Readers Write: Healthcare Needs to Slow-Roll Fast-Moving ChatGPT

Healthcare Needs to Slow-Roll Fast-Moving ChatGPT
By Jay Anders, MD

Jay Anders, MD, MS is chief medical officer of Medicomp Systems of Chantilly, VA.

Now that the initial hype surrounding the chatbot ChatGPT has peaked or perhaps plateaued, its strengths, weaknesses, and applications are being scrutinized.

Perhaps one of the most visible applications revealed recently was the AI tool correctly answering 60% of the United States Medical License Exam (USMLE) medical board exam questions, a task that many top-tier students fail to achieve. This raised a number of concerns about how the technology could, and should, be used in healthcare.

Granted, as an AI language model, ChatGPT has a number of applications in healthcare today, including administrative tasks, triaging patient inquiries, and performing preliminary analysis of medical data. However, ChatGPT is not a trained, certified medical professional and should never be relied upon for clinical guidance or diagnosis. Just like a Google or Bing search, it can provide limited general health information, but it is certainly not a substitute for professional medical advice or treatment.

As a physician, my primary concern with ChatGPT and other large language AI models is that patients accessing the technology will begin to distrust the advice of medical professionals when a disagreement occurs.

Here’s an example of how such a disagreement can go awry. Years ago, a patient came to our practice and told me she wanted to feel like ‘that guy surfing in a wheat field’ in a popular ad for an allergy medication.

When I inquired about her allergy symptoms, she said she had none. She argued that the drug would help her anyway. So, when I would not write her prescription, she switched doctors to one of my practice colleagues. My colleague asked why she was making the change, and I told her. My colleague then revealed that this same patient argued with her as well and then switched to the clinic down the street.

I am a staunch advocate of transparent patient information that is accurate and science based. In this case, a little knowledge could be a dangerous thing. At the time of the dispute, the patient was taking a medication that would interact with this antihistamine and cause a severe reaction.

Although ChatGPT and AI weren’t available at the time of this encounter, the danger is clear. There is a genuine risk that some patients, particularly those without access to primary care or those trying to avoid the inconvenience or expense of an office visit, might rely on AI technology like ChatGPT for medical guidance. This could lead to incorrect self-diagnoses, misinterpretation of symptoms, and any number of potentially harmful consequences. It is essential for consumers and patients to understand the limitations of AI in healthcare and always seek professional medical advice for their health concerns.

AI and the role of the clinician

What is the clinician’s role in this learning curve? Healthcare providers (and naturally, developers of AI solutions) should emphasize the importance of using AI as a supplementary tool rather than as a knowledgeable substitute for professional medical care.

The real issue is the lack of reliable, trustworthy information for patients. Patients, especially those with a rare disease community or with complex conditions, can’t advocate for their own health and care if they don’t know anything about the condition they are battling. Reliable academic medical information isn’t as freely or easily available to them, so they often rely on what they find on the internet to supplement what their doctors tell them for peace of mind and, in some cases, survival. The patient advocacy community calls the patient administrative burden associated with this lack of reliable information “information toxicity.”

That said, patients are already using AI to self-triage, so it’s really up to the medical and technology communities to establish parameters to prevent people from using the technology in lieu of trained medical professionals, or educate them on how to do it safely. Ultimately, it would seem that both communities would work to make the AI better able to do it better.

In my experience as a physician, I’ve encountered many patients who consider themselves quasi-medical experts and excellent researchers. Still, some patients don’t particularly care if the information they unearth is accurate. They just don’t want to feel left in the dark about their symptoms. After all, a wrong answer is still an answer.

Overall, patients want and need to be collaborators in their own care, and with the availability of information being what it is, they are moving forward in the best way available (to them). Unfortunately, the burden is on the physician to correct the misinformation, and that will need to be included in the job description of physicians and nurses going forward. With technologies like this on the rise, with questionable, though increasing, accuracy, there is no choice.

The responsibility is on health systems to educate patients on how to use these technologies and other more reliable websites to research and also regularly share population health information with communities to combat disinformation. Additionally, efforts should be made to ensure equitable access to quality healthcare for all, reducing the reliance on AI technologies for primary medical guidance.

Harnessing AI to supplement clinical decision support

Looking back at those USMLE licensing exams, consider this. The exams are written very discreetly. “A patient presents with X, Y, and Z. What is the diagnosis?” It’s based on a set of facts, and is possibly multiple choice. Humans do not operate that way. Consider a 65-year-old with high blood pressure, elevated cholesterol, diabetes, osteoarthritis, and spinal stenosis. That is not a single question, it’s multiple conditions. Physicians are trained to mesh those conditions together because a treatment for any one condition may exacerbate another. An exam would not approach it this way.

Physicians need to learn how to use AI to augment their practice, knowledge, and skill, not the other way around. Harnessing AI as a supplement to clinical decision support is a promising option.

For now, ChatGPT is out there, and it will be used, sometimes for medical advice. That’s all well and good until it makes a mistake or doesn’t surface something of importance. Meanwhile, there are technologies in use that work with clinicians, in their workflow, and present clinically relevant information regarding conditions in a way that mirrors the way they think and work.

The human element is, by necessity, still very much at the center of healthcare. So, for now, let’s slow the roll on ChatGPT. Let it mature. Crosscheck it. See how it evolves as its models are further trained and deepened. The technology holds tremendous promise, but is still in its infancy.

Readers Write: HLTH, CHIME, ViVE, HIMSS — Choose and Invest Wisely

HLTH, CHIME, ViVE, HIMSS — Choose and Invest Wisely
By Steve Shihadeh

Steve Shihadeh is founder of Get-to-Market Health of Malvern, PA.

Many vendors in the health technology space have just attended ViVE and/or are preparing for HIMSS to showcase their offerings, meet with clients and prospects, and engage with their investors. For most of our clients and friends in the industry, these shows represent a significant investment of time, money, and education for their teams.

Execute these shows right and reap the rewards in new contracts, bought-in clients, and investors who get your plan. Do it not so well and you miss out on the year’s biggest potential market exposure for your company. What can you do to maximize this opportunity?

ViVE

If you just went to ViVE looking to find a vast field of potential customers on the exhibit floor, you probably came up wanting. One well respected colleague called it as “six vendors for every buyer.” The main live customer engagement seemed to come from the well-run Hosted Buyer Program in the ViVE Connect Lounge. This is a “pay for x meetings” gig, where the matched potential customer is trading their time to hear your pitch for reimbursement for ViVE fees and possibly T&L.

Based on our experience, about half of these meetings have potential value for you, but it is in your hands. It is really speed dating. You must be on message, be quick to read the buyer, and put your best foot forward.

ViVE is smaller (although just about every company in the space made sure to have someone there), more posh, and easier to get your head around than HIMSS. If I was mostly intent on getting time with investors and partners, I would have gone to ViVE. If I was mostly focused on potential buyer organizations …  let’s go to HIMSS, which comes up in a few weeks.

HIMSS

HIMSS is the grand old show of the health technology business. In its heyday, 40k+ attendees and healthcare IT companies sent everyone from the CEO to their junior sales reps. COVID and the way HIMSS handled the associated cancellations knocked the show for a bit of a loop. Their breakup with CHIME was the next issue. Now ViVE, in association with CHIME, is giving them competition that they did not have before, along with HLTH.

HIMSS has historically been gigantic and hard to navigate. However, it had most everyone in the business in one enormous convention center, along with a sea of potential buyers evaluating systems. HIMSS attendees slant heavily towards IT staff and leadership, some clinical and financial executives who are in the market for new systems, and an occasional CEO. Given its size, HIMSS takes extra work, extra people, and extra prep to get the most of your investment, but it is too tempting to pass up for most every company in the business.

Given the hip and more accessible vibe of ViVE (sorry, could not resist), I suspect HIMSS will make some adjustments. Good competition will do that for you. It will be great to be at HIMSS and get a real pulse of the industry post-COVID and in the new AI-everything world.

A Few Words on CHIME and HLTH

CHIME (College of Healthcare Information Management Executives) is the single most important event for CIOs and those who are on a CIO career track. They run a fabulous boot camp for people in the field and have an agenda aimed squarely at the CIO. Vendor participation is carefully managed and expensive, but several key luminary vendors in the field, such as Epic, have built their business around important relationships that it established with CIOs via CHIME. If CIOs are crucial to your business, CHIME is the place to be.

HLTH is a relatively new show hosted by the same folks who run ViVE. It is well run, quite upscale, targeted mainly at investors, and attracts enough potential buyers to make it interesting. For those who have been to the JP Morgan Healthcare conference, HLTH is a friendlier environment to tout your plans, show your wares, and get quality time with all the key investors in the space.

Where to Make Your Investments and Our Top 10 Tips to Maximize Your Return

Given how expensive any of these shows can be, we have some suggestions on how to get the most return.

