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Combating Physician Burnout – Let’s Stop Treating Physicians Like Factory Workers

Posted on July 1, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Have you ever seen the Love Medicine Again website? I hadn’t either until yesterday, but it says something that someone would need to create a website like that in the first place. Many doctors are quite unhappy with their life as a doctor and where medicine is heading. I actually came across this website thanks to their article titled “5 Ways to Use Creativity to Combat Physician Burnout.” Here’s the 5 suggestions they make to put creativity to work to reduce physician burnout:

  1. Allow your staff to help you with your schedule
  2. Voice your concerns about something that isn’t working to your colleagues
  3. Give credit where credit is due
  4. Engage your patients to help you help them
  5. Think outside of the box about how to bring improved satisfaction to your job

I wasn’t that impressed with the list. It seems to gloss over the core of what’s burning physicians out. I do love the idea of providing opportunities for physicians to be creative. That has definitely been pushed to the side in many offices.

One of the most common complaints I hear from doctors is “Stop making me be a data entry clerk.” I think this was largely true in the paper world, but it has been made even more so in the world of EHR thanks to things like meaningful use that require a lot of hoop jumping and box clicking to comply. We could certainly do more to make the data entry work easier, but that still just masks the problems.

I think that doctors saying they don’t want to be a data entry clerk is really a proxy for “I want to be creative and thoughtful in how I approach medicine. I don’t have time to be creative.”

The 15 minute (or less) per appointment hits this same pain point. Doctors want to get paid and so they feel the economic reality is that they need to see as many patients as possible. This economic reality leaves no time for doctors to be creative. I think they feel more like factory workers than highly educated leaders.

If we want to solve the physician burnout problem we need to find ways to tap into a physician’s creativity. We need to free them up for churning out patients so they can leverage all their education and experience to solve the larger problems of healthcare. It’s not very often that overworked factory workers are able to solve massive problems. They’re too busy working to think about the larger context. We need to stop treating our doctors like factory workers to solve healthcare’s larger problems.

Do We Want a Relationship With Our Doctor?

Posted on June 22, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

As is often the case, this weekend I was browsing Twitter. Many of the people and hashtags I follow are healthcare and health IT related. Many of the tweets related to the need to change the healthcare system. You know the usual themes: We pay too much for healthcare. We deserve better quality healthcare. We need to change the current healthcare system to be focused on the patient. Etc etc etc.

This wave of tweets ended with one that said “It’s all about the relationships.” I actually think the tweet had more to do with how a company was run, but in the beautiful world of Twitter you get to mesh ideas from multiple disciplines in the same Twitter stream (assuming you follow a good mix of people). I took the tweet and asked the question, “Do We Want a Relationship With Our Doctor?

If you’d asked me a year ago, I would have said, no! Why would I want a relationship with my doctor? I don’t want any relationship with my doctor, because that means that I’m sick and need him to fix something that’s wrong with me. I hope to never see my doctor. Doctor = Bad. Don’t even get me started with hospitals. If Doctor = Bad then Hospital > Doctor.

I’m personally still battling through a change in mindset. It’s not an easy change. It’s really hard to change culture. We have a hard core culture in America of healthcare being sick care. We all want to be healthy, but none of us want to be sick. Going to the doctor admits that we are sick and we don’t want anything to do with that. If we have an actual relationship with our doctor, then we must be really sick.

From the other perspective, do doctors want relationships with their patients? I’ve met some really jaded doctors who probably don’t, but most of the doctors I’ve met would love an actual, deep relationship with their patients. However, they all are asking the question, “How?” They still have to pay the bills, pay off their debts, etc. I don’t know many doctors who have reconciled these practical needs with the desire to have a relationship with their patients.

The closest I’ve seen is the direct primary care and concierge models. It’s still not clear to me that these options will scale across healthcare. Plus, what’s the solution for specialists? Will ACOs and Value Based Reimbursement get us there. I hear a lot of talk in this regard which scares me. Lots of talk without a clear path to results really scares me in healthcare.

What do you think? Do you want a relationship with your doctor? Do doctors want a relationship with their patients? What’s the path to making this a practical reality? Are you already practicing medicine where you have a deep, meaningful relationship with your patient? We’d love to hear your experience.

