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Time for Artificial Intelligence to Meet Healthcare Costs

October 29, 2018
by Anil Patil, 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 Patil 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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Take the Lead to Deploy Emerging Technologies for Improved Outcomes

December 14, 2018
by Brad Wilson, Industry Voice, former CEO of Blue Cross and Blue Shield of North Carolina
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It is a thrilling time to work in healthcare. As the former CEO of Blue Cross and Blue Shield of North Carolina (Blue Cross N.C.), I have had the opportunity to be at the forefront of using new technologies to improve outcomes for our members. Now as a member of the CitiusTech advisory board, I continue that focus on emerging technologies, such as artificial intelligence (AI), and the potential to accelerate the shift to value-based care and improve the healthcare system in material ways.

AI is starting to make a distinct impact in helping providers deliver more effective care, lower costs and create a more consumer-friendly healthcare system. Blue Cross NC recently piloted the use machine learning, a type of AI, to identify spikes in prescriptions for a costly medication. The company reached out to doctors who had been prescribing the medicine in significant numbers. Alerting just one particular physician practice to a generic equivalent brought estimated annual savings of $750,000 for Blue Cross NC customers. The potential of AI is not measured only in dollars, but cost savings are an important consideration.

Machine learning works by applying sophisticated algorithms to rich datasets from electronic medical records (EMRs), patient-reported data, claims and a host of other sources. To be successful, this requires both access to data and significant investment to support the depth and breadth of data analytics capacity and capability.

Yet, historically, one of the biggest barriers to value-based models has been providers’ and payers’ possessiveness of their own data. There is a good business reason for that possessiveness: competitive advantage. The different parts of the healthcare system do not want competitors to use shared data to steal business. But the guarding of data drives healthcare costs higher and, more importantly, makes delivering better, more personalized healthcare more difficult. In the past, power came from hoarding information; today, there is power in serving as an information hub.  Healthcare providers and payers are starting to understand this and there is more willingness to work together in sharing what has traditionally been closely held information.

As consumers’ voices gain in numbers and decibels, it’s clear that analytics technologies that can lead to better care at lower cost are desperately needed, particularly for payers. But the entire healthcare industry needs to move more rapidly. Health plans need to enrich, deepen and widen their analytics capabilities as quickly as possible. If they don’t, we will continue to see disruptors like Google, Apple, and Amazon enter the healthcare market—companies that have a demonstrated ability to be nimble and maximize the impact of their data.

For both providers and payers, forward-thinking organizations recognize that building their own data analytics solutions is not always the answer. Often there is not enough time, resources or enough of the right talent to deliver the capacity and capability required. Fortunately, robust turnkey solutions coupled with deployment expertise are available to efficiently and cost-effectively integrate data and analytics within an organization’s clinical, financial and administrative processes.

As health plan executives map out their strategic plans, look to these emerging technologies as accelerators for leveraging data to manage risk, optimize performance, engage consumers, enhance population care, and improve clinical outcomes to reduce readmissions and further drive evidence-based medicine. The opportunity is here to transform healthcare delivery in significant ways. Success will go to those organizations that understand the potential of these new technologies and take the lead to deploy them effectively—today. 

Brad Wilson is former CEO at Blue Cross and Blue Shield of North Carolina and is a member of the new CitiusTech Advisory Board. Mr. Wilson joined Blue Cross NC in 1995 as General Counsel and held a variety of senior-level positions before being named CEO in 2010. Under his leadership, Blue Cross NC grew to a $9 billion company serving over 3.8 million customers. Mr. Wilson has also served as Director of the BCBS Association, AHIP and numerous other national and state healthcare organizations.

 


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Investors Have Strong Interest in HIT Sector, Despite Valuation Concerns

December 13, 2018
by Heather Landi, Associate Editor
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Healthcare IT remains a hot investment sector despite concerns about these companies being overvalued, according to KPMG-Leavitt Partners 2019 Investment Outlook, a survey of health care investment professionals.

Looking ahead to 2019, more than a third of respondents (34 percent) said they were most interested in investing in health care IT, followed by care management (31 percent), home health (23 percent), retail-centric medical groups (22 percent) and primary care practices (21 percent).

New York City-based KPMG and Leavitt Partners, based in Salt Lake City, surveyed 175 respondents online from corporations, health systems, investment banks, venture capital and private equity firms between September 17, 2018 and October 21, 2018. Of those surveyed 32 percent were C-suite executives; 29 percent were principal, partner or managing director; 32 percent were vice president or director; 6 percent were analysts/associates and 2 percent held other titles.

“We are not surprised by the great deal of interest in health care IT and care delivery outside the hospital,” Governor Mike Leavitt, founder of Salt Lake City-based Leavitt Partners and former Utah Governor and U.S. Health & Human Services Secretary said in a statement. “As health care continues to march toward value, the emphasis on moving care to lower cost sites and enhanced coordination will continue, and those who can increase quality and lower cost will win.”

