Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There?

MOOC Summaries - Medicine in Digital Age - Future of Medicine

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There?

Overview … What does the future of medicine look like? … The Internet of Things… Health, Data, Security, Privacy.. Digital Health and the Aging Population.. Managing Information in the Digital Age… Digital Literacies… Narrative Medicine: Translating Data into a Story… Future of Medicine… Expert Interview: Fred Trotter … Expert Interview: Dr. Eric Topol
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Summaries

  • Future of Medicine > Introduction to Week 4
  • Future of Medicine > The Internet of Things
  • Future of Medicine > Health Data, Security, and Privacy
  • Future of Medicine > Digital Health and the Aging Population
  • Future of Medicine > Managing Information in the Digital Age
  • Future of Medicine > Digital Literacies
  • Future of Medicine > Narrative Medicine: Translating Data into a Story
  • Future of Medicine > The Future of Medicine
  • Expert Interview: Fred Trotter > Part 1/3
  • Expert Interview: Fred Trotter > Part 2/3
  • Expert Interview: Fred Trotter > Part 3/3
  • Expert Interview: Dr. Eric Topol > Dr. Eric Topol with Dr. Vartabedian
  • Expert Interview: Dr. Eric Topol > Dr. Eric Topol with Dr. Ostherr

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > What does the future of medicine look like? > Introduction to Week 4

  • In Week One:
    • looked at broader social and technological changes that have affected all aspects of our lives, including health care.
    • One key takeaway: networked relationships are key; they predate the internet, but they have changed in powerful ways online.
  • In Week Two:
    • looked at what the changes mean for doctors and other health care professionals.
    • one key point: in the history of medicine, doctors have been accustomed to working in private and not having public voices but all of that has changed in the digital age.
    • role of artificial intelligence in medicine and the role of EHRs, Electronic Health Records, in health care.
    • looked at the emergence of wearable technology and self-tracking data as new sources of patient-generated information that is beginning to enter clinical settings.
  • In Week Three:
    • flipped perspective and looked at what the age of digital medicine means for patients and consumers.
    • looked at the historical legacy of e-patients in the HIV/AIDS activist movement and how these movements pose challenges to traditional ideas about the doctor-patient relationship.
    • looked at how big data is posing a challenge for e-patients, because we don’t know what to do with all of this new information.
    • key point: information does not automatically equate to knowledge, and our ability to capture data has outpaced our ability to analyze it in meaningful ways.
    • a big takeaway: technologists should be designing for the people who need health interventions most, even though this means dealing with the bureaucracy of the FDA and HIPAA.
  • Now in this final week:
    • we want to ask: what does the future of medicine look like and what will it take to get there?
    • Topics include:
      • internet of things
      • privacy and security challenges that plague digital life today
      • aging population of the United States and what it means for digital health.
      • the new skills that doctors and patients need in the digital age, including information curation, public engagement, and creative approaches to transforming data into stories.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > What does the future of medicine look like? > The Internet of Things

  • The Internet of Things: everyday gadgets, devices, appliances, and sensors connected to each other, feed data (which hopefully can be turned into information and knowledge) to the web and often back to ourselves.
  • It is convergence of inexpensive sensors, wireless networks, and cloud computing.
  • A well-known example: Nest thermostat – it adjusts the temperature at home and gathers information about your environment, so that it knows your patterns, adjusting itself to save energy.
  • According to John Seely Brown and John Hegel of Deloitte Consulting, the internet is most powerful when it is connected to the physical world, which is the case with the Internet of Things.
  • We see the blurring of boundaries between the hardware and software as it is the digitization of the physical world.
  • Other applications of the Internet of Things:
    • ambient monitoring of an aging population;
    • rhythm changes in the hearts of cardiac patients (and intervention when we still can);
    • give people the right information at the right time and in the right place for health choices;
    • in general, how our bodies connect to the internet.
  • Major challenges/concerns:
    • Interoperability between devices/gadgets etc
    • Privacy e.g. the Federal Trade Commission recommends that companies take precautions to protect their customers.
  • An interesting and really futuristic application would be the emerging use of emotion in the Internet of Things e.g. thoughts and feelings are turned into bits and bytes for subsequent use, influence and control?

