title: Comparison of physician referral and insurance claims data-based risk prediction as approaches to identify patients for care management in primary care: an observational study.
abstract: BACKGROUND
  Primary care-based care management (CM) could reduce hospital admissions in high-risk patients. Identification of patients most likely to benefit is needed as resources for CM are limited. This study aimed to compare hospitalization and mortality rates of patients identified for CM either by treating primary care physicians (PCPs) or predictive modelling software for hospitalization risk (PM).
  
  
  METHODS
  In 2009, a cohort of 6,026 beneficiaries of a German statutory health insurance served as a sample for patient identification for CM by PCPs or commercial PM (CSSG 0.8, Verisk Health). The resulting samples were compared regarding hospitalization and mortality rates in 2010 and in the two year period before patient selection. No CM-intervention was delivered until the end of 2010 and PCPs were blinded for the assessment of hospitalization rates.
  
  
  RESULTS
  In 2010, hospitalization rates of PM-identified patients were 80% higher compared to PCP-identified patients. Mortality rates were also 8% higher in PM-identified patients if compared to PCP-identified patients (10% vs. 2%). The hospitalization rate of patients independently identified by both PM and PCPs was numerically between PM- and PCP-identified patients. Time trend between 2007 and 2010 showed decreasing hospitalization rates in PM-identified patients (-15% per year) compared to increasing rates in PCP-identified patients (+34% per year).
  
  
  CONCLUSIONS
  PM identified patients with higher hospitalization and mortality rates compared to PCP-referred patients. But the latter showed increasing hospitalization rates over time thereby suggesting that PCPs may be able to predict future deterioration in patients with relatively good current health status. These patients may most likely benefit from preventive services like CM.
authors.affiliation: Department of General Practice and Health Services Research, University Hospital Heidelberg, Vossstrasse 2, D-69115 Heidelberg, Germany. tobias.freund@med.uni-heidelberg.de.
authors.forename: Tobias
authors.initials: T
authors.lastname: Freund
authors.forename: Matthias
authors.initials: M
authors.lastname: Gondan
authors.forename: Justine
authors.initials: J
authors.lastname: Rochon
authors.forename: Frank
authors.initials: F
authors.lastname: Peters-Klimm
authors.forename: Stephen
authors.initials: S
authors.lastname: Campbell
authors.forename: Michel
authors.initials: M
authors.lastname: Wensing
authors.forename: Joachim
authors.initials: J
authors.lastname: Szecsenyi
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019090:Case Management; D015331:Cohort Studies; D015897:Comorbidity; D016208:Databases, Factual; D003661:Decision Support Techniques; D019468:Disease Management; D005260:Female; D005858:Germany; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007348:Insurance, Health / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009026:Mortality; D018579:Patient Selection; D011320:Primary Health Care / Q000379:methods*; D012017:Referral and Consultation; D018570:Risk Assessment / Q000379:methods; D013997:Time Factors