Using Standardized Patients to Measure Health Care Quality

Measuring the quality of healthcare is a vexing problem: Quality is multidimensional and deficits in care can manifest as doing “too much” or “too little”. One way to address several outstanding problems in the measurement of quality is through the use of standardized patients – people recruited from local communities and extensively trained to depict the same conditions to multiple providers. The standardized patient methodology offers a unique strategy to assess health care quality: since providers see the “same” patient, confounders arising from differential patient and case-mix are better controlled for than when understanding health care quality through other methods, such as administrative data or medical records. Further, researchers know what illness the patient has; therefore, the performance of healthcare providers can be directly compared to national and international standards of care for that condition. The authors have developed expertise in the use of standardized patients in large-sample, population-based studies, particularly in India, China and Kenya. Based on that experience, this manual provides an overview of the use of standardized patients, extensive training material and methods, as well as detailed questionnaires, IRB applications, and a suite of material that can be used in future such studies.

This manual and its contents are the products of numerous individuals who have worked together across time and space to think through, iterate, and improve upon the fine details required for implementing standardized patients in low-resource settings. For their unwavering effort, openness in sharing their experiences, and answering countless questions, many thanks go to Ranendra K. Das, Rajan Singh, Purshottam, Vaibhav Saria, Chinar Singh, Geeta, Devender, Varun Kumar, Anand Kumar, Babloo, Charu Nanda, and the standardized patients at the Institute for Socio-Economic Research on Development and Democracy (ISERDD); Amy Dolinger at the International Finance Corporation (KePSIE Project); and Sean Sylvia, Alexis Medina, and Scott Rozelle at Stanford University (REAP). We are grateful to members of the Technical Advisory Groups of the Qutub Project in urban India and the KePSIE Project in Kenya for participating in the design, training, and implementation of SPs. We additionally thank Sabnam Mahmuda for editorial support and Brian Chan, Manoj Mohanan, Diana Tabak, and Alaka Holla of the MAQARI Project from which some of this material is based. The findings, interpretations, and conclusions expressed here are those of the authors and do not necessarily represent the views of the World Bank, its Executive Directors, or the governments they represent.