Posts Tagged informatics

Big Ideas for Big Data Analytics in Real-World Evidence: Insights from Dr. Rich Gliklich, CEO of OM1

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Rich Gliklich, MD, CEO of OM1Dr. Patti Peeples, CEO of HealthEconomics.Com, sat down with Dr. Rich Gliklich, CEO of OM1, to discuss how big data analytics are changing the face of real world evidence (RWE). The mission of this Cambridge, Massachusetts digital health company is forward-thinking, like its leader: to solve the problem of determining and understanding the true results of healthcare and offer a more complete view of patient outcomes. By bringing together multiple data sources at the individual patient level to construct patient journeys, OM1 rapidly measures and forecasts patient outcomes, combining expertise in clinical research and informatics with big data technology and advanced data science to reinvent how real world evidence is generated and used.

HealthEcoOM1logonomics.Com asked Dr. Gliklich to shares his views on major transformational changes in evidence development and how these will drive a more personalized delivery of healthcare in the future.

[HE.Com] With the influx of big data, how do you think the pharmaceutical industry’s approach to real-world evidence should evolve? Are patient registries still relevant?

[RG]  Healthcare data is growing at an astounding rate. This creates both challenges and opportunities.  Pharma is being asked to demonstrate value to more and more stakeholders. We define Value as:  Value = Outcomes/Cost, and thus, Pharma will increasingly seek deeper clinical information and true outcomes to help demonstrate value and justify their prices.

To get to this critical evidence, they will need to turn to highly specialized capabilities and data for particular conditions, and they will need these data regularly updated, because the dynamics in the market change. For most organizations, it will be more cost-effective and timely to subscribe to sources that track and analyze these changes, than to build out the infrastructrure and acquire the data independently, such as from clinical trials and prospective patient registries.

The goals of patient registries are still relevant—from understanding the natural history of a disease to meeting a post market safety commitment.  But, big data plus advanced technologies creates alternative opportunities to meet those goals across many therapeutic categories and conditions, and to do so with very large patient numbers (orders of magnitude more patients vs registries), and at a fraction of the cost.

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[HE.Com] Are there disease or therapeutic areas where using big data, as you’ve described, may be more effective? What types/level of disease and patient level data could we get to that is different than what we have access to today with traditional registries and trials?   

[RG] Conditions where comprehensive patient journeys can be readily captured through linking different data sources will be most amenable to using big data.  There are a number of conditions where this is the case, from airway to cardiovascular and immunologic diseases to name a few. And, the number of such conditions with comprehensive patient journeys using disparate data linking is growing every day. Beyond traditional clinical and laboratory data available through registries and trials, we are now able to collect more and more patient-generated data, cost information, socioeconomic data, mortality, and so on. In addition to a more thorough understanding of the patient experience, these approaches also have the advantage of collecting information on all patients. This removes some of the enrollment biases we see in both registries and trials. The graphic below demonstrates the large sample size that can be attained through linked data compared with the sample size from a typical prospective registry.

Linked Big Data in Healthcare

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[HE.Com] Recently STAT News reported that Actemra® (tocilizumab) was responsible for hundreds of deaths and that the risks for life threatening complications were as high or higher than competing products. Could you comment on this finding, and is there a better way to look at this situation, using a big data perspective?

The STAT report was based on the FDA Adverse Event Reporting System.  The problem with those systems is that they are based on voluntary reporting and there is no denominator to actually determine the incidence of the events. This creates potential bias in reporting, since clinicians who are aware of a potential problem with a drug are then more likely to report events associated with it. Using big data, we can have a true denominator where the number of exposed patients and the number of events are both known, and these are derived from a combination of data sources.

In response to the STAT report, OM1 rapidly analyzed 120,000 patients on DMARDS (disease-modifying antirheumatic drugs) over the past 12 months to assess these findings in a more systematic and controlled analysis using big data. We did not find the same difference in event rates when patients carefully adjusted for comorbidities. Since the results are not yet published, I cannot go into details, but it demonstrates the power of using big data to respond rapidly to safety and other signals that may come up from time to time.

