Navigating consumer needs is front and center for UnitedHealth's Rebecca Madsen.

The Patient Experience

Dr. Sachin Jain of SCAN Health's challenges health systems to ask this question when tackling the issue of diversity in the workforce.

Who's Not in the Room?

Our popular podcast is back, featuring Blessing Health's Rose Ghattas, R.N.

Data Book Returns!

Findings of a new study suggest the use of machine learning assistance to prioritize the evaluation of patients with undiagnosed diseases is feasible and may increase the number of applications processed during a given time.

Isaac Kohane, M.D., Ph.D., and a team of investigators hope the findings create discussion around the current practices of automating referral decisions in the broader context of healthcare, which could save time and money for hospitals and health systems.

Kohane and his colleague, Hadi Amiri, Ph.D., developed computational models to effectively predict admission outcomes for applicants seeking Undiagnosed Diseases Network (UDN) evaluation. Further, they ranked the applications based on the likelihood of patient admission to the UDN.

Inclusion criteria were that the applicant should have a condition that was undiagnosed despite evaluation by a healthcare professional and had at least one objective finding pertaining the phenotype for which the application was submitted. Applications in the data set included an application form containing demographic characteristic information; an official referral letter signed by a provider summarizing the applicant’s medical problems, previous diagnoses, treatments, and medications; application submission date; application review date; and the outcome of the application.

The investigators split the data set into training (80%), validation (10%), and test (10%) categories for evaluation. They then developed a logistic regression classifier and used a grid search to optimize its hyperparameters using validation data. The classifier was trained using features obtained or extracted from application materials, including “baseline” features from patient demographic information (normalized age at time of the application, age at disease onset, disease duration, and number of prior UDN visits).

Kohane and Amiri used the confidence score of the logistic classifier to rank applications based on their likelihood of acceptance. To get the confidence score, the team conducted 

-fold cross-validation experiments with the UDN data set and stored confidence scores on test instances for final ranking. They used UDN’s review session frequency and number of applications that could be reviewed in each session to measure the mean application process time from the ranked list of applications. The team considered four approaches to generate ranked lists, including the current processing order at the UDN, first-in-first-out queue, classifier ranking, and accepted-first ranking.

Overall, the accepted cohort was significantly younger (mean age at application, 19.7 years old vs 36.5 years old) and had earlier onset of disease (mean age at symptom onset, 10.8 years old vs 28.4 years old) than those who were not accepted. The duration of the disease and number of prior UDN site visits in both groups were similar. Application processing time was significantly longer for applications that were not accepted (3.29 vs 4.73 months). A large number of applications in both groups were for neurologic (47.6% and 34.1%) and musculoskeletal symptoms (12.5% and 9.6%), while few applications were for gynecologic (.2% and .2%) or toxicologic (0% and .4%) symptoms.

The investigators found the best classifier had a sensitivity of .843, a specificity of .738, and an area under the receiver operating characteristic curve of .844 for predicting admission outcomes among 1,212 accepted and 1,210 not accepted applications. The classifier was able to decrease the mean UDN processing time for accepted applications from 3.29 months to 1.05 months — a 68% improvement — by ordering applications based on their likelihood of acceptance.

The system may assist clinical evaluators to distinguish, prioritize, and accelerate admission to the UDN for patients who have undiagnosed diseases. Accelerating the process could improve the diagnostic journeys for such patients and be a model for automation of triaging or referral for other resource-constrained applications. Further, shorter turnaround time could reduce the overall cost of diagnosis because the longer it takes to accept patients, the more diagnostic routes are likely to be sought.

Machine Learning of Patient Characteristics to Predict Admission Outcomes in the Undiagnosed Diseases Network

Articles

The machine-learning model could save time and healthcare costs. 

Machine-Learning Model Helps Prioritize Evaluation of Patients With Undiagnosed Diseases

Stephan Herron, CEO and President, Scriptel Corporation

There might not be a more wasteful practice than printing a form — especially a multi-page one — for the sole purpose of getting a signature. This is especially true of healthcare organizations that are using an electronic health record (EHR) to reduce paper and ensure a complete, clinician-accessible patient record.

