Healthcare Hot Button Issues

About Healthcare Hot Button Issues

We strive to translate scientific findings to answer your burning questions about healthcare in plain language. Let us know the topics of your interest. We would love to cover them! Please leave comments or email us: Support@AnalyticaNow.net. We explain health care issues based on scientific evidence and include topics such as medical conditions, health economics, cost, physician, clinic & hospital payment, prescription drugs, and nursing & long-term care. You can follow us on Facebook: https://www.facebook.com/HotButtonIssues and Twitter: https://twitter.com/buttonissues The podcast is provided by Analytica Now, a company specializing in health analytics, economics, and policy. The views expressed are the author's and not those of Analytica Now. hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast)

Publisher

Translating Scientific Findings for the Public

Category

health & fitness · science

Language

en

Explicit

No

First episode

29 May 2022

Latest episode

25 Sept 2022

Latest episodes

10 episodes in the feed.

1. 

   25 Sept 2022

   Amazon Care vs. One Medical: a Tale of Two Primary Care Innovation Models

   On July 21, 2022, Amazon announced its $3.9 billion bid for One Medical, a primary care innovator. Some industry observers consider this a smart move (https://knowledge.wharton.upenn.edu/article/why-is-amazon-purchasing-a-health-care-provider/) by Amazon, while others think this might be another failed attempt (https://www.latimes.com/business/story/2022-08-18/column-amazons-one-medical). The deal is currently under regulatory review by the Federal Trade Commission. Just several weeks later, Amazon decided to terminate Amazon Care, its telehealth operation, by the end of 2022. In an email (https://www.cnbc.com/2022/08/24/amazon-is-shutting-down-amazon-care-telehealth-service.html) to employees, Neil Lindsay, the senior vice president of Amazon Health Services, said: “Although our enrolled members have loved many aspects of Amazon Care, it is not a complete enough offering for the large enterprise customers we have been targeting and wasn’t going to work long-term.” Why did Amazon decide to discontinue Amazon Care and acquire One Medical in the meantime? How are these two models different? How can One Medical generate savings and become sustainable in the long term? Below is our analysis to shed some light on these questions. Amazon Care is essentially a telehealth provider and uses a fee-for-service payment model. Amazon Care was launched in 2019 (https://www.zdnet.com/article/why-amazons-push-into-healthcare-could-be-its-most-important-project-yet/) to serve its own employees and their family members located in the State of Washington. In June 2021, Amazon Care expanded its virtual care to all 50 states. It provides a virtual care platform; clinical services are contracted out to Care Medical, a third-party medical group. Surprisingly, it does not have a mission statement on its website (https://amazon.care/about). Amazon Care (https://amazon.care/faqs) is essentially a telehealth provider, supplemented by home-based services from nurses. It offers 24/7 virtual care, including video care or care chat. It is fast: customers are promised to be connected to a clinician within 60 seconds. When recommended by a video care clinician and approved by the customer, a nurse will visit the customer’s home or workplace to perform physical examinations, conduct testing, administer vaccines, or collect lab samples. Its home-based services are only available in select locations and do not involve diagnosis or treatment. Amazon Care is paid on a fee-for-service basis. Eligible employees use their insurance sponsored by their employers and are responsible for co-pay, co-insurance, and deductibles. Amazon Care is not much different from traditional telehealth providers, and it is thus nearly 20 years late to the employer market and has failed to gain traction. Compared to existing telehealth providers such as Teladoc Health, Amazon Care does not differentiate itself much. It provides home-based services, but only nurses visit customers’ homes, and they provide only ancillary services rather than medical care that involves diagnosis and treatment. In other words, it does not offer meaningful in-person care that would differentiate itself from competing telehealth providers. In-person care is critical to managing chronic medical conditions and building trust between clinicians and customers. Unlike Teladoc Health, Amazon Care does not offer chronic condition management and monitoring services. According to the Centers for Disease Control and Prevention (https://www.cdc.gov/chronicdisease/about/costs/index.htm), individuals with chronic medical conditions account for 90% of the total healthcare spending. In comparison, after acquiring Livongo in 2020, Teladoc Health gained capabilities of chronic condition management and monitoring via connected devices. Given a lack of meaningful differentiation in telehealth offerings, Amazon Care is just another telehealth provider. But considering Teladoc was launched in 2002, Amazon Care