Reducing perceived barriers to scaling up overdose education and naloxone distribution and medications for opioid use disorder in the United States in the HEALing (helping end addiction long-term®) communities study.

BACKGROUND: Scaling up overdose education and naloxone distribution (OEND) and medications for opioid use disorder (MOUD) is needed to reduce opioid overdose deaths, but barriers are pervasive. This study examines whether the Communities That HEAL (CTH) intervention reduced perceived barriers to expanding OEND and MOUD in healthcare/behavioral health, criminal-legal, and other/non-traditional venues. METHODS: The HEALing (Helping End Addiction Long-Term®) Communities Study is a parallel, wait-list, cluster randomized trial testing the CTH intervention in 67 communities in the United States. Surveys administered to coalition members and key stakeholders measured the magnitude of perceived barriers to scaling up OEND and MOUD in November 2019-January 2020, May-June 2021, and May-June 2022. Multilevel linear mixed models compared Wave 1 (intervention) and Wave 2 (wait-list control) respondents. Interactions by rural/urban status and research site were tested. RESULTS: Wave 1 respondents reported significantly greater reductions in mean scores for three outcomes: perceived barriers to scaling up OEND in Healthcare/Behavioral Health Venues (-0.26, 95% confidence interval, CI: -0.48, -0.05, p = 0.015), OEND in Other/Non-traditional Venues (-0.53, 95% CI: - 0.84, -0.22, p = 0.001) and MOUD in Other/Non-traditional Venues (-0.34, 95% CI: -0.62, -0.05, p = 0.020). There were significant interactions by research site for perceived barriers to scaling up OEND and MOUD in Criminal-Legal Venues. There were no significant interactions by rural/urban status. DISCUSSION: The CTH Intervention reduced perceived barriers to scaling up OEND and MOUD in certain venues, with no difference in effectiveness between rural and urban communities. More research is needed to understand facilitators and barriers in different venues.

Attitudes towards and sociodemographic determinants of genetic test usage in the USA; data from the Health Information National Trend Survey, 2020.

The purpose of this study was to examine the trends in who obtains genetic tests, and opinions about how genes affect health. Cross-sectional survey data from Health Information National Trends Survey (HINTS) 5, Cycle 4 was used. This data was collected from adults 18 years of age or older who completed mailed surveys sent by the National Cancer Institute between January and April 2020. The sample consisted of 2,947 respondents who answered the question 'Have you ever had a genetic test'? 727 had a test and 2,220 did not have a test. The measures used included survey questions that asked whether respondents obtained certain kinds of genetic tests, who they shared test results with, whether they believed genes affect health status, and their demographic and cancer status information. Multivariate logistic regression models were developed to assess which demographic variables were associated with having different kinds of genetic tests, and whether those who had genetic tests had different opinions about genetic testing and the influence of genes on health. We found that female respondents [OR: 1.9; CI: (1.2-3.1)] had higher odds of having any genetic tests while Hispanic [OR: 0.5; CI: (0.2-1.0)] respondents had lower odds. Our findings indicate that there are demographic disparities in who received genetic tests, and that cancer risk alone does not explain the differences in prevalence of genetic testing.

Association of change in haemoglobin A1c with adverse perinatal outcomes in women with pregestational diabetes.

