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Leveraging Technology to Expand Access to Behavioral Health Care for Medicaid Beneficiaries

Transforming Care: Reporting on Health System Improvement

Leveraging Technology to Expand Access to Behavioral Health Care for Medicaid Beneficiaries

telehealth for behavioral health

Digital health innovators have begun leveraging telehealth tools as well as chatbots and other forms of artificial intelligence to engage Medicaid beneficiaries with behavioral health conditions — a group that accounts for a disproportionate share of spending. We describe how these digital tools are being deployed to retain patients in treatment, customize services to their needs, track outcomes, and provide feedback to physical health care providers.

Many digital health innovators cater to fitness and wellness buffs, leaving behind people coping with chronic conditions, those who have difficulty accessing services, and/or those who can’t afford the latest gadget. Many of those left behind are enrolled in Medicaid. This is in part because of the misconception that Medicaid beneficiaries don’t want or use technology, and because it’s easier for tech developers to market directly to consumers than state Medicaid programs and the myriad plans that serve them.

But this is starting to change. The vast expansion of the Medicaid program, the spread of private managed care plans (which now cover two-thirds of beneficiaries), and pressure on states to contain spending have sparked interest in using digital health tools to increase beneficiaries’ access to care and improve services. Health plans and health systems that assume financial risk for the care of Medicaid beneficiaries also have motivation to use digital health tools to generate insights about patients and connect them to needed services.

In this issue of Transforming Care, we look at how technology is being used to make services more convenient, customized, and responsive to Medicaid beneficiaries with mental illnesses and substance abuse disorders, who account for a disproportionate share of spending: about one of five beneficiaries has a behavioral health diagnosis, but this group accounts for nearly half of all Medicaid spending. And while having Medicaid coverage may provide people with better access to services than having no coverage, many beneficiaries still struggle to find treatment because of shortages of behavioral health clinicians who accept Medicaid reimbursement, particularly in rural areas.1

The companies we profile — drawn from a crowded field of behavioral health innovators — are leveraging telehealth tools and using machine learning, chatbots, and other forms of artificial intelligence to engage more patients and better match them with existing resources or offer complements or alternatives to traditional treatment. “While these tools are not substitutes for human contact, they extend the reach of the current workforce and enable us to monitor patients,” says John Torous, M.D., M.B.I., director of the Division of Digital Psychiatry at Beth Israel Deaconess Medical Center, which seeks to build the evidence base for digital mental health. “Eventually, these kinds of tools might help us identify what does and doesn’t work for particular individuals and customize our approaches.”

For more on the potential of technology in behavioral health — as well as the threats to patient privacy and other pitfalls — see our Q&A with John Torous, M.D., M.B.I., director of the Division of Digital Psychiatry at Beth Israel Deaconess Medical Center.

When I think about the Medicaid population, access is the number-one problem in behavioral health today.

Dan Gebremedhin, M.D. partner at Flare Capital Partners

Behavioral Health Tech: Emerging Use Cases

Some state Medicaid agencies, managed care plans, and providers have begun using digital tools to engage and retain patients in behavioral health treatment, customize services to their needs, track outcomes, and provide feedback to physical health care providers. The tools may help overcome the stigma of treatment and reach people who otherwise would not be willing to take part.

On-Demand Treatment for Opioid Use Disorder

One of the more pressing problems is expanding access to medication-assisted treatment (MAT), which has proved lifesaving for many people coping with opioid use disorder. As we described in a recent issue, a handful of states are using hub-and-spoke models to encourage more primary care clinics to offer it. But many people still live far from MAT providers, and others drop out of treatment because the regimens — which often entail frequent medical visits plus counseling — don’t mesh with their other responsibilities. And some don’t seek help at all because of the stigma of walking into a rehab facility or confiding in their primary care clinicians.

Boulder Care seeks to reduce these barriers by offering on-demand MAT — partnering with pharmacies to deliver buprenorphine (one of the medications used to treat opioid use disorder) to people’s homes and using chat and video messaging to provide support. The platform was developed by three women: addiction medicine physician Amanda Wilson, M.D., who founded the Clean Slate addiction treatment centers; M. J. Darby, a nurse with experience in chronic care management; and Stephanie Papes, a venture capitalist who saw the limitations of scaling brick-and-mortar facilities. “One of our key performance measures is the time between when a patient decides they are ready for treatment and when we can get a prescription to them,” says Papes. “We’re aiming to make that at most 24 hours. Say someone overdoses and winds up in the ED, or we hear from a worried primary care doctor: we can engage with someone right away.”

