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The American Journal of Managed Care October 2018
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Putting the Pieces Together: EHR Communication and Diabetes Patient Outcomes
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Putting the Pieces Together: EHR Communication and Diabetes Patient Outcomes

Marlon P. Mundt, PhD, and Larissa I. Zakletskaia, MA
More frequent electronic health record (EHR) message forwarding in primary care teams is associated with worse outcomes and higher medical costs for patients with diabetes.
ABSTRACT

Objectives: This study seeks to determine how changes in electronic health record (EHR) communication patterns in primary care teams relate to quality of care and costs for patients with diabetes.

Study Design: EHR-extracted longitudinal observational study.

Methods: A total of 83 health professionals in 19 care teams at 4 primary care clinics associated with a large Midwestern university participated in the study. Counts of messages routed between any 2 team members in the EHR in the past 18 months were extracted. Flow-betweenness, defined as the proportion of information passed indirectly within the team, was calculated. The analysis related changes in team flow-betweenness to changes in emergency department visits, hospital stays, and associated medical costs for the teams’ patients with diabetes, while adjusting for team face-to-face communication, patient-level covariates, comorbidities, team size, and clinic fixed effects.

Results: Patient hospital visits increased by 13% (standard error [SE] = 6%) for every increase of 1 percentage point in team EHR message forwarding (ie, higher team flow-betweenness). Medical costs increased by $223 (SE = $105) per patient with diabetes in the past 6 months for every increase of 1 percentage point in team flow-betweenness.

Conclusions: Primary care teams whose EHR communication reached more team members indirectly (ie, via message forwarding) had worse outcomes and higher medical costs for their patients with diabetes. EHR team communication flow patterns may be an important avenue to explore in raising quality of care and lowering costs for patients with diabetes in primary care.

Am J Manag Care. 2018;24(10):462-468
Takeaway Points

This article analyzes the associations between indirect electronic health record (EHR) communication in primary care teams and outcomes and costs for patients with diabetes.
  • More frequent indirect EHR communication (eg, message forwarding) in primary care teams is associated with worse outcomes and higher medical costs for patients with diabetes.
  • Patient hospital visits increased by 13% for every increase of 1 percentage point in team EHR message forwarding.
  • Medical costs increased by $223 per patient with diabetes for every increase of 1 percentage point in message forwarding.
  • Team EHR communication flow patterns may be an important avenue to explore in raising quality of care and lowering costs for patients with diabetes.
Delivering evidence-based, high-quality healthcare for patients with diabetes, a leading cause of morbidity and mortality, is a major public health challenge. The prevalence of diabetes is 9.3% in the US population,1 and the economic cost of diagnosed diabetes in the United States was $245 billion in 2012.2

Team-based diabetes care leads to better glycemic and blood pressure control, improved patient follow-up, increased patient satisfaction, lower risk of diabetes complications, better quality of life, and lower healthcare costs.3-10 A meta-analysis of 66 diabetes intervention studies revealed that team-based interventions demonstrate the most robust improvements in patients’ glycemic control.11

Electronic health record (EHR) communication is a salient aspect of team functioning as primary care teams collaborate in diabetes care delivery.12 Prior research shows that communication networks in teams contribute to the development of a shared team vision of the team’s goals and objectives, which in turn is linked to patient quality-of-care outcomes.13 Team members need to be aware of who requires what information at what time, how information should be given, and whether the information should be reframed, evaluated, or summarized.14,15 The delivery of EHR information should not overwhelm the team members, disrupt their workflow, or delay decision making. Evaluating EHR communication flow among team members is an important step in the assessment of diabetes care quality.16-18

Very limited evidence exists on how team EHR communication patterns are associated with diabetes-related patient outcomes in primary care. To fill this gap, this study uses social network analysis to determine configurations of team EHR communication flow in relation to diabetes patient panel outcomes. Social network analysis is a systematic analytical tool for examining relationships in a complex system (eg, EHR team communication in primary care).19-26

METHODS

Study Setting and Design

The study data were drawn from 4 primary care clinics associated with UW Health, a large healthcare system in southern Wisconsin (see Mundt et al13 for full details on study procedures and recruitment). The Institutional Review Board of the University of Wisconsin approved the study.

All physicians, physician assistants, nurse practitioners, registered nurses (RNs), medical assistants (MAs), licensed practical nurses (LPNs), laboratory technicians, radiology technicians, clinic managers, medical receptionists, and other patient care staff were invited to participate. A trained researcher conducted a 30-minute face-to-face structured survey about team communication in the clinic. Using a clinic staff roster as an aid for memory recall, participants were asked to identify, for each other employee at their clinic, how frequently they communicated face-to-face about patient care.

Clinical Participants

Eligibility criteria included being 18 years or older, able to read and understand English, and employed at the study site in a patient care or patient interaction capacity. More than 97% (83 of 85 invited) of eligible participants took part in the study.

Diabetes Patient Panel Sample

An EHR search linked primary care teams to patients with diabetes (type 1 and type 2) 18 years or older who were seen by the team over the 18-month study period (July 1, 2013, to December 31, 2014). Diabetes diagnoses were determined by the presence of 2 validated International Classification of Diseases, Ninth Revision diabetes codes (250.00-250.03, 250.10-250.13, 250.20-250.23, 250.30-250.33, 250.40-250.43, 250.50-250.53, 250-60-250.63, 250.70-250.73, 250.80-250.83, 250.90-250.93, 357.2, 362.01, 362.02, 366.41) on 2 separate occasions within the previous 3 years.


 
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