[HE.Com] How will payer needs for RWE evolve over the next 5 years, and what are the opportunities for service providers (pharma, researchers, data analytics companies) to address these future needs? 

As payers move towards value-based care, they need a deeper understanding of clinical outcomes beyond what is available in their own claims data sets. While the goal is to understand the clinical outcome, meaning the patient and provider-relevant impact of the treatment on the patient, the actual results today are tabulated from what transactions were billed for by the doctor or hospital.  As a result, these outcomes have generally focused on easily measured billing items such as hospitalizations, adverse event rates or complications of procedures.

But data derived from these sources lacks clinical depth and nuance. Critical questions are unanswered when using billing data for outcomes assessment. How serious was the hospitalization?  Did the patient return to normal functioning and well-being?  Did the underlying disease process improve or worsen as result of the treatment?  None of this is actually measurable in claims data. These shortcomings are leading payers and pharma to seek more clinically-focused RWE, and each will do it for their own purposes.  Payers will also increasingly partner with pharma to support value-based assessments and outcomes based contracts.

[HE.Com] How will patients’ use of big data evolve? Are there case studies of patient use that will become the norm for other disease states in the future?

Both patients, and providers on behalf of patients, will use big data to personalize healthcare.  Big data analytics that are focused on outcomes will support better decision-making for patients. As a result, patients will have the opportunity to better understand their own specific risks and benefits with respect to different therapies, as well as their likelihood to achieve both positive and negative outcomes. Let me give you a generalized example. In the future, a patient with rheumatoid arthritis will be able to know that for patients like them, 80% improved with drug A vs. 40% with drug B and these results were derived from broad big data rather than limited clinical trials. In this scenario, a typical patient will have much more information to make informed choices about their own or their loved one’s healthcare.

[HE.Com] What regulatory hurdles or opportunities do you see as they relate to big data, RWE, or related evidence dissemination?

Regulatory interest in big data and RWE is at an all time high as recent regulations such as the 21st Century Cures Act are driving regulators to consider RWE as a potential replacement for other forms of evidence generation around and post-approval.  In Section 505F of the Cures Act, it states, “The Secretary shall establish a program to evaluate the potential use of real world evidence (1) to help support approval of a new indication under section 505(e); and, (2) to help support or satisfy post-approval study requirements.” The program is to be implemented “within 2 years” and ‘real world evidence’ is defined as data “from sources other than clinical trials”. At the same time, some of these new paths to use RWE for these purposes are untested and there will certainly be some growing pains. Examples of such hurdles are seen in the work we do with outcomes-based contracting where issues regarding measurement outside of the label and Medicaid best price continue to create barriers.

As researchers, we are doing our part to facilitate better informed decisions for individual impact, using our intelligent data cloud to transform population data into precision health. And we’re trying to get deeper into clinical and patient data, more quickly. But there is much work to be done.

[HE.Com] Thank you, Rich. For more information on the work of Dr. Gliklich and colleagues in the area of RWE, view the recent on-demand webinars by clicking on the links below. 

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Rich Gliklich, MD, CEO of OM1About Rich Gliklich, MD

Rich is the CEO of OM1, a healthcare technology company focused on understanding the patient journey and the true results of healthcare. Since 2014, Rich has been an XIR at General Catalyst, where he supports businesses in the healthcare industry. Prior to joining General Catalyst, Rich was President of the Outcome division of Quintiles, the largest provider of biopharmaceutical development and commercial outsourcing services, and he also served on its Executive Committee through its 2013 IPO.   Prior to Quintiles, Rich was Founder, CEO and Chairman of Outcome, a health information and services company that served more than 2,500 healthcare organizations and a majority of the global top 30 life sciences companies.  Rich led Outcome from its start as a spin-off from his Harvard affiliated research laboratory in 1998 through its acquisition by Quintiles in October 2011.  In addition to his experience as an entrepreneur and executive, Dr. Gliklich is well known in the areas of registries, outcomes and analytics.  He is senior editor of the landmark publication by the U.S. Agency for Healthcare Research and Quality (AHRQ) handbook “Registries for Evaluating Patient Outcomes: A User’s Guide” and the PI for the Outcomes Measures Framework, which focuses on standardization of outcomes measurement.  Rich has led several key national and international efforts focused on evaluating the safety, effectiveness, value and quality of healthcare.  Rich also holds several patents for both health outcomes systems and medical devices. Rich is a graduate of Yale University and Harvard Medical School and a former Charles A. Dana Scholar at the University of Pennsylvania. Rich is also a surgeon and the Leffenfeld Professor at Harvard Medical School.

