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.

Temporal trends in incidence of pediatric type 1 diabetes in Alabama: 2000-2017

OBJECTIVE

The incidence of type 1 diabetes has increased in the United States and worldwide. We hypothesized that trends in the annual incidence rates of childhood-onset type 1 diabetes in the state of Alabama would be different by race and sex.

METHODS

We performed a retrospective observational cohort study, analyzing children with type 1 diabetes (n = 3770) managed at the Children's Hospital of Alabama between 2000 and 2017. We compared crude incidence rates using negative binomial regression models and analyzed differences in annual trends of age-adjusted incidence by race and sex using joinpoint regression.

RESULTS

The crude type 1 diabetes incidence rate was estimated at 16.7 per 100 000 children <19 years of age in Alabama. Between 2000 and 2007, there was an increase in age-adjusted incidence of type 1 diabetes with an annual percent change (APC) of 10% from 2000 to 2007 and a 1.7% APC decrease from 2007 to 2017. The age-adjusted incidence for Whites and Blacks increased with an average annual percentage change (AAPC) of 4.4% and 2.8%, respectively. A nearly 11% increasing trend in age-adjusted incidence was observed for both races, though the increase plateaued in 2006 for Whites and 2010 for Blacks.

CONCLUSIONS

Following significantly increasing annual trends for both races, the age-adjusted rate remained statistically stable for Whites and decreased significantly for Blacks. Longer-sustained trend increases for Blacks resulted in type 1 diabetes incidence tripling compared to the doubling of the rate for Whites.