Evaluation of the Impact of In-Person and Telemedicine-Based Medical Education on Diabetes Care and Outcomes in Hospitalized Patients
Phase: NA
Conditions: Diabete Type 2, Hyperglycemic Therapy, Medical Education, Telemedecine
Sponsor: Catholic University of Pelotas

Study Protocol and Statistical Analysis Plan 
Evaluation of Medical Education With Telemedicine on Technical Knowledge and Quality of 
Care for Patients With Hyperglycemia and Diabetes in the Hospital Setting – A Multicenter 
Randomized Clinical Trial 
NCT Number:​
Pending 
Document Date:​
May 31, 2025 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

1.​ Introduction and Rationale 
Diabetes mellitus is a major global health challenge with a growing burden in both 
outpatient and inpatient settings. In Brazil, recent data reveal a high prevalence of diabetes. A 
study conducted across six Brazilian capitals among public university employees aged 35 to 
74 years found a prevalence of 20%, with approximately half of the cases previously 
undiagnosed. 
It is estimated that 22% of all hospitalized patients have diabetes. In the United States, 
hospitalizations account for nearly half of the $174 billion in total annual medical 
expenditures related to diabetes. Each year, 1.6 million new cases are diagnosed in the U.S., 
with an overall prevalence of 23.6 million individuals—7.8% of the population—of whom 
approximately one-quarter remain undiagnosed. 
Hospital admission rates for patients with diabetes range from 14% to 20%, 
particularly within the first 30 days following discharge. Major risk factors for readmission 
include lower socioeconomic status, race/ethnicity (e.g., Hispanic, African American, Native 
American, and Asian American), comorbid conditions, and recent hospitalizations. 
Approximately 30% of patients with two or more hospitalizations account for more 
than 50% of all admissions and related costs. Although there is no universally accepted 
protocol to prevent readmissions, several effective strategies have been reported. These 
include targeted interventions for high-risk patients with poor glycemic control and the 
implementation of transitional care models. 
Glycemic disturbances—such as hyperglycemia, hypoglycemia, and glucose 
variability—in hospitalized patients have been associated with adverse outcomes, including 
prolonged hospital stays, increased morbidity, and mortality. Evidence from clinical practice 
also highlights the relevance of physician knowledge and the role of specialized diabetes care 
teams as important predictors of improved glycemic control and reduced hospital length of 
stay. 
Telemedicine has emerged as a valuable tool in diabetes management, especially 
through remote monitoring, communication platforms, and therapeutic adjustments. 
However, most studies involving telemedicine focus on outpatient or primary care contexts. 
Given the severity of diabetes-related complications, the economic impact of 
hospitalizations, the persistently high readmission rates, and the need to strengthen medical 
knowledge for inpatient diabetes care, this study proposes a structured, telemedicine-based 
educational intervention. The objective is to evaluate its effectiveness in improving medical 
knowledge, insulin prescription quality, and the prevention and management of glycemic 
extremes during hospitalization. 
2.​ Primary and Secondary Objectives 
Primary objective: 
To evaluate the impact of a structured educational intervention via telemedicine on 
internal medicine residents’ knowledge regarding inpatient hyperglycemias. 
Secondary objectives: 
To assess the effect of the intervention on the quality of insulin prescriptions and 
capillary blood glucose monitoring. 

To evaluate the effect on the occurrence of hypoglycemia and hyperglycemia during 
hospitalization. 
To compare the length of hospital stay between the intervention and control groups. 
3.​ Study Design 
This was an open-label, multicenter, randomized clinical trial conducted at university 
hospitals located in southern Brazil. Internal medicine clinical teams were block-randomized 
using stratified allocation by center to ensure balance between groups. 
The intervention group received a 30-minute online theoretical lecture on hospital 
hyperglycemia and participated in a 30-day telemedicine-based continuing education 
program delivered via a messaging platform. The control group continued standard clinical 
activities without any educational intervention. 
Data collection occurred in two phases: a pre-post knowledge assessment using a 
validated questionnaire, and a retrospective chart review of hospitalized patients cared for by 
the participating teams. 
4.​ Intervention 
Residents in the intervention group received a 30-minute online theoretical lecture on 
inpatient hyperglycemia, followed by daily educational content for 30 days via a messaging 
application. Materials included short videos, texts, and clinical guidance on diabetes and 
hospital glycemic management. 
The control group received no educational content and maintained routine clinical 
duties. 
5.​ Inclusion and Exclusion Criteria 
Inclusion criteria: 
Internal medicine residents assigned to clinical teams at participating hospitals. 
Exclusion criteria: 
Residents on leave during the intervention period. 
Teams supervised by endocrinologists. 
Residents who declined participation. 
6.​ Outcome Measures (Primary and Secondary) 
Primary outcome: 
Change in medical knowledge on inpatient hyperglycemia, assessed through a 
validated questionnaire before and after the intervention. 
Secondary outcomes: 
Quality of glucose monitoring and insulin prescribing. 
Incidence of hyperglycemia (>180 mg/dL) and hypoglycemia (<70 mg/dL). 
Length of hospital stay 
7.​ Sample Size Calculation 

Based on previous data showing 46.44% accuracy in key knowledge items, and 
assuming an increase to 80% after the intervention, with 80% power and a 5% significance 
level, a minimum of 62 completed questionnaires (including both pre- and post-intervention 
assessments) was required. 
8.​ Statistical Analysis Plan 
Categorical variables were described as frequencies and percentages. Continuous 
variables were expressed as means and standard deviations or medians and interquartile 
ranges, based on normality (Shapiro-Wilk test). 
Between-group comparisons were made using Student’s t-test or the Mann-Whitney U 
test for continuous variables, depending on distribution. Categorical variables were analyzed 
using Pearson’s chi-square test or Fisher’s exact test, as appropriate. Logistic regression 
analysis was performed to identify independent predictors, including variables with clinical 
relevance or p < 0.20 in the univariate analysis. Statistical analyses were conducted using 
IBM SPSS Statistics for Windows, Version 29.0 (IBM Corp., Armonk, NY, USA). A 
two-sided p-value < 0.05 was considered statistically significant. 
9.​ Ethical Considerations 
All participating physicians provided informed consent. Data were collected with 
institutional authorization and approval by the local ethics committee. Confidentiality and 
privacy were strictly maintained for all participants and patient information.