1. Have a presence, even just one key person, at as many of the shows that you can. It is a great way to drive meetings and prospect engagements, e.g., “Are you going to HLTH?” A lot of startups that cannot justify the fees of the show still get mileage by being around the event and meeting potential partners at local hotels.
2. Based on your company’s priorities, pick your most important show for any exhibit booth investments. Securing, staffing, and running a booth at a show is a significant investment.
3. Send only your best, most committed people. Buyers will judge you by your staff.
4. Be fully committed to setting up meetings in advance. Know who in your target market is attending and schedule meetings and interactions. Do this whether you are exhibiting or not.
5. Train in advance on any new announcements and have your team arrive early for last minute retraining.
6. Trade shows are a fantastic selling opportunity and need to be treated as such. Booth personnel need to be focused on facing clients and prospects and not connecting with industry friends. The best-run booths are hardcore about this. Be best.
7. Booth hygiene matters. Have a dress code and stick to it. No food. No cell phones. No rep-to-rep chatting.
8. Get a modern lead tracking tool and train your booth staff on it.
9. Force (gently) all inquiries to your front desk so you can properly capture their info and direct them to the right staff in your booth.
10. Get your leads into your CRM system ASAP and send immediate follow-up notes to all visitors.

Trade shows are a big lift, so make sure that you and your team are aligned, prepared, and motivated to have a great show. Hone your messaging so that it works from a buyer’s perspective. Practice your demos until they are crisp. Worry about the details and have a fantastic event.

Readers Write: The Myth of the Golden Health Record

The Myth of the Golden Health Record
By Peter Bonis, MD

Peter Bonis, MD, is chief medical officer of Wolters Kluwer Health.

In 2009, President-elect Obama signaled his plan for the federal government to support the adoption of electronic medical records (EMRs). His expectation was that broad adoption would “…cut waste, eliminate red tape and reduce the need to repeat expensive medical tests,” adding that, “it just won’t save billions of dollars and thousands of jobs; it will save lives by reducing the deadly but preventable medical errors that pervade our healthcare system.”

The subsequent Health Information Technology for Economic and Clinical Health (HITECH) Act, part of the larger American Recovery and Reinvestment Act, achieved his directive, at least in part; most healthcare systems now use EMR systems. However, the strategic objectives of reducing costs and preventing medical errors have been elusive. Preventable medical errors remain common, growth in healthcare spending has not been reduced materially, and healthcare providers frequently cite EMR systems as being an important contributor to professional burnout. 

In this backdrop rests a common belief that the full promise of EMR systems has yet to be obtained. It will only be achieved once patient data can flow unimpeded from system to system, permitting healthcare providers (and other stakeholders involved in healthcare services) to have a comprehensive view into patient care wherever it is delivered, a concept referred to as interoperability. Over the years since the HITECH act was passed, many barriers posed challenges for achieving such a vision including concerns related to data privacy, deliberate blocking of information flow (especially when it interfered with business models), and approaches to gathering and making sense of intrinsically messy data.

Nevertheless, the journey has continued; key pieces of legislation and advances in technology have led to demonstrable improvements in interoperability.  Most recently the federal government gave the objective a boost by advancing standards and designating qualified health information networks intended to establish a universal floor for interoperability across the country. As a result, the healthcare system is marching toward a comprehensive, golden health record.

But once we have it, will the golden record enhance the quality, safety, and effectiveness of care? The answer is unsurprisingly no unless more is done to use the data effectively. Primary care providers would need almost 27 hours a day to deliver all the guideline-recommended care, according to one estimate. In this context, more information is not better.

Healthcare data must be delivered in ways that are useful for busy healthcare professionals working in varied settings. Information must be high value and organized into consumable payloads and workflows not only for time-pressed individual clinicians but for extended care teams. It should ideally support decision-making and subsequent actions while saving time, reducing cognitive burden, decreasing administrative overhead, measurably improving the quality and safety of care, and reducing costs. The golden health record is a welcome enabler, but will not in itself accomplish these objectives. 

So, what is needed? Foremost is recognition that the matter is critically important. The core of healthcare delivery is an interaction between providers and patients where decisions are made and care implemented. There is much to be gained by making it easier for healthcare professionals to take care of patients.

A greater sense of urgency is needed. Burnout and other challenges are leading to attrition of healthcare professionals. There will be a shortage of primary care physicians and hence a need for advanced practice providers (such as nurse practitioners and physician assistants) to take on greater responsibilities. They will need help. At the same time, healthcare services are becoming more distributed to new sites of care, such as retail pharmacies and to digital health technology companies, creating greater challenges for coordinating care and optimizing flow of useful information. The proliferation of devices that generate healthcare data adds further complexity.

EMR vendors need to expand capabilities, focusing on metrics that are directly relevant to the experience of various user types and ultimately to the quality of care delivered. Financial incentives and payment models must justify the investment for both EMR vendors and providers.

Healthcare professionals want to deliver exceptional care for their patients. Let’s make their needs a priority. The golden health record is a worthy goal, but the usability of the data should get equal attention.

Readers Write: Healthcare Delivery Must Evolve to Meet the Needs of a Generation in Crisis

Healthcare Delivery Must Evolve to Meet the Needs of a Generation in Crisis
By Bob Booth, MD

Bob Booth, MD, MS is chief care officer at TimelyCare of Fort Worth, TX.

A recent new report from the CDC shows startling trends about the never-before-seen levels of hopelessness and suicidal thoughts among teens.

The findings for teenage girls in the CDC’s 2021 Youth Risk Behavior Survey were particularly grim. Nearly three in five teen girls (57%) said they felt “persistently sad or hopeless,” the highest rate in a decade. And 30% said they have seriously considered suicide, a 60% increase over the past decade.

While boys generally fared better overall, more than 40% of boys and girls said that they had felt so sad or hopeless within the past year that they were unable to do regular activities, such as schoolwork or sports, for at least two weeks.

The members of Generation Z, born in 1997 or later, are experiencing unprecedented levels of stress and emotional turmoil. While some of this is likely to ease as they age out of adolescence, adulthood is certainly no cure for depression, anxiety, loneliness, and other stressors. Additionally, double the number of Generation Z members report feeling emotionally distressed compared to older Millennial and Generation X groups.

In order to meet the healthcare needs of Gen Z, particularly mental and behavioral health, the industry needs to become more proficient in its use of digital and virtual care tools. However, not all of these tools are equally effective or designed to meet these young patients where they are.

The digital-native generation that has never known a world without the Internet or smartphones expects that their preferred technology will deliver relevant information and an engaging experience as part of treatment. It’s something we can expect to see more of as part of the future of care for younger generations.

Artificial intelligence (AI) can play an important role in care delivery and engagement if the algorithms enable a highly personalized and patient-centric experience. For example, not all young adults are ready for, or want, 50-minute, one-on-one counseling sessions with a mental health professional. AI can accurately analyze and interpret intake screenings, so a patient’s selected care pathway is the most relevant and takes into account their unique health and personal needs. AI can even help guide digital-only care pathways through content and activity selection based on the young adult’s interactions with the solution.

The promise of AI is that it delivers an even more personalized experience as its algorithms learn more about young adults, which accelerates their growth and motivation to improve their mental health and well-being. These engagement-building concepts have been understood and applied in other consumer-facing technology for years. Healthcare is finally catching up, and that’s good for young adults and healthcare overall. It’s exciting to see where this will take us in the future.

Gen Z needs a solution that leverages personal technology to enable access to mental health and well-being at their fingertips. By seeking tech-enabled help from a healthcare platform that is designed for them and understands their unique challenges, Gen Z can develop the skills and resilience to help them prepare for college and beyond.

It’s time for healthcare to look beyond traditional models of healthcare delivery and meet a generation who so badly needs care where they are.

Readers Write: The Impact Intelligent Automation Can Have on Healthcare Costs

The Impact Intelligent Automation Can Have on Healthcare Costs
By Krishna Kurapati

Krishna Kurapati is founder and CEO of QliqSOFT of Dallas, TX.

RPA stands for robotic process automation. RPA uses technology to automate repetitive human interactions with a computing system. In other words, instead of a human clicking a button over and over to generate a desired outcome, the system automatically connects and completes the stipulated work process, eliminating significant amounts of manual steps and time for the care team.

A similar approach applies to robotic workflow automation, where a chatbot can automate manual and repetitive tasks between a care team member and a patient. For instance, in healthcare administrative and clinical support tasks, the end-to-end steps include reminding a patient of an appointment, sending them digital forms to complete before the visit, automating patient check-in, and reinforcing instructions after the visit. Each task’s workflow comprises a number of work processes to gather, upload the patient’s information to an electronic health record (EHR) system, and to communicate with and guide the patient.

