4.3 Article

Medication Adherence Clubs: a potential solution to managing large numbers of stable patients with multiple chronic diseases in informal settlements

期刊

TROPICAL MEDICINE & INTERNATIONAL HEALTH
卷 20, 期 10, 页码 1265-1270

出版社

WILEY
DOI: 10.1111/tmi.12539

关键词

operational research; SORT IT; Hypertension; Diabetes Mellitus

资金

  1. MSF
  2. Department for International Development (DFID)
  3. WHO

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ObjectivesTo assess the care of hypertension, diabetes mellitus and/or HIV patients enrolled into Medication Adherence Clubs (MACs). MethodsRetrospective descriptive study was carried out using routinely collected programme data from a primary healthcare clinic at informal settlement in Nairobi, Kenya. All patients enrolled into MACs were selected for the study. MACs are nurse-facilitated mixed groups of 25-35 stable hypertension, diabetes mellitus and/or HIV patients who met quarterly to confirm their clinical stability, have brief health discussions and receive medication. Clinical officer reviewed MACs yearly, when a patient developed complications or no longer met stable criteria. ResultsA total of 1432 patients were enrolled into 47 clubs with 109 sessions conducted between August 2013 and August 2014. There were 1020 (71%) HIV and 412 (29%) non-communicable disease patients. Among those with NCD, 352 (85%) had hypertension and 60 (15%) had DM, while 12 had HIV concurrent with hypertension. A total of 2208 consultations were offloaded from regular clinic. During MAC attendance, blood pressure, weight and laboratory testing were completed correctly in 98-99% of consultations. Only 43 (2%) consultations required referral for clinical officer review before their routine yearly appointment. Loss to follow-up from the MACs was 3.5%. ConclusionsThis study demonstrates the feasibility and early efficacy of MACs for mixed chronic disease in a resource-limited setting. It supports burden reduction and flexibility of regular clinical review for stable patients. Further assessment regarding long-term outcomes of this model should be completed to increase confidence for deployment in similar contexts.

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