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > What does the future of medicine look like? > Health Data, Security, and Privacy

  • Data security, privacy, personal health data etc are issues that need to be considered in the discussions and use of wearable technologies; EHRs; companies analyzing and prediction consumer behaviours; insurance companies setting premiums; and employers screening job applicants.
  • “Personal Data for the Public Good” has extensive discussions of data privacy and security concerns for personal health data from wearable devices.
  • “Here’s Looking at You, How Personal Health Information Is Being Tracked and Used” analyzes the risks and opportunities around privacy and big data.
  • Data privacy and security are often perceived as major barriers to innovation digital health e.g.
    • HIPAA (Health Information Portability and Accountability Act) aims to protect the privacy and security of personally identifiable health information.
    • But legislation oftens means patients are unable to access and share their own data due to firewalls between their records and their own wearables data.
  • Increasingly, there are experts and non-experts  who feel that health data privacy needs to be updated to emphasize context of use such as:
    • who captured the data;
    • how was it captured;
    • for what purpose;
    • who is using it;
    • how they obtained it; and
    • for what purpose.
  • There remains concerns over the adequacy of data privacy law especially in light of new technologies like the Internet of Things e.g. it has been shown that anonymised data/info can be re-idenitifed from two or more pieces of personal data, thus making sensitive patient data vulnerable to many issues.
  • Consumers also have strong concerns about companies exploiting their data and governments using data for surveillance (i.e. it is not just malware and hacking – data piracy), even as they continue to use mobile and online services.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > What does the future of medicine look like? > Digital Health and the Aging Population

  • A major issue is the aging of the populations in many countries around the world e.g. due to diseases of aging, such as cancer, stroke, heart disease, Alzheimer’s, Parkinson’s etc.
  • This include the baby boomer generation in the United States – by the year 2060, there will be over 92 million Americans aged 65 or older, more than twice the number in 2012.
  • Health care resources will have to to be provided.
  • Historically, the older generation are lagging adopters of new technology, but each the current older generation are using the internet and broadband more than the previous generation.
  • Research has shown that information and communication technologies – such as video, computer programs, electronic registries, and EHRs – can tackle many end-of-life health problems such as advance care planning through ease of use storage and retrieval of documents, promoting end of life health literacy, and enabling more effective use of palliative care and end of life decision making.
  • Digital health tools can also be individualized, increasing the efficacy of health interventions, be adapted to different cultural norms, reach underserved populations, and respond to different contexts.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > What does the future of medicine look like? > Managing Information in the Digital Age

  • David Weinberger from the Berkman Center at Harvard Law School has suggested that information is not the solution but the problem because of the volume of information, speed, immediacy, and real time flow.
  • Doctors will have to learn how to filter and become active participants in shaping their own filters and their own information streams.
    • NYU professor Clay Shirky has suggested that our problem is really not information overload, but rather filter failure.
  • Now information finds us through our social networks or based upon our context. Context may ultimately represent the most important thing helping us to control information.
  • Doctors will also go from memorizing to accessing information – technologies like smartphones and glasses with built-in screens will supplement clinical work.
  • Artificial intelligence will play a larger role in clinical decision making e.g.
    • the new role that IBM Watson is playing at Memorial Sloan Kettering Cancer Institute – Watson takes data from the EHR, analyzes it against published data, and offers suggestions for treatment.
    • the first practical (and very impressive) application of artificial intelligence in a clinical setting.
  • New access to information will require new literacies, workflows, and new ways of seeing what we do as physicians.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > What does the future of medicine look like? > Digital Literacies

  • Literacy used to be considered the ability to read and write; but today, literacies can be thought of as the broad skill sets needed to function.
  • Physicians will need to learn to see themselves beyond their offices, and as part of a broader network of collective knowledge.
  • Doctors need to understand their filters and participate in information gathering, processing, and sharing.
  • The challenge is to take the knowledge and translate it into the digital medium.
  • At the same time, doctors will have to balance technology with attention to patients – no matter much network knowledge exists, what matters is how much of that is brought to the single human encounter with the patient.
  • The list of literacies will need to be discussed and built upon.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > What does the future of medicine look like? > Narrative Medicine: Translating Data into a Story

  • One of the biggest challenges in digital health is to make sense of the data in ways that doctors, patients, and other health care stakeholders can relate to i.e. transforming data into meaningful stories.
  • There is growing emphasis on evidence-based medicine:
    • medical decision-making that is not based on the random sample of any given doctor’s personal experience or intuition;
    • but on on data, ideally data generated through randomized controlled trials;
    • and in the digital age, also through population health findings that will start to emerge from EHR-based clinical outcomes.
  • But human beings use stories to make sense of the world e.g. doctors ask patients, “So, what brings you in today?” and rely on those stories to piece together into a coherent picture.
  • Such narratives help
    • construct hypotheses about cause and effect, that are crucial to determining the etiology of a disease, a necessary step in determining a diagnosis and treatment plan.
    • (on a larger scale) connect discrete biomedical data points to the environment, social systems, and networks in which they occur.
  • Patient stories are unstructured data so computational techniques are needed to structure them e.g. through big data analytics, natural language processing technologies, health taxonomies, and semantic analysis.
  • At the same time, there are unstructured data that are never captured, and so we might have data without narratives. This is where human interaction is needed.
  • We need new storytelling models so that we can make good, contextually sensitive decisions based on big and small data and based on unstructured data.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > What does the future of medicine look like? > The Future of Medicine

