Explaining Differences in the Acceptability of 99DOTS, a Cell Phone–Based Strategy for Monitoring Adherence to Tuberculosis Medications: Qualitative Study of Patients and Health Care Providers
Autor: | Spurthi N Bhatt, Amit Khandewale, Chidiebere Onongaya, Ramnath Subbaraman, M Chiranjeevi, Beena E Thomas, Kenneth H. Mayer, Daksha Shah, Jessica E. Haberer, Murugesan Periyasamy, J Vignesh Kumar, Amith T. Galivanche, Geetha Ramachandran |
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Rok vydání: | 2020 |
Předmět: |
medicine.medical_specialty
Health Personnel education India Health Informatics Information technology Unified theory of acceptance and use of technology Medication Adherence 03 medical and health sciences 0302 clinical medicine Phone Health care Humans Medicine 030212 general & internal medicine mHealth Expectancy theory Original Paper mobile phone implementation science business.industry Public health Workload T58.5-58.64 tuberculosis 030228 respiratory system Family medicine Public aspects of medicine RA1-1270 business Cell Phone qualitative research Qualitative research |
Zdroj: | JMIR mHealth and uHealth JMIR mHealth and uHealth, Vol 8, Iss 7, p e16634 (2020) |
ISSN: | 2291-5222 |
DOI: | 10.2196/16634 |
Popis: | Background 99DOTS is a cell phone–based strategy for monitoring tuberculosis (TB) medication adherence that has been rolled out to more than 150,000 patients in India’s public health sector. A considerable proportion of patients stop using 99DOTS during therapy. Objective This study aims to understand reasons for variability in the acceptance and use of 99DOTS by TB patients and health care providers (HCPs). Methods We conducted qualitative interviews with individuals taking TB therapy in the government program in Chennai and Vellore (HIV-coinfected patients) and Mumbai (HIV-uninfected patients) across intensive and continuation treatment phases. We conducted interviews with HCPs who provide TB care, all of whom were involved in implementing 99DOTS. Interviews were transcribed, coded using a deductive approach, and analyzed with Dedoose 8.0.35 software (SocioCultural Research Consultants, LLC). The findings of the study were interpreted using the unified theory of acceptance and use of technology, which highlights 4 constructs associated with technology acceptance: performance expectancy, effort expectancy, social influences, and facilitating conditions. Results We conducted 62 interviews with patients with TB, of whom 30 (48%) were HIV coinfected, and 31 interviews with HCPs. Acceptance of 99DOTS by patients was variable. Greater patient acceptance was related to perceptions of improved patient-HCP relationships from increased phone communication, TB pill-taking habit formation due to SMS text messaging reminders, and reduced need to visit health facilities (performance expectancy); improved family involvement in TB care (social influences); and from 99DOTS leading HCPs to engage positively in patients’ care through increased outreach (facilitating conditions). Lower patient acceptance was related to perceptions of reduced face-to-face contact with HCPs (performance expectancy); problems with cell phone access, literacy, cellular signal, or technology fatigue (effort expectancy); high TB- and HIV-related stigma within the family (social influences); and poor counseling in 99DOTS by HCPs or perceptions that HCPs were not acting upon adherence data (facilitating conditions). Acceptance of 99DOTS by HCPs was generally high and related to perceptions that the 99DOTS adherence dashboard and patient-related SMS text messaging alerts improve quality of care, the efficiency of care, and the patient-HCP relationship (performance expectancy); that the dashboard is easy to use (effort expectancy); and that 99DOTS leads to better coordination among HCPs (social influences). However, HCPs described suboptimal facilitating conditions, including inadequate training of HCPs in 99DOTS, unequal changes in workload, and shortages of 99DOTS medication envelopes. Conclusions In India’s government TB program, 99DOTS had high acceptance by HCPs but variable acceptance by patients. Although some factors contributing to suboptimal patient acceptance are modifiable, other factors such as TB- and HIV-related stigma and poor cell phone accessibility, cellular signal, and literacy are more difficult to address. Screening for these barriers may facilitate targeting of 99DOTS to patients more likely to use this technology. |
Databáze: | OpenAIRE |
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