Differences by Race in Outcomes of an In-Person Training Intervention on Use of an Inpatient Portal: A Secondary Analysis of a Randomized Clinical Trial.

Importance: Differences in patient use of health information technologies by race can adversely impact equitable access to health care services. While this digital divide is well documented, there is limited evidence of how health care systems have used interventions to narrow the gap. Objective: To compare differences in the effectiveness of patient training and portal functionality interventions implemented to increase portal use among racial groups. Design, Setting, and Participants: This secondary analysis used data from a randomized clinical trial conducted from December 15, 2016, to August 31, 2019. Data were from a single health care system and included 6 noncancer hospitals. Participants were patients who were at least 18 years of age, identified English as their preferred language, were not involuntarily confined or detained, and agreed to be provided a tablet to access the inpatient portal during their stay. Data were analyzed from September 1, 2022, to October 31, 2023. Interventions: A 2 × 2 factorial design was used to compare the inpatient portal training intervention (touch, in-person [high] vs built-in video tutorial [low]) and the portal functionality intervention (technology, full functionality [full] vs a limited subset of functions [lite]). Main Outcomes and Measures: Primary outcomes were inpatient portal use, measured by frequency and comprehensiveness of use, and use of specific portal functions. A logistic regression model was used to test the association of the estimators with the comprehensiveness use measure. Outcomes are reported as incidence rate ratios (IRRs) for the frequency outcomes or odds ratios (ORs) for the comprehensiveness outcomes with corresponding 95% CIs. Results: Of 2892 participants, 550 (19.0%) were Black individuals, 2221 (76.8%) were White individuals, and 121 (4.2%) were categorized as other race (including African, American Indian or Alaska Native, Asian or Asian American, multiple races or ethnicities, and unknown race or ethnicity). Black participants had a significantly lower frequency (IRR, 0.80 [95% CI, 0.72-0.89]) of inpatient portal use compared with White participants. Interaction effects were not observed between technology, touch, and race. Among participants who received the full technology intervention, Black participants had lower odds of being comprehensive users (OR, 0.76 [95% CI, 0.62-0.91), but interaction effects were not observed between touch and race. Conclusions and Relevance: In this study, providing in-person training or robust portal functionality did not narrow the divide between Black participants and White participants with respect to their inpatient portal use. Health systems looking to narrow the digital divide may need to consider intentional interventions that address underlying issues contributing to this inequity. Trial Registration: ClinicalTrials.gov Identifier: NCT02943109.

Effects of the Communities that Heal (CTH) intervention on perceived opioid-related community stigma in the HEALing Communities Study: results of a multi-site, community-level, cluster-randomized trial.

Background: Community stigma against people with opioid use disorder (OUD) and intervention stigma (e.g., toward naloxone) exacerbate the opioid overdose crisis. We examined the effects of the Communities that HEAL (CTH) intervention on perceived opioid-related community stigma by stakeholders in the HEALing Communities Study (HCS). Methods: We collected three surveys from community coalition members in 66 communities across four states participating in HCS. Communities were randomized into Intervention (Wave 1) or Wait-list Control (Wave 2) arms. We conducted multilevel linear mixed models to compare changes in primary outcomes of community stigma toward people treated for OUD, naloxone, and medication for opioid use disorder (MOUD) by arm from time 1 (before the start of the intervention) to time 3 (end of the intervention period in the Intervention arm). Findings: Intervention stakeholders reported a larger decrease in perceived community stigma toward people treated for OUD (adjusted mean change (AMC) -3.20 [95% C.I. -4.43, -1.98]) and toward MOUD (AMC -0.33 [95% C.I. -0.56, -0.09]) than stakeholders in Wait-list Control communities (AMC -0.18 [95% C.I. -1.38, 1.02], p = 0.0007 and AMC 0.11 [95% C.I. -0.09, 0.31], p = 0.0066). The relationship between intervention status and change in stigma toward MOUD was moderated by rural-urban status (urban AMC -0.59 [95% CI, -0.87, -0.32], rural AMC not sig.) and state. The difference in stigma toward naloxone between Intervention and Wait-list Control stakeholders was not statistically significant (p = 0.18). Interpretation: The CTH intervention decreased stakeholder perceptions of community stigma toward people treated for OUD and stigma toward MOUD. Implementing the CTH intervention in other communities could decrease OUD stigma across diverse settings nationally. Funding: US National Institute on Drug Abuse.

