European Journal of Cardiovascular Medicine

Diabetes is one of the biggest health issues nowadays. The International Diabetes Federation (IDF) predicts 643 million cases in 2030 and 783 million in 2045 [1]. Diabetes affected 537 million 20–79-year-olds in 2021. Type 2 diabetes mellitus (T2DM), induced by obesity, inactivity, and poor diet, accounts for most of these occurrences. Diabetes complications such as heart disease, renal disease, blindness, nerve damage, and lower limb amputations are a primary cause of death and disability [2]. These problems cost patients, healthcare systems, and governments money and lower the quality of life. India has one of the highest prevalence of diabetes globally, with approximately 74 million adults affected in 2021 [3]. Rapid urbanization, lifestyle changes, and nutritional changes have increased non-communicable diseases. Medical treatments, monitoring, and long-term diabetes management raise healthcare costs. Diabetes costs are largely due to poor glucose management and unnecessary complications [4]. If the region needs to reduce diabetes clinical and economic costs, it must increase antidiabetic medication adherence.

Medication adherence is healthy when a patient takes their doctor's orders, eats well, and makes other lifestyle changes [5]. Adherence is essential in diabetes therapy to chance glycaemic goals and prevent illness. Multiple clinical trials and observational data show that insulin therapy plus oral antidiabetic pill adherence lowers HbA1c levels and microvascular and macrovascular issues [6]. Non-adherence leads to poor glycaemic control, more hospitalizations, and higher healthcare costs [7]. Non-adherence is a problem in diabetes care all over the world. This is accurate even though pharmaceutical therapy and patient education have certainly come a long way. People in India have trouble controlling their blood sugar, even though there are many types of insulin and oral hypoglycaemia drugs [8]. Many diabetics failure their glucose goals because they fail to utilize their medications as prescribed [9]. People fail to take their pills for several reasons. Treatments that are hard to understand, side effects, forgetfulness, false information, psychological resistance, and social and economic barriers [10]. Language diversity, varying levels of health literacy, and cultural beliefs about long-term health are some of the factors that affect medication adherence among patients [11, 12].

Problems with diabetes adherence cost patients and doctors money and affect patient outcomes. Hospitals check for obedience to better help people with diabetes. Diabetes control and taking medications as prescribed lacks accurate EMR data. Most research is cross-sectional or based on surveys. Additionally, and more clinical situations need objective reviews of past adherence practices and diabetes outcomes. Researchers can look at patient data to determine if taking medications as prescribed has an effect on diabetes. This looks at real-life data, gets rid of memory bias, and shows how therapy works. Using records of drug refills, HbA1c readings, and visit frequencies, retrospective studies can show how adherence affects glycaemic outcomes in situations where diabetes is not under control. Evidence-based medicine helps doctors evaluate diabetes control plans, get patients to stick to them more, and make treatments more effective for each patient. With a lot of people living with diabetes and a healthcare system that is quickly becoming more modern. These analyses can show important trends that can help make government programs to prevent diabetes better.

Study Objectives

1. To evaluate the relationship between antidiabetic medication adherence and glycaemic control among patients with Type 2 Diabetes Mellitus treated at the Medicine Department, Central Hospital, Kalla, India.
2. To determine the proportion of patients achieving optimal glycaemic targets (HbA1c <7%) in relation to their medication adherence levels measured by MPR/PDC.
3. To identify demographic and clinical factors influencing medication adherence and glycaemic outcomes using retrospective EMR data from June 2024 to June 2025.

Study Design

This study used EMR data from people with T2DM to examine their history. Researchers examined old clinical data to investigate how taking drugs as prescribed affects diabetes control over a year. They picked this method to show therapy adherence and results in the real world while keeping clinical practices and patient care.

Study Setting

The study was conducted at the Medicine Department, Central Hospital, Kalla, India, using Electronic Medical Records (EMR) from June 2024 to June 2025. The hospital provides outpatient and inpatient diabetes care and maintains electronic records of prescriptions, laboratory results.

