The Current State of Interoperability in Healthcare

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Interoperability in healthcare refers to the seamless and secure exchange of electronic health information between authorized users of such information. In other words, it is as much about sharing, as it is about protecting the privacy of patient health data. Healthcare interoperability is complicated by the sheer number of players that might be involved in any given health-related transaction (e.g., providers, payers, consumers), all of whom may be utilizing disparate and potentially inconsistent systems and structures of data. Accordingly, to facilitate the seamless transfer, exchange, and protection of personal health information, it must occur at four distinct “levels” that have been defined by the Health Information and Management Systems Society:

  • Foundational – which addresses inter-connectivity requirements within systems themselves to communicate data between/among one another. 
  • Structural  – which defines format, syntax, and organization of data necessary for sharing and exchange.
  • Semantic – which defines underlying models for data, including standardized codes such as those established by HIPAA, enabling shared understanding between users of disparate systems.
  • “New” Organizational – which is akin to “information governance” (framing the overarching policy for handling all information received or generated by an organization).

In late 2015, the Office of the National Coordinator for Health Information Technology (ONC) released what it refers to as a roadmap for enabling individuals and organizations to securely share health information with any provider—with the goal of  supporting “a wide range of health and wellness functions, which will ultimately benefit patients and their families.” In so doing, ONC essentially called on all health IT stakeholders to develop policies and technical approaches to help achieve the ability to share information seamlessly. As of March 2019, the federal government has invested $36 billion in promoting the digitization of health information. In 2017 alone, hospitals spent nearly $25 billion globally on electronic health records, and such spending is projected to increase to $33 billion by 2023.

Yet according to the Centers for Disease Control and Prevention, the percentage of office-based physicians using a certified EHR system is not even 80 percent.And despite all the spending, a 2018 survey of nearly 600 primary care physicians (PCPs) conducted by The Harris Poll on behalf of Stanford Medicine indicates providers have yet to see significant value in their investments of money, time, and effort in adopting and using EHRs.

Here are the key findings from that poll:

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Healthcare’s most significant inefficiencies all have in common the failure to meaningfully leverage patient health information. The effect is increased cost yet eroded quality of care. This failure directly impacts patient care and ultimately public health. However, it also indirectly affects public health, by, among other things, directly obstructing an efficient claims process. In our next post, we’ll be exploring precisely how one small error in coding can have a big impact on the claims process. Can’t wait? Check out the full story in our Q4 Edition of PluggedIN: Tell Us Where It Hurts: How Tech Can Heal Healthcare.

 

 


Sources:

https://www.hipaajournal.com/onc-10-year-interoperability-roadmap-8136/

https://www.hipaajournal.com/onc-10-year-interoperability-roadmap-8136/

https://khn.org/news/death-by-a-thousand-clicks/

https://www.healthcarefinancenews.com/news/ehr-investments-slowing-down-hospitals-cite-high-costs-study-finds

https://www.cdc.gov/nchs/fastats/electronic-medical-records.htm

https://med.stanford.edu/content/dam/sm/ehr/documents/EHR-Poll-Presentation.pdf

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One Small Coding Error, One Giant Problem for Public Health

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Although one of the goals of coding is streamlining the claims process, coding errors can lead to delays in the claims process, which can kick of a daisy-chain of consequences that can significantly and negatively impact public health. Delays in the claims process are costly to the payer. They also lengthen the payment cycle for providers and create cash flow issues for patients, creating economic hardship for all. Here’s how that might work in a given situation:

→ Denials

When delays turn into denials, costly appeals by the patient and/or the provider may follow.

→ Patient Default

Denials can lead to patient default on medical bills. During 2016, more than 66% of patients defaulted on bills of $500 or less. By 2020, that number could increase to 95%.

  Increased Administrative Expenses

Patient default can lead to costly collection efforts. A large portion of provider administrative expenses can be attributed to provider collection efforts, according to Suresh Yannamani, Exela’s president.

→  Increased Prices

One of many reasons healthcare providers charge as much as they do is to cover the cost of patient defaults and uninsured patients. What’s the alternative? Going out of business altogether?