Implications for Electronic Surveys in Inpatient Settings Based on Patient Survey Response Patterns: Cross-Sectional Study.

BACKGROUND: Surveys of hospitalized patients are important for research and learning about unobservable medical issues (eg, mental health, quality of life, and symptoms), but there has been little work examining survey data quality in this population whose capacity to respond to survey items may differ from the general population. OBJECTIVE: The aim of this study is to determine what factors drive response rates, survey drop-offs, and missing data in surveys of hospitalized patients. METHODS: Cross-sectional surveys were distributed on an inpatient tablet to patients in a large, midwestern US hospital. Three versions were tested: 1 with 174 items and 2 with 111 items; one 111-item version had missing item reminders that prompted participants when they did not answer items. Response rate, drop-off rate (abandoning survey before completion), and item missingness (skipping items) were examined to investigate data quality. Chi-square tests, Kaplan-Meyer survival curves, and distribution charts were used to compare data quality among survey versions. Response duration was computed for each version. RESULTS: Overall, 2981 patients responded. Response rate did not differ between the 174- and 111-item versions (81.7% vs 83%, P=.53). Drop-off was significantly reduced when the survey was shortened (65.7% vs 20.2% of participants dropped off, P<.001). Approximately one-quarter of participants dropped off by item 120, with over half dropping off by item 158. The percentage of participants with missing data decreased substantially when missing item reminders were added (77.2% vs 31.7% of participants, P<.001). The mean percentage of items with missing data was reduced in the shorter survey (40.7% vs 20.3% of items missing); with missing item reminders, the percentage of items with missing data was further reduced (20.3% vs 11.7% of items missing). Across versions, for the median participant, each item added 24.6 seconds to a survey's duration. CONCLUSIONS: Hospitalized patients may have a higher tolerance for longer surveys than the general population, but surveys given to hospitalized patients should have a maximum of 120 items to ensure high rates of completion. Missing item prompts should be used to reduce missing data. Future research should examine generalizability to nonhospitalized individuals.

Community-level determinants of stakeholder perceptions of community stigma toward people with opioid use disorders, harm reduction services and treatment in the HEALing Communities Study.

BACKGROUND: Community stigma toward people with opioid use disorder (OUD) can impede access to harm reduction services and treatment with medications for opioid use disorder (MOUD). Such community OUD stigma is partially rooted in community-level social and economic conditions, yet there remains a paucity of large-scale quantitative data examining community-level factors associated with OUD stigma. We examined whether rurality, social inequity, and racialized segregation across communities from four states in the HEALing Communities Study (HCS) were associated with 1) greater perceived community stigma toward people treated for OUD, 2) greater perceived intervention stigma toward MOUD, and 3) greater perceived intervention stigma toward naloxone by community stakeholders in the HCS. METHODS: From November 2019-January 2020, a cross-sectional survey about community OUD stigma was administered to 801 members of opioid overdose prevention coalitions across 66 communities in four states prior to the start of HCS intervention activities. Bivariate analyses assessed pairwise associations between community rural/urban status and each of the three stigma variables, using linear mixed effect modeling to account for response clustering within communities, state, and respondent sociodemographic characteristics. We conducted similar bivariate analyses to assess pairwise associations between racialized segregation and social inequity. RESULTS: On average, the perceived community OUD stigma scale score of stakeholders from rural communities was 4% higher (ß=1.57, SE=0.7, p≤0.05), stigma toward MOUD was 6% higher (ß=0.28, SE=0.1, p≤0.05), and stigma toward naloxone was 10% higher (ß=0.46, SE=0.1, p≤0.01) than among stakeholders from urban communities. No significant differences in the three stigma variables were found among communities based on racialized segregation or social inequity. CONCLUSION: Perceived community stigma toward people treated for OUD, MOUD, and naloxone was higher among stakeholders in rural communities than in urban communities. Findings suggest that interventions and policies to reduce community-level stigma, particularly in rural areas, are warranted.

Multicomponent provider-patient intervention to improve glycaemic control in Medicaid-insured pregnant individuals with type 2 diabetes: clinical trial protocol for the ACHIEVE study.

