ArticleHealth services research2018
Sampling for Patient Exit Interviews: Assessment of Methods Using Mathematical Derivation and Computer Simulations.
Article in Health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- The Impact of Immediate Initiation of Antiretroviral Therapy on Patients' Healthcare Expenditures: A Stepped-Wedge Randomized Trial in Eswatini.AIDS and behavior · 2021Trial
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- The impact of community health worker-led home delivery of antiretroviral therapy on virological suppression: a non-inferiority cluster-randomized health systems trial in Dar es Salaam, Tanzania.BMC health services research · 2017Trial
- Patient's willingness to pay for improved community health insurance in Tanzania.Health policy OPEN · 2024Article
- Valuing Outpatients' Perspective on Primary Health Care Services in Greece: A Cross-Sectional Survey on Satisfaction and Personal-Centered Care.Healthcare (Basel, Switzerland) · 2024Article
- Article
- Article
- Out-of-pocket Expenses and Time Spent on Clinic Visits Among HIV Pre-exposure Prophylaxis Users and Other Clinic Attendees in Eswatini.AIDS and behavior · 2023Observational
- Clients satisfaction at primary healthcare facilities and its association with implementation of client service charter in Tanzania.PloS one · 2022Article
- Effect of Universal Health Coverage on the Availability of Medicines in Public Health Facilities in Kisumu County, in Kenya.Rwanda journal of medicine and health sciences · 2021Article
- Willingness to pay for community delivery of antiretroviral treatment in urban Tanzania: a cross-sectional survey.Health policy and planning · 2021Article
- Satisfaction with mental health and psycho-social support services provided to Syrians under temporary protection in Turkey, evidence from refugee health training centers.Journal of migration and health · 2020Article
- Evaluating Primary Health Care Performance from User Perspective in China: Review of Survey Instruments and Implementation Issues.International journal of environmental research and public health · 2019Review
- Preference for injectable over oral HIV pre-exposure prophylaxis in public-sector primary-care clinics in Swaziland.AIDS (London, England) · 2018Article
- Reaching endpoints for lymphatic filariasis elimination- results from mass drug administration and nocturnal blood surveys, South Gujarat, India.PLoS neglected tropical diseases · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objective(1) To evaluate the operational efficiency of various sampling methods for patient exit interviews; (2) to discuss under what circumstances each method yields an unbiased sample; and (3) to propose a new, operationally efficient, and unbiased sampling method. STUDY
designLiterature review, mathematical derivation, and Monte Carlo simulations. PRINCIPAL
findingsOur simulations show that in patient exit interviews it is most operationally efficient if the interviewer, after completing an interview, selects the next patient exiting the clinical consultation. We demonstrate mathematically that this method yields a biased sample: patients who spend a longer time with the clinician are overrepresented. This bias can be removed by selecting the next patient who enters, rather than exits, the consultation room. We show that this sampling method is operationally more efficient than alternative methods (systematic and simple random sampling) in most primary health care settings.
conclusionUnder the assumption that the order in which patients enter the consultation room is unrelated to the length of time spent with the clinician and the interviewer, selecting the next patient entering the consultation room tends to be the operationally most efficient unbiased sampling method for patient exit interviews.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.