is nearly 20 years late to the employer market. This is one of the reasons that it has not gained much traction. As of 2022, less than 10 major employers use Amazon Care, including Whole Foods, one of Amazon’s subsidiaries. By the way, this is not the first time Amazon has failed in healthcare due to a lack of differentiation. You can read our analysis (https://hotbutton.substack.com/p/a-tale-of-two-employer-based-healthcare-aa1) on why Haven Healthcare - its joint venture with JP Morgan and Berkshire Hathaway - did not fly. Amazon Care is supplemental to the existing healthcare system and unlikely to generate sustainable savings. In the absence of in-person care offerings, a telehealth provider like Amazon Care is only supplemental to the existing inefficient system used by employers, who have to pay additional fees for telehealth services. In Amazon’s own words (https://www.computerworld.com/article/3441397/why-amazon-care-may-be-the-new-model-for-corporate-healthcare.html), “…the company's program is supplemental and additional to coverage already offered – not a substitute for health insurance already offered to its employees. In fact, only workers already participating in company-offered healthcare insurance can participate in Amazon Care.” Being a supplement to the existing healthcare system creates additional fragmentation in care delivery that tends to lead to waste and inefficiency. Without the capabilities of managing chronic conditions, building long-term trusting relationships with customers, and changing the existing healthcare delivery approach meaningfully, it is very unlikely that Amazon Care will generate savings and become a long-term solution for employers. In contrast, One Medical has a hybrid model - both virtual and in-person care - with significant differentiation from traditional primary care and has achieved high customer satisfaction. Founded in San Francisco, CA in 2007, One Medical (https://www.sec.gov/Archives/edgar/data/1404123/000140412322000010/onem-20211231.htm) uses a “human-centered, technology-powered model” to transform primary care to achieve three aims: better care, better health, and lower cost. Last year, it spent $2.1 billion to acquire Iora Health, a primary care innovator serving the Medicare Advantage market. The company is growing fast. In the last six months, it added 62,000 members (https://www.sec.gov/Archives/edgar/data/1404123/000140412322000054/onem-20220630.htm), equivalent to an annual growth rate of 17%. Currently, One Medical has 204 physical offices in 25 markets, serving 8,500 employers, 750,000 employees and their family members, and 40,000 Medicare or Medicaid beneficiaries. One Medical offers convenient and quality care. It provides 24/7 on-demand virtual care available within minutes, same-day or next-day appointments for in-person care, and an inviting physical office environment at convenient locations. Its brick-and-mortar offices and in-person care allow One Medical to build long-term relationships with customers, manage chronic medical conditions and high-need patients, and offer a wide range of wellness programs. The core differentiator is its “team-based and salaried provider model.” Clinicians are not subject to perversive incentives under a fee-for-service system. Clinicians see “35% fewer patients than average (https://digital.hbs.edu/platform-rctom/submission/one-medical-group-curing-the-process-of-healthcare-delivery/),” and its technology platform allows them to spend less time on documenting and more time with customers. So far, One Medical has generated high customer satisfaction, with a net promoter score of 90 in 2021, which is calculated as the difference between the percentage of customers who recommend the services and that among those who do not. In the first half of 2022, One Medical has nearly quadrupled its capitation-based revenue and thus down-weighted the importance of its fee-for-service revenue. One Medical has four major sources of revenue: membership fees, health partnership fees, fee-for-service revenue, and Medicare capitation revenue. The company charges an annual fee of $199 per member, with a total of $86 million in 2021 (https://www.sec.gov/Archives/edgar/data/1404123/000140412322000010/onem-20211231.htm) (14% of the total revenue). One Medical provides primary care services to enterprise customers covered by health partners and receives per-employee fixed fees ($224 million in 2021, 36%). The company also receives payments for clinical services on a fee-for-service basis and care management services from certain payers ($182 million in 2021, 29%). Capitation revenue from Medicare amounted to $127 million in 2021, 20% of the total revenue. During the first six months of 2022, capitation revenue from Medicare increased at an annual rate of 400% to $253 million (https://www.sec.gov/Archives/edgar/data/1404123/000140412322000054/onem-20220630.htm). As a result, capitation revenue accounts for 50% of the total revenue. This also leads to a decrease in the weight of the fee-for-service revenue from 29% to 15%. However, One Medical has been losing money, and it might be fighting an uphill battle to become