The Association of Frailty and Neighborhood Disadvantage with Emergency Department Visits and Hospitalizations in Older Adults.

BACKGROUND: Risk stratification and population management strategies are critical for providing effective and equitable care for the growing population of older adults in the USA. Both frailty and neighborhood disadvantage are constructs that independently identify populations with higher healthcare utilization and risk of adverse outcomes. OBJECTIVE: To examine the joint association of these factors on acute healthcare utilization using two pragmatic measures based on structured data available in the electronic health record (EHR). DESIGN: In this retrospective observational study, we used EHR data to identify patients aged ≥ 65 years at Atrium Health Wake Forest Baptist on January 1, 2019, who were attributed to affiliated Accountable Care Organizations. Frailty was categorized through an EHR-derived electronic Frailty Index (eFI), while neighborhood disadvantage was quantified through linkage to the area deprivation index (ADI). We used a recurrent time-to-event model within a Cox proportional hazards framework to examine the joint association of eFI and ADI categories with healthcare utilization comprising emergency visits, observation stays, and inpatient hospitalizations over one year of follow-up. KEY RESULTS: We identified a cohort of 47,566 older adults (median age = 73, 60% female, 12% Black). There was an interaction between frailty and area disadvantage (P = 0.023). Each factor was associated with utilization across categories of the other. The magnitude of frailty's association was larger than living in a disadvantaged area. The highest-risk group comprised frail adults living in areas of high disadvantage (HR 3.23, 95% CI 2.99-3.49; P < 0.001). We observed additive effects between frailty and living in areas of mid- (RERI 0.29; 95% CI 0.13-0.45; P < 0.001) and high (RERI 0.62, 95% CI 0.41-0.83; P < 0.001) neighborhood disadvantage. CONCLUSIONS: Considering both frailty and neighborhood disadvantage may assist healthcare organizations in effectively risk-stratifying vulnerable older adults and informing population management strategies. These constructs can be readily assessed at-scale using routinely collected structured EHR data.

Residential Segregation and Emergency Department Utilization Among an Underserved Urban Emergency Department Sample in North Carolina.

BACKGROUND Residential segregation is a spatial manifestation of structural racism. Racial disparities in emergency department (ED) utilization mirror social inequity in the larger community. We evaluated associations between residential segregation and ED utilization in a community with known disparities and geographically concentrated social and health risk.METHODS Cross-sectional data were collected from electronic medical records of 101 060 adult ED patients living in Mecklenburg County, North Carolina in 2017. Community context was measured as residential segregation using the dissimilarity index, categorized into quintiles (Q1-Q5) using 2013-2017 American Community Survey estimates, and residency in a public health priority area (PHPA). The outcome was measured as total ED visits during the study period. Associations between community context and ED utilization were modeled using Anderson's behavioral model of health service utilization, and estimated using negative binomial regression, including interaction terms by race.RESULTS Compared to areas with the lowest proportions of Black residents (Q1), living in Q4 was associated with higher rates of ED utilization among Black/Other (AME = 0.11) and White (AME = 0.23) patients, while associations with living in Q5 were approximately equivalent (AME = 0.12). PHPA residency was associated with higher rates of ED utilization among Black/Other (AME = 0.10) and White patients (AME = 0.22).LIMITATIONS Associations should not be interpreted as causal, or be generalized to the larger community without ED utilization. Health system leakage is possible but limited.CONCLUSIONS Residential segregation is associated with higher rates of ED utilization, as are PHPA residency and other individual-level determinants.

Variations in Receipt of Contraceptives by Insurance Status and Race/Ethnicity.

