and risk adjustment in observational studies, supporting informed decision-making in health policy planning.Plain language summary: Administrative health claims data are increasingly accessible and play a crucial role in public health research. However, these data often lack detailed information about individual health conditions. Accurately identifying a patient’s health condition, or comorbidities, is essential for ensuring healthcare safety, quality, effective policy planning, and evaluation. This study evaluated a tool called the Rx-Risk Index, which uses prescription data to identify health conditions and adjust for health risks in epidemiological analysis. We have updated the list of medicines and conditions included in this tool to ensure alignment with evolving treatment practices.Researchers used data from two large Australian health databases for people aged 65 and older to test the Rx-Risk Index. They compared the conditions identified by this tool to patient reports and hospital records. The Rx-Risk Index was effective at identifying conditions like diabetes and chronic airways disease, which have specific medication treatments. However, it was less accurate for high blood pressure, as medications for this condition can be used to treat various other conditions. Despite this limitation, the Rx-Risk Index was a strong predictor of whether someone might die within a year.Overall, the Rx-Risk Index is a valuable tool for identifying certain health conditions, especially those requiring specific medications, and for adjusting health risks in epidemiological research. However, its accuracy varies by condition, and it may need adjustments for use in countries with different medication practices.Keywords: prescription claims data, disease classification, risk adjustment, predictive validity, observational study, pharmacoepidemiology