Diabetes is a multisystem disease requiring complex management provided by a variety health care professionals (HCPs). Comprehensive care of patients with diabetes requires frequent testing of hemoglobin A1c (A1C),and research indicates that use of point-of-care testing (POCT) can affect patients' A1C results in the shortterm. The purpose of this qualitative study was to explore the ideas, opinions, and expectations of HCPs and patients with diabetes about the potential role of POCT, including its impact on patient-provider interactions, patient care, and issues of implementation. In-depth interviews, which were audiotaped and transcribed verbatim, were conducted with key stakeholders. The analysis used immersion and crystalization strategies. Thirty-seven interviews were conducted: seven with endocrinologists and internists, seven with family physicians, eight with diabetes educators, seven with family practice nurses, and eight with patients with diabetes. Two major themes emerged from the data analysis: 1) the impact of POCT on the clinical encounter and the care of patients, and 2) the POCT machine, including accuracy and the cost of incorporating the machine into clinical practice. The analysis revealed strong similarities across all groups of HCPs, and patients also expressed similar concerns. This study illuminates perceptions of HCPs and patients regarding the impact of POCT on diabetes management. POCT was viewed as having many benefits in the clinical care of patients with diabetes, including face-to-face encounters that offer immediate feedback, proactive patient education,increased collaboration between patients and providers, and improved patient adherence. However, logistical issues, such as the machine's accuracy and cost factors, could be significant barriers to implementation
BACKGROUND Hypoglycemia prognostic models contingent on prospective, self-reported survey data offer a powerful avenue for determining real-world event susceptibility and interventional targets. OBJECTIVE This protocol describes the design and implementation of the 1-year iNPHORM (Investigating Novel Predictions of Hypoglycemia Occurrence Using Real-world Models) study, which aims to measure real-world self-reported severe and nonsevere hypoglycemia incidence (daytime and nocturnal) in American adults with type 1 or 2 diabetes mellitus prescribed insulin and/or secretagogues, and develop and internally validate prognostic models for severe, nonsevere daytime, and nonsevere nocturnal hypoglycemia. As a secondary objective, iNPHORM aims to quantify the effects of different antihyperglycemics on hypoglycemia rates. METHODS iNPHORM is a prospective, 12-wave internet-based panel survey that was conducted across the United States. Americans (aged 18-90 years) with self-reported type 1 or 2 diabetes mellitus prescribed insulin and/or secretagogues were conveniently sampled via the web from a pre-existing, closed, probability-based internet panel (sample frame). A sample size of 521 baseline responders was calculated for this study. Prospective data on hypoglycemia and potential prognostic factors were self-assessed across 14 closed, fully automated questionnaires (screening, baseline, and 12 monthly follow-ups) that were piloted using semistructured interviews (n=3) before fielding; no face-to-face contact was required as part of the data collection. Participant responses will be analyzed using multivariable count regression and machine learning techniques to develop and internally validate prognostic models for 1-year severe and 30-day nonsevere daytime and nocturnal hypoglycemia. The causal effects of different antihyperglycemics on hypoglycemia rates will also be investigated. RESULTS Recruitment and data collection occurred between February 2020 and March 2021 (ethics approval was obtained on December 17, 2019). A total of 1694 participants completed the baseline questionnaire, of whom 1206 (71.19%) were followed up for 12 months. Most follow-up waves (10,470/14,472, 72.35%) were completed, translating to a participation rate of 179% relative to our target sample size. Over 70.98% (856/1206) completed wave 12. Analyses of sample characteristics, quality metrics, and hypoglycemia incidence and prognostication are currently underway with published results anticipated by fall 2022. CONCLUSIONS iNPHORM is the first hypoglycemia prognostic study in the United States to leverage prospective, longitudinal self-reports. The results will contribute to improved real-world hypoglycemia risk estimation and potentially safer, more effective clinical diabetes management. CLINICALTRIAL ClinicalTrials.gov NCT04219514; https://clinicaltrials.gov/ct2/show/NCT04219514 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/33726
Abstract Background Indigenous populations have increased risk of developing diabetes and experience poorer treatment outcomes than the general population. The FORGE AHEAD program partnered with First Nations communities across Canada to improve access to resources by developing community-driven primary healthcare models. Methods This was an economic assessment of FORGE AHEAD using a payer perspective. Costs of diabetes management and complications during the 18-month intervention were compared to the costs prior to intervention implementation. Cost-effectiveness of the program assessed incremental differences in cost and number of resources utilization events (pre and post). Primary outcome was all-cause hospitalizations. Secondary outcomes were specialist visits, clinic visits and community resource use. Data were obtained from a diabetes registry and published literature. Costs are expressed in 2023 Can$. Results Study population was ~ 60.5 years old; 57.2% female; median duration of diabetes of 8 years; 87.5% residing in non-isolated communities; 75% residing in communities < 5000 members. Total cost of implementation was $1,221,413.60 and cost/person $27.89. There was increase in the number and cost of hospitalizations visits from 8/$68,765.85 (pre period) to 243/$2,735,612.37. Specialist visits, clinic visits and community resource use followed this trend. Conclusion Considering the low cost of intervention and increased care access, FORGE AHEAD represents a successful community-driven partnership resulting in improved access to resources.