Boulder boxes will be delivered to patients undergoing medication-assisted treatment for opioid use disorder at home. The boxes include equipment to collect saliva for lab testing, gum to mask what some reported was the bad taste of the saliva applicator, and a case so people can mount their phones during telemedicine appointments and video chats used for observing dosing and tests. Source: Boulder Care

Boulder Care’s model is now being piloted in New Hampshire and Oregon, with clinicians seeing patients once before they begin using the virtual platform. In October the Drug Enforcement Administration will promulgate a new rule allowing prescribers to forgo an in-person exam before MAT induction, enabling Boulder Care to scale its model without having clinicians in the same location as patients. Trials of home induction for MAT, with remotely provided support, have found it can be as effective as office-based approaches.

Patients can reach out to their Boulder Care team — a prescribing physician, nurse, and certified peer specialist (someone with experience in addiction and recovery) — using video and chat tools; providers check in often during the first few weeks then adjust the intensity of services based on patients’ preferences and progress. To demonstrate compliance with their regimen, patients videotape themselves using saliva test swabs, which also can detect their buprenorphine levels and whether they’re using illicit substances. “Today, patients get called in for a drug test or know they’ll have one during a clinic appointment, and they can modify drug use a couple of days before,” says Papes. “Instead, we ping a patient to say it's time for your test today. In a 24-hour period, the patient goes on video to take the saliva test. We watch the swab change color and watch them put it into a bar-coded tag and seal it on camera.”

Boulder Care’s peer specialists work with patients to help them find counselors and social supports, but these activities are not a requirement for treatment; the immediate goal is to stabilize patients and then empower them to make changes. “There has been a lot taken from these patients,” Papes says. “We work to remind them that they are more than capable of finding a job, going to school, and otherwise taking back their lives.”

Closing the Loop on Behavioral Health Referrals

Health care providers often struggle to refer Medicaid beneficiaries (and other patients) for behavioral health care; this is particularly a problem in hospitals, where care managers may spend hours faxing or calling to find help for people who turn up in emergency departments in crisis. There are shortages of dedicated beds for psychiatric patients as well as shortages of outpatient programs, particularly ones that accept Medicaid patients; there is also a bewildering array of treatment programs and often a lack of clarity about quality or results.

Several tech companies are trying to streamline behavioral health referrals by making it easier to assess patients’ needs and identify available and appropriate programs. One platform, OpenBeds, focuses on behavioral health referrals and coordination; it was founded by Nishi Rawat, M.D., who as a critical care physician in a small Baltimore hospital struggled to find treatment slots for patients with behavioral health problems.2

OpenBeds offers decision support tools to help clinicians as well as case managers assess patients’ acuity and particular needs. “Many physicians don’t know much about behavioral health,” Rawat says. “We don’t know what kinds of evidence-based treatment might work for a particular patient and we don’t know the right level of treatment.” The system then generates a list of recommended facilities; users can make digital referrals and receive responses from the facilities. They can also use the platform to track whether patients are engaged in treatment.

Delaware is one of two states (the other is Indiana) that have implemented the platform statewide; four other states are in the process of doing so. The state requires all behavioral health treatment providers that accept Medicaid to use its Delaware Treatment and Referral Network (DTRN) and also has made it available to emergency departments (EDs), primary care clinics, departments of correction, and youth services departments. ED care managers, in particular, have been enthusiastic; in over half of cases, they have been able to complete referrals in less than 30 minutes. Since the network went live in September 2018, some 42 providers have made nearly 11,000 referrals.

An immediate goal of DTRN is to reduce the number of people with mental health problems who are “lost to follow up”: “We don’t give people having a heart attack a list of cardiac surgeons,” says Elizabeth Romero, director of the Division of Substance Use and Mental Health at Delaware’s Department of Health and Human Services. “These are people in crisis and we need to empower someone to actually help them.”

The state also has begun to analyze referral patterns to monitor capacity and identify bottlenecks. It has found, for example, that when facilities decline to accept patients, it’s usually not because of insurance denials as anecdotal accounts had suggested, but rather because there’s a mismatch between patients’ needs and available bed types. For example, many facilities are ill prepared to support patients who have medical needs (e.g., help changing colostomy bags) along with mental health issues. The state hopes to leverage DTRN to help its network of Medicaid providers more accurately and efficiently triage patients — to make sure those with less acuity don’t take up resources for those with more complex needs, and to give each patient the best chance of receiving the support they need.