→  Physician Burnout

“Physician burnout” is now a diagnosable illness caused by excessive workloads and administrative burdens, which are exacerbated by SNAFUs in the claims process.

→ Diminished Access to Quality Care

Physician burnout leads to physicians exiting the provider space, ultimately diminishing patient access. It also interferes with physicians providing the highest quality of care.

→ Erosion of public health

Diminished access to healthcare is known to directly negatively impact public health. For example, it’s associated with poor management of chronic disease, increased incidence of preventable diseases, and premature death.

Of course, coding errors can’t be singularly blamed for all of healthcare’s woes. As discussed earlier, it’s just one of many examples of the way effective healthcare information management has become pivotal to public health. [In our next post, we’ll be exploring how to get started with your health information management program. Can’t wait? Check out the full story in our Q4 Edition of PluggedIN: Tell Us Where It Hurts: How Tech Can Heal Healthcare.

 

 

 

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Why is the Healthcare Industry Lagging in Digital Transformation?

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Inefficiencies in the healthcare industry cost the people of the U.S. around $935 billion in annual spending. That’s approximately one-quarter of all dollars spent on U.S. healthcare. The latest issue of PluggedIN, Exela’s quarterly thought leadership news magazine, was devoted to discussing the roots of those inefficiencies, and what can be done to turn things around before losing even more ground (see: PluggedIN: Tell Us Where It Hurts: How Tech Can Heal Healthcare). As the Everest Group has noted, digital transformation can address much of healthcare’s inefficiency. Yet the industry’s adoption of digital transformation initiatives has been “modest”.  It’s not there’s any shortage of transformative technology. Rather, the problem appears to be the industry’s reluctance to embrace the changes digital transformation promises.

So, why the reluctance? Experts pose a variety of explanations, but most boil down to one of the following:

 

The misconception that medical consumers aren’t chomping at the bit for change

Because relatively few patients seem to be jumping on board with digital health services, many healthcare executives believe patients simply aren’t interested in those services. In fact, the reason patients are slow to adopt digital healthcare is the services being offered aren’t actually services they’re interested in—or worse, they’re of poor quality. If better digital services were offered, it’s entirely possible adoption rates would increase.

The “go big or go home” myth of healthcare transformation

In many industries (and not just healthcare), there’s a misconception that digital offerings have to “dazzle.”  In reality, according to research conducted by McKinsey, healthcare consumers would be happy with just the basics, starting with simplifying navigation of the increasingly complex healthcare system.

Learn how Exela’s Patient Portal improves the experience for payers and providers, along with medical consumers, by simplifying such routine tasks as patient registration, eligibility verification, billing, and payment

The provider shortage

“In the face of the physician shortage in the U.S. doctors don’t have time to trade out their proven workflows to take a risk on a solution that may or may not be successful, and will almost certainly take time to learn and implement into their practice,” notes HIT Consultant,  which also notes the way around this isn’t continuing to do things the same way they’ve been done all along but perhaps pushing for changes to the payment structure so that providers don’t feel pressured to pack their daily schedules with patient appointments.[1]  In the meantime, it may be worth thinking about starting with small changes that have the potential to save providers time—if not by scheduling fewer appointments, then by simplifying “time-sucking” administrative tasks such as medical billing. Exela’s Medical Billing solutions are designed to save time while eliminating errors, reducing recovery times, and improving recovery rates.

 

[1] https://hitconsultant.net/2019/12/04/digital-transformation-in-healthcare-not-happening/

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How the FDA is Using Data Analytics to Address the Nation’s Opioid Epidemic

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Every day, more than 130 people in the United States die as a result of opioid overdose. The enormous human cost is just the beginning, however.[1]  The Centers for Disease Control and Prevention estimate the total "economic burden" of prescription opioid misuse in the U.S. to be around $78.5 billion a year, taking into account the costs of healthcare, addiction treatment, loss of work, and the involvement of the criminal justice system. “The opioid crisis is one of the largest and most complex public health tragedies that our nation has ever faced," FDA Commissioner, Mark Gottlieb, noted in a press release earlier this year, and overcoming it will require “innovation.” [2]

Just to be clear, Gottlieb is referring to technological innovation, including information management solution such as data unification and data analytics. The hope is that these solution swill identify social and clinical trends that may be contributing to the opioid crisis. “Waiting for the accumulation of definitive evidence of harm left us a step behind a crisis that was evolving quickly, and sometimes furtively, in vulnerable communities that were too often being tragically ignored,” Gottlieb explained.