BACKGROUND Although use of contraceptives has increased among young women in the United States, more than half of pregnancies remain unplanned. The goal of this study was to examine the association between insurance status and receipt of contraceptives among young women receiving care within a large integrated health care system in the Southeastern United States to better inform strategies for increasing access to contraception.METHODS This retrospective study used electronic medical record data from an integrated health care system based in Charlotte, North Carolina. Data were analyzed for 51,900 women aged 18-29 who lived in Mecklenburg County and had at least 1 primary care visit between 2014 and 2016. Contraceptive orders were identified by service and procedure codes and grouped into long-acting reversible contraceptives (LARC) and non-LARC categories. Adjusted multinomial logistic regression models were used to assess the association between receipt of contraceptives and insurance status.RESULTS Compared to non-Hispanic White women with commercial insurance, non-Hispanic Black (OR = 1.25; 95% CI, 1.13-1.38) and Hispanic (OR = 2.25; 95% CI, 1.93-2.61) women with Medicaid had higher odds of receiving LARC. Similar variations by insurance and race/ethnicity were observed for the non-LARC group.LIMITATIONS Data were limited to a single health care system and did not capture contraceptive orders by unaffiliated providers. Analyses used the most frequent payor and did not account for changes in insurance status.CONCLUSION Findings indicate an important role of race/ethnicity and insurance coverage in contraceptive care. Higher receipt of LARC among Black and Hispanic women also suggests that implicit biases may influence contraception counseling and promotion practices. Future study is warranted to further delineate these relationships.

Ambulatory care, insurance, and avoidable emergency department utilization in North Carolina.

OBJECTIVE: To examine whether and how avoidable emergency department (ED) utilization is associated with ambulatory or primary care (APC) utilization, insurance, and interaction effects. DESIGN AND SAMPLE: A cross-sectional analysis of electronic health records from 70,870 adults residing in Mecklenburg County, North Carolina, who visited an ED within a large integrated healthcare system in 2017. METHODS: APC utilization was measured as total visits, categorized as: 0, 1, and > 1. Insurance was defined as the method of payment for the ED visit as: Medicaid, Medicare, private, or uninsured. Avoidable ED utilization was quantified as a score (aED), calculated as the sum of New York University Algorithm probabilities multiplied by 100. Quantile regression models were used to predict the 25th, 50th, 75th, 95th, and 99th percentiles of avoidable ED scores with APC visits and insurance as predictors (Model 1) and with an interaction term (Model 2). RESULTS: Having >1 APC visit was negatively associated with aED at the lower percentiles and positively associated at higher percentiles. A higher aED was associated with having Medicaid insurance and a lower aED was associated with having private insurance, compared to being uninsured. In stratified models, having >1 APC visit was negatively associated with aED at the 25th percentile for the uninsured and privately insured, but positively associated with aED at higher percentiles among the uninsured, Medicaid-insured, and privately insured. CONCLUSIONS: The association between APC utilization and avoidable ED utilization varied based on segments of the distribution of ED score and differed significantly by insurance type.

Protocol for a two-arm pragmatic stepped-wedge hybrid effectiveness-implementation trial evaluating Engagement and Collaborative Management to Proactively Advance Sepsis Survivorship (ENCOMPASS).

BACKGROUND: Sepsis survivors experience high morbidity and mortality, and healthcare systems lack effective strategies to address patient needs after hospital discharge. The Sepsis Transition and Recovery (STAR) program is a navigator-led, telehealth-based multicomponent strategy to provide proactive care coordination and monitoring of high-risk patients using evidence-driven, post-sepsis care tasks. The purpose of this study is to evaluate the effectiveness of STAR to improve outcomes for sepsis patients and to examine contextual factors that influence STAR implementation. METHODS: This study uses a hybrid type I effectiveness-implementation design to concurrently test clinical effectiveness and gather implementation data. The effectiveness evaluation is a two-arm, pragmatic, stepped-wedge cluster randomized controlled trial at eight hospitals in North Carolina comparing clinical outcomes between sepsis survivors who receive Usual Care versus care delivered through STAR. Each hospital begins in a Usual Care control phase and transitions to STAR in a randomly assigned sequence (one every 4 months). During months that a hospital is allocated to Usual Care, all eligible patients will receive usual care. Once a hospital transitions to STAR, all eligible patients will receive STAR during their hospitalization and extending through 90 days from discharge. STAR includes centrally located nurse navigators using telephonic counseling and electronic health record-based support to facilitate best-practice post-sepsis care strategies including post-discharge review of medications, evaluation for new impairments or symptoms, monitoring existing comorbidities, and palliative care referral when appropriate. Adults admitted with suspected sepsis, defined by clinical criteria for infection and organ failure, are included. Planned enrollment is 4032 patients during a 36-month period. The primary effectiveness outcome is the composite of all-cause hospital readmission or mortality within 90 days of discharge. A mixed-methods implementation evaluation will be conducted before, during, and after STAR implementation. DISCUSSION: This pragmatic evaluation will test the effectiveness of STAR to reduce combined hospital readmissions and mortality, while identifying key implementation factors. Results will provide practical information to advance understanding of how to integrate post-sepsis management across care settings and facilitate implementation, dissemination, and sustained utilization of best-practice post-sepsis management strategies in other heterogeneous healthcare delivery systems. TRIAL REGISTRATION: NCT04495946 . Submitted July 7, 2020; Posted August 3, 2020.