A recent report by The Center for American Progress 

 that 14% of all U.S. healthcare expenditures are administrative, while the McKinsey Global Institute 

 more than $90 billion is spent on inefficient and redundant administrative practices in healthcare per year.

For many healthcare executives, peripherals aren’t always top of mind. However, they are a major consideration during an EHR implementation. That was the case at University of Illinois Hospital and Health Sciences System (UI Health), where more than 10 peripherals needed to change throughout numerous facilities, including signature pads.

UI Health, which includes a 462-bed tertiary-care hospital serving more than 135,000 patients per year, 21 outpatient clinics, 14 federally qualified health centers, and seven University of Illinois at Chicago health science colleges, began implementing Epic’s EHR in 2019.

Knowing that just about every signature pad in the health system would need to change as part of the Epic implementation, Andrew Mosio, director of technology and service delivery at the Chicago-area health system, began evaluating options. Ultimately, 

 that received positive IT and user feedback.

Hospital environments are extraordinarily tough on small peripherals like signature pads. So, one of the many tests Mosio and his team performed on the vendor’s units was throwing them on the ground. After all, signature pads need to be able to take a lot of abuse in the clinical setting.

The units under consideration came through the tests with flying colors — proving extremely durable and 100% plug and play. Mosio, who has been with UI Health’s IT department for almost nine years, said it was the peripheral they spent the least amount of time on and the only one that caused no problems during and after the Epic go-live.

Today, there are just under 1,500 signature pads deployed across the UI Health system. In addition to use at patient check-in, they’re in all ambulatory clinical settings and hospital departments.

The goal of Mosio’s team was to eliminate paper signatures in favor of capitalizing on Epic’s eSignature API, given the EHR vendor’s strong commitment to electronic data capture. Anywhere signatures were needed for acknowledgement, they’ve deployed signature pads. Mosio and his team were extremely satisfied with the support they received from 

 during testing and noted they received no user complaints about the units during the rollout or since.

Electronic signature pads check all the boxes when it comes to saving money and reducing paper waste, allowing hospitals, like UI Health, to purchase fewer printers and less paper and toner while saving clerical staff considerable time waiting for documents to print and filing or scanning them once signed.

 is Chief Executive Officer and President of Scriptel Corporation, a leading developer of eSignature and signature capture technology. 

Electronic signature pads save money and reduce paper waste at health systems.

How One Chicago-Area Health System Eliminated Paper Signatures

It is important to maintain appropriate healthcare staffing to provide a safe work environment for healthcare personnel as well as safe patient care. Because of this, and potential shortages due to coronavirus disease 2019 (COVID-19), the Centers for Disease Control and Prevention (CDC) updated a guidance to address staffing shortages at healthcare facilities.

New contingency strategies would allow asymptomatic providers who have had a higher-risk exposure to SARS-CoV-2 but are not known to be infected to shorten their duration of work restriction. Further, CDC updated to the guidance to allow asymptomatic fully vaccinated providers who have had a higher-risk exposure to SARS-CoV-2 but are not known to be infected to continue to work onsite throughout their 14-day post-exposure period.

In the guidance, CDC notes the need for healthcare facilities to understand their staffing needs and the minimum number of staff needed to provide both safe work environment and safe care for patients. The agency suggests healthcare facilities be in communication with local healthcare coalitions, federal, state, and local public health partners to identify additional healthcare providers when needed.

Contingency capacity strategies were implemented by CDC, so if staffing shortages are anticipated, healthcare facilities and employers can prepare to mitigate the problem. For one, CDC recommends adjusting staff schedules, hiring additional healthcare providers, and rotating healthcare providers to positions that support patient care activities. All non-essential procedures and visits should be cancelled, and healthcare providers should be shifted to work in areas to support other patient care activities in the facility. The facilities must ensure the providers are appropriately trained to work in new areas. Additional providers should also be identified to work in the facility and, if appropriate, request providers postpone elective time off from work.

It could also be beneficial to develop regional plans to find designated healthcare facilities or alternate care sites with adequate staffing to care for those with COVID-19.

What’s more, facilities should consider allowing asymptomatic providers who have had a higher-risk exposure to SARS-CoV-2 but are not known to be infected to shorten their duration of work restriction. Shortening the duration of work restriction might result in additional transmission risks, however. Those vaccinated should be prioritized to first shorten their duration of work restriction, then unvaccinated workers.