AIMS: To determine whether a net decline in glycosylated haemoglobin (HbA1c ) from early to late pregnancy is associated with lower risk of adverse perinatal outcomes at delivery among women with pregestational diabetes. METHODS: A retrospective analysis from 2012 to 2016 at a tertiary care centre. The exposure was the net change in HbA1c from early (<20 weeks gestation) to late pregnancy (≥20 weeks gestation). Primary outcomes were large for gestational age (LGA) and neonatal hypoglycaemia. The association between outcomes per 6 mmol/mol (0.5%) absolute decrease in HbA1c was evaluated using modified Poisson regression, and adjusted for age, body mass index, White Class, early HbA1c and haemoglobin and gestational age at HbA1c measurement and delivery. RESULTS: Among 347 women with pregestational diabetes, HbA1c was assessed in early (9 weeks [IQR 7,13]) and late pregnancy (31 weeks [IQR 29,34]). Mean HbA1c decreased from early (59 mmol/mol [7.5%]) to late (47 mmol/mol [6.5%]) pregnancy. Each 6 mmol/mol (0.5%) absolute decrease in HbA1c was associated with a 12% reduced risk of LGA infant (30%, aRR:0.88; 95% CI:0.81,0.95), and a 7% reduced risk of neonatal hypoglycaemia (35%, aRR:0.93; 95% CI:0.87,0.99). Preterm birth (36%, aRR:0.93; 95% CI:0.89,0.98) and neonatal intensive care unit admission (55%, aRR:0.95; 95% CI:0.91,0.98) decreased with a net decline in HbA1c , but not caesarean delivery, pre-eclampsia, shoulder dystocia and respiratory distress syndrome. CONCLUSIONS: Women with pregestational diabetes with a reduction in HbA1c may have fewer infants born LGA or with neonatal hypoglycaemia. Repeated assessment of HbA1c may provide an additional measure of glycaemic control.

Co-establishing an infrastructure for routine data collection to address disparities in infant mortality: planning and implementation.

BACKGROUND: Efforts to address infant mortality disparities in Ohio have historically been adversely affected by the lack of consistent data collection and infrastructure across the community-based organizations performing front-line work with expectant mothers, and there is no established template for implementing such systems in the context of diverse technological capacities and varying data collection magnitude among participating organizations. METHODS: Taking into account both the needs and limitations of participating community-based organizations, we created a data collection infrastructure that was refined by feedback from sponsors and the organizations to serve as both a solution to their existing needs and a template for future efforts in other settings. RESULTS: By standardizing the collected data elements across participating organizations, integration on a scale large enough to detect changes in a rare outcome such as infant mortality was made possible. Datasets generated through the use of the established infrastructure were robust enough to be matched with other records, such as Medicaid and birth records, to allow more extensive analysis. CONCLUSION: While a consistent data collection infrastructure across multiple organizations does require buy-in at the organizational level, especially among participants with little to no existing data collection experience, an approach that relies on an understanding of existing barriers, iterative development, and feedback from sponsors and participants can lead to better coordination and sharing of information when addressing health concerns that individual organizations may struggle to quantify alone.

Differences in Hemoglobin A1c during Pregnancy between Non-Hispanic Black versus White Women with Prepregnancy Diabetes.

OBJECTIVE: The objective of this was to determine whether the change in hemoglobin A1c (HbA1c) from early to late pregnancy differs between non-Hispanic Black and White women with prepregnancy diabetes. STUDY DESIGN: A retrospective analysis was performed from an integrated prenatal and diabetes care program from 2012 to 2016. We compared HbA1c as a continuous measure and secondarily, HbA1c <6.5%, cross-sectionally, and longitudinally in early (approximately 10 weeks) and late (approximately 31 weeks) pregnancies. Linear and logistic regression were used and adjusted for age, body mass index, White diabetes class, medication use, diabetes type, gestational age at baseline HbA1c measurement, and baseline hemoglobin. RESULTS: Among 296 non-Hispanic Black (35%) and White pregnant women (65%) with prepregnancy diabetes (39% type 1 and 61% type 2), Black women were more likely to experience increased community-level social determinants of health as measured by the Social Vulnerability Index (SVI) and were less likely to have type 1 diabetes and have more severe diabetes versus White women (p < 0.05). Black women had higher mean HbA1c (7.8 vs. 7.4%; beta: 0.75; 95% confidence interval [CI]: 0.30-1.19) and were less likely to have HbA1c < 6.5% at 10 weeks compared with White women (24 vs. 35%; adjusted odds ratio: 0.45; 95% CI: 0.24-0.81) but not after adjusting for SVI. At 31 weeks, both groups had similar mean HbA1c (both 6.5%) and were equally as likely to have HbA1c < 6.5% (57 vs. 54%). From early to late pregnancy, Black women had a higher percentage decrease in HbA1c (1.3 vs. 0.9%; beta = 0.63; 95% CI: 0.27-0.99) and were equally as likely to have an improvement or stable HbA1C < 6.5% from 10 to 31 weeks, with both groups having a similar mean HbA1c (6.5%) at 31 weeks. CONCLUSION: Despite experiencing greater community-level social determinants of health, Black women with pregestational diabetes had a larger reduction in HbA1c and were able to equally achieve the target of HbA1c < 6.5% by late pregnancy compared with White women as part of an integrated diabetes and prenatal care program. KEY POINTS: · An integrated diabetes and pregnancy care program may decrease racial and ethnic disparities in glycemic control.. · Black women had a larger reduction in HbA1c versus White women.. · Black women were able to equally achieve the target of HbA1c < 6.5% by late pregnancy versus White women..

