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Background: Health care systems are increasingly screening for unmet social needs. The association between patient-reported social needs and health care utilization is not well understood. Objective: To investigate the association between patient-reported social needs, measured by the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE), and inpatient and emergency department (ED) utilization. Design: This cohort study analyzed merged 2017–2019 electronic health record (EHR) data across multiple health systems. Participants: Adult patients from a federally qualified health center (FQHC) in central North Carolina who completed PRAPARE as part of a primary care visit with behavioral health services. Main Measures: The count of up to 12 unmet social needs, aggregated as 0, 1, 2, or 3 +. Outcomes include the probability of an ED visit and hospitalization 12 months after PRAPARE assessment, modeled by logistic regressions controlling for age, sex, race, ethnicity, comorbidity burden, being uninsured, and prior utilization in the past 12 months. Key Results: The study population consisted of 1924 adults (38.7% male, 50.1% Black, 36.3% Hispanic, 55.9% unemployed, 68.2% of patients reported 1 + needs). Those with more needs were younger, more likely to be unemployed, and experienced greater comorbidity burden. 35.3% of patients had ED visit(s) and 36.3% had hospitalization(s) 1 year after PRAPARE assessment. In adjusted analysis, having 3 + needs was associated with a percentage point increase in the predicted probability of hospitalization (average marginal effect 0.06, SE 0.03, p < 0.05) compared with having 0 needs. Similarly, having 2 needs (0.07, SE 0.03, p < 0.05) or 3 + needs (0.06, SE 0.03, p < 0.05) was associated with increased probability of ED visits compared to 0 needs. Conclusions: Patient-reported social needs were common and associated with health care utilization patterns. Future research should identify interventions to address unmet social needs to improve health and avoid potentially preventable escalating medical intervention. [ABSTRACT FROM AUTHOR]

Multilevel interventions (MLIs) are appropriate to reduce health disparities among Indigenous peoples because of their ability to address these communities' diverse histories, dynamics, cultures, politics, and environments. Intervention science has highlighted the importance of context-sensitive MLIs in Indigenous communities that can prioritize Indigenous and local knowledge systems and emphasize the collective versus the individual. This paradigm shift away from individual-level focus interventions to community-level focus interventions underscores the need for community engagement and diverse partnerships in MLI design, implementation, and evaluation. In this paper, we discuss three case studies addressing how Indigenous partners collaborated with researchers in each stage of the design, implementation, and evaluation of MLIs to reduce health disparities impacting their communities. We highlight the following: (1) collaborations with multiple, diverse tribal partners to carry out MLIs which require iterative, consistent conversations over time; (2) inclusion of qualitative and Indigenous research methods in MLIs as a way to honor Indigenous and local knowledge systems as well as a way to understand a health disparity phenomenon in a community; and (3) relationship building, maintenance, and mutual respect among MLI partners to reconcile past research abuses, prevent extractive research practices, decolonize research processes, and generate co-created knowledge between Indigenous and academic communities. [ABSTRACT FROM AUTHOR]

Background: Routine concordance evaluation between pathology and imaging findings was introduced for CT-guided biopsies. Purpose: To analyze malignancy rate in concordant, discordant, and indeterminate non-malignant results of CT-guided lung biopsies. Methods: Concordance between pathology results and imaging findings of consecutive patients undergoing CT-guided lung biopsy between 7/1/2016 and 9/30/2021 was assessed during routine meetings by procedural radiologists. Concordant was defined as pathology consistent with imaging findings; discordant was used when pathology could not explain imaging findings; indeterminate when pathology could explain imaging findings but there was concern for malignancy. Recommendations for discordant and indeterminate were provided. All the malignant results were concordant. Pathology of repeated biopsy, surgical sample, or follow-up was considered reference standard. Results: Consecutive 828 CT-guided lung biopsies were performed on 795 patients (median age 70 years, IQR 61–77), 423/828 (51%) women. On pathology, 224/828 (27%) were non-malignant. Among the non-malignant, radiology-pathology concordance determined 138/224 (62%) to be concordant with imaging findings, 54/224 (24%) discordant, and 32/224 (14%) indeterminate. When compared to the reference standard, 33/54 (61%) discordant results, 6/30 (20%) indeterminate, and 3/133 (2%) concordant were malignant. The prevalence of malignancy in the three groups was significantly different (p < 0.001). Time to diagnosis was significantly different between patients who reached the diagnosis with imaging follow-up (median 114 days, IQR 69–206) compared to repeat biopsy (33 days, IQR 18–133) (p = 0.01). Conclusion: Routine radiology-pathology concordance evaluation of CT-guided lung biopsy correctly identifies patients at high risk for missed diagnosis of malignancy. Repeat biopsy is the fastest method to reach diagnosis. Clinical relevance statement: A routine radiology-pathology concordance assessment identifies patients with non-malignant CT-guided lung biopsy result who are at greater risk of missed diagnosis of malignancy. Key Points: • A routine radiology-pathology concordance evaluation of CT-guided lung biopsies classified 224 non-malignant results as concordant, discordant, or indeterminate. • The percentage of malignancy on follow-up was significantly different in concordant (2%), discordant (61%), and indeterminate (20%) (p < 0.001). • Time to definitive diagnosis was significantly shorter with repeat biopsy (33 days), compared to imaging follow-up (114 days), p = 0.01. [ABSTRACT FROM AUTHOR]

The article focuses on the HIMSS-SIIM Enterprise Imaging Community White Papers, reflecting on past achievements and future directions, highlighting the collaboration between HIMSS and SIIM in generating informative documents. It discusses the impact and future prospects of these white papers, marking the renaming of SIIM's Journal of Digital Imaging to the Journal of Imaging Informatics in Medicine (JIIM).