profitable. In 2020 and 2021, the company lost $90 million and $256 million (https://www.sec.gov/Archives/edgar/data/1404123/000140412322000010/onem-20211231.htm), respectively. In the first six months of 2022, it had a loss of $185 million (https://www.sec.gov/Archives/edgar/data/1404123/000140412322000054/onem-20220630.htm) or $370 million on an annual basis. There are several possible explanations. First, One Medical is investing about 18% of its revenue in the technology platform, new physical offices, and other infrastructure for future expansion. In addition, it spends about 10% of its revenue on marketing and sales. Second, its general and administrative expenses are very high, accounting for 52% of the total revenue in 2021, which was partially due to the acquisition of Iora Health. But it decreased considerably in the first six months of 2022 to 37% of the revenue. It is likely that the company has not reached the economics of scale beyond which point, the average administrative expense per member will come down dramatically. Lastly but importantly, it is generally considered challenging to generate savings (https://hbr.org/2022/01/can-new-players-revive-u-s-primary-care) from primary care innovation. Primary care spending accounts for 5 to 8% of the total healthcare spending in the U.S., but prime care clinicians do not control the rest of 92 to 95% of spending on specialty and hospital care unless they act as a gatekeeper, which is not common. Also, academic research does not lend us much confidence either. Existing studies on primary care innovations have shown inconsistent findings: some demonstrate savings (https://dash.harvard.edu/handle/1/42029777) while others do not (https://journals.lww.com/lww-medicalcare/Abstract/2018/09000/Changes_in_Utilization_and_Expenditures_for.7.aspx). In particular, the 4-year Comprehensive Primary Care Initiative (CPC) and the first two years of its successor - CPC Plus - reduced the growth rate (https://doi.org/10.1007/s11606-021-06952-w) of hospital admissions and emergency department visits but failed to achieve a statistically significant decline in the total cost of care. Fortunately, there might be a way out, and it seems One Medical is heading in the right direction. A promising approach (https://hbr.org/2022/01/can-new-players-revive-u-s-primary-care) is to take risks and manage the health of a population. This is because Primary care innovation can only sustain in a payment environment where two-thirds or more (https://www.healthaffairs.org/doi/10.1377/hlthaff.2017.0367) expenses are reimbursed on a capitation basis. The fall of Turntable Health (https://www.forbes.com/sites/robertpearl/2017/10/24/primary-care/) is a case in point. Using the above approach, the savings generated by primary care innovation through reductions in unnecessary care, urgent or emergent care, and hospitalizations could be used to improve primary and preventive care. A portion of savings would become part of the company’s bottom line. It seems the company is heading in the right direction as its capitation-based revenue from Medicare has quadrupled during the first half of 2022. One Medical can also leverage its existing network of specialty and hospital providers to offer quality and efficient care. In addition, as membership grows, the company will be able to reap the benefits of economies of scale and result in lower administrative expenses per member. Further, high member retention rates are critical to One Medical’s long-term profitability. This is largely due to the fact that potential savings increases (https://www.sec.gov/Archives/edgar/data/1404123/000140412322000010/onem-20211231.htm) as a member’s tenure increases. Given high customer satisfaction, its member retention rate should be high. One Medical’s at-risk arrangement with Medicare has the right target population. It takes time, years or even decades, to materialize the economic benefits of wellness and prevention in a relatively healthy population. Managing the Medicare population increases the chance of generating short- and medium-term savings because the Medicare population incurs higher spending than the working population. Summary Aiming to innovate primary and urgent care, Amazon Care, in its current form, does not differentiate itself sufficiently from traditional virtual care providers and has not been able to gain traction in the employer market. In stark contrast, One Medical has a number of differentiators from traditional primary care providers. Although facing challenges in generating sustainable savings, its at-risk arrangements with Medicare holds promise and has been growing very fast. Based on what we observed, it is therefore not surprising that Amazon decided to shut down Amazon Care and acquire One Medical. — Let us know the topics of your interest (support@AnalyticaNow.net (mailto:support@AnalyticaNow.net)). We would love to cover them. The article is provided by Analytica Now (https://analyticanow.net/), a company specializing in health analytics, economics, and policy. Thank you for being part of our community! 🎉 This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