To illustrate, let’s examine the case of patient intake: Today, the office staff creates a paper clipboard and shares it with the patient on arrival, who takes five to 15 minutes to complete the paperwork. Staff then looks up the patient record, scans and uploads the requisite forms to the EHR, and checks the patient in. Humans can be removed entirely from this sequence of steps with RPA and chatbots, which automate the workflow to capture and process the requisite patient data to meet clinical and billing purposes.

The benefits of intelligent automation in healthcare

Faced with a never-ending need for reporting and data entry, healthcare organizations must manage high volumes of administrative duties. A recent study found that the average employee spends 60 hours per month on easily automatable tasks, making healthcare an ideal use of RPA to digitize and scale manual, routine processes. The upshot is dramatically reduced labor costs while optimizing workforce usage for lower costs.

In a January 2023 paper by the National Bureau of Economic Research titled “The Potential Impact of Artificial Intelligence on Healthcare Spending,” the authors calculated that hospitals employing AI-enabled use cases could achieve total annual run-rate net savings of $60 billion to $120 billion (roughly 4% to 10% of total costs for hospitals) within the next five years using today’s technologies, without sacrificing quality or access. The Academy projected that 60% of clinical workflows can be automated through AI, including bots, signifying untapped potential in new revenue and cost reduction.

The role intelligent automation will play in transforming healthcare

Digital health is about delivering care and managing data electronically. Unfortunately, many patient experiences at healthcare systems and practices are handled through traditional communications, including paper transfer, phone calls, snail mail, and fax. This can lead to disconnected patient communication, misdiagnosis, medical errors, waste, and poor quality care. Digital capabilities help providers, innovators, payers, and other stakeholders come together collaborating in an agile, more communicative way to solve problems, overcome scalability limitations, empower patients, improve efficiencies, and speed up throughput.

Once digital infrastructure and capabilities are built, the robotic process automation sits on top to automate workflows. The conjoining of digital and RPA accelerates and scales processes and elevates innovation to create a new standard for the patient experience.

Current use of intelligent automation

Automation started in revenue cycle management processes and is relatively new to the clinical side of healthcare, where the initial focus is processing and management of large quantities of paper into the EMR or content management systems.

Although automation is now happening on the clinical side, it’s not yet well adopted. The most common focus areas are patient communication regarding appointment reminders, appointment scheduling, patient intake, billing, procedure readiness, documentation management, and evidenced-based content for patient education.

The future state of intelligent automation in healthcare

Automation’s ability to simplify healthcare is limited only by our imagination. The cost of labor has skyrocketed to 64% of total operating costs, creating new pressure to reexamine workflow and adopt automation. Healthcare has two broad categories where automation can be of service:

• Eliminating work by automating existing manual, repetitive administrative tasks staff are doing today.
• Supporting automated communication and monitoring needs not possible today because of staffing limitations, such as readmission prevention.

I expect intelligent automation to play a larger role in healthcare for years to come. The time is now to blend clinical and business efficiencies to improve operations and provide relief to overworked and understaffed healthcare professionals.

Readers Write: A Glimpse of Telehealth’s Future: Five Takeaways from ATA 2023

A Glimpse of Telehealth’s Future: Five Takeaways from ATA 2023
By Lyle Berkowitz, MD

Lyle Berkowitz, MD, is CEO of KeyCare of Chicago, IL.

My recent visit to the American Telemedicine Association (ATA)’s annual meeting offered an opportunity to briefly reflect on how far the industry has come, as well as provided a few glimpses of what the future of telehealth might hold.

When ATA was founded three decades ago, broadband internet was a rare commodity and telehealth visits were primarily via phone calls. Fast forward to today and it’s obvious that telehealth is leading healthcare transformation in multiple areas, from urgent care to women’s health needs to lifestyle medications – while pushing how we can use virtual care tools to simultaneously improve the patient experience, quality, and cost.

Here are five of my key takeaways from the ATA 2023 Annual Conference and Expo:

1. The rise of femtech and women’s health. Numerous startups are developing solutions that leverage telehealth to address women’s health issues. For example, Nest provides virtual same-day lactation support and has partnered with several hospitals to improve infant health outcomes. Separately, SimpliFed partners with caregivers before an infant is born to develop feeding plans and delivers support to patients through a virtual breastfeeding provider network.
2. Increased focus on hybrid care. In this context, hybrid models refer to those that offer patients access to telehealth visits which can coordinate with in-person care, based on a patient’s individual care needs. Corporate giants like Amazon, CVS, and Walmart are lurking around in this space, but health systems have the greatest potential to own it. That’s because it is far more straightforward, simple, and cost-effective to add a virtual care partner to a robust office-based health system than to bolt on office-based care to a virtual care company.
3. A new market for hearing aids. Over-the-counter hearing aids are now available to the public, thanks to a ruling by the US Food and Drug Administration last year. As a result, companies like Audicus have jumped into this market to serve customers via telehealth. In this easy and convenient process, a hearing test is performed online, a hearing aid is shipped out, and any adjustments are done via a video visit.
4. The rise of remote patient monitoring. Like telehealth, remote patient monitoring (RPM) technology has been around for decades, and while various startups have different approaches for obtaining data, they all have the same vision in mind. For example, some companies use a wearable patch for continuous monitoring, others use Bluetooth to connect to devices a patient may have, and “device-less” companies use a chatbot that allows a patient to self-enter data. Some may even combine these tools or add others. Then all of this data is sent to a dashboard for analysis and display so that a virtual team can appropriately monitor and engage with patients, and then identify outliers which need to be escalated to office-based providers. However, the real trick is knowing where to apply RPM and align incentives. The post-acute care area has been popular for years; the chronic care space has experienced slow growth but offers strong potential; and the new hot area is clearly hospital at home.
5. Niche products. It has become easier for companies to focus on specific use cases for virtual care monitoring and management. For example, I came across the super niche startup Staling Medical, which has created an at-home urine diagnostics tool that uses a patient’s smartphone microphone to listen to their urine stream, with a goal of improving outcomes for recurrent urinary tract infections, urinary obstructions, and chronic kidney disease.

It’s a fun time to be in telehealth. I’m looking forward to seeing what’s up next at ATA 2024!

Readers Write: Value-Based Care Arrangements: Four Ways Specialty Care Providers Can Prepare for Claims Data

Value-Based Care Arrangements: Four Ways Specialty Care Providers Can Prepare for Claims Data
By Tyler Johnson

Tyler Johnson is VP of strategic partnerships at Ursa Health of Nashville, TN.

Companies that are bringing new specialty care models to market face a big early hurdle when partnering with plans, full-risk provider groups, or self-insured employers: working with claims data. Although lacking some clinical context, clean, well-organized claims data is vital for creating longitudinal patient views and the main fuel for analytics (which of course become even more powerful when supplemented with clinical and other data sources). Trusted analytics, in turn, are the first step toward optimal operations and outcomes, as well as the financial reconciliation between partners that value-based contracts require.

With everything else involved in launching or expanding a new business, specialty care providers (SCPs) may be tempted to put data and analytics planning on the back burner. Those that delay too long, however, could find themselves scrambling to get new partnerships off the ground or to keep up with an ever-changing landscape. In the best-case scenario, late-night heroics save the day but inordinately stress the team. In the worst, lack of planning leads to lost sales, crumbling partnerships, and dwindling rather than growing healthcare impact.

SCPs must ready themselves to consume claims data from their partners in four key ways.

The first concerns the security review. Organizations are very particular about how and where their data gets shared. Convincing business or clinical leadership to try a novel intervention is tough, but convincing security and InfoSec folks that others can be trusted with their most prized possession is another obstacle altogether.

Before any data is shared, an organization will ask its potential SCP partner to submit to a comprehensive vetting process to ensure the SCP’s technical and administrative safeguards are strong enough to meet both internal and HIPAA requirements. To prepare for the review process, the SCP should:

• Create very tight and easy-to-understand documentation around its technical architecture, including where data is going to live and what people, tools, and processes are going to touch it.
• Create an overview document that summarizes its security posture.
• Organize employee business and security procedures for easy reference.
• Devise a system for retaining answers to assessment questions to expedite the next review.
• Consider being HITRUST and SOC2 certified, which can quickly ease the security team’s concerns. Because the level of effort isn’t trivial, working with a technology vendor that is already certified can help organizations that do not have the internal resources to pursue certification themselves.

Second, an SCP needs to prepare is its tech stack. The contracting and security assessment process can feel a lot like hurry up and wait, but the reality is that this is a task in a very long queue, and once the organization assigns resources to complete that task, it will expect a new partner to be ready to roll.

If the SCP can tap into and pull from the organization’s existing infrastructure for hosting data, great. If not, it needs its own secure cloud storage mechanism (e.g., Amazon S3, Azure blob storage) into which data can be dropped, as well as a pre-defined process for granting access to it. In addition to transmission mechanisms, a database/warehouse and any data modeling and transformation tools must be up and ready to use.

