U.S. blows past coronavirus record with more than 70,000 new cases in one day

https://www.washingtonpost.com/nation/2020/07/17/coronavirus-live-updates-us/?utm_campaign=wp_post_most&utm_medium=email&utm_source=newsletter&wpisrc=nl_most

FirstFT: Today's top stories | Financial Times

There was a time in the United States when 40,000 coronavirus cases in a day seemed like an alarming milestone. That was less than three weeks ago.

Now, the number of new infections reported each day is reaching dizzying new heights. On Thursday, the daily U.S. caseload topped 70,000 for the first time, according to data tracked by The Washington Post.

Record numbers of covid-19 fatalities were reported in Florida, Texas and South Carolina on Thursday, and officials throughout the Sun Belt are worried that hospitals could soon reach a breaking point.

Here are some significant developments:

  • Masks are now mandatory in more than half of U.S. states — with the governors of Arkansas and Colorado the latest to issue face-covering orders. Major retailers phased in new mask policies, and Maryland Gov. Larry Hogan (R), chairman of the National Governors Association, said that masks should be mandated in states across the country.
  • Larry Fink, the chief executive of investment firm BlackRock, said that if states moving forward with reopening plans required masks, the economy would recover much sooner.
  • Atlanta Mayor Keisha Lance Bottoms (D) blasted Georgia’s Republican governor, Brian Kemp (R), for suing to stop block her city’s mask ordinance, accusing him of “putting politics over people.”
  • An unpublished report from the White House Coronavirus Task Force suggests that nearly 20 hard-hit states should enact tougher public health measures.
  • Real-time coronavirus tracking data temporarily disappeared from the Centers for Disease Control and Prevention’s website, sparking an outcry.
  • President Trump faces rising disapproval and widespread distrust on coronavirusaccording to a new Post-ABC poll.
  • India on Friday surpassed 1 million confirmed coronavirus cases, becoming the third country to cross that threshold, behind the United States and Brazil..

 

 

 

 

Disappearance of covid-19 data from CDC website spurs outcry

https://www.washingtonpost.com/health/2020/07/16/coronavirus-hospitalization-data-outcry/?utm_campaign=wp_main&utm_medium=social&utm_source=facebook&fbclid=IwAR2ONMOtMxy2LFUw0qKhDZwb1n5yFRv2oCTZlrr49_YpdO8WTzkSC90JjY0

Disappearance of covid-19 data from CDC website spurs outcry ...

Governors join calls for delay of administration plan to shift control from the CDC as Trump administration pledges to make data available to the public.

On the eve of a new coronavirus reporting system this week, data disappeared from a Centers for Disease Control and Prevention website as hospitals began filing information to a private contractor or their states instead. A day later, an outcry — including from other federal health officials — prompted the Trump administration to reinstate that dashboard and another daily CDC report on the pandemic.

And on Thursday, the nation’s governors joined the chorus of objections over the abruptness of the change to the reporting protocols for hospitals, asking the administration to delay the shift for 30 days. In a statement, the National Governors Association said hospitals need the time to learn a new system, as they continue to deal with this pandemic.

The governors also urged the administration to keep the information publicly available.

The disappearance of the real-time data from the CDC dashboard, which was taken down Tuesday night before resurfacing Thursday morning, was a ripple effect of the administration’s new hospital reporting protocol that took effect Wednesday, according to a federal health official who spoke on the condition of anonymity to discuss internal deliberations.

Without receiving the data firsthand, CDC officials were reluctant to maintain the dashboard — which shows the number of patients with covid-19, the disease caused by the virus, and hospital bed capacity — and took it down, the federal health official said. The CDC dashboard states that its information comes directly from hospitals and does not include data submitted to “other entities contracted by or within the federal government.” It also says the dashboard will not be updated after July 14.

The dashboard “was taken down in a fit of pique,” said Michael R. Caputo, the assistant secretary for public affairs at the Department of Health and Human Services. “The idea CDC scientists cannot rely upon their colleagues in the same department for data collection, or any other scientific work, is preposterous.”

This week, the CDC, the government’s premier public health agency whose medical epidemiologists analyze the hospital data, also stopped producing reports about trends in the pandemic that had gone twice a week to states, and six days a week to officials at multiple federal agencies. Adm. Brett Giroir, an assistant secretary in the HHS who oversees coronavirus testing, was unhappy that the CDC hospital report stopped Wednesday and Thursday mornings, according to the federal health official.

Caputo said that the administration’s goal is to maintain transparency, adding that conversations were still taking place between HHS officials and the CDC on a plan to keep producing the dashboard updates and the reports. “We expect a resolution,” he said.

Another HHS spokesperson said the CDC might create a new dashboard, based on a wider set of information.

During a conference call for journalists Thursday on coronavirus testing, Giroir did not acknowledge his displeasure with the reports’ discontinuation. But he said: “Those data are really critical to all of us. … I wake up in the morning and first thing I do, I look at the data. I look at midday. I look at it at night before I go to bed. … We drive the response based on that.”

The CDC site had been one of the few public sources of granular information about hospitalizations and ICU bed capacity. About 3,000 hospitals, or about 60 percent of U.S. hospitals, reported their data to the CDC’s system.

