Factors Associated With Loss to Follow-up During the First Year After Total Knee Arthroplasty.

Despite increased pressure to capture patient-reported outcome measures for at least 1 year following total joint arthroplasty (TJA), follow-up rates during the first year after TJA are typically lower than desired and may result in biased findings if data are not missing at random. We conducted a retrospective review of medical records of primary total knee arthroplasty patients treated by a single surgeon at an urban academic private hospital. Main measures were demographics (sex, age, race, and insurance), body mass index, travel distance to clinic, and the Knee Injury and Osteoarthritis Outcome Score (KOOS). Multivariable regression analyses were performed to identify patient characteristics associated with attendance at follow-up visits and predictors of attendance at 6-month follow-up. Among the 205 study patients, follow-up visit attendance declined from a high of 95.7% at day 14 to lows of 69.2% at 6 months and 64.4% at 1 year. Attendance at the previously scheduled follow-up visit was a statistically significant predictor of attendance at 3-month (P=.0015), 6-month (P=.0002), and 1-year (P<.0001) follow-up visits, and travel distance was significantly associated with attending the 1-year follow-up visit (P=.042). Patients with the most favorable KOOS Symptom, Pain, and Function in daily living subscale scores at 3-month follow-up were significantly less likely to attend the 6-month follow-up visit than patients with the least favorable KOOS scores. Prospective studies are needed to identify the full range of factors that may contribute to high rates of loss to follow-up after TJA, which should be of concern to researchers, clinicians, and hospitals. [Orthopedics. 2023;46(2):93-97.].

Quantifying Mediators of Racial Disparities in Knee Osteoarthritis Outcome Scores: A Cross-Sectional Analysis.

Studies on symptomatic osteoarthritis suggest that Black patients report worse pain and symptoms compared with White patients with osteoarthritis. In this study, we aimed to quantify the relationship among variables such as overall health and socioeconomic status that may contribute to disparities in patient-reported outcomes. METHODS: A total of 223 patients were enrolled. A mediation analysis was used to evaluate cross-sectional associations between race and the Knee injury and Osteoarthritis Outcome Score (KOOS) questionnaire, which was administered to patients prior to undergoing primary total knee arthroplasty. RESULTS: Black patients had worse KOOS pain, symptoms, and activities of daily living subscale scores than White patients. In our cohort, Black patients were younger, more likely to be female, and more likely to report lower educational status. We identified age, sex, Charlson Comorbidity Index, and education as partial mediators of racial disparities in KOOS subscale scores. Insurance status, deformity, radiographic (Kellgren-Lawrence) grade, C-reactive protein level, marital status, body mass index, and income did not show mediating effects. We found that, if age and sex were equal in both cohorts, the racial disparity in KOOS symptom scores would be reduced by 20.7% and 9.1%, respectively (95% confidence intervals [CIs], -5.1% to 47% and -5.5% to 26.3%). For KOOS pain scores, age and education level explained 18.9% and 5.1% of the racial disparity (95% CIs, -0.6% to 37% and -10.8% to 22.9%). Finally, for KOOS activities of daily living scores, education level explained 3.2% of the disparity (95% CI, -19.4% to 26.6%). CONCLUSIONS: No single factor in our study completely explained the racial disparity in KOOS scores, but our findings did suggest that several factors can combine to mediate this disparity in outcome scores. Quantification of variables that mediate racial disparity can help to build models for risk adjustment, pinpoint vulnerable populations, and identify primary points of intervention. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Objective Data Reveals Gender Preferences for Patients' Primary Care Physician.

BACKGROUND AND OBJECTIVES: Most studies based on self-reported data indicate that female patients more often than males have a same-gender preference for their primary care physician (PCP). Because self-reported preferences may not reflect true preferences, we analyzed objective data to investigate patients' preferences for PCP gender. METHODS: Analyses were performed on 2192 new patients seen within a university-based healthcare system by 13 PCPs (2 male, 11 female) during 2017. New patients were asked about their PCP gender preference when assigned a PCP. We compared the expected prevalence (proportion of males/females in overall patient population) and observed prevalence (gender distribution of patients for each PCP) by PCP gender. A mixed model with PCP as a random effect examined the odds of male and female patients being assigned a same-gender physician. RESULTS: The expected prevalence of new patients was 65% female and 35% male. The observed prevalence (95% confidence interval [CI]) of male patients among male and female PCPs was, respectively, 59.7% (49.0%-69.5%) and 28.0% (24.0%-32.4%), with neither CI containing the expected prevalence of male patients (35%). Similarly, the observed prevalence of female patients among male and female PCPs was, respectively, 40.3% (95% CI 30.5%-51.0%) and 72.0% (95% CI 67.6%-76.0%), with neither CI containing the expected prevalence of female patients (65%). CONCLUSIONS: Both male and female patients often preferred to see a same-gender PCP with this preference more pronounced in males. Future research should seek to clarify the relationships between patients' gender preferences, patient-physician gender concordance/discordance, patient satisfaction, and health outcomes.