Study Population

The trial included Type 2 Diabetes Mellitus adults (18+) and Indian participants. An objective sample of 100 patient records was chosen by random sampling. Female and male diabetics who took oral antidiabetic medicines, insulin, or both for at least six months before the trial ended were included.

Inclusion Criteria

• Confirmed diagnosis of Type 2 Diabetes Mellitus.
• Receiving oral antidiabetic medications and/or insulin therapy for at least six months previous to data collection.
• Complete clinical and laboratory records, including a valid HbA1c measurement, for the study period.

Exclusion Criteria

• Diagnosis of Type 1 Diabetes Mellitus or gestational diabetes.
• Incomplete or missing clinical data regarding medications or HbA1c levels.
• Medical facility transfers throughout the study period led to missing follow-up data.

Data Collection

The EMR of the Medicine Department, Central Hospital, Kalla, India, were accessed using a pre-designed data extraction form.

• Demographic variables: age, gender, and nationality.
• Clinical variables: duration of diabetes, comorbid conditions (e.g., hypertension, dyslipidemia), body mass index (BMI), and most recent HbA1c value.
• Medication adherence: calculated using the MPR or Proportion of Days Covered (PDC), derived from pharmacy refill data.
  • MPR = (Total days’ supply of medication / Number of days in the observation period) × 100.
  • Adherence was categorized as:
    • High adherence: MPR or PDC ≥ 80%
    • Moderate adherence: 50–79%
    • Low adherence: < 50%.
  • Glycaemic control: evaluated using HbA1c values; patients with HbA1c <7% were classified as having controlled glycemia, while those with HbA1c ≥7% were classified as uncontrolled.

Statistical Analysis

• Data entry and analysis were performed using R or SPSS 26.0 (IBM Corp., Armonk, NY, USA).
• Percentage, frequency, SD, and mean were used to summarize demographic and clinical data.
• Inferential statistics were employed to find links between taking drugs as prescribed and better blood sugar control. It used an independent sample t-test to compare mean HbA1c levels among adherence groups and the Chi-square test to evaluate categorical factor associations.
• The Pearson correlation coefficient was calculated to link adherence to HbA1c readings.
• A p-value below 0.05 indicated statistical significance.

Demographic Characteristics

One hundred inclusion-eligible medical records were analysed. Participants' ages ranged from 32 to 78 years, with a mean age of 55.8 ± 10.6 years. The sample was evenly distributed between men and women (54% male, 46% female). Patients were predominantly from the local region, with 62% from nearby districts and 38% from other parts of the state.

Table 1 Demographic Characteristics of Study Participants (n = 100)

Clinical Characteristics

The individuals' average diabetes duration was 8.4 ± 5.2 years, ranging from 1 to 22 years. The majority of participants were overweight or obese, with a mean BMI of 29.1 ± 4.7 kg/m². Hypertension (58%), dyslipidaemia (49%), and coronary artery disease (12%) were the most common co-occurring diseases.

Table 2 Clinical Characteristics of the Study Population

Medication Adherence

According to MPR and PDC estimates, 39% of patients had adherence ≥80%, 37% had moderate adherence (50-79%), and 24% had extremely low adherence (<50%).

Glycaemic Control

All participants had an average HbA1c of 7.9 ± 1.3%. A total of 43% of patients had managed glycemia (HbA1c <7%), whereas 57% had uncontrolled glycemia (HbA1c ≥7%).  The average HbA1c level among high-adherence patients was 7.1 ± 0.9%, whereas moderate-adherence patients had 8.0 ± 1.2% and the lowest group had 8.6 ± 1.5%.

Statistical Association Between Adherence and Glycaemic Control

A significant negative connection (r = -0.48, p < 0.001) links higher medication adherence to lower HbA1c levels and improved glycaemic management.

Table 3 Association Between Medication Adherence and Glycaemic Control

The association between medication adherence and glycaemic control is significant (p-value <0.001). HbA1c targets were more often met by adherence-oriented patients.

