It has been said that a surgeon’s skill and judgment account for between 80% and 90% of a patient’s outcome. (I believe this is true for both surgical and nonsurgical treatments.) Throw in a physician’s ability to listen and clearly communicate with patients, and I am sure we are approaching that 90% mark. That means that when we conduct randomized trials comparing two types of knee prostheses or fracture-fixation constructs, we are, in essence, scrutinizing only about 10% of the patient-outcome equation.
So how do we best evaluate the 90% of the outcome equation that is physician-dependent? With the advent of “bundled” episodes of care, the orthopaedic community has emphasized the need for risk-adjustment in evaluating surgeon performance. Clearly, there are certain patients who are at higher risk for worse outcomes than others, such as those with diabetes, nicotine abuse, advanced age, and less social support.
In the December 19. 2018 issue of The Journal, Thigpen et al. report on patient outcomes 6 months after arthroscopic rotator cuff repair in 995 patients treated by 34 surgeons. The authors evaluated patient-reported outcomes from all surgeons using both unadjusted and adjusted ASES change scores. The adjusted scores took into account about a dozen baseline patient characteristics, including symptom severity, functional and mental scores, medical comorbidities, and Workers’ Compensation status. Relative to performance rankings based on unadjusted data, risk adjustment significantly altered the rankings for 91% of the surgeons. According to the authors, these findings “underpin the importance of risk-adjustment approaches to accurately report surgeon performance.”
But what is of even greater interest to me is that risk adjustment led to positive increases in patient outcomes for some surgeons, while decreasing outcomes for other surgeons. Some of these outcome differences likely reflect each surgeon’s patient-selection biases, but in the words of the authors, the numbers strongly suggest “that there is a meaningful, distinguishable difference in patient outcomes between surgeons.”
What should we do with this data? In my opinion, surgeons in the lower 80% of the list, at least, ought to be engaging with the surgeons who demonstrated the highest adjusted performance scores to understand what is helping them obtain outcomes that are superior to everyone else’s. We owe it to our patients to understand what our personal outcomes are for at least the most common conditions we treat. I believe it borders on unethical behavior to quote patients outcome data of a procedure from the peer-reviewed literature when we have no idea how our personal results compare. Orthopaedic surgeons need to be more active in lobbying our groups and health systems to support best practices for clinical outcome data collection and reporting so we can, in turn, improve our care by adopting the best practices of the surgeons with the best outcomes.
Marc Swiontkowski, MD
In 2015, JBJS launched an “article exchange” collaboration with the Journal of Orthopaedic & Sports Physical Therapy (JOSPT) to support multidisciplinary integration, continuity of care, and excellent patient outcomes in orthopaedics and sports medicine.
During the month of August 2018, JBJS and OrthoBuzz readers will have open access to the JOSPT article titled “Impact of Risk Adjustment on Provider Ranking for Patients With Low Back Pain Receiving Physical Therapy.”
The authors’ findings confirmed their hypothesis that robust risk adjustment is essential for objective comparison of patient-reported outcomes and for accurately reflecting quality of care among patients treated for low back pain.
All you stats geeks out there will love the January 6, 2016 study in The Journal of Bone & Joint Surgery by Schilling and Bozic. We at OrthoBuzz are going to skip the gory statistical details for the most part and focus on the essential findings.
First the premise and purpose of the study: Because measuring and improving health care outcomes are nowadays top priorities, risk adjustment—methods to account for differences in patient characteristics across providers—has become a contentious issue. General risk-assessment models tend not to be well-tailored to orthopaedic procedures. So Schilling and Bozic developed a series of risk-adjustment models specific to 30-day morbidity and mortality following hip fracture repair (HFR), total hip arthroplasty (THA), and total knee arthroplasty (TKA). To develop their models, they used prospectively collected clinical data from the National Surgical Quality Improvement Program.
Here are the major findings: For THA and TKA, risk-adjustment models using age, sex, and American Society of Anesthesiologists (ASA) physical status classification were nearly as predictive as models using many additional covariates. HFR model discrimination improved with the addition of comorbidities and laboratory values. Vital signs did not improve model discrimination for any of the procedures.
The study confirms that it is possible to provide adequate risk adjustment for analyzing outcomes of these procedures using only a handful of the most predictive variables commonly available within the operative record. “More parsimonious models are a viable alternative when the adequacy of risk adjustment must be weighed against the cost and burden of large-scale data extraction from the clinical record,” the authors conclude.