Health System Integration and Cancer Center Access for Rural Hospitals.

BACKGROUND: Cancer centers provide superior care but are less accessible to rural populations. Health systems that integrate a cancer center may provide broader access to quality surgical care, but penetration to rural hospitals is unknown. METHODS: Cancer center data were linked to health system data to describe health systems based on whether they included at least one accredited cancer center. Health systems with and without cancer centers were compared based on rural hospital presence. Bivariate tests and multivariable logistic regression were used with results reported as P-values and odds ratios (OR) with 95% confidence intervals (CIs). RESULTS: Ninety percent of cancer centers are in a health system, and 72% of health systems (434/607) have a cancer center. Larger health systems (P = .03) with more trainees (P = .03) more often have cancer centers but are no more likely to include rural hospitals (11% vs 6%, P = .43; adjusted OR .69, 95% CI .28-1.70). The minority of cancer centers not in health systems (N = 95) more often serve low complexity patient populations (P = .02) in non-metropolitan areas (P = .03). DISCUSSION: Health systems with rural hospitals are no more likely to have a cancer center. Ongoing health system integration will not necessarily expand rural patients' access to surgical care under existing health policy infrastructure and incentives.

Real-World Adherence to Nodal Surveillance for Sentinel Lymph Node-Positive Melanoma.

BACKGROUND: Patients with sentinel lymph node-positive (SLN+) melanoma are increasingly undergoing active nodal surveillance over completion lymph node dissection (CLND) since the Second Multicenter Selective Lymphadenectomy Trial (MSLT-II). Adherence to nodal surveillance in real-world practice remains unknown. METHODS: In a retrospective cohort of SLN+ melanoma patients who underwent nodal surveillance at a single institution from July 2017 through April 2021, this study evaluated adherence to nodal surveillance ultrasound (US). Adherence to nodal US was compared with adherence to other surveillance methods based on receipt of adjuvant therapy. Early recurrence data were reported using descriptive statistics. RESULTS: Among 109 SLN+ patients, 37 (34%) received US surveillance at recommended intervals. Of the 72 (66%) non-adherent patients, 16 were lost to follow-up, and 33 had planned follow-up at an outside institution without available records. More patients had a minimum of bi-annual clinic visits (83%) and cross-sectional imaging (53%) compared to those who were adherent with nodal US. The patients who received adjuvant therapy (60%) had fewer ultrasounds (p < 0.01) but more exams (p < 0.01) and a trend toward more cross-sectional imaging (p = 0.06). Of the overall cohort, 26 patients (24%) experienced recurrence at a median follow-up period of 15 months. Of these recurrences, 10 were limited to the SLN basin, and all of these isolated nodal recurrences were resectable. CONCLUSIONS: Pragmatic challenges to real-world delivery of nodal surveillance remain after MSLT-II, and adjuvant therapy appears to be associated with a decreased likelihood of US adherence. Understanding US utility alongside cross-sectional imaging will be critical as increasingly more patients undergo nodal surveillance and adjuvant therapy.

Factors associated with loss to follow-up after radiation therapy for head and neck cancer.

OBJECTIVES: Head and neck cancer (HNC) patients are at high risk for late occurring radiation-related morbidity and recurrence, necessitating close long-term medical surveillance. This study identified factors associated with becoming lost to follow-up (LTFU) at a comprehensive cancer center. MATERIALS AND METHODS: Patients were drawn from survivors who received radiation for HNC at a single institution between 2001 and 2018. LTFU was defined as living patients without a clinical encounter within 2 years of the data query. RESULTS: In total, 537 patients met the inclusion criteria and 57 (10.6%) were identified as LTFU. Individual comparisons identified time since completing radiation, non-White race and being unmarried as associated with LTFU. Multiple regression identified time since treatment and being unmarried as factors associated with LTFU. A decision tree correctly sorted 89.4% using time, distance, and marital status. CONCLUSION: Time since radiation, distance to clinic, and being unmarried were factors associated with becoming LTFU.