Patients Can Squawk, But We Have Little To Crow About Open Data

Posted on June 15, 2015 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

One of the biggest disappointments at this year’s Health Datapalooza (which I found disappointing overall) was the continued impasse presented to patients who, bolstered by the best thinking in health care as well as Federal laws and regulations, ask for health data stored about them by doctors and other institutions.

Activists such as Regina Holliday and e-Patient Dave proved years ago that giving patients information and involving them in decisions will save lives. The Society for Participatory Medicine enshrines the principle. But the best witnesses for patient empowerment are the thousands of anonymous patients, spouses, parents, and children quietly trundling folders with their own records through the halls of hospitals, building up more knowledge of their chronic conditions than any professional clinician possesses, and calmly but inflexibly insisting on being equal partners with those who treat them.

There were plenty of high-minded words at the Datapalooza about patient rights to data. It was recognized as a key element of patient empowerment (or “activation,” as the more timid speakers liked to say) as well as an aid to better care. An online petition backed by an impressive array of health reformers is collecting signatures (whom someone will presumably look at) and encourages activists to speak up about this topic on July 4. HHS announced that anyone denied access to data to which the law gives her a right can submit an informal report to noinformationblocking@cms.hhs.gov.

Although occasional mention was made of personal health records (PHRs), most of the constant discussion about interoperability stayed on the safe topic of provider-to-provider data exchange. Keeping data with health care providers leads to all sorts of contorted practices. For instance, patient matching and obtaining consent are some of the most difficult challenges facing health IT in the U.S., all caused by keeping data with providers instead of the patients themselves.

The industry’s slowness to appreciate patient-generated data is also frustrating. Certainly, the health IT field needs to do a lot more to prepare data for use: consumer device manufacturers must assure clinicians of the devices’ accuracy, and researchers need to provide useful analytics that clinicians can plug in to their electronic systems. Still, doctors are demonstrating a disappointing lack of creativity in the face of this revolutionary source of information. It’s all to easy to carp about accuracy (after all, lab tests have limited accuracy as well) or just to state that you don’t know what to do with the data.

I heard about recent progress at the UK’s National Health Service from Brian Ahier, who is the only person I know who can explain the nuances of extensions to FHIR resources while actively using both his laptop and his cell phone at the same time. Ahier heard at a UK-US Bootcamp before the Datapalooza that the NHS has given 97% of its patients access to their records.

But there’s a bit of a caution around that statistic: only one-fifth of the patients have taken advantage of this right. This doesn’t bother me. First of all, one-fifth of the population with access to their personal records would be a dizzying accomplishment for most countries, including the U.S. Second, few people need access to records until some major problem arises, such as the need to see a specialist. They probably feel relieved to know the records will be there when needed.

Another aspect of patient control over data is research. The standard researcher-centered model is seen as increasingly paternalistic, driving patients away. They’re not impressed with being told that some study will benefit people like them–they want to tell researchers what really matters to them as sufferers, and hear more about the study as it goes along. Researchers are frantic to reverse a situation where most studies fail simply because they can’t sign up enough subjects.

The Patient-Centered Outcomes Research Institute (PCORI) is one of the progressive institutions in health care who understand that giving patients more of a say will be increasingly important for signing up patients in the first place, as well doing research of value to them. Its PCORnet combines traditional research databases with databases maintained by patient advocacy groups. Each member network can create its own policies for getting consent, which allows researchers to bend with the needs of their research subjects.

OpenClinica, the open source clinical research platform, just announced the release of an app that may contribute to the goals of taking input from patients and binding them closer to the research endeavor.

Public health officials also recognize the sensibilities of the people they monitor. At a panel on data about low-income people, speakers stressed the importance of collecting data in a respectful way that doesn’t make people feel they’re being spied on or could be punished for their behavior.

Let’s talk a minute about health care costs, if only because doctors and insurers don’t want to. (Some doctors are prohibited by their employers from telling patients how much a recommended procedure will cost, supposedly because they don’t want costs to intrude on what should ideally be a clinical decision. This is changing with the increase in deductibles, but often the doctors don’t even know what the final cost will be after insurance.)

One app so admired by the Datapalooza team that they allowed the company to demonstrate its product on the main stage during keynote time was Sensentia. This product everybody is so impressed with takes in information from health plans to allow patients as well as the staff at health care providers to quickly find the health plan benefits for a procedure. (I recently covered another company doing similar work with insurance and costs.)

