The impact of stigma on HIV testing decisions for gay, bisexual, queer and other men who have sex with men: a qualitative study.

BACKGROUND: Stigmatization may prompt gay, bisexual, queer and other men who have sex with men (GBQMSM) to avoid or delay HIV testing. There has been little attention to GBQMSMs' perspectives about how stigma may influence their decisions about whether, where, and how often to get tested for HIV. METHODS: We conducted nine focus groups with 64 adult GBQMSM in Metropolitan Detroit, including HIV-negative men and people living with HIV (PLWH). Data were thematically analyzed deductively and inductively in three rounds. RESULTS: Three themes emerged regarding whether to get tested: (1) Perceived promiscuity, risk perceptions and HIV testing; (2) Fearing sexual rejection; and (3) Fearing friend and family member distancing and rejection. Themes concerning where to get tested included: (4) Conflating HIV testing and diagnosis; and (5) Seeking privacy and safety at specialized services. As for how often to get tested, themes included: (6) Reducing contact with healthcare providers due to intersectional stigma; (7) Responsibility and regular testing; and (8) HIV stigma and testing as routine care. Black participants articulated themes (3), (4), and (6) with greater frequency than other participants. Framing HIV testing as a personal responsibility may have created a "new stigma," with unintended consequences not observed with "routine healthcare" messaging. CONCLUSIONS: GBQMSMs' perspectives indicate the potential for new foci for HIV testing promotion interventions based on stigma-related issues that they deem important. There is a need for interventions to challenge the "promiscuity" stereotype, and to reduce the sexual stigmatization of GBQMSM living with HIV/AIDS-especially online. Provider stigma requires both intervention and continued availability of specialized services. Future stigma-reduction interventions for Black GBQMSM could focus on building family support/acceptance, awareness of multiple testing options, and integrating LGBTQ-related issues into initiatives for racial justice in health care.

Comparative Analysis of Recruitment Strategies in a Study of Men Who Have Sex with Men (MSM) in Metropolitan Detroit.

HIV/AIDS-related research requires recruitment of representative samples of MSM; yet, we know little about the comparative yield, diversity and cost-benefit tradeoffs between different recruitment venues. We compared 11 recruitment venues used for nine HIV prevention-related focus groups with MSM in Metropolitan Detroit. Of the 64 participants, 24 were clients recruited via an HIV/AIDS-focused nonprofit, 20 from Grindr advertisements, 6 from university-student email lists, and 5 from flyers/palmcards. Significantly more African-American, low-income and HIV-positive participants were recruited via the nonprofit. The best cost-benefit tradeoffs were for organizational Facebook posts, email groups, personal networking, and nonprofit recruitment. Grindr increased the size of the sample, though at greater expense. Facebook and Scruff advertisements and gay bar outreach represented greater costs than benefits. Only 11.6% of Grindr respondents attended the focus groups. A mix of online and offline recruitment venues can generate a large and diverse sample of MSM, but venue performance is uneven.

Community-based surveillance of maternal deaths in rural Ghana.

OBJECTIVE: To examine the feasibility and effectiveness of community-based maternal mortality surveillance in rural Ghana, where most information on maternal deaths usually comes from retrospective surveys and hospital records. METHODS: In 2013, community-based surveillance volunteers used a modified reproductive age mortality survey (RAMOS 4+2) to interview family members of women of reproductive age (13-49 years) who died in Bosomtwe district in the previous five years. The survey comprised four yes-no questions and two supplementary questions. Verbal autopsies were done if there was a positive answer to at least one yes-no question. A mortality review committee established the cause of death. FINDINGS: Survey results were available for 357 women of reproductive age who died in the district. A positive response to at least one yes-no question was recorded for respondents reporting on the deaths of 132 women. These women had either a maternal death or died within one year of termination of pregnancy. Review of 108 available verbal autopsies found that 64 women had a maternal or late maternal death and 36 died of causes unrelated to childbearing. The most common causes of death were haemorrhage (15) and abortion (14). The resulting maternal mortality ratio was 357 per 100 000 live births, compared with 128 per 100 000 live births derived from hospital records. CONCLUSION: The community-based mortality survey was effective for ascertaining maternal deaths and identified many deaths not included in hospital records. National surveys could provide the information needed to end preventable maternal mortality by 2030.

Structured and unstructured social risk factor documentation in the electronic health record underestimates patients' self-reported risks.

