Medication adherence, recall periods and factors affecting it: A community‐based assessment on patients with chronic diseases in urban slums

• Published in: International journal of clinical practice (Esher) Vol. 75; no. 8; pp. e14316 - n/a
• Main Authors: Atal, Shubham, Ray, Avik, Ahmed, Shah Newaz, Singh, Pooja, Fatima, Zeenat, Sadasivam, Balakrishnan, Pakhare, Abhijit, Joshi, Ankur, Joshi, Rajnish
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.08.2021
• Subjects: Antihypertensives; Chronic illnesses; Diabetes; Diabetes mellitus; Hypertension; Medication adherence; Patient compliance
• ISSN: 1368-5031; 1742-1241; 1742-1241
• DOI: 10.1111/ijcp.14316

Objective To evaluate medication adherence, the effect of recall periods on self‐reported adherence and factors influencing medication adherence among patients of chronic diseases, such as hypertension and diabetes, particularly in the community. Methods A cross‐sectional cohort study was conducted among individuals with hypertension and/or diabetes coming as outpatients in community camps organised in a cluster of urban slums. Responses towards questions regarding self‐reported quantitative and qualitative adherence for one week and one month along with information on pill burden, socio‐demographic and other factors were recorded using a mobile application. Results Among 379 participants living in urban slum communities, who were prescribed anti‐hypertensive or oral anti‐diabetic medications previously, mean medication adherence over previous one week was 67.99% (standard deviation (SD) ± 38.32) and 6.87 (SD ± 3.62) on a ten‐point numeric scale. The medication adherence for one month showed a strong significantly positive correlation with that of 1 week for both percentage‐based (r = +0.910, 95% CI = 0.864 to 0.950, P < .0001) and Likert (ρ = +0.836, 95% CI = 0.803 to 0.863, P < .0001) scales. Age (r = 0.219, 95% CI = 0.120 to 0.313, P = .043) and pill burden (r = −0.231, 95% CI = −0.145 to −0.322, P < .0001) were found to significantly affect medication adherence. The odds of random blood sugar reduction were found to be significant (OR 1.98, 95% CI = 1.30 to 3.00, P = .001) with adequate adherence. A linear regression equation was developed to predict medication adherence percentage for a patient which was found to have 61.8% predictive power using multilayer perceptron modelling. Conclusion Overall, medication adherence was sub‐optimal. Adherence assessments can be reliably performed using either one week or one month recall periods. With further refinement and validation, the regression equation could prove to be a useful tool for physicians.