Putting Evidence-Based Therapies in People’s Pockets

Another crop of tech companies is creating platforms that offer therapy, education, and coaching delivered via algorithm-driven programs that complement or serve as alternatives to traditional talk therapy. One platform, myStrength, part of the Livongo company, is being used by Medicaid managed care plans to engage members who appear to have unmet behavioral health needs. First-time users answer a series of questions about their well-being, social supports, and life experiences and are then directed to a suite of interactive resources based on cognitive behavioral therapy, motivational interviewing, mindfulness, and other evidence-based counseling approaches. Someone coping with depression, for example, may be guided through strategies to help them feel better, while someone with anxiety may be offered tools to reduce panic and prevent future instances when they feel out of control.

“The platform is helping people figure out for themselves what feels most important — a key distinction from placing them into a particular counseling program,” says Abigail Hirsch, Ph.D., myStrength’s chief clinical officer. For example, MyStrength asks members about their religious or spiritual preferences and whether they’d like them to be part of their support. A majority say they do, yet this question is not often asked in therapy, Hirsch says.

Along with health plans, some health care providers are using myStrength to track how patients are doing day to day. For example, Atrium Health, a health system in North and South Carolina, has made the tool available to its primary care clinics, where health coaches use it to identify people whose behavioral health conditions may be worsening so they can prioritize their outreach activities.

A similar platform, developed by Pyx Health, monitors people who have moderate-to-severe mental health issues or are at risk of developing behavioral health problems because of their life circumstances. “Think of someone we’ll call Janet,” says Cindy Jordan, founder and CEO. “She is 57, works as a substitute teacher, and suffers a stroke. Despite her best-in-class care, she ends up in the hospital, then a SNF. Then she ends up losing her job, suffering from food insecurity, and doesn’t want to tell friends because she is embarrassed. She is starting to get depressed. More than anything, she’s feeling isolated.”

The face of Pyx Health is Pyxir, a friendly chatbot — a type of artificial intelligence that simulates human conversation. Pyxir prompts people each day to indicate how they’re feeling using an “emoji wheel” and, every two weeks, walks them through surveys that detect depression, anxiety, or loneliness. Based on this information, Pyxir offers tailored support: gentle nudges, words of encouragement, or even jokes or silly gifs. According to the company, most users (88%) say they turn to Pyxir first before asking another person for help.

The Pyx app uses conversational language to guide users through evidence-based screenings for depression, anxiety, and loneliness and recommends cognitive behavioral therapy strategies based on responses.

The platform also leverages people’s natural supports; users can choose to have family members or friends notified if they appear to need help. “We don’t say Christina is not doing well. Instead, we give suggestions on how to interact with Christina,” says Jordan. “Just like how you would think of engaging a family member in group therapy with a patient.”

Pyx Health also seeks to leverage the trusting relationships users develop with Pyxir to ask about their social needs and offer an immediate response — connecting them with a nearby food bank, for example, or other supports from a curated list of resources.


Given gaping holes in access, the behavioral health field is ripe for disruption. As these examples illustrate, innovators are finding ways to leverage technology to make behavioral health services more convenient and responsive — and more of them are targeting the underserved Medicaid market. These examples notwithstanding, experts say there is a lot of redundancy in the field as is typical of early-stage innovation, with many tools targeting low-hanging fruit (e.g., people with moderate conditions rather than serious mental illnesses).

While savvy developers recognize that those with low incomes or unstable lives may be open to using technology, they must also remain cognizant of the unique needs of low-income users. Pyx Health, for example, purposefully doesn’t use video because users may avoid content likely to gobble up their limited data plans. (Read this for more on how developers can match digital tech to patients’ preferences.)

States, managed care plans, and providers need support in vetting and implementing new tools. States like Delaware and North Carolina are taking a top-down approach: deploying new technology as part of broader efforts to improve services for Medicaid beneficiaries, and then using both incentives and mandates to encourage health plans and providers to adopt it. The nonprofit tech incubator Adaptation Health runs Medicaid Innovation Challenges in which they invite Medicaid agencies and plans to define their problems and invite vendors to present solutions. “States and health plans don’t have the time and capacity to engage with vendors,” says David Kulick, Adaptation Health’s cofounder. “But a buyer’s-side market is necessary so that you are creating better market fit. That cascades down to better solutions, better products, better pilots, and less waste.”

Organizations such as the Center for Care Innovations and the recently formed HealthTech4Medicaid also are working to call attention to market opportunities and promote collaboration among developers, states, health plans, and patient advisory panels. “There’s not a lot of end-user research around this population. We want to shed light on what the Medicaid population needs and how they need it,” says Adimika Arthur, M.P.H., HealthTech4Medicaid’s executive director.