Specifically, the FDA has plans to roll out an information management plan that leverages the sort of data unification and centralization technologies described here to facilitate data analytics designed to identify vulnerabilities to opioid misuse that may be lurking within the healthcare system and within community cohorts. Funded by a $20 million grant, the plan anticipates the creation of a large-scale data warehouse to facilitate data analytics, including predictive analytics and machine learning, to:

  • Assess geographic and demographic vulnerabilities
  • Identify trends contributing to those vulnerabilities and the epidemic at large
  • Target regulatory changes to address the vulnerabilities.

The innovations the FDA plans to deploy are in addition to innovations states and federal agencies have been bringing to bear in recent years, including the use of PDMPs (sometimes called PMPs), which stands for Prescription Drug Monitoring Programs. PDMPs collect and house information about controlled substances, to whom they were dispensed, how much, and by whom. Securely stored and accessed using circumscribed credentials, can be a powerful tool for doctors and pharmacists in identifying people who may be abusing opioids, whether intentionally or as a result of medical mismanagement or mistake.[3] For example, a 2010 study found that the use of PDMP data in an emergency room  context affects opioid prescribing behavior by providers in 41% of patients, with 61% of those representing a provider choice to not prescribe, or prescribe less of, the opiate than the provider had planned.[4]

Data management is just one of the ways technology is healing what ails the healthcare industry. For more information, check Exela’s game-changing solutions for healthcare providers, payers, and other players here.

 

[1] https://www.drugabuse.gov/drugs-abuse/opioids/opioid-overdose-crisis
[2]https://www.fda.gov/news-events/press-announcements/statement-fda-commissioner-scott-gottlieb-md-agencys-2019-policy-and-regulatory-agenda-continued
[3]http://info.iwpharmacy.com/what-is-the-pdmp
[4]https://www.ncjrs.gov/pdffiles1/ondcp/pdmp.pdf
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Large Healthcare Company Automates Accounts Payable Workflow for Huge Savings and Superb Customer Service

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CHALLENGE:

A national health care company was processing more than 50,000 invoices a month. It wanted to improve customer service and patient care across its 308 urgent care facilities. To accomplish this, the company needed to transform its paper-based Accounts Payable workflow, which was causing documents to be lost and payments to vendors delayed. AP workflows among the facilities lacked standardization, integration and visibility. And, there was no efficient system for collecting information from a large number of invoices at once. The company was also unable to find invoices when there was a discrepancy. By automating their AP process, Directors at each center could now re-focus efforts on helping patients.

SOLUTION:

To achieve its goals, this company decided to replace its existing AP process with an entirely automated workflow. It selected Exela's end-to-end cloud-based BancPay solution for its exceptional invoice management capabilities. Featuring a user-friendly interface, the solution provides easy access to invoice images for routing and approval. As an added benefit, the company's suppliers can check the status of invoice payments online, facilitating greater communication and workflow management.

BENEFITS:
  • Improved customer service through more accurate payments to vendors
  • Realized savings by reducing AP staff by six employees
  • Reallocated resources for additional customer-service initiatives
  • Increased productivity and visibility into the AP process
  • Expanded opportunities for future automation initiatives
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Applying RPA to Healthcare Data Management

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The application of a robotic process automation solution provides significant results for a large health insurance organization.

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CHALLENGE:

The decommissioning of databases that supply information to the insurance provider’s national corporate data centers required data migration and resulted in the need for multiple database searches across dozens of disparate data centers. This caused offsite direct data capture productivity to drop by approximately 30%. The customer required productivity improvements and the avoidance of errors associated with manual migration.