The president of the American Medical Association, Susan R. Bailey, spoke out Thursday on the uncertainties about access to data. “[W]e urge and expect that the scientists at the CDC will continue to have timely, comprehensive access to data critical to inform response efforts,” she said.

Governors, hospital officials and state health officers were given scant notice of the change in the reporting system. Two top administration health officials said in a letter to governors early this week that some hospitals were not complying with the previous protocols, suggesting that states might want to consider bringing in the National Guard to help gather the information. Hospital industry leaders vehemently protested that characterization, as well as the idea that they should be assisted by the National Guard in the midst of a pandemic.

HHS and CDC officials have said the protocol was changed to streamline reporting of data that is used, among other things, to determine the federal allocation of therapeutics, testing supplies and protective gear. Instead of reporting to the long-standing CDC system, hospitals must send data about covid-19 patients and other metrics to a recently hired federal contractor, called TeleTracking, or to their state health departments.

At least some state health departments that have been collecting data for their hospitals and sending it to Washington have already said the switch will make it impossible for them to continue, at least for now. The changed protocol includes a requirement that hospitals send several additional types of data that some state systems are not equipped to handle, state health officials said.

The Pennsylvania Department of Health sent a notice to hospitals Tuesday night saying that its platform was not ready to accommodate the new federal requirements, so that hospitals needed to report every day to both the state and to TeleTracking.

Charles L. Gischlar, spokesman for the Maryland Department of Health, said the reporting change “is a heavy lift for hospitals.”

The new system “exceeds the capacity of the current statewide system” to which hospitals had been reporting, he said, so the state no longer can send consolidated information to the federal government. As a result, he said in a statement, hospitals must provide data individually to the government.

 

 

 

 

The U.S. is way behind on coronavirus contact tracing. Here’s how we can catch up.

The U.S. is way behind on coronavirus contact tracing. Here’s how we can catch up.

The US is amassing an army of contact tracers to contain the covid ...

Get this: Vietnam, a country of 97 million people, has reported zero deaths from only 372 cases of coronavirus.

Theories abound about how they pulled it off. But public health experts chalk it up to swift action by the Vietnamese government, including contact tracing, mass testing, lockdowns, and compulsory wearing of masks.

Here, masks have become a political landmine. And despite President Trump claiming, “We have the greatest testing program anywhere in the world,” some states with surging infections have testing shortages—like Arizona.

But what about contact tracing, the process of calling potentially exposed people and persuading them to quarantine?

“I don’t think we’re doing very well,” said Dr. Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases, when asked in June about contact tracing nationwide. Most states haven’t even made public how fast or well they’re implementing the process, if at all.

Florida, the nation’s current No. 1 hotspot for the virus, is often failing to trace positive cases. This, despite the state spending over $27 million on a contract with Maximus, a company notorious for underbidding, understaffing, and performing poorly on government services contracts in multiple states.

Yet, there are bright spots elsewhere. California allocated 5 percent of staff across 90 state government departments to contact trace. North Carolina’s Wake County trained 110 librarians. In Massachusetts, counties have used state pandemic funds to hire more nurses.

There are three reasons why state and local governments should reassign public employees or hire new staff outright as the country—finally—ramps up contact tracing.

One, outsourcing what should be a public job to for-profit companies like Maximus reduces transparencylimits democratic decision-makinglowers service quality, and increases inequality, all while rarely saving public dollars. Public control is particularly important when it comes to contact tracing, which involves personal health data.

Two, this is a chance to begin to reverse decades of cuts to public health budgets, which have made the worst public health crisis in a century even worse. Almost a quarter of the local public health workforce has been let go since 2008. Federal spending on nondefense discretionary programs like public health is now at a historic low.

The Trump administration, as expected, is headed in the wrong direction. On Tuesday, it stripped the Centers for Disease Control and Prevention (CDC) of control over coronavirus data. State and local governments must do all they can to right the ship.

And three, contact tracing is an opportunity to chip away at systemic racism. Since World War II, public sector employment has helped equalize American society by offering workers of color stable, well-paid employment. The median wage earned by Black employees is significantly higher in the public sector than in private industries.

Privatizing public work like contact tracing contributes to racial and gender income disparities. Workers at federal call centers operated by Maximus, for example, are predominately women and people of color paid poverty wages as low as $10.80 an hour with unaffordable health care.

If #BlackLivesMatter—as many governors and mayors across the country have proclaimed in recent weeks—then contact tracing should be treated as what it is: a public good.

To catch up to other countries like Vietnam, the U.S. needs to get contact tracing right—and that means doing it with public workers.

 

 

 

 

White House tells hospitals to bypass CDC on COVID-19 data reporting

https://thehill.com/policy/healthcare/507321-white-house-tells-hospitals-to-bypass-cdc-on-covid-data-reporting?fbclid=IwAR2Q0n6LNYQa1p6rPQeRGUPi-54i8uTAyRxcmTcZXC6Q9mbVRZx3e1GH518

White House tells hospitals to bypass CDC on COVID-19 data ...