 

If you or someone you know would like to be featured in the HealthEconomics.Com CEO Profiles Series, contact Dr. Patti Peeples, CEO of HealthEconomics.Com. 

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Health Informatics, A Fast-Growing Field and a Crucial Skill-Set: An Interview with Dr. Patrick Casimir

What is Health Informatics?

What discipline combines information technology, programming, analytical skills, communication abilities, and a deep desire to improve healthcare quality and safety? Health Informatics Word Cloud

Health Informatics.  Health Informatics encompasses the management (acquiring, storing, retrieving, and utilizing) of healthcare information to foster better collaboration among a patient’s various healthcare providers, and plays a critical role in the push toward healthcare reform.  In the field of health economics and outcomes research (HEOR), health informatics is integral in the utilization of data to explore and analyze interventions, systems, and processes that affect patient health outcomes in real-life and theoretical situations.

Tremendous Growth in Health Informatics Field

Over the past several years, the growth in electronic health record (EHR) adoption as well as “meaningful use” incentive programs from the Centers for Medicare and Medicaid have been a catalyst in the growth in the health informatics field.  As more and more providers and health systems implement EHR, and seek to drive improved outcomes to maximize reimbursement, health informatics specialists will be in high demand.

Health Informatics should not be confused with Health Information Technology.  Health Informatics is the application of informatics concepts, theories, and practices to healthcare, and is “the science, the how, and the why, behind health IT”, as stated by the Centers for Disease Control and Prevention.  Recognition of the growing complexity of health inform​ation needs has led to a call for the creation of a new health care professional. Health Informaticists are asked to forecast for demand in pharmaceuticals for providers and networks, devise datasets to dea​​l with the uncert​ainty of the implementation of the Affordable Care Act, and help to bring together data for providers and payers to better understand how patients are faring within their system with their protocols.  It is a discipline that has a place for a strongly analytical “techie”, or a highly communicative “people person” who is focused on patients, the healthcare system, and their care providers.

What is Health Informatics Infographic
Infographic by USF Health Online.

 

Interview with a Newly-Formed Health Informatics Master’s Degree Program

In an effort to better understand this burgeoning new career path, HealthEconomics.Com interviewed Dr. Patric Casimir, Program Director and Assistant Professor of the newly formed Health Informatics program at Jacksonville University at the Brooks Rehabilitation College of Health Sciences of Jacksonville University, located in Jacksonville, Florida.  We asked Dr. Casimir to share his vision of health informatics education, including the type of work that is done and the external drivers in society and health policy that have caused this explosive growth in the field.  Below is the interview with Patrick Casimir [PC], by Dr. Patti Peeples, CEO and Founder of HealthEconomics.Com.

Patti Peeples, CEO and Founder, HealthEconomics.Com

[PP] Please describe some of the major national trends in the Informatics field, and provide some context to how this profession is growing in importance in the US and internationally?