2. 

   21 Aug 2022

   Digital Mental Health Has an Achilles' Heel in Generating Savings for Payers. But There is a Way Out.

   Digital mental health is a sizzling-hot area that attracts a large amount of investment. In 2021, venture capital poured $5 billion (https://www.modernhealthcare.com/digital-health/beyond-byline-behavioral-health-startups-draw-record-level-investment) into digital mental health startups, accounting for one-sixth of the $30 billion investment in digital health. In the first half of 2022, the pace slowed down, but still, these companies hauled in $1.3 billion (https://bhbusiness.com/2022/07/11/mental-health-still-tops-digital-health-investment-but-signs-point-to-potential-slowdown/), larger than any other non-mental health digital health investments. It was estimated that about 10,000 to 20,000 (https://www.apa.org/monitor/2021/01/trends-mental-health-apps) mental health apps are available, ranging from mindfulness, meditation, and therapy, to prescription drugs. Digital mental health interventions may be provided via computers, tablets, smartphones, virtual reality equipment, and gaming devices, and they may come with or without support from unlicensed personnel or licensed clinicians. Roughly speaking, digital mental health interventions can be classified into three buckets: consumer-driven apps, therapeutic apps, and clinician-led digital interventions. Consumer-driven apps are typically used by consumers on their own, and these apps do not claim to diagnose, prevent, or treat mental health conditions and do not require the approval of the Food and Drug Administration (FDA). These apps may offer psycho-education, motivational guidance, or coping skills. Therapeutic apps are developed to treat mental health conditions and require FDA premarket approval. So far, only a few apps (https://www.verywellmind.com/fda-approval-and-mental-health-apps-5193123) have been approved; they can be used to treat attention deficit hyperactivity disorder, nightmare disorder, substance abuse, and insomnia. Clinician-led digital interventions are tele-mental health services (i.e., tele-psychiatry or tele-therapy) led and supervised by licensed clinicians. Existing academic evidence shows that well-designed mental health apps are effective in improving health outcomes, particularly for anxiety and depression, but they are generally not reimbursed by payers. There is consistent evidence (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7951054/) on the usability, acceptance, safety, and effectiveness of digital mental health interventions. Mental health apps based on clinical guidelines and developed with input from both users and clinicians improve common mental health conditions such as anxiety and depression. Digital mental health interventions are particularly effective and generate high user satisfaction when licensed clinicians are involved. Most mental health apps are consumer-driven apps, but they are typically not reimbursed by payers, although some self-insured employers or integrated systems (https://www.apa.org/monitor/2021/10/news-digital-interventions) cover them. Payers do cover clinician-led digital interventions but may not reimburse therapeutic apps. During the pandemic, most payers waived cost-sharing (https://www.ahip.org/health-insurance-providers-respond-to-coronavirus-covid-19) for clinician-led digital interventions. Digital mental health has an Achilles’ heel in generating savings for payers: its convenience makes people come out of the woodwork and increases service volume. This is due to several reasons that make the utilization of formal care highly sensitive to the economic cost of receiving treatment, e.g., increased availability of treatment options, improved insurance coverage, lower cost-sharing, and reduced travel. As a result of the factors discussed below, when digital mental health offers convenience and reduces the cost of receiving treatment, more people may seek formal care instead of relying on informal care or receiving no care at all. Among those who already receive formal care, the frequency and duration of such care may increase. 