This document, titled "Health Keynesianism: Why Full Employment Policy Matters for Population Health," discusses the relationship between income and health and argues for the importance of full employment in improving income distribution and promoting health. The author explains that full employment improves worker bargaining power, leading to higher wages, decreased income inequality, and improved health outcomes. The document also discusses the principles of Health Keynesianism, which include using monetary and fiscal policy to pursue full employment and avoiding unemployment crises through financial sector regulation. The author concludes that full employment is a feasible way to improve health conditions and should be taken seriously in health equity discussions. [Extracted from the article]

Background: Food insecurity is associated with many aspects of poor health. However, trials of food insecurity interventions typically focus on outcomes of interest to funders, such as healthcare use, cost, or clinical performance metrics, rather than quality of life outcomes that may be prioritized by individuals who experience food insecurity. Objective: To emulate a trial of a food insecurity elimination intervention, and quantify its estimated effects on health utility, health-related quality of life, and mental health. Design: Target trial emulation using longitudinal, nationally representative data, from the USA, 2016–2017. Participants: A total of 2013 adults in the Medical Expenditure Panel Survey screened positive for food insecurity, representing 32 million individuals. Main Measures: Food insecurity was assessed using the Adult Food Security Survey Module. The primary outcome was the SF-6D (Short-Form Six Dimension) measure of health utility. Secondary outcomes were mental component score (MCS) and physical component score (PCS) of the Veterans RAND 12-Item Health Survey (a measure of health-related quality of life), Kessler 6 (K6) psychological distress, and Patient Health Questionnaire 2-item (PHQ2) depressive symptoms. Key Results: We estimated that food insecurity elimination would improve health utility by 80 QALYs per 100,000 person-years, or 0.008 QALYs per person per year (95% CI 0.002 to 0.014, p = 0.005), relative to the status quo. We also estimated that food insecurity elimination would improve mental health (difference in MCS [95% CI]: 0.55 [0.14 to 0.96]), physical health (difference in PCS: 0.44 [0.06 to 0.82]), psychological distress (difference in K6: −0.30 [−0.51 to −0.09]), and depressive symptoms (difference in PHQ-2: −0.13 [−0.20 to −0.07]). Conclusions: Food insecurity elimination may improve important, but understudied, aspects of health. Evaluations of food insecurity interventions should holistically investigate their potential to improve many different aspects of health. [ABSTRACT FROM AUTHOR]

To improve the estimation of healthcare expenditures by introducing a novel method that is well-suited to situations where data exhibit strong skewness and zero-inflation. Simulations, and two real-world datasets: the 2016–2017 Medical Expenditure Panel Survey; the Back Pain Outcomes using Longitudinal Data. Super learner is an ensemble machine learning approach that can combine several algorithms to improve estimation. We propose a two-stage super learner that is well suited for healthcare expenditure data by separately estimating the probability of any healthcare expenditure and the mean amount of healthcare expenditure conditional on having healthcare expenditures. These estimates can then be combined to yield a single estimate of expenditures for each observation. The analytical strategy can flexibly incorporate a range of individual estimation approaches for each stage of estimation, including both regression-based approaches and machine learning algorithms such as random forests. We compare the performance of the two-stage super learner with a one-stage super learner, and with multiple individual algorithms for estimation of healthcare cost under a broad range of data settings in simulated and real data. The predictive performance was compared using Mean Squared Error and R2. Our results indicate that the two-stage super learner has better performance compared with a one-stage super learner and individual algorithms, for healthcare cost estimation under a wide variety of settings in simulations and in empirical analyses. The improvement of the two-stage super learner over the one-stage super learner was particularly evident in settings when zero-inflation is high. [ABSTRACT FROM AUTHOR]

Background: Cross-sectional studies have found that health-related quality of life and mental health are worse among food-insecure compared with food-secure individuals. However, how these outcomes change as food insecurity changes is unclear. Objective: To evaluate how common patient-reported health-related quality of life and mental health scales change in response to changes in food security. Design: Retrospective cohort study using data representative of the civilian, adult, non-institutionalized population of the USA. Participants: Food insecure adults who completed the 2016–2017 Medical Expenditure Panel Survey. Main Measures: Mental health, as measured by the mental component score of the Veterans Rand 12-Item Health Survey (VR-12) (primary outcome), along physical health (physical component score of the VR-12), self-rated health status, psychological distress (Kessler 6), depressive symptoms (PHQ2), and the SF-6D measure of health utility. We fit linear regression models adjusted for baseline outcome level, age, gender, race/ethnicity, education, health insurance, and family size followed by predictive margins to estimate the change in outcome associated with a 1-point improvement in food security. Key Results: A total of 1,390 food-insecure adults were included. A 1-point improvement in food security was associated with a 0.38 (95%CI 0.62 to 0.14)-point improvement in mental health, a 0.15 (95%CI 0.02 to 0.27)-point improvement in psychological distress, a 0.05 (95%CI 0.01 to 0.09)-point improvement in depressive symptoms, and a 0.003 (95%CI 0.000 to 0.007)-point improvement in health utility. Point estimates for physical health and self-rated health were in the direction of improvement, but were not statistically significant. Conclusions: Improvement in food insecurity was associated with improvement in several patient-reported outcomes. Further work should investigate whether similar changes are seen in food insecurity interventions, and the most useful scales for assessing changes in health-related quality of life and mental health in food insecurity interventions. [ABSTRACT FROM AUTHOR]

Despite technological advances in the analysis of digital images for medical consultations, many health information systems lack the ability to correlate textual descriptions of image findings linked to the actual images. Images and reports often reside in separate silos in the medical record throughout the process of image viewing, report authoring, and report consumption. Forward-thinking centers and early adopters have created interactive reports with multimedia elements and embedded hyperlinks in reports that connect the narrative text with the related source images and measurements. Most of these solutions rely on proprietary single-vendor systems for viewing and reporting in the absence of any encompassing industry standards to facilitate interoperability with the electronic health record (EHR) and other systems. International standards have enabled the digitization of image acquisition, storage, viewing, and structured reporting. These provide the foundation to discuss enhanced reporting. Lessons learned in the digital transformation of radiology and pathology can serve as a basis for interactive multimedia reporting (IMR) across image-centric medical specialties. This paper describes the standard-based infrastructure and communications to fulfill recently defined clinical requirements through a consensus from an international workgroup of multidisciplinary medical specialists, informaticists, and industry participants. These efforts have led toward the development of an Integrating the Healthcare Enterprise (IHE) profile that will serve as a foundation for interoperable interactive multimedia reporting. [ABSTRACT FROM AUTHOR]

