UNASSIGNED: Reduced institutional postacute care has been associated with savings in alternative payment models. However, organizations may avoid voluntary participation if participation could threaten their own revenues.
UNASSIGNED: To characterize the association between hospital-skilled nursing facility (SNF) integration and participation in Medicare\'s Bundled Payments for Care Improvement Advanced (BPCI-A) program.
UNASSIGNED: This is a cross-sectional analysis of hospital participation in BPCI-A beginning with its launch in 2018. Each SNF-integrated hospital was matched with 2 nonintegrated hospitals for each of 4 episode-specific analyses. Fifteen hospital-level variables were used for matching: beds, case mix index, days, area SNF beds, metropolitan location, ownership, region, system membership, and teaching status. Hospitals were also matched on episode-specific volume, target price, and the interaction of target price and case mix. Episode-specific logistic models were estimated regressing hospital participation on integration and the previously listed variables. The marginal effect of integration on participation was then calculated. Analysis took place from August 2022 to May 2024.
UNASSIGNED: Hospital-SNF integration, as defined by common ownership and referral patterns and identified using cost reports, Medicare claims, and Provider Enrollment, Chain, and Ownership System records. Additional sources included records of target prices and participation, the Area Health Resources File, and the Compendium of US Health Systems.
UNASSIGNED: Participation in BPCI-A.
UNASSIGNED: In total, 1524 hospitals met criteria for inclusion in the hip and femur (HFP) analysis, 1825 were included in the major joint replacement of the lower extremity (MJRLE) analysis, 2018 were included in the sepsis analysis, and 1564, were included in the stroke-specific analysis. Across episodes, 191 HFP-eligible hospitals (12.5% of HFP-eligible hospitals), 302 MJRLE-eligible hospitals (16.5%), 327 sepsis-eligible hospitals (16.2%), and 185 sepsis-eligible hospitals (11.8%) were SNF integrated. In total, 79 hospitals (5.2%) participated in the HFP episode, 128 (7.0%) participated in the MJRLE episode, 204 (10.1%) participated in the sepsis episode, and 141 (9.0%) participated in the stroke episode. Integration was associated with a 4.7-percentage point decrease (95% CI, 2.4 to 6.9 percentage points) in participation in the MJRLE episode. There was no association between integration and participation for HFP (0.5-percentage point increase in participation moving from nonintegrated to integrated; 95% CI, -2.9 to 3.8 percentage points), sepsis (1.0-percentage point increase; 95% CI, -2.2 to 4.2 percentage points), and stroke (0.3-percentage point decrease; 95% CI, -3.1 to 3.8 percentage points).
UNASSIGNED: In this cross-sectional study, there was an uneven association between hospital-SNF integration and participation in Medicare\'s BPCI-A program. Other factors may be more consistent determinants of selection into voluntary payment reform.

This study aimed to improve the predictive accuracy of the Braden assessment for pressure injury risk in skilled nursing facilities (SNFs) by incorporating real-world data and training a survival model. A comprehensive analysis of 126 384 SNF stays and 62 253 in-house pressure injuries was conducted using a large calibrated wound database. This study employed a time-varying Cox Proportional Hazards model, focusing on variations in Braden scores, demographic data and the history of pressure injuries. Feature selection was executed through a forward-backward process to identify significant predictive factors. The study found that sensory and moisture Braden subscores were minimally contributive and were consequently discarded. The most significant predictors of increased pressure injury risk were identified as a recent (within 21 days) decrease in Braden score, low subscores in nutrition, friction and activity, and a history of pressure injuries. The model demonstrated a 10.4% increase in predictive accuracy compared with traditional Braden scores, indicating a significant improvement. The study suggests that disaggregating Braden scores and incorporating detailed wound histories and demographic data can substantially enhance the accuracy of pressure injury risk assessments in SNFs. This approach aligns with the evolving trend towards more personalized and detailed patient care. These findings propose a new direction in pressure injury risk assessment, potentially leading to more effective and individualized care strategies in SNFs. The study highlights the value of large-scale data in wound care, suggesting its potential to enhance quantitative approaches for pressure injury risk assessment and supporting more accurate, data-driven clinical decision-making.