1. There is a potential demand for mental health services that has not been materialized. According to the National Institute of Mental Health, 52.9 million (21 percent) (https://www.nimh.nih.gov/health/statistics/mental-illness) U.S. adults had at least one diagnosable mental illness in 2020, but only 24.3 million (46 percent) received professional mental health services. Also, 14.2 million (6 percent) adults had serious mental illnesses, among whom 65 percent (9.1 million) received formal care. This may be because of a shortage of licensed clinicians. Nationally, the existing clinicians can serve less than one-third (https://www.kff.org/other/state-indicator/mental-health-care-health-professional-shortage-areas-hpsas/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%22asc%22%7D) of the U.S. population, assuming one clinician per 30,000 population. 2. There are various potential substitutes for professional mental health services, especially for non-severe mental conditions. Social support plays an important and interesting role (https://doi.org/10.1177/2156869310392793) in seeking formal care. When mental health conditions are mild or moderate, family, friends, co-workers, churches, or even bar tenders may help mitigate or resolve an individual’s mental health syndromes such as anxiety or depression. That is, informal care can substitute for formal care, and as a result, individuals with social support are less likely to seek formal care. However, when symptoms are severe, the greater social support, the more likely an individual would seek professional mental health services. This is because support givers would encourage an individual to seek formal treatment; they may even pressure that individual to do so when cognitive or emotional impairment is so severe that the affected individual is not able to make treatment decisions. There are also substitutes for formal care other than social support for certain mental conditions, e.g., yoga, meditation, and massage, among others. 3. Even in the absence of digital interventions, mental health services utilization is much more sensitive to the price (or cost) of treatment than physical health services. In economic terms, mental health services have a larger elasticity of demand. According to the existing academic research, the elasticity of demand for outpatient mental health services is typically two to three times (https://oxfordre.com/economics/economics/economics/view/10.1093/acrefore/9780190625979.001.0001/acrefore-9780190625979-e-80) that of typical outpatient medical (i.e., physical health) services. 4. Digital mental health offers convenience and facilitates access to care. Both consumer-driven mental health apps and clinician-led digital interventions make access easier; formal care provided by clinicians is literarily available at your fingertips. In addition, the use of digital interventions can reduce stigma (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9153904/), a major barrier to receiving mental health services. The jury is still out, but it is more likely than not that wide adoption of digital mental health will increase overall spending for payers. There is a paucity of research on whether implementing digital mental health affects the total cost of care, and the limited results are inconclusive. A 2011 study (https://journals.lww.com/lww-medicalcare/Abstract/2011/09000/A_Budget_Impact_Analysis_of_Telemedicine_based.13.aspx) conducted by the Veteran Affairs (VA) compared tele-psychiatry to usual care among depression patients. Patients in the tele-psychiatry group spent more resources on depression treatment as well as physical health specialty care, resulting in a significantly higher total outpatient cost. But another VA study (https://www.psychiatrist.com/jcp/psychotherapy/cost-effectiveness-of-psychotherapy-via-telehealth/) published in 2018 reached a different conclusion about tele-psychiatry vs. in-person care: an annual savings of $2,100 per patient. Given that mental health services are sensitive to the convenience and cost of receiving treatment, chances are high that digital mental health would lead to a higher total cost of care. Payers may hesitate to adopt digital mental health interventions without restrictions before innovators can prove with rigor that digital interventions can not only improve patient outcomes but also reduce total healthcare costs. Increased service utilization may partially offset the savings generated from improved outcomes and efficiency. From a payer’s perspective, the ideal situation is to improve patient outcomes and lower healthcare costs. One key benefit of clinician-led digital interventions is that they generate savings from reduced patient travel, but these savings do not accrue to payers. Digital interventions have been shown to improve patient outcomes, but service volume may increase at the same time. Unless the cost per service session decreases sufficiently to offset the increased volume, the total spending will increase, offsetting the efficiency gain partially or completely. But, what can we do to generate savings for payers? Finding the right payment arrangement and improving efficiency is the way out of this predicament. 