The potential partner is also going to expect the SCP to quickly provide feedback and ask questions about the data. If the environment is ready to go in advance, the SCP can spend more time on loading and investigation instead of provisioning cloud resources. It is also extremely helpful to get answers to data questions while the company’s technical resources are still engaged and informed.

As a final note, SCPs should think in advance about how they will assess the quality of the incoming data, both in a general sense (e.g., data completeness) and regarding specific data points or lineage that is important to their analyses.

The third way to prepare is to ensure a scalable approach exists for organizing and analyzing data. Without a proactive approach to a data model, an SCP can very easily stack up technical debt — in the form of silos of logic and code that are custom to analyzing data from a single source — that becomes a nightmare to untangle down the road and will prohibit efficient scaling of its business.

Once it has defined the data model, the SCP should apply transformation logic to all incoming raw data sources to map the data to that standardized structure. Rules and algorithms to interpret data for specific use case(s) should only be authored on top of that standardized data model, an approach called hierarchical data modeling. This approach facilitates scalability while making it easier to marry up claims data with other sources of information: for example, clinical data from the EHR, patient engagement data, and internal product data.

The final way to prepare is to identify how the claims data will be used to provide insight into their operations and business. This planning should occur before any value-based contract is signed, let alone claims data is shared, to help determine whether other sources of data will be needed — for example, other patient data or industry-available supplemental data such as value sets and provider rosters. Armed with a clear understanding of what insights need to be derived, SCPs can more intelligently articulate their needs and the anticipated value to partnering organizations.

Effective partnership in the co-management of patient populations demands a strong data foundation paired with trusted, useful analytics. Bad data in results in bad data out. SCPs embarking on new value-based partnerships can increase their chances of success and make life easier for both parties with some basic preparation. With a solid and scalable data foundation in place, technical resources can shift their attention away from non-strategic data wrangling work and focus on building the special sauce that differentiates it from competitors and adds the most value to its customers.

Readers Write: The Cost of Doing Nothing: Five Learnings from the Build versus Buy Debate

The Cost of Doing Nothing: Five Learnings from the Build versus Buy Debate
By Kimberly Hartsfield

Kimberly Hartsfield, MPA is EVP of growth enablement at VisiQuate of Santa Rosa, CA.

It’s a conundrum that health system executives regularly face. Build a much-needed software solution in-house or buy it from a vendor?

Once hospital leaders identify the need for a solution that requires new functionality, the debate is on. Revenue cycle management (RCM) solutions are no different.  While many hospital IT departments are no doubt capable of designing, constructing, and implementing new RCM solutions, leadership must decide whether taking this route is likely to yield the best business results.

Often, it starts with hospital leaders surveying vendors, seeing the price tag, and deciding to embark on the journey to complete the project internally, with the premise that it will be at a much lower cost. The decision frequently backfires. Rather than making the investment and having the technology that hospitals need to support their RCM operations efficiently, do-it-yourself health IT projects often end up taking years to fail and costing hospitals far more than if they would have signed with a vendor in the first place.

Health IT leaders see a pretty Tableau or Qlik dashboard and think, “We can do this ourselves.” When it comes to data visualization, they probably can. What they don’t consider is that the data aggregation, normalization, and transformation work that happens under the hood is actually the challenging part of RCM transformation.

The following are factors to consider when considering whether to build or buy a new RCM solution.

Complex health IT projects require more than health IT

IT departments sometimes believe that because they have their own developers and analysts, they can design, build, and implement complex health IT systems on their own. However, complex health IT projects require far more than technical skills. There must be business knowledge and experience married to that technical skill. Frequently that is where the projects break down because the people with the business knowledge already have full time jobs in the organization that are not related to building a platform.

Indeed, the reality of large IT projects is that they frequently exceed timelines, go over budget, or sacrifice important functionality. For example, one in six large IT projects have an average cost overrun of 200% and a schedule overrun of almost 70%, according to Harvard Business Review. Similarly, 56% of IT projects fall short of the original vision, according to a study by McKinsey.

It’s all about speed to value

Leading RCM vendors have been waking up every day for years thinking about how they can work to evolve revenue cycle analytics and deliver value and ROI to clients. Vendors have the benefit of having seen and evaluated RCM systems from healthcare organizations of many different shapes and sizes across the country. They understand best practices, having implemented RCM solutions alongside numerous electronic health records systems. This experience enables the ability to identify idiosyncrasies that hide within data and frequently uncover gaps that clients didn’t know existed.

While hospital do-it-yourself RCM projects may take years to complete, leading vendors can perform an installation in 90 days, delivering immediate insights and ROI.

RCM processes are broken and technology is the fix

It’s an unprecedented time for healthcare. There is no model for the circumstances the industry is undergoing, given labor shortages, supply chain constraints, and the financial after-effects of the COVID-19 pandemic. Across the nation, hospitals are pushing for more automation to augment staffing issues, letting their staff focus on tasks that require decision making, not repetition.

In many cases, RCM processes are broken, and technology is the only route hospitals can take to do more with less. Hospitals must lean into technology and automation, leveraging data to build predictive models and using artificial intelligence and machine learning to boost efficiency.

Unless hospitals are large, mature, and complex, they typically don’t have the resources to handle a large RCM project internally. Smaller hospitals often lack resources like a database administrator, a data warehouse, and data scientists who can build predictive analytics models, for example.

RCM processes continually evolve

It’s easy to forget that RCM projects typically are not “build it and you’re done” solutions. In addition to building RCM solutions, hospital IT departments must provide ongoing support and maintenance. These projects continually evolve, with new requests for additional reports or functionality upgrades. This often requires analysts, engineers, and other highly paid technical resources that are difficult to find and are only growing more expensive.

Further, it’s an open question as to whether build-it-yourself solutions deliver enough value and differentiation to be worth the time, expense, and effort. For example, if all an organization’s competitors can simply build their own systems to accomplish a certain objective, then that system is hardly a source of competitive advantage.

Move from descriptive to predictive

RCM employees cannot manage by spreadsheets. The industry is moving beyond rows and columns. RCM employees need to be able to visualize data to detect patterns to quickly identify outliers and manage by exception. Additionally, hospitals must move their RCM processes beyond descriptive analytics to predictive and prescriptive analytics.

It is no longer acceptable for hospital leadership to simply understand what happened yesterday. Hospital leaders must look to the future with the ability to anticipate and predict what will happen tomorrow, next month, or even in six months. Through automation and advanced data analytics, leading RCM solutions drive those insights.

Readers Write: Making a Case for Digitizing HICS Protocols and Emergency Notification Processes

Making a Case for Digitizing  HICS Protocols and Emergency Notification Processes
By Dave Sinkinson

Dave Sinkinson, MBA is VP of mobile at Rave Mobile Safety of Framingham, MA.

Patient safety is and always will be at the forefront for healthcare systems. While planned events such as a move or community open house warrant and receive pre-planning by hospital officials, emergency situations can and do arise in the healthcare setting at a moment’s notice. Whether it is a global pandemic, natural disaster, system malfunction, or a violent incident, hospitals must plan for and respond quickly to adverse events, not only for the sake of their patients, but also because they have a duty of care to safeguard employees and visitors to their facilities.

That’s where the Hospital Incident Command system (HICS) comes in. HICS offers hospitals and other healthcare organizations a standardized framework for managing complex emergencies and helps health systems prioritize safety. But meeting the various HICS requirements in the midst of an already busy role can be arduous for health system emergency managers and those they rely on during crisis events. Healthcare safety practitioners are ditching outdated tools and technologies — such as printed manuals, paper phone tree lists, or legacy communication systems — in favor of digital solutions that streamline work, automate compliance, meet quorum requirements, and improve notification capabilities.

Digital transformation is certainly not new in the healthcare sector. Healthcare safety leaders have been using technology to improve patient care processes and outcomes for years, and to help with emergency notification. However, healthcare safety practitioners are realizing the benefits of using these same tools to digitize incident command protocols and to enhance operational efficiencies.

The Mayo Clinic is using technology to tackle the manual, time-consuming tasks on their HICS to-do list. Their automated approach to industry compliance is not only ensuring that all HICS team members are on the same page, in real time, it is ticking the box on staff accountability, notification, and reporting. Emergency management professionals at the world’s top hospital recognized how unrealistic it was for key personnel to access hard copies of crisis plans with detailed responsibilities or to search for materials in times when seconds matter. They digitized safety protocols, resources, and benchmarks in a handy, one-stop app that not only helps them to accomplish necessary HICS steps, but allows them to do even more, for example, further leveraging the Common Alerting Protocol (CAP) for a more integrated approach to safety.

By automating HICS activations, healthcare safety professionals can lay out emergency response plans in the order they need to be carried out, manage permissions, reassign responsibilities if they are not undertaken swiftly, and notify certain audiences about an event unfolding and steps that need to be taken. Technology also captures important data including when an emergency alert was sent, who received important messages, and which HICS team members performed emergency response actions.

