PATIENT SUPPORTED CARE MODEL: FEASIBILITY STUDY OF A MOBILE APPLICATION-BASED TOOL TO EXPLORE DRUG COMPLIANCE IN CHRONIC KIDNEY DISEASE

Introduction:

Chronic Kidney Disease (CKD) patients often face challenges in adhering to prescribed treatments due to various reasons. Mobile technology-based applications offer the promise of monitoring adherence and improving compliance. We developed an Android mobile OS based application and pilot tested its effect on compliance with treatment in patients with CKD.

Methods:

The study was planned in two phases. Phase 1 was development and initial testing of mobile application designed to track compliance with treatment regimen. The conceptual flow is shown in figure 1. Phase 2 was open-label randomized controlled trial that randomized patients with CKD stage G3-4 patients into two groups: Control group receiving standard care and intervention group using mobile application developed in Phase 1 in addition to standard of care. The duration of the clinical trial was 3 months. As shown in figure 1, data regarding compliance and reasons for non-compliance were recorded at 03 months. Compliance was calculated as % of drugs taken by patient relative to prescribed quantity for 3 months. It was calculated from prescribed quantity, bought quantity (from pharmacy) and unused medication in strips/bottles remaining at the end of 3 months. Causes for non-compliance were collated through unstructured interview at the end of 3 months in control group. In the intervention group, real time data collected through mobile application regarding compliance were available, in addition. Primary outcome was difference in overall compliance (average of compliance for all prescribed drugs) between groups. Secondary outcome were reasons for non-compliance and irregular usage of mobile application. We planned to enroll 50 patients in the pilot phase. A difference of 10% in overall compliance was presumed to be clinically significant to decide on further testing of the intervention. 

Results:

Out of 152 patients who were screened, 50 were enrolled (Figure 2). Baseline characteristics of two groups are shown in table 1. Overall compliance was 82.4% in the intervention group as compared to 63.3% in the control group. The most common causes of non-compliance were unavailability of prescribed brands and high medication costs. Causes as reported by the study participants are reflected in table 2. In the intervention group, 88% of patients responded to notifications at least once. Cumulative non-response for >15 days over 3-month period was recorded in 92%. Only 8% of patients achieved a response rate >70% with the app notifications. Common reasons for decreased usage of the app included mobile phone glitches, mobile app software glitches, difficulty in adding/editing medication in the app, unavailability of the mobile for the response to notification and inadvertent swiping out of the notification rather than registering response as shown in table 3.

Conclusions:

Overall compliance with prescribed treatment was higher in the intervention group. Financial constraints continue to be a major factor leading to non-compliance in low resource settings. Larger studies with extended follow-up are needed to validate these results and uncover further benefits.

I have no potential conflict of interest to disclose.

I did not use generative AI and AI-assisted technologies in the writing process.