Posts Tagged ‘Disruptive Technology’
January 6, 2013
I was happy to have the opportunity to contribute to the iHealthbeat titled “11 Experts on Health IT Progress, Frustrations and Hopes for 2013″ with some very good company. I noted the growth of EMR adoption and mHealth. But I neglected an area which I will be more immersed in this year – Clinical Analytics which is one of the strongest growth areas in Health IT.
Another key set of predictions is by Lucien Engelen. Specifically, the trend toward changes in staffing in healthcare, specifically that more women are becoming physicians and more are looking at part-time work and flexible hours. Also, there are changes in location of care as length of hospital stays decrease and more care is done virtually through remote monitoring and remote communication.
Predictions about technology trends like mHealth need to be placed in the context of other changes in healthcare and there are many including the growth of the ePatient movement.Share this:
December 26, 2012
2012 may go down as a most traveled year for me both in terms of the number of trips and miles traveled but also in terms of new opportunities.
In January, I gave a lecture to the 3rd year medical students at the Cleveland Clinic Lerner College of Medicine on Biomedical Informatics challenging them to think about the future of algorithms in medicine among other topics.
Beginning in February, my chapter on eResearch in the book Health Informatics, was published.
Later in February, it was off to Las Vegas for HIMSS. I was a guest of the Dutch delegation and spoke on Electronic Medical Records: From Clinical Decision Support to Precision Medicine. It was great to see Health IT social media colleagues at the HIMSS social media center. Also during February, I was invited to be on the advisory board for Health Works Collective and contributed to their interest in European trends with a blog post on How Europe is Growing Health Apps.
In March I attended the American Medical Informatics Association Clinical Research Informatics meeting in San Francisco. I presented two posters and one podium presentation all focused on the use of EMR data in research.
Then in April, it was on to the Netherlands for TEDx Maastricht and a visit to Radboud University Medical Center in Nijmeg en to meet at the ReShape & Innovation Center see a preview of the movie The Waiting Room. Also had a tour of the In Vitro programming there with ePatient Dave. Later in April I attend the Epic Research Advisory Council for the first time. Another valuable meeting of other user of the Epic EMR on the secondary use of EMR data in research and how to integrate research into the EMR.
May brought the publication of a blog post in iHealthbeat on A Look at Social Media in Health Care — Two Years Later , a follow up post on my original commentary on Healthcare social media from 2010. Also, I attended the Patient Experience Summit at the Cleveland Clinic which included fellow HealthWorksCollective bloggers Robin Carrey and Barbara Ficarra. Also published was a Technology Brief from the American Association of Medical Colleges on Mobile Apps. These one page summaries are targeted at medical school leadership.
June brought a trip to Barcelona for the Hospital Liquido conference. I presented an updated version of From Clinical Decision Support to Precision Medicine, This was a great opportunity to see one of Europe’s most beautiful cities as well as see the health IT innovation including Doctoralia.
In July I presented virtually at Salud 2.0 in Bilbao, another offering from Spain in medical innovation. My presentation on Social Media in Health Care: A Reasoned Approach was well received. I had the opportunity to answer questions via phone. Hopefully, I will be able to attend this conference in person in a future year.
In August, I was invited to become Adjunct Faculty at Kent State University in Health Informatics. Preparing a course in Clinical Analytics to be taught in May and June, 2013. This is a completely online masters program will be a new experience for me including online videos, readings, assignments and weekly discussion topics. At the end of August I attend the Ohio Health Data Symposium at Case Western Reserve University. Ohio like many states has a rich repository of public health information on everything from chronic diseases to behavioral health.
In early September, I completed a chapter on Computing and Information for a new textbook on Wireless Health: Remaking of Medicine by Pervasive Technologies. The concept of pervasive technology in healthcare is certainly at a tipping point. The book will be out in February 2013. Also in September I attended an internal Cleveland Clinic event, the annual Healthcare Technology Forum which showcased some of the many IT initiatives at all Cleveland Clinic locations including Abu Dhabi.
October 29-31, I attend the Cleveland Clinic Innovation Summit which focused on Orthopedics but included presentations by IBM, 23andMe and Explorys.
November took me to Chicago for the AMIA Annual Symposium. With record attendance (3500), I had the opportunity to organize and present a pre-symposium workshop on Clinical Research Informatics Infrastructure and a poster on the use of a wiki to educate healthcare professionals about secondary use of EMR data. The same week I attend the Informatics Key Functional Committee of the Clinical and Translational Science Awards of the NIH. It was valuable to see what tools are being developed and particularly to attend the Integrated Data Repository workgroup. Also significant for AMIA this year was being featured on the website under Faces of AMIA and participating in the mentorship program, working with an up an coming informaticist, Anja Timmerman. I would encourage all experienced health IT professionals to participate in mentoring to bring along the next generation of informatics.
