Improving outcomes for high-risk diabetics using information systems

J Am Board Fam Med. May-Jun 2007;20(3):245-51. doi: 10.3122/jabfm.2007.03.060185.

Abstract

Background: Diabetes care requires management of complex clinical information. We examine the relationship between diabetic outcomes and practices' use of information.

Methods: We performed a cross-sectional, secondary analysis of baseline data from 50 community primary care practices participating in a practice improvement project. Medical record review assessed clinical targets for diabetes (HbA(1c) < or =8, LDL < or =100, BP < or =130/85). Practices' use of information was derived from clinician responses to a survey on their use of clinical information systems for patient identification and tracking. Hierarchical linear modeling examined relationships between patient outcomes and practice use of information, controlling for patient level covariates (age, gender, hypertension, and cardiovascular comorbidities) and practice level covariates (solo/group, and electronic health record [EHR] presence).

Results: Practices' use of identification and tracking systems significantly (P < .007 and 0.002) increased odds of achieving diabetes care targets (odds ratio [OR] 1.23 95%, confidence interval [CI] 1.06 to 1.44, and OR 1.32 95% CI 1.11 to 1.59). For diabetic patients with hypertension, odds of hypertension control were higher with higher use of tracking systems (OR = 1.52, P = .0017) and reflected similar trend with higher use of identification systems (OR = 1.28, P = .1349). EHR presence was not associated with attainment of clinical targets.

Conclusions: Use of relatively simple systems to identify and track patient information can improve diabetic care outcomes. Practices making investments in an EHR must recognize that this technology alone is not sufficient for achieving desirable clinical outcomes. Researchers must explore the interrelationships of organizational factors necessary for successful information use.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Cross-Sectional Studies
  • Diabetes Mellitus / therapy*
  • Humans
  • Information Systems*
  • New Jersey
  • Pennsylvania
  • Quality of Health Care*
  • Risk Assessment
  • Treatment Outcome