Sequences of Events from the Electronic Medical Record and the Onset of Infection.

We present a novel model of time-series analysis to learn from electronic health record (EHR) data when infection occurred in the intensive care unit (ICU) by translating methods from proteomics and Bayesian statistics. Using 48,536 patients hospitalized in an ICU, we describe each hospital course as an 'alphabet' of 23 physician actions ('events') in temporal order. We analyze these as k-mers of length 3-12 events and apply a Bayesian model of (cumulative) relative risk (RR). The log2-transformed RR (median=0.248, mean=0.226) supported the conclusion that the events selected were individually associated with increased risk of infection. Selecting from all possible cutoffs of maximum gain (MG), MG>0.0244 predicts administration of antibiotics with PPV 82.0 %, NPV 44.4 %, and AUC 0.706. Our approach holds value for retrospective analysis of other clinical syndromes for which time-of-onset is critical to analysis but poorly marked in EHRs, including delirium and decompensation.

Differential Effects of Outpatient Portal User Status on Inpatient Portal Use: Observational Study.

BACKGROUND: The decision to use patient portals can be influenced by multiple factors, including individuals' perceptions of the tool, which are based on both their personal skills and experiences. Prior experience with one type of portal may make individuals more comfortable with using newer portal technologies. Experienced outpatient portal users in particular may have confidence in their ability to use inpatient portals that have similar functionality. In practice, the use of both outpatient and inpatient portal technologies can provide patients with continuity of access to their health information across care settings, but the influence of one type of portal use on the use of other portals has not been studied. OBJECTIVE: This study aims to understand how patients' use of an inpatient portal is influenced by outpatient portal use. METHODS: This study included patients from an academic medical center who were provided access to an inpatient portal during their hospital stays between 2016 and 2018 (N=1571). We analyzed inpatient portal log files to investigate how inpatient portal use varied by using 3 categories of outpatient portal users: prior users, new users, and nonusers. RESULTS: Compared with prior users (695/1571, 44.24%) of an outpatient portal, new users (214/1571, 13.62%) had higher use of a select set of inpatient portal functions (messaging function: incidence rate ratio [IRR] 1.33, 95% CI 1.06-1.67; function that provides access to the outpatient portal through the inpatient portal: IRR 1.34, 95% CI 1.13-1.58). Nonusers (662/1571, 42.14%), compared with prior users, had lower overall inpatient portal use (all active functions: IRR 0.68, 95% CI 0.60-0.78) and lower use of specific functions, which included the function to review vitals and laboratory results (IRR 0.51, 95% CI 0.36-0.73) and the function to access the outpatient portal (IRR 0.53, 95% CI 0.45-0.62). In comparison with prior users, nonusers also had lower odds of being comprehensive users (defined as using 8 or more unique portal functions; odds ratio [OR] 0.57, 95% CI 0.45-0.73) or composite users (defined as comprehensive users who initiated a 75th or greater percentile of portal sessions) of the inpatient portal (OR 0.42, 95% CI 0.29-0.60). CONCLUSIONS: Patients' use of an inpatient portal during their hospital stay appeared to be influenced by a combination of factors, including prior outpatient portal use. For new users, hospitalization itself, a major event that can motivate behavioral changes, may have influenced portal use. In contrast, nonusers might have lower self-efficacy in their ability to use technology to manage their health, contributing to their lower portal use. Understanding the relationship between the use of outpatient and inpatient portals can help direct targeted implementation strategies that encourage individuals to use these tools to better manage their health across care settings.

