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Developing and validating a diabetes database in a large health system.

Janice C Zgibor1, Trevor J Orchard, Melissa Saul

  • 1University of Pittsburgh, Department of Epidemiology, Graduate School of Public Health, Pittsburgh, United States. zgiborj@upmc.edu

Diabetes Research and Clinical Practice
|August 29, 2006
PubMed
Summary
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Creating a diabetes patient registry using multiple data points, including outpatient diagnosis, effectively identifies a large, diverse patient population for quality improvement initiatives.

Area of Science:

  • Health Informatics
  • Clinical Information Systems
  • Population Health Management

Background:

  • Patient registries are crucial components of clinical information systems for identifying care gaps and driving quality improvement.
  • Existing registries often rely on specific selection criteria (e.g., insurer membership), limiting their representation of demographically diverse populations.
  • Data on registries for heterogeneous populations are scarce.

Purpose of the Study:

  • To develop and validate methods for identifying a large, unselective diabetes patient database from administrative and clinical data.
  • To assess the effectiveness of various criteria for inclusion in a diabetes registry.
  • To establish a foundation for tracking processes and outcomes in a demographically diverse diabetes patient population.

Main Methods:

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  • Utilized administrative and clinical data from 2000-2003, encompassing over 46 million lab reports and 233 million medical records for approximately 2 million unique patients.
  • Identified the diabetes source population using criteria such as ICD-9 code 250, hemoglobin A1c results, blood glucose levels >200mg/dl, or diabetes medication.
  • Validated diagnostic criteria through trained chart reviewers and analyzed single indicators versus combinations to optimize patient identification.

Main Results:

  • Using two or more indicators or an outpatient diagnosis achieved high positive predictive value (96-97%) and sensitivity (99-100%), identifying 55,807 individuals.
  • Including patients with a single outpatient diagnosis (PPV 94-95%) alongside those with multiple indicators expanded the final sample size to 65,725.
  • Demonstrated that a combination of criteria effectively captures a substantial and representative diabetes patient cohort.

Conclusions:

  • The combination of two or more indicators or an outpatient diagnosis is an effective strategy for creating a sizeable and unselective diabetes patient database.
  • This approach enables robust tracking of processes and outcomes for a broad diabetes patient population.
  • The findings support the use of such registries for quality improvement in diverse patient groups.