Health systems are also tapping into these tools for non-emergencies. They are being used to communicate about staffing shortages and to share severe weather updates that may impact employees coming to work or leaving their shift. They are also being used more often as digital resource centers. In the past, it may have been sensible to house emergency preparedness and response materials on a hospital website or intranet portal, but when you consider how many of us are tethered to our phones these days, it just makes sense to prioritize safety apps.

As with anything worthwhile, it is not simply a matter of building it and they will come. Hospitals must consistently communicate about safety tech solutions via signage, during meetings, and as part of staff onboarding to raise awareness and encourage usage during crisis situations and as part of the health system’s engagement culture. They must commit to training staff at different intervals throughout the year so that personnel can take an active role in their own personal safety by using anonymous tip-to-text technology and two-way communication components, or simply just so they know where to go for important hospital updates. Reviewing page visits and other digital data can also help hospitals to better understand what is resonating with employees and what may need tweaking or highlighting.

Communication and collaboration are the foundation for any HICS plan. With the push of a button, safety apps can effectively connect hospital leaders with people in the trenches while simultaneously informing first responders of an emergency situation.

Readers Write: Social Determinants of Health and Interoperability

Social Determinants of Health and Interoperability
By Jada Parker

Jada Parker is a public health graduate student at George Washington University.

Social determinants of health (SDOH) have a huge impact on population health. SDOH can be defined as the conditions and environments where individuals are born, live, learn, work, play, worship, and age. Political determinants of health, such as voting patterns, government makeup, and policies, have led to SDOH and the resulting population health inequities.

SDOH can be divided into five domains: economic stability, education access and quality, healthcare access and quality, neighborhood and built environment, and social community context. These factors heavily influence health, functioning, and overall quality of life. Care management and community partnerships allow healthcare organizations to address patients’ social needs in areas such as housing, food security, financial assistance, and intimate partner violence.

Health IT can help physicians and clinicians address and understand how SDOH impact their patients’ overall health. Investments in health IT can also support care management in better addressing SDOH to improve patient health.

Interoperability across IT systems plays a pivotal role in addressing SDOH. When organizations can share patient healthcare data, community partnerships are strengthened and providers are able to provide more streamlined referrals to and better coordination with social service resource providers. Resource providers and care management teams are better able to help patients manage chronic conditions as well through care coordination with healthcare providers allowed by interoperability.

Patients who are experiencing homelessness provide a prime use case of how interoperability facilitates care coordination to address SDOH. Homelessness heavily influences overall health, as it may interfere with a patient’s ability to take their medication as prescribed. Homelessness can also result in multiple hospital readmissions for a number of reasons, including poor health management and that a night at the hospital may provide better conditions than a night at a shelter or outside.

Care coordination, improved by interoperability, allows physicians to make social care referrals and share information with necessary outside resource providers. Without interoperability between health IT systems, much of the burden of obtaining and keeping up with paper referrals and records falls on the patient.

Organizations like Administration for Community Living (ACL) provide IT solutions to support healthcare and community-based organizations partnering in order to provide social and whole-health care for the elderly and individuals with disabilities. ACL incorporates open application programming interfaces to provide resource directories through their Open Referral Initiative. These types of IT solutions streamline the referral process, improve care coordination, and strengthen community partnerships .

SDOH data gaps pose limitations to interoperability. However, there are emerging standards for using and sharing SDOH. The Gravity Project is working to define SDOH information so that it may be documented and shared across digital health and human service platforms. ONC Health IT Certification Program and ONC Interoperability Standards Advisory provide many of the current interoperability standards.

Readers Write: How Healthcare is Using AI to Address the Staffing Shortage

How Healthcare is Using AI to Address the Staffing Shortage
By Ed Ricks

Ed Ricks, MHA is managing director of healthcare consulting for Baker Tilly US of Chicago, IL.

One of the greatest challenges facing healthcare providers in 2023 is staffing shortages, particularly among medical doctors and nursing professionals. This stems from a variety of factors, including shifting demographics with an aging Baby Boomer population that is increasing the demand for medical care, a generation of nurses and doctors retiring, the education system not being equipped to create enough new medical professionals, and the demands of the profession that was exacerbated from the coronavirus pandemic.

With staffing shortages not going away any time soon, patients are continuing to experience adverse effecting, including a greater chance for errors, higher morbidity and mortality, employee burnout and dissatisfaction, and patient dissatisfaction, which create a spiraling expense to provider organizations.

Nonetheless, many experts predict that the influence of AI can help address the shortage, so I thought I would ask an AI engine to tell me a story of how AI could help. Here is the response from ChatGPT:

Once upon a time, in a world filled with endless technology, healthcare was facing a major problem. The nursing shortage was plaguing hospitals and nursing homes, leaving patients without proper care.

But then, a group of tech geniuses decided to put their minds together and come up with a solution. They created AI robots designed specifically for the healthcare industry. These robots were programmed with all the knowledge and skills necessary to be a nurse, and they could work 24/7 without taking breaks or getting tired.

At first, people were skeptical about the use of robots in the healthcare field. But as soon as the AI robots started working, everyone was blown away by their efficiency and care. They could do everything a human nurse could do, and they did it better! They never made a mistake, and they never complained about working overtime.

The nursing shortage was soon a thing of the past, and hospitals and nursing homes were able to provide the best possible care to their patients. Everyone was happy, except for the nurses who had been replaced by the robots. But they eventually found other jobs, and they were happy too.

And that, my friends, is the story of how AI robots fixed the nursing shortage in healthcare and made the world a better place. The end.

While this sounds cool, the reality is that proven methods already blend AI technology using computer vision and other input feeds with a repeatable change management framework. By doing so, providers can apply advanced analytics to determine ROI and the best impact opportunities that will lead to dramatic results for their patients and their margins.

Using this type of technology can help harmonize workflows, automate documentation tasks, and simplify communications to give nurses time back to spend with their patients. This leads to reducing friction from the act of providing care. When this type of automation is coupled with a remote nursing and care strategy across an organization with appropriate change management, the results can be far greater.

When combining the use of a proven technology platform with proven outcome driven change management strategies, health systems can see a dramatic impact on reductions in staffing costs, nursing turnover and associated costs, and patient falls. They can also see improved patient outcomes and increased staff and patient satisfaction.

We don’t have to wait for the day that we really have the sentient robots running around delivering full care in health systems. Let’s use the available processes and AI tools now to help providers make a difference on their transformational journey.

Readers Write: I Know You’re Not Thinking About Blocking Patient Data

I Know You’re Not Thinking About Blocking Patient Data
By Troy Bannister

Troy Bannister, MS is co-founder and CEO of Particle Health of New York, NY.

If you’ve worked in healthcare for 10+ years, this is probably the one hundredth time you’ll read an article about patients being unable to access their own medical data. Here’s why I think that trend might be coming to an end soon.

During healthcare’s slow digital transformation, care providers moved from fax machines to 1:1 digital pipelines to manual portal scraping tools, just to get the charts of their patients. In many instances, these processes are occurring in what are negatively referred to as data silos.

Technology solutions for improving healthcare data accessibility have evolved over the years. The legal requirements for complying with data accessibility have followed closely behind. Most clinicians are connected to nationwide interoperability networks through an EHR, theoretically giving them at least some ability to exchange patient records. Now, the US government has made it clear that their patients have the right to access their medical records in those same technically feasible ways.

Enter the Anti-Information Blocking Rule, the culmination of government efforts to legislate clinical data accessibility. Just like it sounds, its goal is to eliminate practices that interfere with the access, exchange, and use of electronic health information.

Whereas HIPAA has long made it clear that individuals can request their own records in paper format, information blocking rules theoretically give patients access to the same advanced Health Information Networks that care providers use to digitally exchange data.

The Office of the National Coordinator for Health IT (ONC), which sets the rules for information blocking, is working particularly hard to prevent cases where an individual is arbitrarily blocked from access to their own personal health information.

Despite ONC’s intentions, repercussions for information blocking were nonexistent. For that reason, healthcare organizations have continued to drag their feet when it comes to allowing patient data exports.

I’m here to spread the news that information blocking is coming to an end. As of October 2022, the HHS Office of the Inspector General began collecting reports of information blocking on its new online portal, with a mandate to issue fines of up to $1 million per violation. It is no longer in question that healthcare organizations will be held accountable unless they improve patients’ access to their own data.

Information blocking regulations don’t have any health IT loopholes. Providers can’t implement patient-only release delays, turn information into an unreadable format, or seek other ways to water down the rule’s provisions. Generally speaking, EHR vendors, Health Information Networks, and provider organizations must release the entire HIPAA-established designated records set of electronic health information (EHI) to a patient upon request.