A novel model to label delirium in an intensive care unit from clinician actions.

BACKGROUND: In the intensive care unit (ICU), delirium is a common, acute, confusional state associated with high risk for short- and long-term morbidity and mortality. Machine learning (ML) has promise to address research priorities and improve delirium outcomes. However, due to clinical and billing conventions, delirium is often inconsistently or incompletely labeled in electronic health record (EHR) datasets. Here, we identify clinical actions abstracted from clinical guidelines in electronic health records (EHR) data that indicate risk of delirium among intensive care unit (ICU) patients. We develop a novel prediction model to label patients with delirium based on a large data set and assess model performance. METHODS: EHR data on 48,451 admissions from 2001 to 2012, available through Medical Information Mart for Intensive Care-III database (MIMIC-III), was used to identify features to develop our prediction models. Five binary ML classification models (Logistic Regression; Classification and Regression Trees; Random Forests; Naïve Bayes; and Support Vector Machines) were fit and ranked by Area Under the Curve (AUC) scores. We compared our best model with two models previously proposed in the literature for goodness of fit, precision, and through biological validation. RESULTS: Our best performing model with threshold reclassification for predicting delirium was based on a multiple logistic regression using the 31 clinical actions (AUC 0.83). Our model out performed other proposed models by biological validation on clinically meaningful, delirium-associated outcomes. CONCLUSIONS: Hurdles in identifying accurate labels in large-scale datasets limit clinical applications of ML in delirium. We developed a novel labeling model for delirium in the ICU using a large, public data set. By using guideline-directed clinical actions independent from risk factors, treatments, and outcomes as model predictors, our classifier could be used as a delirium label for future clinically targeted models.

Metrics for Outpatient Portal Use Based on Log File Analysis: Algorithm Development.

BACKGROUND: Web-based outpatient portals help patients engage in the management of their health by allowing them to access their medical information, schedule appointments, track their medications, and communicate with their physicians and care team members. Initial studies have shown that portal adoption positively affects health outcomes; however, early studies typically relied on survey data. Using data from health portal applications, we conducted systematic assessments of patients' use of an outpatient portal to examine how patients engage with the tool. OBJECTIVE: This study aimed to document the functionality of an outpatient portal in the context of outpatient care by mining portal usage data and to provide insights into how patients use this tool. METHODS: Using audit log files from the outpatient portal associated with the electronic health record system implemented at a large multihospital academic medical center, we investigated the behavioral traces of a study population of 2607 patients who used the portal between July 2015 and February 2019. Patient portal use was defined as having an active account and having accessed any portal function more than once during the study time frame. RESULTS: Through our analysis of audit log file data of the number and type of user interactions, we developed a taxonomy of functions and actions and computed analytic metrics, including frequency and comprehensiveness of use. We additionally documented the computational steps required to diagnose artifactual data and arrive at valid usage metrics. Of the 2607 patients in our sample, 2511 were active users of the patients portal where the median number of sessions was 94 (IQR 207). Function use was comprehensive at the patient level, while each session was instead limited to the use of one specific function. Only 17.45% (78,787/451,762) of the sessions were linked to activities involving more than one portal function. CONCLUSIONS: In discussing the full methodological choices made in our analysis, we hope to promote the replicability of our study at other institutions and contribute to the establishment of best practices that can facilitate the adoption of behavioral metrics that enable the measurement of patient engagement based on the outpatient portal use.

Exploring the Digital Divide: Age and Race Disparities in Use of an Inpatient Portal.