If staffing shortages continue despite mitigation strategies, CDC recommends as a last resort to consider allowing healthcare providers with suspected or confirmed COVID-19 infection who are well enough and willing to work but have not met all 

 to work. To determine which providers could be allowed to work, consider the type of shortages that need to be addressed and where the individual provider is in the course of their illness, along with symptoms and the degree of interaction with patients and other providers in the facility.

The updated guidance focuses on asymptomatic providers who are exposed to COVID-19.

CDC Updates Guidance on COVID-19 HCP Shortages

PursueCare and Herren Project today announced a partnership to enhance the accessibility of substance use disorder treatment services.

Through the partnership, PursueCare, a telehealth addiction treatment service, and Herren Project, a national addiction nonprofit organization, will provide thousands of patients access to virtual treatment for substance use disorder using PursueCare’s telehealth platform. Patients will benefit from Herren Project’s free support, online events, and tailored resources.

"Now more than ever, people need evidence-based and accessible treatment options that meet them where they are, and help them to reduce risk of harm," Nicholas Mercadante, founder and CEO of PursueCare, said. "We are proud to partner with Herren Project and support initiatives that provide better options for treatment without judgment. We believe this will improve their program members' prospects for getting care when it is needed, no matter what barriers they may have experienced in the past.”

PursueCare’s platform helps patients get access to medication like buprenorphine, psychiatry, and counseling from licensed providers through live video on a smartphone or tablet. Patients using the application can meet with their provider whenever needed to complete their individualized recovery program at home on their own time. A majority of patients start treatment within the first 24 hours of contact and Medicaid, Medicare, and other private insurances are accepted by the company. There are also other financing options available for those without insurance, such as monthly or per-session self-pay.

Seeking professional help for substance use disorder can often come with feelings of stigma for patients. And during COVID-19, use of telehealth services has skyrocketed. Now, patients have less barriers to access care for this condition, which can improve outcomes if adhered to.

"Access to services for substance use disorder and mental health is more critical than ever. With the increase in overdose deaths nationally, we knew it was crucial to find a quality partner who could provide virtual at-home resources for our clients to have a chance at recovery," Kevin Mikolazyk, executive director of Herren Project, said.

The partnership may reduce barriers to care for patients with substance use disorder.

PursueCare and Herren Project Partner to Improve Access to Telehealth for Substance Use Disorder

Approximately 30% of health systems and hospitals are unable to manage their revenue cycle automation efforts without at least two vendors, according to the findings of a recent survey by Alpha Health.

What’s more, 30% of health systems and hospitals, of which, more than 76% were large organizations with $1 billion or more in net patient revenues, built internal automation teams.

The survey, conducted through the Healthcare Financial Management Association’s Pulse Survey Program, was taken between May 19 and June 22, 2020 by 587 chief financial officers and revenue cycle leaders at health systems across the U.S.

The process of automating revenue cycle tasks typically includes observing and documenting workflows, programming the technology to perform the work as documented, and maintaining the solution as inputs and variables in specific processes change. Business process consultants generally handle the first step and work with a technology vendor to manage the second and third steps. Because maintenance can require internal revenue cycle staff to coordinate with business process consultants and technology vendors, many large health systems invest in their own automation teams.

“Many automation technologies, such as robotic process automation, were originally developed for other industries and purposes. Trying to retrofit these solutions to healthcare revenue cycle operations can result in unnecessarily complex deployment processes. This also requires significant investments in maintenance resources, whether those be multiple vendors or entirely new internal automation teams,” Ben Beadle-Ryby, co-founder and vice president of operations at Alpha Health, said in 

When survey respondents were asked which best described how many outside consulting firms and vendors they used to automate revenue cycle operations, 38.5% said they used one vendor who could do all three automation steps of the process. Just more than 30% (31.5%) said they did not use external consultants or vendors and instead had an internal team dedicated to automation who handled all steps of the automation process. Less than 20% (19.6%) used two vendors but had one vendor who handled multiple parts of the process.

The survey also revealed larger organizations were more likely to use more vendors than smaller organizations.

Revenue cycle automation is looked at to save time, speed up claims processes, decrease denials, and collect payment faster. 

