The Association Between Oncology Outreach and Timely Treatment for Rural Patients with Breast Cancer: A Claims-Based Approach.

BACKGROUND: Oncology outreach is a common strategy for increasing rural access to cancer care, where traveling oncologists commute across healthcare settings to extend specialized care. Examining the extent to which physician outreach is associated with timely treatment for rural patients is critical for informing outreach strategies. METHODS: We identified a 100% fee-for-service sample of incident breast cancer patients from 2015 to 2020 Medicare claims and apportioned them into surgery and adjuvant therapy cohorts based on treatment history. We defined an outreach visit as the provision of care by a traveling oncologist at a clinic outside of their primary hospital service area. We used hierarchical logistic regression to examine the associations between patient receipt of preoperative care at an outreach visit (preoperative outreach) and > 60-day surgical delay, and patient receipt of postoperative care at an outreach visit (postoperative outreach) and > 60-day adjuvant delay. RESULTS: We identified 30,337 rural-residing patients who received breast cancer surgery, of whom 4071 (13.4%) experienced surgical delay. Among surgical patients, 14,501 received adjuvant therapy, of whom 2943 (20.3%) experienced adjuvant delay. In adjusted analysis, we found that patient receipt of preoperative outreach was associated with reduced odds of surgical delay (odds ratio [OR] 0.75, 95% confidence interval [CI] 0.61-0.91); however, we found no association between patient receipt of postoperative outreach and adjuvant delay (OR 1.04, 95% CI 0.85-1.25). CONCLUSIONS: Our findings indicate that preoperative outreach is protective against surgical delay. The traveling oncologists who enable such outreach may play an integral role in catalyzing the coordination and timeliness of patient-centered care.

Characterizing the Traveling Oncology Workforce and Its Influence on Patient Travel Burden: A Claims-Based Approach.

PURPOSE: Oncology outreach is a common strategy for extending cancer care to rural patients. However, a nationwide characterization of the traveling workforce that enables this outreach is lacking, and the extent to which outreach reduces travel burden for rural patients is unknown. METHODS: This cross-sectional study analyzed a rural (nonurban) subset of a 100% fee-for-service sample of 355,139 Medicare beneficiaries with incident breast, colorectal, and lung cancers. Surgical, medical, and radiation oncologists were linked to patients using Part B claims, and traveling oncologists were identified by observing hospital service area (HSA) transition patterns. We defined oncology outreach as the provision of cancer care by a traveling oncologist outside of their primary HSA. We used hierarchical gamma regression models to examine the separate associations between patient receipt of oncology outreach and one-way patient travel times to chemotherapy, radiotherapy, and surgery. RESULTS: On average, 9,935 of 39,960 oncologists conducted annual outreach, where 57.8% traveled with low frequency (0-1 outreach visits/mo), 21.1% with medium frequency (1-3 outreach visits/mo), and 21.1% with high frequency (>3 outreach visits/mo). Oncologists provided surgery, radiotherapy, and chemotherapy to 51,715, 27,120, and 5,874 rural beneficiaries, respectively, of whom 2.5%, 6.9%, and 3.6% received oncology outreach. Rural patients who received oncology outreach traveled 16% (95% CI, 11 to 21) and 11% (95% CI, 9 to 13) less minutes to chemotherapy and radiotherapy than those who did not receive oncology outreach, corresponding to expected one-way savings of 15.9 (95% CI, 15.5 to 16.4) and 11.9 (95% CI, 11.7 to 12.2) minutes, respectively. CONCLUSION: Our study introduces a novel claims-based approach for tracking the nationwide traveling oncology workforce and supports oncology outreach as an effective means for improving rural access to cancer care.

Rural-urban disparities in health care delivery for children with medical complexity and moderating effects of payer, disability, and community poverty.

PURPOSE: Children with medical complexity (CMC) may be at increased risk of rural-urban disparities in health care delivery given their multifaceted health care needs, but these disparities are poorly understood. This study evaluated rural-urban disparities in health care delivery to CMC and determined whether Medicaid coverage, co-occurring disability, and community poverty modified the effects of rurality on care delivery. METHODS: This retrospective cohort study of 2012-2017 all-payer claims data from Colorado, Massachusetts, and New Hampshire included CMC <18 years. Health care delivery measures (ambulatory clinic visits, emergency department visits, acute care hospitalizations, total hospital days, and receipt of post-acute care) were compared for rural- versus urban-residing CMC in multivariable regression models, following established methods to evaluate effect modification. FINDINGS: Of 112,475 CMC, 7307 (6.5%) were rural residing and 105,168 (93.5%) were urban residing. A total of 68.9% had Medicaid coverage, 33.9% had a disability, and 39.7% lived in communities with >20% child poverty. In adjusted analyses, rural-residing CMC received significantly fewer ambulatory visits (risk ratio [RR] = 0.95, 95% confidence interval [CI]: 0.94-0.96), more emergency visits (RR = 1.12, 95% CI: 1.08-1.16), and fewer hospitalization days (RR = 0.90, 95% CI = 0.85-0.96). The estimated modification effects of rural residence by Medicaid coverage, disability, and community poverty were each statistically significant. Differences in the odds of having a hospitalization and receiving post-acute care did not persist after incorporating sociodemographic and clinical characteristics and interaction effects. CONCLUSIONS: Rural- and urban-residing CMC differed in their receipt of health care, and Medicaid coverage, co-occurring disabilities, and community poverty modified several of these effects. These modifying effects should be considered in clinical and policy initiatives to ensure that such initiatives do not widen rural-urban disparities.

