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Purpose: Cancer patient navigators (CPNs) can decrease the time from diagnosis to treatment, but workloads vary widely, which may lead to burnout and less optimal navigation. Current practice for patient distribution among CPNs at our institution approximates random distribution. A literature search did not uncover previous reports of an automated algorithm to distribute patients to CPNs. We sought to develop an automated algorithm to fairly distribute new patients among CPNs specializing in the same cancer type(s) and assess its performance through simulation on a retrospective data set., Methods: Using a 3-year data set, a proxy for CPN work was identified and multiple models were developed to predict the upcoming week's workload for each patient. An XGBoost-based predictor was retained on the basis of its superior performance. A distribution model was developed to fairly distribute new patients among CPNs within a specialty on the basis of predicted work needed. The predicted work included the week's predicted workload from a CPN's existing patients plus that of newly distributed patients to the CPN. Resulting workload unfairness was compared between predictor-informed and random distribution., Results: Predictor-informed distribution significantly outperformed random distribution for equalizing weekly workloads across CPNs within a specialty., Conclusion: This derivation work demonstrates the feasibility of an automated model to distribute new patients more fairly than random assignment (with unfairness assessed using a workload proxy). Improved workload management may help reduce CPN burnout and improve navigation assistance for patients with cancer.

Screening for social determinants of health (SDOH) is recommended, but numerous barriers exist to implementing SDOH screening in clinical spaces. In this study, the authors identified how both active and passive information retrieval methods may be used in clinical spaces to screen for SDOH and meet patient needs. The authors conducted a retrospective sequential cohort analysis comparing the active identification of SDOH through a patient-led digital manual screening process completed in primary care offices from September 2019 to January 2020 and passive identification of SDOH through natural language processing (NLP) from September 2016 to August 2018, among 1735 patients at a large midwestern tertiary referral hospital system and its associated outlying primary care and outpatient facilities. The percent of patients identified by both the passive and active identification methods as experiencing SDOH varied from 0.3% to 4.7%. The active identification method identified social integration, domestic safety, financial resources, food insecurity, transportation, housing, and stress in proportions ranging from 5% to 36%. The passive method contributed to the identification of financial resource issues and stress, identifying 9.6% and 3% of patients to be experiencing these issues, respectively. SDOH documentation varied by provider type. The combination of passive and active SDOH screening methods can provide a more comprehensive picture by leveraging historic patient interactions, while also eliciting current patient needs. Using passive, NLP-based methods to screen for SDOH will also help providers overcome barriers that have historically prevented screening.

Mammography screening rates are typically lower in those with less economic advantage (EA). This study, conducted at an integrated health care system covering a mixed rurality population, assessed the ability of interventions (text messages linking to a Web microsite, digital health care workers, and a community health fair) to affect mammography screening rates and disparity in those rates among different EA populations. Payor type served as a proxy for greater (commercially insured) versus lower (Medicaid insured) EA. 4,342 subjects were included across the preintervention ("Pre") and postintervention ("Post") periods. Interventions were prospectively applied to all Medicaid subjects and randomly selected commercial subjects. Applying interventions only to lower EA subjects reversed the screening rate disparity (2.6% Pre vs. -3.7% Post, odds ratio [OR] 2.4 P  < 0.01). When intervention arms ("Least," "More," "Most") were equally applied, screening rates in both EA groups significantly increased in the More arm (Medicaid OR = 2.04 P  = 0.04, Commercial OR = 3.08 P  < 0.01) and Most arm (Medicaid OR 2.57 P  < 0.01, Commercial OR 2.33 P  < 0.01), but not in the Least (text-only) arm (Medicaid OR 1.83 P  = 0.11, Commercial OR 1.72 P  = 0.09), although this text-only arm was inadequately powered to detect a difference. In summary, targeting interventions to those with lower EA reversed screening rate disparities, text messaging combined with other interventions improved screening rates in both groups, and future research is needed to determine whether interventions can simultaneously improve screening rates for all without worsening the disparity.