Sensentia is a neat product, I am willing to aver. It accepts natural language queries, crunches the data about health plans and insurers, and returns the actual health plan benefits for a treatment. Of course, I know the cost of flying from Boston to San Francisco after six clicks in my browser, even though the calculations that go into offering me a price are at least as complicated as those run by health plans. One may be shocked to hear that that current phone calls to an insurer cost $3-$10. This is the state of health care–it costs more than five bucks on average for a doctor just to find out how much it will cost to offer his own service.

A panel on patient-generated data reported more barriers than successes in getting doctors to work with data from patient devices and reports from everyday life. Another panel about improving quality measures culminated in the moderator admitting that more patients use Yelp than anything else to choose providers–and that it works pretty well for them.

For me that was the conference’s low point, and a moment of despairing cynicism that doesn’t reflect the mood of the conference or the health care field as a whole. Truly, if Yelp could solve our quality problems, we wouldn’t need a Datapalooza or the richness of data analysis it highlights. But I think reformers need more strategies to leap the hurdles we’re facing and implement the vision we all share.

Early Warnings Demonstrate an Early Advance in the Use of Analytics to Improve Health Care

Posted on May 4, 2015 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Early warning systems–such as the popular Modified Early Warning System (MEWS) used in many hospitals–form one of the first waves in the ocean of analytics we need to wash over our health care system. Eventually, health care will elegantly integrate medical device output, electronic patient records, research findings, software algorithms, and–yes, let us not forget–the clinician’s expertise in a timely intervention into patient care. Because early warning systems are more mature than many of the analytics that researchers are currently trying out, it’s useful to look at advances in early warning to see trends that can benefit the rest of health care as well.

I talked this week to Susan Niemeier, Chief Nursing Officer at CapsuleTech, a provider of medical device integration solutions. They sell (among other things) a bedside mobile clinical computer called the Neuron that collects, displays, and sends to the electronic medical record vital signs from medical devices: temperature, pulse, respiration, pulse oximetry, and so on. A recent enhancement called the Early Warning Scoring System (EWSS) adds an extra level of analytics that, according to Niemeier, can identify subtle signs of patient deterioration well before a critical event. It’s part of Capsule’s overarching aim to enable hospitals to do more with the massive amount of data generated by devices.

For more than 18 years, CapsuleTech provided bedside medical device connectivity products and services that captured patient vital signs and communicated that data to the hospital EMR. Rudimentary as this functionality may appear to people using automated systems in other industries, it was a welcome advance for nurses and doctors in hospitals. Formerly, according to Niemeier, nurses would scribble down on a scrap of paper or a napkin the vital signs they saw on the monitors. It might be a few hours before they could enter these into the record–and lots could go wrong in that time. Furthermore, the record was a simple repository, with no software observing trends or drawing conclusions.

Neuron 2 running Early Warning Scoring System

Neuron 2 running Early Warning Scoring System

So in addition to relieving the nurse of clerical work (along with likely errors that it entails), and enhancing workflow, the Neuron could make sure the record immediately reflected vital signs. Now the Neuron performs an even more important function: it can run a kind of clinical support to warn of patients whose conditions are deteriorating.

The Neuron EWSS application assigns a numerical score to each vital sign parameter. The total early warning score is then calculated on the basis of the algorithm implemented. The higher the score, the greater the likelihood of deterioration. The score is displayed on the Neuron along with actionable steps for immediate intervention. These might include more monitoring, or even calling the rapid response team right away.

The software algorithm is configured in a secure management tool accessible through a web browser and sent wirelessly to the Neuron at a scheduled time. The management tool is password protected and administered by a trained designee at the hospital, allowing for greater flexibility and complete ownership of the solution.

Naturally, the key to making this simple system effective is to choose the right algorithm for combining vital signs. The United Kingdom is out in front in this area. They developed a variety of algorithms in the late 1990s, whereas US hospitals started doing so only 5 years ago. The US cannot simply adopt the UK algorithms, though, because our care delivery and nursing model is different. Furthermore, each hospital has different patient demographics, priorities, and practices.

On the other hand, according to Niemeier, assigning different algorithms to different patients (young gun-shot victims versus elderly cardiac patients, for instance) would be impractical because mobile Neuron computers are used across the entire hospital facility. If you tune an algorithm for one patient demographic, a nurse might inadvertently use it on a different kind of patient as the computer moves from unit to unit. Better, then, to create a single algorithm that does its best to reflect the average patient. The algorithm should use vital signs and observations that are consistently collected, not vitals that are intermittently measured and documented.