Automation technologies for healthcare revenue cycle operations may be unnecessarily complex to deploy.

Health Systems Need Help Managing Revenue Cycle Automation

Heart rate variability metrics collected from an Apple Watch can predict the diagnosis of coronavirus disease 2019 (COVID-19) and identify COVID-19-related symptoms.

The preliminary results, completed on a group of healthcare workers, identified a novel, easily measured physiological metric that could aid in the tracking and identification of COVID-19 infections.

Robert Hirten, M.D., and investigators of the study followed healthcare workers in the Mount Sinai Health System as they used the wearable and a custom Warrior Watch Study app to see if the data collected would help identify and predict the disease and related symptoms.

The primary goal of the study was to determine whether changes in heart rate variability could differentiate participants who were infected and not infected with COVID-19. Another study goal was to observe if changes in heart rate variability could predict the development of COVID-19 infection prior to diagnosis by a PCR test.

Participants in the study were at least 18 years old, were current employees in the Mount Sinai Health System, had an iPhone Series 6 or higher, and had or were willing to wear an Apple Watch Series 4 or higher. The investigators collected daily symptoms including fever and chills, feeling tired or weak, body aches, dry cough, sneezing, runny nose, diarrhea, sore throat, headache, shortness of breath, loss of smell or taste, itchy eyes, none, or other.

All participants downloaded the Warrior Watch app to complete eligibility questionnaires and sign a consent form. The app included daily survey questions which captured COVID-19-related symptoms, symptom severity, COVID-19 nasal swab PCR test results, serum antibody test results, and daily patient care-related exposure. The Apple Watch was worn for a minimum of eight hours per day.

The wearable was connected through Bluetooth to the participant’s iPhone. The watch had an enhance photoplethysmogram optical heart sensor that combined a green light-emitting diode paired with a light-sensitive photodiode generating time series peaks that correlated with the magnitude of change in the green light generated from each heartbeat. Heart rate variability was calculated from the time difference between heartbeats, classified as the interbeat interval. The Apple Watch and the Apple Health app automatically calculated heart rate variability using the standard deviation of the interbeat interval or normal sinus beats.

The data collected through the watch were characterized by a circadian pattern, a sparse sampling over a 24-hour period, and nonuniform timing across days and participants.

Overall, the team enrolled 297 participants between April 29 and Sept. 29, 2020. The median age was 36 years old and a majority (69.4%) were women. Of those who participated, 6.7% reported having a positive PCR test prior to enrollment and 9.4% had a positive blood antibody test prior to the study. There was a median follow-up of 42 days and a median of 28 heart rate variability samples were obtained for each participant.

The mean amplitude of the circadian pattern of the standard deviation of the interbeat interval of normal sinus beats differed between participants with and without COVID-19 (

=.006). The amplitude of the pattern differed between participants during the seven days before and the seven days after a COVID-19 diagnosis compared to the same metric during uninfected time periods (

=.01). There were significant changes in the mean amplitude of the pattern of the standard deviation of the interbeat interval of normal sinus beats between the first day of reporting relating symptoms compared to all other symptom-free days (

Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study

Data collected on the Apple Watch may help identify COVID-19. 

Apple Watch Data Help Predict, Identify COVID-19

A virtually enabled biorepository and electronic health record (EHR)-embedded, scalable cohort for precision medicine (VESPRE) demonstrated feasible digital screening, successful enrollment, biologic sampling, and lower costs compared with a traditional study design.

Study findings indicated VESPRE may be scalable across patients, centers, and laboratories at low incremental cost and burden.

Kimberley DeMerle, M.D., and a team of investigators developed VESPRE and compared the feasibility, enrollment, and costs compared with those of a traditional study design in acute care. The goals of VESPRE were to create a digital tool for patient screening and enrollment embedded in the EHR, to develop automated sample collection for a virtually enabled biorepository of waste tissue (remnant blood and urine specimens), and to develop a thin-client software that ensured adequate data integration, security, curation, and scalability across multiple hospitals. To do this, the team combined three components: existing tools of EHR sepsis screening, EHR data for clinical research, and remnant sample analyses.