  • We will see a new generation of doctors and patients: technologies that
    • support the empowered patient;
    • redefines what it means to be a doctor;
    • create a future that is patient-centric.
  • The future will be:
    • networked – intelligent networks will extend what we do as individuals;
    • collective – collective knowledge will play a major role shaping research and directing patient care;
    • individualized;
    • precise;
    • real time;
    • current/responsive – instead of the episodic interactions with the healthcare system now.
  • Key future technologies:
    • phone emerges as a personal device for monitoring things such as rhythm disturbances;
    • machines extend, even replace, what we can do with our hands, eyes, our ears.
  • What training do we need? What knowledge is needed? Who will interpret and analyse the data generated? Who will pay for the healthcare that occurs outside conventional healthcare venues?
  • Technology will also force us to confront our limitations, and we will have to define what is essentially human that will never be automated or replaced by a computer.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > Expert Interview: Fred Trotter > Fred Trotter Interview Part 1/3

  • Fred Trotter is a data journalist and a founder of DocGraph Journal, and he’s also at CareSet Systems.
    • Data journalism – finds important health care data sets, and releases them (working with conventional journalists sometimes)
  • DocGraph Journal – many use the work, and it strives to be place where you can get a very good map of the health care system and undeimportant health care issues.
  • CareSet Systems: startup where they hope they can make some money by taking a lot of the data from DocGraph Journal, and make it useful to the health care system.
    • They are most famous for the referral data set; they asked Medicare to give them time series data where they could see how different physicians and hospitals and labs were working together in time; referrals were the simplest case of that.
    • We can collect all data and make connections, but what does it mean? It is map of the health system of how everything is tied together, and the data sets have been used to go after fraud.
    • As  result of Obamacare, there is a deepening of networks – the difference between in-network and out-of-network is substantially magnified.
    • To be price competitive on the insurance markets, insurance companies say that if you go to our team, it is really cheap; but if you go outside, it’s going to vert expensive.
    • Hence networks are getting deeper.
    • CareSet systems looks into these deeper links.
  • Not all data sets have money making potential e.g.
    • food data;
    • medication data;
    • how people understand medicine.
  • DocGraph Journal makes it possible to know much more about the health care system and how health care works in general.
  • It is becoming a very good map map, and it is not clear how best to use the map just yet e.g. there are studies outcomes but in general, the health care system does not do outcomes:
    • We might certain surgical procedures work in Mayo Clinic or Cleveland Clinic doing it i.e. places that regarded as excellent
    • But we do not have much data about how things work elsewhere.
  • A data journalist can only do something is the data exists; if it does not, one can use data in such a way that it creates a a strong incentive for others/industry to start tracking the right stuff.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > Expert Interview: Fred Trotter > Fred Trotter Interview Part 2/3

  • Our fears of patient privacy has resulted in us choosing to do nothing.
  • We have to address a few issues:
    • First question: are we giving patients the appropriate return on the investment (i.e. they have allowed us to their their data) – in that regard, we have been found wanting.
    • After we have a plan to give an appropriate return, we need to ensure the plan respects their privacy.
  • The benefit needs to be in both directions; now the laws do not allow for that (and these laws were put in place in the past to protect AIDS patients).
  • There is also an issue that in the past, it made sense from a business standpoint to hoard patient data as it was extremely profitable.
  • On privacy, patients often do not understand privacy law e.g. even Facebook settings are hard for people to understand and use.
  • Another issue: we have yet to develop a science that takes into account the addition of patient generated data into how doctors and the healthcare system works – once we have done so (e.g. 10 years from now), it would make a huge difference.
  • New questions will arise – what if you had a patient’s heart data since they were born and in a particular month, you see a change? Will we need patient records and what will it look like? What would EHR/EMR look like since in the past this has been a record of what happened to a patient? What is the impact of AI? What questions are needed?