Background: Compared to traditional Medicare (TM), Medicare Advantage (MA) plans impose out-of-pocket cost limits and offer extra benefits, potentially providing financial relief for MA enrollees, especially for those with food insecurity.To examine whether the prevalence of food insecurity differs between TM and MA enrollees at baseline and then examine whether MA enrollment in a baseline year is associated with less financial hardships in the following year, relative to TM enrollment, especially for those experiencing food insecurity.We conducted a retrospective longitudinal cohort study.Our analysis included 2807 Medicare beneficiaries (weighted sample size, 23,963,947) who maintained continuous enrollment in either TM or MA in both 2020 and 2021 from the Medical Expenditure Panel Survey.We assessed outcomes related to financial hardships in health care and non-health care domains (measured in 2021). Our primary independent variables were food insecurity and MA enrollment (measured in 2020).The point estimate of food insecurity prevalence was greater among MA enrollees than TM enrollees, but the difference was not statistically significant (1.1 percentage points [95% CI, − 1.0, 3.4]). Furthermore, there is evidence that compared to TM enrollment, MA enrollment did not mitigate the risk of financial hardship, particularly for food-insecure enrollees. Rather, food-secure MA enrollees faced greater financial hardship in the following year than food-secure TM enrollees (11.2% [8.9–13.6] and 7.6% [6.9–8.3] for problems paying medical bills and 5.5% [4.6–6.4] and 2.8% [2.1–3.6] for paying medical bills over time). Moreover, the point estimate of financial hardship was higher among food-insecure MA enrollees than food-insecure TM enrollees (21.5% [5.4–37.5] and 11.2% [4.1–18.4] and 23.7% [9.6–37.9] and 6.9% [0.5–13.3]) despite the lack of statistical significance.These findings suggest that the promise of financial protection offered by MA plans has not been fully realized, particularly for those with food insecurity.Objective: Compared to traditional Medicare (TM), Medicare Advantage (MA) plans impose out-of-pocket cost limits and offer extra benefits, potentially providing financial relief for MA enrollees, especially for those with food insecurity.To examine whether the prevalence of food insecurity differs between TM and MA enrollees at baseline and then examine whether MA enrollment in a baseline year is associated with less financial hardships in the following year, relative to TM enrollment, especially for those experiencing food insecurity.We conducted a retrospective longitudinal cohort study.Our analysis included 2807 Medicare beneficiaries (weighted sample size, 23,963,947) who maintained continuous enrollment in either TM or MA in both 2020 and 2021 from the Medical Expenditure Panel Survey.We assessed outcomes related to financial hardships in health care and non-health care domains (measured in 2021). Our primary independent variables were food insecurity and MA enrollment (measured in 2020).The point estimate of food insecurity prevalence was greater among MA enrollees than TM enrollees, but the difference was not statistically significant (1.1 percentage points [95% CI, − 1.0, 3.4]). Furthermore, there is evidence that compared to TM enrollment, MA enrollment did not mitigate the risk of financial hardship, particularly for food-insecure enrollees. Rather, food-secure MA enrollees faced greater financial hardship in the following year than food-secure TM enrollees (11.2% [8.9–13.6] and 7.6% [6.9–8.3] for problems paying medical bills and 5.5% [4.6–6.4] and 2.8% [2.1–3.6] for paying medical bills over time). Moreover, the point estimate of financial hardship was higher among food-insecure MA enrollees than food-insecure TM enrollees (21.5% [5.4–37.5] and 11.2% [4.1–18.4] and 23.7% [9.6–37.9] and 6.9% [0.5–13.3]) despite the lack of statistical significance.These findings suggest that the promise of financial protection offered by MA plans has not been fully realized, particularly for those with food insecurity.Design: Compared to traditional Medicare (TM), Medicare Advantage (MA) plans impose out-of-pocket cost limits and offer extra benefits, potentially providing financial relief for MA enrollees, especially for those with food insecurity.To examine whether the prevalence of food insecurity differs between TM and MA enrollees at baseline and then examine whether MA enrollment in a baseline year is associated with less financial hardships in the following year, relative to TM enrollment, especially for those experiencing food insecurity.We conducted a retrospective longitudinal cohort study.Our analysis included 2807 Medicare beneficiaries (weighted sample size, 23,963,947) who maintained continuous enrollment in either TM or MA in both 2020 and 2021 from the Medical Expenditure Panel Survey.We assessed outcomes related to financial hardships in health care and non-health care domains (measured in 2021). Our primary independent variables were food insecurity and MA enrollment (measured in 2020).The point estimate of food insecurity prevalence was greater among MA enrollees than TM enrollees, but the difference was not statistically significant (1.1 percentage points [95% CI, − 1.0, 3.4]). Furthermore, there is evidence that compared to TM enrollment, MA enrollment did not mitigate the risk of financial hardship, particularly for food-insecure enrollees. Rather, food-secure MA enrollees faced greater financial hardship in the following year than food-secure TM enrollees (11.2% [8.9–13.6] and 7.6% [6.9–8.3] for problems paying medical bills and 5.5% [4.6–6.4] and 2.8% [2.1–3.6] for paying medical bills over time). Moreover, the point estimate of financial hardship was higher among food-insecure MA enrollees than food-insecure TM enrollees (21.5% [5.4–37.5] and 11.2% [4.1–18.4] and 23.7% [9.6–37.9] and 6.9% [0.5–13.3]) despite the lack of statistical significance.These findings suggest that the promise of financial protection offered by MA plans has not been fully realized, particularly for those with food insecurity.Participants: Compared to traditional Medicare (TM), Medicare Advantage (MA) plans impose out-of-pocket cost limits and offer extra benefits, potentially providing financial relief for MA enrollees, especially for those with food insecurity.To examine whether the prevalence of food insecurity differs between TM and MA enrollees at baseline and then examine whether MA enrollment in a baseline year is associated with less financial hardships in the following year, relative to TM enrollment, especially for those experiencing food insecurity.We conducted a retrospective longitudinal cohort study.Our analysis included 2807 Medicare beneficiaries (weighted sample size, 23,963,947) who maintained continuous enrollment in either TM or MA in both 2020 and 2021 from the Medical Expenditure Panel Survey.We assessed outcomes related to financial hardships in health care and non-health care domains (measured in 2021). Our primary independent variables were food insecurity and MA enrollment (measured in 2020).The point estimate of food insecurity prevalence was greater among MA enrollees than TM enrollees, but the difference was not statistically significant (1.1 percentage points [95% CI, − 1.0, 3.4]). Furthermore, there is evidence that compared to TM enrollment, MA enrollment did not mitigate the risk of financial hardship, particularly for food-insecure enrollees. Rather, food-secure MA enrollees faced greater financial hardship in the following year than food-secure TM enrollees (11.2% [8.9–13.6] and 7.6% [6.9–8.3] for problems paying medical bills and 5.5% [4.6–6.4] and 2.8% [2.1–3.6] for paying medical bills over time). Moreover, the point estimate of financial hardship was higher among food-insecure MA enrollees than food-insecure TM enrollees (21.5% [5.4–37.5] and 11.2% [4.1–18.4] and 23.7% [9.6–37.9] and 6.9% [0.5–13.3]) despite the lack of statistical significance.These findings suggest that the promise of financial protection offered by MA plans has not been fully realized, particularly for those with food insecurity.Main Measures: Compared to traditional Medicare (TM), Medicare Advantage (MA) plans impose out-of-pocket cost limits and offer extra benefits, potentially providing financial relief for MA enrollees, especially for those with food insecurity.To examine whether the prevalence of food insecurity differs between TM and MA enrollees at baseline and then examine whether MA enrollment in a baseline year is associated with less financial hardships in the following year, relative to TM enrollment, especially for those experiencing food insecurity.We conducted a retrospective longitudinal cohort study.Our analysis included 2807 Medicare beneficiaries (weighted sample size, 23,963,947) who maintained continuous enrollment in either TM or MA in both 2020 and 2021 from the Medical Expenditure Panel Survey.We assessed outcomes related to financial hardships in health care and non-health care domains (measured in 2021). Our primary independent variables were food insecurity and MA enrollment (measured in 2020).The point estimate of food insecurity prevalence was greater among MA enrollees than TM enrollees, but the difference was not statistically significant (1.1 percentage points [95% CI, − 1.0, 3.4]). Furthermore, there is evidence that compared to TM enrollment, MA enrollment did not mitigate the risk of financial hardship, particularly for food-insecure enrollees. Rather, food-secure MA enrollees faced greater financial hardship in the following year than food-secure TM enrollees (11.2% [8.9–13.6] and 7.6% [6.9–8.3] for problems paying medical bills and 5.5% [4.6–6.4] and 2.8% [2.1–3.6] for paying medical bills over time). Moreover, the point estimate of financial hardship was higher among food-insecure MA enrollees than food-insecure TM enrollees (21.5% [5.4–37.5] and 11.2% [4.1–18.4] and 23.7% [9.6–37.9] and 6.9% [0.5–13.3]) despite the lack of statistical significance.These findings suggest that the promise of financial protection offered by MA plans has not been fully realized, particularly for those with food insecurity.Results: Compared to traditional Medicare (TM), Medicare Advantage (MA) plans impose out-of-pocket cost limits and offer extra benefits, potentially providing financial relief for MA enrollees, especially for those with food insecurity.To examine whether the prevalence of food insecurity differs between TM and MA enrollees at baseline and then examine whether MA enrollment in a baseline year is associated with less financial hardships in the following year, relative to TM enrollment, especially for those experiencing food insecurity.We conducted a retrospective longitudinal cohort study.Our analysis included 2807 Medicare beneficiaries (weighted sample size, 23,963,947) who maintained continuous enrollment in either TM or MA in both 2020 and 2021 from the Medical Expenditure Panel Survey.We assessed outcomes related to financial hardships in health care and non-health care domains (measured in 2021). Our primary independent variables were food insecurity and MA enrollment (measured in 2020).The point estimate of food insecurity prevalence was greater among MA enrollees than TM enrollees, but the difference was not statistically significant (1.1 percentage points [95% CI, − 1.0, 3.4]). Furthermore, there is evidence that compared to TM enrollment, MA enrollment did not mitigate the risk of financial hardship, particularly for food-insecure enrollees. Rather, food-secure MA enrollees faced greater financial hardship in the following year than food-secure TM enrollees (11.2% [8.9–13.6] and 7.6% [6.9–8.3] for problems paying medical bills and 5.5% [4.6–6.4] and 2.8% [2.1–3.6] for paying medical bills over time). Moreover, the point estimate of financial hardship was higher among food-insecure MA enrollees than food-insecure TM enrollees (21.5% [5.4–37.5] and 11.2% [4.1–18.4] and 23.7% [9.6–37.9] and 6.9% [0.5–13.3]) despite the lack of statistical significance.These findings suggest that the promise of financial protection offered by MA plans has not been fully realized, particularly for those with food insecurity.Conclusion: Compared to traditional Medicare (TM), Medicare Advantage (MA) plans impose out-of-pocket cost limits and offer extra benefits, potentially providing financial relief for MA enrollees, especially for those with food insecurity.To examine whether the prevalence of food insecurity differs between TM and MA enrollees at baseline and then examine whether MA enrollment in a baseline year is associated with less financial hardships in the following year, relative to TM enrollment, especially for those experiencing food insecurity.We conducted a retrospective longitudinal cohort study.Our analysis included 2807 Medicare beneficiaries (weighted sample size, 23,963,947) who maintained continuous enrollment in either TM or MA in both 2020 and 2021 from the Medical Expenditure Panel Survey.We assessed outcomes related to financial hardships in health care and non-health care domains (measured in 2021). Our primary independent variables were food insecurity and MA enrollment (measured in 2020).The point estimate of food insecurity prevalence was greater among MA enrollees than TM enrollees, but the difference was not statistically significant (1.1 percentage points [95% CI, − 1.0, 3.4]). Furthermore, there is evidence that compared to TM enrollment, MA enrollment did not mitigate the risk of financial hardship, particularly for food-insecure enrollees. Rather, food-secure MA enrollees faced greater financial hardship in the following year than food-secure TM enrollees (11.2% [8.9–13.6] and 7.6% [6.9–8.3] for problems paying medical bills and 5.5% [4.6–6.4] and 2.8% [2.1–3.6] for paying medical bills over time). Moreover, the point estimate of financial hardship was higher among food-insecure MA enrollees than food-insecure TM enrollees (21.5% [5.4–37.5] and 11.2% [4.1–18.4] and 23.7% [9.6–37.9] and 6.9% [0.5–13.3]) despite the lack of statistical significance.These findings suggest that the promise of financial protection offered by MA plans has not been fully realized, particularly for those with food insecurity. [ABSTRACT FROM AUTHOR]