Hospitals will begin sending coronavirus-related information directly to the Department of Health and Human Services (HHS), not the Centers for Disease Control and Prevention (CDC), under new instructions from the Trump administration.

The move will take effect on Wednesday, according to a new guidance and FAQ document for hospitals and clinical labs quietly posted on the HHS website.

Previously, hospitals reported to the CDC’s National Healthcare Safety Network, which the agency describes as the nation’s most widely used health care-associated infection tracking system.

The CDC tracked information including how many beds are available, the number of ventilators available and how many COVID-19 patients the hospitals have.

Beginning Wednesday, hospitals will report the same data but will bypass the CDC and send it to HHS directly. 

According to HHS, the goal is to streamline data collection, which will be used to inform decisions at the federal level such as allocation of supplies, treatments and other resources.

But the move comes amid concerns that the White House has been sidelining the CDC and after Trump administration officials attacked Anthony Fauci, the nation’s top infectious disease expert and a member of the White House coronavirus task force.

 

 

Pandemic response complicated by public health agencies’ inability to receive data from hospitals

https://www.healthcaredive.com/news/pandemic-response-complicated-by-public-health-agencies-inability-to-recei/578663/

Dive Brief:

  • The biggest problem with electronic syndromic surveillance reporting isn’t that hospitals lack the capacity to send data — it’s that public health agencies lack the ability to receive it, according to a new report published in the Journal of the American Medical Informatics Association.
  • More than four in 10 U.S. hospitals say their local, state and federal public health agencies are unable to receive data electronically, reflecting a decade-long investment in health IT infrastructure on the private sector side without a concomitant investment from its federal partners, researchers found.
  • Hospitals in regions forecast to be some of the hardest hit from COVID-19 were more likely to say public health agencies were unable to receive health data electronically, implying areas of highest need were some of the least prepared to mount a coordinated, data-driven response going into the pandemic.

Dive Insight:

Effective pandemic response requires real-time, accurate data sharing between providers and public health agencies, allowing the government to track outbreaks and allocate resources as needed.

A lack of nationwide, interoperable reporting infrastructure has been one of the major criticisms of the Trump administration’s handling of the pandemic, which has infected almost 1.7 million and killed 99,000 people in the U.S. as of Wednesday.

CMS requires hospitals be able to electronically send and receive health information, including lab results and syndromic surveillance data, to and from public health agencies like their state’s department of health. For more than a decade, providers have funneled significant resources into their IT infrastructure due to a slurry of federal incentive programs, though EHR implementation remains piecemeal across the U.S. due to cost and other barriers.

The JAMIA study, one of the first looking at the state of health data reporting, analyzed 2018 American Hospital Association data to identify hospital-reported barriers to surveillance data reporting, and Harvard Global Health Institute data on the coronavirus pandemic’s projected impact on hospital capacity at the hospital referral region (HRR) level. Researchers assumed a 40% population infection rate over 12 months.

The group found 31 high-need HRRs, those in the top quartile of projected beds needed for COVID-19 patients, with more than half of the hospitals in the region saying the relevant public health agency couldn’t electronically receive data.

That suggests areas more likely to be overwhelmed by the pandemic had some of the least interoperable data-sharing capabilities going into it, hamstringing outbreak response.

Researchers found the most common barrier to data-sharing nationwide, reported by 41% of hospitals, was that public health agencies didn’t have the capacity to receive data electronically.

The next most common, reported by 32% of hospitals, was interface-related issues, such as costs or implementation complexity; followed by difficulty extracting data from the EHR (14% of hospitals reporting), different data standards (also 14%), hospitals lacking the capacity to send data (8%) and hospitals being unsure what public health agencies to send the data to (3%).

Researchers also found significant state variance in hospitals saying public health agencies couldn’t receive needed data electronically, running the gamut from 83% of hospitals saying so in Hawaii and Rhode Island to 40% in New Jersey and Virginia to none in Delaware.

Geographic variation is likely due to different funding priorities in different places, as some agencies may only be able to receive specific data elements or interface with a select number of EHRs. This spotty IT implementation results in a patchwork picture of disease progression across the U.S., though the Centers for Disease Control and Prevention is working to automate the COVID-19 reporting process.

The study does have some significant limitations. It’s a relatively one-sided portrayal of the issue, as researchers did not have access to data or survey results from public health agencies. And, since AHA survey results were from two years ago, the EHR landscape could have shifted since 2018.

However, researchers called upon policymakers to build up public health agencies’ IT capabilities, especially as states begin to reopen despite an increasingly likely resurgence of the virus in the fall.

“Policymakers should prioritize investment in public health IT infrastructure along with broader health system information technology for both long-term COVID-19 monitoring as well as future pandemic preparedness,” authors A Jay Holmgren, a doctoral candidate at Harvard Business School; Nate Apathy, a doctoral candidate at Indiana University’s Richard M. Fairbanks School of Public Health; and Julia Adler-Milstein, a professor at University of San Francisco Department of Medicine, wrote.