In other words, if information exchange is doable for doctors, it’s doable for patients too. Information must be in the manner a patient initially requested. That could entail release over the same efficient digital channels, including APIs, that clinicians have access to.

The lack of access to clinical data at scale remains a core problem for US healthcare that can be linked to many of our system’s inefficiencies. These issues have a fundamental impact on healthcare costs, care quality, and ultimately on patient outcomes. Stakeholders cannot continue to wait for healthcare organizations to make their data-sharing preparations. Information blocking is no longer an acceptable policy, and yet we see it every day.

Ahead of the October 2022 information sharing deadline, there were concerted efforts from several healthcare organizations urging HHS to postpone enforcement, and not for the first time. However, regulators felt there was too much at stake to keep patients and digital health pioneers waiting any longer. Information blocking rules have survived multiple presidential administrations, and there’s bipartisan agreement that they are here to stay.

In reality, not every health system is at the same level of readiness when it comes to anti-information blocking compliance. Patient access to EHI has been a complicated task for many healthcare institutions, especially those that are not prepared to share patient data electronically. Many organizations are scrambling to find their own tools to support such efforts.

Fortunately, the technical challenges of anti-information blocking compliance are addressed by the 21st Century Cures Act, the law which led to information blocking rules in the first place.

The Cures Act aims to increase innovation by fostering an ecosystem that supports the development of data-driven applications. The rule also calls on the healthcare industry to adopt standardized APIs, which will help allow individuals access structured EHI using smartphone applications securely and easily. From new health tools to transferring records between providers, information blocking rules will help patients to take greater ownership of their care.

“In 2023, the vast majority of docs and hospitals will have FHIR APIs live,” Steven Posnack, the Deputy National Coordinator of ONC, predicted last month. With the ONC incentivizing this change, digital health organizations should urgently consider a single, comprehensive API that enables a seamless data sharing experience for institutions of all shapes and sizes. Integrating a pre-built API lets providers retrieve medical records in just a few clicks, eliminating reliance on faxes, portals, and other tired forms of data exchange.

For large organizations that support value-based care models, being able to work with patient health records at scale lets providers proactively address patient needs. This is especially critical when it comes to evaluating patients with chronic disease and comorbidities, leading to reduced readmissions. For example, on an ongoing basis, an API can help kidney care organizations that track glomerular filtration rate (GFR), endocrinologists who chart A1c values, and cancer care institutions that research case histories. In these instances, the ability to easily query patient health records allows healthcare providers to more efficiently and effectively care for their patient populations.

Moving ahead, digital organizations can look forward to obtaining data quickly and easily, powering tools that deliver more effective care. But it’s not just the data itself that matters; it’s how you get it. Leveraging advanced technology like a single API helps healthcare organizations and their patients tap into their health history when they need it.

Readers Write: For Safety’s Sake, Healthcare Must Address Its Patient Matching Problem

For Safety’s Sake, Healthcare Must Address Its Patient Matching Problem
By Gregg Church

Gregg Church is president of 4medica of Marina del Rey, CA.

Imagine if you log into your bank’s website to conduct a transaction, only to find that the bank can’t match your identity to your account. Not only are you unable to complete your transaction, you can’t even access your own information.

You rightfully would complain, and the bank almost certainly would move quickly to resolve the issue because, (a) it’s clearly unacceptable, and (b) the bank wants to continue benefiting from providing you with financial services.

Yet patient identification matching problems still proliferate in healthcare and are a major contributor to data integrity issues within electronic health records (EHRs). Average duplication rates among health organizations in America still range between 10% and 20%, with some duplication rates reaching as high as 30%.

At the 20% rate, this means one in five patients are at risk of having their medical records either duplicated or overlaid (when one patient’s data is placed in another patient’s medical file). It’s hard to imagine a bank or its customers tolerating a 20% error rate in customer records.

Wrong medical records accessed by providers and care team members could easily result in a wrong patient diagnosis, wrong medication prescribed, wrong lab test performed, wrong procedure or surgery conducted, and perhaps death due to a misdiagnosed condition. The problem is real, and the number of duplicate patient records is expanding as more clinical data is being moved digitally and shared across networks by hospitals, health systems, health information exchanges, labs and clinics.

What can healthcare organizations do to reduce patient identification matching problems and improve overall health data quality? Here are three things that could help healthcare organizations improve patient matching.

Standardize how data is collected at the point of care

Patient identification problems most commonly originate at registration. Busy staffers may make mistakes when entering data manually, or a lack of identifying information prompts the intake worker to create a new patient record, which can become a duplicate. Bad data can remain in an EHR for years, unbeknownst to clinicians or patients.

However, even if a healthcare organization is able to standardize data collection internally, other organizations with which they exchange data may have different processes, coding and data collection standards. The inevitable result for all stakeholders is low-quality data. Intelligent technologies such as artificial intelligence (AI), machine learning (ML) and referential matching can be used to identify and correct errors in patient data.

Patient ID to verify correct patient to medical record

Provider organizations lack a simple way to accurately identify patients. They are forced to rely on a combination of driver licenses, home addresses, Social Security numbers, phone numbers, and other non-medical identifiers. But what happens when a patient changes addresses or phone numbers? That’s when you see frustrated frontline staffers defaulting to creating a new (and duplicate) record for the patient.

A unified, single patient identifier would help resolve this problem. Unfortunately, a HIPAA proposal calling for the creation of a unique patient identifier (UPI), has been stalled by lack of funding. Until there is national patient ID, healthcare organizations must rely on technology to improve patient matching and mitigate related safety issues.

Data governance standards

Data governance is a framework for healthcare organizations to capture, process, normalize, use, store, and dispose of patient data. By consistently applying best practices to data, healthcare organizations can help ensure the accuracy of records in the EHRs and clinical systems is never comprised.

Effective data governance benefits healthcare organizations and patients in several ways. It improves the patient experience, leads to better clinical outcomes, and reduces healthcare costs through increased efficiency and better resource utilization. Finally, data governance can increase the value of a healthcare organization’s data because the governance process has improved its quality. This makes the data more attractive to prospective buyers such as pharmaceuticals and health policy researchers.

Accurately matching patients to their medical records is a daunting challenge to healthcare organizations as the volume of patient data – and the number of sources – continues to explode. Collecting and organizing patient data in a more standardized way will enable providers, labs, and other stakeholders to better serve patients while lowering costs and increasing the value of their data.

Readers Write: Social Care Help Shouldn’t Come at Social Cost: Why Dignity and Ease Should Be at the Heart of Modernizing America’s Safety Net

Social Care Help Shouldn’t Come at Social Cost: Why Dignity and Ease Should Be at the Heart of Modernizing America’s Safety Net
By Jaffer Traish

Jaffer Traish is COO of Findhelp of Austin, TX.

The Safety Net

Social safety nets are different in each country. Some focus on poverty alleviation, economic mobility, or disaster relief. The World Bank has estimated that safety net programs have helped 36% of the poorest in the world escape extreme poverty.

In the US, we have seen federal administrations strengthen and weaken safety net funding over decades. The history of social safety nets in the US has been shaped by voluntarism, the notion that the voluntary actions and agreements undertaken by private charity and industry are preferable to state-mandated social welfare programs.

Nonetheless, the US has tens of millions of vulnerable people looking for services. 

This is a breakdown of healthcare specific needs after analyzing 10% of searches from a population of 16 million Americans. 

COVID-19 placed a spotlight on the vast array of needs. Our public benefit data mirrors what we heard and saw of the struggle for individuals and families.

Policy Winds

With the increasing awareness of social disparities and impact on health, we now see many major policy changes:

• ACO REACH Model. This model began on January 1 and includes focus areas on equity, access, and community health. There are reimbursement calculations and withholdings related to the area deprivation index (API) and SDoH quality measures.
• Joint Commission. New rules in effect January 1 include identifying a system leader who is accountable to address disparities in the patient population, as well as social needs screening and the sharing of community resources.
• NCQA. They released new HEDIS measures, including the SNS-E measure related to assistance for plan members needing food, housing, and transportation.
• CMS guidance letter. CMS issued a guidance letter on January 4 to state Medicaid Directors related to ILOS (In Lieu of Services) for Medicaid Managed Care, which relates to the Cal-AIM California waiver and many future waivers. The guidance strongly emphasizes the importance of measuring utilization and impact of non-traditional services such as social supports.

Private Company Technology is Accelerating Modernization

With any emerging market, we’ll see some companies taking advantage for short-term profit, multi-million dollar software costs, and a story of hype that fades post contract signature.  We will see others that aim to maximize funding going to communities, to capacity building, and to community health worker staffing. Government and private sector buyers must be well educated to avoid the expensive shiny object that doesn’t deliver.

The good news is that healthcare leaders have long had a vision for what’s possible, including Judy Faulkner and Epic, where social services digitization is found in her original business plan.