OBJECTIVES: National attention has focused on increasing clinicians' responsiveness to the social determinants of health, for example, food security. A key step toward designing responsive interventions includes ensuring that information about patients' social circumstances is captured in the electronic health record (EHR). While prior work has assessed levels of EHR "social risk" documentation, the extent to which documentation represents the true prevalence of social risk is unknown. While no gold standard exists to definitively characterize social risks in clinical populations, here we used the best available proxy: social risks reported by patient survey. MATERIALS AND METHODS: We compared survey results to respondents' EHR social risk documentation (clinical free-text notes and International Statistical Classification of Diseases and Related Health Problems [ICD-10] codes). RESULTS: Surveys indicated much higher rates of social risk (8.2%-40.9%) than found in structured (0%-2.0%) or unstructured (0%-0.2%) documentation. DISCUSSION: Ideally, new care standards that include incentives to screen for social risk will increase the use of documentation tools and clinical teams' awareness of and interventions related to social adversity, while balancing potential screening and documentation burden on clinicians and patients. CONCLUSION: EHR documentation of social risk factors currently underestimates their prevalence.

Characterizing the relative frequency of clinician engagement with structured social determinants of health data.

OBJECTIVE: Electronic health records (EHRs) are increasingly used to capture social determinants of health (SDH) data, though there are few published studies of clinicians' engagement with captured data and whether engagement influences health and healthcare utilization. We compared the relative frequency of clinician engagement with discrete SDH data to the frequency of engagement with other common types of medical history information using data from inpatient hospitalizations. MATERIALS AND METHODS: We created measures of data engagement capturing instances of data documentation (data added/updated) or review (review of data that were previously documented) during a hospitalization. We applied these measures to four domains of EHR data, (medical, family, behavioral, and SDH) and explored associations between data engagement and hospital readmission risk. RESULTS: SDH data engagement was associated with lower readmission risk. Yet, there were lower levels of SDH data engagement (8.37% of hospitalizations) than medical (12.48%), behavioral (17.77%), and family (14.42%) history data engagement. In hospitalizations where data were available from prior hospitalizations/outpatient encounters, a larger proportion of hospitalizations had SDH data engagement than other domains (72.60%). DISCUSSION: The goal of SDH data collection is to drive interventions to reduce social risk. Data on when and how clinical teams engage with SDH data should be used to inform informatics initiatives to address health and healthcare disparities. CONCLUSION: Overall levels of SDH data engagement were lower than those of common medical, behavioral, and family history data, suggesting opportunities to enhance clinician SDH data engagement to support social services referrals and quality measurement efforts.

Social and Medical Care Integration Practices Among Children's Hospitals.

OBJECTIVES: In response to evidence linking social risk factors and adverse health outcomes, new incentives have emerged for hospitals to screen for adverse social determinants of health (SDOH). However, little information is available about the current state of social risk-related care practices among children's hospitals. To address outstanding knowledge gaps, we sought to describe social risk-related care practices among a national sample of children's hospitals. METHODS: We analyzed responses to the 2020 American Hospital Association Annual Survey. Among children's hospitals, we calculated the prevalence of screening for social needs, strategies to address social risks/needs, partnerships with community-based organizations to address social risks/needs at the individual and community level, and rates of impact assessments of how social risk-related interventions affect outcomes. We also used χ2 tests to compare results by hospital characteristics. We weighted results to adjust for nonresponse. RESULTS: The sample included 82 children's hospitals. A total of 79.6% screened for and 96.0% had strategies to address at least 1 social risk factor, although rates varied by SDOH domain. Children's hospitals more commonly partnered with community-based organizations to address patient-level social risks than to participate in community-level initiatives. A total of 39.2% of hospitals assessed SDOH intervention effectiveness. Differences in social risk-related care practices commonly varied by hospital ownership and Medicaid population but not by region. CONCLUSIONS: We found wide variability in social risk-related care practices among children's hospitals based on the risk domain and hospital characteristics. Findings can be used to monitor whether social risk-related care practices change in the setting of new incentives.

Physician awareness of social determinants of health documentation capability in the electronic health record.

Healthcare organizations are increasing social determinants of health (SDH) screening and documentation in the electronic health record (EHR). Physicians may use SDH data for medical decision-making and to provide referrals to social care resources. Physicians must be aware of these data to use them, however, and little is known about physicians' awareness of EHR-based SDH documentation or documentation capabilities. We therefore leveraged national physician survey data to measure level of awareness and variation by physician, practice, and EHR characteristics to inform practice- and policy-based efforts to drive medical-social care integration. We identify higher levels of social needs documentation awareness among physicians practicing in community health centers, those participating in payment models with social care initiatives, and those aware of other advanced EHR functionalities. Findings indicate that there are opportunities to improve physician education and training around new EHR-based SDH functionalities.

Health informatics interventions to minimize out-of-pocket medication costs for patients: what providers want.