In December I presented at Cleveland Clinic Medical Informatics Grand Rounds on Use of an EMR-based Registry to Support Clinical Research. Mature EMR systems are quickly become key tools in all aspects of research
Quite a year of opportunities and evolution in my thinking. As you can see, much of my work is shifting from social media in healthcare (although this is still an interest of mine) to research informatics and specifically secondary use of EMR data. More later on what next year might bring.
December 14, 2012
One of the most powerful concepts in changing healthcare is the Learning Healthcare System explained in most detail in this Institute of Medicine report. The concept of using evidence from research to rapidly into practice in a virtuous cycle. But how exactly to operationalize this concept?
Two recent examples are beginning to move along this path in utilizing data to develop customized order sets. One is IBM Watson working with Memorial Sloan Kettering Cancer Center. Using its powerful natural language processing (NLP), Watson is able to match patient data including complex genomics with the wide array of order sets available for different types of cancer. ” The medical center has about 2,000 order sets it can pull from when choosing a cancer treatment.” And data on millions of patients. Finding patterns that match requires the speed and logic of the Watson engine.
A second example uses existing medical knowledge and updates it as published and then converts these into order sets for a procedure-based EMR system. With their combination of the knowledge of current practices in tools like Up-To-Date and an EMR called Provation, they are now combining these products to enable the regular updating of order sets in the EMR including integration with comprehensive EMRs. This demonstrates the last mile of clinical decision support and evidence-based medicine. Bringing the latest discoveries to EMR order sets through an integrated solutions.
Looking forward to more solutions that fulfill the vision of the Learning Healthcare System.Share this:
November 29, 2012
Clinical Integrated Data Repositories are now become common at academic medical centers. With tools like i2b2 and RemedyMD, plus a broad range of analytic tools, access to large volumes of clinical data for research and population management is coming to maturity. The opportunities for use of this data in enabling clinical trials and accelerating research are promising. Quality and patient safety can also be enhanced through use of electronic medical records; a recent New England Journal of Medicine article by Dean Sittig details how to “Use EHRs to Monitor and Improve Patient Safety.” “Organizations must leverage EHRs to facilitate rapid detection of common errors (including EHR-related errors), to monitor the occurrence of high-priority safety events, and to more reliably track trends over time.”
To maximize these opportunities, physicians and other health professionals must develop skills in understanding and utilizing this data. Medical informatics has been successful in developing tools for data mining, but translating raw data into research questions and disease trends requires training medical professionals in new ways of thinking. Understanding clinical workflow in an EMR does not directly translate into this type of research. One must understand how the data is organized and coded to create disease cohorts for analysis. Informaticists are key in training a new generation of physicians in this skill. Because of the complexity of this clinical data, there are three approaches to this data mining and analysis:
- Self-service data mining enabled by cohort definition tools, both vendor developed and open source
- Analyst provided data – skilled data analysts can pull relevant data sets based on their understanding of the research question and the data. However, there are limitations on the number of experienced data analyst any organization can afford to meet the coming demand
- Predictive analytics – this is the realm of the biostatistician who will be key consumers of large data sets to create predictive models to be used in clinical practice. This is also a limited resource, so prioritizing predictive modeling projects which major impact is key
Data mining and analytics should be taught in medical schools for the next generation of providers. Data visualization will be helpful in exploring this complex, big data. More on this in a future post.Share this:
November 14, 2012
Lucien Engelen of the Radboud ReShape Innovation Center in the Netherlands, had an extensive interview at this innovative conference. In this interview he discusses how his center at Radboud Medical Center will have have a game consultant visit weekly to consult with physicians, patients and others to discuss games for health.
Twitter stream on the conference is at #GFH12EU
October 31, 2012
At the Cleveland Clinic Medical Innovation Summit, there was a discussion about big data in health care which moved to the issue of patient engagement and the need for not only transparency of data but also providing tools to manage and interpret data. Two panelists had important inputs – 23&Me and Dr. Harris, CIO of the Cleveland Clinic. What is needed includes PHRs, like MyChart, but also interpretation of results, such as offered by 23&Me. The tools must provide actionable results.