Tech developers need to demonstrate meaningful results. There’s a lot of hype in the digital health field, with developers touting metrics such as the number of downloads rather than the number of active users. Some companies have partnered with health systems or plans to track the downstream impact of their tools and found they have led to better management of behavioral health conditions and reduced emergency department or hospital use. But experts point out that these studies are often self-funded or have small sample sizes and other design problems.

Some experts say that randomized control trials (RCTs) of digital behavioral health tools may not be necessary. “A lot of start-ups will spend time investing in this kind of quasi-RCT such that they can persuade potential clients,” says Dan Gebremedhin, M.D., partner at Flare Capital Partners, a venture capital firm focused on health technology and services. “If I were to found a start-up today I don't know that I would invest in that. Instead, I would make sure that the type of intervention is one that activated and engaged patients and reduced the friction for utilization.” The value proposition for some digital health tools is that many people are going without treatment — driving up overall medical and societal costs — and it’s worth trying to engage them in some way.

But better evidence of digital health tools’ effectiveness is clearly needed and randomized controlled trials could enhance the credibility of the tools and spur their adoption. To mitigate their financial risk, some clients are only paying digital health companies when their tools achieve results (“pay for success” models). Other forms of risk-based contracting, such as capitation or shared savings, may spur further development, says Gebremedhin, because they allow developers to invest in technology and services that might not otherwise be reimbursed. Boulder Care’s model of at-home substance use treatment is predicated on receiving per member per month payments, which may range from $900 to $3,500 per member per month.

Technology might be part of comprehensive solutions to help those with the most complex needs. Not only does technology have the potential to provide continuous support and monitor how well people are doing day to day, it may offer policymakers and program leaders a much clearer picture of Medicaid beneficiaries’ needs and preferences and help them identify effective treatment approaches. The key is to be able to act on this information. But not all health plans and providers are prepared to respond to daily alerts that patients are in distress.

Gebremedhin says that provider groups like CityBlock and Galileo are increasingly taking on this oversight role by taking financial risk for discrete populations of Medicaid beneficiaries, including those with serious mental illnesses and/or struggling with substance abuse, and creating bespoke care models to meet their clinical and social needs. Those that are successful will use technology as part of efforts to create new ways of delivering care. “You can’t just invest in technology,” he says, “you need to invest in businesses that are transforming delivery and payment models in health care that are broken.”

Editorial Advisory Board, June 2019

Special thanks to Editorial Advisory Board member Harold Pincus, M.D., for his help with this issue.

Anne-Marie J. Audet, M.D., M.Sc., senior medical officer, The Quality Institute, United Hospital Fund

Eric Coleman, M.D., M.P.H., professor of medicine, University of Colorado

Michael Chernew, Ph.D., professor of health policy, Harvard Medical School

Marshall Chin, M.D., M.P.H., professor of healthcare ethics, University of Chicago

Don Goldmann, M.D., chief medical and scientific officer, Institute for Healthcare Improvement

Laura Gottlieb, M.D., M.P.H., assistant professor of family and community medicine, University of California, San Francisco, School of Medicine

Carole Roan Gresenz, Ph.D., senior economist, RAND Corp.

Allison Hamblin, M.S.P.H., vice president for strategic planning, Center for Health Care Strategies

Thomas Hartman, vice president, IPRO

Clemens Hong, M.D., M.P.H., medical director of community health improvement, Los Angeles County Department of Health Services

Lauren Murray, director of consumer engagement and community outreach, National Partnership for Women & Families

Kathleen Nolan, M.P.H., regional vice president, Health Management Associates

J. Nwando Olayiwola, M.D., M.P.H., associate professor of family and community medicine, University of California, San Francisco, School of Medicine

James Pelegano, M.D., M.S., assistant professor of healthcare quality and safety, Thomas Jefferson University

Harold Pincus, M.D., professor of psychiatry, Columbia University

Chris Queram, M.A., president and CEO, Wisconsin Collaborative for Healthcare Quality

Sara Rosenbaum, J.D., professor of health policy, George Washington University

Michael Rothman, Dr.P.H., executive director, Center for Care Innovations

Mark A. Zezza, Ph.D., director of policy and research, New York State Health Foundation

Publications of Note: April–June 2019

Behavioral Health and Other Chronic Conditions Common Among Adult Medicaid Enrollees Subject to Work Requirements