SDoH is in the spotlight, with 80 bills proposed in Congress and $90 million of requested funding by states related to social care. Requests fall into several categories,including Medicaid waivers and federal match money.

We have the opportunity to build private-public partnerships that align on key principles. Education of key stakeholders is essential.

Influence 

People go to helpers to get help. Those helpers might be a librarian, a pastor, or a neighbor. Those helpers may also be care coordinators, social workers, and hospital discharge planners.

State government can heavily influence the funding for services. Medicaid directors, Health and Human Services secretaries, commissioners, and deputies control how money is spent through Medicaid waivers, MCO contracting, non-profit capacity grants, and more. There are tough decisions to make, and there is incredible respect for people in these roles who are lobbied heavily by industry.

A large influence on these decisions is improving overall health and driving down the cost of healthcare. We all know over the last two decades of electronic health record implementations that technology alone is not the answer. Technology enables us to work more efficiently and more collaboratively, though it doesn’t solve governance, community engagement, or equitable service delivery.

State agencies want to understand the needs of their populations, where people are going to receive help, the services delivered, and when possible, the correlations with healthcare cost and clinical outcomes.

Some vendors promise a panacea of results via a top-down monopoly that goes something like this:

• Mandate use of a specific, single technology system.
• Force communities to use one system.
• Force non-profits into a contract.
• Force a per-user license model so the vendor makes more money with every user whether they adopt or not.
• Force a one-time consent so the vendor owns data sharing.
• Restrict federal dollars being used outside of this system.

This sounds like a good way to make a vendor rich and to skirt consumer privacy, interoperability, and non-profit autonomy.

The Choice

Procure one technology system with a hand in the face of private sector procurement or empower the community and health systems to choose the tools that make the most sense for them. Require that they report the data using standards and even certifications as the Office of National Coordinator (ONC) has supported for years.

Dignity and Ease

At the heart of this work is privacy. Imagine that you signed a single consent form for your healthcare provider to put your information into a system to facilitate a referral to a local food pantry or domestic violence shelter. But with that one action, you’ve granted more than 120 non-profit organizations the ability to access all of the personal financial, social, and medical data you reported. This is happening today because social care privacy standards haven’t kept pace with healthcare. People expect that their sensitive information will only be visible to the organizations and people they choose. Too many are blindly forced into one-time, all-in consent models in exchange for getting the help they so desperately need.

Healthcare, government, and non-profit leaders must improve safeguarding personal information by building a consumer-directed privacy approach to social care technology. Last year, the State of New Hampshire adopted a first-in-the-nation privacy protection law that established a policy framework to prioritize a person’s right to informed consent when seeking social services.

The Future of the Safety Net

• Imagine a future where applying for state benefits is a dignified, fast, digital process, not a paper process with a custom system.
• Imagine a future where a person in need can log in to a patient portal and see covered benefits, whether value-added, supplemental, community bank funded, or other non-profit led.
• Imagine a future where payers can see member needs and where their member has received help (with permission) anywhere in the country, and (with permission), intervene to prevent costly chronic or other clinical adverse events.
• Imagine a future where social workers, discharge planners, and other helpers simply use their EHR or care management system to make referrals and orders without worrying about which vendor is powering the SDoH network, a true API network model.

This is all possible. We should not be asking governments to pick winners and then learning too late about the risks to privacy and dignity taking place behind a curtain.

With network effects, community engagement, and trust building, the outcomes that we all want to see are possible. We can enact policies that do not create data silos or create monopolies with false promise. The right interoperability policies will create innovation in health and human services that are ubiquitous in every other sector.

Readers Write: What Health IT Companies Can Expect in 2023

What Health IT Companies Can Expect in 2023
By Jodi Amendola

Jodi Amendola is founder and CEO of Amendola Communications of Scottsdale, AZ.

My crystal ball says tighter budgets, LinkedIn, and more targeted, integrated campaigns.

The beginning of a new year provides an irresistible temptation to make predictions. Unlike the ancient Romans, we don’t look to the flight patterns of birds to foretell the future, but base our predictions on what we see in the industry and the economy, what we hear from clients, technological developments, etc. Here are my predictions for what to expect this year in healthcare/health IT.

A tumultuous economy

Economists have been arguing for months about whether the US is headed toward a recession and, if so, how severe it will be. I don’t pretend to know the answer, but I do expect 2023 to be challenging for the healthcare and health IT industry given the challenges faced by providers and payers. Hospitals are still recovering from the COVID-19 pandemic and coping with rising expenses, ongoing staffing shortages, and continuing capacity constraints. In response, health systems have restricted services, laid off employees, closed departments, and even shut down entire hospitals.

However, systems are also investing in new digital technologies that allow them to operate more efficiently and expand care models, such as remote and virtual care, in the face of these challenges. The vendors who sell these products and others that support the digitization of healthcare are ramping up marketing and PR efforts to position themselves as the solutions to help systems clear these barriers.

To best reach their target audiences, what I am seeing for healthcare and health IT companies are budget considerations, such as whether to invest heavily in trade show marketing or if those dollars should be reallocated to more targeted account-based marketing (ABM), digital marketing, or integrated marketing programs.

Twitter down, LinkedIn up

I think 2023 will be a critical year for Twitter as an advertising vehicle and, quite possibly, as a viable social media platform. The uncertainty over Elon Musk’s takeover, the departure of so many staff, and Musk’s controversial decision to largely stop moderating tweets and to welcome back accounts that had been banned for misleading or false content has made brands understandably wary of being associated with Twitter.

According to a recent Media Matters report, half of Twitter’s top 100 advertisers have stopped promoting on the platform, brands which have accounted for nearly $2 billion in advertising since 2020. Some publicly announced their break with Twitter, while others have quietly stepped away. And Musk’s myopic claim that companies who choose not to advertise on Twitter are somehow engaging in censorship or violating free speech principles is not the way to woo them back. Brands have every right to avoid unnecessary and unwelcome controversy when choosing where to advertise.

By contrast, we’re seeing heightened interest among clients in LinkedIn as a marketing and advertising platform. The oldest of the social media platforms, LinkedIn has evolved from a glorified jobs board to a place where companies — including healthcare providers and payers — research vendors, network, and promote themselves.

LinkedIn content is becoming richer and more interesting as well. Yes, there are still plenty of photos of people sitting in hotel ballrooms captioned: “Excited to be attending the annual Widget Trade Show in Walla Walla,”, but creative brands are using it to tell stories and connect with target audiences on a deeper level. To encourage this, LinkedIn is adding content-friendly features, such as Creator Mode, Auto Embed, and image templates.

As LinkedIn becomes more important and versatile, brands would be wise to re-evaluate their approach to the platform with an eye toward expanding their content to engage target audiences beyond what they’ve traditionally posted.

Marketing and PR integration

It’s long been a good idea to integrate PR and marketing, but at many health IT companies, they are still separate silos. With tight budgets for both likely in 2023, it’s never been more important that they work closely together to achieve shared goals, measured using agreed upon performance metrics.

Comprehensive, integrated marketing programs that include webinars, events, digital marketing, and account-based marketing, in addition to media relations, social media, and thought leadership activities, will deliver better returns than separate, disjointed campaigns and help rise above the noise.

That also supports another 2023 trend: companies focusing more on strategic messaging and marketing to reach specific prospects. In a tough economy, it makes sense for businesses to focus on satisfying their most important accounts and landing the whales that could make the difference in a difficult year. Making the best use of tight resources and budgets through integrated marketing and PR campaigns can make all the difference.

Marketing resolutions

January is a great time for making resolutions, as well as predictions. In anticipation of what is likely to happen this year, here’s what healthcare and health IT companies should do:

• Look for new ideas and partnerships that work within their budgets while continuing to deliver great ROI.
• Integrate marketing and PR. Synchronizing efforts delivers a greater punch than pursuing separate tracks. If 2023 does prove to be a difficult year economically, it’s even more important to deliver a strong, coordinated message.
• Take creative risks. One of the great things about marketing and PR is that it’s not static; there’s always a new medium, platform or strategy to explore. This is going to be a good year to go exploring.

Whatever your resolutions, I hope you achieve them. Here’s to a happy and fulfilling new year.

Readers Write: Netflix and Reed Hastings: Ghost of Christmas Past

Netflix and Reed Hastings: Ghost of Christmas Past
By Chuck Dickens

As the countdown to Christmas 2022 ticks away, Reed Hastings sits alone in the dim basement of his parents’ house, lost in the immersive world of video games. But the monotony of his day job at Blockbuster weighs heavy on his mind.

Every day, he dutifully rewinds VHS tapes and updates spreadsheets, tracking the $5 fines for customers who neglect to rewind their rentals. It’s a tedious task, but it’s a necessary one. After all, late fees and rewind fines are the company’s second-largest source of profit, surpassed only by the seemingly endless stream of “Die Hard” rentals that pour in every holiday season.

