Validating and Improving Adjusted Clinical Group's Future Hospitalization and High-Cost Prediction Models for Dutch Primary Care

Population Health Management, vol. 26, pp. 430–437

Abstract

The rise in health care costs, caused by older and more complex patient populations, requires Population Health Management approaches including risk stratification. With risk stratification, patients are assigned individual risk scores based on medical records. These patient stratifications focus on future high costs and expensive care utilization such as hospitalization, for which different models exist. With this study, the research team validated the accuracy of risk prediction scores for future hospitalization and high health care costs, calculated by the Adjusted Clinical Group (ACG)'s risk stratification models, using Dutch primary health care data registries. In addition, they aimed to adjust the US-based predictive models for Dutch primary care. The statistical validity of the existing models was assessed. In addition, the underlying prediction models were trained on 95,262 patients' data from de Zoetermeer region and externally validated on data of 48,780 patients from Zeist, Nijkerk, and Urk. Information on age, sex, number of general practitioner visits, International Classification of Primary Care coded information on the diagnosis and Anatomical Therapeutic Chemical Classification coded information on the prescribed medications, were incorporated in the model. C-statistics were used to validate the discriminatory ability of the models. Calibrating ability was assessed by visual inspection of calibration plots. Adjustment of the hospitalization model based on Dutch data improved C-statistics from 0.69 to 0.75, whereas adjustment of the high-cost model improved C-statistics from 0.78 to 0.85, indicating good discrimination of the models. The models also showed good calibration. In conclusion, the local adjustments of the ACG prediction models show great potential for use in Dutch primary care.

Authors 5

1. Shelley‐Ann M. Girwar corresponding Aachen Department of Public Health and Primary Care

   Leiden University Medical Center

   Affiliation as printed

   Department of Public Health and Primary Care, Health Campus The Hague, Leiden University Medical Center, The Hague, The Netherlands

2. Marta F. Fiocco Aachen Mathematical Institute Medical Statistics Department of Biomedical Data Science

   Leiden University · Leiden University Medical Center · Princess Máxima Center

   Affiliation as printed

   Mathematical Institute, Leiden University, Leiden, The Netherlands

   Medical Statistics Department of Biomedical Data Science, Leiden University Medical Center, Leiden, The Netherlands

   Trial and Data Center, Princess Maxima Center for Pediatric Oncology, Utrecht, The Netherlands

3. Stephen P. Sutch Aachen Department of Public Health and Primary Care

   Johns Hopkins University · Leiden University Medical Center

   Affiliation as printed

   Department of Health Policy and Management, Bloomberg School of Public Health Johns Hopkins University, Baltimore Maryland, USA

   Department of Public Health and Primary Care, Health Campus The Hague, Leiden University Medical Center, The Hague, The Netherlands

4. Mattijs Everard Numans Aachen Department of Public Health and Primary Care

   Leiden University Medical Center

   Affiliation as printed

   Department of Public Health and Primary Care, Health Campus The Hague, Leiden University Medical Center, The Hague, The Netherlands

5. Marc Abraham Bruijnzeels Aachen Department of Public Health and Primary Care

   Leiden University Medical Center

   Affiliation as printed

   Department of Public Health and Primary Care, Health Campus The Hague, Leiden University Medical Center, The Hague, The Netherlands

   Jan van Es Instituut, Ede, The Netherlands