 

 

 

COVID-19 and the End of Individualism

https://www.project-syndicate.org/commentary/covid19-economic-interdependence-waning-individualism-by-diane-coyle-2020-05?utm_source=Project+Syndicate+Newsletter&utm_campaign=1cfd702284-covid_newsletter_07_05_2020&utm_medium=email&utm_term=0_73bad5b7d8-1cfd702284-105592221&mc_cid=1cfd702284&mc_eid=5f214075f8

Daniel Innerarity - Project Syndicate

The pandemic has shown that it is not existential dangers, but rather everyday economic activities, that reveal the collective, connected character of modern life. Just as a spider’s web crumples when a few strands are broken, so the coronavirus has highlighted the risks arising from our economic interdependence.

CAMBRIDGE – Aristotle was right. Humans have never been atomized individuals, but rather social beings whose every decision affects other people. And now the COVID-19 pandemic is driving home this fundamental point: each of us is morally responsible for the infection risks we pose to others through our own behavior.

In fact, this pandemic is just one of many collective-action problems facing humankind, including climate change, catastrophic biodiversity loss, antimicrobial resistance, nuclear tensions fueled by escalating geopolitical uncertainty, and even potential threats such as a collision with an asteroid.

As the pandemic has demonstrated, however, it is not these existential dangers, but rather everyday economic activities, that reveal the collective, connected character of modern life beneath the individualist façade of rights and contracts.

Those of us in white-collar jobs who are able to work from home and swap sourdough tips are more dependent than we perhaps realized on previously invisible essential workers, such as hospital cleaners and medics, supermarket staff, parcel couriers, and telecoms technicians who maintain our connectivity.

Similarly, manufacturers of new essentials such as face masks and chemical reagents depend on imports from the other side of the world. And many people who are ill, self-isolating, or suddenly unemployed depend on the kindness of neighbors, friends, and strangers to get by.

The sudden stop to economic activity underscores a truth about the modern, interconnected economy: what affects some parts substantially affects the whole. This web of linkages is therefore a vulnerability when disrupted. But it is also a strength, because it shows once again how the division of labor makes everyone better off, exactly as Adam Smith pointed out over two centuries ago.

Today’s transformative digital technologies are dramatically increasing such social spillovers, and not only because they underpin sophisticated logistics networks and just-in-time supply chains. The very nature of the digital economy means that each of our individual choices will affect many other people.

Consider the question of data, which has become even more salient today because of the policy debate about whether digital contact-tracing apps can help the economy to emerge from lockdown faster.

This approach will be effective only if a high enough proportion of the population uses the same app and shares the data it gathers. And, as the Ada Lovelace Institute points out in a thoughtful report, that will depend on whether people regard the app as trustworthy and are sure that using it will help them. No app will be effective if people are unwilling to provide “their” data to governments rolling out the system. If I decide to withhold information about my movements and contacts, this would adversely affect everyone.

Yet, while much information certainly should remain private, data about individuals is only rarely “personal,” in the sense that it is only about them. Indeed, very little data with useful information content concerns a single individual; it is the context – whether population data, location, or the activities of others – that gives it value.

Most commentators recognize that privacy and trust must be balanced with the need to fill the huge gaps in our knowledge about COVID-19. But the balance is tipping toward the latter. In the current circumstances, the collective goal outweighs individual preferences.

But the current emergency is only an acute symptom of increasing interdependence. Underlying it is the steady shift from an economy in which the classical assumptions of diminishing or constant returns to scale hold true to one in which there are increasing returns to scale almost everywhere.

In the conventional framework, adding a unit of input (capital and labor) produces a smaller or (at best) the same increment to output. For an economy based on agriculture and manufacturing, this was a reasonable assumption.

But much of today’s economy is characterized by increasing returns, with bigger firms doing ever better. The network effects that drive the growth of digital platforms are one example of this. And because most sectors of the economy have high upfront costs, bigger producers face lower unit costs.

One important source of increasing returns is the extensive experience-based know-how needed in high-value activities such as software design, architecture, and advanced manufacturing. Such returns not only favor incumbents, but also mean that choices by individual producers and consumers have spillover effects on others.

The pervasiveness of increasing returns to scale, and spillovers more generally, has been surprisingly slow to influence policy choices, even though economists have been focusing on the phenomenon for many years now. The COVID-19 pandemic may make it harder to ignore.

Just as a spider’s web crumples when a few strands are broken, so the pandemic has highlighted the risks arising from our economic interdependence. And now California and Georgia, Germany and Italy, and China and the United States need each other to recover and rebuild. No one should waste time yearning for an unsustainable fantasy.

 

 

 

Five Healthcare Industry Changes to Watch in 2020

https://www.managedhealthcareexecutive.com/news/five-healthcare-industry-changes-watch-2020

Innovation

Industry experts expect significant changes to shake up the healthcare landscape in the next few years, which will affect both health insurers and providers. Many are the result of a shift toward value-based care, a move toward decreased care in hospital settings, technological advances, and other forces.