Background: Food insecurity, limited or uncertain access to enough food for an active, healthy life, affected over 37 million Americans in 2018. Food insecurity is likely to be associated with worse health-related quality of life (HRQoL), but this association has not been measured with validated instruments in nationally representative samples. Given growing interest understanding food insecurity's role in health outcomes, it would be useful to learn what HRQoL measures best capture the experience of those with food insecurity. Objective: To determine the association between food insecurity and several validated HRQoL instruments in US adults. Design: Cross-sectional. Participants: US adults (age ≥ 18), weighted to be nationally representative. Main Measures: Food insecurity was assessed with three items derived from the USDA Household Food Security Survey Module. HRQoL was assessed using PROMIS-Preference (PROPr), which contains 7 PROMIS domains, self-rated health (SRH), Euroqol-5D-5L (EQ-5D), Health Utilities Index (HUI), and Short Form-6D (SF-6D). Key Results: In December 2017, 4142 individuals completed at least part of the survey (31% response rate), of whom 4060 (98.0%) reported food security information. Of survey respondents, 51.7% were women, 12.5% self-identified as black, 15.8% were Hispanic, and 11.0% did not have a high school diploma. 14.1% of respondents reported food insecurity. In adjusted analyses, food insecurity was associated with worse HRQoL across all instruments and PROMIS domains (p <.0001 for all). The magnitude of the difference between food-insecure and food-secure participants was largest with the SF-6D, EQ-5D, and PROPr; among individual PROMIS domain scores, the largest difference was for ability to participate in social roles. Conclusions: Food insecurity is strongly associated with worse HRQoL, with differences between food-secure and food-insecure individuals best measured using the SF-6D, EQ-5D, and PROPr. Future work should develop a specific instrument to measure changes in HRQoL in food insecurity interventions. [ABSTRACT FROM AUTHOR]