An analysis of data from the National Survey on Drug Use and Health found people with behavioral health and other chronic conditions were more likely to be enrolled in Medicaid and subject to work requirements than those without any identified health conditions. Among Medicaid enrollees, these groups were also less likely to have worked 20 hours or more in the past week, and thus would be less likely to meet work requirements. The authors say that if work requirements are to be a continued element of Medicaid programs, policy changes are needed to ensure the program covers a full continuum of behavioral health services and that enrollees with work-limiting conditions are given reasonable accommodations and exemptions. Hefei Wen, Brendan Saloner, and Janet R. Cummings, “Behavioral and Other Chronic Conditions Among Medicaid Enrollees: Implications for Work Requirements,” Health Affairs 38, no. 4 (Apr. 2019): 660–67.

Vulnerable Subpopulations Not Adversely Impacted by Bundled Payments Initiative

The Bundled Payments for Care Improvement (BPCI) initiative, which bundles reimbursement for certain medical and surgical procedures into a single payment for an episode of care, has on average lowered Medicare spending without adversely impacting quality of care. To see if beneficiaries with one or more of three vulnerable characteristics — dementia, dual eligibility for Medicare and Medicaid, and recent institutional care — were negatively impacted relative to other groups, researchers looked at changes in emergency department (ED) visits, unplanned hospital readmissions, and all-cause mortality within 90 days of hospital discharges. The results for 12 types of medical and surgical episodes suggest that bundled payment did not adversely affect care quality for beneficiaries with such vulnerabilities. Nonetheless, the authors recommend policymakers support ongoing research to ensure that vulnerable populations are not adversely affected. The study examined BPCI model two, the largest of four BPCI models. Brandon C. Maughan et al., “Medicare’s Bundled Payments for Care Improvement Initiative Maintained Quality of Care for Vulnerable Patients,” Health Affairs 38, no. 4 (Apr. 2019): 561–68.

Adjusting for Social Risk Factors Would Reduce Readmission Penalties for Safety-Net Hospitals

Researchers found poverty, disability, housing instability, residence in a disadvantaged neighborhood, and share of hospital population from a disadvantaged neighborhood were associated with higher readmission rates among hospitals. Using the current specifications for Medicare’s Hospital Readmissions Reduction Program, they found safety-net hospitals had higher readmission rates than the most affluent hospitals for three conditions (acute myocardial infarction, pneumonia, and congestive heart failure). Adding social factors to risk adjustment cut these differences in half. More than half of the safety-net hospitals saw the penalty decline with this risk adjustment, and 47.5 percent went from having a penalty to no penalty, resulting in a $17 million reduction in penalties. Karen E. Joynt Maddox et al., “Adjusting for Social Risk Factors Impacts Performance and Penalties in the Hospital Readmissions Reduction Program,” Health Services Research 54, no. 2 (Apr. 2019): 327–36.

Developing a Lexicon for Social Risk

The authors of this commentary advocate for defining and distinguishing key terms and concepts related to the social determinants of health to ensure they are not misunderstood, conflated, or confused. They propose a set of definitions for key terms, including social determinants of health, population health, social needs, social risk factors, and behavioral risk factors as these terms describe different approaches and causes of action. Some characterize structural factors that govern the distribution of resources such as income and education, which may not in and of themselves impair health, while others point to individual-level social or behavioral risk factors that do. Hugh Alderwick and Laura M. Gottlieb, “Meanings and Misunderstandings: A Social Determinants of Health Lexicon for Health Care Systems,” Milbank Quarterly 97, no. 2 (June 2019): 407–19.

Review of Evidence Suggests ACOs Reduce Institutional Care, Improve Chronic Disease Management

A review of publications describing the association between public and private accountable care organizations (ACOs) and health care service use, processes, and outcomes found the most consistent associations across payer types were reduced inpatient use, reduced emergency department visits, and improved measures of preventive care and chronic disease management. Seven studies evaluating patient experience or clinical outcomes found no evidence that ACOs worsen outcomes of care. The authors say the impact on patient care and outcomes should continue to be monitored. The 42 articles covered a mix of ACO contracts: Medicare (24), Medicaid (5), commercial (11), and all payers (2). Brystana G. Kaufman et al., “Impact of Accountable Care Organizations on Utilization, Care, and Outcomes: A Systematic Review,” Medical Care Research and Review 76, no. 3 (June 2019): 255–90.