Here’s a look at what can payers and providers can expect to occur, why each change is occurring, and how payers and providers can prepare for each change:

1. A shift in healthcare delivery from hospital to ambulatory settings

Healthcare delivery will continue to move from inpatient to outpatient facilities. “More surgeries and diagnostic procedures that historically have required an inpatient hospital stay can now be performed more safely and efficiently in an outpatient setting,” says Stephen A. Timoni, JD, an attorney and partner at the law firm Lindabury, McCormick, Estabrook & Cooper, in Westfield, New Jersey, who represents healthcare providers in areas of reimbursement and managed care contracting. A growing volume of outpatient care will be provided in ambulatory surgery centers, primary care clinics, retail clinics, urgent care centers, nurse managed health centers, imaging facilities, emergency departments, retail clinics, and patients’ homes.

This change is occurring as the result of clinical innovations, patient preferences, financial incentives, electronic health records, telemedicine, and an increased focus on improving quality of care and clinical outcomes. “The upward trend in value-based payment models is also influencing this shift, with the goal of reducing the cost of care and improving the overall patient experience,” Timoni says.

Payers and providers can prepare for this shift by analyzing and forecasting the cost and reimbursement implications of providing care in outpatient settings compared to inpatient settings. They should continue to analyze changing patient demographics, consumer preferences, and satisfaction trends, Timoni says. Collecting and analyzing data regarding quality and clinical outcomes as the result of changes in delivery of care from inpatient to outpatient is also key. Healthcare providers should develop effective strategies to grow capacity and infrastructure for outpatient services and invest in innovative mobile technologies, diagnostic tools, and telemedicine systems.

2. Consolidation will continue industry wide

More healthcare entities will continue to merge together. “Even though the number of available partners for transactions is shrinking, new deals pop up all the time because smaller entities are being targeted or entities that had been holding out are now changing their position,” says Matthew Fisher, JD, partner and chair of the Health Law Group at Mirick O’Connell, a law firm in Westborough, Massachusetts. Increased consolidation will result in higher healthcare prices as larger sized institutions use their size to their advantage. Another impact will be narrowing the field of contracting options, which will result in greater dominance by fewer entities in a market.

This change is occurring because industry stakeholder believes that consolidation is the way to survive in a healthcare landscape still being shaped by the ACA. “The belief is that value-based care models require single unified entities as opposed to more contractual-based ventures to succeed,” Fisher says. Another factor is that momentum for consolidations across the industry has continued to build and no player wants to be left behind.

Along these lines, Timoni says that consolidation has been motivated by the evolving and challenging commercial and government reimbursement models which include lower fee-for-service payment rates, value-based payment components, and incentives to move care from inpatient to outpatient settings. “Basic economic theory suggests that consolidation of hospitals and physicians enables these combined providers to charge higher prices to private payers as the result of a lack of competition,” Timoni says. “Likewise, combined insurers are able to charge higher premiums to their subscribers.”

Payers and providers can prepare for this change by evaluating their operations and determining whether consolidation with another entity is advantageous. “This requires assessing an entity’s operations and the risks of consolidation,” Fisher says.

Timoni advises payers and providers to monitor the consolidation landscape and develop effective merger and acquisition strategies. These strategies should focus on optimizing economies of scale to reduce costs and finding the best partners to achieve improved quality of care and effectively manage population health.

3. Protecting data privacy

Ongoing attention will be given to protecting the privacy of healthcare data. New laws, at both the federal and state levels, will be considered that could introduce new regulatory requirements, Fisher says.

While a federal law in an election year may be doubtful, individual states are proceeding. The California Consumer Protection Act (CCPA), intended to enhance privacy rights and consumer protection, will become effective in 2020, for example. Even though the CCPA doesn’t cover all healthcare data, healthcare organizations will still collect additional information that could be subject to CCPA, which means more compliance obligations, Fisher says. Other states are considering how to jump on the privacy legislation bandwagon, which means that regulatory requirements will increase. “Even in the absence of legislation, payers and providers can expect individuals to assert concerns and use public pressure to drive increased attention to privacy issues,” Fisher says.

Meanwhile, debates around what is meant by privacy continue to evolve, Fisher continues. A backlash against the non-transparent sharing of healthcare data and arguable profiteering is creating anger among patients and other groups. Simultaneously, data breaches continue to be reported on a daily basis. Add in that healthcare is a prime target, and all of the factors point to healthcare needing to do more to protect data.

Payers and providers can embrace increased data privacy by focusing on existing compliance efforts, which will require taking time to better understanding HIPAA. “Ignoring or only making superficial efforts to respect data privacy is insufficient,” Fisher says. “Merely doing what is legally permissible may not be good enough.”

4. Consumerization of healthcare

As patients assume more financial responsibility for their healthcare costs due to higher premiums, co-pays, co-insurance, and deductibles, they have become more concerned with the value of the care they receive as well as cost. Patients will likely demand improved access to clearer benefits, billing, and network information to improve transparency, says Brooks Dexter, MBA, Los Angeles-based managing director and head of the healthcare M&A advisory practice at Duff & Phelps, a global consultancy firm.

“Healthcare providers must follow suit to meet value expectations and deliver more consumer-friendly services or may risk losing market share to innovative new healthcare arrangements, such as direct primary care, which offer convenient and quality care with simplified medical billing,” Dexter says. Some ways to do this are to offer better patient portals, expanded hours, improved access, and clear procedure pricing. Despite the trend, payers and providers will most likely continue to resist CMS’ efforts to force greater cost transparency by requiring hospitals to post payer-specific negotiated charges for common services that can be shopped.