INTRODUCTION: Type 2 diabetes (T2D) is one of the most frequent comorbid medical conditions in pregnancy. Glycaemic control decreases the risk of adverse pregnancy outcomes for the pregnant individual and infant. Achieving glycaemic control can be challenging for Medicaid-insured pregnant individuals who experience a high burden of unmet social needs. Multifaceted provider-patient-based approaches are needed to improve glycaemic control in this high-risk pregnant population. Mobile health (mHealth) applications (app), provider dashboards, continuous glucose monitoring (CGM) and addressing social needs have been independently associated with improved glycaemic control in non-pregnant individuals living with diabetes. The combined effect of these interventions on glycaemic control among pregnant individuals with T2D remains to be evaluated. METHODS AND ANALYSIS: In a two-arm randomised controlled trial, we will examine the combined effects of a multicomponent provider-patient intervention, including a patient mHealth app, provider dashboard, CGM, a community health worker to address non-medical health-related social needs and team-based care versus the current standard of diabetes and prenatal care. We will recruit 124 Medicaid-insured pregnant individuals living with T2D, who are ≤20 weeks of gestation with poor glycaemic control measured as a haemoglobin A1c ≥ 6.5% assessed within 12 weeks of trial randomisation or within 12 weeks of enrolling in prenatal care from an integrated diabetes and prenatal care programme at a tertiary care academic health system located in the Midwestern USA. We will measure how many individuals achieve the primary outcome of glycaemic control measured as an A1c<6.5% by the time of delivery, and secondarily, adverse pregnancy outcomes; patient-reported outcomes (eg, health and technology engagement, literacy and comprehension; provider-patient communication; diabetes self-efficacy; distress, knowledge and beliefs; social needs referrals and utilisation; medication adherence) and CGM measures of glycaemic control (in the intervention group). ETHICS AND DISSEMINATION: The Institutional Review Board at The Ohio State University approved this study (IRB: 2022H0399; date: 3 June 2023). We plan to submit manuscripts describing the user-designed methods and will submit the results of the trial for publication in peer-reviewed journals and presentations at international scientific meetings. TRIAL REGISTRATION NUMBER: NCT05662462.

Accelerating Colorectal Cancer Screening and Follow-up through Implementation Science (ACCSIS) in Appalachia: protocol for a group randomized, delayed intervention trial.

Appalachian regions of Kentucky and Ohio are hotspots for colorectal cancer (CRC) mortality in the USA. Screening reduces CRC incidence and mortality; however, screening uptake is needed, especially in these underserved geographic areas. Implementation science offers strategies to address this challenge. The aim of the current study was to conduct multi-site, transdisciplinary research to evaluate and improve CRC screening processes using implementation science strategies. The study consists of two phases (Planning and Implementation). In the Planning Phase, a multilevel assessment of 12 health centers (HC) (one HC from each of the 12 Appalachian counties) was conducted by interviewing key informants, creating community profiles, identifying HC and community champions, and performing HC data inventories. Two designated pilot HCs chose CRC evidence-based interventions to adapt and implement at each level (i.e., patient, provider, HC, and community) with evaluation relative to two matched control HCs. During the Implementation Phase, study staff will repeat the rollout process in HC and community settings in a randomized, staggered fashion in the remaining eight counties/HCs. Evaluation will include analyses of electronic health record data and provider and county surveys. Rural HCs have been reluctant to participate in research because of concerns about capacity; however, this project should demonstrate that research does not need to be burdensome and can adapt to local needs and HC abilities. If effective, this approach could be disseminated to HC and community partners throughout Appalachia to encourage the uptake of effective interventions to reduce the burden of CRC.

We conducted a multi-site study to evaluate and improve CRC screening processes using implementation science strategies at multiple levels including the patient, provider, health center, and community. Our goals were to increase rates of guideline-recommended CRC screening, follow-up, and referral-to-care in an Appalachian, medically underserved population.

Effect of In-Person vs Video Training and Access to All Functions vs a Limited Subset of Functions on Portal Use Among Inpatients: A Randomized Clinical Trial.