Specialties Providing Ambulatory Care and Associated Health Care Utilization and Quality for Children With Medical Complexity.

OBJECTIVE: Although children with medical complexity (CMC) have substantial health care needs, the extent to which they receive ambulatory care from primary care versus specialist clinicians is unknown. We aimed to determine the predominant specialty providing ambulatory care to CMC (primary care or specialty discipline), the extent to which specialists deliver well-child care, and associations between having a specialty predominant provider and health care utilization and quality. METHODS: In a retrospective cohort analysis of 2012-17 all-payer claims data from Colorado, New Hampshire, and Massachusetts, we identified the predominant specialty providing ambulatory care for CMC <18 years. Propensity score weighting was used to create a balanced sample of CMC and assess differences in outcomes, including adequate well-child care, continuity of care, emergency visits, and hospitalizations, between CMC with a primary care versus specialty predominant provider. RESULTS: Among 67,218 CMC, 75.3% (n = 50,584) received the plurality of care from a primary care discipline. Body system involvement, age > 2 years, urban residence, and cooccurring disabilities were associated with predominantly receiving care from specialists. After propensity score weighting, there were no significant differences between CMC with a primary care or specialist "predominant specialty seen" (PSS) in ambulatory visit counts, adequate well-child care, hospitalizations, or overall continuity of care. Specialists were the sole providers of well-child care and vaccines for 49.9% and 53.1% of CMC with a specialist PSS. CONCLUSIONS: Most CMC received the plurality of care from primary care disciplines, and there were no substantial differences in overall utilization or quality based on the PSS.

Prevalence of Children With Medical Complexity and Associations With Health Care Utilization and In-Hospital Mortality.

Importance: Children with medical complexity (CMC) have substantial health care needs and frequently experience poor health care quality. Understanding the population prevalence and associated health care needs can inform clinical and public health initiatives. Objective: To estimate the prevalence of CMC using open-source pediatric algorithms, evaluate performance of these algorithms in predicting health care utilization and in-hospital mortality, and identify associations between medical complexity as defined by these algorithms and clinical outcomes. Design, Setting, and Participants: This retrospective cohort study used all-payer claims data from Colorado, Massachusetts, and New Hampshire from 2012 through 2017. Children and adolescents younger than 18 years residing in these states were included if they had 12 months or longer of enrollment in a participating health care plan. Analyses were conducted from March 12, 2021, to January 7, 2022. Exposures: The pediatric Complex Chronic Condition Classification System, Pediatric Medical Complexity Algorithm, and Children With Disabilities Algorithm were applied to 3 years of data to identify children with complex and disabling conditions, first in their original form and then using more conservative criteria that required multiple health care claims or involvement of 3 or more body systems. Main Outcomes and Measures: Primary outcomes, examined over 2 years, included in-hospital mortality and a composite measure of health care services, including specialized therapies, specialized medical equipment, and inpatient care. Outcomes were modeled using logistic regression. Model performance was evaluated using C statistics, sensitivity, and specificity. Results: Of 1 936 957 children, 48.4% were female, 87.8% resided in urban core areas, and 45.1% had government-sponsored insurance as their only primary payer. Depending on the algorithm and coding criteria applied, 0.67% to 11.44% were identified as CMC. All 3 algorithms had adequate discriminative ability, sensitivity, and specificity to predict in-hospital mortality and composite health care services (C statistic = 0.76 [95% CI, 0.73-0.80] to 0.81 [95% CI, 0.78-0.84] for mortality and 0.77 [95% CI, 0.76-0.77] to 0.80 [95% CI, 0.79-0.80] for composite health care services). Across algorithms, CMC had significantly greater odds of mortality (adjusted odds ratio [aOR], 9.97; 95% CI, 7.70-12.89; to aOR, 69.35; 95% CI, 52.52-91.57) and composite health care services (aOR, 4.59; 95% CI, 4.44-4.73; to aOR, 18.87; 95% CI, 17.87-19.93) than children not identified as CMC. Conclusions and Relevance: In this study, open-source algorithms identified different cohorts of CMC in terms of prevalence and magnitude of risk, but all predicted increased health care utilization and in-hospital mortality. These results can inform research, programs, and policies for CMC.