OBJECTIVE: To provide information on the association between risk factors and the development of new or worsened stage 2 to 4 pressure injuries (PIs) in patients in long-term care hospitals (LTCHs), inpatient rehabilitation facilities (IRFs), and skilled nursing facilities (SNFs).
BACKGROUND: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and nurses with an interest in skin and wound care.
OBJECTIVE: After participating in this educational activity, the participant will:1. Compare the unadjusted PI incidence in SNF, IRF, and LTCH populations.2. Explain the extent to which the clinical risk factors of functional limitation (bed mobility), bowel incontinence, diabetes/peripheral vascular disease/peripheral arterial disease, and low body mass index are associated with new or worsened stage 2 to 4 PIs across the SNF, IRF, and LTCH populations.3. Compare the incidence of new or worsened stage 2 to 4 PI development in SNF, IRF, and LTCH populations associated with high body mass index, urinary incontinence, dual urinary and bowel incontinence, and advanced age.
UNASSIGNED:

To assess whether hospitals participating in Medicare\'s Bundled Payments for Care Improvement (BPCI) program for joint replacement changed their referral patterns to favor higher-quality skilled nursing facilities (SNFs).
Retrospective observational study using 2009-2015 inpatient and outpatient claims from a 20% sample of Medicare beneficiaries undergoing joint replacement in US hospitals (N = 146,074) linked with data from Medicare\'s BPCI program and Nursing Home Compare.
We ran fixed effect regression models regressing BPCI participation on hospital-SNF referral patterns (number of SNF discharges, number of SNF partners, and SNF referral concentration) and SNF quality (facility inspection survey rating, patient outcome rating, staffing rating, and registered nurse staffing rating).
We found that BPCI participation was associated with a decrease in the number of SNF referrals and no significant change in the number of SNF partners or concentration of SNF partners. BPCI participation was associated with discharge to SNFs with a higher patient outcome rating by 0.04 stars (95% CI, 0.04-0.26). BPCI participation was not associated with improvements in discharge to SNFs with a higher facility survey rating (95% CI, -0.03 to 0.11), staffing rating (95% CI, -0.07 to 0.04), or registered nurse staffing rating (95% CI, -0.09 to 0.02).
BPCI participation was associated with lower volume of SNF referrals and small increases in the quality of SNFs to which patients were discharged, without narrowing hospital-SNF referral networks.

BACKGROUND: Emerging evidence suggests that there is an increase in healthcare utilization (HCU) in patients due to Coronavirus Disease 2019 (COVID-19). We investigated the change in HCU pre and post hospitalization among patients discharged home from COVID-19 hospitalization for up to 9 months of follow up.
METHODS: This retrospective study from a United States cohort used Optum® de-identified Clinformatics Data Mart; it included adults discharged home post hospitalization with primary diagnosis of COVID-19 between April 2020 and March 2021. We evaluated HCU of patients 9 months pre and post -discharge from index hospitalization. We defined HCU as emergency department (ED), inpatient, outpatient (office), rehabilitation/skilled nursing facility (SNF), telemedicine visits, and length of stay, expressed as number of visits per 10,000 person-days.
RESULTS: We identified 63,161 patients discharged home after COVID-19 hospitalization. The cohort of patients was mostly white (58.8%) and women (53.7%), with mean age 72.4 (SD± 12) years. These patients were significantly more likely to have increased HCU in the 9 months post hospitalization compared to the 9 months prior. Patients had a 47%, 67%, 65%, and 51% increased risk of ED (rate ratio 1.47; 95% CI 1.45-1.49; p < .0001), rehabilitation (rate ratio 1.67; 95% CI 1.61-1.73; p < .0001), office (rate ratio1.65; 95% CI 1.64-1.65; p < .0001), and telemedicine visits (rate ratio 1.5; 95% CI 1.48-1.54; p < .0001), respectively. We also found significantly different rates of HCU for women compared to men (women have higher risk of ED, rehabilitation, and telemedicine visits but a lower risk of inpatient visits, length of stay, and office visits than men) and for patients who received care in the intensive care unit (ICU) vs those who did not (ICU patients had increased risk of ED, inpatient, office, and telemedicine visits and longer length of stay but a lower risk of rehabilitation visits). Outpatient (office) visits were the highest healthcare service utilized post discharge (64.5% increase). Finally, the risk of having an outpatient visit to any of the specialties studied significantly increased post discharge. Interestingly, the risk of requiring a visit to pulmonary medicine was the highest amongst the specialties studied (rate ratio 3.35, 95% CI 3.26-3.45, p < .0001).
CONCLUSIONS: HCU was higher after index hospitalization compared to 9 months prior among patients discharged home post-COVID-19 hospitalization. The increases in HCU may be driven by those patients who received care in the ICU.

