Maryland's Global Budget Revenue Payment Model and Shifts in the Surgical Site of Care Among Medicare Beneficiaries.

OBJECTIVE: To assess the association between the Global Budget Revenue (GBR) payment model and shifts to the outpatient setting for surgical procedures among Medicare fee-for-service beneficiaries in Maryland versus control states. SUMMARY BACKGROUND DATA: The GBR model provides fixed global payments to hospitals to reduce spending growth and incentivize hospitals to reduce the costs of care while improving care quality. Since surgical care is a major contributor to hospital spending, the GBR model might accelerate the ongoing shift from the inpatient to the outpatient setting to generate additional savings. METHODS: A difference-in-differences (DiD) design was used to compare changes in surgical care settings over time from pre-GBR (2011-2013) to post-GBR (2014-2018) for Maryland versus control states for common surgeries that could be performed in the outpatient setting. A cross-sectional approach was used to compare the difference in care settings in 2018 for total knee arthroplasty which was on Medicare's Inpatient-Only List before then. RESULTS: We studied 47,542 surgical procedures from 44,410 beneficiaries in Maryland and control states. GBR's 2014 implementation was associated with an acceleration in the shift from inpatient to outpatient settings for surgical procedures in Maryland (DiD: 3.9 percentage points, 95% CI: 2.3, 5.4). Among patients undergoing total knee arthroplasty in 2018, the proportion of outpatient surgeries in Maryland was substantially higher than that in control states (difference: 27.6 percentage points, 95% CI: 25.6, 29.6). CONCLUSIONS: Implementing Maryland's GBR payment model was associated with an acceleration in the shift from inpatient to outpatient hospital settings for surgical procedures.

A nationwide cross-sectional study on the association of patient-level factors with financial anxiety in the context of chronic medical conditions.

Patient-level characteristics associated with the prevalence and severity of financial anxiety have yet to be described. We conducted a cross-sectional analysis of survey data assessing financial anxiety in patients with chronic medical conditions in December 2020. 1771 patients (42.6% response rate) participated in the survey. Younger age (19-35 age compared to ≥ 75 age) (ß, 5.86; 95% CI 2.10-9.63), male sex (ß, - 1.9; 95% CI - 3.1 to - 0.73), Hispanic/Latino race/ethnicity (compared with White patients) (ß, 2.55; 95% CI 0.39-4.71), household size ≥ 4 (compare with single household) (ß, 4.54; 95% CI 2.44-6.64), household income of ≥ $96,000-$119,999 (compared with ≤ $23,999) (ß, - 3.2; 95% CI - 6.3 to 0.04), single marital status (compared with married) (ß, 2.18; 95% CI 0.65-3.71), unemployment (ß, 2.07; 95% CI 0.39-3.74), high-school education (compared with advanced degrees) (ß, 3.10; 95% CI 1.32-4.89), lack of insurance coverage (compared with private insurance) (ß, 6.05; 95% CI 2.66-9.45), more comorbidities (≥ 3 comorbidities compared to none) (ß, 2.95; 95% CI 1.00-4.90) were all independently associated with financial anxiety. Patients who are young, female, unmarried, and representing vulnerable sub-populations are at elevated risk for financial anxiety.

Trends in Episode-of-Care Spending for Cancer-Directed Surgery Among US Medicare Beneficiaries From 2011 to 2019.

This cross-sectional study examines trends in the number of cancer-directed surgeries from 2011 to 2019 among US patients aged 65 years or older and in Medicare spending for those surgeries overall and by inpatient vs outpatient sites of care.

Development and Assessment of Machine Learning Models for Individualized Risk Assessment of Mastectomy Skin Flap Necrosis.