Loss of SNAP Associated with Food Insecurity and Poor Health in Working Families with Young Children

Researchers examined how benefit reductions or cutoffs in the Supplemental Nutrition Assistance Program (SNAP) were related to economic hardships (food and energy insecurity, unstable housing, forgone health and/or dental care, and health cost sacrifices) and to caregiver and child health. Families with children younger than age 4 whose benefits were altered after their incomes increased had significantly higher odds of household and child food insecurity compared with a group with consistent participation in SNAP, a program that helps working families meet their nutritional needs. Reduced benefits were also associated with 1.43 and 1.22 times greater odds of fair or poor caregiver and child health, respectively. The authors recommend policy modifications to smooth changes in benefit levels as families’ income increases. Stephanie Ettinger de Cuba et al., “Loss of SNAP Is Associated with Food Insecurity and Poor Health in Working Families with Young Children,” Health Affairs 38, no. 5 (May 2019): 765–73.

Medicaid Expansions Reduce Disparities in Birth Outcomes Between Black and White Women

Using data from 2011–16, researchers found expansion of Medicaid eligibility was not significantly associated with differences in rates of low birth weight or preterm birth outcomes overall, but there were significant improvements in relative disparities for black infants compared with white infants in states that expanded Medicaid compared with those that did not. In these states, disparities between white and black infants declined for preterm birth, very preterm birth, low birthweight, and very low birthweight. Clare C. Brown et al., “Association of State Medicaid Expansion Status with Low Birth Weight and Preterm Birth,” Journal of the American Medical Association 321, no. 16 (April 23/30, 2019): 1598–1609.

Collaborations Between Health and Social Service Sectors Benefit Health System Engagement

A study that sought to identify the features of effective collaboration between the health and social services sectors measured six types of ties (any collaboration, referrals, sharing information, cosponsoring projects, financial contracts, and joint needs assessment), examining their impact on avoidable health care use and spending for older adults. The researchers found high-performing networks were distinguished from low-performing networks by two features: having health care organizations occupy a central position and having subnetworks that were more cohesive. Across all networks, Area Agencies on Aging were more centrally positioned than any other type of organization. The authors conclude that cross-sector engagement by health care organizations may reduce preventable health care use and spending. These efforts could leverage Area Agencies on Aging, which are already positioned as network brokers, they say. Amanda L. Brewster et al., “Collaboration in Health Care and Social Service Networks for Older Adults,” Medical Care 57, no. 5 (May 2019): 327–33.

Women in High-Deductible Health Plans Experienced Delayed Breast Cancer Care

A study of time to first breast cancer diagnostic testing, diagnosis, and chemotherapy among a group of women whose employers switched their insurance coverage from health plans with low deductibles ($500 or less) to plans with high deductibles ($1,000 or more) found low-income women in high-deductible plans experienced relative delays of 1.6 months to first breast imaging, 2.7 months to first biopsy, 6.6 months to incident early-stage breast cancer diagnosis, and 8.7 months to first chemotherapy. High-income women in high-deductible plans experienced delays; however, these were shorter than those experienced by their low-income counterparts. The authors found members living in metropolitan, nonmetropolitan, predominantly white, and predominantly nonwhite areas also experienced delayed breast cancer care. Policies that reduce out-of-pocket spending obligations for breast cancer care may be needed, they say. J. Frank Wharam et al., “Vulnerable and Less Vulnerable Women in High-Deductible Health Plans Experienced Delayed Breast Cancer Care,” Health Affairs 38, no. 3 (Mar. 2019): 408–15.

Mental Health Visits to the ED Rising Among Youth and Young Adults

Researchers found visits to the emergency department (ED) for psychiatric purposes among youth are rising across the U.S. Between 2011 and 2015, there was a 28 percent overall increase in psychiatric ED visits per 1,000 youth. The largest increases were observed among adolescents (54%) and African American (53%) and Hispanic patients (91%). A 2.5-fold increase in suicide-related visits was observed among adolescents. Although psychiatric ED visits were long (more than half were three or more hours in length), only 16 percent of patients were seen by a mental health professional during their visit. The authors say psychiatric expertise as well as effective mental health treatment options, particularly those directed at combatting the rising suicide epidemic among adolescents, are needed in the ED. Luther G. Kalb et al., “Trends in Psychiatric Emergency Department Visits Among Youth and Young Adults in the U.S.,” Pediatrics 143, no. 4 (Apr. 2019): e20182192.