1. Leverage value-based contracting and be a solution to payers. If we put ourselves in the shoes of a payer, reimbursing digital interventions on a fee-for-service basis involves a considerable risk of overspending because of the uncertainty in volume increases. One way to solve this is to lower the charge per service session to the extent that a payer would not perceive an excess risk of overspending. For example, innovators can set a price for using mental health apps and another for clinician-led digital interventions. This approach would give rise to several issues. Payers would still consider fees for mental health apps as additional spending. Innovators will have to figure out how low a unit price they should charge for clinician-led digital interventions. Clinicians are unlikely to lower their prices. A better arrangement is to offer a solution to payers, promising to deliver a specific level of outcome and bearing the risk of over-utilization. This would allow innovators to leverage technology, improve efficiency (more on this below), and build a competitive advantage. 2. Leverage technology and facilitate clinicians to practice at the top of their licenses to improve efficiency. Optimal results were observed in research studies when mental health apps are used under the guidance of clinicians, i.e., a blended approach. To best utilize resources, clinicians should practice at the top of their licenses. For example, doctoral-level therapists can delegate tasks to master’s-level ones, unlicensed personnel, or mental health apps, and supervise as appropriate. This would allow a doctoral-level therapist to maximize the size of her patient panel. Note that such an approach to organizing care is difficult, if not impossible, to implement in a fee-for-service setting because of misaligned incentives. And a patient risk stratification and treatment assignment system is needed to determine when a patient can achieve desired outcome improvements using mental health apps only (with or without the support of unlicensed personnel), clinician-led digital interventions only, or a combination of both. Of course, mental health apps can be used to screen mental illnesses, monitor patient symptoms, and collect timely data as well. Equipped with a risk stratification system, innovators may focus on a specific sub-population with mental illnesses, among whom savings are more likely to occur. Kaiser Permanente’s integration of consumer-driven apps into its healthcare delivery system is a case in point (https://catalyst.nejm.org/doi/pdf/10.1056/CAT.20.0295). The organization started the integration in 2018. Clinicians can refer patients to mental health apps via its electronic health record system and provide guided support. They included Calm, Headspace, Whil, myStrength, SilverClound, and Thrive, among others to help patients reduce stress and anxiety, improve sleep, and conduct cognitive behavioral therapy. Takeaways Digital mental health has attracted a large amount of investment capital in the last several years, but payers are hesitating to reimburse such technologies, especially consumer-driven apps, likely due to a fear of potential over-utilization. For innovators, the way out of this predicament is to provide a solution to payers. They can leverage technology, facilitate clinicians to practice at the top of their licenses, and utilize value-based contracting to address the challenge. Nonetheless, rigorous research is urgently needed to confirm if a comprehensive digital mental health solution improves outcomes and generates savings in the meantime. — Let us know the topics of your interest (support@AnalyticaNow.net (mailto:support@AnalyticaNow.net)). We would love to cover them. The article is provided by Analytica Now (https://analyticanow.net/), a company specializing in health analytics, economics, and policy. Thank you for being part of our community! 🎉 This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