Furthermore, algorithms can be tuned over time. Not only do patient populations evolve, but hospitals can learn from the data they collect. CapsuleTech advises a retrospective chart review of rapid response events prior to selecting an algorithm. What vital signs did the patient have during the eight hours before the urgent event? Retrospectively apply the EWSS to the vital signs to determine the right algorithm and trends in that data to recognize deterioration earlier.

Without help such as the Early Warning Scoring System, rapid response teams have to be called when a clear crisis emerges or when a nurse’s intuition suggests they are needed. Now the nurse can check his intuition against the number generated by the system.

I think clinicians are open to the value of analytics in early warning systems because they dramatically heighten chances for avoiding disaster (and the resulting expense). The successes in early warning systems give us a glimpse of what data can do for more mundane aspects of health care as well. Naturally, effective use of data takes a lot more research: we need to know the best ways to collect the data, what standards allow us to aggregate it, and ultimately what the data can tell us. Advances in this research, along with rich new data sources, can put information at the center of medicine.

Telehealth, or ‘How to Ditch the Waiting Room’

Posted on February 13, 2015 I Written By

The following is a guest blog post by Ryan Nelson, Director of Business Development for Medical Web Experts.

Navigating the doctor’s office for a non-emergency can feel like getting lost in a quagmire of lengthy routines. For those who choose to forego the experience for as long as possible, haphazardly browsing WebMD in the middle of the night is no better. This could all change soon.

Telemedicine is on the rise as health insurers and employers have become more willing to pay for online video consultations in recent years. Convenience (imagine not having to leave the comfort of your home for every service!) and positive health outcomes – not to mention significant cost savings for both employers and patients – are propelling online video consultations to the forefront of healthcare strategies.

Convenience
People don’t like driving far, and they don’t like spending 45 minutes in a waiting room only to be discharged in under 15. The average wait time for a doctor’s appointment is 20 days in the US. This is more than enough time to deter patients from booking appointments for conditions that could be minor. Doctors usually don’t get reimbursed for time spent taking phone calls, so they often nix the medium altogether. Virtual doctor visits can fulfill patients’ need for instantaneous advice, closing a potentially dangerous communication gap while opening a new business opportunity for healthcare professionals.

A recent Harris Poll survey commissioned by Amwell found that around 40% of consumers would opt for video appointments for both antibiotics and birth control prescriptions, while at least 70% would rather have an online video visit to obtain a prescription than travel to their doctor’s office. Telehealth also offers a good solution for patients with mobility issues or chronic conditions, and it gives patients and doctors in rural or remote communities more options for receiving and dispensing care.

Health Outcomes
Biomed Central’s systematic review of telehealth service studies revealed that health outcomes for telehealth and in-person appointments are usually similar. About one-third of studies showed improved outcomes and only two indicated that telehealth was less effective. One way that online video appointments can improve health outcomes for the general population is to filter out minor health concerns and free up ER staff to deal with more serious ailments in-house. Additionally, video consultations can make it easier for physicians to track the recovery of discharged patients and to monitor patient adherence in a time-sensitive manner.

Cost Savings
The Amwell survey revealed that 64% of patients are willing to attend virtual appointments, challenging the dated assumption that in-person interactions tend to be perceived as a better experience. Contributing to this popularity is the fact that virtual appointments cost much less than an ER visit and are cheaper than an urgent care center or most face-to-face consults, generally figuring in around $40 to $50.

Biomed Central also found that out of 36 studies, nearly two-thirds showed cost savings for employers and patients. Meanwhile, Towers Watson predicted that the number of employers offering telemedicine will increase by 68% in 2015, which would result in $6B in employer savings.

Consumer Concerns
Consumers are concerned about how doctors can thoroughly examine patients through video, according to Amwell. However, the proliferation of self-monitoring mobile devices that can be used in conjunction with video consultations suggests that doctors may be able to get much of the information they need online. Besides, it can be argued that during most medical appointments a doctor doesn’t have much time to perform a comprehensive examination or truly get to know a patient.

Amwell subjects also questioned how a patient can be certain that he or she is speaking to a real doctor; however, this can easily be addressed by medical web platforms that thoroughly screen physicians and can thus provide adequate proof of their qualifications.

