Risk-Standardized PAC Rates (RSPR)

Measuring the quality of care reliably, across care settings, and for a multititude of conditions, illnesses and treatments, is now possible thanks to our risk-standardized PAC rate measure -- RSPR.

Developed over a decade, potentially avoidable complications are negative events that can cause some harm to patients and add costs to an episode of care. To build the RSPR we first count the frequency with which PACs occur across patients who have a particular episode. For example, assume that a physician is treating patients with diabetes and that one third of those patients end up by having a potentially avoidable complication related to their diabetes. That physician's PAC rate will be 33.33%. Of course, that physician's patients may have more complex forms of diabetes, may be older and have other related conditions. We therefore adjust that PAC rate for the severity of patients, which may bring the severity adjusted PAC rate to 25%. But by itself, that number may not mean much. To understand whether that rate is better, the same, or worse than that of other physicians who treat patients with diabetes, we have to normalize the rate, index it, and create a risk-stratified rate that performs as a true comparitive measure of quality. Further, the measure must then be tested for its reliability, meaning that the measure must distinguish one physician's performance from another. The reliability test provides a minimum threshold of patients, below which the measurement is not reliable. Staying with our example, let's assume that the reliability test yields a minimum threshold of 50 patients. That means only physicians (or physician practices, health systems, ACOs) with at least 50 patients would have a reported measure. And finally, those being measured are stratified into three groups -- above average, average, and below average.

The net result of all those calculations is a graph illustrated by the figure below where each dot in the line represents a physician being measured, those above the blue box have a higher than average RSPR and those below have a lower one. In this measure, lower is better because it measn fewer avoidable complications.


Like most measures of quality, the RSPR should be used in conjunction with pricing information to more fully inform consumers and others. The advantage of the PROMETHEUS Analytics is that it can do both. It can generate a RSPR and a severity adjusted episode price for any given physician, practice, hospital, health system or ACO. As illustrated in the graph below, which was generated from information from the New Hampshire all-payer claims database, and looking at the RSPR and price for facilities performing hysterectomies, there are some facilities that have a low RSPR and average price, some that have a low price but average RSPR, and some that have high prices and high RSPRs. Without the combination of the information, a consumer-patient could end up making a wrong decision on where to seek care.

This method is being used by the state of Maryland in its public website on price and quality transparency, WearTheCost.org and we encourage you to see this method in action.

And for more information and details on the methodology, please review the Issue Brief below.


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