According to an October report from Rock Health, 2018 is already the most-funded year ever for digital health startups. Digital health funding in this past third quarter soared to $3.3 billion across 93 deals, pushing 2018 funding to $6.8 billion, already exceeding last year’s annual funding total, which was $5.7 billion, by more than a billion dollars.

Drilling down into respondents’ predictions for investment activity in 2019, in the health care and life sciences market, 96 percent of respondents see either a lot or a moderate amount of investment in health IT and data next year, while a similar percentage (90 percent) see significant or moderate investment in outpatient services. Forty-four percent forecast a lot of investment in post-acute care services, 39 percent predict significant investment in provider services and about a quarter of respondents believe there will be a lot of investment in managed public programs, payer service providers and pharmaceutical and biotech manufacturers. Eighteen percent believe there will be significant investment in medical device and diagnostics and medical equipment.

The survey results indicate there is concern that health IT is overvalued, yet investors believe there is some room to climb.

The majority of investment professionals see health care IT investments as an overvalued sector (64 percent), yet 40 percent expect the valuations to increase in 2019 while 51 percent see them staying the same. About two-thirds of respondents (62 percent) think the health IT sector will grow faster than the market in 2019, and three quarters of investment professionals see increasing competition in the health IT market. Investors also estimate that the average purchase price multiple, in terms of EBITDA, will be 12.5 for the health IT sector in 2019. Survey respondents expect ongoing demand for tools to help with consumerism will impact investment and deal making in the sector, according to the survey.

About four in ten respondents believe the healthcare market is experiencing a “moderate bubble,” while 9 percent believe the bubble will likely burst.

Care management solutions for risk-bearing providers, a highly competitive sector which helps coordinate care of the chronically ill or seriously injured, are expected to be the second highest sector for investment behind health care IT, similarly driven by trends of consumerism and increased focus on early care interventions.

Looking at potential drivers of M&A activity in the health care and life sciences sector in the coming year, 64 percent of respondents cited cost consolidation and economies of scale, while 45 percent cited accretive acquisition strategies. Forty percent of respondents see changing payment models as a driver of M&A activity, and 38 percent cited pressure from competition. Other drivers cited by respondents include expansion/divestiture of service areas (25 percent), geographic expansion/contraction (24 percent), revenue synergies (22 percent), need to deploy cash on balance sheet (17 percent), and regulations and legislation (13 percent).

“Deals are largely being driven by the need for savings, economies of scale, and improving cash flow or accretive earnings per share,” Carole Streicher, Deal Advisory leader for healthcare & life sciences at New York City-based KPMG, said in a statement. “Secondarily, there is a bit of a defensive posture motivating investments as health care organizations contend with competition and reimbursement models connected to quality and efficiency, as well as the entrance of tech firms investing in the sector.”

 

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Report: Massachusetts General Hospital Targeting Various Blockchain Use Cases

December 7, 2018
by Rajiv Leventhal, Managing Editor
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Massachusetts General Hospital (MGH) researchers are partnering with MediBloc, a Korean healthcare blockchain company, with the aim to improve patient data sharing and storing, according to an article in CoinDesk.

Per the article, the Laboratory of Medical Imaging and Computation by MGH and Harvard Medical School will be escalating research in a variety of broad areas “from medical image analysis to health information exchange by leveraging our cutting-edge technologies such as blockchain, artificial intelligence and machine learning,” according to Synho Do who is the laboratory’s director.

Do specifically told CoinDesk, “In collaboration with MediBloc, we aim to explore potentials of blockchain technology to provide secure solutions for health information exchange, integrate healthcare AI applications into the day-to-day clinical workflow, and support [a] data sharing and labeling platform for machine learning model development.”

Interestingly, MGH won’t be using any real patient data for its research, but rather simulated data, according to officials, since the various institutions that have the real patient data keep it in a way “that can’t be shared securely and often is in various incompatible formats.”

MediBloc’s CEO noted that the company is not only developing a distributed ledger for storing and sharing medical data, but also working on a tool that would convert data now held by hospitals from existing formats to a universal one, per the article.

For this initiative, MediBloc has already gotten partners across Asia, including eight healthcare organizations and 14 technology companies, officials said.

Earlier this year, a testing environment version of the blockchain was launched, and the network is expected to go live before the end of the year before becoming fully functional in the second quarter of 2019. Furthermore, there are also apps in the works that are planning to go live next year, with one of them, currently in a beta testing phase, “designed for patients to sell the information about their symptoms and the prescriptions they get to MediBloc. After that MediBloc will analyze that data and sell the analysis to pharmaceutical and insurance companies,” according to the story.

In the end, the main goal of the blockchain project will be to let patients independently decide what to do with their information.

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