 

Patrick Casimir, PhD, Program Director of Health Informatics, Jacksonville University

[PC] The major national trends that have affected the field of health informatics include the use of new technologies such as electronic health records (EHRs), computerized provider order entry (CPOE), as well clinical decision support systems (CDSS). Other trends affecting this field are explosive growth in data analytics and management, as well as mobile health.  It is essential to also consider the impact of the trend toward value-based healthcare payment structures (tracking particular interventions and determining outcome, asking “is it working?” “how well is it working?” and “is it cost-effective”.  There is also a focus on quality metrics by all organizations, because of new rules in reimbursement. The implementation of clinical information systems and health informatics in general has been critical in saving patients’ life through the reduction of medication errors and the detection of harmful drug allergies, interactions, and adverse dosing events.  Health Informaticists also play crucial roles in assessing healthcare quality and providing the data to better understand how organizations can provide quality care in the most effective and efficient way possible given their particular patient population and treatment paradigms.

[PP] What kinds of jobs and companies do Health Informatics professionals work within today, and will they work in within the next 5 years?  And, who are some of the team members in the type of projects that Health Informatics professionals work on (that is, who do they work with to “get the job done”)?

[PC] The types of individuals health informatics professionals work with are quite vast.  Typically, right now you will see them working for hospitals and other healthcare related organizations such as insurance companies or data analytic companies. Commonly, health informatics professionals work with nurses, physicians, CNOs, CIOs, CEOs, project managers, and medical health services researchers.  As the field matures, our data capabilities get more extensive, and the demand for data analysis grows, the types of organizations and jobs will only increase, and the impact of this type of work will continue to grow and be leveraged within the organization up through the C-Suite.

[PP] Can you tell us a little more about the faculty in Jacksonville University Masters of Science Health Informatics program?  What kinds of work experience do the other professors have and how will this practical experience be brought into the classroom?

[PC] We are recruiting faculty in the JU Health Informatics program with an emphasis on experienced health informatics professionals, health services outcomes researchers, and academicians who have taught in this discipline and in related disciplines for many years. By example, I will direct the program and teach as professor and I’ve been a long time healthcare consultant. Since 2010, I’ve worked as a Health Information Technology (HIT) application analyst, consultant, and CPOE implementation expert at the following hospitals and medical centers across the nation, including Kingman Regional Medical Center, Kingman AZ; Hamilton Medical Center, Dalton, GA; Mountain States Health Alliance, Johnson City, TN; Community Health Systems, Scranton, PA; Arkansas Heart Hospital, Little Rock, AR; Garden City Medical Center, Garden City, MI; Peconic Bay Medical Center, Riverhead, NY; Southeast Medical Center, Cape Girardeau, MO; Baptist Health South Florida, Coral Gables, FL.  As an HIT expert, I’ve helped and supported small hospitals and large regional health care systems transitioning to electronic medical records, implemented computer provider order entry (CPOE), and embarking on true clinical systems’ integration for meaningful attestation.

I’ve also taught as an Adjunct Professor of the Master Science Biomedical Informatics program at Nova Southeastern University since 2010. As an Adjunct Professor, I taught and developed numerous courses and used his industry experience to help graduate students identify and complete appropriate practicum and research projects within hospitals, other healthcare organizations, and the HIT field in general.  I’ve been spending the past several months interviewing and building this JU program to be a significant force in the health informatics field in Florida and nationwide.

[PP]  What additional resources are there in Jacksonville/North Florida that can be utilized for the graduate students to avail themselves of, both personally and professionally?

[PC]  The Jacksonville/North Florida is a powerhouse in terms of highly respected, world class healthcare facilities, including the Mayo Clinic Hospital, Shands, Baptist Medical Center, Memorial Hospital, Brooks Rehabilitation, Florida Blue, and St Vincent Medical Center to name a few.  The presence of such highly esteemed research and patient care hospitals and provider networks will give ample opportunity for practical real-life training and internships, as well as future job opportunities.  In addition, Jacksonville is a city in high growth as the arts are infusing every walk of life, and of course, the beautiful St. Johns River, the intracoastal waterway, and the Atlantic ocean beaches offer tremendous recreation for students and their families.  The cost of living is low, and it is a welcoming city with southern hospitality but a big city + beachy feel.  Nowhere else offers this combination of experiences other than Jacksonville and the First Coast.

To learn more about Jacksonville University’s Master’s Degree in Health Informatics, please click here.

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