Does Hypothetical Centralization of Revision THA and TKA Exacerbate Existing Geographic or Demographic Disparities in Access to Care by Increased Patient Travel Distances or Times? A Large-database Study

Abstract Background Higher hospital volume is associated with lower rates of adverse outcomes after revision total joint arthroplasty (TJA). Centralizing revision TJA care to higher-volume hospitals might reduce early complication and readmission rates after revision TJA; however, the effect of centralizing revision TJA care on patient populations who are more likely to experience challenges with access to care is unknown. Questions/purposes (1) Does a hypothetical policy of transferring patients undergoing revision TJA from lower-to higher-volume hospitals increase patient travel distance and time? (2) Does a hypothetical policy of transferring patients undergoing revision TJA from lower- to higher-volume hospitals disproportionately affect travel distance or time in low income, rural, or racial/ethnic minority populations? Methods Using the Medicare Severity Diagnosis Related Groups 466-468, we identified 37,147 patients with inpatient stays undergoing revision TJA from 2008 to 2016 in the Statewide Planning and Research Cooperative System administrative database for New York State. Revisions with missing or out-of-state patient identifiers (3474 of 37,147) or those associated with closed or merged facilities (180 of 37,147) were excluded. We chose this database for our study because of relative advantages to other available databases: comprehensive catchment of all surgical procedures in New York State, regardless of payer; each patient can be followed across episodes of care and hospitals in New York State; and New York State has an excellent cross-section of hospital types for TJA, including rural and urban hospitals, critical access hospitals, and some of the highest-volume centers for TJA in the United States. We divided hospitals into quartiles based on the mean revision TJA volume. Overall, 80% (118 of 147) of hospitals were not for profit, 18% (26 of 147) were government owned, 78% (115 of 147) were located in urban areas, and 48% (70 of 147) had fewer than 200 beds. The mean patient age was 66 years old, 59% (19,888 of 33,493) of patients were females, 79% (26,376 of 33,493) were white, 82% (27,410 of 33,493) were elective admissions, and 56% (18,656 of 33,493) of admissions were from government insurance. Three policy scenarios were evaluated: transferring patients from the lowest 25% by volume hospitals, transferring patients in the lowest 50% by volume hospitals, and transferring patients in the lowest 75% by volume hospitals to the nearest higher-volume institution by distance. Patients who changed hospitals and travelled more than 60 miles or longer than 60 minutes with consideration for average traffic patterns after the policy was enacted were considered adversely affected. The secondary outcome of interest was the impact of the three centralization policies, as defined above, on lower-income, nonwhite, rural versus urban counties, and Hispanic ethnicity. Results Transferring patients from the lowest 25% by volume hospitals resulted in only one patient stay that was affected by an increase in travel distance and travel time. Transferring patients from the lowest 50% by volume hospitals resulted in 9% (3050 of 33,493) of patients being transferred, with only 1% (312 of 33,493) of patients affected by either an increased travel distance or travel time. Transferring patients from the lowest 75% by volume hospitals resulted in 28% (9323 of 33,493) of patients being transferred, with 2% (814 of 33,493) of patients affected by either an increased travel distance or travel time. Nonwhite patients were less likely to encounter an increased travel distance or time after being transferred from the lowest 50% by volume hospitals (odds ratio 0.31 [95% CI 0.15 to 0.65]; p = 0.002) or being transferred from the lowest 75% by volume hospitals (OR 0.10 [95% CI 0.07 to 0.15]; p < 0.001) than white patients were. Hispanic patients were more likely to experience increased travel distance or time after being transferred from the lowest 50% by volume hospitals (OR 12.3 [95% CI 5.04 to 30.2]; p < 0.001) and being transferred from the lowest 75% by volume hospitals (OR 3.24 [95% CI 2.24 to 4.68]; p < 0.001) than non-Hispanic patients were. Patients from a county with a lower median income were more likely to experience increased travel distances or time after being transferred from the lowest 50% by volume hospitals (OR 69.5 [95% CI 17.0 to 283]; p < 0.001) and being transferred from the lowest 75% by volume hospitals (OR 3.86 [95% CI 3.21 to 4.64]; p < 0.001) than patients from counties with a higher median income. Patients from rural counties were more likely to be affected after being transferred from the lowest 50% by volume hospitals (OR 98 [95% CI 49.6 to 192.2]; p < 0.001) and being transferred from the lowest 75% by volume hospitals (OR 11.7 [95% CI 9.89 to 14.0]; p < 0.001) than patients from urban counties. Conclusion Although centralizing revision TJA care to higher-volume institutions in New York State did not appear to increase the travel burden for most patients, policies that centralize revision TJA care will need to be carefully designed to minimize the disproportionate impact on patient populations that already face challenges with access to healthcare. Further studies should examine the feasibility of establishing centers of excellence designations for revision TJA, the effect of best practices adoption by lower volume institutions to improve revision TJA care, and the potential role of care-extending technology such as telemedicine to improve access to care to reduce the effects of travel distances on affected patient populations. Level of Evidence Level III, prognostic study.