Study Objective: We assess accuracy and variability of triage score assignment by emergency department (ED) nurses using the Emergency Severity Index (ESI) in 3 countries. In accordance with previous reports and clinical observation, we hypothesize low accuracy and high variability across all sites., Methods: This cross-sectional multicenter study enrolled 87 ESI-trained nurses from EDs in Brazil, the United Arab Emirates, and the United States. Standardized triage scenarios published by the Agency for Healthcare Research and Quality (AHRQ) were used. Accuracy was defined by concordance with the AHRQ key and calculated as percentages. Accuracy comparisons were made with one-way ANOVA and paired t test. Interrater reliability was measured with Krippendorff's α. Subanalyses based on nursing experience and triage scenario type were also performed., Results: Mean accuracy pooled across all sites and scenarios was 59.2% (95% confidence interval [CI] 56.4% to 62.0%) and interrater reliability was modest (α=.730; 95% CI .692 to .767). There was no difference in overall accuracy between sites or according to nurse experience. Medium-acuity scenarios were scored with greater accuracy (76.4%; 95% CI 72.6% to 80.3%) than high- or low-acuity cases (44.1%, 95% CI 39.3% to 49.0% and 54%, 95% CI 49.9% to 58.2%), and adult scenarios were scored with greater accuracy than pediatric ones (66.2%, 95% CI 62.9% to 69.7% versus 46.9%, 95% CI 43.4% to 50.3%)., Conclusion: In this multinational study, concordance of nurse-assigned ESI score with reference standard was universally poor and variability was high. Although the ESI is the most popular ED triage tool in the United States and is increasingly used worldwide, our findings point to a need for more reliable ED triage tools., (Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)

Introduction: Low and middle income countries bear a disproportionate burden of paediatric morbidity and mortality. South Africa, a middle income country, has unacceptably high mortality in children less than 5 years of age. Many factors that contribute to the child mortality rate are time sensitive and require efficient access to emergency care. Delays and barriers within the emergency medical services (EMS) system increase paediatric morbidity and mortality from time sensitive illnesses., Methods: This study is a qualitative evaluation of the prehospital care system for paediatric patients in Cape Town, South Africa. A purposive sample of healthcare personnel within and interacting with the EMS system were interviewed. A structured interview form was used to gather data. All interviews were audio recorded and transcribed; two independent reviewers performed blinded content analysis of the transcribed script., Results: 33 structured interviews were conducted over a 4 week period. Eight broad themes were identified during coding, including: access, communication, community education, equipment, infrastructure, staffing, training and triage. Subcategories were used to identify areas for targeted intervention. Overall agreement between the two independent coders was 93.36%, with a κ coefficient of 0.69., Conclusions: The prehospital system is central to delivering time sensitive care for paediatric patients. In a single centre middle income setting, communication barriers between dispatch personnel and medical facilities/EMS personnel were deemed to be a high priority intervention in order to improve care delivery. Other areas for targeted interventions should include broadening the advanced life support provider base and introducing basic medical language in dispatch staff training., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

Objective: To pilot an in-home unintentional injury hazard assessment tool and to quantify potential injury risks for young children in a low-income urban setting., Methods: Two low-income neighbourhoods in Karachi, Pakistan, were mapped, and families with at least one child between the ages of 12 and 59 months were identified. Using existing available home injury risk information, an in-home injury risk assessment tool was drafted and tailored to the local setting. Home injury assessments were done in June-July 2010 after obtaining informed consent., Results: Approximately 75.4% of mothers were educated through at least grade 12. The main risks identified were stoves within the reach of the child (n=279, 55.5%), presence of open buckets in the bathroom (n=240, 47.7%) within the reach of the child, and pedestal fans accessible to the child (n=242, 48.1%). In terms of safety equipment, a first-aid box with any basic item was present in 70% of households, but only 4.8% of households had a fire extinguisher in the kitchen., Conclusions: This was the first time that an in-home, all-unintentional injury risk assessment tool was tailored and applied in the context of a low-income community in Pakistan. There was a significant burden of hazards present in the homes in these communities, representing an important opportunity for injury prevention. This pilot may have future relevance to other LMICs where child injury prevention is a critical need.