Digital Relationships
Research has shown that online video communication improves patient satisfaction and increases efficiency and access to healthcare for all demographics, at all times. While the medium appeals to people across all age groups, it especially appeals to younger, tech-savvy patients. This demographic tends to prefer instantaneous communication for non-emergencies and is generally comfortable communicating despite physical distance.

Consumers already use technology to communicate with their friends and families. Finally, doctors – another one of every person’s most intimate relationships – can join the ranks.

References:
Amwell
Biomed
Towers Watson

Apervita Creates Health Analytics for the Millions

Posted on January 9, 2015 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Health officials are constantly talking up the importance of clinical decision support, more popularly known now as evidence-based medicine. We’re owning up to the awkward little fact–which really should embarrass nobody–that most doctors lack expertise on many of the conditions they encounter and can’t read the thousands of relevant studies published each year. New heuristics are developed all the time for things such as predicting cardiac arrest or preventing readmissions after surgery. But most never make their way into the clinic.

Let’s look at what has to happen before doctors and patients can benefit from a discovery:

  1. The researcher has to write a paper with enough detail to create a working program from the heuristic, and has to publish the paper, probably in an obscure journal.

  2. A clinician or administrator has to find the article and line up staff to write and thoroughly test a program.

  3. If the program is to be used outside the hospital where it was created, it has to be disseminated. The hospital is unlikely to have an organization set up to package and market the program. Even if it is simply put out for free use, other institutions have to learn about it and compile it to work on their systems, in order for it to spread widely. Neither the researcher nor the hospital is likely to be compensated for the development of the program.

  4. The program has to be integrated into the doctor’s workflow, by being put on a menu or generating an alert.

Evidence-based medicine, therefore, is failing to tap a lot of resources that could save lives. A commonly cited observation is that research findings take 17 years to go into widespread practice. That’s 17 years of unnecessary and costly suffering.

I have often advocated for better integration of analytics into everyday medical practice, and I found a company called Apervita (originally named Pervasive Health) that jumps off in the right direction. Apervita, which announced a Series A round of funding on January 7, also has potential users outside of clinical settings. Pharma companies can use it to track adverse drug events, while payers can use it to predict fraud and risks to patients. There is not much public health data in the platform yet, but they’re working on it. For instance, Leapfrog group has published hospital safety info through their platform, and Diameter Health provides an all-cause 30-day readmissions prediction for all non-maternal, non-pediatric hospitalizations.

Here’s how the sequence of events I laid out before would go using Apervita:

  1. The researcher implements her algorithm in Python, chosen because Python is easy for non-programmers to learn and is consequently one of the most popular programming languages, particularly in the sciences. Apervita adds functions to Python to make it easy, such as RangeCompute or tables to let you compute with coefficients, and presents these through an IDE.

  2. The researcher creates an analytic on the Apervita platform that describes and publishes the analytic, along with payment terms. Thus, the researcher derives some income from the research and has more motivation to offer the analytic publicly. Conversely, the provider pays only for usage of the analytic, and does not have to license or implement a new software package.

  3. Clinicians search for relevant analytics and upload data to generate reports at a patient or population level. Data in popular formats such as Excel or comma-separated value (CSV) files can be uploaded manually, while programmers can automate data exchange through a RESTful web service, which is currently the most popular way of exchanging data between cooperating programs. Rick Halton, co-founder and Chief Marketing Officer of Apervita, said they are working on support for HL7’s CCD, and are interested in Blue Button+ button, although they are not ready yet to support it.

  4. Clinicians can also make the results easy to consume through personalized dashboards (web pages showing visualizations and current information) or by triggering alerts. A typical dashboard for a hospital administrator might show a graphical thermometer indicating safety rankings at the hospital, along with numbers indicating safety grades. Each department or user could create a dashboard showing exactly what a clinician cares about at the moment–a patient assessment during an admission, or statistics needed for surgical pre-op, for instance.

  5. Apervita builds in version control, and can automatically update user sites with corrections or new versions.

I got a demo of Apervita and found the administration pretty complex, but this seems to be a result of its focus on security and the many options it offers large enterprises to break staff into groups or teams. The bottom line is that Apervita compresses the difficult processes required to turn research into practice and offers them as steps performed through a Web interface or easy programming. Apervita claims to have shown that one intern can create as many as 50 health analytics in one week on their platform, working just from the articles in journals and web resources.

The platform encrypts web requests and is HIPAA-compliant. It can be displayed off-platform, and has been integrated with at least one EHR (OpenMRS).

