University Hospitals Applies Homegrown Discharge Planning Workflow Solution to Opioid Prescribing | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

University Hospitals Applies Homegrown Discharge Planning Workflow Solution to Opioid Prescribing

November 1, 2018
by David Raths, Contributing Editor
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Seeks to commercialize logistics platform powering UH Care Continues
Eric Beck, president of UH Ventures

Cleveland-based University Hospitals is taking advantage of an internally developed technology platform to re-imagine the discharge process, including identifying patients at risk for opioid misuse and dependence.

Ohio has been described as “ground zero” for the opioid epidemic. According to the Ohio Department of Health, drug-related deaths eclipsed auto accidents as the state’s top cause of injury deaths in 2007 and that trend has continued ever since. Earlier this year the UH Care Continues discharge planning process was awarded $200,000 from the Ohio Opioid Technology Challenge for its technology solution to help health professionals in the fight against the opioid epidemic. 

In an interview with Healthcare Informatics, Eric Beck, D.O., M.P.H., an emergency medicine physician and president of UH Ventures, the business innovation arm of the UH system, explained the genesis of UH Care Continues and the health system’s intention to commercialize the solution.

“We began a journey earlier this year to re-imagine our care transitions process — how we get patients out of the hospital and thinking intentionally about where they go and what happens to them afterwards,” Beck said. “We were developing new roles, new processes, and new technology. One of our core tools is a logistics platform.”

Applying the platform systemwide to opioid prescribing, Beck said 18-hospital UH sought to put a reflective pause in the process to try to limit controlled substances, particularly opioids, to only the patients who really need them. There was a fair amount of inertia and “muscle memory” in terms of prescribing opioids for certain conditions, he added. In some cases, they are being prescribed as needed or prophylactically. “To the extent we can stem some of that, contain it, or add a little bit of conditionality, that was the opportunity we saw.”

The technology solution surveils patients as they are leaving the hospital, and as it identifies a patient with an opioid prescription, the pause asks if it is really necessary. Is the patient still having pain? Is it uncontrolled? To the extent that the answer is not an obvious yes, Beck said, are there alternative therapies available? “Or perhaps the patient only needs a couple of pills for an urgent issue and then they can call us for more active management of their pain.”

The platform manages both work flows and resources. “To the extent that the patient is leaving the hospital on opioids or may benefit from alternative resources, such as acupuncture or massage, how do we bring those resources to bear at the point of service?” Beck asked. “Part of the effort is trying to contain inappropriate prescriptions, but also marrying that with a set of alternative resources that the patient can be navigated to, based upon their needs and clinical condition.”

Besides triggering workflow and optionality around alternatives, the reflective pause also deploys an algorithm to risk-stratify whether the person is at high risk of becoming dependent.

“To the extent they need the opioid, let’s risk-stratify them,” Beck said, “and put them into a surveillance workflow and make sure that any excess opioids are disposed of properly. To the extent they don’t need it, let’s navigate them to something else.”

How will UH assess whether the platform is having a beneficial impact? By measuring follow-on behavior related to all opioid prescriptions, Beck explained. “Following them into post-acute space, did they take the opioid? Was it disposed of? When we look at patients offered alternatives, did they use those and was their pain controlled? We are engaging with resources within UH and the community to track the utilization of those services that we are navigating patients to.”

Although the opioid module meets a pressing need, Beck stressed that UH Care Continues has many other potential use cases, including driving care coordination between all the various actors in the hospital: the therapists, social workers, medical teams and nurses, as well as the off-site administrative support for getting patients out of the hospital and setting up resources, whether they are going to a facility or back home. “It also enables new choices like hospital at home – alternatives to hospitalization or getting patients home more quickly,” Beck said. “We think we have a winner here because it has a broader value proposition than just the opioid work flow. The opioid module is just one element that can be deployed. We are moving down the path of our commercialization milestones, and we will want to bring it to market.”

In fact, Beck said, UH Ventures has a queue of things it is looking to bring to market, some spun out as new companies.  “We are the innovation and commercialization engine for the system,” he said. “We are engaged with our digital health accelerator here in Cleveland and are working with early stage companies to provide them usability and validation support.”

 

 


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New Blockchain Project Sets to Tackle Provider Credentialing

November 12, 2018
by Rajiv Leventhal, Managing Editor
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A group of five healthcare enterprises—National Government Services, Spectrum Health, WellCare Health Plans, Inc., Accenture, and The Hardenbergh Group—are linking up to participate in a distributed ledger program aimed at resolving administrative inefficiencies related to professional credentialing.

The project, Professional Credentials Exchange, is being developed by ProCredEx and Hashed Health, a blockchain innovation consortium. The exchange leverages “advanced data science, artificial intelligence, and blockchain technologies to greatly simplify the acquisition and verification of information related to professional credentialing and identity,” according to officials.

