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tranSMART and i2b2 Show that Open Source Software Can Fuel Precision Medicine

Posted on April 19, 2017 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://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.

Medical reformers have said for years that the clinic and the research center have to start working closely together. The reformists’ ideal–rarely approached by any current institution–is for doctors to stream data about treatments and outcomes to the researchers, who in turn inject the insights that their analytics find back into the clinic to make a learning institution. But the clinicians and researchers have trouble getting on the same page culturally, and difficulties in data exchange exacerbate the problem.

On the data exchange front, software developers have long seen open source software as the solution. Proprietary companies are stingy in their willingness to connect. They parcel out gateways to other providers as expensive favors, and the formats often fail to mesh anyway (as we’ve always seen in electronic health records) because they are kept secret. In contrast, open source formats are out for everyone to peruse, and they tend to be simpler and more intuitive. As open source, the software can be enhanced by anyone with programming skill in order to work with other open source software.

Both of these principles are on display in the recent merger announced by two open source projects, the tranSMART Foundation and i2b2. As an organizational matter, this is perhaps a minor historical note–a long-awaited rectification of some organizational problems that have kept apart two groups of programmers who should always have been working together. But as a harbinger of progress in medicine, the announcement is very significant.

tranSMART logo

Here’s a bit about what these two projects do, to catch up readers who haven’t been following their achievements.

  • i2b2 allows doctors to transform clinical data into a common format suitable for research. The project started in 2004 in response to an NIH Roadmap initiative. It was the brainchild of medical researchers trying to overcome the frustrating barriers to extracting and sharing patient data from EHRs. The nugget from which i2b2 came was a project of the major Boston hospital consortium, Partners Healthcare. As described in another article, the project was housed at the Harvard Medical School and mostly funded by NIH.

  • The “trans” in tranSMART stands for translational research, the scientific effort that turns chemistry and biology into useful cures. It was a visionary impulse among several pharma companies that led them to create the tranSMART Foundation in 2013 from a Johnson & Johnson project, as I have documented elsewhere, and then to keep it open source and turn it into a model of successful collaboration. Their software helps researchers represent clinical and research data in ways that facilitate analytics and visualizations. In an inspired moment, the founders of the tranSMART project chose the i2b2 data format as the basis for their project. So the tranSMART and i2b2 foundations have always worked on joint projects and coordinated their progress, working also with the SMART open source API.

Why, then, have tranSMART and i2b2 remained separate organizations for the past three or four years? I talked recently with Keith Elliston, CEO of the tranSMART, who pointed to cultural differences as the factor that kept them apart. A physician culture drove i2b2, whereas a pharma and biochemistry research culture drove tranSMART. In addition, as development shops, they evolved in very different ways from the start.

tranSMART, as I said, adopted a robust open source strategy early on. They recognized the importance of developing a community, and the whole point of developing a foundation–just like other stalwarts of the free software community, such as the Apache Foundation, OpenStack Foundation, and Linux Foundation–was to provide a nurturing but neutral watering hole from which many different companies and contributors could draw what they need. Now the tranSMART code base benefits from 125 different individual contributors.

In contrast, i2b2 started and remained a small, closely-knit team. Although the software was under an open source license, the project operated in a more conservative model, although accepting external contributions.

Elliston says the two projects have been talking for the last two and a half years about improving integration and more recently merging, and that each has learned the best of what the other has to offer in order to meet in the middle. tranSMART is adopting some of i2b2’s planning, while i2b2 is learning how to organize a community around its work.

Together they believe their projects can improve more quickly. Ultimately, they’ll contribute to the movement to target cures to patients, proceeding now under the name Precision Medicine. Fund-raising and partnerships will be easier.

I have written repeatedly about these organizations to show the power that free and open source software brings to medicine. Their timely merger shows that open source overcomes cultural and institutional barriers. What it did for these two organizations it can do for the fractured landscape of hospitals, clinics, long-term care facilities, behavioral health centers, and other medical institutions struggling to work together. My hope is that the new foundation’s model for collaboration, as well as the results of its research, can slay the growing monster of health care costs and make us all healthier.

#TransformHIT Think Tank Hosted by DellEMC

Posted on April 5, 2017 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.


DellEMC has once again invited me back to participate at the 6th annual #TransformHIT Healthcare Think Tank event happening Tuesday, April 18, 2017 from Noon ET (9 AM PT) – 3 PM ET (Noon PT). I think I’ve been lucky enough to participate 5 of the 6 years and I’ve really enjoyed every one of them. DellEMC does a great job bringing together really smart, interesting people and encourages a sincere, open discussion of major healthcare IT topics. Plus, they do a great job making it so everyone can participate, watch, and share virtually as well.

This year they asked me to moderate the Think Tank which will be a fun new adventure for me, but my job will be made easy by this exceptional list of people that will be participating:

  • John Lynn (@techguy)
  • Paul Sonnier (@Paul_Sonnier)
  • Linda Stotsky (@EMRAnswers)
  • Joe Babaian (@JoeBabaian)
  • Dr. Joe Kim (@DrJosephKim)
  • Andy DeLaO (@cancergeek)
  • Dan Munro (@danmunro)
  • Dr. Jeff Trent (@TGen)
  • Shahid Shah (@ShahidNShah)
  • Dave Dimond(@NextGenHIT)
  • Mike Feibus (@MikeFeibus)

This panel is going to take on three hot topics in the healthcare industry today:

  • Consumerism in Healthcare
  • Precision Medicine
  • Big Data and AI in Healthcare

The great thing is that you can watch the whole #TransformHIT Think Tank event remotely on Livestream (recording will be available after as well). We’ll be watching the #TransformHIT tweet stream and messages to @DellEMCHealth during the event as well if you want to ask any questions or share any insights. We’ll do our best to add outside people’s comments and questions into the discussion. The Think Tank is being held in Phoenix, AZ, so if you’re local there are a few audience seats available if you’d like to come watch live and meet any of the panelists in person. Just let me know in the comments or on our contact us page and I can give you more details.

