Interaction between Type of Comorbidity and Visit Frequency on Diabetes Care

Pentakota S, Rajan M, Tseng C, Fincke G, Miller DR, Christiansen C. Interaction between Type of Comorbidity and Visit Frequency on Diabetes Care. Poster session presented at: AcademyHealth Annual Research Meeting; 2012 Jun 25; Orlando, FL.

Related HSR&D Project(s)

• IIR 08-355 – Interplay of Chronic Illness, Race, Age and Sex in Glycemic Control

Research Objective: Comorbid illnesses among diabetes patients may complicate care by competing for time, attention, or other resources. Our study objective was to evaluate the relationship between diabetes care and types of comorbidity, classified by the degree to which their treatment is concordant with that for diabetes. Additionally we assessed whether this relationship differed by utilization rates, measured here as visit frequency. Study Design: Retrospective cohort study of Veteran healthcare (VHA) users with diabetes. Population Studied: We identified 42,826 veterans with new-onset diabetes (DM) in FY2003 from the Diabetes Epidemiology Cohort (DEpiC) database. Veterans were classified into 5 major chronic co-morbid illness groups (CCIGs): none, concordant only, discordant only, both, and dominant, based upon a competing demands framework (Piette and Kerr, Diabetes Care 2006). The chronic co-morbid illnesses were ascertained using data from FY2003 and a two-year look-back period (FY2001- 02). Five DM care-related outcomes were assessed in FY 2004 (guideline-consistent testing and treatment goals for HbA1c and LDL-C, and diabetes-related (250.xx codes) outpatient visits. We ran four logistic regression models, beginning with CCIG as the independent variable, and then sequentially adding socio-demographic variables, visit frequency, and an interaction term between visit frequency and CCIGs (fully adjusted model). The models adjusted for the effects of clustering by VHA facility. Principal Findings: Only 20% of patients had no chronic comorbidities. Mean number of annual visits ranged from 7.8 (no CCIG) to 17.5 (dominant CCIG). In unadjusted analyses, presence of any illness was associated with equivalent or better care. In the fully adjusted model, we found significant interaction between CCIG and visit frequency. When visits were < 7/year, the odds of meeting a HbA1c < 8% measure were similar in the concordant (0.96(0.83-1.11)) and lower in the discordant (0.90(0.81-0.99)). For the LDL-C < 130 mg/dL measure, the corresponding odds were (1.16(1.01-1.33)) and (0.87(0.79-0.96)), respectively. Among patients with > 24 visits/year these odds were not significant. Conclusions: Comorbidity type affected diabetes care. Having concordant illnesses was associated with similar or better diabetes care; having discordant illnesses was associated with decreased diabetes care; and the presence of dominant illnesses resulted in the markedly decreased diabetes care. This difference was more pronounced among patients who made less frequent visits. Implications for Policy, Delivery, or Practice: Better care-coordination efforts within health care systems might help to improve rates of adherence to diabetes care indicators among patients with comorbidities. Coordination of diabetes care between specialists and primary care, at least for processes, might be one approach. For patients with multiple conditions, patient groups that might be receiving over- or under-treatment can be identified and specific interventions to improve care can be designed. Also, patients with similar barriers (mental health or musculoskeletal conditions) might benefit from programs such as shared medical appointments or from motivational interviewing based upon agreed upon goals.