We show that this sampling method is operationally more efficient than alternative methods (systematic and simple random sampling) in most primary health care settings. This bias can be removed by selecting the next patient who enters, rather than exits, the consultation room. We demonstrate mathematically that this method yields a biased sample: patients who spend a longer time with the clinician are overrepresented. ![]() Our 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. Literature review, mathematical derivation, and Monte Carlo simulations. (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. ![]() ![]() Geldsetzer, Pascal Fink, Günther Vaikath, Maria Bärnighausen, Till Sampling for Patient Exit Interviews: Assessment of Methods Using Mathematical Derivation and Computer Simulations.
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