Importance: Inpatient portals provide patients with clinical data and information about their care and have the potential to influence patient engagement and experience. Although significant resources have been devoted to implementing these portals, evaluation of their effects has been limited. Objective: To assess the effects of patient training and portal functionality on use of an inpatient portal and on patient satisfaction and involvement with care. Design, Setting, and Participants: This randomized clinical trial was conducted from December 15, 2016, to August 31, 2019, at 6 noncancer hospitals that were part of a single health care system. Patients who were at least 18 years of age, identified English as their preferred language, were not involuntarily confined or detained, and agreed to be provided a tablet to access the inpatient portal during their stay were eligible for participation. Data were analyzed from May 1, 2019, to March 15, 2021. Interventions: A 2 × 2 factorial intervention design was used to compare 2 levels of a training intervention (touch intervention, consisting of in-person training vs built-in video tutorial) and 2 levels of portal function availability (tech intervention) within an inpatient portal (all functions operational vs a limited subset of functions). Main Outcomes and Measures: The primary outcomes were inpatient portal use, measured by frequency and comprehensiveness of use, and patients' satisfaction and involvement with their care. Results: Of 2892 participants, 1641 were women (56.7%) with a median age of 47.0 (95% CI, 46.0-48.0) years. Most patients were White (2221 [76.8%]). The median Charlson Comorbidity Index was 1 (95% CI, 1-1) and the median length of stay was 6 (95% CI, 6-7) days. Notably, the in-person training intervention was found to significantly increase inpatient portal use (incidence rate ratio, 1.34 [95% CI, 1.25-1.44]) compared with the video tutorial. Patients who received in-person training had significantly higher odds of being comprehensive portal users than those who received the video tutorial (odds ratio, 20.75 [95% CI, 16.49-26.10]). Among patients who received the full-tech intervention, those who also received the in-person intervention used the portal more frequently (incidence rate ratio, 1.36 [95% CI, 1.25-1.48]) and more comprehensively (odds ratio, 22.52; [95% CI, 17.13-29.62]) than those who received the video tutorial. Patients who received in-person training had higher odds (OR, 2.01 [95% CI, 1.16-3.50]) of reporting being satisfied in the 6-month postdischarge survey. Similarly, patients who received the full-tech intervention had higher odds (OR, 2.06 [95%CI, 1.42-2.99]) of reporting being satisfied in the 6-month postdischarge survey. Conclusions and Relevance: Providing in-person training or robust portal functionality increased inpatient engagement with the portal during the hospital stay. The effects of the training intervention suggest that providing personalized training to support use of this health information technology can be a powerful approach to increase patient engagement via portals. Trial Registration: ClinicalTrials.gov Identifier: NCT02943109.

Examining the Relationship between Health Literacy, Health Numeracy, and Patient Portal Use.

OBJECTIVES: The objective of this study is to investigate the relationships between health literacy and numeracy (HLN) and patient portal use, measured in inpatient and outpatient settings. METHODS: Using data collected as part of a pragmatic randomized controlled trial conducted across the inpatient population of a U.S.-based academic medical center, the present study evaluated the relationships between patients' perceptions of health literacy and their skills, interpreting medical information with metrics of engagement with patient portals. RESULTS: Self-reported levels of HLN for patients in the study sample (n = 654) were not significantly associated with inpatient portal use as measured by frequency of use or the number of different inpatient portal functions used. Use of the outpatient version of the portal over the course of 6 months following hospital discharge was also not associated with HLN. A subsequent assessment of patients after 6 months of portal use postdischarge (response rate 40%) did not reveal any differences with respect to portal use and health numeracy; however, a significant increase in self-reported levels of health literacy was found at this point. CONCLUSION: While previous studies have suggested that low HLN might represent a barrier to inpatient portal adoption and might limit engagement with outpatient portals, we did not find these associations to hold. Our findings, however, suggest that the inpatient setting may be effective in facilitating technology acceptance. Specifically, the introduction of an inpatient portal made available on hospital-provided tablets may have practical implications and contribute to increased adoption of patient-facing health information technology tools.

Assessment of structured data elements for social risk factors.

OBJECTIVES: Computable social risk factor phenotypes derived from routinely collected structured electronic health record (EHR) or health information exchange (HIE) data may represent a feasible and robust approach to measuring social factors. This study convened an expert panel to identify and assess the quality of individual EHR and HIE structured data elements that could be used as components in future computable social risk factor phenotypes. STUDY DESIGN: Technical expert panel. METHODS: A 2-round Delphi technique included 17 experts with an in-depth knowledge of available EHR and/or HIE data. The first-round identification sessions followed a nominal group approach to generate candidate data elements that may relate to socioeconomics, cultural context, social relationships, and community context. In the second-round survey, panelists rated each data element according to overall data quality and likelihood of systematic differences in quality across populations (ie, bias). RESULTS: Panelists identified a total of 89 structured data elements. About half of the data elements (n = 45) were related to socioeconomic characteristics. The panelists identified a diverse set of data elements. Elements used in reimbursement-related processes were generally rated as higher quality. Panelists noted that several data elements may be subject to implicit bias or reflect biased systems of care, which may limit their utility in measuring social factors. CONCLUSIONS: Routinely collected structured data within EHR and HIE systems may reflect patient social risk factors. Identifying and assessing available data elements serves as a foundational step toward developing future computable social factor phenotypes.