Leveraging Data Analytics to Advance Personal, Population, and System Health: Moving Beyond Merely Capturing Services Provided.

The health care industry collects ever-increasing volumes of patient data. Currently, this largely untapped "big data" primarily documents encounters and facilitates billing. This issue of the North Carolina Medical Journal explores the promise and the perils of big data as we seek to transform our health care system into one that is more proactive, equitable, and value based.

Shared decision making and time to exacerbation in children with asthma.

Objective: Although shared decision making (SDM) is a promising approach for improving outcomes for patients with chronic diseases, no evidence currently supports the use of SDM to delay asthma exacerbations. We evaluated the impact of an SDM intervention implemented by providers in a real-world setting on time to exacerbation in children with asthma. Methods: This study used a prospective cohort observed between 2011 and 2013 at five primary care practices that serve vulnerable populations (e.g., Medicaid and uninsured patients) in Charlotte, NC. Patients aged 2 to 17 receiving SDM were matched to those receiving usual care using propensity scores. Time to asthma exacerbation (asthma hospitalization, emergency department visit or oral steroid prescription in the outpatient setting) was compared between groups using Kaplan-Meier curves and conditional Cox proportional hazards models. Results: The cohort included 746 children, 60.5% male and 54.2% African American, with a mean age of 8.6 years. Of these, 625 received usual care and 121 received SDM. The final analysis included 100 matched pairs of children. Kaplan-Meier curves showed longer exacerbation-free time for patients in the SDM intervention compared to those in usual care (p = 0.005). The difference in risk of experiencing an exacerbation was marginally significant between the two groups (HR = 0.56, 95% C.I. = 0.29-1.08, p = 0.08). Conclusions: SDM was found to delay exacerbations among children with asthma. Clinicians should consider incorporating patient preferences in treatment decisions through SDM as a means for longer exacerbation-free time among children with poor asthma control.

Impact of shared decision making on asthma quality of life and asthma control among children.

OBJECTIVE: Few studies have examined the effectiveness of shared decision making (SDM) in clinical practice. This study evaluated the impact of SDM on quality of life and symptom control in children with asthma. METHODS: We conducted a prospective 3-year study in six community-based practices serving a low-income patient population. Practices received training on SDM using an evidence-based toolkit. Patients aged 2-17 with a diagnosis of asthma were identified from scheduling and billing data. At approximate 6-month intervals, patients completed a survey consisting of the Mini Pediatric Asthma Quality of Life Questionnaire (range 1-7) and the control domain of the Pediatric Asthma Therapy Assessment Questionnaire (range 0-7). We used propensity scores to match 46 children receiving SDM to 46 children receiving usual care with decision support. Included children had completed a baseline survey and at least one follow-up survey. Random coefficient models incorporated repeated measures to assess the effect of SDM on asthma quality of life and asthma control. RESULTS: The sample was primarily of non-White patients (94.6%) with Medicaid insurance (92.4%). Receipt of SDM using an evidence-based toolkit was associated with higher asthma quality of life [mean difference 0.9; 95% confidence interval (CI) 0.4-1.4] and fewer asthma control problems (mean difference -0.9; 95% CI -1.6--0.2) compared to usual care with decision support. CONCLUSIONS: Implementation of SDM within clinical practices using a standardized toolkit is associated with improved asthma quality of life and asthma control for low-income children with asthma when compared to usual care with decision support.

Using Community-Based Participatory Research to Develop Geospatial Models Toward Improving Community Health for Disadvantaged Hispanic Populations in Charlotte, NC.