Background: Age and race disparities in the use of new technologies-the digital divide-may be limiting the potential of patient-facing health information technology to improve health and health care. Objective: To investigate whether disparities exist in the use of patient portals designed specifically for the inpatient environment. Methods: Patients admitted to the six hospitals affiliated with a large, Midwestern academic medical center from July 2017 to July 2018 were provided with access to a tablet equipped with an inpatient portal and recruited to participate in the study (n = 842). Demographic characteristics of study enrollees were obtained from patients' electronic health records and surveys given to patients during their hospital stay. Log files from the inpatient portal were used to create a global measure of use and calculate use rates for specific portal features.Results: We found both age and race disparities in use of the inpatient portal. Patients aged 60-69 (45.3% difference, p < 0.001) and those over age 70 (36.7% difference, p = 0.04) used the inpatient portal less than patients aged 18-29. In addition, African American patients used the portal less than White patients (40.4% difference, p = 0.004).Discussion: These findings suggest that the availability of the technology alone may be insufficient to overcome barriers to use and that additional intervention may be needed to close the digital divide. Conclusions: We identified lower use of the inpatient portal among African American and older patients, relative to White and younger patients, respectively.

Improving Acceptance of Inpatient Portals: Patients' and Care Team Members' Perspectives.

Background: Inpatient portals are gaining interest as a means to increase patient-centered care during hospitalization. However, acceptance of a new technology such as the inpatient portal relies on perceptions of both its usefulness and ease of use. These factors have not been studied in the context of inpatient portal implementation. Methods: We interviewed patients (n = 123) and care team members (n = 447) about their experiences using an inpatient portal that had been implemented across a large, academic medical center. Interviews lasted 5-15 min, were audio-recorded, transcribed verbatim, and then analyzed using a combination of deductive and inductive methods. Results: Collectively, interviewees reported that the inpatient portal was a useful tool as it improved patients' access to information, enhanced communication, facilitated education, and appeared to promote patients' sense of control while in the hospital. Most interviewees also found the technology easy to use. However, there were concerns that the portal was not easy to use for those less experienced with technology. Interviewees identified the need to emphasize the value of the technology to both patients and care team members and the need to provide additional training to support portal use, as ways to promote acceptance of the tool. Discussion and Conclusions: Inpatient portals can improve patient-centered care, but such improvements require acceptance of the tool by both patients and care team members. Our findings about the usefulness and ease of use of an inpatient portal can inform future efforts to improve the implementation and acceptance of this new technology.

Patients' Perceptions of Portal Use Across Care Settings: Qualitative Study.

BACKGROUND: Patient portals are a promising instrument to improve patient-centered care, as they provide patients information and tools that can help them better manage their health. The implementation of portals in both the inpatient and outpatient setting gives health care providers an opportunity to support patients both during hospitalization and after discharge. Thus, there is a need to better understand how inpatient and outpatient portals are used across care contexts. OBJECTIVE: This study aimed to examine patients' perceptions of using inpatient and outpatient portals across the care settings, including how they used the portals and the benefits and concerns associated with portal use. METHODS: This study was conducted in a large Midwestern academic medical center consisting of seven hospitals. We interviewed 120 patients who had used an inpatient portal during their hospitalization, at 15 days and 6 months postdischarge, to determine their perspectives of portal use in both hospital and outpatient settings. Interview transcripts were analyzed inductively and deductively by using team coding processes consistent with a grounded theory approach. RESULTS: Interviews focused on three main areas of portal use: experience with the portal features, perceived benefits, and concerns. Responses at 15 days (n=60) and 6 months (n=60) postdischarge were consistent with respect to perceptions about portal use. Patients identified viewing their health information, managing their schedule, and communicating with providers as notable activities. Convenience, access to information, and better engagement in care were indicated as benefits. Concerns were related to technology issues and privacy/security risks. CONCLUSIONS: Implementation of inpatient portals as a complement to outpatient portals is increasing and can enable patients to better manage aspects of their care. Although care processes vary substantively across settings, the benefits of convenience, improved access to information, and better engagement in care provide opportunities for portal use across care settings to support patient-centered care.