Examining the Dimensionality of Trust in the Inpatient Setting: Exploratory and Confirmatory Factor Analysis.

BACKGROUND: Trust in healthcare providers is associated with important outcomes, but has primarily been assessed in the outpatient setting. It is largely unknown how hospitalized patients conceptualize trust in their providers. OBJECTIVE: To examine the dimensionality of a measure of trust in the inpatient setting. DESIGN: Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). PARTICIPANTS: Hospitalized patients (N = 1756; 76% response rate) across six hospitals in the midwestern USA. The sample was randomly split such that approximately one half was used in the EFA, and the other half in the CFA. MAIN MEASURES: The Trust in Physician Scale, adapted for inpatient care. KEY RESULTS: Based on the Kaiser-Guttman criterion and parallel analysis, EFAs were inconclusive, indicating that trust may be comprised of either one or two factors in this sample. In follow-up CFAs, a 2-factor model fit best based on a chi-squared difference test (Δχ2 = 151.48(1), p < .001) and a Comparative Fit Index (CFI) difference test (CFI difference = .03). The overall fit for the 2-factor CFA model was good (χ2 = 293.56, df = 43, p < .01; CFI = .95; RMSEA = .081 [90% confidence interval = .072-.090]; TLI = .93; SRMR = .04). Items loaded onto two factors related to cognitive (i.e., whether patients view providers as competent) and affective (i.e., whether patients view that providers care for them) dimensions of trust. CONCLUSIONS: While measures of trust in the outpatient setting have been validated as unidimensional, in the inpatient setting, trust appears to be composed of two factors: cognitive and affective trust. This provides initial evidence that inpatient providers may need to work to ensure patients see them as both competent and caring in order to gain their trust.

Examining Patients' Capacity to Use Patient Portals: Insights for Telehealth.

BACKGROUND: The increase in telehealth in response to the coronavirus disease 2019 pandemic highlights the need to understand patients' capacity to utilize this care modality. Patient portals are a tool whose use requires similar resources and skills as those required for telehealth. Patients' capacity to use patient portals may therefore provide insight regarding patients' readiness and capacity to use telehealth. OBJECTIVE: The aim of this study was to examine factors related to patients' capacity to use a patient portal and test the impact of these factors on patients' portal use. RESEARCH DESIGN AND SUBJECTS: Using data from a large-scale pragmatic randomized controlled trial of patient portal use, 1081 hospitalized patients responded to survey items that were then mapped onto the 4 dimensions of the Engagement Capacity Framework: self-efficacy, resources, willingness, and capabilities. MEASURES: The outcome variable was frequency of outpatient portal use. We evaluated associations between Engagement Capacity Framework dimensions and patient portal use, using regression analyses. RESULTS: Patients with fewer resources, fewer capabilities, lower willingness, and lower overall capacity to use patient portals used the portal less; in contrast, those with lower perceived self-efficacy used the portal more. CONCLUSIONS: Our findings highlight differences in patients' capacity to use patient portals, which provide an initial understanding of factors that may influence the use of telehealth and offer important guidance in efforts to support patients' telehealth use. Offering patients training tailored to the use of telehealth tools may be particularly beneficial.

Development of a multilevel intervention to increase colorectal cancer screening in Appalachia.