Always attuned to the technical difficulties of data use, I asked Halton how the users of Apervita analytics could make sure their data formats and types match the formats and types defined by the people who created the analytics. Halton said that the key was the recognition of different ontolgies, and the ability to translate between them using easy-to-create “codesets.”

An ontology is, in general, a way of representing data and the relationships between pieces of data. SNOMED and ICD are examples of common ontologies in health care. An even simpler ontology might simply be a statement that units of a particular data field are measured in milliliters. Whether simple or complex, standard or custom-built, the ontology is specified by the creator of an analytic. If the user has data in a different ontology, a codeset can translate between the two.

As an example of Apervita’s use, a forward prediction algorithm developed by Dr. Dana Edelson and others from the University of Chicago Medical Center can predict cardiac arrests better than the commonly used VitalPAC Early Warning Score (ViEWS) or Modified Early Warning Score (MEWS). Developed from a dataset of over 250,000 patient admissions across five hospitals, “eCART” (electronic Cardiac Arrest Triage) can identify high-risk hospital ward patients and improve ICU triage decisions, often as much as 48 hours in advance.

The new funding will allow Apervita to make their interface even easier for end-users, and to solicit algorithms from leading researchers such as the Mayo Clinic.

Halton heralds Apervita as a “community” for health care analytics for authors and providers. Not only can the creators of analytics share them, but providers can create dashboards or other tools of value to a wide range of colleagues, and share them. I believe that tools like Apervita can bridge the gap between the rare well-funded health clinic with the resources to develop tools, and the thousands of scattered institutions struggling to get the information that will provide better care.

Consumers Are Still Held Back From Making Rational Health Decisions

Posted on November 25, 2014 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Price and quality of care–those are what we’d like to know when we need a medical procedure. But a perusal of a recent report from the Government Accountability Office reminded me that both price and quality information are hard to get nowadays.

This has to make us all a little leery about trends in health reform. Governments, insurers, and employers want us to get choosy about where we have our procedures. They justify rises in copays and deductibles by saying, “You patients should start to take responsibility for the costs of your own health care.”

Yeah, as responsible as a person looking for his car keys in the dark. Let’s start with prices, which in many countries are uniform and are posted on the clinic wall.

Sites such as Clear Health Costs and Castlight Health prove what we long knew anecdotally: charges in the US vary vertiginously among different institutions. Anyone who had missed that fact would have been enlightened by Steven Brill’s 2013 Time Magazine article.

But aspirations become difficult when we get down to the issue at hand–choosing a provider. That’s because US insurance and reimbursement systems are also convoluted. We don’t know whether a hospital will charge our insurer their official price, or how much the insurer will cover. It might feel righteous to punish a provider with high posted prices (or prices reported by other consumers), but most patients have a different goal: to keep as much of their own money as they can.

We can gauge the depth of the cost problem from one narrow suggestion made in the GAO report that yet could help a lot of health consumers: the suggestion that Centers for Medicare & Medicaid Services (CMS) publish out-of-pocket expenditures for Medicare recipients as well as raw costs of procedures (page 31). Even this is far from simple. HHS pointed out that 90% of Medicare patients have supplemental overage that reduces their out-of-pocket expenditures (page 43). Tracking all the ancillary fees is also a formidable job.

Castlight Health is out in front when it comes to measuring the real impact of charges on consumer. They achieve great precision by hooking up with employers. Thus, they know the insurer and the precise employer plan that covers each individual visiting their site, and can take deductibles, exclusions, and caps into account when calculating the cost of a procedure. A recent study found that Castlight users enjoyed lower costs, especially for labs and imaging. Some nationwide system built around standards for reporting these things could unpack the cost conumdrum for all patients.

Let’s turn to quality. As one might expect, it’s always a slippery concept. The GAO report pointed out that quality may be measured in different ways by different providers (page 26). A recently begun program releases Medicare data on mortality and readmissions, but it hasn’t been turned into usable consumer information yet (pages 27-28). Two more observations from the report:

  • “…with the exception of Hospital Compare, none of CMS’s transparency tools currently provide information on patient-reported outcomes, which have been shown to be particularly relevant to consumers considering common elective medical procedures, including hip and knee replacements.” (Page 21)

  • “CMS’s consumer testing has focused on assessing the ability of consumers to interpret measures developed for use by clinicians, rather than to develop or select measures that specifically address consumer needs.” (Page 25)

Some price-check sites simply don’t try to measure quality. A highly publicized crowdsourcing effort by California radio station KQED, based on the Clear Health Costs service, admitted that quality measures were not available but excused themselves by citing the well-known lack of correlation between price and quality.