A key design of the study was to seek a waiver of consent for VESPRE, reduce time and cost, and allow rapid enrollment with minimal patient risk. Patient screening, enrollment, and sample acquisition were done prospectively while daily screening alerts were created through a secure communication that reported potentially eligible encounters to the study team. Data collected from the EHR included patient demographics along with intensive care unit admission, hospital and intensive care unit length of stay, in-hospital mortality, and 90-day mortality.

Eligible patients were at least 18 years old who met criteria for sepsis within six hours of presenting at the emergency department. Sepsis was defined as sepsis-3. To identify sepsis-3, the team developed a digital alert to flag patients with location in the enrolling emergency department, at least 18 years old, blood cultures obtained in the first six hours after arrival, and antibiotics administered in the first six hours.

DeMerle and the team collected remnant blood and urine samples in the VESPRE biorepository to maximize the number of samples and minimize cost and time. The biorepository had embedded electronic alerts that triggered the research staff to collect samples.

The cost of VESPRE was compared with a prehospital cohort study and a hypothetical prospective cohort among hospitalized patients.

There was a total of 1,027 patients enrolled in the study and 549 were included in the proof-of-concept analysis (56% men; median age, 59 years old). VESPRE collected nearly 13,000 remnant blood and urine samples and showed adequate feasibility for clinical, biomarker, and microbiome analyses. The total cost was approximately $39 per enrolled patient compared to $239 per patient for a traditional cohort study.

To encourage precision medicine in acute care, an infrastructure embedded in the EHR that created a virtually enabled biorepository proved to be feasible and less costly for time-sensitive conditions.

Feasibility of Embedding a Scalable, Virtually Enabled Biorepository in the Electronic Health Record for Precision Medicine

The total cost is approximately $39 per enrolled patient compared to $239 per patient for a traditional cohort study.

Virtually Enabled Biorepository in EHR Feasible, Cost Effective

Even before the pandemic, suicide had become a public health concern. According to 

, suicide was the 10thleading cause of death in the United States in 2018, with the 48,344 deaths more than doubling the number of homicides. Suicide is also the second-leading cause of death among those ages 10 to 34, and the fourth-leading cause among those 35 to 54.

Research shows that an attempt at suicide 

 of a completed suicide, even if patients 

 more dangerous methods. Amid the rising death toll, public health experts are investigating interventions that can begin with patients after they leave the emergency room. But less is known about the success of these interventions from the patient’s perspective.

 from authors at the Lausanne University Hospital in Switzerland shows why prevention can be so difficult—interviews with patients who had attempted suicide showed the same intervention yielded vastly different reactions. The latest results follow publication of the original study, which 

 of adding nurse practitioner check-in calls for a three-month period and a family intervention. Some patients refused the intervention, and others who accepted it refused the follow-up calls discussed in the most recent study, which authors said highlight the challenge of working with patients.

Respondents reported a range of reactions: Some thought the check-in calls from a nurse practitioner were very helpful, while others thought they came too often. Others were upset when the calls ceased. The authors wrote that some participants “deplored that too much attention was being paid to the suicide attempt, referring for instance to the fact that this act could be considered as a ‘personal choice.’”

“Multiple post-suicide attempt interventions have been studied but they followed almost always a ‘one size fits all’ approach, namely same intervention for everyone,” the authors wrote. “Our results seem to indicate, rather, that intervention needs are specific to individuals.”

Much of the paper features patients’ own voices, including this statement that sums up the authors’ call for personalized care after a suicide attempt: “It is a necessity but the call shouldn’t be too frequent; there should be an agreement with the person on how many times a week and at what schedule.”

Other patients blanched at the number of people involved in their care, especially if they were already being seen by a psychiatrist. Said one, “My doctor was already calling me and watching how I was doing, so it [the phone calls included in the intervention] kind of oppressed me actually.”

A second part of the original intervention, coming up with a joint crisis plan, brought mixed reviews. Many respondents said the timing of the planning process—while still in emergency care—occurred when patients admitted they were too aggressive for the process to be useful.

But the idea of establishing a relationship with a case manager, the person charged with developing the plan, had merit for some.

Patients who are being treated after a suicide attempt might be offered the chance to customize their aftercare, the authors said. Quality of encounters matter, and for some, a face-to-face follow-up may be preferable to phone calls.