Objective: To explore diverse provider perspectives on: strategies for addressing patient medication cost barriers; patient medication cost information gaps; current medication cost-related informatics tools; and design features for future tool development. Materials and Methods: We conducted 38 semistructured interviews with providers (physicians, nurses, pharmacists, social workers, and administrators) in a Midwestern health system in the United States. We used 3 rounds of qualitative coding to identify themes. Results: Providers lacked access to information about: patients' ability to pay for medications; true costs of full medication regimens; and cost impacts of patient insurance changes. Some providers said that while existing cost-related tools were helpful, they contained unclear insurance information and several questioned the information's quality. Cost-related information was not available to everyone who needed it and was not always available when needed. Fragmentation of information across sources made cost-alleviation information difficult to access. Providers desired future tools to compare medication costs more directly; provide quick references on costs to facilitate clinical conversations; streamline medication resource referrals; and provide centrally accessible visual summaries of patient affordability challenges. Discussion: These findings can inform the next generation of informatics tools for minimizing patients' out-of-pocket costs. Future tools should support the work of a wider range of providers and situations and use cases than current tools do. Such tools would have the potential to improve prescribing decisions and better link patients to resources. Conclusion: Results identified opportunities to fill multidisciplinary providers' information gaps and ways in which new tools could better support medication affordability for patients.

"It's a mess sometimes": patient perspectives on provider responses to healthcare costs, and how informatics interventions can help support cost-sensitive care decisions.

OBJECTIVE: We investigated patient experiences with medication- and test-related cost conversations with healthcare providers to identify their preferences for future informatics tools to facilitate cost-sensitive care decisions. MATERIALS AND METHODS: We conducted 18 semistructured interviews with diverse patients (ages 24-81) in a Midwestern health system in the United States. We identified themes through 2 rounds of qualitative coding. RESULTS: Patients believed their providers could help reduce medication-related costs but did not see how providers could influence test-related costs. Patients viewed cost conversations about medications as beneficial when providers could adjust medical recommendations or provide resources. However, cost conversations did not always occur when patients felt they were needed. Consequently, patients faced a "cascade of work" to address affordability challenges. To prevent this, collaborative informatics tools could facilitate cost conversations and shared decision-making by providing information about a patient's financial constraints, enabling comparisons of medication/testing options, and addressing transportation logistics to facilitate patient follow-through. DISCUSSION: Like providers, patients want informatics tools that address patient out-of-pocket costs. They want to discuss healthcare costs to reduce the frequency of unaffordable costs and obtain proactive assistance. Informatics interventions could minimize the cascade of patient work through shared decision-making and preventative actions. Such tools might integrate information about efficacy, costs, and side effects to support decisions, present patient decision aids, facilitate coordination among healthcare units, and eventually improve patient outcomes. CONCLUSION: To prevent a burdensome cascade of work for patients, informatics tools could be designed to support cost conversations and decisions between patients and providers.

More than a Database: Understanding Community Resource Referrals within a Socio-Technical Systems Framework.

Addressing patients' social determinants of health via community resource referrals has historically been the primary domain of social workers and information and referral specialists; however, community resource referral platforms have recently entered the market. We lack an account of the process of community resource referrals and the role of technologies within it. Using sociotechnical systems theory, we analyze data from 12 focus groups (n=102) with healthcare providers, and community organization staff and volunteers in Metropolitan Detroit to describe the process of community resource referral. Findings reveal a deeply sociotechnical process including the following steps: assessing patients' social needs; choosing appropriate referral sources; and facilitating connections. We characterize the importance of knowledge and skills, personal relationships, interorganizational networks, and data sources such as service directories in the referral process. Findings suggest that digital platforms may augment referral functions, but should not be seen to replace interpersonal work, relationships, and interorganizational networks.

Uncovering the relationship between food-related discussion on Twitter and neighborhood characteristics.

OBJECTIVE: Initiatives to reduce neighborhood-based health disparities require access to meaningful, timely, and local information regarding health behavior and its determinants. We examined the validity of Twitter as a source of information for neighborhood-level analysis of dietary choices and attitudes. MATERIALS AND METHODS: We analyzed the "healthiness" quotient and sentiment in food-related tweets at the census tract level, and associated them with neighborhood characteristics and health outcomes. We analyzed keywords driving the differences in food healthiness between the most and least-affluent tracts, and qualitatively analyzed contents of a random sample of tweets. RESULTS: Significant, albeit weak, correlations existed between healthiness and sentiment in food-related tweets and tract-level measures of affluence, disadvantage, race, age, U.S. density, and mortality from conditions associated with obesity. Analyses of keywords driving the differences in food healthiness revealed foods high in saturated fat (eg, pizza, bacon, fries) were mentioned more frequently in less-affluent tracts. Food-related discussion referred to activities (eating, drinking, cooking), locations where food was consumed, and positive (affection, cravings, enjoyment) and negative attitudes (dislike, personal struggles, complaints). DISCUSSION: Tweet-based healthiness scores largely correlated with offline phenomena in the expected directions. Social media offer less resource-intensive data collection methods than traditional surveys do. Twitter may assist in informing local health programs that focus on drivers of food consumption and could inform interventions focused on attitudes and the food environment. CONCLUSIONS: Twitter provided weak but significant signals concerning food-related behavior and attitudes at the neighborhood level, suggesting its potential usefulness for informing local health disparity reduction efforts.