To further knowledge of diabetes management in family practice. DESIGN Retrospective, observational chart audit study.Southwestern Ontario.A random sample of non-academic family physicians and a random selection of their patients with type 2 diabetes mellitus.Glycemic control as measured by HbA1c and adherence to recommendations in clinical practice guidelines (CPGs).Eighty-four percent of patients had at least one HbA1c test ordered in the previous year. Overall mean HbA1c was 0.079 and half-the patients had levels deemed acceptable by 1992 CPGs. Screening for microvascular complications was disappointing; only 28% were tested for microalbuminuria, and 15% were examined for diabetes-related foot conditions. Screening for macrovascular complications was more comprehensive; blood pressure was measured in 88%, and lipid profiles documented in 48%, of patient charts.Management of glycemic control and screening for microvascular and macrovascular disease in family practice can be improved.
Impaired awareness of hypoglycemia (IAH) has been linked to an increased rate of severe hypoglycemia (SH) in T1DM. Yet, few investigations have focused on quantifying this relationship in the context of T2DM, particularly from a pragmatic epidemiological lens. This study leverages the value of self-reported SH data to explore the real-world, population-based effect of IAH severity on SH rates in T2DM. A validated questionnaire (InHypo-DMPQ) was administered online to a nationally representative panel comprising Canadians (≥18 years) with T2DM using insulin and/or secretagogues. Data were collected on respondents’ socio-demographic/clinical traits; self-reported incidence of SH (in the past year); and IAH severity, trisected by no, moderate, and severe impairment. Multivariable negative binomial regression (NBR) analysis was used to isolate the effect of IAH on SH. A directed acyclic graph was devised to identify the minimally sufficient adjustment set. Of the 452 complete respondents (mean age: 53.2 (SD: 14.7) years; male: 56%), 6% were classified with severe IAH, 67% with moderate IAH, and 27% with no IAH. Those with severe IAH had the highest crude annual SH rate (5.89 events/person-year, 95% CI: 5.01-6.88), which over doubled and tripled the SH rate in people with moderate IAH (p<0.001) and no IAH (p<0.001), respectively. The adjusted NBR analysis revealed a statistically significant association between IAH and SH (p=0.039). Individuals with severe IAH reported an adjusted annual SH rate that was 3.23 (95% CI: 1.13-9.27, p=0.029) times greater than those with no IAH. A similar trend was observed for moderate IAH versus no IAH (p=0.038). This real-world, population-based study provides timely insight into the high prevalence of moderate and severe IAH in people with T2DM using insulin and/or secretagogues. The marked impact of IAH on increased SH rates underscores a pressing need for the clinical prioritization of IAH assessment and management in T2DM. Disclosure A. Ratzki-Leewing: None. S.B. Harris: Advisory Panel; Self; AstraZeneca, Janssen Pharmaceuticals, Inc., Lilly/Boehringer Ingelheim, Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Consultant; Self; AstraZeneca, Janssen Pharmaceuticals, Inc., Lilly/Boehringer Ingelheim, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Research Support; Self; Abbott, AstraZeneca, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Other Relationship; Self; Canadian Diabetes Association, Canadian Institutes of Health Research, The Lawson Foundation. N.H. Au: None. S. Webster-Bogaert: None. J.B. Brown: None. S.M. Reichert: Advisory Panel; Self; Abbott, AstraZeneca, Novo Nordisk Inc., Sanofi, Servier. Research Support; Self; Canadian Institutes of Health Research. Speaker's Bureau; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Inc., Sanofi. B.L. Ryan: None. Funding Sanofi Canada
