Background In 2014, only 26 states and D.C. chose to implement the Affordable Care Act (ACA) Medicaid expansions for low-income adults. Objective To estimate whether the state Medicaid expansions were associated with changes in insurance coverage, access to and utilization of health care, and self-reported health. Design Comparison of outcomes before and after the expansions in states that did and did not expand Medicaid. Setting U.S. Participants Citizens aged 19–64 with family incomes below 138% of the Federal Poverty Level in the 2010–2014 National Health Interview Surveys. Measurements Health insurance coverage (private, Medicaid, uninsured); health insurance better than last year; visits with doctors in general practice and with specialists; hospitalizations and ED visits; skipped or delayed medical care; usual source of care; diagnoses of diabetes, high cholesterol, and hypertension; self-reported health; and depression. Results In the second half of 2014, low-income adults in expansion states experienced increased health insurance (7.4 percentage points; 95% CI, −11.3 to −3.4) and Medicaid (10.5 percentage points; 95% CI, 6.5 to 14.5) coverage, and increased quality of insurance coverage compared to a year ago (7.1 percentage points; 95% CI, 2.7 to 11.5) when compared to adults in states that did not expand Medicaid. Medicaid expansions were associated with increased visits with doctors in general practice (6.6 percentage points; 95% CI, 1.3 to 12.0), overnight hospital stays (2.4 percentage points; 95% CI, 0.7 to 4.2), and rates of diagnosis of diabetes (5.2 percentage points; 95% CI, 2.4 to 8.1) and high cholesterol (5.7 percentage points; 95% CI, 2.0 to 9.4); changes in other outcomes were not statistically significant. Limitations Observational study may be susceptible to unmeasured confounders; relies on self-reported data; limited post-ACA timeframe provides information on short-term changes only. Conclusions The ACA Medicaid expansions were associated with higher rates of insurance coverage, improved quality of coverage, increased utilization of some types of health care, and higher rates of diagnosis of chronic health conditions for low-income adults.

Medicaid expansion was associated with increased insurance coverage and access to care during the second year of implementation, but it was also associated with longer wait times for appointments, which suggests that challenges in access to care persist.

BackgroundE-therapy is defined as a licensed mental health care professional providing mental health services via e-mail, video conferencing, virtual reality technology, chat technology, or any combination of these. The use of e-therapy has been rapidly expanding in the last two decades, with growing evidence suggesting that the provision of mental health services over the Internet is both clinically efficacious and cost effective. Yet there are still unanswered concerns about e-therapy, including whether it is possible to develop a successful therapeutic relationship over the Internet in the absence of nonverbal cues.ObjectiveOur objective in this study was to systematically review the therapeutic relationship in e-therapy.MethodsWe searched PubMed, PsycINFO, and CINAHL through August 2011. Information on study methods and results was abstracted independently by the authors using a standardized form.ResultsFrom the 840 reviewed studies, only 11 (1.3%) investigated the therapeutic relationship. The majority of the reviewed studies were focused on the therapeutic alliance—a central element of the therapeutic relationship. Although the results do not allow firm conclusions, they indicate that e-therapy seems to be at least equivalent to face-to-face therapy in terms of therapeutic alliance, and that there is a relationship between the therapeutic alliance and e-therapy outcome.ConclusionsOverall, the current literature on the role of therapeutic relationship in e-therapy is scant, and much more research is needed to understand the therapeutic relationship in online environments.

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A pervasive design issue of AI systems is their explainability-how to provide appropriate information to help users understand the AI.The technical field of explainable AI (XAI) has produced a rich toolbox of techniques. Designers are now tasked with the challenges of how to select the most suitable XAI techniques and translate them into UX solutions. Informed by our previous work studying design challenges around XAI UX, this work proposes a design process to tackle these challenges. We review our and related prior work to identify requirements that the process should fulfill, and accordingly, propose a Question-Driven Design Process that grounds the user needs, choices of XAI techniques, design, and evaluation of XAI UX all in the user questions. We provide a mapping guide between prototypical user questions and exemplars of XAI techniques, serving as boundary objects to support collaboration between designers and AI engineers. We demonstrate it with a use case of designing XAI for healthcare adverse events prediction, and discuss lessons learned for tackling design challenges of AI systems.CCS Concepts: • Human-centered computing → Interaction design process and methods; • Computing methodologies → Artificial intelligence.

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The response to COVID-19 has involved an unprecedented expansion in telehealth. While older Americans and minority populations among others are known to be disadvantaged by the digital divide, few studies have examined disparities in telehealth specifically, and none during COVID-19. This study uses data from a large health system in NYC – the initial epicenter of the US crisis – to describe characteristics of patients seeking COVID-related care via telehealth, ER, or office encounters during the peak pandemic period. Demographic factors are significantly predictive of encounter type. Of any age group, patients 65+ had the lowest odds of using telehealth versus other modalities. By race and ethnicity, Black and Hispanic patients have lower odds of using telehealth versus either the ER or an office visit than either Whites or Asians – this remains true even after adjusting for age, comorbidities and preferred language. Additional research into sociodemographic heterogeneity in telehealth use is needed to prevent potentially further exacerbating health disparities overall.

We examine the effect of the Medicaid expansions under the 2010 Patient Protection and Affordable Care Act (ACA) on consumer financial outcomes using data from a major credit reporting agency for a large, national sample of adults. We employ the synthetic control method to compare individuals living in states that expanded Medicaid to those that did not. We find that the Medicaid expansions significantly reduced the number of unpaid bills and the amount of debt sent to third-party collection agencies among those residing in zip codes with the highest share of low-income, uninsured individuals. Our estimates imply a reduction in collection balances of approximately $1,140 among those who gain Medicaid coverage due to the ACA. Our findings suggest that the ACA Medicaid expansions had important financial impacts beyond increasing health care use.