title: Time-to-event methodology improved statistical evaluation in register-based health services research.
abstract: OBJECTIVE
  Complex longitudinal sampling and the observational structure of patient registers in health services research are associated with methodological challenges regarding data management and statistical evaluation. We exemplify common pitfalls and want to stimulate discussions on the design, development, and deployment of future longitudinal patient registers and register-based studies.
  
  
  METHODS
  For illustrative purposes, we use data from the prospective, observational, German DIabetes Versorgungs-Evaluation register. One aim was to explore predictors for the initiation of a basal insulin supported therapy in patients with type 2 diabetes initially prescribed to glucose-lowering drugs alone.
  
  
  RESULTS
  Major challenges are missing mortality information, time-dependent outcomes, delayed study entries, different follow-up times, and competing events. We show that time-to-event methodology is a valuable tool for improved statistical evaluation of register data and should be preferred to simple case-control approaches.
  
  
  CONCLUSIONS
  Patient registers provide rich data sources for health services research. Analyses are accompanied with the trade-off between data availability, clinical plausibility, and statistical feasibility. Cox' proportional hazards model allows for the evaluation of the outcome-specific hazards, but prediction of outcome probabilities is compromised by missing mortality information.
authors.affiliation: Institute of Statistics, Ulm University, Helmholtzstrasse 20, 89081 Ulm, Germany. Electronic address: tobias.bluhmki@uni-ulm.de.
authors.forename: Tobias
authors.initials: T
authors.lastname: Bluhmki
authors.affiliation: Institute for Pharmacology and Preventive Medicine, Menzelstrasse 21, 15831 Mahlow, Germany.
authors.forename: Peter
authors.initials: P
authors.lastname: Bramlage
authors.affiliation: axaris software & systeme GmbH, Max-Eyth-Weg 2, 89160 Dornstadt, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Volk
authors.affiliation: Gemeinschaftspraxis Kaltheuner-v. Boxberg, Kalkstraße 117, 51377 Leverkusen, Germany; winDiab GmbH, Kehler Strasse 24, 40468 Düsseldorf, Germany.
authors.forename: Matthias
authors.initials: M
authors.lastname: Kaltheuner
authors.affiliation: Children's and Youth Hospital "Auf der Bult", Janusz-Korczak-Allee 12, 30173 Hannover, Germany.
authors.forename: Thomas
authors.initials: T
authors.lastname: Danne
authors.affiliation: Institute for Biometrics and Epidemiology, German Diabetes Center (DDZ) Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Rathmann
authors.affiliation: Institute of Statistics, Ulm University, Helmholtzstrasse 20, 89081 Ulm, Germany.
authors.forename: Jan
authors.initials: J
authors.lastname: Beyersmann
mesh_terms: D003920:Diabetes Mellitus / Q000188:drug therapy*; D005858:Germany; D006302:Health Services Research / Q000379:methods* / Q000706:statistics & numerical data*; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use*; D008137:Longitudinal Studies; D011446:Prospective Studies; D012042:Registries / Q000706:statistics & numerical data*; D013995:Time; D016896:Treatment Outcome
chemical_list: D007004:Hypoglycemic Agents
keywords: Diabetes mellitus; Health services research; Longitudinal study; Mortality; Registers; Survival analysis