Furthermore, Peter Manoogian, principal at ZS, a consulting firm focused on healthcare in Boston, says that the voices of older adults will become comparatively louder as this rapidly growing segment becomes more tech-savvy. The Trump Administration supports increased use of Medicare Advantage and expanding consumer choices. Plan options will reach a record high this year and create an unprecedented amount of choices for this population. The average number of plans a beneficiary has access to this year will be 28, up by a whopping 50% from 2017. What’s more, new entrants that boast a customer-driven approach such as Oscar Health are entering the fray in major markets such as New York and Houston.

Health plans need to be laser focused on improving their understanding and engagement of their customers—who are evolving themselves. “To stay ahead of the change, health plans need access to the right data coupled with leading-edge analytics and technology to continuously mine insights on what members are seeking in their healthcare experience, how patients and providers interact throughout their healthcare journey, and how to meet the needs of future healthcare customers,” Manoogian says.

Health plans will need to take more of a retail focus than what they’re accustomed to, Manoogian says. The bar for providing a great experience and retaining members will also increase.

5. More technological innovations will emerge

Technological innovation will continue to dramatically and rapidly change the manner in which healthcare is delivered, resulting in more personalized care, improved clinical outcomes and patient experience, and overall quality of life. “Information systems, mobile technology, high-tech digital devices, and electronic medical records will allow payers and providers to accurately measure clinical outcomes and effectively manage the continuum of medical care and their population’s overall health,” Timoni says.

One specific way that care will change is that providers will start seeing telehealth play a more critical role in care delivery as the brick-and-mortar, in-person care model becomes less common. “Telehealth will grow past a nice-to-have tool into a standard of care, particularly for low-risk and predictable appointments,” says Cindy Gaines, MSN, RN, clinical leader, Population Health Management, Philips, a company focused on transforming care through collaborative health management in Alpharetta, Georgia. This transformation will enable providers to better tailor their care to patients’ unique needs, while increasing patient autonomy and engagement.

Technological innovations are occurring due to booming private sector interest and investment in medical technology innovation. “Patients are demanding real-time health information, personalized medicine, higher quality of care, and convenient treatment options,” Timoni says. “Payers are demanding more detailed and expansive outcomes data to scientifically manage the reimbursement system to lower costs and improve their subscribers’ health. The medical and information technology fields are attracting more high-skilled workers, who will continue to drive innovation to new levels as long as investor interest is sustained.”

Regarding the increased use of telehealth, Gaines says that many appointments that occur in a hospital today can take place outside of the hospital. And, as the healthcare industry increasingly moves toward value-based care, providers need to extend their line-of-sight outside of a hospital’s four walls. For example, a low-risk follow-up appointment after an operation is usually mostly dialogue and has a predictable outcome—it could be conducted electronically. “By filling up hospitals with visits that could occur virtually, it makes it harder for patients who need face-to-face healthcare access to get it,” she says.

A lack of insurance coverage is a major impediment to telehealth adoption for most health systems. Therefore, providers should pair guaranteed reimbursement opportunities with change management workflows to advance these efforts, Gaines says. They would also be smart to leverage their patients’ everyday devices to manage their care, whether it’s on their smart phone, a fitness watch, or voice assistant.

To embrace technological innovation, payers and providers must continue to be educated and aware of the expanding medical technology landscape and develop technology investment and deployment strategies. “Consider investing and participating in technology venture capital funds and partnering with private sector technology manufacturers and research institutions,” Timoni says.

 

 

 

The Tragedy of the Healthcare Data Commons

The Tragedy of the Healthcare Data Commons

Image result for The Tragedy of the Healthcare Data Commons

Once the system can discriminate on a multitude of data points, the commons collapses.

A theme of my writing over the past ten or so years has been the role of data in society. I tend to frame that role anthropologically: How have we adapted to this new element in our society? What tools and social structures have we created in response to its emergence as a currency in our world? How have power structures shifted as a result?

Increasingly, I’ve been worrying a hypothesis: Like a city built over generations without central planning or consideration for much more than fundamental capitalistic values, we’ve architected an ecosystem around data that is not only dysfunctional, it’s possibly antithetical to the core values of democratic society. Houston, it seems, we really do have a problem.

Last week ProPublica published a story titled Health Insurers Are Vacuuming Up Details About You — And It Could Raise Your Rates.  It’s the second in an ongoing series the investigative unit is doing on the role of data in healthcare. I’ve been watching this story develop for years, and ProPublica’s piece does a nice job of framing the issue. It envisions  “a future in which everything you do — the things you buy, the food you eat, the time you spend watching TV — may help determine how much you pay for health insurance.”

Unsurprisingly, the health industry has  developed an insatiable appetite for personal data about the individuals it covers. Over the past decade or so, all of our quotidian activities (and far more) have been turned into data, and that data can and is being sold to the insurance industry:

“The companies are tracking your race, education level, TV habits, marital status, net worth. They’re collecting what you post on social media, whether you’re behind on your bills, what you order online. Then they feed this information into complicated computer algorithms that spit out predictions about how much your health care could cost them.”