But just as Reed finishes his fifth cup of coffee, something strange happens. A shimmering light appears out of nowhere, coalescing into a humanoid form that seems to float effortlessly in the air. For a moment, Reed is startled, but then he recognizes the ghostly figure as the Ghost of Christmas Past, as depicted in countless retellings of “A Christmas Carol.” With a jolt, he’s suddenly transported back to 1997, reliving the excitement of a disruptive new idea that once seemed destined for greatness.

After cashing in on the sale of his software company, Reed was on the hunt for his next big opportunity. He wanted something innovative and disruptive, and he had his sights set on the movie rental industry.

In 1997, movie rentals were a major form of entertainment in the United States, with most employers offering them as a employment benefit and the government eventually extending the perk to everyone over the age of 65. As a result, movie theaters dwindled in number, and the rental market was dominated by a few large players such as Blockbuster and Hollywood Movies.

But after paying a hefty late fee to Blockbuster for “Apollo 13,” Reed began talking to his friend Marc Randolph about the frustrating experiences they and their friends and family had had with the rental giants. The local store had limited titles, and the popular ones were often unavailable. Even though movie rentals were offered as a benefit, the co-pay was still substantial, and if customers wanted to drive to a different location to find a specific movie, they had to pay extra out of pocket.

Determined to bring a better rental experience to customers, Reed and Marc came up with the idea for Netflix. The company that would offer DVDs by mail for a low, fixed monthly fee, with no late penalties, a vast selection of movies to choose from, and fast turnaround time. They were confident that their service would revolutionize the industry and put an end to the frustrations of traditional rental models. They were so convinced of the superiority of their service that they invested a large part of their own money in addition to VC funds to get the company off the ground.

But by next Christmas, as Reed and Marc struggled to scale up their business and delved deeper into the movie rental market, they discovered a number of strange quirks and injustices.

The compensation paid to movie industry professionals was set by a committee (Relative Video Unit Update Committee – RUC) that was largely composed of people involved in a genre called “film noir,” who claimed that these films were the most expensive to produce and should therefore be paid the highest rates. This left other genres such as romantic comedies, which were popular with customers but low on the payment scale, struggling to find funding and talent.

Another example was that every time a movie was rented, Blockbuster used a special code to designate the genre of the movie and other details. These codes eventually determined who got paid how much for the rental. Not only did the American Movie Association (AMA) controlled who got paid, but they charged everyone a licensing fees to use the code set itself in a classic case of double-dipping.

Additionally, the distributors were owned by Blockbuster and Hollywood Movies. They negotiated with movie studios and employers to determine which movies would be made available and at what rental price. Since everyone got a percentage of the rental price, lowering the rental price wasn’t in anyone’s business interest collectively. Further, government was not allowed to negotiate late fees and penalties, as it was prohibited by law (American Movie Association and American Hollywood Association had strong lobbying arms).

From the very beginning, Netflix faced an uphill battle in convincing consumers to sign up for its flat fee subscription model. Many people received movie rental benefits through their employer and weren’t willing to pay for Netflix out of pocket. And while the company’s vast library and lack of late fees were appealing, people were hesitant to trust a new company with such a crucial part of their entertainment.

Netflix tried to appeal to employers, offering to provide subscriptions as a benefit to employees, but benefits managers were resistant due to long-term contracts with established rental companies like Blockbuster and Hollywood Movies. As for other charges, such as late fees and facility fees — to compensate them for higher operational expenses of a physical location – Blockbuster and Hollywood Movies had arranged it so that those charges were paid directly by the employer and people never perceived those being charged to them, even though indirectly, it was all coming out from their paychecks and taxes.

Undeterred, Netflix approached Blockbuster and Hollywood Movie (because everyone said that that’s where the money was) with the idea of using their advanced technology to lower the cost and improve the availability of movie rentals. But they were met with laughter and derision, as the traditional companies saw higher costs as a way to increase revenue.

Despite this, Reed and Marc remained convinced that technology could be a game-changer for their company. So when their engineering team came up with the idea of streaming movies directly into living rooms all over the country, they were thrilled. However, they quickly realized that employers and the government wouldn’t pay for these streaming movies. Regulations prohibited them from streaming across state lines, requiring them to set up streaming centers in each state and significantly increasing their costs.

But even with these setbacks, Reed and Marc were undeterred. They saw the potential for incorporating AI into their streaming service to create an even more attractive offering. As Christmas Eve 2007 approached, they had signed up a few thousand direct subscribers, mostly in affluent communities, and a few progressive employers were conducting pilots with their service. Despite the challenges they faced, they remained convinced that they were on the cusp of something big.

Despite its advanced technology and AI, Netflix struggled to overcome the stranglehold of monopolies and regulations in the movie rental industry. For over two decades, the company barely made a profit and continued to hemorrhage money.

But in the winter of 2020, everything changed. A global pandemic swept the world, forcing people to stay at home and closing down stores like Blockbuster and Hollywood Movies. In response to widespread discontent, the government allowed nationwide streaming of movies and set up a system to pay for it. Suddenly, Netflix was a household name, valued at billions of dollars despite still not turning a profit.

However, the success of the streaming service sparked a wave of competition, including from Blockbuster and Hollywood Movies, which created their own streaming video service with the help of their legacy IT vendor. As the pandemic waned and the traditional players saw their core business model threatened, they worked to regain the upper hand. They pressured the government to reinstate state-level restrictions on streaming and encouraged the movie industry to charge a “streaming fee” for on-demand movies.

By Christmas 2021, Netflix was deep in debt and Reed and Marc were forced to liquidate the company to avoid personal bankruptcy. They both moved back in with their parents and took jobs at Blockbuster and Hollywood Movies, which were thriving again thanks to government loans during the pandemic.

As he headed off to work at Blockbuster, Reed couldn’t help but wonder why the movie rental industry couldn’t use technology to improve customer service and reduce prices like other industries such as healthcare. In fact, at every innovation forum, people kept asking him, “Why can’t movie rental business be innovative like healthcare and be agile at adoption of technology?”

“Because healthcare is not insanely regulated and doesn’t have government and private monopolies to distort the market and incentives like the movie rental business,” he muttered to himself, recalling the Ghost of Christmas Past’s explanation. And with that, he set off for another day at the grindstone.

Readers Write: It’s Time to Make Price Transparency Data Useful

It’s Time to Make Price Transparency Data Useful
By Lewis Parker

Lewis “Lew” Parker, MSIS, MBA is SVP of engineering and CTO of Arrive Health of Denver, CO.

The price transparency movement in healthcare is growing, supported by factors including consumer demand and rules from CMS requiring health plans and hospitals to post pricing information for covered items and services.

It’s good that organizations are complying with these regulations by uploading detailed machine-readable documents to their websites. However, it will only be great when this overwhelming amount of information is digested, personalized, and presented in a way that enables decision-making for all parties involved, at the right time.

These moments include when providers are engaging with patients and making care decisions, when care team members are helping patients manage affordability barriers, and when patients are trying to find lower-cost care options.

How do we get to this future state, when data drives behavior change in a way that impacts affordability, accessibility, and outcomes? Here are three things that must happen to make price transparency data useful.

• Translate the data. The US healthcare system is highly complex, and multiple data sources are used when completing a medication order: electronic health records (EHRs), drug databases (First Databank, Medispan, etc.), and insurance plan design and patient accumulators (plans, PBMs, and payers). There are rarely consistent fields, and even standards such as those provided by NCPDP may not go far enough to create a seamless prescribing experience. This is why the first step to price transparency must be translation.
• Make it simple. New tools must be simple and integrated into existing workflows if they are going to be adopted, especially considering growing provider burnout worries. Neither consumers nor providers are accustomed to pharmacy benefit jargon. Real-time cost and coverage tools must go beyond unifying and normalizing content from disparate sources by translating that information into messages that are meaningful to the appropriate audience. For example, providers, care teams, and patients all want to see different pricing information. The provider may want to see lower-cost clinically equivalent alternatives, the care team considers options that avoid a prior authorization (PA), and the patient wants to know how much they will owe at the pharmacy counter. Price transparency solutions need to account for this and deliver useful and actionable information to each individual.
• Build insights. Price transparency data will become its most powerful the more it is understood. Analytics tools can identify where opportunities exist to maximize price transparency data in clinical decision-making. Robust reporting and user-friendly dashboards show which providers are engaging the most (or least) with cost and coverage data and which are ultimately making decisions — like switching to a lower-cost medication or selecting a clinically relevant option that doesn’t require prior authorization — based on that data. Insights can also highlight which medication classes have available competitive options, and where there are barriers to medication switches.

Achieving price transparency in healthcare is challenging but possible. With all types of costs increasing, not just healthcare costs, now is the time to go beyond the bare minimum and invest in tools that will make price transparency data usable and impactful for all stakeholders involved.