4.1 Article

The feasibility of novel point-of-care diagnostics for febrile illnesses at health centres in Southeast Asia: a mixed-methods study

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OXFORD UNIV PRESS
DOI: 10.1093/trstmh/trad036

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feasibility; febrile illnesses; health centres; point-of-care diagnostics

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This study aimed to assess the feasibility of using point-of-care tests to diagnose acute febrile illnesses in primary care settings. The results showed that all three point-of-care tests performed well under assessment, but sample collection for the dengue test was difficult. Health workers found the diagnostics useful but not as convenient as standard malaria rapid tests.
Background The decline of malaria in Southeast Asia means other causes of fever are increasingly relevant, but often undiagnosed. The objective of this study was to assess the feasibility of point-of-care tests to diagnose acute febrile illnesses in primary care settings. Methods A mixed-methods study was conducted at nine rural health centres in western Cambodia. Workshops introduced health workers to the STANDARD(TM) Q Dengue Duo, STANDARD(TM) Q Malaria/CRP Duo and a multiplex biosensor detecting antibodies and/or antigens of eight pathogens. Sixteen structured observation checklists assessed users' performances and nine focus group discussions explored their opinions. Results All three point-of-care tests were performed well under assessment, but sample collection was difficult for the dengue test. Respondents expressed that the diagnostics were useful and could be integrated into routine clinical care, but were not as convenient to perform as standard malaria rapid tests. Health workers recommended that the most valued point-of-care tests would directly inform clinical management (e.g. a decision to refer a patient or to provide/withhold antibiotics). Conclusions Deployment of new point-of-care tests to health centres could be feasible and acceptable if they are user-friendly, selected for locally circulating pathogens and are accompanied by disease-specific education and simple management algorithms.

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