Risk adjustment as a mechanism to refine procedure-based payments to hospitals


In Israel to date, according to the Price and Services Supervision Order, every surgical procedure for which the health plans pay hospitals has one price in the Ministry of Health (PRG) tariff. This price does not reflect the large variation in costs between patients, but rather compensates for the average cost. This payment mechanism does not reward the hospitals in a way that incentivizes them to provide the best possible care within the framework of the resources available to them and harms hospitals that treat the more complex cases without adequate compensation. The average price method also creates an incentive to cream-skim, both within the public system and in the private system relative to the public system that can also perform surgeries with public funding since 2017.


To develop a compensation mechanism based on the existing mechanism that includes ex-ante risk adjustment methods that adjusts hospitals’ prices by case-complexity.  Such a mechanism is expected to promote more precise accounting regarding the current situation between the health-plans and hospitals, reduce the incentive to cream-skim non-complex patients versus more complex patients, and lead to improved efficiency of the system.

Our model is currently being discussed for implementation as part of a pilot project for seven procedures in the cardiac surgery system: valve surgery, bypass surgery, valve & bypass surgery, defect repair, ventricular septum repair, interascent septum repair, and membrane and heart tissue surgeries.


The study developed a model that categorizes surgical procedures (PRGs) according to several indicators of case complexity (including treatment complexity and patient complexity) that affect hospital costs. The five-stage model calculates individual complexity scores for each patient, thus enabling the creation of differential price lists by groups that take into account the complexity of the case. To date, the model’s price lists have been created for age and gender groups. The data file included all cardiac patients who underwent publicly-funded surgery in public hospitals in 2014-2021 and in private hospitals in 2017-2021, for the set of procedures included in the pilot. Treatment complexity variables: urgent arrival at the hospital (as opposed to elective procedure), stay in intensive care longer than average, stay in other departments (other than intensive care) longer than average, mortality in hospital. Patient complexity variables: age, gender, the Charelson index of comorbidity (CCI). The complexity variables were selected based on a extensive literature review and their presence in the database.


Between 2014 and 2021, 46% of patients in the cardiac wards underwent bypass surgery, 27% underwent valve surgery and 7% underwent valve and bypass surgery. The rest underwent various other types of surgeries – defect repair, septum repair, and meninges and heart tissue surgeries.

A high degree of variation was found in the treatment complexity variables between the various procedures and according to the complexity of the patients. Accordingly, variation was found in the distribution of the individual complexity score according to these variables. The average complexity score was highest for patients who underwent the membrane and heart tissue procedure (2 times the average for all procedures), and the average lowest complexity score were received by patients who underwent the interascent septum repair procedure (one-fifth of the overall average). In the bypass and valve & bypass procedures, women scored a significantly higher average complexity score than men (more than 3 times).

The relationship between complexity score and age is not uniform across all procedures. In some procedures, middle age groups were more complex, and in others, complexity was found to be uniform throughout life.

Conclusion and recommendations

Compensation mechanisms represent one of the basic building blocks of any health system and are a powerful tool for policy makers to promote desired incentives t to enhance government policy. The research team has already made several recommendations to the Ministry of Health. Among other things, the team recommends applying the model to pilot procedures and updating and optimizing the model as treatment complexity variables and patient complexity variables are added to the ministry database. Finally, in any pricing model and standardization of procedures, data from the private system must also be included in the calculations in order to promote fairness and efficiency of the system. This is important because public hospitals handle more complex cases than private hospitals and do not receive adequate compensation.


Citing suggestion: Brammli-Greenberg, S., & Fialco, S. (2024). Risk adjustment as a mechanism to refine procedure-based payments to hospitals. S-227-24. Myers-JDC-Brookdale Institute. (Hebrew)