Patient Engagement as Measured by Inpatient Portal Use: Methodology for Log File Analysis.

BACKGROUND: Inpatient portals (IPPs) have the potential to increase patient engagement and satisfaction with their health care. An IPP provides a hospitalized patient with similar functions to those found in outpatient portals, including the ability to view vital signs, laboratory results, and medication information; schedule appointments; and communicate with their providers. However, IPPs may offer additional functions such as meal planning, real-time messaging with the inpatient care team, daily schedules, and access to educational materials relevant to their specific condition. In practice, IPPs have been developed as websites and tablet apps, with hospitals providing the required technology as a component of care during the patient's stay. OBJECTIVE: This study aimed to describe how inpatients are using IPPs at the first academic medical center to implement a system-wide IPP and document the challenges and choices associated with this analytic process. METHODS: We analyzed the audit log files of IPP users hospitalized between January 2014 and January 2016. Data regarding the date/time and duration of interactions with each of the MyChart Bedside modules (eg, view lab results or medications and patient schedule) and activities (eg, messaging the provider and viewing educational videos) were captured as part of the system audit logs. The development of a construct to describe the length of time associated with a single coherent use of the tool-which we call a session-provides a foundational unit of analysis. We defined frequency as the number of sessions a patient has during a given provision day. We defined comprehensiveness in terms of the percentage of functions that an individual uses during a given provision day. RESULTS: The analytic process presented data challenges such as length of stay and tablet-provisioning factors. This study presents data visualizations to illustrate a series of data-cleaning issues. In the presence of these robust approaches to data cleaning, we present the baseline usage patterns associated with our patient panel. In addition to frequency and comprehensiveness, we present considerations of median data to mitigate the effect of outliers. CONCLUSIONS: Although other studies have published usage data associated with IPPs, most have not explicated the challenges and choices associated with the analytic approach deployed within each study. Our intent in this study was to be somewhat exhaustive in this area, in part, because replicability requires common metrics. Our hope is that future researchers in this area will avail themselves of these perspectives to engage in critical assessment moving forward.

Patient and Provider Perspectives About the Use of Patient-Generated Health Data During Pregnancy: Qualitative Exploratory Study.

BACKGROUND: There is increasing interest in using patient-generated health data (PGHD) to improve patient-centered care during pregnancy. However, little research has examined the perspectives of patients and providers as they report, collect, and use PGHD to inform obstetric care. OBJECTIVE: This study aims to explore the perspectives of patients and providers about the use of PGHD during pregnancy, including the benefits and challenges of reporting, collecting, and using these data, as well as considerations for expanding the use of PGHD to improve obstetric care. METHODS: We conducted one-on-one interviews with 30 pregnant or postpartum patients and 14 health care providers from 2 obstetrics clinics associated with an academic medical center. Semistructured interview guides included questions for patients about their experience and preferences for sharing PGHD and questions for providers about current processes for collecting PGHD, opportunities to improve or expand the collection of PGHD, and challenges faced when collecting and using this information. Interviews were conducted by phone or videoconference and were audio recorded, transcribed verbatim, and deidentified. Interview transcripts were analyzed deductively and inductively to characterize and explore themes in the data. RESULTS: Patients and providers described how PGHD, including physiologic measurements and experience of symptoms, were currently collected during and between in-person clinic visits for obstetric care. Both patients and providers reported positive perceptions about the collection and use of PGHD during pregnancy. Reported benefits of collecting PGHD included the potential to use data to directly inform patient care (eg, identify issues and adjust medication) and to encourage ongoing patient involvement in their care (eg, increase patient attention to their health). Patients and providers had suggestions for expanding the collection and use of PGHD during pregnancy, and providers also shared considerations about strategies that could be used to expand PGHD collection and use. These strategies included considering the roles of both patients and providers in reporting and interpreting PGHD. Providers also noted the need to consider the unintended consequences of using PGHD that should be anticipated and addressed. CONCLUSIONS: Acknowledging the challenges, suggestions, and considerations voiced by patients and providers can inform the development and implementation of strategies to effectively collect and use PGHD to support patient-centered care during pregnancy.