In an announcement, officials noted that credentialing healthcare professionals “is a universally problematic process for any industry member that delivers or pays for patient care.  The process often requires four to six months to complete and directly impedes the ability for a healthcare professional to deliver care and be reimbursed for their work.”

They added, “Hospitals alone forfeit an average of $7,500 in daily net revenues waiting for credentialing and payer enrollment processes to complete.  Further, nearly every organization required to perform this work does so independently—creating a significant administrative burden for practitioners.”

As such, the groups, via the exchange, will aim to address the time, cost, and complexity associated with these processes by facilitating the secure, trusted exchange of verified credentials information between exchange members.

Included in the collaboration are WellCare Health Plans, which serves about 5.5 million members, and Spectrum Health, a 12-hospital health system in western Michigan. National Government Services is a Medicare contractor for the Centers for Medicare & Medicaid Services (CMS), and processes more than 230 million Medicare claims annually.

"A fundamental component of developing the exchange lays in building a network of members that bring significant verified credential datasets to the marketplace," Anthony Begando, ProCredEx's co-founder and CEO, said in a statement.  "These are the leading participants in a growing group of collaborators who bring data and implementation capabilities to accelerate the deployment and scaling of the exchange."

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Google Taps Geisinger CEO David Feinberg to Assume Healthcare Leadership Role

November 9, 2018
by Rajiv Leventhal, Managing Editor
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Top healthcare execs continue to leave the hospital and health system space to move into tech

Geisinger Health System CEO David Feinberg, M.D. has been tapped by Google to assume a leadership role over its healthcare initiatives.

According to a report from CNBC, “Feinberg's job will be figuring out how to organize Google's fragmented health initiatives, which overlap among many different business groups.” The report, from CNBC’s Christina Farr, added, “The search has been underway for months, according to several people familiar with the search process. Artificial intelligence head Jeff Dean has been deeply involved in the process and personally interviewing candidates.”

Earlier this year, it was rumored that Feinberg—the lead at the Danville, Pa.-based Geisinger for the last four years—could join the Amazon/Berkshire Hathaway/JP Morgan Chase  healthcare initiative, but that was put to bed when Feinberg released a statement in June, provided to CNBC’s Farr, in which he said, “I personally remain 100-percent committed to Geisinger and remain excited about the work we are doing and the opportunities ahead as we continue to deliver exceptional care to our patients, our members and our communities." Amazon, Berkshire Hathaway, and JPMorgan Chase ended up hiring Atul Gawande, M.D., as CEO of the initiative.

David Feinberg, M.D.Google has made several forays into the healthcare space over the years, and most recently tapped former Cleveland Clinic CEO Toby Cosgrove, M.D., to join the team has an executive advisor. Interestingly, the Cosgrove hiring was announced by Gregory Moore, M.D., Ph.D., vice president of Google Cloud’s healthcare division, who is also a former clinical IT executive at Geisinger.

As Healthcare Informatics reported on in its Top Ten Tech Trends package a few months ago, new business and technology combinations and ventures are heralding a new era of disruption in U.S. healthcare delivery. As Editor-in-Chief Mark Hagland wrote in his story, “Alphabet, Google’s parent company, is leveraging its extensive cloud platform and data analytics capabilities to hone in on trends in population health, [a] Business Insider report noted. The company plans to drive more strategic health system partnerships by identifying issues with electronic health record (EHR) interoperability and currently limited computing infrastructure.”

Indeed, these new “disruptors” are not only making major moves in the healthcare space, but also hiring some of the smartest minds from hospitals and health systems—a trend that some might see as troubling for the traditional healthcare player.

What’s more, the research firm Kalorama Intelligence recently reported that three companies—Google, Apple, and Microsoft—have filed more than 300 healthcare patents between 2013-2017—among them, Google’s 186 patents, mainly focused on investments for DeepMind, its artificial intelligence and Verily , its healthcare and disease research entity.

Feinberg also had some interesting comments about his vision for healthcare at the “HLTH: The Future of Healthcare Conference” this past May. Healthcare Informatics’ Hagland, who was at that event, reported this from Feinberg’s keynote: “For us, what really matters is so much about what’s happening outside the clinics or the hospitals,” he said. “We have 13 hospitals in our system. And I think my job is to close all of them. I know that out of 2,000 beds we have, if people ate right, used alcohol in moderation, didn’t use illegal drugs, wore seatbelts, ate healthily, had access to broccoli and blueberries, and didn’t shoot people with guns, 1,000 of those beds could be gone…”

As it relates to Google, Farr noted in her recent report, “Among the groups interested in healthcare are Google's core search team, its cloud business, the Google Brain artificial intelligence team (one of several groups at Alphabet working on AI), the Nest home automation group and the Google Fit wearables team.”

She added, “One particular area of interest is building out a health team within Nest to help manage users' health at home, as well as to monitor seniors who are choosing to live independently. Nest had been an independent company under Google holding company Alphabet, but was absorbed back into the Google Home team earlier this year.”

