Bridging the Digital Health Divide: Characterizing Patient Portal Users and Nonusers in the U.S.

OBJECTIVE: The objectives of this study were to (1) examine demographic differences between patient portal users and nonusers; and (2) examine health literacy, patient self-efficacy, and technology usage and attitudes between patient portal users and nonusers. METHODS: Data were collected from Amazon Mechanical Turk (MTurk) workers from December 2021 to January 2022. MTurk workers completed an online survey, which asked about their health, access to technology, health literacy, patient self-efficacy, media and technology attitudes, and patient portal use for those with an account. A total of 489 MTurk workers completed the survey. Data were analyzed using latent class analysis (LCA) and multivariate logistic regression models. RESULTS: Latent class analysis models revealed some qualitative differences between users and nonusers of patient portals in relation to neighborhood type, education, income, disability status, comorbidity of any type, insurance type, and the presence or absence of primary care providers. These results were partially confirmed by logistic regression models, which showed that participants with insurance, a primary care provider, or a disability or comorbid condition were more likely to have a patient portal account. CONCLUSIONS: Our study findings suggest that access to health care, along with ongoing patient health needs, influence the usage of patient portal platforms. Patients with health insurance have the opportunity to access health care services, including establishing a relationship with a primary care provider. This relationship can be critical to a patient ever creating a patient portal account and actively engaging in their care, including communicating with their care team.

Social Determinants of Health and Quality of Life in Endocrine Surgery Patients.

INTRODUCTION: Quality of life (QoL) of endocrine surgery patients is an important patient outcome but the role of social determinants of health (SDH) on preoperative QoL is understudied. METHODS: This study used preoperative data of 233 endocrine surgery patients participating in a longitudinal QoL study to examine the influence of SDH (patient-level and environmental) on preoperative QoL. Patient-level SDH was assessed with structured survey questions and environmental SDH with the Social Vulnerability Index. Multiple domains of QoL were assessed with the Patient-Reported Outcomes Measurement Information System-29 (PROMIS-29). RESULTS: The average age of the sample was 52.9 y and 76.8% were female, 10% were Hispanic, 55.8% were White, 32.6% were Black, 6.9% were Other, and 4.7% were Asian. Patients with patient-level SDH were more likely to have worse preoperative QoL in multiple PROMIS domains. Patients who lived in the most socially vulnerable areas had the same or better QoL scores in the PROMIS-29 domains than those living in less vulnerable areas. Minority race patients were more likely to have patient-level SDH and to live in the most vulnerable areas. CONCLUSIONS: This study is the first to our knowledge to examine the role of patient-level and environmental SDH on preoperative QoL among endocrine surgery patients. The results identified specific patient-level factors that could be used as the basis for interventions aimed to improve patients' QoL. Future studies that evaluate the role of preoperative SDH on long-term QoL and clinical outcomes would further enhance our understanding of the impact of SDH on patient wellbeing.

A socio-technical systems approach to the use of health IT for patient reported outcomes: Patient and healthcare provider perspectives.

BACKGROUND: Patient-Reported Outcomes (PROs) can be used to inform the clinical management of individuals, including patient self-management, care planning, and goal setting. Despite a rapid proliferation of technology to collect and integrate PROs in clinical care, uptake by patients and healthcare providers remains sub optimal. A consideration of systems factors to understand these challenges is needed. OBJECTIVES: To apply the socio-technical systems (STS) model as a framework for understanding the usability and functional requirements of patients collecting PRO data using applications (apps), and of healthcare providers using these data at the point of care in ambulatory settings. METHODS: With questions guided by the STS model, semi-structured interviews were conducted with eighteen patients and nine healthcare providers to elicit feedback about facilitators and barriers to successful use of PRO apps and PRO data in ambulatory settings. Patient participants were selected to fit into two categories: older, low utilizers of technology with less than a bachelor's degree, and younger higher utilizers of technology with at least a bachelor's degree. Participants were from primary and specialty care practices. Data were analyzed inductively to identify emergent themes. RESULTS: Younger patients were only interested in using a PRO app if they had an active health issue to track. The nine older patients preferred passive means of data collection if they were to track a health issue, and preferred direct contact with their healthcare provider and using office visits to share information. All patients desired optimal usability and emphasized bidirectional communication in an app that is transparent about privacy. All nine healthcare providers agreed that PRO data would be most useful and relevant if key patient populations were targeted based on the specific measure. In this case the healthcare providers noted potentially optimal utility of collecting physical function PRO data for patients 65 and older. Access to the data was highlighted by each healthcare provider stating that these data would be most useful if they were seamlessly integrated into the electronic health record. DISCUSSION: Several emergent themes were identified under the five selected dimensions of the STS model (clinical content, human computer interface, hardware and software computing infrastructure, people, and workflow and communication). Findings highlighted the continued need for innovative methods to obtain more rapid cycle, continuous feedback to identify system factors impacting use of these technologies. CONCLUSION: The STS model provides a comprehensive framework that can be applied to collect patient and healthcare provider feedback to better guide the design and implementation of new health information technology.