Homeless Infants Face Long-Standing Health Challenges

By linking Massachusetts emergency shelter enrollment records with Medicaid claims, researchers found infants born during a period of unstable housing resulting in homelessness had higher rates of low birthweight, respiratory problems, fever, and other common conditions as well as higher annual spending. The differences in most health conditions persisted for two to three years. Asthma diagnoses, emergency department visits, and spending were significantly higher through age 6. They say while screening and access to health care can be improved for homeless infants, long-term solutions require a broader focus on housing and income. Robin E. Clark et al., “Infants Exposed to Homelessness: Health, Health Care Use, and Health Spending from Birth to Age Six,” Health Affairs 38, no. 5 (May 2019): 721–28.

Practicing Physicians’ Knowledge About Their Legal Obligations When Caring for Patients with Disability

Researchers interviewed practicing physicians to explore their knowledge of their obligations to accommodate patients with disability under federal civil rights law. Interviewees reported having had little formal training about, and demonstrated superficial or incorrect understanding of, their obligations in three potentially problematic areas: deciding which accommodations their practices should implement, refusing patients with disability, and holding patients accountable for costs of accommodations. To achieve equitable treatment of the approximately 61 million Americans with disability, further education in the Americans with Disabilities Act and other disability civil rights laws may be warranted, the authors say. Nicole D. Agaronnik et al., “Knowledge of Practicing Physicians About Their Legal Obligations When Caring for Patients with Disability,” Health Affairs 38, no. 4 (Apr. 2019): 545–53.


1. The Mental Health Parity and Addiction Equity Act of 2008 mandated that Medicaid managed care plans must cover mental health and substance use disorder services on par with medical and surgical benefits. This may have exacerbated or brought lack of capacity into relief.

2. OpenBeds’ development was funded in part by a $1.8 million grant from the National Institutes of Health aimed at helping providers refer patients to the nation’s patchwork of opioid use disorder treatment facilities.

Publication Details



Martha Hostetter, Consulting Writer and Editor, Pear Tree Communications

[email protected]


Martha Hostetter and Sarah Klein, “In Focus: Leveraging Technology to Expand Access to Behavioral Health Care for Medicaid Beneficiaries,” Transforming Care (newsletter), June 27, 2019.

Q&A with John Torous: The Benefits and Perils of Using Digital Health Tools to Address Behavioral Health Problems

John Torous headshot

John Torous, M.D., M.B.I., is director of the Division of Digital Psychiatry at Beth Israel Deaconess Medical Center in Boston, where he investigates the risks and benefits of behavioral health technologies. Torous also chairs the American Psychiatric Association’s workgroup on smartphone apps. Transforming Care spoke to him about his research and views of the potential and pitfalls of new technology.

Transforming Care: We’ve never heard of a division of digital psychiatry. What is it?

Torous: Our division conducts research projects funded by industry, philanthropies, and the National Institutes of Health and helps educate clinicians as well as medical students and residents on how to evaluate digital health tools and incorporate them into practice. We also host a small digital clinic where we see people for face-to-face care and ask them to use apps outside of sessions to augment care. We work with a lot of people with schizophrenia, for instance, who now have access to smartphones but may not ever have had any formal training on how to use them for recovery.

Transforming Care: Your platform MindLAMP and a lot of your research focuses on digital phenotyping, which involves use of smartphones to track people’s sleep patterns, physical activity, and other patterns and monitor human–computer interactions. What have you learned so far about the reliability of these markers?

Torous: We know they have a lot of potential to inform us of functional outcomes, which has been the missing piece for this field. The tricky part is getting the data in a reliable way: there are so many different types of phones and operating systems and people use their phones very differently. What we’ve been focusing on now is metadata — looking at how someone interacts with the phone because doing so takes a certain amount of attention, memory, and engagement, and we can begin to measure those. For example, with one of the cognitive assessment games we have designed, we can see how long a patient with schizophrenia spends on a screen, how quickly they tap numbers, and whether they stop and get stuck in the middle. It’s a new way to look at cognition that gets around some of the privacy and ethical concerns that arise when you collect continuous passive data like GPS and call or text logs from phones.

Transforming Care: Why did you create your own platform for collecting digital signals?

Torous: We wanted something that was completely free and open source. A lot of us do similar research on digital phenotypes but the tools people are selling are prohibitively expensive. There are costs of maintaining an app platform, but they are not nearly as high as the fees many are charging for use of their app. And a challenge of proprietary tools is they don’t share their methods so are not reproducible. Because MindLAMP is free, it’s exciting to see its uptake. For example, researchers in China and Canada are using it to study schizophrenia and a group in Los Angeles is using it to study language and stress. Clinicians in the Netherlands and Nepal also are using it to learn new information about their patients. At the end of the day, it’s about being able to capture real-time data from our patients in a safe, secure, and reliable manner and combine that with passive data.