Meanwhile, at Geisinger, Feinberg—who will remain at the health system through the end of the year—will be replaced by Jaewon Ryu, M.D., as interim president and CEO.


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Time for Artificial Intelligence to Meet Healthcare Costs

October 29, 2018
by Anil Patel, M.D., Industry Voice
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Technology has improved the entire face of the healthcare industry. It has lessened the time taken to examine and diagnose a patient as well as eased the processing and retrieval of records. Artificial intelligence (AI) promises to do much more for the constantly changing industry. The changes envisioned include, lowered cost of healthcare, improved access to information, shorter service times and fewer errors due to misinformation or data mishandling.

AI promises to process large amounts of data and make meaningful conclusions out of them. The AI systems can process data just like informaticians do and use this feedback to ease operations within the organizations but much faster and with accuracy. For example, both patients and doctors can save a lot of time scheduling appointments and entering patient data into the electronic system. This can be made much faster by the application of artificial intelligence. The scheduling can be made much faster and with fewer conflicts as the data is checked by the system instead of manual work. The institutions can also manage process patient data and use it prepare the institutions facilities for changing needs. This is a better system than the one currently in place as it makes work easier.

AI can also help the government prevent and manage outbreaks that are caused by infectious diseases. This can be done through the use of a process called “modeling.” A mathematical model collects the surveillance data from healthcare workers and creates an outbreaks trajectory within the community. This trajectory is then used to classify community members according to their level of risk. Measures are then put in place to take care of the infected while isolating the recovered and the immune. The information will guide the government to coordinate health care efforts and direct all other related agencies. This process is accelerated by AI as the progress and effectiveness of the interventions can be determined using a similar AI model. Real-time data can also help healthcare workers to prepare themselves regardless of policy and protocol. The overall effect on the human immune system can also be examined.

AI can help reduce hospital readmissions by providing sound management for patients suffering from chronic diseases. The patients can work with the medical staff after they are discharged in order to design a self-reliant program. AI solutions can be programmed into devices such as smartphones and watches. These devices can monitor a patient's vital signs and they can be relayed real time to the hospital a standby team that uses this data to monitor patient's status. The insights from AI can help ensure the execution of the treatment protocol and to change treatment plans if deemed necessary. This will lower the rate of emergency hospitalizations and readmissions and will improve health outcomes and lower the cost of care dramatically. The AI systems may also plan and schedule post-discharge visits and lab and imaging follow up tests. AI can keep an up to date database of clinical and diagnostic information. AI can use this info to generate the alerts and reminders for the treating physicians and the patients to predict the ailments ahead of time.

Evidence-based medicine initiatives can be expanded and improved on in several ways. Tools can be developed to make the information more specific and focused. The starting point is developing a focused question that can provide guided answers. The most promising evidence can be gathered then be appraised by qualified personnel who will later front recommendations. The initiatives can then participate in well-controlled trials that will determine the commercial potential of the initiative. The results can further be published and presented to the relevant authorities as soon as possible. The initiatives can also be protected by enforcing policies that protect the freedom of expression and experience.

There are algorithms that can be used to fast-track the possible outcomes of evidence-based medicine initiatives. They often assist the research team to develop systems that operate like formula. The formula can help a researcher compare the possible outcomes of different patients with different combinations of treatment. The algorithms also utilize other data such as the age of the patients and other existing conditions and drug interactions. Algorithms may include deep learning in their setup that can quickly establish patterns that can be used to develop treatment plans swiftly.

AI can be used to reduce the exorbitant cost of drug trials and to shorten the length of time a drug trial is executed. Algorithms can be developed to eliminate the initial tests. They include things like toxicity tests and early screening for genetic markers and drug combinations. AI can also create a database with a list of the compounds are that didn't have any value. The AI systems may also classify and process background information into relevant information. Software to read through data also provides the best approach for researchers. They are able to generate a summarized report detailing the required communication. This way, time is spent doing other parts of the research. Finally, AI may contribute to the development of sound systems that make human life easier.

One of the main barriers to the implementation of AI systems that can improve the healthcare industry is cost. The systems have a high initial cost that put off many potential investors and stakeholders. Staffing of the trained system users for the institutions are the other major problems. The readily available informaticians and analysts may not give required support as they did not have the necessary skills to use the AI systems effectively. They may leave a lot of information unaccounted and hence won't give optimal results. The different regulatory and compliance bodies also pose problems in registration and approval. Human resistance from the stakeholders is sometimes risky and may even delay a good product from distribution.

Anil Patel is a physician and health IT professional experienced in inventing clinical IT tools for healthcare industries in the U.S., Canada, and India. He has been involved in bridging the gap between diverse healthcare professionals and development and design teams to define, build, and maintain intuitive clinical IT solutions that are critical to patient care, growth, engagement, and customer retention. For more information, please contact him at patilanild@gmail.com.


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