OBJECTIVE: To determine if a tiered hospital benefit and safety incentive shifted the distribution of admissions toward safer hospitals. DATA SOURCES/STUDY SETTING: A large manufacturing company instituted the hospital safety incentive (HSI) for union employees. The HSI gave union patients a financial incentive to choose hospitals that met the Leapfrog Group's three patient safety "leaps." The analysis merges data from four sources: claims and enrollment data from the company, the American Hospital Association, the AHRQ HCUP-SID, and a state Office of the Insurance Commissioner. STUDY DESIGN: Changes in hospital admissions' patterns for union and nonunion employees using a difference-in-difference design. We estimate the probability of choosing a specific hospital from a set of available alternatives using conditional logistic regression. PRINCIPAL FINDINGS: Patients affiliated with the engineers' union and admitted for a medical diagnosis were 2.92 times more likely to select a hospital designated as safer in the postperiod than in the preperiod, while salaried nonunion (SNU) patients (not subject to the financial incentive) were 0.64 times as likely to choose a compliant hospital in the post- versus preperiod. The difference-in-difference estimate, which is based on the predictions of the conditional logit model, is 0.20. However, the machinists' union was also exposed to the incentive and they were no more likely to choose a safer hospital than the SNU patients. The incentive did not have an effect on patients admitted for a surgical diagnosis, regardless of union status. All patients were averse to travel time, but those union patients selecting an incentive hospital were less averse to travel time. CONCLUSIONS: Patient price incentives and quality/safety information may influence hospital selection decisions, particularly for medical admissions, though the optimal incentive level for financial return to the plan sponsor is not clear.
OBJECTIVE: To determine if a tiered hospital benefit and safety incentive shifted the distribution of admissions toward safer hospitals. DATA SOURCES/STUDY SETTING: A large manufacturing company instituted the hospital safety incentive (HSI) for union employees. The HSI gave union patients a financial incentive to choose hospitals that met the Leapfrog Group's three patient safety "leaps." The analysis merges data from four sources: claims and enrollment data from the company, the American Hospital Association, the AHRQ HCUP-SID, and a state Office of the Insurance Commissioner. STUDY DESIGN: Changes in hospital admissions' patterns for union and nonunion employees using a difference-in-difference design. We estimate the probability of choosing a specific hospital from a set of available alternatives using conditional logistic regression. PRINCIPAL FINDINGS:Patients affiliated with the engineers' union and admitted for a medical diagnosis were 2.92 times more likely to select a hospital designated as safer in the postperiod than in the preperiod, while salaried nonunion (SNU) patients (not subject to the financial incentive) were 0.64 times as likely to choose a compliant hospital in the post- versus preperiod. The difference-in-difference estimate, which is based on the predictions of the conditional logit model, is 0.20. However, the machinists' union was also exposed to the incentive and they were no more likely to choose a safer hospital than the SNU patients. The incentive did not have an effect on patients admitted for a surgical diagnosis, regardless of union status. All patients were averse to travel time, but those union patients selecting an incentive hospital were less averse to travel time. CONCLUSIONS:Patient price incentives and quality/safety information may influence hospital selection decisions, particularly for medical admissions, though the optimal incentive level for financial return to the plan sponsor is not clear.
Authors: Dana P Goldman; Geoffrey F Joyce; Jose J Escarce; Jennifer E Pace; Matthew D Solomon; Marianne Laouri; Pamela B Landsman; Steven M Teutsch Journal: JAMA Date: 2004-05-19 Impact factor: 56.272
Authors: Richard C Lindrooth; R Tamara Konetzka; Amol S Navathe; Jingsan Zhu; Wei Chen; Kevin Volpp Journal: Health Serv Res Date: 2013-01-24 Impact factor: 3.734