HIPPA, the regulatory framework governing health information in the United States, only covers and protects medical data – not search histories, streaming usage, or grocery loyalty data. But if you think your search, video, and food choices aren’t related to health, well, let’s just say your insurance company begs to differ.

Lest we dive into a rabbit hole about the corrosive combination of healthcare profit margins with personal data (ProPublica’s story does a fine job of that anyway), I want to pull back and think about what’s really going on here.

The Tragedy of the Commons

One of the most fundamental tensions in an open society is the potential misuse of resources held “in common” – resources to which all individuals have access. Garrett Hardin’s 1968 essay on the subject, “The Tragedy of the Commons,” explores this tension, concluding that the problem of human overpopulation has no technical solution. (A technical solution is one that does not require a shift in human values or morality (IE, a political solution), but rather can be fixed by application of science and/or engineering.) Hardin’s essay has become one of the most cited works in social science – the tragedy of the commons is a facile concept that applies to countless problems across society.

In the essay, Hardin employs a simple example of a common grazing pasture, open to all who own livestock. The pasture, of course, can only support a finite number of cattle. But as Hardin argues, cattle owners are financially motivated to graze as many cattle as they possibly can, driving the number of grass munchers beyond the land’s capacity, ultimately destroying the commons. “Freedom in a commons brings ruin to all,” he concludes, delivering an intellectual middle finger to Smith’s “invisible hand” in the process.

So what does this have to do with healthcare, data, and the insurance industry? Well, consider how the insurance industry prices its policies. Insurance has always been a data-driven business – it’s driven by actuarial risk assessment, a statistical method that predicts the probability of a certain event happening. Creating and refining these risk assessments lies at the heart of the insurance industry, and until recently, the amount of data informing actuarial models has been staggeringly slight. Age, location, and tobacco use are pretty much how policies are priced under Obamacare, for example. Given this paucity, one might argue that it’s utterly a *good* thing that the insurance industry is beefing up its databases. Right?

Perhaps not. When a population is aggregated on high-level data points like age and location, we’re essentially being judged on a simple shared commons – all 18 year olds who live in Los Angeles are being treated essentially the same, regardless if one person has a lurking gene for cancer and another will live without health complications for decades. In essence, we’re sharing the load of public health in common – evening out the societal costs in the process.

But once the system can discriminate on a multitude of data points, the commons collapses,  devolving into a system rewarding whoever has the most profitable profile. That 18-year old with flawless genes, the right zip code, an enviable inheritance, and all the right social media habits will pay next to nothing for health insurance. But the 18 year old with a mutated BRCA1 gene, a poor zip code, and a proclivity to sit around eating Pringles while playing Fortnite? That teenager is not going to be able to afford health insurance.

Put another way, adding personalized data to the insurance commons destroys the fabric of that commons. Healthcare has been resistant to this force until recently, but we’re already seeing the same forces at work in other aspects of our previously shared public goods.

A public good, to review, is defined as “a commodity or service that is provided without profit to all members of a society, either by the government or a private individual or organization.” A good example is public transportation. The rise of data-driven services like Uber and Lyft have been a boon for anyone who can afford these services, but the unforeseen externalities are disastrous for the public good. Ridership, and therefore revenue, falls for public transportation systems, which fall into a spiral of neglect and decay. Our public streets become clogged with circling rideshare drivers, roadway maintenance costs skyrocket, and – perhaps most perniciously – we become a society of individuals who forget how to interact with each other in public spaces like buses, subways, and trolley cars.

Once you start to think about public goods in this way, you start to see the data-driven erosion of the public good everywhere. Our public square, where we debate political and social issues, has become 2.2 billion data-driven Truman Shows, to paraphrase social media critic Roger McNamee. Retail outlets, where we once interacted with our fellow citizens, are now inhabited by armies of Taskrabbits and Instacarters. Public education is hollowed out by data-driven personalized learning startups like Alt School, Khan Academy, or, let’s face it, YouTube how to videos.

We’re facing a crisis of the commons – of the public spaces we once held as fundamental to the functioning of our democratic society. And we have data-driven capitalism to blame for it.

Now, before you conclude that Battelle has become a neo-luddite, know that I remain a massive fan of data-driven business. However, if we fail to re-architect the core framework of how data flows through society – if we continue to favor the rights of corporations to determine how value flows to individuals absent the balancing weight of the public commons – we’re heading down a path of social ruin. ProPublica’s warning on health insurance is proof that the problem is not limited to Facebook alone. It is a problem across our entire society. It’s time we woke up to it.

So what do we do about it? That’ll be the focus of a lot of my writing going forward.  As Hardin writes presciently in his original article, “It is when the hidden decisions are made explicit that the arguments begin. The problem for the years ahead is to work out an acceptable theory of weighting.” In the case of data-driven decisioning, we can no longer outsource that work to private corporations with lofty sounding mission statements, whether they be in healthcare, insurance, social media, ride sharing, or e-commerce.