OBJECTIVE: To explore how people with stroke, discharged to skilled nursing facilities before returning home, experience the chain of care and rehabilitation.
METHODS: Qualitative, semi-structured interview design.
METHODS: Thirteen stroke survivors discharged from a stroke unit to a skilled nursing facility before returning to independent living participated. Semi-structured telephone interviews were conducted 2-5 months after stroke and analysed with content analysis.
RESULTS: The analysis resulted in three categories, Organizational processes, critical and complex, Rehabilitation, the right support at the right time and Adaptation to the changed situation, with a total of 9 subcategories. The informants perceived low participation in planning and goalsetting and limited information. Support from the healthcare services was important to proceed with improvements although the amount of supported training varied. Factors hindering and facilitating managing everyday life were described, as well as lingering uncertainty of what the future would be like.
CONCLUSIONS: Support and rehabilitation as well as individuals\' needs varied, throughout the chain of care. To enable participation in the rehabilitation, assistance in setting goals and repeated information is warranted. Tailored care and rehabilitation throughout the chain of care should be provided, followed up at home, and coordinated for smooth transitions between organizations.

BACKGROUND: Both length of hospital stay and discharge to a skilled nursing facility are key drivers of total knee arthroplasty (TKA)-associated spending. Identifying patients who require increased postoperative care may improve expectation setting, discharge planning, and cost reduction. Balance deficits affect patients undergoing TKA and are critical to recovery. We aimed to assess whether a device that measures preoperative balance predicts patients\' rehabilitation needs and outcomes after TKA.
METHODS: 40 patients indicated for primary TKA were prospectively enrolled and followed for 12 months. Demographics, KOOS-JR, and PROMIS data were collected at baseline, 3-months, and 12-months. Single-leg balance and sway velocity were assessed preoperatively with a force plate (Sparta Science, Menlo Park, CA). The primary outcome was patients\' discharge facility (home versus skilled nursing facility). Secondary outcomes included length of hospital stay, KOOS-JR scores, and PROMIS scores.
RESULTS: The mean preoperative sway velocity for the operative leg was 5.7 ± 2.7 cm/s, which did not differ from that of the non-operative leg (5.7 ± 2.6 cm/s, p = 1.00). Five patients (13%) were discharged to a skilled nursing facility and the mean length of hospital stay was 2.8 ± 1.5 days. Sway velocity was not associated with discharge to a skilled nursing facility (odds ratio, OR = 0.82, 95% CI = 0.27-2.11, p = 0.690) or longer length of hospital stay (b = -0.03, SE = 0.10, p = 0.738). An increased sway velocity was associated with change in PROMIS items from baseline to 3 months for global07 (\"How would you rate your pain on average?\" b = 1.17, SE = 0.46, p = 0.015) and pain21 (\"What is your level of pain right now?\" b = 0.39, SE = 0.17, p = 0.025) at 3-months.
CONCLUSIONS: Preoperative balance deficits were associated with postoperative improvements in pain and function after TKA, but a balance focused biometric that measured single-leg sway preoperatively did not predict discharge to a skilled nursing facility or length of hospital stay after TKA making their routine measurement cost-ineffective.

