Using Propensity Score Matching Technique to Estimate Utilization and Costs of General Practitioners’ Services associated with Alzheimer’s Disease

Objective: General practitioners (GPs) play an important role in caring for people with Alzheimer’s disease (AD). However, the cost and the extent of service utilization from GPs due to AD patients are difficult to assess. This study aimed to explore the principles of propensity score matching (PSM) technique to assess the additional GP service use and cost imposed by AD in persons aged ≥60 years in Denmark. Design: PSM was used to estimate the additional use and cost of GP services attributable to AD. Case and control baseline characteristics were compared with and without the application of PSM. Propensity scores were then estimated using the generalized boosted model, a multivariate, nonparametric and automated algorithm technique. Setting: Observational data from Statistics Denmark registry. Subjects: 3368 cases and 3368 controls; cases with AD were defined as patients with diagnoses G30 and F00 and/or those with primary care prescriptions for anti-AD drugs from the years 2004 until 2009. Main Outcome Measures: GP service utilisation and costs attributable to AD. Results: PSM brought a large improvement to the balance of observed covariates among the cases and control groups. AD patients received around 20% more GP services and utilized services that cost 15% more than non-AD controls during a calendar year. Conclusion: AD patients utilize more GP services and incur higher costs as compared to their matched controls. The PSM technique can be an effective tool to reduce imbalance of observable confounders from register based data and improve the estimations.