OBJECTIVE: To develop, validate, and evaluate ML algorithms for predicting MSFN. BACKGROUND: MSFN is a devastating complication that causes significant distress to patients and physicians by prolonging recovery time, compromising surgical outcomes, and delaying adjuvant therapy. METHODS: We conducted comprehensive review of all consecutive patients who underwent mastectomy and immediate implant-based reconstruction from January 2018 to December 2019. Nine supervised ML algorithms were developed to predict MSFN. Patient data were partitioned into training (80%) and testing (20%) sets. RESULTS: We identified 694 mastectomies with immediate implant-based reconstruction in 481 patients. The patients had a mean age of 50 ± 11.5 years, years, a mean body mass index of 26.7 ± 4.8 kg/m 2 , and a median follow-up time of 16.1 (range, 11.9-23.2) months. MSFN developed in 6% (n = 40) of patients. The random forest model demonstrated the best discriminatory performance (area under curve, 0.70), achieved a mean accuracy of 89% (95% confidence interval, 83-94), and identified 10 predictors of MSFN. Decision curve analysis demonstrated that ML models have a superior net benefit regardless of the probability threshold. Higher body mass index, older age, hypertension, subpectoral device placement, nipple-sparing mastectomy, axillary nodal dissection, and no acellular dermal matrix use were all independently associated with a higher risk of MSFN. CONCLUSIONS: ML algorithms trained on readily available perioperative clinical data can accurately predict the occurrence of MSFN and aid in individualized patient counseling, preoperative optimization, and surgical planning to reduce the risk of this devastating complication.

Determinants of telemedicine adoption among financially distressed patients with cancer during the COVID-19 pandemic: insights from a nationwide study.

PURPOSE: Telemedicine use during the COVID-19 pandemic among financially distressed patients with cancer, with respect to the determinants of adoption and patterns of utilization, has yet to be delineated. We sought to systematically characterize telemedicine utilization in financially distressed patients with cancer during the COVID-19 pandemic. METHODS: We conducted a cross-sectional analysis of nationwide survey data assessing telemedicine use in patients with cancer during the COVID-19 pandemic collected by Patient Advocate Foundation (PAF) in December 2020. Patients were characterized as financially distressed by self-reporting limited financial resources to manage out-of-pocket costs, psychological distress, and/or adaptive coping behaviors. Primary study outcome was telemedicine utilization during the pandemic. Secondary outcomes were telemedicine utilization volume and modality preferences. Multivariable and Poisson regression analyses were used to identify factors associated with telemedicine use. RESULTS: A convenience sample of 627 patients with cancer responded to the PAF survey. Telemedicine adoption during the pandemic was reported by 67% of patients, with most (63%) preferring video visits. Younger age (19-35 age compared to ≥ 75 age) (OR, 6.07; 95% CI, 1.47-25.1) and more comorbidities (≥ 3 comorbidities compared to cancer only) (OR, 1.79; 95% CI, 1.13-2.65) were factors associated with telemedicine adoption. Younger age (19-35 years) (incidence rate ratios [IRR], 1.78; 95% CI, 24-115%) and higher comorbidities (≥ 3) (IRR; 1.36; 95% CI, 20-55%) were factors associated with higher utilization volume. As area deprivation index increased by 10 units, the number of visits decreased by 3% (IRR 1.03, 95% CI, 1.03-1.05). CONCLUSIONS: The rapid adoption of telemedicine may exacerbate existing inequities, particularly among vulnerable financially distressed patients with cancer. Policy-level interventions are needed for the equitable and efficient provision of this service.

Representation of African American Patients in Social Media for Breast Reconstruction.

BACKGROUND: Social media use by plastic surgeons may contribute to the overall increase in breast reconstruction in the United States. However, recent data show a concerning decrease in breast reconstruction in African American women. The purpose of this study was to analyze the inclusion of African American women in social media posts for breast reconstruction, with the premise that this may be a possible contributing factor to decreasing rates of breast reconstruction in this population. METHODS: Data from several social media platforms were obtained manually on December 1, 2019. Each image was analyzed using the Fitzpatrick scale as a guide. RESULTS: A total of 2580 photographs were included that met the authors' criteria. Only 172 photographs (6.7 percent) were nonwhite. This study surveyed 543 surgeons, 5 percent of whom were nonwhite. The analysis of the results from the random sample of the top plastic surgery social media influencers showed that only 22 (5 percent) of the photographs uploaded were nonwhite patients. Furthermore, 30 percent of surgeons did not have any photographs of nonwhite patients uploaded. CONCLUSIONS: Numerous factors can contribute to the disparity between the growing trend of white patients seeking reconstructive surgery compared to the decreasing trend of African American patients, one of which may be the disparity in their representation in social media, particularly among common platforms and social media influencers. This study highlights the evolving factors that may impair African American breast cancer patients' access to safe, effective breast reconstruction, which must be identified and resolved.