The Case for Diabetes Population Health Improvement: Evidence-Based Programming for Population Outcomes in Diabetes

Abstract

Purpose of Review The goal of this review is to describe diabetes within a population health improvement framework and to review the evidence for a diabetes population health continuum of intervention approaches, including diabetes prevention and chronic and acute diabetes management, to improve clinical and economic outcomes. Recent Findings Recent studies have shown that compared to usual care, lifestyle interventions in prediabetes lower diabetes risk at the population-level and that group-based programs have low incremental medial cost effectiveness ratio for health systems. Effective outpatient interventions that improve diabetes control and process outcomes are multi-level, targeting the patient, provider, and healthcare system simultaneously and integrate community health workers as a liaison between the patient and community-based healthcare resources. A multi-faceted approach to diabetes management is also effective in the inpatient setting. Interventions shown to promote safe and effective glycemic control and use of evidence-based glucose management practices include provider reminder and clinical decision support systems, automated computer order entry, provider education, and organizational change. Summary Future studies should examine the cost-effectiveness of multi-faceted outpatient and inpatient diabetes management programs to determine the best financial models for incorporating them into diabetes population health strategies.

Retrospective study of inpatient diabetes management service, length of stay and 30-day readmission rate of patients with diabetes at a community hospital

“…Our findings are also consistent with the published literature, where about a quarter of all admitted hospital patients that have diabetes are more likely to originate from emergency departments [26,34], rather than planned admissions (e.g., planned surgery). Studies that evaluated specialized healthcare teams to manage patients with diabetes found that multidisciplinary and interactive teams were effective in providing improved care for patients with diabetes [8,25,26,34,35]. Increased diabetes education for healthcare providers and/or increased nursing training may be especially effective [8,25,36,37].…”

“…Studies that evaluated specialized healthcare teams to manage patients with diabetes found that multidisciplinary and interactive teams were effective in providing improved care for patients with diabetes [8,25,26,34,35]. Increased diabetes education for healthcare providers and/or increased nursing training may be especially effective [8,25,36,37]. When diabetes-related educational policies were targeted at nurses, medical providers, and patients, a decrease in LOS was observed .…”

“…When diabetes-related educational policies were targeted at nurses, medical providers, and patients, a decrease in LOS was observed . Most, but not all, studies have found associations between the presence of IDMS teams and reduced LOS and 30DR [8,16,[24][25][26]33,34,39]. Horton and colleagues evaluated the effects of a guideline-derived physician resident educational program on LOS and observed a decrease in LOS after the guidelines were implemented (5.03 days vs 6.98 days; P = 0.042) [16].…”

“…Diabetes is an expensive disease. The estimated cost of diagnosed diabetes care in the U.S. was $327 billion in 2017 [8,9], and a major proportion of this expense was from hospitalizations and medications [10]. Thus, hospitals may be under pressure to cut healthcare costs given limited resources.…”

Estimating risk and cost: An analysis of patients with risk factors for Type 2 Diabetes in rural Jalisco, Mexico

“…It is also possible that having a dedicated nurse or nursing staff to see patients at risk for diabetes may lower costs, given the number of patients seen and the ability of nurses to provide comprehensive and adequate care and counseling. [21] There are several limitations in this study, the first being recall bias. Data extracted from chart reviews relies partially on patient reported data for family and personal history.…”