Incentivizing performance in health care: a rapid review, typology and qualitative study of unintended consequences

Abstract

Background Health systems are increasingly implementing policy-driven programs to incentivize performance using contracts, scorecards, rankings, rewards, and penalties. Studies of these “Performance Management” (PM) programs have identified unintended negative consequences. However, no single comprehensive typology of the negative and positive unintended consequences of PM in healthcare exists and most studies of unintended consequences were conducted in England or the United States. The aims of this study were: (1) To develop a comprehensive typology of unintended consequences of PM in healthcare, and (2) To describe multiple stakeholder perspectives of the unintended consequences of PM in cancer and renal care in Ontario, Canada. Methods We conducted a rapid review of unintended consequences of PM in healthcare (n = 41 papers) to develop a typology of unintended consequences. We then conducted a secondary analysis of data from a qualitative study involving semi-structured interviews with 147 participants involved with or impacted by a PM system used to oversee 40 care delivery networks in Ontario, Canada. Participants included administrators and clinical leads from the networks and the government agency managing the PM system. We undertook a hybrid inductive and deductive coding approach using the typology we developed from the rapid review. Results We present a comprehensive typology of 48 negative and positive unintended consequences of PM in healthcare, including five novel unintended consequences not previously identified or well-described in the literature. The typology is organized into two broad categories: unintended consequences on (1) organizations and providers and on (2) patients and patient care. The most common unintended consequences of PM identified in the literature were measure fixation, tunnel vision, and misrepresentation or gaming, while those most prominent in the qualitative data were administrative burden, insensitivity, reduced morale, and systemic dysfunction. We also found that unintended consequences of PM are often mutually reinforcing. Conclusions Our comprehensive typology provides a common language for discourse on unintended consequences and supports systematic, comparable analyses of unintended consequences across PM regimes and healthcare systems. Healthcare policymakers and managers can use the results of this study to inform the (re-)design and implementation of evidence-informed PM programs.

Unintended consequences of the 18-week referral to treatment standard in NHS England: a threshold analysis

“…A recently published review suggested inappropriate or sub-optimal care, reduction in patient-centred care and exacerbation of inequalities are some of the possible unintended negative consequences of threshold targets for patients. 17 …”

“…A recently published review suggested inappropriate or sub-optimal care, reduction in patient-centred care and exacerbation of inequalities are some of the possible unintended negative consequences of threshold targets for patients. 17 The second behaviour refers to how hospital trusts report the data used for measuring performance in relation to the target. A hospital trust may be encouraged to be more accurate in reporting its data or it could lead to a hospital trust manipulating its data to meet the target.…”

“…(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23) on May 25, 2024 by guest. Protected by copyright.http://qualitysafety.bmj.com/ BMJ Qual Saf: first published as 10.1136/bmjqs-2023-015949 on 5 September 2023.…”

An interrupted time-series analysis of the effects of withdrawal of financial incentives on diagnosis of atrial fibrillation as resolved. Does withdrawal of an incentive reverse its unintended effects?

“…Financial incentives have been observed to increase rates of diagnosis but can also have unintended effects. 17 , 18 The authors are aware of no other research investigating the effect of incentives or their withdrawal on diagnosis. Previous research has observed withdrawal of incentives leads to reduction in documented quality of care.…”

Clinical algorithms, racism, and “fairness” in healthcare: A case of bounded justice

“…For example, given that compensation is tied to performance on measures of quality of care, algorithms are often designed to target the quality measures themselves (e.g. reducing 30-day readmissions) as opposed to the underlying goal of improving patient outcomes (Cox et al, 2022; Li and Evans, 2022). Furthermore, the pursuit of profit in the U.S. healthcare system has contributed to the entrenchment of systemic barriers restricting patient access to care such as underinsurance, predatory debt collection, and high administrative costs for billing (Bai et al, 2021; Yearby et al, 2022).…”