3. 

   28 Jul 2022

   Why Did New York City’s $30-Million Mental Health Program Fail?

   In July 2015, the first lady of New York City - Chirlane McGray – announced (https://www1.nyc.gov/office-of-the-mayor/news/527-15/mayor-s-fund-advance-new-york-city-corporation-national-community-service-announce) a 5-year Connections-to-Care (C2C) program that aimed to transform mental health service delivery to low-income populations. It had a budget of $30 million, sponsored by the Mayor’s Fund, the federal Social Innovation Fund, private foundations, and service partners. It became part of the $850-million ThriveNYC initiative later that year. The program’s goal (https://www.rand.org/pubs/research_reports/RR3083.html) was to improve access to mental health services and treatment outcomes among the low-income populations served by community-based organizations (CBO), such as out-of-school youth, unemployed adults, expectant parents, caregivers of young children, homeless individuals, and immigrants. Given the shortage of mental health providers in New York City, the program was to train CBO staff in four mental health skills – mental health screening, mental health first aid, motivational interviewing, and psycho-education – and connect individuals to professional mental health providers as needed. The core idea behind this is called “task shifting.” That is, specialists (e.g., psychiatrists, psychologists, and social workers) would train and supervise lay persons. In turn, these trained individuals could then deploy basic skills learned and help their clients in need of mental health services. Under the C2C program, these lay persons included various types of CBO staff members, including CBO service providers, case managers, administrative assistants, security guards, and supervisors. However, after all was said and done, a formal evaluation (https://www.rand.org/pubs/research_reports/RR3083.html) completed in 2020 (disclosure: I was on the evaluation team) shows that overall, the program did not increase access to professional mental health services, nor did it improve mental health symptoms. Nonetheless, among some subgroups, the program was associated with a small or medium effect on reduced symptoms. But we should be cautious in interpreting the findings about subgroups because the more statistical tests we conduct, the more likely we get false positive findings. So the question is, Why didn’t the program work out as expected? Perspectives and insights you won't be able to find in other venues. The primary culprit is that the program was not designed correctly. There are two major categories of barriers (https://www.rand.org/pubs/research_reports/RR3083.html) to access to mental health services: logistical barriers and stigma-related ones. Logistical barriers include things like health insurance, cost-sharing, lack of transportation, provider availability, and lack of providers who speak an individual’s language. Also, patients may have concerns over privacy and other consequences and are afraid of others finding out they are receiving mental health services. Unfortunately, the C2C program was not designed to fully address these barriers. It mainly targeted the “provider availability” aspect of the problem. Presumably, individuals receiving CBO services would trust their staff and be less concerned about the stigma, but the evaluation results do not support this. Also, trained CBO staff did refer individuals with potential needs to professional mental health providers; for some reason, no differential improvements in access were observed when compared to non-intervention CBOs. There are several other plausible explanations, although they are less important than the flawed program design. 1. Task shifting may not work in the U.S. When the program was launched, there was little evidence that task shifting would work in the U.S. setting. However, the concept of task shifting (https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(11)61093-3/fulltext) in mental health services had been well established in developing countries. Many studies, including a number of randomized clinical trials, showed that primary care doctors, nurses, health workers, or other non-mental health medical staff were trained and supervised by psychiatrists or psychologists and achieved significant improvements in patient and caregiver outcomes. Although more evidence is needed, it is possible that the task-shifting approach does not work in the U.S., leading to the program’s failure. 2. The program could have been implemented better. There were many challenges in the first two program years. CBOs had to invest considerable time and resources to learn and integrate the four skills into their routine services. The launch period lasted for more than a year. However, data suggests that CBOs exceeded the expectation in terms of the number of staff members trained and clients served. The program was also well received by CBO staff and mental health providers who provided training and supervision. In addition, more than 80 percent of referred individuals had the first appointment with a professional mental health provider, much higher than the rates of other mental health interventions. Again, it is possible but unlikely that bad implementation has caused the ineffectiveness of the program. 3. The non-intervention CBOs selected for the evaluation were not ideal. The program was evaluated during a period when the City was implementing other mental health interventions as part of its $850-million initiative. For example, many community organizations were trained in mental health first aid. The Mayor’s Fund also launched a city-wide public awareness campaign to reduce the stigma associated with mental health services. However, other interventions were much less intensive than C2C. Even if all non-intervention CBOs were affected by other interventions, we would expect to see some program impact. Find this article helpful? Why not share it with ONE person you know? Finally, while it is normal to fail when testing a new approach, the City could have scaled back the program’s scope. We all agree that trial and error is part of the problem-solving process. So why should we make a big deal out of this failure? One thing the City could have done differently is to scale back the scope of the program. A $30-million project is not small by any measure, especially given that the program’s effectiveness was unknown at the time of its launch. The whole ThriveNYC initiative to strengthen mental health cost $850 million. Was it because of political considerations? This, of course, is a wild guess. Takeaways New York City spent $30 million to test the task-shifting approach to improve access to and outcomes of mental health, but to no avail. The failure is primarily due to flaws in the program design. Nevertheless, the City could have spent less on the program. Perspectives and insights you won’t be able to find in other venues. — Let us know the topics of your interest (support@AnalyticaNow.net (mailto:support@AnalyticaNow.net)). We would love to cover them. The article is provided by Analytica Now (https://analyticanow.net/), a company specializing in health analytics, economics, and policy. Thank you for being part of our community! 🎉 This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

4. 