Screening tools to address social determinants of health in the United States: A systematic review.

The Centers for Medicare & Medicaid Services have mandated that hospitals implement measures to screen social determinants of health (SDoH). We sought to report on available SDoH screening tools. PubMed, Scopus, Web of Science, as well as the grey literature were searched (1980 to November 2023). The included studies were US-based, written in English, and examined a screening tool to assess SDoH. Thirty studies were included in the analytic cohort. The number of questions in any given SDoH assessment tool varied considerably and ranged from 5 to 50 (mean: 16.6). A total of 19 SDoH domains were examined. Housing (n = 23, 92%) and safety/violence (n = 21, 84%) were the domains assessed most frequently. Food/nutrition (n = 17, 68%), income/financial (n = 16, 64%), transportation (n = 15, 60%), family/social support (n = 14, 56%), utilities (n = 13, 52%), and education/literacy (n = 13, 52%) were also commonly included domains in most screening tools. Eighteen studies proposed specific interventions to address SDoH. SDoH screening tools are critical to identify various social needs and vulnerabilities to help develop interventions to address patient needs. Moreover, there is marked heterogeneity of SDoH screening tools, as well as the significant variability in the SDoH domains assessed by currently available screening tools.

Association Between Neighborhood Opportunity, Allostatic Load, and All-Cause Mortality in Patients With Breast Cancer.

PURPOSE: Adverse neighborhood contextual factors may affect breast cancer outcomes through environmental, psychosocial, and biological pathways. The objective of this study is to examine the relationship between allostatic load (AL), neighborhood opportunity, and all-cause mortality among patients with breast cancer. METHODS: Women age 18 years and older with newly diagnosed stage I-III breast cancer who received surgical treatment between January 1, 2012, and December 31, 2020, at a National Cancer Institute Comprehensive Cancer Center were identified. Neighborhood opportunity was operationalized using the 2014-2018 Ohio Opportunity Index (OOI), a composite measure derived from neighborhood level transportation, education, employment, health, housing, crime, and environment. Logistic and Cox regression models tested associations between the OOI, AL, and all-cause mortality. RESULTS: The study cohort included 4,089 patients. Residence in neighborhoods with low OOI was associated with high AL (adjusted odds ratio, 1.21 [95% CI, 1.05 to 1.40]). On adjusted analysis, low OOI was associated with greater risk of all-cause mortality (adjusted hazard ratio [aHR], 1.45 [95% CI, 1.11 to 1.89]). Relative to the highest (99th percentile) level of opportunity, risk of all-cause mortality steeply increased up to the 70th percentile, at which point the rate of increase plateaued. There was no interaction between the composite OOI and AL on all-cause mortality (P = .12). However, there was a higher mortality risk among patients with high AL residing in lower-opportunity environments (aHR, 1.96), but not in higher-opportunity environments (aHR, 1.02; P interaction = .02). CONCLUSION: Lower neighborhood opportunity was associated with higher AL and greater risk of all-cause mortality among patients with breast cancer. Additionally, environmental factors and AL interacted to influence all-cause mortality. Future studies should focus on interventions at the neighborhood and individual level to address socioeconomically based disparities in breast cancer.

Assessment of physician performance for diabetes: a bias-corrected data envelopment analysis model.