Hispanic immigrant communities across the U.S. experience persistent health disparities and barriers to primary care. We examined whether community-based participatory research (CBPR) and geospatial modeling could systematically and reproducibly pinpoint neighborhoods in Charlotte, North Carolina with large proportions of Hispanic immigrants who were at-risk for poor health outcomes and health disparities. Using a CBPR framework, we identified 21 social determinants of health measures and developed a geospatial model from a subset of those measures to identify neighborhoods with large proportions of Hispanic immigrant populations at risk for poor health outcomes. The geospatial model included four measures-poverty, English ability, acculturation and violent crime-which comprised our Hispanic Health Risk Index (HHRI). We developed a Primary Care Barrier Index (PCBI) to determine (1) how well the HHRI correlated with a statistically derived composite measure incorporating all 21 measures identified through the CBPR process as being associated with access to primary care; (2) whether the HHRI predicted primary care access as well as the statistically-derived composite measure in a statistical model; and (3) whether the HHRI identified similar neighborhoods as the statistically derived composite measure. We collapsed 17 of the 21 social determinants using principal components analysis to develop the PCBI. We determined the correlation of each index with inappropriate emergency department (ED) visits, a proxy for primary care access, using logistic generalized estimating equations. Results from logistic regression models showed positive associations of both the HHRI and the PCBI with the use of the ED for primary care treatable conditions. Enhanced by the knowledge of the local community, the CBPR process with geospatial modeling can guide the multi-tiered validation of social determinants of health and identify neighborhoods that are at-risk for poor health outcomes and health disparities.

Results from a pragmatic prospective cohort study: Shared decision making improves outcomes for children with asthma.

OBJECTIVE: Patient/provider shared decision making (SDM) improves asthma control in a pragmatic clinical trial setting. This study evaluated the impact of an evidence-based SDM toolkit on outcomes for patients with asthma implemented by providers in a real world setting. We hypothesized that these patients with asthma would demonstrate improved outcomes such as reduced emergency department (ED) visits, hospitalizations, and oral steroid use in the 12 months following a SDM visit compared to those who did not receive the intervention. METHODS: Patients with asthma were identified within six primary care practices that serve vulnerable populations in Charlotte, NC (746 children; 718 adult patients). Propensity scores were used to match 200 children and 206 adults for analysis. The primary outcome variable was asthma exacerbation defined as an ED visit or hospitalization for asthma or outpatient prescription of an oral steroid. Patients were monitored at 3, 6, and 12 months after the intervention date. The outcome variables of ED visits, hospitalizations, and oral steroids were compared between intervention and matched control patients. RESULTS: The proportion of pediatric patients with one or more exacerbations was significantly lower in the SDM intervention group compared to controls during 12 months after exposure to the intervention (33% vs. 47%, p = 0.023). For adults, there was not a strong association between use of the SDM intervention and outcomes improvement. CONCLUSIONS: The evidence-based SDM intervention implemented in this study was associated with improved asthma outcomes for pediatric patients but not adult patients in a real world clinical setting.

Bringing Big Data to the Forefront of Healthcare Delivery: The Experience of Carolinas HealthCare System.

The use of big data to transform care delivery is rapidly becoming a reality. To deliver on the promise of value-based care, providers must know the key drivers of wellness at the patient and community levels, as well as understand resource constraints and opportunities to improve efficiency in the health-care system itself. Data are the linchpin. By gathering the right data and finding innovative ways to glean knowledge, we can improve clinical care, advance the health of our communities, improve the lives of our patients, and operate more efficiently. At Carolinas HealthCare System-one of the nation's largest health-care systems, with nearly 12 million patient encounters annually at more than 900 care locations-we have made substantial investments to establish a centralized data and analytics infrastructure that is transforming the way we deliver care across the continuum. Although the impetus and vision for our program have evolved over the past decade, our efforts coalesced into a strategic, centralized initiative with the launch of the Dickson Advanced Analytics (DA) group in 2012. DA has yielded significant gains in our ability to use data, not only for reporting purposes and understanding our business but also for predicting outcomes and informing action.While these efforts have been successful, the path has not been easy. Effectively harnessing big data requires navigating myriad technological, cultural, operational, and other hurdles. Building a program that is feasible, effective, and sustainable takes concerted effort and a rigorous process of continuous self-evaluation and strategic adaptation.