“Our results seem therefore to speak for such a ‘one-on-one’ intervention,” they wrote. “Indeed, such an approach could take into account how patients understand their suicide attempt and how they plan to recover from it … by avoiding overcare when patients prefer to rely on other resources.”

A study interviewed patients in a study of a post-suicide intervention and received a range of answers on how it was received.

Interviews After Suicide Attempts Show There’s No “One Size Fits All” to Care

Coronavirus disease 2019 (COVID-19) has exposed weaknesses in the healthcare delivery system and the glaring inequities that result, a group of experts from the front lines of the pandemic said this week during Academy Health’s Datapalooza and National Health Policy Conference.

Academy Health President and CEO Lisa Simpson, M.B., B.Ch., MPH, led the discussion that featured John Brownstein, Ph.D., chief innovation officer at Boston Children’s Hospital; Shereef Elnahal, M.D., M.B.A., president and CEO at 

; Brian Caveney, M.D., J.D., M.P.H., executive vice president, president for diagnostics and chief medical officer for 

 and Kara Odom Walker, M.D., M.P.H., MSHS, senior vice president and chief population health officer, 

The mobilization that has occurred to rein in COVID-19, including the data systems developed to track the disease and develop a vaccine, must not be forgotten when the pandemic ends, but instead must be deployed to tackle the health and economic disparities that have led to higher infection rates and more loss of life among minorities, the group said.

It won’t be easy, because the inequities are so deeply rooted, Walker said.

“Many of us are just trying to figure out how we embrace this moment to undo some of the underfunding by government,” she said. “We can't undo 60 or 70 years of a lack of investment in Black and brown communities, just by elevating and talking about it. We actually need to put money into those efforts, that is going to take time.”

Caveney said the pandemic has pressed every part of the health system to its limits, including the global supply chains that provide consumables, equipment, reagents and primers, and, as many saw early on, personal protective equipment (PPE).

“The gloves, masks, everything else—all the different components for clinical and drug research” were in short supply, he said. Few appreciate the global of supply chains, or that during the first days of the pandemic, “Some very specific border closures—for both political and health reasons—massively disrupted the supply chain and the ability to move those goods around the world.”

Thus, healthcare delivery relied not only on good clinical care but also on dealing effectively with agencies such as Homeland Security or the the Transportation Security Administration. Caveney recalled one episode that derailed testing early on: “Most of you will remember that the first epicenter outside China was near Milan, Italy. Well, it just so happens that by far the most important nasal pharyngeal swab manufacturer in the world, Copan, is just a few miles east of Milan, which was just down.”

This created the massive shortage of nasal swabs when COVID-19 testing was just ramping up. Business and emergency plans that called for redundancy suddenly became more important than ever. “We made a decision very early on that we needed to make sure we had many different labs all across the planet, but particularly across America,” Caveney said. This becomes important not just in a pandemic, but in events such as the winter storms that have gripped Southern states, knocking out power.

“We're diverting so many clinical specimens, not just for COVID, but for all of the other 5000 tests we do to our other labs,” he said. The United States needs to be more nimble at these types of logistics, “for whatever the world throws at us next, including the next pandemic.”

Just as the pandemic exposes the need for change, it has also propelled long overdue changes in areas such as telemedicine. “We’ve had a telemedicine program and efforts in digital health for so many years,” Brownstein said. “But it took this moment to bring all these stakeholders together—clinicians, researchers, business leaders, and we’ve seen an unprecedented level of innovation both within our system, but also on a global level.”

Hospitals, which he said “are not known for their agility,” were able to mobilize in novel ways: Brownstein’s own hospital has built a 

 that was deployed to identify “pain points,” showing where to increase testing capacity and implement contact tracing. Use of telemedicine has soared.

In the process, he said, “We’ve built what we think is the foundation and institutional muscle” for additional data gathering and healthcare delivery, including the leveraging of social media streams. “This is the starting point.”

There were many disappointments and frustrations in the public health arena early on, and information was lacking, Walker said. But she agreed that the ability to pull together a data infrastructure that ultimately guided the healthcare response was a bright spot.

“Ripple Effects” of Inequity Revealed

Walker, who previously served Delaware’s secretary of Health and Services, said the intersection of politics and public health was “pretty shocking and surprising to me, in that we had no ability to bring those two worlds together in a coordinated way as a nation, and certainly at the state level.”