Evaluation of a Text Message-Based COVID-19 Vaccine Outreach Program Among Older Patients: Cross-sectional Study.

BACKGROUND: COVID-19 vaccines are vital tools in the defense against infection and serious disease due to SARS-CoV-2. There are many challenges to implementing mass vaccination campaigns for large, diverse populations from crafting vaccine promotion messages to reaching individuals in a timely and effective manner. During this unprecedented period, with COVID-19 mass vaccination campaigns essential for protecting vulnerable patient populations and attaining herd immunity, health care systems were faced with the dual challenges of vaccine outreach and distribution. OBJECTIVE: The aim of this cross-sectional study was to assess the effectiveness of a COVID-19 vaccine text outreach approach for patients aged 65 years and older. Our goal was to determine whether this approach was successful in scheduling patients for COVID-19 vaccine appointments. METHODS: We developed SMS text messages using the Tavoca platform. These messages informed patients of their vaccine eligibility and allowed them to indicate their interest in scheduling an appointment via a specific method (email or phone) or indicate their lack of interest in the vaccine. We tracked the status of these messages and how patients responded. Messages were sent to patients aged 65 years and older (N=30,826) at a nonprofit health care system in Washington, DC. Data were collected and examined from January 14 to May 10, 2021. Data were analyzed using multivariate multinomial and binary logistic regression models in SAS (version 9.4; SAS Institute Inc). RESULTS: Approximately 57% of text messages were delivered to patients, but many messages received no response from patients (40%). Additionally, 42.1% (12,978/30,826) of messages were not delivered. Of the patients who expressed interest in the vaccine (2938/30,826, 9.5%), Black or African American patients preferred a phone call rather than an email for scheduling their appointment (odds ratio [OR] 1.69, 95% CI 1.29-2.21) compared to White patients. Patients aged 70-74 years were more likely to schedule an appointment (OR 1.38, 95% CI 1.01-1.89) than those aged 65-69 years, and Black or African American patients were more likely to schedule an appointment (OR 2.90, 95% CI 1.72-4.91) than White patients. CONCLUSIONS: This study provides insights into some advantages and challenges of using a text messaging vaccine outreach for patients aged 65 years and older. Lessons learned from this vaccine campaign underscore the importance of using multiple outreach methods and sharing of patient vaccination status between health systems, along with a patient-centered approach to address vaccine hesitancy and access issues.

Social Determinants of Health and Patient Safety: An Analysis of Patient Safety Event Reports Related to Limited English-Proficient Patients.

BACKGROUND: Racial and ethnic disparities in healthcare safety have persisted for decades, particularly for patients with language barriers. Previous studies have investigated the frequency and nature of safety events impacting patients with language barriers; others have proposed solutions to fix them. A gap analysis, however, of how we are currently addressing safety issues and why these efforts have not been effective is lacking. METHOD: This analysis uses reports from a patient safety event reporting system. Reports contain information regarding no-harm (near miss) events and events where harm may have reached the patient. Reports occurring with patients with a preferred language other than English were extracted and analyzed to determine whether the language barrier contributed to the safety event, the language barrier was mentioned in the resolution, and themes were mentioned for addressing language barriers. RESULTS: A subset of 1553 events pertaining to non-English-speaking patients were first categorized as "likely" (3%), "plausibly" (10%), or "unlikely" (87%) related to the patient's language barrier. Second, events related to the patient's language barrier were categorized as directly addressing (19%), indirectly addressing (3%), not mentioning (69%) the language barrier, or containing insufficient information to determine whether the language barrier was addressed (7%). Third, thematic analysis revealed that the most common methods for addressing language barriers included presenting issues to interpreter services and subsequent use of interpreter services. CONCLUSIONS: This study found that it is challenging to determine the direct role of certain social determinants of health (e.g., language barriers) in safety events. In many cases, the language barrier was not addressed in the event report. Furthermore, when the language barrier was addressed, solution themes typically involved weaker, less sustainable suggested actions.