Accountable Care Communities.

Accountable care communities are a new health model that involves multiple stakeholders working together to improve the health and well-being of their communities by addressing social determinants of health. Stakeholders include health care delivery systems, public health organizations, and community organizations. In an accountable care community, the stakeholders commit to share responsibility, resources, and data to improve community health indicators. Accountable care communities are a promising model to both decrease medical costs and improve health outcomes by placing greater emphasis on addressing social and economic issues that ultimately define health. This issue of the NCMJ highlights accountable care communities in other states and provides an overview of how accountable care community initiatives are working in North Carolina to improve the overall health of our communities.

Bringing Big Data to the Forefront of Healthcare Delivery: The Experience of Carolinas HealthCare System.

The use of big data to transform care delivery is rapidly becoming a reality. To deliver on the promise of value-based care, providers must know the key drivers of wellness at the patient and community levels, as well as understand resource constraints and opportunities to improve efficiency in the healthcare system itself. Data are the linchpin. By gathering the right data and finding innovative ways to glean knowledge, we can improve clinical care, advance the health of our communities, improve the lives of our patients, and operate more efficiently. At Carolinas HealthCare System-one of the nation's largest healthcare systems, with nearly 12 million patient encounters annually at more than 900 care locations-we have made substantial investments to establish a centralized data and analytics infrastructure that is transforming the way we deliver care across the continuum. Although the impetus and vision for our program have evolved over the past decade, our efforts coalesced into a strategic, centralized initiative with the launch of the Dickson Advanced Analytics (DA2) group in 2012. DA2 has yielded significant gains in our ability to use data, not only for reporting purposes and understanding our business but also for predicting outcomes and informing action.While these efforts have been successful, the path has not been easy. Effectively harnessing big data requires navigating myriad technological, cultural, operational, and other hurdles. Building a program that is feasible, effective, and sustainable takes concerted effort and a rigorous process of continuous self-evaluation and strategic adaptation.

Patients' and providers' perceptions of asthma and asthma care: a qualitative study.

BACKGROUND: Differences in patients' and providers' perceptions of asthma and asthma care can create barriers to successful treatment. The primary goal of this qualitative study was to further explore patient and provider perceptions of asthma and asthma care as part of a larger Asthma Comparative Effectiveness Study. METHODS: Focus groups held every 6 months for 3 years were designed to have a mix of both patients and providers allowing for unique understanding around asthma care. RESULTS: The discussion centered on goal setting, asthma action plans and prevention strategies for asthma exacerbations. Three overarching themes, with a variety of subthemes, emerged as the main findings of this study. The three main themes were Cost/Economic Barriers/Process, Self-Governance/Adherence and Education. CONCLUSIONS: These themes indicated a strong need for patient educational interventions around asthma as well as education for providers around cost, insurance coverage and patient-centered communication. Specifically, education on learning to use inhalers properly, avoiding triggers and understanding the importance of a controller medication will benefit patients in the long-term management of asthma.

Adapting community based participatory research (CBPR) methods to the implementation of an asthma shared decision making intervention in ambulatory practices.

OBJECTIVE: Translating research findings into clinical practice is a major challenge to improve the quality of healthcare delivery. Shared decision making (SDM) has been shown to be effective and has not yet been widely adopted by health providers. This paper describes the participatory approach used to adapt and implement an evidence-based asthma SDM intervention into primary care practices. METHODS: A participatory research approach was initiated through partnership development between practice staff and researchers. The collaborative team worked together to adapt and implement a SDM toolkit. Using the RE-AIM framework and qualitative analysis, we evaluated both the implementation of the intervention into clinical practice, and the level of partnership that was established. Analysis included the number of adopting clinics and providers, the patients' perception of the SDM approach, and the number of clinics willing to sustain the intervention delivery after 1 year. RESULTS: All six clinics and physician champions implemented the intervention using half-day dedicated asthma clinics while 16% of all providers within the practices have participated in the intervention. Themes from the focus groups included the importance of being part the development process, belief that the intervention would benefit patients, and concerns around sustainability and productivity. One year after initiation, 100% of clinics have sustained the intervention, and 90% of participating patients reported a shared decision experience. CONCLUSIONS: Use of a participatory research process was central to the successful implementation of a SDM intervention in multiple practices with diverse patient populations.