BACKGROUND: In most national health systems, especially when universal coverage is provided, family physicians act as gatekeepers, because most healthcare services are only delivered if there is a formal prescription provided by a primary care physician. Although the consumption of healthcare resources is initiated by prescriptions coming from family physicians, studies that evaluate their performance, especially those using a consolidated methodology (e.g.quality and efficiency) are limited in the literature. The specific aim of this paper is to propose a method for assessing primary care performance. METHODS: The novelty of the proposed model is twofold. First, physician performance is assessed following a clinical pathway that focuses on homogeneous groups of patients, in this case, diabetes patients. Second, we argue that performance should not be limited to efficiency, but should encompass clinical effectiveness. Performance assessment is not based on the physician practice as a whole, but on a single disease, in this paper, diabetes. Data were collected from a sample of family physician practices in Italy, and Data Envelopment Analysis (DEA) is used to evaluate their efficiency performance. RESULTS: We found that 35 of 96 practices were efficient based on the standard DEA model. The number of efficient practices decreased based on three restricted models that explored various behavioural preferences of physicians in relation to patient visits, medication administration and referrals to hospitals. CONCLUSION: The efficiency assessment is completed by a post-hoc evaluation of effectiveness, which in this study is defined as patient care adherence to the prescribed guideline. This study identified best practices both in terms of efficiency and effectiveness. The methods used in this paper are generalisable and could be applied to many other chronic conditions, which may constitute the prevalent activities within the primary care.

Developing and testing an integrated patient mHealth and provider dashboard application system for type 2 diabetes management among Medicaid-enrolled pregnant individuals based on a user-centered approach: Mixed-methods study.

Background: A tailored and integrated technology solution (patient mHealth application and provider dashboard) can provide a 360° view of Medicaid-enrolled patients with type 2 diabetes (T2D) during pregnancy that could improve health outcomes and address health inequities. Objectives: To develop a set of user specifications for the mHealth and dashboard applications, develop prototypes based on user needs, and collect initial impressions of the prototypes to subsequently develop refined tools that are ready for deployment. Methods: Study activities followed a double-diamond framework with a participatory design mindset. Activities were divided into two phases focused on a qualitative inquiry about participant needs and values (phase 1) and design, development, and usability testing of low and high-fidelity prototypes (phase 2). Results: We identified themes that exemplified pregnancy experience among Medicaid-enrolled individuals with T2D. Patients (n = 7) and providers (n = 7) expressed a core set of expectations for the mHealth and dashboard applications. Participants provided feedback to improve the mHealth and dashboard. For both applications, participants reported scores for the NASA Task load Survey (TLX) that were in the 20th percentile of national TLX scores. Conclusions: Digital health tools have the ability to transform health care among Medicaid-enrolled patients with T2D during pregnancy, with the goal of managing their blood glucose levels, which is a precursor to experiencing a successful pregnancy and birth. Distilling patient and provider needs and preferences-then using them, along with prior studies and theory, to develop applications-holds great potential in tackling complicated health care issues.

Patient and provider perspectives on the use of patient portals during pregnancy and the postpartum period.

INTRODUCTION: Interest in the use of patient portals to support prenatal and postpartum care is growing. This study was conducted to understand patient and provider perspectives about the impact of portal use during pregnancy and the postpartum period. METHODS: Interviews were conducted with 30 pregnant or postpartum patients and 15 obstetric care providers at an academic medical center that offers its patients access to an outpatient portal. Interview transcripts were analyzed deductively and inductively to categorize findings and identify emergent themes. RESULTS: Patients and providers described how use of a patient portal during pregnancy and postpartum impacted communication (by supporting convenient communication and access to information), care processes (by aiding appointment attendance and helping with medication management), and care experience (by reducing anxiety and promoting patient involvement). Interviewees provided suggestions to improve patient portal use in obstetric care including using portals to increase access to educational materials and supportive resources, to collect patient-generated data, and to increase patient involvement in postpartum care. DISCUSSION: Patient portals have particular value for patients' use during pregnancy and the postpartum period due to the frequency of healthcare visits and the heightened attention to one's health during this time. There are opportunities to tailor portal content and functions to patients' needs to improve communication, care processes, and care experiences for this patient population. Further improving the functionality of patient portals for patients' use during pregnancy and the postpartum period has the potential to positively impact patient experiences and health outcomes.