SOLUTION:

Exela utilized robotic process automation (RPA) for direct data capture deployment to connect disparate data systems. This solution automates the extraction of all provider information from the customer’s system into a unified spreadsheet for easy lookup. A software bot was deployed to update new provider information daily. All information was uploaded into a single view within the Exela RPA Design Studio interface.

BENEFITS:
  • 60% volume direct data capture edit utilized RPA

  • 35% productivity gain (from 15 claims per hour to 20+)

  • Simplified data storage and retrieval

  • Reduced workforce demand

  • Flexible, scalable bot deployment

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Why Data Analytics Can Manage Healthcare Administrative Waste

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If you’re an American, you’re probably worried about the affordability of healthcare. In fact, 80% of Americans surveyed in a recent Gallup poll admit to worrying at least a fair amount, with 55% saying they worry a “great deal.”[1] While it’s not wrong to worry about healthcare’s affordability, the issue isn’t completely out of our hands. While the high cost of care is driven by a variety of factors, one of the most significant is healthcare administrative waste. The good news, however, is that the problem isn’t anything data analytics can’t address.

 

Administrative expenses (i.e., those not directly associated with providing goods and services to people in need of care), amount to anywhere from 15 to 30 percent of medical spending, according to Harvard economist, David M. Cutler, PhD.[2] The bulk of those expenses is spent in connection with billing and payment by providers.

 

While some of that expense can be attributed to provider efforts to collect payment from insurance companies, much is attributable to efforts to collect accounts receivable from patients, observes Exela’s president, Suresh Yannamani (you can learn more about Exela’s leadership team here.). During 2016, more than two-thirds of patients defaulted on hospital bills of $500 or less, and by the year 2020, that number could increase to 95%.[3]

 

While one might argue if healthcare weren’t so expensive, consumers wouldn’t have so much trouble paying for it, one reason healthcare providers charge as much as they do is to cover the cost of treating patients who can’t pay for services rendered. After all, if a provider has no way to cover the cost of treating patients who can’t pay, they risk going out of business (i.e., unable to care for any patients at all).  In other words, we’re looking at a vicious circle, where consumers can’t afford to pay for their healthcare, which further drives up the cost of healthcare, thus making it harder for consumers to pay, and so on.

 

What many providers might not realize, however, is the “massive potential to collect, organize, and apply payment and patient data to accounts receivable in order to keep operations running smoothly,” Yannamani points out. Some of that data, such as patient payment history, is already right there in the provider’s possession. Once in digitized format, it’s ready for the application of programmed analytics that can help the provider determine best billing practices. For example, if data analytics reveal certain patients are more likely to wait three months before paying, the provider can decide to focus their collection efforts beginning in “month two.”

 

Data analytics can be applied to better utilize administrative time and effort in collecting from insurance payers as well. For example, if a provider sees one payer takes months to submit payments for appendectomies while another takes only a few weeks, the provider can focus immediate efforts on the latter and gear up later for collecting on the former.

 

“Too many health systems waste significant time and money burying themselves in paperwork and chasing after payments,” notes Yannamani. To eliminate the waste, “health systems must use the rich payment data they collect on every transaction to inform the billing department. With a better collections strategy, systems can streamline their accounts receivable and realign valuable resources to where they are more valuable.”

 

You can read all of Yannamani’s observations and recommendations on this topic here. You can learn more about Exela’s health information management solutions here, and Exela’s revenue integrity solutions here. In all cases, our mission is to help you identify and recover all sums due.

 

For Exela’s in-depth look at the inefficiencies that drive the Journal of the American Medical Association to estimate waste in the healthcare system to be as high as $935 billion (approximately 25% of total healthcare spending), please check out Exela’s Q4 edition of PluggedIN, Exela’s quarterly thought leadership publication: Tell Us Where It Hurts: How Tech Can Heal Healthcare.

 


[1] https://news.gallup.com/poll/248159/healthcare-once-again-tops-list-americans-worries.aspx

[2] https://www.help.senate.gov/imo/media/doc/Cutler.pdf

 

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Healthcare Solutions Suite (HSS)

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