Diagnostic and evidential static image, video clip, and sound multimedia are captured during routine clinical care in cardiology, dermatology, ophthalmology, pathology, physiatry, radiation oncology, radiology, endoscopic procedural specialties, and other medical disciplines. Providers typically describe the multimedia findings in contemporaneous electronic health record clinical notes or associate a textual interpretative report. Visual communication aids commonly used to connect, synthesize, and supplement multimedia and descriptive text outside medicine remain technically challenging to integrate into patient care. Such beneficial interactive elements may include hyperlinks between text, multimedia elements, alphanumeric and geometric annotations, tables, graphs, timelines, diagrams, anatomic maps, and hyperlinks to external educational references that patients or provider consumers may find valuable. This HIMSS-SIIM Enterprise Imaging Community workgroup white paper outlines the current and desired clinical future state of interactive multimedia reporting (IMR). The workgroup adopted a consensus definition of IMR as "interactive medical documentation that combines clinical images, videos, sound, imaging metadata, and/or image annotations with text, typographic emphases, tables, graphs, event timelines, anatomic maps, hyperlinks, and/or educational resources to optimize communication between medical professionals, and between medical professionals and their patients." This white paper also serves as a precursor for future efforts toward solving technical issues impeding routine interactive multimedia report creation and ingestion into electronic health records. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) models for decision support have been developed for clinical settings such as radiology, but little work evaluates the potential impact of such systems. In this study, physicians received chest X-rays and diagnostic advice, some of which was inaccurate, and were asked to evaluate advice quality and make diagnoses. All advice was generated by human experts, but some was labeled as coming from an AI system. As a group, radiologists rated advice as lower quality when it appeared to come from an AI system; physicians with less task-expertise did not. Diagnostic accuracy was significantly worse when participants received inaccurate advice, regardless of the purported source. This work raises important considerations for how advice, AI and non-AI, should be deployed in clinical environments. [ABSTRACT FROM AUTHOR]

Things would be different, of course, if our outcomes had been different - for example a time-to-event outcome, or a risk outcome (i.e., the probability of an event occurring in a given period of time) or a rate outcome (i.e., the number of events occurring in a given period of time). It is this second meaning, the time over which the outcome is assessed, that is relevant for discussions of immortal time bias - if the start of the outcome assessment window precedes "treatment assignment", this can create immortal time bias. The outcome assessment window we used in this study is reasonable for the study outcomes - responses on health-related quality of life and mental health scales. [Extracted from the article]

Purpose Of Review: Machine learning approaches-which seek to predict outcomes or classify patient features by recognizing patterns in large datasets-are increasingly applied to clinical epidemiology research on diabetes. Given its novelty and emergence in fields outside of biomedical research, machine learning terminology, techniques, and research findings may be unfamiliar to diabetes researchers. Our aim was to present the use of machine learning approaches in an approachable way, drawing from clinical epidemiological research in diabetes published from 1 Jan 2017 to 1 June 2020.Recent Findings: Machine learning approaches using tree-based learners-which produce decision trees to help guide clinical interventions-frequently have higher sensitivity and specificity than traditional regression models for risk prediction. Machine learning approaches using neural networking and "deep learning" can be applied to medical image data, particularly for the identification and staging of diabetic retinopathy and skin ulcers. Among the machine learning approaches reviewed, researchers identified new strategies to develop standard datasets for rigorous comparisons across older and newer approaches, methods to illustrate how a machine learner was treating underlying data, and approaches to improve the transparency of the machine learning process. Machine learning approaches have the potential to improve risk stratification and outcome prediction for clinical epidemiology applications. Achieving this potential would be facilitated by use of universal open-source datasets for fair comparisons. More work remains in the application of strategies to communicate how the machine learners are generating their predictions. [ABSTRACT FROM AUTHOR]

