Abstract
BackgroundWithin the Dutch health care system the focus is shifting from a disease oriented approach to a more population based approach. Since every inhabitant in the Netherlands is registered with one general practice, this offers a unique possibility to perform Population Health Management analyses based on general practitioners’ (GP) registries. The Johns Hopkins Adjusted Clinical Groups (ACG) System is an internationally used method for predictive population analyses. The model categorizes individuals based on their complete health profile, taking into account age, gender, diagnoses and medication. However, the ACG system was developed with non-Dutch data. Consequently, for wider implementation in Dutch general practice, the system needs to be validated in the Dutch healthcare setting. In this paper we show the results of the first use of the ACG system on Dutch GP data. The aim of this study is to explore how well the ACG system can distinguish between different levels of GP healthcare utilization.MethodsTo reach our aim, two variables of the ACG System, the Aggregated Diagnosis Groups (ADG) and the mutually exclusive ACG categories were explored. The population for this pilot analysis consisted of 23,618 persons listed with five participating general practices within one region in the Netherlands. ACG analyses were performed based on historical Electronic Health Records data from 2014 consisting of primary care diagnoses and pharmaceutical data. Logistic regression models were estimated and AUC’s were calculated to explore the diagnostic value of the models including ACGs and ADGs separately with GP healthcare utilization as the dependent variable. The dependent variable was categorized using four different cut-off points: zero, one, two and three visits per year.ResultsThe ACG and ADG models performed as well as models using International Classification of Primary Care chapters, regarding the association with GP utilization. AUC values were between 0.79 and 0.85. These models performed better than the base model (age and gender only) which showed AUC values between 0.64 and 0.71.ConclusionThe results of this study show that the ACG system is a useful tool to stratify Dutch primary care populations with GP healthcare utilization as the outcome variable.
Highlights
Within the Dutch health care system the focus is shifting from a disease oriented approach to a more population based approach
Prescribed medication was registered as Anatomical Therapeutic Chemical (ATC) codes [12], general practitioners’ (GP) visits were defined as all GP encounters, including physical and telephone consults and home visits by either GPs or nurse practitioners working at the GP practices
With respect to model performance, results showed that distinctions between the different levels of GP healthcare utilization can be made with the Adjusted Clinical Groups (ACG) system
Summary
Within the Dutch health care system the focus is shifting from a disease oriented approach to a more population based approach. With the upcoming need for improved organization and management of healthcare and the increasing possibilities of big data, strategies based on health registry analyses are becoming popular. One use of health registry data in population health management strategies is risk stratification. With rising pressure on medical services provided by general practitioners (GPs) in most European countries [1], primary care can benefit from proven advantages of risk stratification approaches, such as improved care management [2], resource allocation [3] and identification of sub-populations for tailored care interventions [4]. Risk stratification approaches using Dutch GP registry data can be especially beneficial due to the gatekeeper’s function of Dutch GPs, providing the opportunity to overview a near total population
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