Summary of Key Findings

• Nearly 40% of patients adhered well to their medicine. The majority were obese and middle-aged.
• The prevalence of dyslipidaemia and hypertension was high. Glycaemic management was inadequate in 57% of patients (HbA1c 7% or higher).
• Medication adherence indicates improved glycaemic outcomes, with a strong inverse connection (r = -0.48, p < 0.001) between HbA1c and adherence.

At the Medicine Department, Central Hospital, Kalla, India between June 2024 and June 2025, T2DM patients' glycaemic control and antidiabetic medication adherence were studied. 37% of patients strictly followed their treatment regimen, while 57% had poor glycaemic control (HbA1c ≥7%). Research shows a significant negative correlation (r = -0.48, p < 0.001) between adherence and HbA1c, indicating a strong association between adherence and improved glycaemic

This study confirms that diabetes care requires adherence. Global study shows that diabetics who follow their treatment programs are less likely to have problems and more possible to attain their HbA1c targets. Study 1 found that medication adherence improved by 10% and HbA1c decreased by 0.1%. Non-adherence was a key cause of poorly regulated blood sugar in type 2 diabetics. Study 2 observed that less than half of diabetes patients took their medication as prescribed, and non-adherence was strongly linked to uncontrolled HbA1c. Study 3 found similar issues in Indian patient concerns, such as limited health literacy and obliviousness, which caused poor adherence.

Table 4 Comparison of Present Study with Previous Studies on Antidiabetic Medication Adherence and Glycaemic Control

Significance of Adherence on Glycaemic Outcomes

Medication adherence stabilizes plasma drug levels, reducing glucose fluctuations and long-term effects on glycaemic management. Since high-adherence patients had far lower HbA1c levels than moderate- or low-adherence patients, this study supports the premise that adherence is crucial to diabetes therapy. Non-adherence can cause frequent hyperglycaemia, higher healthcare costs, and more hospitalizations, emphasizing the necessity to monitor adherence in clinical practice.

Barriers to Adherence

Several factors contribute to low medication adherence. Common barriers identified in previous studies include memory lapses, complex medication regimens, and adverse side effects. Financial difficulties including pharmaceutical costs may also affect expats with poor health coverage. Culture, diabetes ignorance, and medication dependence are additional obstacles. Patients can get past these issues with the help of education, streamlined treatment plans, digital reminders, and solutions led by pharmacists.

Clinical Implications

These findings highlight the need for diabetic adherence evaluation. Pharmacists, diabetes educators, and dietitians regularly follow up appointments and individualized counselling to help patients take their medication. Mobile health apps, electronic reminders, and education may improve patient engagement and long-term illness control. Clinicians must consider treatment tiredness and diabetes distress, which can impair adherence.

Limitations and Strengths

The retrospective study makes linking adherence and glycaemic control difficult. The results may not apply to diabetics due to the small sample size (n = 100) and single-centre setup. Using prescription refills to measure adherence may not accurately reflect medication intake. However, the study is beneficial and neutrally measures adherence and glycaemic results using real-world EMR data. It provides local data on Indian diabetes and is one of the few studies to focus on adherence control.

The Medicine Department, Central Hospital, Kalla, India, treated Type 2 Diabetes Mellitus patients. Glycaemic control and antidiabetic medication adherence were examined in this retrospective analysis. High adherence rates reduced mean HbA1c and improved glycaemic control. Despite healthcare and pharmaceutical support, several patients had moderate to poor adherence, emphasizing treatment compliance issues. These results show how important it is to stick to treatment plans exactly to avoid diabetes problems and have good therapeutic outcomes. The study discovered that digital alerts, pharmacy refill systems, patient education, and regular follow-ups all help people stick to their treatment plans. A prospective, multicentre study with a larger sample size is needed to confirm these results and to examine the social, economic, and behavioural factors that influence medication adherence among diabetic patients.

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