There is growing interest in value-based healthcare in the United States. Statistical analysis of large databases can inform us of the factors associated with and the probability of adverse events and unplanned readmissions that diminish quality and add expense. Many surgeons rely on their knowledge and intuition when assessing the risk of a procedure. Comparing clinically driven with statistically derived risk models of total shoulder arthroplasty (TSA) offers insight into potential gaps between common practice and evidence-based medicine. We therefore asked: Does a statistically driven model better explain the variation in unplanned readmission or adverse events within 30 days of discharge when compared with a clinical model based on expert orthopaedic surgeon opinion?
Our study found that the clinically driven model found no risk factors and accounted for 1.4% of the variation in unplanned readmission and 0.95% of the variation in adverse events (1). In contrast, the statistically driven model explained 4.6% of the variation in unplanned readmission and found that operating time and hypertension requiring medications were associated with unplanned readmission accounting for all other factors. Model, age, men, operating time, and high blood urea nitrogen were associated with adverse events when accounting for all other factors, explaining 3.3% of the variation. However, neither the clinically driven model nor the statistically driven model provided much explanatory power.
The observation that a statistically derived risk model performs better than a clinically driven model affirms the value of research based on large databases, although the models derived need to be tested prospectively. Clinicians can utilize our results to understand that clinician intuition may not always offer the best risk adjustment and that factors impacting TSA unplanned readmission and adverse events may be best derived from large data sets. However, because current analyses explain limited variation in outcomes, future studies might look to better define what factors drive the variation in unplanned readmission and adverse events.
References
- Bernstein DN, Keswani A, Ring D. Perioperative Risk Adjustment for Total Shoulder Arthroplasty: Are Simple Clinically Driven Models Sufficient? Clin Orthop Relat Res. 2017 Dec;475(12):2867-2874. doi: 10.1007/s11999-016-5147-y. PubMed PMID: 27905060; PubMed Central PMCID: PMC5670040.