Aphasia severity is modulated by race and lesion size in chronic survivors: A retrospective study.

INTRODUCTION: In stroke survivors with aphasia (SWA), differences in behavioral language performance have been observed between Black and White Americans. These racial differences in aphasia outcomes may reflect biological stroke severity, disparities in access to care, potential assessment bias, or interactions between these factors and race. Understanding the origin of disparities in aphasia outcomes is critical to any efforts to promote health equity among SWA. In this study, we explore aphasia outcomes by examining the relationship between race, socioeconomic status, and neurological factors in SWA. METHOD: Eighty-five chronic left-hemisphere SWA (31 Black, 54 White) participated in the study. The primary aphasia outcome measure was the Western Aphasia Battery-Revised (WAB-R). Lesion size was measured based on manual lesion segmentations. FLAIR and T2 images were scored for severity of white matter disease. Independent sample t-tests were used to determine differences by race in education, age, income, aphasia severity, white matter disease, and lesion size. A linear regression model was used to explore factors that predicted aphasia severity on the WAB-R. RESULT: Level of education and estimated income differed by race in our sample. For predictors of aphasia severity, the regression model revealed a significant effect of lesion size on WAB Aphasia Quotient and an interaction of race x lesion size, such that Black and White participants with small lesions had similar WAB scores, but in individuals with larger lesions, Black participants had lower WAB scores than White participants. CONCLUSION: We suggest two explanations for the difference between Black and White SWA in the relationship between lesion size and aphasia severity. First, the impact of disparities in access to rehabilitation after stroke may be more evident when a stroke is larger and causes significant aphasia. Additionally, an assessment bias in aphasia outcome measures may be more evident with increasing severity of aphasia. Future studies should further discern the drivers of observed disparities in aphasia outcomes in order to identify opportunities to improve equity in aphasia care.

Population subgroup differences in the use of a COVID-19 chatbot.

COVID-19 chatbots are widely used to screen for symptoms and disseminate information about the virus, yet little is known about the population subgroups that interact with this technology and the specific features that are used. An analysis of 1,000,740 patients invited to use a COVID-19 chatbot, 69,451 (6.94%) of which agreed to participate, shows differences in chatbot feature use by gender, race, and age. These results can inform future public health COVID-19 symptom screening and information dissemination strategies.

A novel application of SMART on FHIR architecture for interoperable and scalable integration of patient-reported outcome data with electronic health records.

OBJECTIVE: Despite a proliferation of applications (apps) to conveniently collect patient-reported outcomes (PROs) from patients, PRO data are yet to be seamlessly integrated with electronic health records (EHRs) in a way that improves interoperability and scalability. We applied the newly created PRO standards from the Office of the National Coordinator for Health Information Technology to facilitate the collection and integration of standardized PRO data. A novel multitiered architecture was created to enable seamless integration of PRO data via Substitutable Medical Apps and Reusable Technologies on Fast Healthcare Interoperability Resources apps and scaled to different EHR platforms in multiple ambulatory settings. MATERIALS AND METHODS: We used a standards-based approach to deploy 2 apps that source and surface PRO data in real-time for provider use within the EHR and which rely on PRO assessments from an external center to streamline app and EHR integration. RESULTS: The apps were developed to enable patients to answer validated assessments (eg, a Patient-Reported Outcomes Measurement Information System including using a Computer Adaptive Test format). Both apps were developed to populate the EHR in real time using the Health Level Seven FHIR standard allowing providers to view patients' data during the clinical encounter. The process of implementing this architecture with 2 different apps across 18 ambulatory care sites and 3 different EHR platforms is described. CONCLUSION: Our approach and solution proved feasible, secure, and time- and resource-efficient. We offer actionable guidance for this technology to be scaled and adapted to promote adoption in diverse ambulatory care settings and across different EHRs.