A Multilevel Approach to Investigate Relationships Between Healthcare Resources and Lung Cancer.

BACKGROUND: Screening for lung cancer is an evidence-based but underutilized measure to reduce the burden of lung cancer mortality. Lack of adequate data on geographic availability of lung cancer screening inhibits the ability of healthcare providers to help patients with decision-making and impedes equity-focused implementation of screening-supportive services. OBJECTIVES: This analysis used data from the 2012-2016 Surveillance, Epidemiology, and End Results (SEER) Program, the Behavioral Risk Factor Surveillance System, and the county health ranking to examine (a) which cancer resources and county-level factors are associated with late-stage lung cancer at diagnosis and (b) associations between county rurality and lung cancer incidence/mortality rates. METHODS: Using the New York state SEER data, we identified 68,990 lung cancer patients aged 20-112 years; 48.3% had late-stage lung cancers, and the average lung cancer incidence and mortality rates were 70.7 and 46.2 per 100,000, respectively. There were 144 American College of Radiology-designated lung cancer screening centers and 376 Federally Qualified Health Centers identified in New York state. County rurality was associated with a higher proportion of late-stage lung cancers and higher lung cancer mortality rates. DISCUSSION: Visual geomapping showed the scarcity of rural counties' healthcare resources. County rurality is a significant factor in differences in lung cancer screening resources and patient outcomes. Use of publicly available data with geospatial methods provides ways to identify areas for improvement, populations at risk, and additional infrastructure needs.

A Change from a Spinal Immobilization to a Spinal Motion Restriction Protocol was Not Associated with an Increase in Disabling Spinal Cord Injuries.

BACKGROUND: Over the past decade, Emergency Medical Service (EMS) systems decreased backboard use as they transition from spinal immobilization (SI) protocols to spinal motion restriction (SMR) protocols. Since this change, no study has examined its effect on the neurologic outcomes of patients with spine injuries. OBJECTIVES: The object of this study is to determine if a state-wide protocol change from an SI to an SMR protocol had an effect on the incidence of disabling spinal cord injuries. METHODS: This was a retrospective review of patients in a single Level I trauma center before and after a change in spinal injury protocols. A two-step review of the record was used to classify spinal cord injuries as disabling or not disabling. A binary logistic regression was used to determine the effects of protocol, gender, age, level of injury, and mechanism of injury (MOI) on the incidence of significant disability from a spinal cord injury. RESULTS: A total of 549 patients in the SI period and 623 patients in the SMR period were included in the analysis. In the logistic regression, the change from an SI protocol to an SMR protocol did not demonstrate a significant effect on the incidence of disabling spinal injuries (OR: 0.78; 95% CI, 0.44 - 1.36). CONCLUSION: This study did not demonstrate an increase in disabling spinal cord injuries after a shift from an SI protocol to an SMR protocol. This finding, in addition to existing literature, supports the introduction of SMR protocols and the decreased use of the backboard.

Predicting hospital-onset Clostridium difficile using patient mobility data: A network approach.

OBJECTIVE: To examine the relationship between unit-wide Clostridium difficile infection (CDI) susceptibility and inpatient mobility and to create contagion centrality as a new predictive measure of CDI. DESIGN: Retrospective cohort study. METHODS: A mobility network was constructed using 2 years of patient electronic health record data for a 739-bed hospital (n = 72,636 admissions). Network centrality measures were calculated for each hospital unit (node) providing clinical context for each in terms of patient transfers between units (ie, edges). Daily unit-wide CDI susceptibility scores were calculated using logistic regression and were compared to network centrality measures to determine the relationship between unit CDI susceptibility and patient mobility. RESULTS: Closeness centrality was a statistically significant measure associated with unit susceptibility (P < .05), highlighting the importance of incoming patient mobility in CDI prevention at the unit level. Contagion centrality (CC) was calculated using inpatient transfer rates, unit-wide susceptibility of CDI, and current hospital CDI infections. The contagion centrality measure was statistically significant (P < .05) with our outcome of hospital-onset CDI cases, and it captured the additional opportunities for transmission associated with inpatient transfers. We have used this analysis to create easily interpretable clinical tools showing this relationship as well as the risk of hospital-onset CDI in real time, and these tools can be implemented in hospital EHR systems. CONCLUSIONS: Quantifying and visualizing the combination of inpatient transfers, unit-wide risk, and current infections help identify hospital units at risk of developing a CDI outbreak and, thus, provide clinicians and infection prevention staff with advanced warning and specific location data to inform prevention efforts.