Transforming Care: How do these data get incorporated into practice? Can you give us an example?

Torous: We had a patient with schizophrenia who was becoming more depressed and psychotic. When we looked at the data with him, it was very clear something about his sleep was likely exacerbating his symptoms. We helped him monitor his sleep and he could see as his sleep improved, his symptoms got better. Until he saw it week by week, I don’t think he believed those two go together. With clinicians, we stress the importance of using data to open a dialogue. One of the big fantasies of this field is that data alone will fix everything. But what probably helps the most is the therapeutic alliance. Some digital health apps can help build that alliance by bringing in new kinds of information or making certain patterns more apparent. Patients will bring up things that wouldn't have come up before and this information offers a way for people to start a new conversation. The challenge with a lot of digital health apps is that the data go into a silo and it’s very hard to access it, let alone show your clinician on a visit. One app may track your medicine, another your cognitive-behavioral therapy (CBT). It's very hard to put it all together and understand how you are doing.

Transforming Care: As you look across the landscape of digital apps, where do you see the most activity and where are the missed opportunities?

Torous: We're definitely seeing a lot in terms of predictive analytics and digital phenotyping offerings that leverage information from online behavior and smartphone signals to discern patterns and identify at-risk patients. There is also a lot in what I would call CBT and mindfulness delivered to your phone. What we're not seeing as much is thinking about complete clinical pathways or tools that look across the patient journey. In some ways you could say the digital health tools are addressing potholes in the road. Many solutions today are more like carve-outs in that they aren’t easy to integrate into clinical care. There’s also a lot of duplication of apps and algorithms with less focus on how these tools can and should be used in actual care settings. (For examples of how digital health tools are being integrated into clinical care, see our companion piece.)

Transforming Care: You’ve also spent a fair amount of time thinking about how to evaluate apps in terms of privacy and safety. What are the biggest concerns in this regard?

Torous: The privacy concerns are hard to minimize, especially for a health plan looking to pick an app to invest in. We actually hacked some of these mental health apps and intercepted the traffic to see if what the privacy policy promises about where they send data is true and what we found is over half the apps were sending data to sources they never disclosed. We described our findings in JAMA, and it was shocking enough I went to the Federal Trade Commission in May to talk to them about what we found.

Transforming Care: We’ve read that some people may actually prefer talking to a chatbot or an avatar than to a counselor or psychiatrist. Can this kind of relationship have therapeutic value?

Torous: Yes, but what’s interesting is we don’t really know who might respond best to a virtual versus a human approach, so it’s really hard to look at someone a priori and say who’s going to benefit and who may be harmed. For example, some people with certain anxiety disorder will benefit from pushing through their comfort zone and engaging in nonvirtual interventions. We have to think about how we match the person to the tool.

Transforming Care: How about in terms of measuring effectiveness. Where do we stand now?

Torous: I think as app development becomes cheaper and people can build these tools, we are going to see more of a focus on studying how it works, who it works for, at what dose, and how long you should use it. Right now there are so many CBT programs, so many digital phenotype programs, and so many survey programs. Really what we need is research saying who does it work for and why does it work? A study recently found the mindfulness app Headspace worked no better than a placebo (a sham meditation app that didn’t teach users core mindfulness tenets or introduce progressive or varied techniques). That gets to the mechanism of action. As you can imagine, it's very hard to do that research. You have to have a platform just like Headspace or build one.

Transforming Care: Tell us about your work with the American Psychiatric Association. What are you trying to accomplish?

Torous: In essence, we’re trying to help clinicians make informed choices about digital health apps by teaching them how to analyze these apps rather than providing recommendations, which would be hard and often misleading to do because apps are so dynamic and personal. We published a framework in Lancet Digital Health that we developed with input from patients, clinicians, and payers to evaluate privacy, safety, data ownership policies, and other factors. Today when considering apps, I think a lot of people start with the look and feel. Those are important, but we need to get people thinking about privacy and safety first. With the American Psychiatric Association, we will be showing how we analyzed a few apps so people can see there is no magic formula or black box or score. You're just asking the right questions and because of that making a better decision.


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Martha Hostetter, Consulting Writer and Editor, Pear Tree Communications

[email protected]


Martha Hostetter and Sarah Klein, “Q&A with John Torous: The Benefits and Perils of Using Digital Health Tools to Address Behavioral Health Problems,” Transforming Care (newsletter), June 27, 2019.

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