PLATEDIAN (Telemedicine on Metabolic Control in Type 1 Diabetes Mellitus Andalusian Patients) (NCT03332472) was a multicenter, randomized, 6-month follow-up, open-label, parallel-group controlled study performed in patients with type 1 diabetes with suboptimal metabolic control (HbA_1c <8% [<64 mmol/mol]), treated with multiple daily injections. A total of 388 patients were assessed for eligibility; 379 of them were randomized 1:1 to three face-to-face visits (control cohort [CC]) (n = 167) or the replacement of an intermediate face-to-face visit by a telemedicine visit using Diabetic (intervention cohort [IC]) (n = 163). The primary efficacy end point was the mean change of HbA_1c levels from baseline to month 6. Other efficacy and safety end points were mean blood glucose, glucose variability, episodes of hypoglycemia and hyperglycemia, patient-reported outcomes, and physicians’ satisfaction.

At month 6, the mean change in HbA_1c levels was –0.04 ± 0.5% (–0.5 ± 5.8 mmol/mol) in the CC and 0.01 ± 0.6% (0.1 ± 6.0 mmol/mol) in the IC (P = 0.4941). The number of patients who achieved HbA_1c <7% (<53 mmol/mol) was 73 and 78 in the CC and IC, respectively. Significant differences were not found regarding safety end points at 6 months. Changes in HRQoL between the first visit and final visit did not differ between cohorts, and, regarding fear of hypoglycemia (FH-15 score ≥28), statistically significant differences observed at baseline remained unchanged at 6 months (P < 0.05).

The use of telemedicine in patients with type 1 diabetes with HbA_1c <8% (<64 mmol/mol) provides similar efficacy and safety outcomes as face-to-face visits.

Six years of outpatient electronic health record (EHR) data were analyzed for care gaps before and 2 years after implementing a QI initiative in an urban academic medical center. QI strategies included 1) individual provider and departmental outcome reports, 2) patient outreach programs to address timely follow-up care, 3) a patient awareness campaign to improve understanding of achieving clinical goals, 4) improving EHR data capture to improve population monitoring, and 5) professional education.

Analysis (January 2010 to May 2018) of 7,798 patients from Tulane Medical Center (mean age 61 years, 57% female, 62% black, 97% insured) with 136,004 visits showed target improvements. A Cox proportional hazards model controlling for age, sex, race, and HbA_1c level showed a statistically significant reduction in HbA_1c undertesting >6 months (hazard ratio 1.20 ± 0.07). Statistical process control charts showed 15.5% relative improvement in the patient proportion with HbA_1c >9% (75 mmol/mol) from 13% to 11% (P < 10^–6) following QI interventions and a 2.1% improvement of population mean HbA_1c from 7.4% (57 mmol/mol) to 7.2% (55 mmol/mol) (P < 10^–6).

Multidisciplinary QI teams using EHR data to design interventions for providers and patients produced statistically significant improvements in both care process and clinical outcome goals.

Using Oregon Medicaid administrative data from 1 January 2014 to 30 September 2016, a retrospective cohort study was conducted with propensity score–matched Medicaid eligibility groups (newly and previously eligible). Outcome measures included total per-member per-month (PMPM) Medicaid expenditures and PMPM expenditures in the following 12 categories: inpatient visits, emergency department visits, primary care physician visits, specialist visits, prescription drugs, transportation services, tests, imaging and echography, procedures, durable medical equipment, evaluation and management, and other or unknown services.

Total PMPM Medicaid expenditures for newly eligible enrollees with diabetes were initially considerably lower compared with PMPM expenditures for matched previously eligible enrollees during the first postexpansion quarter (mean values $561 vs. $793 PMPM, P = 0.018). Within the first three postexpansion quarters, PMPM expenditures of the newly eligible increased to a similar but slightly lower level. Afterward, PMPM expenditures of both groups continued to increase steadily. Most of the overall PMPM expenditure increase among the newly eligible was due to rapidly increasing prescription drug expenditures.

Newly eligible Medicaid enrollees with diabetes had slightly lower PMPM expenditures than previously eligible Medicaid enrollees. The increase in PMPM prescription drug expenditures suggests greater access to treatment over time.

A validated survey of 585 eligible family or general internal medicine practices seeing ≥30 adult patients with diabetes in or near Minnesota during 2017 evaluated the presence of 62 SysCMs. From 419 (72%) practices completing the survey, NQF#0729 was determined in 396 (95%) from electronic health records, including 215,842 patients with type 1 or type 2 diabetes.

Three SysCMs were associated with higher rates of meeting performance targets across all practices: 1) a systematic process for shared decision making with patients (P = 0.001), 2) checklists of tests or interventions needed for prevention or monitoring of diabetes (P = 0.002), and 3) physician reminders of guideline-based age-appropriate risk assessments due at the patient visit (P = 0.002). When all three were in place, an additional 10.8% of the population achieved recommended performance measures. In subgroup analysis, 15 additional SysCMs were associated with better care in particular types of practices.

Diabetes care outcomes are better in primary care settings that use a patient-centered approach to systematically engage patients in decision making, remind physicians of age-appropriate risk assessments, and provide checklists for recommended diabetes interventions. Practice size and location are important considerations when redesigning delivery systems to improve performance.

Data on health care resource utilization from 100,391 people with type 2 diabetes were extracted from the electronic database used at the Catalan Health Institute. Multivariate regression models were carried out to test the impact of glycemic control (HbA_1c) on total health care, hospital admission, and medication costs; model 1 adjusted for a variety of covariates, and model 2 also included micro- and macrovascular complications. Glycemic control was classified as good for HbA_1c <7%, fair for ≥7% to <8%, poor for ≥8% to <10%, and very poor for ≥10%.

Mean per patient annual direct medical costs were 3,039 ± SD 6,581. Worse glycemic control was associated with higher total health care costs: compared with good glycemic control, health care costs increased by 18% (509.82) and 23% (661.35) in patients with very poor and poor glycemic control, respectively, when unadjusted and by 428.3 and 395.1, respectively, in model 2. Medication costs increased by 12% in patients with fair control and by 28% in those with very poor control (model 2). Patients with poor control had a higher probability of hospitalization than those with good control (5% in model 2) and a greater average cost when hospitalization occurred (811).

Poor glycemic control was directly related to higher total health care, hospitalization, and medication costs. Preventive strategies and good glycemic control in people with type 2 diabetes could reduce the economic impact associated with this disease.

We measured inpatient (n = 816) health care utilization for Bronx A1C participants using an administrative data set containing all hospital discharges for New York State from 2006 to 2014. Multilevel mixed modeling was used to assess changes in health care utilization and costs between the telephonic diabetes intervention (Tele/Pr) arm and print-only (PrO) control arm.

During follow-up, excess relative reductions in all-cause hospitalizations for the Tele/Pr arm compared with PrO arm were statistically significant for odds of hospital use (odds ratio [OR] 0.89; 95% CI 0.82, 0.97; P < 0.01), number of hospital stays (rate ratio [RR] 0.90; 95% CI 0.81, 0.99; P = 0.04), and hospital costs (RR 0.90; 95% CI 0.84, 0.98; P = 0.01). Reductions in hospital use and costs were even stronger for diabetes-related hospitalizations. These outcomes were not significantly related to changes observed in hemoglobin A_1c during individuals’ participation in the 1-year intervention.

These results indicate that the impact of the Bronx A1C intervention was not just on short-term improvements in glycemic control but also on long-term health care utilization. This finding is important because it suggests the benefits of the intervention were long-lasting with the potential to not only reduce hospitalizations but also to lower hospital-associated costs.