It’s shocking, she said, that U.S. deaths from COVID-19 account for 20% of all such deaths worldwide—a far higher share than its population—because politics overwhelmed common sense, public health guidance. Elnahal agreed, saying anti-vaccination activists have targeted the communities of color that make up 80% of the population near his safety net hospital. It’s taken diligent work to move the vaccination acceptance rate from 40% to 60%.

“I can’t tell you how many times I’ve repeated, ‘Wash your hands, stay away from people, stay home,’” Walker said, and yet economic inequities meant some people could not stay home, because their front lines required them to show up if they were going to pay the rent. “The ripple effects were intense,” and that led to nursing home deaths “the inability to protect our most vulnerable.”

Overall, health systems should have been better prepared. One area where society has been least prepared, she said, “is around the outpouring around anti-racism and around our need to focus on equity.”

The issue of health disparities has been raised in a glaring way, but Walker questions whether the country is ready to deal with this issue in an ongoing way.

Like Walker, Elnahal served in state government as New Jersey’s health commissioner, and taking on disparities was already part of his portfolio before the pandemic. But with COVID-19, “The cracks in health equity essentially became earthquakes in our community.” As a hospital leader just a few months into the job, Elnahal confronted challenges even the veterans he worked with had not faced.

There were nursing-patient ratios like none anyone had seen, pharmacists who worried about running out of sedating medications for the ICU, and, echoing Caveney’s comments, the constant worry about running out of personal protective equipment—while bidding against the cash-rich hospitals that populate the New Jersey suburbs.

“We couldn’t help but notice that every single person in our hospital that was filled with COVID patients was a person of color, and we have a much more diverse community that we serve at baseline,” Elnahal said. “That was heartbreaking.”

Working with allies in the faith-based community to build trust in both COVID-19 testing and vaccination, while promoting social distancing and contact tracing, “has never been more important.”

Elnahal and other panelists said that if the health system and the pharmaceutical infrastructure can mobilize to get people tested and vaccinated, and develop data systems to track the disease, there’s no reason they should not be able to use this model to take on the other plagues of minority communities.

“What about late stage breast cancer in black women? What about colon cancer and rectal cancer and prostate cancer and black men? What about chronic disease and our communities?” Elnahal asked. “Where’s the will and the effort to do that? We have to make a promise and fulfill that promise to community—that are we begging for their trust at this point on the vaccine, because it impacts all of us—and we have to deliver on that.”

Like Walker, he said that to change outcomes for the long haul, data on health inequities must be put front and center in front of policy makers and health system leaders, “and everyone in between.”

Experts from the front lines of COVID-19 discuss how lessons learned could help close health disparities. 

Supply Chains, Data, Equity, and Trust: COVID-19 Reveals Healthcare Gaps

IBM is considering selling its Watson Health business unit, according to several media outlets including 

Reports indicate the tech giant is aiming to streamline IBM and become more competitive in cloud computing. The company is looking for alternatives for IBM Watson Health that may include a sale to a private-equity firm or industry player or a merger with a blank-check company, those familiar with the situation say.

IBM Watson Health currently employs artificial intelligence (AI) to help hospitals, insurers, and drug makers manage their data. The business unit was initially launched with the goal to expand into personalized medicine via DNA translation and the input of electronic health records. Watson Health, however, did not excel in the healthcare sector, partially due to physicians being hesitant to adopt AI technology, according to 

. The unit has roughly $1 billion in annual revenue though it is not currently profitable.

Watson Health’s brands include Merge Healthcare, which analyzes mammograms and MRIs, Phytel, which assists with patient communications, and Truven Health Analytics, which analyzes complex healthcare data.

IBM has been looking to boost its revenue share from hybrid-cloud software and services to let customers store data in private servers and on multiple public clouds. With its focus on cloud technology, new chief executive office Arvind Krishna said at the end of last year that he would spin off IBM’s managed infrastructure services unit into a separate publicly traded company. The unit is currently part of the Global Technology Services division and handles day-to-day infrastructure service operations such as managing client data centers and traditional information technology support for installing, repairing, and operating equipment.

The company is looking to focus on cloud technology. 