Background: The relationship between risk factor or biomarker trajectories and contemporaneous short-term clinical outcomes is poorly understood. In diabetes patients, it is unknown whether hemoglobin A1c (HbA1c) trajectories are associated with clinical outcomes and can inform care in scenarios in which a single HbA1c is uninformative, for example, after a diagnosis of coronary artery disease (CAD). Objective: To compare associations of HbA1c trajectories and single HbA1c values with short-term mortality in diabetes patients evaluated for CAD Design: Retrospective observational cohort study Participants: Diabetes patients (n = 7780) with and without angiographically defined CAD Main Measures: We used joint latent class mixed models to simultaneously fit HbA1c trajectories and estimate association with 2-year mortality after cardiac catheterization, adjusting for clinical and demographic covariates. Key Results: Three HBA1c trajectory classes were identified: individuals with stable glycemia (class A; n = 6934 [89%]; mean baseline HbA1c 6.9%), with declining HbA1c (class B; n = 364 [4.7%]; mean baseline HbA1c 11.6%), and with increasing HbA1c (class C; n = 482 [6.2%]; mean baseline HbA1c 8.5%). HbA1c trajectory class was associated with adjusted 2-year mortality (3.0% [95% CI 2.8, 3.2] for class A, 3.1% [2.1, 4.2] for class B, and 4.2% [3.4, 4.9] for class C; global P = 0.047, P = 0.03 comparing classes A and C, P > 0.05 for other pairwise comparisons). Baseline HbA1c was not associated with 2-year mortality (P = 0.85; hazard ratios 1.01 [0.96, 1.06] and 1.02 [0.95, 1.10] for HbA1c 7–9% and ≥ 9%, respectively, relative to HbA1c < 7%). The association between HbA1c trajectories and mortality did not differ between those with and without CAD (interaction P = 0.1). Conclusions: In clinical settings where single HbA1c measurements provide limited information, HbA1c trajectories may help stratify risk of complications in diabetes patients. Joint latent class modeling provides a generalizable approach to examining relationships between biomarker trajectories and clinical outcomes in the era of near-universal adoption of electronic health records. [ABSTRACT FROM AUTHOR]

Medical documentation is one of the primary methods by which physicians share clinical information and impressions over time with one another. As the adage says, "a picture is worth a thousand words," and physicians have started leveraging consumer mobile technology to share images with one another. However, image sharing often uses short message service texting and similar methods, which can be noncompliant with privacy regulations and can also limit the ability to communicate information longitudinally and across specialties. Sharing of such information is increasingly important, however, as smaller practices are joining to create large geographically spread out health care networks. To this end, we developed an application to acquire and store images via smartphone and seamlessly transfer into the patient's electronic medical record (EMR) to enable digital consults and longitudinal evaluation in a private and compliant method. [ABSTRACT FROM AUTHOR]

Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's chest, but requires specialized training for proper interpretation. With the advent of high performance general purpose computer vision algorithms, the accurate automated analysis of chest radiographs is becoming increasingly of interest to researchers. Here we describe MIMIC-CXR, a large dataset of 227,835 imaging studies for 65,379 patients presenting to the Beth Israel Deaconess Medical Center Emergency Department between 2011–2016. Each imaging study can contain one or more images, usually a frontal view and a lateral view. A total of 377,110 images are available in the dataset. Studies are made available with a semi-structured free-text radiology report that describes the radiological findings of the images, written by a practicing radiologist contemporaneously during routine clinical care. All images and reports have been de-identified to protect patient privacy. The dataset is made freely available to facilitate and encourage a wide range of research in computer vision, natural language processing, and clinical data mining. Measurement(s) Radiograph • investigation results report Technology Type(s) Chest Radiography • digital curation • Radiologist Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.10303823 [ABSTRACT FROM AUTHOR]

Purpose Of Review: To explore the relationship between the built environment and type 2 diabetes, considering both risk factors and policies to reduce risk. The built environment refers to the physical characteristics of the areas in which people live including buildings, streets, open spaces, and infrastructure.Recent Findings: A review of current literature suggests an association between the built environment and type 2 diabetes, likely driven by two key pathways-physical activity and the food environment. Other hypothesized mechanisms linking the built environment and type 2 diabetes include housing policy, but evidence in these areas is underdeveloped. Policies designed to enhance the built environment for diabetes risk reduction are mechanistically plausible, but as of yet, little direct evidence supports their effectiveness in reducing in type 2 diabetes risk. Future work should rigorously evaluate policies meant to reduce type 2 diabetes via the built environment. [ABSTRACT FROM AUTHOR]

Background: Food insecurity, defined as inconsistent food access owing to cost, leads to poor health.Objective: To test whether a medically tailored meal delivery program improved dietary quality in individuals with type 2 diabetes and food insecurity.Design: Randomized cross-over clinical trial.Participants: Forty-four adults with diabetes, hemoglobin A1c > 8.0%, and food insecurity (defined as at least one positive item on the two-item "Hunger Vital Sign").Intervention: In the Community Servings: Food as Medicine for Diabetes cross-over clinical trial (NCT02426138), conducted from June 2015 to July 2017, we randomly assigned the order of "on-meals" (home delivery of 10 meals/week for 12 weeks delivered by Community Servings, a non-profit organization) and "off-meals" (12 weeks usual care and a Choose MyPlate healthy eating brochure) periods.Main Measures: The primary outcome was Healthy Eating Index 2010 score (HEI), assessed by three 24-h food recalls in both periods. Higher HEI score (range 0-100; clinically significant difference 5) represents better dietary quality. Secondary outcomes included food insecurity and self-reported hypoglycemia.Key Results: Mean "on-meal" HEI score was 71.3 (SD 7.5) while mean "off-meal" HEI score was 39.9 (SD 7.8) (difference 31.4 points, p < 0.0001). Participants experienced improvements in almost all sub-categories of HEI score, with increased consumption of vegetables, fruits, and whole grains and decreased solid fats, alcohol, and added sugar consumption. Participants also reported lower food insecurity (42% "on-meal" vs. 62% "off-meal," p = 0.047), less hypoglycemia (47% "on-meal" vs. 64% "off-meal," p = 0.03), and fewer days where mental health interfered with quality of life (5.65 vs. 9.59 days out of 30, p = 0.03).Conclusions: For food-insecure individuals with diabetes, medically tailored meals improved dietary quality and food insecurity and reduced hypoglycemia. Longer-term studies should evaluate effects on diabetes control (e.g., hemoglobin A1c) and patient-reported outcomes (e.g., well-being). [ABSTRACT FROM AUTHOR]