IBM Watson was also featured with a new initiative with Cleveland Clinic to “send Watson to Medical School” using medical students and others to improve paths for medical decisions. This exciting prospect is an experiment in human-computer interaction and machine learning. See this video for more details:
Finally, the top ten innovations announced at the conference including everything from handheld imaging to bariatric surgery.Share this:
October 26, 2012
This is a new textbook editted by Mehran Mehregany for the Wireless Health course at Case Western Reserve University in Cleveland (the course is actually conducted in San Diego). I wrote Chapter 12, Computing and Information, which outlines changes in information technology in the past 10 years and how these are enabling pervasive computing in health care. The release date is February 2013 so stay tuned. Check out the table of contents which includes a broad range of topics from gaming and social networks to medical device design and electronic instrumentation.Share this:
August 22, 2012
The Rainforest was recommended to me by my friend Enoch Choi who lives in Silicon Valley. The book has a fresh perspective on Silicon Valley pointing out the affect of the western pioneer spirit on California in general and the Valley in specific. A spirit of independence and willingness to take risks is proposed as a basis for the unique entrepreneurial direction of the Valley. The book uses several summaries of principles, such as, extra-rational motivations and “err, fail, persist”, what stood out to me were two themes which may sound contradictory: Rule breaking and Trust. This quote about rule breaking sums it up:
“For the Rainforest to thrive, people must accept that rule breaking and believing in grand aspirations are acceptable forms of social behavior. They enable someone to believe that what was previously been considered impossible is in fact possible.” And regarding trust: “the willingness to take the initiative to trust others” and “demonstrate the transparency of its motivations as part of its routine transactions.”
Although the rainforest analogy seems to go to far at times, the concept of enabling international collaboration is right on. The book makes a strong case for the unique environment which spawns innovation in the Valley and questions the ability of many cities and regions which would like to foster innovation and new companies to do so without that unique environment. One exception Cleveland Clinic which has not only generated multiple patents and spin offs but also is now showing other health care organizations how to commercialize their intellectual property.Share this:
July 20, 2012
Several new publications about Big Data in healthcare are showing up with good analysis of this emerging field.
First, an article from PharmExec called “Super-Size Me: Optimizing the Information Explosion” which came out in May. They note new sources of information including:
- Electronic Medical Records
- Social Media
- Real world evidence
- Personalized medicine
- Track and trace systems
They see significant potential value in big data:
» Uncover unmet needs
» Assess the feasibility of clinical trial designs and recruit trial subjects
» Demonstrate product value
» Conduct pharmacovigilance
» React more quickly to market changes via real-time market measurement and sophisticated KPIs
» Enhance commercial activities and enable more personalized messaging
» Deploy predictive capabilities rather than retrospective analytics
And next they note the layers of technology required:
- Collection, Aggregation, and Storage
- “Nowcasting,” real-time data analysis, and pattern recognition will surely get better.
- The good of Big Data will outweigh the bad. User innovation could lead the way, with “do-it-yourself analytics.”
- Open access to tools and data “transparency” are necessary for people to provide information checks and balances. A re they enough?
- The Internet of Things will diffuse intelligence, but lots of technical hurdles must be overcome.
- Humans, rather than machines, will still be the most capable of extracting insight and making judgments using Big Data. Statistics can still lie.
- Respondents are concerned about the motives of governments and corporations, the entities that have the most data and the incentive to analyze it. Manipulation and surveillance are at the heart of their Big Data agendas.
June 28, 2012
This significant report by NEHI (New England Health Policy Institute) reviews current tech trends which will impact the future of chronic disease management. The report categorizes these technologies into 4 classes based on the significant evidence supporting clinical and financial benefits. The technologies reviewed are:
- Extended Care eVisits
- Home Telehealth
- In-Car Telehealth
- Medication Adherence Tools
- Mobile Asthma Management Tools
- Mobile Cardiovascular Tools
- Mobile Clinical Decision Support
- Mobile Diabetes Management Tools
- Social Media Promoting Health
- Tele-Stroke Care
- Virtual Visits
Social media for promoting health was put in class IV. They note that some “their goal is to give simple daily challenges or “micro-actions” that add up to significant health improvements over time.” They report that their is a lack of evidence of effectiveness because they are so new and reports of success are mostly anecdotal by the vendors themselves. The exception are some studies of smoking cessation. While there may be a limited number of randomized clinical trials in the use of social media, there is a growing evidence of the effectiveness of social media in healthcare. Also, social media in healthcare is much broader than promoting health. Online communities, apps, and Twitter are powerful tools capable of having a significant impact on managing and coping with illness. Also, increasing evidence is being published weekly in journals like Journal of Medical Internet Research and the Journal of Participatory Medicine.
Conclusion: this report has excellent analysis on several underutilized technologies in medicine but the evidence for the effectiveness of social media is stronger in my opinion.Share this: