Estimating waiting times, patient flow, and waiting room occupancy density as part of tuberculosis infection prevention and control research in South African primary health care clinics

Aaron S Karat; Nicky McCreesh; Kathy Baisley; Indira Govender; Idriss I Kallon; Karina Kielmann; Hayley MacGregor; Anna Vassall; Tom A Yates; Alison D Grant

doi:10.1371/journal.pgph.0000684

Estimating waiting times, patient flow, and waiting room occupancy density as part of tuberculosis infection prevention and control research in South African primary health care clinics

PLOS Glob Public Health. 2022 Jul 20;2(7):e0000684. doi: 10.1371/journal.pgph.0000684. eCollection 2022.

Authors

Aaron S Karat^{1

2}, Nicky McCreesh¹, Kathy Baisley^{1

3}, Indira Govender¹, Idriss I Kallon^{4

5}, Karina Kielmann², Hayley MacGregor⁶, Anna Vassall¹, Tom A Yates⁷, Alison D Grant^{1

3

8}

Affiliations

¹ TB Centre, London School of Hygiene & Tropical Medicine, London, United Kingdom.
² The Institute for Global Health and Development, Queen Margaret University, Edinburgh, United Kingdom.
³ Africa Health Research Institute, School of Laboratory Medicine & Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
⁴ Division of Social and Behavioural Sciences, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
⁵ Centre for Evidence-Based Health Care, Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
⁶ The Institute of Development Studies, University of Sussex, Brighton, United Kingdom.
⁷ Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.
⁸ School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.

Abstract

Transmission of respiratory pathogens, such as Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2, is more likely during close, prolonged contact and when sharing a poorly ventilated space. Reducing overcrowding of health facilities is a recognised infection prevention and control (IPC) strategy; reliable estimates of waiting times and 'patient flow' would help guide implementation. As part of the Umoya omuhle study, we aimed to estimate clinic visit duration, time spent indoors versus outdoors, and occupancy density of waiting rooms in clinics in KwaZulu-Natal (KZN) and Western Cape (WC), South Africa. We used unique barcodes to track attendees' movements in 11 clinics, multiple imputation to estimate missing arrival and departure times, and mixed-effects linear regression to examine associations with visit duration. 2,903 attendees were included. Median visit duration was 2 hours 36 minutes (interquartile range [IQR] 01:36-3:43). Longer mean visit times were associated with being female (13.5 minutes longer than males; p<0.001) and attending with a baby (18.8 minutes longer than those without; p<0.01), and shorter mean times with later arrival (14.9 minutes shorter per hour after 0700; p<0.001). Overall, attendees spent more of their time indoors (median 95.6% [IQR 46-100]) than outdoors (2.5% [IQR 0-35]). Attendees at clinics with outdoor waiting areas spent a greater proportion (median 13.7% [IQR 1-75]) of their time outdoors. In two clinics in KZN (no appointment system), occupancy densities of ~2.0 persons/m2 were observed in smaller waiting rooms during busy periods. In one clinic in WC (appointment system, larger waiting areas), occupancy density did not exceed 1.0 persons/m2 despite higher overall attendance. In this study, longer waiting times were associated with early arrival, being female, and attending with a young child. Occupancy of waiting rooms varied substantially between rooms and over the clinic day. Light-touch estimation of occupancy density may help guide interventions to improve patient flow.

Copyright: © 2022 Karat et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Grants and funding

The support of the Economic and Social Research Council (UK) is gratefully acknowledged. The Umoya omuhle study is funded by the Antimicrobial Resistance Cross Council Initiative supported by the seven research councils in partnership with other funders including support from the GCRF (ref. ES/P008011/1). Additional support was received from The Bloomsbury SET (Research England; ref. CCF17-7779). TAY is funded via an NIHR Academic Clinical Fellowship and acknowledges support from the NIHR Imperial Biomedical Research Centre. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.