Dietary intake and adherence to the 2010 Dietary Guidelines for Americans among individuals with chronic spinal cord injury: a pilot study.

OBJECTIVE: To investigate dietary intake and adherence to the 2010 Dietary Guidelines for Americans in individuals with chronic spinal cord injury (SCI) and able-bodied individuals. DESIGN: A pilot study of dietary intake among a sample of individuals with SCI >1 year ago from a single site compared with able-bodied individuals. PARTICIPANTS/METHODS: One hundred black or white adults aged 38-55 years old with SCI >1 year and 100 age-, sex-, and race-matched adults enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Dietary intake was assessed by the CARDIA dietary history. Linear regression analysis was used to compare dietary intake between the subjects with SCI and those enrolled in the CARDIA study. Further, adherence to the 2010 Dietary Guidelines for dairy, fruits, and vegetables, and whole-grain foods was assessed. RESULTS: Compared with CARDIA participants, participants with SCI consumed fewer daily servings of dairy (2.10 vs. 5.0, P < 0.001), fruit (2.01 vs. 3.64, P = 0.002), and whole grain foods (1.20 vs. 2.44 P = 0.007). For each food group, fewer participants with SCI met the recommended servings compared with the CARDIA participants. Specifically, the participants with SCI and in CARDIA who met the guidelines were, respectively: dairy, 22% vs. 54% (P < 0.001), fruits and vegetables 39% vs. 70% (P = 0.001), and whole-grain foods 8% vs. 69.6% (P = 0.001). CONCLUSIONS: Compared with able-bodied individuals, SCI participants consumed fewer daily servings of fruit, dairy, and whole grain foods than proposed by the 2010 Dietary Guideline recommendations. Nutrition education for this population may be warranted.

Dietary intake relative to cardiovascular disease risk factors in individuals with chronic spinal cord injury: a pilot study.

BACKGROUND: The relationship between cardiovascular disease (CVD) risk factors and dietary intake is unknown among individuals with spinal cord injury (SCI). OBJECTIVE: To investigate the relationship between consumption of selected food groups (dairy, whole grains, fruits, vegetables, and meat) and CVD risk factors in individuals with chronic SCI. METHODS: A cross-sectional substudy of individuals with SCI to assess CVD risk factors and dietary intake in comparison with age-, gender-, and race-matched able-bodied individuals enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Dietary history, blood pressure, waist circumference (WC), fasting blood glucose, high-sensitivity C-reactive protein (hs-CRP), lipids, glucose, and insulin data were collected from 100 SCI participants who were 38 to 55 years old with SCI >1 year and compared to 100 matched control participants from the CARDIA study. RESULTS: Statistically significant differences between SCI and CARDIA participants were identified in WC (39.2 vs 36.2 in.; P < .001) and high-density lipoprotein cholesterol (HDL-C; 39.2 vs 47.5 mg/dL; P < .001). Blood pressure, total cholesterol, triglycerides, glucose, insulin, and hs-CRP were similar between SCI and CARDIA participants. No significant relation between CVD risk factors and selected food groups was seen in the SCI participants. CONCLUSION: SCI participants had adverse WC and HDL-C compared to controls. This study did not identify a relationship between consumption of selected food groups and CVD risk factors.

Patient engagement and informed decision making regarding medical imaging.

Misuse and overuse of medical imaging have gained widespread attention due to rising costs, radiation exposure risks, and limited comparative effectiveness evidence. Involving patients in shared decision making offers an opportunity to more clearly define risks and benefits, thus allowing patients to consider both personal values and the best available evidence.

Evaluating primary care delivery systems for an uninsured Hispanic immigrant population.

Hispanic populations experience disparities in health outcomes and health care. Using participatory methods, we evaluated 4 systems of primary care delivery for an uninsured Hispanic population. Best practices were determined that could be translated back to the partner clinics and the community. The assessment included patient service areas, provider discussion groups, patient surveys, calculation of travel distances, and costs. The following best practices were identified: improved proximity to services, enhanced bilingual services, affordable services, and integrated services. Researchers and providers not only identified translatable service delivery practices but also laid the foundation for ongoing research partnerships.