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METHODOLOGY
Open Access

Strategies for Optimal Implementation of Simulated Clients for Measuring Quality of Care in Low- and Middle-Income Countries

Anne Fitzpatrick and Katherine Tumlinson
Global Health: Science and Practice January 2017, GHSP-D-16-00266; https://doi.org/10.9745/GHSP-D-16-00266
Anne Fitzpatrick
aDepartment of Economics, University of Massachusetts-Boston, Boston, MA, USA.
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  • For correspondence: Anne.Fitzpatrick{at}umb.edu
Katherine Tumlinson
bThe Office of Population Research, Wallace Hall, Princeton University, Princeton, NJ, USA. Now with the Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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When properly implemented, use of simulated clients (“mystery clients”) can provide insight into actual experiences of real clients and evaluate quality of care. Successful implementation calls for recruiting mystery clients who represent the facility’s clientele, have strong recall of recent events, and are comfortable being undercover data collectors. Developing training protocols and checklists to standardize mystery client behavior and responses is also key.

ABSTRACT

The use of simulated clients or “mystery clients” is a data collection approach in which a study team member presents at a health care facility or outlet pretending to be a real customer, patient, or client. Following the visit, the shopper records her observations. The use of mystery clients can overcome challenges of obtaining accurate measures of health care quality and improve the validity of quality assessments, particularly in low- and middle-income countries. However, mystery client studies should be carefully designed and monitored to avoid problems inherent to this data collection approach. In this article, we discuss our experiences with the mystery client methodology in studies conducted in public- and private-sector health facilities in Kenya and in private-sector facilities in Uganda. We identify both the benefits and the challenges in using this methodology to guide other researchers interested in using this technique. Recruitment of appropriate mystery clients who accurately represent the facility’s clientele, have strong recall of recent events, and are comfortable in their role as undercover data collectors are key to successful implementation of this methodology. Additionally, developing detailed training protocols can help ensure mystery clients behave identically and mimic real patrons accurately while short checklists can help ensure mystery client responses are standardized. Strict confidentiality and protocols to avoid unnecessary exams or procedures should also be stressed during training and monitored carefully throughout the study. Despite these challenges, researchers should consider mystery client designs to measure actual provider behavior and to supplement self-reported provider behavior. Data from mystery client studies can provide critical insight into the quality of service provision unavailable from other data collection methods. The unique information available from the mystery client approach far outweighs the cost.

  • Received: 2016 Aug 16.
  • Accepted: 2016 Nov 22.
  • © Fitzpatrick and Tumlinson.

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 properly cited. To view a copy of the license, visit http://creativecommons.org/licenses/by/3.0/. When linking to this article, please use the following permanent link: https://doi.org/10.9745/GHSP-D-16-00266

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Global Health: Science and Practice: 13 (2)
Global Health: Science and Practice
Vol. 13, No. 2
December 31, 2025
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Strategies for Optimal Implementation of Simulated Clients for Measuring Quality of Care in Low- and Middle-Income Countries
Anne Fitzpatrick, Katherine Tumlinson
Global Health: Science and Practice Jan 2017, GHSP-D-16-00266; DOI: 10.9745/GHSP-D-16-00266

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Strategies for Optimal Implementation of Simulated Clients for Measuring Quality of Care in Low- and Middle-Income Countries
Anne Fitzpatrick, Katherine Tumlinson
Global Health: Science and Practice Jan 2017, GHSP-D-16-00266; DOI: 10.9745/GHSP-D-16-00266
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