title: Diabetes and hypertension quality measurement in four safety-net sites: lessons learned after implementation of the same commercial electronic health record.
abstract: BACKGROUND
  In this new era after the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, the literature on lessons learned with electronic health record (EHR) implementation needs to be revisited.
  
  
  OBJECTIVE
  Our objective was to describe what implementation of a commercially available EHR with built-in quality query algorithms showed us about our care for diabetes and hypertension populations in four safety net clinics, specifically feasibility of data retrieval, measurements over time, quality of data, and how our teams used this data.
  
  
  METHODS
  A cross-sectional study was conducted from October 2008 to October 2012 in four safety-net clinics located in the Midwest and Western United States. A data warehouse that stores data from across the U.S was utilized for data extraction from patients with diabetes or hypertension diagnoses and at least two office visits per year. Standard quality measures were collected over a period of two to four years. All sites were engaged in a partnership model with the IT staff and a shared learning process to enhance the use of the quality metrics.
  
  
  RESULTS
  While use of the algorithms was feasible across sites, challenges occurred when attempting to use the query results for research purposes. There was wide variation of both process and outcome results by individual centers. Composite calculations balanced out the differences seen in the individual measures. Despite using consistent quality definitions, the differences across centers had an impact on numerators and denominators. All sites agreed to a partnership model of EHR implementation, and each center utilized the available resources of the partnership for Center-specific quality initiatives.
  
  
  CONCLUSIONS
  Utilizing a shared EHR, a Regional Extension Center-like partnership model, and similar quality query algorithms allowed safety-net clinics to benchmark and improve the quality of care across differing patient populations and health care delivery models.
authors.affiliation: Wayne State University , Nursing, Detroit, Michigan, United States.
authors.forename: R
authors.initials: R
authors.lastname: Benkert
authors.affiliation: GLIDE , San Francisco, California, United States.
authors.forename: P
authors.initials: P
authors.lastname: Dennehy
authors.affiliation: Michigan Public Health Institute , Center for Data Management and Translational Research, Okemos, Michigan, United States.
authors.forename: J
authors.initials: J
authors.lastname: White
authors.affiliation: Alliance of Chicago Community Health Services , Clinical Informatics, Chicago, Illinois, United States.
authors.forename: A
authors.initials: A
authors.lastname: Hamilton
authors.affiliation: Michigan Public Health Institute , Center for Data Management and Translational Research, Okemos, Michigan, United States.
authors.forename: C
authors.initials: C
authors.lastname: Tanner
authors.affiliation: The University of Michigan , School of Nursing, Ann Arbor, Michigan, United States.
authors.forename: J M
authors.initials: JM
authors.lastname: Pohl
mesh_terms: D003920:Diabetes Mellitus / Q000175:diagnosis / Q000453:epidemiology* / Q000628:therapy; D057286:Electronic Health Records / Q000592:standards* / Q000706:statistics & numerical data*; D019983:Guideline Adherence / Q000706:statistics & numerical data; D006801:Humans; D006973:Hypertension / Q000175:diagnosis / Q000453:epidemiology* / Q000628:therapy; D008507:Medically Underserved Area; D015995:Prevalence; D011785:Quality Assurance, Health Care; D064876:Safety-net Providers / Q000592:standards* / Q000706:statistics & numerical data*; D014481:United States
keywords: Electronic health records and systems; patient with chronic illness or special needs; performance improvement; safety net clinic