title: The impact of a patient's concordant and discordant chronic conditions on diabetes care quality measures.
abstract: OBJECTIVE
  Most patients with diabetes have comorbid chronic conditions that could support (concordant) or compete with (discordant) diabetes care. We sought to determine the impact of the number of concordant and discordant chronic conditions on diabetes care quality.
  
  
  METHODS
  Logistic regression analysis of electronic health record data from 7 health systems on 24,430 patients with diabetes aged 18-75 years. Diabetes testing and control quality care goals were the outcome variables. The number of diabetes-concordant and the number of diabetes-discordant conditions were the main explanatory variables. Analysis was adjusted for health care utilization, health system and patient demographics.
  
  
  RESULTS
  A higher number of concordant conditions were associated with higher odds of achieving testing and control goals for all outcomes except blood pressure control. There was no to minimal positive association between the number of discordant conditions and outcomes, except for cholesterol testing which was less likely with 4+ discordant conditions.
  
  
  CONCLUSIONS
  Having more concordant conditions makes diabetes care goal achievement more likely. The number of discordant conditions has a smaller, inconsistently significant impact on diabetes goal achievement. Interventions to improve diabetes care need to align with a patient's comorbidities, including the absence of comorbidities, especially concordant comorbidities.
authors.affiliation: Health Innovation Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Family and Community Medicine, University of California, Davis, Sacramento, CA, USA. Electronic address: elizabeth.magnan@ucdmc.ucdavis.edu.
authors.forename: Elizabeth M
authors.initials: EM
authors.lastname: Magnan
authors.affiliation: Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
authors.forename: Mari
authors.initials: M
authors.lastname: Palta
authors.affiliation: Health Innovation Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
authors.forename: Heather M
authors.initials: HM
authors.lastname: Johnson
authors.affiliation: Health Innovation Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
authors.forename: Christie M
authors.initials: CM
authors.lastname: Bartels
authors.affiliation: Health Innovation Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
authors.forename: Jessica R
authors.initials: JR
authors.lastname: Schumacher
authors.affiliation: Health Innovation Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
authors.forename: Maureen A
authors.initials: MA
authors.lastname: Smith
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002908:Chronic Disease / Q000453:epidemiology / Q000628:therapy*; D015897:Comorbidity; D048909:Diabetes Complications / Q000517:prevention & control*; D003920:Diabetes Mellitus / Q000097:blood / Q000453:epidemiology / Q000628:therapy*; D057286:Electronic Health Records; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D006943:Hyperglycemia / Q000517:prevention & control; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015146:Midwestern United States / Q000453:epidemiology; D010342:Patient Acceptance of Health Care; D011320:Primary Health Care; D011787:Quality of Health Care; D009626:Terminology as Topic; D055815:Young Adult
chemical_list: D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human
keywords: Comorbidity; Diabetes; Multimorbidity; Multiple chronic conditions; Outcomes; Quality