Infant Mortality Associated With Prenatal Opioid Exposure.

Importance: Knowledge of health outcomes among opioid-exposed infants is limited, particularly for those not diagnosed with neonatal opioid withdrawal syndrome (NOWS). Objectives: To describe infant mortality among opioid-exposed infants and identify how mortality risk differs in opioid-exposed infants with and without a diagnosis of NOWS compared with infants without opioid exposure. Design, Setting, and Participants: A retrospective cohort study of maternal-infant dyads was conducted, linking health care claims with vital records for births from January 1, 2010, to December 31, 2014, with follow-up of infants until age 1 year (through 2015). Maternal-infant dyads were included if the infant was born in Texas at 22 to 43 weeks' gestational age to a woman aged 15 to 44 years insured by Texas Medicaid. Data analysis was performed from May 2019 to October 2020. Exposure: The primary exposure was prenatal opioid exposure, with infants stratified by the presence or absence of a diagnosis of NOWS during the birth hospitalization. Main Outcomes and Measures: Risk of infant mortality (death at age <365 days) was examined using Kaplan-Meier and log-rank tests. A series of logistic regression models was estimated to determine associations between prenatal opioid exposure and mortality, adjusting for maternal and neonatal characteristics and clustering infants at the maternal level to account for statistical dependence owing to multiple births during the study period. Results: Among 1 129 032 maternal-infant dyads, 7207 had prenatal opioid exposure, including 4238 diagnosed with NOWS (mean [SD] birth weight, 2851 [624] g) and 2969 not diagnosed with NOWS (mean [SD] birth weight, 2971 [639] g). Infant mortality was 20 per 1000 live births for opioid-exposed infants not diagnosed with NOWS, 11 per 1000 live births for infants with NOWS, and 6 per 1000 live births in the reference group (P < .001). After adjusting for maternal and neonatal characteristics, mortality in infants with a NOWS diagnosis was not significantly different from the reference population (odds ratio, 0.82; 95% CI, 0.58-1.14). In contrast, the odds of mortality in opioid-exposed infants not diagnosed with NOWS was 72% greater than the reference population (odds ratio, 1.72; 95% CI, 1.25-2.37). Conclusions and Relevance: In this study, opioid-exposed infants appeared to be at increased risk of mortality, and the treatments and supports provided to those diagnosed with NOWS may be protective. Interventions to support opioid-exposed maternal-infant dyads are warranted, regardless of the perceived severity of neonatal opioid withdrawal.

Comparative effectiveness of direct admission and admission through emergency departments for children: a randomized stepped wedge study protocol.

BACKGROUND: Approximately 2 million children are hospitalized each year in the United States, with more than three-quarters of non-elective hospitalizations admitted through emergency departments (EDs). Direct admission, defined as admission to hospital without first receiving care in the hospital's ED, may offer benefits for patients and healthcare systems in quality, timeliness, and experience of care. While ED utilization patterns are well studied, there is a paucity of research comparing the effectiveness of direct and ED admissions. The overall aim of this project is to compare the effectiveness of a standardized direct admission approach to admission beginning in the ED for hospitalized children. METHODS/DESIGN: We will conduct a stepped wedge cluster randomized controlled trial at 3 structurally and geographically diverse hospitals. A total of 70 primary and urgent care practice sites in the hospitals' catchment areas will be randomized to a time point when they will begin participation in the multi-stakeholder informed direct admission program. This crossover will be unidirectional and occur at 4 time points, 6 months apart, over a 24-month implementation period. Our primary outcome will be the timeliness of clinical care provision. Secondary outcomes include (i) parent-reported experience of care, (ii) unanticipated transfer to the intensive care unit within 6 h of hospital admission, and (iii) rapid response calls within 6 h of hospital admission. We anticipate that 190 children and adolescents will be directly admitted, with 1506 admitted through EDs. Analyses will compare the effectiveness of direct admission to admission through the ED and will evaluate the causal effect of implementing a direct admission program using linear regression with random effects for referring practice clusters and time period fixed effects. We will further examine the heterogeneity of treatment effects based on hypotheses specified a priori. In addition, we will conduct a mixed-methods process evaluation to assess reach, effectiveness, adoption, implementation, and maintenance of our direct admission intervention. DISCUSSION: Our study represents the first randomized controlled trial to compare the effectiveness of direct admission to admission through the ED for pediatric patients. Our scientific approach, pairing a stepped wedge design with a multi-level assessment of barriers to and facilitators of implementation, will generate valuable data about how positive findings can be reproduced across other healthcare systems. TRIAL REGISTRATION: ClinicalTrials.gov NCT04192799 . Registered on December 10, 2019).