   12 Jul 2022

   Podcast #7. Great Disappointment: Some Policymakers Ignore Basic Economics in Drafting Prescription Drug Pricing Policies

   In this episode, we discuss why some policymakers ignore basic economic principles in crafting prescription drug pricing policies. Medicare drug price negotiation, if implemented, would reduce investment in innovation, especially in drugs for Medicare beneficiaries. 00:00 Introduction 02:05 How R&D investment decisions are made 03:35 What academic research says 05:08 Summary We strive to translate scientific findings into plain language to answer challenging healthcare questions of our time. Our unique perspectives and insights are hard to find from other venues. You can find our articles here: https://hotbutton.substack.com Let us know the topics of your interest. We would love to cover them. Thank you! The video is provided by Analytica Now, a company specializing in health analytics, economics, and policy. https://analyticanow.net This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

5. 

   6 Jul 2022

   Podcast #6. Regulating Pharmacy Benefit Managers’ Rebate Practices: Are We Barking Up the Wrong Tree?

   In this episode, we discuss why regulating PBMs’ rebate practices will not shift rebate benefits from PBMs to payers or consumers, nor will it bend the cost curve. On the contrary, prohibiting rebates or fees linked to list prices and volume would increase prescription drug spending. See below why that is the case. 00:00 Introduction 03:03 What does a PBM do? 04:15 How do PBMs make money? 05:39 How much value do PBMs generate for the society? 06:55 Why regulating PBM rebate practices will not work? 11:06 What can we do to address the public's concerns then? 13:35 Summary We strive to translate scientific findings into plain language to answer challenging healthcare questions of our time. Our unique perspectives and insights are hard to find from other venues. You can find our articles here: https://hotbutton.substack.com Let us know the topics of your interest. We would love to cover them. Thank you! The video is provided by Analytica Now, a company specializing in health analytics, economics, and policy. https://analyticanow.net This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

6. 

   22 Jun 2022

   Podcast #5. Employers Investing in a RosenCare-Like Model Could Generate Savings

   In this episode, we explain why replicating the exact RosenCare delivery model and its savings requires several conditions. The model is certainly not for every employer, but prior research shows that adopting some variants of the model elements could help many employers generate savings and gain a competitive advantage in the labor market. 00:00 Introduction 01:47 Why RosenCare has not been widely adopted; it is not for everyone 06:49 Adopting some variants of the model elements can generate savings for many employers 09:54 Summary We strive to translate scientific findings into plain language to answer challenging healthcare questions of our time. Our unique perspectives and insights are hard to find from other venues. You can find our articles here: https://hotbutton.substack.com Let us know the topics of your interest. We would love to cover them. Thank you! The video is provided by Analytica Now, a company specializing in health analytics, economics, and policy. https://analyticanow.net This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

7. 

   15 Jun 2022

   Podcast #4. A Tale of Two Employer-Based Healthcare Models: RosenCare vs. Haven

   In this episode, we compare and contrast two different employer-based healthcare delivery model. We explain why one has a spectacular run for 30 years while the other failed in just 3 years. The drivers behind the incredible success of RosenCare are urgently needed in our healthcare system to reach the triple aim: better care, better health, and lower costs. 00:00 Introduction 00:28 RosenCare 01:49 Haven Healthcare 05:42 More on RosenCare 08:04 Why on succeeded while the other failed 15:19 Summary We strive to translate scientific findings into plain language to answer challenging healthcare questions of our time. Our unique perspectives and insights are hard to find from other venues. You can find our articles here: https://hotbutton.substack.com Let us know the topics of your interest. We would love to cover them. Thank you! The video is provided by Analytica Now, a company specializing in health analytics, economics, and policy. https://analyticanow.net This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

8. 

   6 Jun 2022

   Podcast #3. Want to Prevent Mass Public Shootings? Ask the Right Questions First

   This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

9. 

   29 May 2022

   Podcast #2. First Monkeypox Genome Sequences Show the Current Outbreak Has a Single Origin

   This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

10. 

    29 May 2022

    Podcast #1. Published Evidence Suggests We Won’t Have a Monkeypox Pandemic

    This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hotbutton.substack.com (https://hotbutton.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

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