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > Expert Interview: Fred Trotter > Fred Trotter Interview Part 3/3

  • Electronic Medical Record versus Electronic Healthcare Record: seven years ago, they were used  interchangeably.
  • The Federal Government conducted a study and concluded that:
    • EMRs were going to be medical records that were digital; and
    • EHRs were EMRs that were interoperable
    • i.e. only difference were that EHRs are interoperable.
  • We now have high tech electronic health care records, but not much interoperability i.e. we paid for EHRs but got a lot of EMRs.
  • There are two ways to think about interoperability:
    • The Internet  way: you can do whatever you want another way;
    • The Facebook way:  you can interoperate with other Facebook users.
  • Portals are good but only as walled gardens, which is not the same as interoperability – need to invest in technologies and protocols that allow patients to take their data where they want them, even when their physician thinks it is a bad idea.
  • In future, clinical decision support is likely to be as good as a doctor, and will be pervasive.
    • Example: it is likely we will have a radiologist and a software looking at scans (instead of two radiologists). One backs up the other, and it does not matter which is first, as they are about as good as each other.
  • But clinical decision support obviously depends on the quality of the EHR, which is not very good currently. So there will be a data quality issue.
  • Because of this the physician is likely to continue to have an advantage over AI in the interim. The AI will likely need to be integrated with sensors.

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > Expert Interview: Dr. Eric Topol > Dr. Eric Topol with Dr. Vartabedian

  • Topol published a book titled “Creative Destruction of Medicine and The Patient Will See You Now.”
  • Vinod Khosla has suggested that, some 80% of doctors might be out of a job in a few years.
  • Because it is an information era, and what used to be electronic health records is going to be a joke.
  • So diagnostics and monitoring functions for most routine and straightforward things are going to be done by patients with equal or even better accuracy.
  • But human contact, touch factor, face-to-face interaction, dealing with the treatments, imparting wisdom and experience and guidance – that will be the real doctoring of the future.
  • If the medical schools wanted to, they could really energize the curriculum by bringing in all the new pieces such as digital devices, bioinformatics or medical informatics, telemedicine, and sensors etc.
  • Actual interpersonal capabilities will become even more important i.e. the ability to connect with others and care for them.
  • The problem in most medical schools is not the students, it’s the faculty as there are not many physicians who realize that that they can do far better in doing a physical exam with modern technology.
  • For example, traditional institutions like the AMA represent physicians during the analog age:
    • AMA lobbied against people getting access to their genomic data, going after 23andMe etc.
    • They said it has to be a doctor or genetic counselor.
  • Doctors need a new literacy: communicating and translating information for public consumption.
  • Last year, 800,000 pregnant women had their fetus sequenced between eight and 12 weeks (~ 20% of the four million live births in the United States), and they only got read whether there was Downs or other major chromosomal abnormalities.
  • Change is likely to come from patients as doctors have been uncomfortable with patients bringing in their own data or information they got from the internet.
  • It is the first time in the history of medicine where patients are reshaping doctors..

Week 4: What Does the Future of Medicine Look Like and What Will it Take to Get There? > Expert Interview: Dr. Eric Topol > Dr. Eric Topol with Dr. Ostherr

  • Patients, if they have the tools that we have now, could become very empowered.
  • We could focus on prevention – for example, we could give a cheap smartphone to people who do not have one, so that they can use the medical resources online; they could be given a service contract and that would cost less cheaper than emergency room visits and hospitalizations.
    • In some countries, tech companies and donations are providing this for free to people who do not have computers
    • This could also help homeless people as they could get better medical care by getting their own information.
  • In Rwanda, there is an accurate diagnosis one can do with a a smartphone – a diagnosis with for HIV and syphilis in 15 minutes for pennies i.e. a pathologist in the pocket.
  • When people do get their information, no matter what socioeconomic background, many become activated, engaged, and take charge to be healthier.
    • They had a much better quality of life;
    • This reinforces findings from studies that information is not just empowering, it can help you feel healthier.
  • To achieve these, we will need:
    • to be able to handle and integrate multiple layers of data, sensors, records, information etc, for a complete “map” of the person;
    • new privacy laws to assure individuals.
  • Surveys show that 80 to 90% of people are happy to share their data for research to help others.
  • Other potential technologies:
    • Virtual Medical Assistant –  pulls your data together and starts to text/talk/coach you e.g. blood pressure or sleeping issues, have you taken your medicine etc – helps an
    • Ability to sequence your own DNA or their microbiome.
  • With all the data and information one might have about yourself, the only reasonable solution might be a personal cloud or equivalent, from birth or even pre-womb, and throughout life.
  • If so, we need new data and digital literacies such knowing engaging in peer to peer health care online, communicating and accessing information, using the computers intelligently, all without having to have the same training and understanding as a doctor.
    • For example, a picture of your child’s eardrum, you do not know much  about eardrums, but cloud computing feedback tells us everything is ok.
  • Massive Open Online Medicine – each person’s individual medical and health data; if we are willing to share, a new information resource is created, creating new opportunities for better medical care.
  • We will also need to attract people who are keen on technology and have them join the healthcare sector so that they can create the applications and solutions for this new digital healthcare. We have to help them see this is a noble way to apply their talent.

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