Background: Healthcare systems use population health management programs to improve the quality of cardiovascular disease care. Adding a dedicated population health coordinator (PHC) who identifies and reaches out to patients not meeting cardiovascular care goals to these programs may help reduce disparities in cardiovascular care.Objective: To determine whether a program that used PHCs decreased racial/ethnic disparities in LDL cholesterol and blood pressure (BP) control.Design: Retrospective difference-in-difference analysis.Participants: Twelve thousdand five hundred fifty-five primary care patients with cardiovascular disease (cohort for LDL analysis) and 41,183 with hypertension (cohort for BP analysis).Intervention: From July 1, 2014-December 31, 2014, 18 practices used an information technology (IT) system to identify patients not meeting LDL and BP goals; 8 practices also received a PHC. We examined whether having the PHC plus IT system, compared with having the IT system alone, decreased racial/ethnic disparities, using difference-in-difference analysis of data collected before and after program implementation.Main Measures: Meeting guideline concordant LDL and BP goals.Key Results: At baseline, there were racial/ethnic disparities in meeting LDL (p = 0.007) and BP (p = 0.0003) goals. Comparing practices with and without a PHC, and accounting for pre-intervention LDL control, non-Hispanic white patients in PHC practices had improved odds of LDL control (OR 1.20 95% CI 1.09-1.32) compared with those in non-PHC practices. Non-Hispanic black (OR 1.15 95% CI 0.80-1.65) and Hispanic (OR 1.29 95% CI 0.66-2.53) patients saw similar, but non-significant, improvements in LDL control. For BP control, non-Hispanic white patients in PHC practices (versus non-PHC) improved (OR 1.13 95% CI 1.05-1.22). Non-Hispanic black patients (OR 1.17 95% CI 0.94-1.45) saw similar, but non-statistically significant, improvements in BP control, but Hispanic (OR 0.90 95% CI 0.59-1.36) patients did not. Interaction testing confirmed that disparities did not decrease (p = 0.73 for LDL and p = 0.69 for BP).Conclusions: The population health management intervention did not decrease disparities. Further efforts should explicitly target improving both healthcare equity and quality. Clinical Trials #: NCT02812303 ( ClinicalTrials.gov ). [ABSTRACT FROM AUTHOR]

Objectives To determine use of recommended maternal healthcare services among refugee and immigrant women in a setting of near-universal insurance coverage. Methods Refugee women age ≥18 years, who arrived in the US from 2001 to 2013 and received care at the same Massachusetts community health center, were matched by age, gender, and date of care initiation to Spanish-speaking immigrants and US-born controls. The primary outcome was initiation of obstetrical care within the first trimester (12 weeks gestation). Secondary outcomes were number of obstetrical visits and attending a postpartum visit. Results We included 375 women with 763 pregnancies (women/pregnancies: 53/116 refugee, 186/368 immigrant, 136/279 control). More refugees (20.6 %) and immigrants (15.0 %) had their first obstetric visit after 12 weeks gestation than controls (6.0 %, p < 0.001). In logistic regression models adjusted for age, education, insurance, BMI, and median census tract household income, both refugee (odds ratio [OR] 4.58, 95 % confidence interval [CI] 1.73-12.13) and immigrant (OR 2.21, 95 % CI 1.00-4.84) women had delayed prenatal care initiation. Refugees had fewer prenatal visits than controls (median 12 vs. 14, p < 0.001). Refugees (73.3 %) and immigrant (78.3 %) women were more likely to have postpartum care (controls 54.8 %, p < 0.001) with differences persisting after adjustment (refugee [OR 2.00, 95 % CI 1.04-3.83] and immigrant [OR 2.79, 95 % CI 1.72-4.53]). Conclusions for Practice Refugee and immigrant women had increased risk for delayed initiation of prenatal care, but greater use of postpartum visits. Targeted outreach may be needed to improve use of beneficial care. [ABSTRACT FROM AUTHOR]

To determine the difference in risk of developing diabetes for refugees, immigrants, and American-born participants living in the same communities, and to explore potential mediators of that difference. Retrospective longitudinal cohort from January 1, 2003 and December 31, 2013. Refugees aged ≥18 years were matched in a 1:3 ratio by age, gender, and date of care initiation to (1) Spanish-speaking non-refugee immigrants, and (2) English-speaking controls receiving care in the same community health center. We used proportional hazards regression to estimate the risk of incident diabetes. We tested whether differences in education or baseline obesity mediated diabetes risk using counterfactual mediation analysis. We included 3174 participants. Among refugee participants, the most common countries of origin were Somalia (17.8 %), Iraq (16.7 %) and Bhutan (8.8 %). Diabetes incidence rate was 1.94, 1.91, and 1.22 cases per 100 person-years follow-up for refugees, immigrants, and controls, respectively. In adjusted models, both refugee (HR 2.08 95 % CI 1.32-3.30) and immigrant (HR 1.51 95 % CI 1.01-2.24) statuses were associated with increased diabetes risk compared with controls. Risk between refugees and immigrants did not differ (adjusted HR for refugees 1.37 95 % CI 0.91-2.06). In mediation analyses, educational attainment mediated 36 % ( p = 0.007) of the difference in diabetes risk between refugees/immigrants and controls. Baseline obesity did not mediate difference in diabetes risk (proportion mediated 1 %, p = 0.84). Refugees and immigrants had significantly increased risk for diabetes, partially mediated by education. Education-based lifestyle interventions may be a promising strategy to prevent diabetes for these vulnerable patients. [ABSTRACT FROM AUTHOR]