Originally published here.

2018 July 27

 

 

 

Healthcare mergers and acquisitions require sensible data sharing strategies, and a solid analytics framework

https://www.healthcarefinancenews.com/news/healthcare-mergers-and-acquisitions-require-sensible-data-sharing-strategies-and-solid?mkt_tok=eyJpIjoiTmpJME5qVTNOVEU1TXpRdyIsInQiOiJDdUIxQ1NKdng1b0FkQ1wvQlwvNFBTc1JIbmVwYUZOeUhCZ3VlNlZzdmhNbkhBQlhnXC9JeTI4c2NDeE80REk0YWJ1Nk1jSzl4QjFDbjFMTkxKdmVCblY1RUlSYTIwUmlhSEJ6VXpkOUZZdytUWDhaV1poaEljcVh5ZFdEOUdVZlQzZyJ9

While it’s important for disparate EHRs to communicate with one another, organizations need a better handle on analytics and dashboards.

Mergers and acquisitions in healthcare have been going along at a pretty good clip for a number of years now. The volume of deals remains high, and with larger entities primed to scoop up some of their smaller, struggling peers, the trend seems poised to continue.

There’s an issue that consolidating organizations consistently run into, however: data sharing.

Specifically, many organizations that have initiated merger activity fail to consider that not only will the consolidation necessitate integrating multiple electronic health records, but other ancillary systems as well.

These organizations need to produce the analytics that are required to manage what’s essentially a new business, and that starts with the development of some sort of analytics blueprint early on in the merger activity.

As two or more forces join into one, it’s important to have the analytics blueprint in place so leaderships knows which dashboards are going to be needed for success.

“There used to be a trend where everyone was converted onto the same EHR platform,” said John Walton, solutions architect for IT consulting company CTG. “I guess the thought is that if everyone is converted, the problem will go away. Now … they end up in a situation where they can’t produce the kind of dashboards that are needed.”

THE FRAMEWORK

A key component of an effective analytics blueprint is a conceptual data model — basically a visual representation of what domains are needed for the dashboards.

“It sounds difficult to produce, but if it takes more than four to six weeks to produce something like that, you’re overthinking it,” said Walton. “But that’s then starting point. The key component is that analytics framework.”

Failure to have a framework in place can result in the newly merged entity losing out in terms of revenue and productivity. And once the problem becomes manifest, there’s often a lot of manual effort that goes into serving, for example, the financial dashboards that are so needed by CFOs. A lot of the manual effort goes into putting the data into Excel spreadsheets, which only puts a Band-Aid on the problem.

“The framework essentially provides pre-built routines to extract data from multiple data sources, as well as from financial systems,” said Walton. “It also provides, for lack of a better term, the data plumbing to enterprise standards, and most importantly there’s an analytic layer. The endgame is that the dashboards need to sit on top of an analytics layer that is easy to do analytics on. What it contains is pre-computed performance indicators based on approved business rules with multiple levels of aggregation.”

An effective framework, as with so many other things, begins with C-suite leadership. Having executive sponsorship, or at least an understanding of the issue at an executive level, can translate into a vision for how to integrate the data and provide the analytics that are needed to successfully manage the business.

PLANNING PROACTIVELY

Walton once observed a national organization that acquired another entity, and after two years the CEO still didn’t have any executive dashboards — which means a lack of visibility into the performance metrics. The CEO hen issued what was effectively a mandate to the acquiring organization: Get this done within three months, or else.

Thus began a flurry of activity to et the dashboard situation straightened out, which is not where an organization wants to be. Proactive planning is essential, yet Walton doesn’t see a lot of that in healthcare.

“I’ve never seen an organization proactively plan for this,” he said. “That doesn’t mean it’s not happening, but in my experience I haven’t seen it.”

In the meantime, mergers and acquisitions keep happening. Even if merging organizations become aware of the problem and factor that into their decision-making there’s another issue to consider.

“Another extremely significant problem is data quality and information consistency,” said Walton. “That problem really is not universally dealt with, in healthcare or for that matter other industries. It’s almost like they’ve learned to live with it. It’s almost like we need a call to arms or something. You’re almost certainly going to have the need for an analytics framework that will apply the data to your standards.”

The data in question could encompass missing or clinically inappropriate data. Quality, in this case, has to do with the cleanliness of the data. In terms of consistency, a good example would be something like average length of stay. There’s an opportunity to ensure that the right data ownership and stewardship is in place.

Importantly, it’s primarily a business solution. It’s possible that one of the merging entities has a data governance strategy, but all too often that strategy was launched by the IT department — which is not where an organization wants to be, said Walton, because it’s primarily a business problem rather than one that’s purely technical.

Data governance is a very well-known concept, but people struggle with its actual implementation for a number of reasons,” he said. “One, there’s a technical aspect of it, which centers around how we identify data quality issues. What kinds of tools are they going to use to address data quality issues?

“Then there’s establishing ownership of the data, and who are the subject matter experts. And there’s a workflow aspect that most organizations fail to deal with.”

It all starts with the framework. Only then can merging organizations get an appropriate handle on its data and analytics landscape.