Scores derived from comorbidities can help with risk adjustment of quality and safety data. The Charlson and Elixhauser comorbidity measures are well-known risk adjustment models, yet the optimal score for orthopaedic patients remains unclear.

Many patients having discretionary orthopaedic surgery take opioids daily, either with a prescription or illicitly, however little is known regarding the prevalence and effect of high-risk opioid use (eg, abuse, dependence) in the perioperative orthopaedic setting.

In the midst of rapid expansion of medical knowledge and decision-support tools intended to benefit diverse patients, patients with limited health literacy (the ability to obtain, process, and understand information and services to make health decisions) will benefit from asking questions and engaging actively in their own care. But little is known regarding the relationship between health literacy and question-asking behavior during outpatient office visits.

Background: Lower-extremity arthroplasty constitutes the largest burden on health-care spending of any Medicare diagnosis group. Demand for upper extremity arthroplasty also continues to rise. It is necessary to better understand costs as health care shifts toward a bundled-payment accounting approach. We aimed (1) to identify whether variation exists in total cost for different types of joint arthroplasty, and, if so, (2) to determine which cost parameters drive this variation. Methods: The cost of the episode of inpatient care for 22,215 total joint arthroplasties was calculated by implementing time-driven activity-based costing (TDABC) at a single orthopaedic specialty hospital from 2015 to 2018. Implant price, supply costs, personnel costs, and length of stay for total knee, total hip, anatomic total shoulder, reverse total shoulder, total elbow, and total ankle arthroplasty were analyzed. Individual cost parameters were compared with total cost and volume. Results: Higher implant cost appeared to correlate with higher total costs and represented 53.8% of the total cost for an inpatient care cycle. Total knee arthroplasty was the least-expensive and highest-volume procedure, whereas total elbow arthroplasty had the lowest volume and highest cost (1.65 times more than that of total knee arthroplasty). Length of stay was correlated with increased personnel cost but did not have a significant effect on total cost. Conclusions: Total inpatient cost at our orthopaedic specialty hospital varied by up to a factor of 1.65 between different fields of arthroplasty. The highest-volume procedures—total knee and hip arthroplasty—were the least expensive, driven predominantly by lower implant purchase prices. Clinical Relevance: We are not aware of any previous studies that have accurately compared cost structures across upper and lower-extremity arthroplasty with a uniform methodology. The present study, because of its uniform accounting process, provides reliable data that will allow clinicians to better understand cost relationships between different procedures.

Background: As payment models shift toward a focus on value, an accurate understanding of surgical costs and preoperative correlates of high-cost patients is important for effective implementation of cost-saving strategies. This study used time-driven activity-based costing (TDABC) to explore inpatient cost of total shoulder arthroplasty (TSA) and to identify preoperative characteristics of high-cost patients. Methods: Using TDABC, we calculated the cost of inpatient care for 415 patients undergoing elective primary TSA between 2016 and 2017. Patients in the top decile of cost were defined as high-cost patients. Multivariable logistic regression modeling was employed to determine preoperative characteristics (e.g., demographics, comorbidities, American Society of Anesthesiologists [ASA] score, and American Shoulder and Elbow Surgeons [ASES] score) associated with high-cost patients. Results: Implant purchase price was the main driver (57%) of total inpatient costs, followed by personnel cost from patient check-in through the time in the operating room (20%). There was a 1.3-fold variation in total cost between patients in the 90th percentile for cost and those in the 10th percentile; the widest cost variation was in personnel cost from the post-anesthesia care unit through discharge (2.5-fold) and in medication cost (2.4-fold). High-cost patients were more likely to be women and chronic opioid users and to have diabetes, depression, an ASA score of ≥3, a higher body mass index (BMI), and a lower preoperative ASES score than non-high-cost patients. After multivariable adjustment, the 3 predictors of high-cost patients were female sex, an ASA score of ≥3, and a lower ASES score. Total inpatient cost correlated strongly with the length of the hospital stay but did not correlate with operative time. Conclusions: Our study provides actionable data to contain costs in the perioperative TSA setting. From the hospital’s perspective, efforts to reduce implant purchase prices may translate into rapid substantial cost savings. At the patient level, multidisciplinary initiatives aimed at reducing length of stay and controlling medication expenses for patients at risk for high cost (e.g., infirm women with poor preoperative shoulder function) may prove effective in narrowing the existing patient-to-patient variation in costs. Level of Evidence: Economic and Decision Analysis Level IV. See Instructions for Authors for a complete description of levels of evidence.

As payment models shift toward a focus on value and reimbursement becomes increasingly tied to quality and patient experience, minimizing unexpected acute health needs has become a priority for both policymakers and clinical leaders. Despite recent emphasis on emergency department (ED) visits as a quality measure in surgery, little is known about the role of the ED in the early postoperative period after hand surgery.