BACKGROUND: Colorectal cancer (CRC) screening rates are lower in Appalachian regions of the United States than in non-Appalachian regions. Given the availability of various screening modalities, there is critical need for culturally relevant interventions addressing multiple socioecological levels to reduce the regional CRC burden. In this report, we describe the development and baseline findings from year 1 of "Accelerating Colorectal Cancer Screening through Implementation Science (ACCSIS) in Appalachia," a 5-year, National Cancer Institute Cancer MoonshotSM-funded multilevel intervention (MLI) project to increase screening in Appalachian Kentucky and Ohio primary care clinics. METHODS: Project development was theory-driven and included the establishment of both an external Scientific Advisory Board and a Community Advisory Board to provide guidance in conducting formative activities in two Appalachian counties: one in Kentucky and one in Ohio. Activities included identifying and describing the study communities and primary care clinics, selecting appropriate evidence-based interventions (EBIs), and conducting a pilot test of MLI strategies addressing patient, provider, clinic, and community needs. RESULTS: Key informant interviews identified multiple barriers to CRC screening, including fear of screening, test results, and financial concerns (patient level); lack of time and competing priorities (provider level); lack of reminder or tracking systems and staff burden (clinic level); and cultural issues, societal norms, and transportation (community level). With this information, investigators then offered clinics a menu of EBIs and strategies to address barriers at each level. Clinics selected individually tailored MLIs, including improvement of patient education materials, provision of provider education (resulting in increased knowledge, p = .003), enhancement of electronic health record (EHR) systems and development of clinic screening protocols, and implementation of community CRC awareness events, all of which promoted stool-based screening (i.e., FIT or FIT-DNA). Variability among clinics, including differences in EHR systems, was the most salient barrier to EBI implementation, particularly in terms of tracking follow-up of positive screening results, whereas the development of clinic-wide screening protocols was found to promote fidelity to EBI components. CONCLUSIONS: Lessons learned from year 1 included increased recognition of variability among the clinics and how they function, appreciation for clinic staff and provider workload, and development of strategies to utilize EHR systems. These findings necessitated a modification of study design for subsequent years. TRIAL REGISTRATION: Trial NCT04427527 is registered at https://clinicaltrials.gov and was registered on June 11, 2020.

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.

Persistent digital divide in health-related internet use among cancer survivors: findings from the Health Information National Trends Survey, 2003-2018.

PURPOSE: Prior research on the use of the internet among cancer survivors indicates a digital divide. The online landscape and patterns of information consumption, however, have notably changed over the past decade necessitating an updated examination of health-related internet use (HRIU) among cancer survivors. METHODS: Using survey data from 2003, 2005, 2007, 2011, 2013, 2017, and 2018 Health Information National Trends Survey (HINTS) iterations, the objectives of this study were to report prevalence, trends, and user profiles in HRIU in terms of emailing doctors, buying medicine online, and support group participation. Descriptive analyses and weighted multivariate logistic regression analyses were performed. RESULTS: Cancer survivors who reported not using the internet were more likely to be older, belong to ethnic minorities, be less educated, and reside in rural areas as compared with those who reported using the internet. Except for participation in online support groups, all other types of HRIU increased in prevalence across the years. CONCLUSIONS: Consistent with the increased penetration of the internet and the altered online health communication landscape, we found increased prevalence of HRIU among cancer survivors. However, the digital divide persists in terms of internet access. These findings can inform initiatives to bridge the gap among survivors of varying profiles in using the internet for their health needs. IMPLICATIONS FOR CANCER SURVIVORS: There is increased reliance on online platforms to obtain and communicate health-related information. The risk with this approach is potential oversight of ensuring equity in terms of internet access and technology literacy among survivors.

Differences Between Races in Health Information Seeking and Trust Over Time: Evidence From a Cross-Sectional, Pooled Analyses of HINTS Data.

PURPOSE: Assessed racial disparities in health information-seeking behavior and trust of information sources from 2007 to 2017. DESIGN: Pooled cross-sectional survey data. SETTING: Health Information National Trends Survey (HINTS). PARTICIPATION: Data included 6 iterations of HINTS (pooled: N = 19 496; 2007: n = 3593; 2011: n = 3959; 2013: n = 3185; Food and Drug Administration [FDA] 2015: n = 3738; 2017: n = 3285; and FDA 2017: n = 1736). MEASURES: Outcome variables were health information seeking, high confidence, and high trust of health information from several sources. Independent variable was race group, controlling for other sociodemographic and socioeconomic variables. ANALYSIS: Weighted descriptive and multivariate logistic regression for the pooled sample assessed associations by race. Fully interacted models with race-survey year interactions compared differences in outcomes between years. RESULTS: Black respondents, relative to white, had greater odds of having high confidence in their ability to attain health information, trust of health information from newspapers and magazines, radio, internet, television, government, charitable organizations, and religious organizations. Hispanic respondents, relative to white, had lower odds of seeking health information and trusting health information from doctors. They had higher odds of trusting health information from the radio, the internet, television, charitable organizations, and religious organizations. CONCLUSION: Disparities between races in trust of information sources remained across time. Understanding optimal information media, their reach, and credibility among racial groups could enable more targeted approaches to developing interventions. Our analytical approach minimized limitations present in the HINTS.