Health-related social needs, such as food insecurity, housing instability, and lack of transportation, are associated with worse health outcomes, and are increasingly the focus of health-related social needs interventions within healthcare. Adoption of health-related social needs interventions is often justified by the potential to reduce healthcare costs. However, this can present a conundrum to clinicians. Physicians are often more accustomed to justifying clinical innovation based on improvements in health, in accord with the fundamental values of the medical profession, which include using our knowledge, skills, and the resources at our disposal to improve both individual and public health. In cases where health-related social needs interventions improve health but are not cost-saving, these two types of justifications can conflict. We provide a framework for considering these issues, and an agenda for scholarly work on this topic. Ultimately, if promoting patient and public health are key values for our profession, then understanding when to emphasize values-based care, rather than simply value-based care, is crucial to fulfilling our professional duty. [ABSTRACT FROM AUTHOR]

Food insecurity is an important issue in public health even in developed societies, particularly for vulnerable populations. Food insecurity refers to the uncertain or limited access to adequate and safe foods. Emerging evidence shows an association between food insecurity, type 2 diabetes risk factors, and management of type 1 and type 2 diabetes. A review of the current literature describing the association between food insecurity and diabetes reveals possible mechanisms and pathophysiologic pathways. There is less evidence for effective interventions, and much of the current literature is limited to cross-sectional studies. Future work should evaluate longitudinal associations and ways to help vulnerable patients with diabetes access adequate food for effective diabetes management. [ABSTRACT FROM AUTHOR]

BACKGROUND: Improving colorectal cancer (CRC) screening rates for patients from socioeconomically disadvantaged backgrounds is a recognized public health priority. OBJECTIVE: Our aim was to determine if implementation of a system-wide screening intervention could reduce disparities in the setting of improved overall screening rates. DESIGN: This was an interrupted time series (ITS) analysis before and after a population management intervention. PARTICIPANTS: Patients eligible for CRC screening (age 52-75 years without prior total colectomy) in an 18-practice research network from 15 June 2009 to 15 June 2012 participated in the study. INTERVENTION: The Technology for Optimizing Population Care (TopCare) intervention electronically identified patients overdue for screening and facilitated contact by letter or telephone scheduler, with or without physician involvement. Patients identified by algorithm as high risk for non-completion entered into intensive patient navigation. MAIN MEASURES: Patients were dichotomized as ≤ high school diploma (≤ HS), an indicator of socioeconomic disadvantage, vs. >HS diploma (> HS). The monthly disparity between ≤ HS and > HS with regard to CRC screening completion was examined. KEY RESULTS: At baseline, 72 % of 47,447 eligible patients had completed screening, compared with 75 % of 51,442 eligible patients at the end of follow-up ( p < 0.001). CRC screening completion was lower in ≤ HS vs. >HS patients in June 2009 (65.7 % vs. 74.5 %, p < 0.001) and remained lower in June 2012 (69.4 % vs. 76.7 %, p < 0.001). In the ITS analysis, which accounts for secular trends, TopCare was associated with a significant decrease in the CRC screening disparity (0.7 %, p < 0.001). The effect of TopCare represents approximately 99 additional ≤ HS patients screened above prevailing trends, or 26 life-years gained had these patients remained unscreened. CONCLUSIONS: A multifaceted population management intervention sensitive to the needs of vulnerable patients modestly narrowed disparities in CRC screening, while also increasing overall screening rates. Embedding interventions for vulnerable patients within larger population management systems represents an effective approach to increasing overall quality of care while also decreasing disparities. [ABSTRACT FROM AUTHOR]

Unmet material needs, such as food insecurity and housing instability, are associated with increased risk of diabetes and worse outcomes among diabetes patients. Healthcare delivery organizations are increasingly held accountable for health outcomes that may be related to these 'social determinants,' which are outside the scope of traditional medical intervention. This review summarizes the current literature regarding interventions that provide material support for income, food, housing, and other basic needs. In addition, we propose a conceptual model of the relationship between unmet needs and diabetes outcomes and provide recommendations for future interventional research. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: We tested the hypothesis that age younger than 65 years at type 2 diabetes diagnosis is associated with worse subsequent glycaemic control. Methods: A cross-sectional analysis of data from participants in the 2005–2010 National Health and Nutrition Examination Survey was performed. For adults with self-reported diabetes, we dichotomised age at diabetes diagnosis as younger (<65 years) vs older (≥65 years). The primary outcome of interest was HbA 1c >9.0% (75 mmol/mol). Secondary outcomes were HbA 1c >8.0% (64 mmol/mol) and >7.0% (53 mmol/mol). We used multivariable logistic regression for analysis. Results: Among 1,438 adults with diabetes, a higher proportion of those <65 years at diagnosis compared with those ≥65 at diagnosis had an HbA 1c >9.0% (14.4% vs 2.5%, p < 0.001). After adjustment for sex, race/ethnicity, education, income, insurance, usual source of care, hyperglycaemia medication, duration of diabetes, family history, BMI and waist circumference, age <65 years at diagnosis remained significantly associated with greater odds of HbA 1c >9.0% (OR 3.22, 95% CI 1.54, 6.72), HbA 1c >8.0% (OR 2.72, 95% CI 1.43, 5.16) and HbA 1c >7.0% (OR 1.92, 95% CI 1.18, 3.11). The younger group reported fewer comorbidities, but were less likely to report good health (OR 0.54, 95% CI 0.36, 0.83). Conclusions/interpretation: Younger age at type 2 diabetes diagnosis is significantly associated with worse subsequent glycaemic control. Because patients who are younger at diagnosis have fewer competing comorbidities and complications, safe, aggressive, individualised treatment could benefit this higher-risk group. [ABSTRACT FROM AUTHOR]

In this prospective evaluation of a large health-related social needs screening and navigation program for predicted high utilizers of healthcare services, Schickedanz et al. [1] estimate a small decrease in healthcare utilization that is not statistically significant, when comparing those screened to all other predicted high utilizers. To the extent that decreased healthcare utilization represents preemption of problems that would otherwise have prompted healthcare use, then decreased utilization is good. In sum, the results presented here add to the mounting evidence that health-related social needs screening and navigation programs are important tools for improving health and healthcare. [Extracted from the article]

The article focuses on the trends in diabetes treatment of Medicare beneficiaries, and talks of increased use of metformin and reduced use of sulfonylureas, randomized clinical trial to prevent side effects, reduce cost and involve patient preference, and changes in medication cost.