Price and quality may not be related, but that doesn’t relieve consumers of concerns over quality. Can you really exchange Mount Sinai Hospital in New York for Daddy-o’s Fix-You-Up Clinic based on price alone? Without robust and reliable quality data, people will continue choosing the historically respected hospitals with the best marketing and PR departments–and the highest prices.

A recent series on health care costs concludes by admonishing consumers to “get in the game and start to push back.” The article laments the passivity of consumers in seeking low-cost treatment, but fails to cite the towering barriers that stand in the way.

The impasse we’ve reached on consumer choice, driven by lack of data, reflects similar problems with analytics throughout the health care field. For instance, I recently reported on how hard a time researchers have obtaining and making use of patient data. Luckily, the GAO report cites several HHS efforts to enhance their current data on price and quality. Ultimately, of course, what we need is a more rational reimbursement system, not a gleaming set of computerized tools to make the current system more transparent. Let’s start by being honest about what we’re asking health consumers to achieve.

Treating a Healthy Patient

Posted on November 21, 2014 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I first coined the concept of what I call treating a healthy patient back in 2011. I’ve always loved the concept of a doctor actually treating someone who thinks and feels completely healthy. The challenge is that this type of relationship is very different than what we have in our current health system today.

While our current model is very different, I’m hearing more and more things that get me back to healthcare treating an otherwise healthy patient. Although, someone recently pointed out to me that we’re not really treating a healthy patient, because we’re all sick. We just each have different degrees of sickness. It’s a fine point, but I still argue we’re “healthy” because we feel “healthy.”

This analysis points out one layer of change that I see happening in healthcare. This change is being able to detect and predict sickness. Yes, that still means a doctor is treating a sickness. However, I see a wave of new sensors, genetics, and other technology that’s going to absolutely change what we define as “sick.”

This is a massive change and one that I think is very good. I recently read an article by Joseph Kvedar which commented that we’re very likely to seek medical help when we break our arm, because the pain is a powerful motivating factor to get some help. Can this new wave of sensors and technology help us know the “pain” our bodies are suffering through and thus inspire us to seek medical attention? I think they will do just that.

The problem is that our current health system isn’t ready to receive a patient like this. Doctors are going to have to continue to evolve in what they consider a “disease” and the treatment they provide. Plus, we’ll likely have to include many other professionals in the treatment of patients. Do we really want our highly paid doctors training on exercise and nutrition when they’ve had almost no training in medical school on the subjects? Of course, not. We want the dietitian doing this. We’ll need to go towards a more team based approach to care.

I’ve regularly said, “Treating a healthy patient is more akin to social work than it is medicine.” Our health system is going to have to take this into consideration and change accordingly.

Treating a healthy patient won’t solve all our healthcare problems. In fact, I’ve wondered if in some ways treating a healthy patient isn’t just shifting the costs as opposed to lowering the costs. Regardless of the cost impact, this is where I see healthcare heading. Yes, we’ll still need many doctors to do important procedures. Just because you detect possible heart issues doesn’t mean that patient won’t eventually need a heart bypass surgery some day. In fact, a whole new set of medical procedures will likely be created that treat possible heart issues before they become straight up heart issues.

What other ways do you see the system moving towards or away from “treating healthy patients”?

Which Comes First in Accountable Care: Data or Patients?

Posted on September 30, 2014 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

The headlines are stark and accusatory. “ACOs’ health IT capabilities remain rudimentary.” “ACOs held back by poor interoperability.” But a recent 19-page survey released by the eHealth Initiative tells two stories about Accountable Care Organizations–and I find the story about interoperability less compelling than another one that focuses on patient empowerment.
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Are Limited Networks Necessary to Reduce Health Care Costs?

Posted on September 10, 2014 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Among the dirty words most hated by health care consumers–such as “capitation” and “insufficient medical necessity”–a special anxiety infuses the term “out-of-network.” Everybody harbors the fear that the world-famous specialist who can provide a miracle cure for a rare disease he or she may unexpectedly suffer from will be unavailable due to insurance limitations. So it’s worth asking whether limited networks save money, and whether they improve or degrade health care.
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