BACKGROUND: General surgery procedures place stress on geriatric patients, and postdischarge care options should be evaluated. We compared the association of discharge to a skilled nursing facility (SNF) versus home on patient readmission.
METHODS: We retrospectively reviewed the Nationwide Readmission Database (2016-2019) and included patients ≥65 y who underwent a general surgery procedure between January and September. Our primary outcome was 30-d readmissions. Our secondary outcome was predictors of readmission after discharge to an SNF. We performed a 1:1 propensity-matched analysis adjusting for patient demographics and hospital course to compare patients discharged to an SNF with patients discharged home. We performed a sensitivity analysis on patients undergoing emergency procedures and a stepwise regression to identify predictors of readmission.
RESULTS: Among 140,056 included patients, 33,916 (24.2%) were discharged to an SNF. In the matched population of 19,763 pairs, 30-d readmission was higher in patients discharged to an SNF. The most common diagnosis at readmission was sepsis, and a greater proportion of patients discharged to an SNF were readmitted for sepsis. In the sensitivity analysis, emergency surgery patients discharged to an SNF had higher 30-d readmission. Higher illness severity during the index admission and living in a small or fringe county of a large metropolitan area were among the predictors of readmission in patients discharged to an SNF, while high household income was protective.
CONCLUSIONS: Discharge to an SNF compared to patients discharged home was associated with a higher readmission. Future studies need to identify the patient and facility factors responsible for this disparity.

BACKGROUND: Nearly 2.9 million older Americans with lower incomes live in subsidized housing. While regional and single-site studies show that this group has higher rates of healthcare utilization compared to older adults in the general community, little is known about healthcare utilization nationally nor associated risk factors.
METHODS: We conducted a retrospective cohort study of Medicare beneficiaries aged ≥65 enrolled in the National Health and Aging Trends Study in 2011, linked to Medicare claims data, including individuals living in subsidized housing and the general community. Participants were followed annually through 2020. Outcomes were hospitalization, short-term skilled nursing facility (SNF) utilization, long-term care utilization, and death. Fine-Gray competing risks regression analysis was used to assess the association of subsidized housing residence with hospitalization and nursing facility utilization, and Cox proportional hazards regression analysis was used to assess the association with death.
RESULTS: Among 6294 participants (3600 women, 2694 men; mean age, 75.5 years [SD, 7.0]), 295 lived in subsidized housing at baseline and 5999 in the general community. Compared to older adults in the general community, those in subsidized housing had a higher adjusted subdistribution hazard ratio [sHR] of hospitalization (sHR 1.21; 95% CI, 1.03-1.43), short-term SNF utilization (sHR 1.49; 95% CI, 1.15-1.92), and long-term care utilization (sHR 2.72; 95% CI, 1.67-4.43), but similar hazard of death (HR, 0.86; 95% CI, 0.69-1.08). Individuals with functional impairment had a higher adjusted subdistribution hazard of hospitalization and short-term SNF utilization and individuals with dementia and functional impairment had a higher hazard of long-term care utilization.
CONCLUSIONS: Older adults living in subsidized housing have higher hazards of hospitalization and nursing facility utilization compared to those in the general community. Housing-based interventions to optimize aging in place and mitigate risk of nursing facility utilization should consider risk factors including functional impairment and dementia.

OBJECTIVE: Existing research has associated nursing home (NH) staff turnover with poor performance, yet the impact of nursing home administrator (NHA) turnover remains relatively understudied. This study aimed to explore the relationship between NHA turnover and NH quality, and to determine if this relationship was mediated by registered nurse (RN) turnover.
METHODS: Utilizing data from multiple secondary sources, including the Care Compare: Skilled Nursing Facility Quality Reporting Program (SNF QRP) and LTCFocus.org, this study employed a longitudinal analysis covering the period 2021-2022 (n = 19,645). The dependent variable was quality star ratings from SNF QRP, whereas the independent variable was NHA turnover, reflecting the number of administrators who left each facility annually. We used Baron and Kenny\'s mediation testing method, incorporating 2-way fixed effects (state and year level) with appropriate organizational and market level control variables.
RESULTS: The results affirmed that NHA turnover negatively affected quality, decreasing the likelihood of a higher star rating by 14% with one departure and 25% with multiple departures (p = .001). Additionally, NHA turnover correlated with an increase in RN turnover by 7% and 11%, respectively, for one and multiple departures (p = .001). RN turnover fully mediated the impact of NHA turnover on quality, nullifying the direct effect of NHA turnover.
CONCLUSIONS: The results of this study highlight the synergistic relationship between administrators and caregivers in NHs. To enhance NHA retention, NHs should improve compensation and benefits. Nonetheless, broader governmental support and interventions might be necessary to sustain these improvements.