Professor Tolga Tezcan, London Business School
The Hospital Readmissions Reduction Program (HRRP) reduces Medicare payments to hospitals with higher than expected readmission rates where the expected readmission rate for each hospital is determined based on national average readmission levels.
Although similar relative performance based schemes are shown to lead to socially optimal outcomes in other settings, HRRP differs from these schemes in three respects:
- deviation from the targets are adjusted using a multiplier
- the total financial penalty for a hospital with higher-than-expected readmission rate is capped
- hospitals with lower-than-expected readmission rates do not receive bonus payments.
We study three regulatory schemes derived from HRRP to determine the impact of each feature, and use a principle-agent model to show that:
- HRRP over-penalises hospitals with excess readmissions because of the multiplier and its effect can be substantial
- having a penalty cap can curtail the effect of financial incentives and result in a no-equilibrium outcome when the cap is too low
- not allowing bonus payments leads to many alternative symmetric equilibria, including one where hospitals exert no effort to reduce readmissions.
These results show that HRRP does not provide the right incentives for hospitals to reduce readmissions.
Next we show that a bundled payment type reimbursement method, which reimburses hospitals once for each episode of care (including readmissions), leads to socially optimal cost and readmissions reduction efforts.
Finally we show that, when delays to accessing care are inevitable, the reimbursement schemes need to provide additional incentives for hospitals to invest sufficiently in capacity.
Tolga Tezcan is a Professor of Management Science and Operations at London Business School (LBS). He teaches courses in data mining and business analytics. Prior to joining LBS, he was a faculty member at Simon School of Business in University of Rochester between 2010 and 2015, where he was placed in the teaching honour roll in 2014, and at University of Illinois at Urbana-Champaign between 2006 and 2010.
Tolga holds a PhD in industrial and systems engineering and a MS in mathematics from Georgia Tech, a MS in industrial and systems engineering from Colorado State-Pueblo, and a BS in industrial engineering from Bilkent University, Turkey. Tolga’s research focuses on the robust management of service systems, such as customer service centres and healthcare systems, under uncertainty.
His research has appeared in leading journals such as Management Science, Operations Research, M&SOM, and Annals of Applied Probability.
He has received the Career Award from National Science Foundation (NSF) of USA in 2010.