Trust and Privacy: How Patient Trust in Providers is Related to Privacy Behaviors and Attitudes.

Healthcare today requires extensive sharing and access to patient health information. The use of health information technology (health IT) exacerbates patients' privacy concerns because it expands the availability of patient data to numerous members of the healthcare team. Patient concerns about the privacy of their data may be associated with nondisclosure of their information to providers. Patient trust in physicians, a multi-dimensional perception influenced by patient, physician, and situational factors, can facilitate disclosure and use of health IT. Previous work has done little to explore how specific dimensions of trust in physicians are related to patient information-sharing concerns or behavior. Using data from a nationally-representative survey, we show that patients with higher trust in provider confidentiality have significantly lower likelihood of reporting having ever withheld important health information and lower likelihood of thinking it is important to find out who has looked at their medical records. Patient trust in physician competence is related to higher likelihood of thinking it is important for health care providers to share information electronically This work sheds light on the importance of considering multiple dimensions of trust for patient behavior and attitudes related to their information sharing with health care providers.

Hybrid bag of approaches to characterize selection criteria for cohort identification.

OBJECTIVE: The 2018 National NLP Clinical Challenge (2018 n2c2) focused on the task of cohort selection for clinical trials, where participating systems were tasked with analyzing longitudinal patient records to determine if the patients met or did not meet any of the 13 selection criteria. This article describes our participation in this shared task. MATERIALS AND METHODS: We followed a hybrid approach combining pattern-based, knowledge-intensive, and feature weighting techniques. After preprocessing the notes using publicly available natural language processing tools, we developed individual criterion-specific components that relied on collecting knowledge resources relevant for these criteria and pattern-based and weighting approaches to identify "met" and "not met" cases. RESULTS: As part of the 2018 n2c2 challenge, 3 runs were submitted. The overall micro-averaged F1 on the training set was 0.9444. On the test set, the micro-averaged F1 for the 3 submitted runs were 0.9075, 0.9065, and 0.9056. The best run was placed second in the overall challenge and all 3 runs were statistically similar to the top-ranked system. A reimplemented system achieved the best overall F1 of 0.9111 on the test set. DISCUSSION: We highlight the need for a focused resource-intensive effort to address the class imbalance in the cohort selection identification task. CONCLUSION: Our hybrid approach was able to identify all selection criteria with high F1 performance on both training and test sets. Based on our participation in the 2018 n2c2 task, we conclude that there is merit in continuing a focused criterion-specific analysis and developing appropriate knowledge resources to build a quality cohort selection system.

A Rapid Process for Identifying and Prioritizing Technology-Based Tools for Health System Implementation.

BACKGROUND: Health system decisions to put new technologies into clinical practice require a rapid and trustworthy decision-making process informed by best evidence. OBJECTIVE: This study aimed to present a rapid evidence review process that can be used to inform health system leaders and clinicians seeking to implement new technology tools to improve patient-clinician decision making and patient-oriented outcomes. METHODS: The rapid evidence review process we pioneered involved 5 sequential subprocesses: (1) environmental scan, (2) expert panel recruitment, (3) host evidence review panel, (4) analysis, and (5) local validation panel. We conducted an environmental scan of health information technology (IT) literature to identify relevant digital tools in oncology care. We synthesized the recent literature using current evidence review methods, creating visual summaries for use by a national panel of experts. Panelists were taken through a 6-hour modified Delphi process to prioritize tools for implementation. Findings from the rapid evidence review panel were taken to a local validation panel for further rapid review during a 3-hour session. RESULTS: Our rapid evidence review process shows promise for informing decision making by reducing the amount of time and resources needed to identify and prioritize adoption of IT tools. Despite evidence of improved patient outcomes, panelists had substantial concerns about implementing patient-reported outcome tracking tools, voicing concerns about liability, lack of familiarity with new technology, and additional time and workflow changes such tools would require. Instead, clinicians favored technologies that did not require clinician involvement. CONCLUSIONS: Health system leaders can use the rapid evidence review process presented here to usefully inform local technology adoption, implementation, and use in practice.