Care Team Perspectives About an Inpatient Portal: Benefits and Challenges of Patients' Portal Use During Hospitalization.

While current research about inpatient portals has focused largely on the patient perspective, it is also critical to consider the care team point of view, as support from these individuals is essential to successful portal implementation and use. We held brief in-person interviews with 433 care team members across a six-hospital health system to explore opinions about patients' use of an inpatient portal as perceived by care team members. Using the Inpatient Portal Evaluation Framework, we characterized benefits and challenges of portal use that care team members reported affected patients, themselves, and the collaborative work of these care teams with their patients. Interviewees noted inpatient portals can improve patient care and experience and also indicated room for improvement in portal use for hospitalized patients. Further understanding of the care team perspective is critical to inform approaches to inpatient portal implementation that best benefit both patients and providers.

Community dashboards to support data-informed decision-making in the HEALing communities study.

BACKGROUND: With opioid misuse, opioid use disorder (OUD), and opioid overdose deaths persisting at epidemic levels in the U.S., the largest implementation study in addiction research-the HEALing Communities Study (HCS)-is evaluating the impact of the Communities That Heal (CTH) intervention on reducing opioid overdose deaths in 67 disproportionately affected communities from four states (i.e., "sites"). Community-tailored dashboards are central to the CTH intervention's mandate to implement a community-engaged and data-driven process. These dashboards support a participating community's decision-making for selection and monitoring of evidence-based practices to reduce opioid overdose deaths. METHODS/DESIGN: A community-tailored dashboard is a web-based set of interactive data visualizations of community-specific metrics. Metrics include opioid overdose deaths and other OUD-related measures, as well as drivers of change of these outcomes in a community. Each community-tailored dashboard is a product of a co-creation process between HCS researchers and stakeholders from each community. The four research sites used a varied set of technical approaches and solutions to support the scientific design and CTH intervention implementation. Ongoing evaluation of the dashboards involves quantitative and qualitative data on key aspects posited to shape dashboard use combined with website analytics. DISCUSSION: The HCS presents an opportunity to advance how community-tailored dashboards can foster community-driven solutions to address the opioid epidemic. Lessons learned can be applied to inform interventions for public health concerns and issues that have disproportionate impact across communities and populations (e.g., racial/ethnic and sexual/gender minorities and other marginalized individuals). TRIAL REGISTRATION: ClinicalTrials.gov (NCT04111939).

Model and approach for assessing implementation context and fidelity in the HEALing Communities Study.

BACKGROUND: In response to the U.S. opioid epidemic, the HEALing (Helping to End Addiction Long-termSM) Communities Study (HCS) is a multisite, wait-listed, community-level cluster-randomized trial that aims to test the novel Communities That HEAL (CTH) intervention, in 67 communities. CTH will expand an integrated set of evidence-based practices (EBPs) across health care, behavioral health, justice, and other community-based settings to reduce opioid overdose deaths. We present the rationale for and adaptation of the RE-AIM/PRISM framework and methodological approach used to capture the CTH implementation context and to evaluate implementation fidelity. METHODS: HCS measures key domains of the internal and external CTH implementation context with repeated annual surveys and qualitative interviews with community coalition members and key stakeholders. Core constructs of fidelity include dosage, adherence, quality, and program differentiation-the adaptation of the CTH intervention to fit each community's needs. Fidelity measures include a monthly CTH checklist, collation of artifacts produced during CTH activities, coalition and workgroup attendance, and coalition meeting minutes. Training and technical assistance delivered by the research sites to the communities are tracked monthly. DISCUSSION: To help attenuate the nation's opioid epidemic, the adoption of EBPs must be increased in communities. The HCS represents one of the largest and most complex implementation research experiments yet conducted. Our systematic examination of implementation context and fidelity will significantly advance understanding of how to best evaluate community-level implementation of EBPs and assess relations among implementation context, fidelity, and intervention impact.

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.