If you have an interest in healthcare consumerism, precision medicine, or big data and AI in healthcare, then please join us on Tuesday, April 18, 2017 from Noon ET (9 AM PT) – 3 PM ET (Noon PT) for the live stream. It’s sure to be a lively and interesting discussion.
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Healthcare CIOs Focus On Optimizing EMRs

Posted on March 30, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Few technical managers struggle with more competing priorities than healthcare CIOs. But according to a recent survey, they’re pretty clear what they have to accomplish over the next few years, and optimizing EMRs has leapt to the top of the to-do list.

The survey, which was conducted by consulting firm KPMG in collaboration with CHIME, found that 38 percent of CHIME members surveyed saw EMR optimization as their #1 priority for capital investment over the next three years.  To gather results, KPMG surveyed 122 CHIME members about their IT investment plans.

In addition to EMR optimization, top investment priorities identified by the respondents included accountable care/population health technology (21 percent), consumer/clinical and operational analytics (16 percent), virtual/telehealth technology enhancements (13 percent), revenue cycle systems/replacement (7 percent) and ERP systems/replacement (6 percent).

Meanwhile, respondents said that improving business and clinical processes was their biggest challenge, followed by improving operating efficiency and providing business intelligence and analytics.

It looks like at least some of the CIOs might have the money to invest, as well. Thirty-six percent said they expected to see an increase in their operating budget over the next two years, and 18 percent of respondents reported that they expect higher spending over the next 12 months. On the other hand, 63 percent of respondents said that spending was likely to be flat over the next 12 months and 44 percent over the next two years. So we have to assume that they’ll have a harder time meeting their goals.

When it came to infrastructure, about one-quarter of respondents said that their organizations were implementing or investing in cloud computing-related technology, including servers, storage and data centers, while 18 percent were spending on ERP solutions. In addition, 10 percent of respondents planned to implement cloud-based EMRs, 10 percent enterprise systems, and 8 percent disaster recovery.

The respondents cited data loss/privacy, poorly-optimized applications and integration with existing architecture as their biggest challenges and concerns when it came to leveraging the cloud.

What’s interesting about this data is that none of the respondents mentioned improved security as a priority for their organization, despite the many vulnerabilities healthcare organizations have faced in recent times.  Their responses are especially curious given that a survey published only a few months ago put security at the top of CIOs’ list of business goals for near future.

The study, which was sponsored by clinical communications vendor Spok, surveyed more than 100 CIOs who were CHIME members  — in other words, the same population the KPMG research tapped. The survey found that 81 percent of respondents named strengthening data security as their top business goal for the next 18 months.

Of course, people tend to respond to surveys in the manner prescribed by the questions, and the Spok questions were presumably worded differently than the KPMG questions. Nonetheless, it’s surprising to me that data security concerns didn’t emerge in the KPMG research. Bottom line, if CIOs aren’t thinking about security alongside their other priorities, it could be a problem.

EMR Information Management Tops List Of Patient Threats

Posted on March 23, 2017 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

A patient safety organization has reached a conclusion which should be sobering for healthcare IT shops across the US. The ECRI Institute , a respected healthcare research organization, cited three critical health IT concerns in its list of the top 10 patient safety concerns for 2017.

ECRI has been gathering data on healthcare events and concerns since 2009, when it launched a patient safety organization. Since that time, ECRI and its partner PSOs have collected more than 1.5 million event reports, which form the basis for the list. (In other words, the list isn’t based on speculation or broad value judgments.)

In a move that won’t surprise you much, ECRI cited information management in EMRs as the top patient safety concern on its list.

To address this issue, the group suggests that healthcare organizations create cross-functional teams bringing varied perspectives to the table. This means integrating HIM professionals, IT experts and clinical engineers into patient safety, quality and risk management programs. ECRI also recommends that these organizations see that users understand EMRs, report and investigate concerns and leverage EMRs for patient safety programs.

Implementation and use of clinical decision support tools came in at third on the list, in part because the potential for patient harm is high if CDS workflows are flawed, the report says.

If healthcare organizations want to avoid these problems, they need to give a multidisciplinary team oversight of the CDS, train end users in its use and give them access to support, the safety group says. ECRI also recommends that organizations monitor the appropriateness of CDS alerts, evaluating the impact on workflow and reviewing staff responses.

Test result reporting and follow-up was ranked fourth in the list of safety issues, driven by the fact that the complexity of the process can lead to distraction and problems with follow-up.

The report recommends that healthcare organizations respond by analyzing their test reporting systems and monitor their effectiveness in triggering appropriate follow-ups. It also suggests implementing policies and procedures that make it clear who is accountable for acting on test results, encouraging two-way conversations between healthcare professionals and those involved in diagnostic testing and teaching patients how to address test information.

Patient identification issues occupied the sixth position on the list, with the discussion noting that about 9 percent of misidentification problems lead to patient injury.

Healthcare leaders should prioritize this issue, engaging clinical and nonclinical staffers in identifying barriers to safe identification processes, the ECRI report concludes. It notes that if a provider has redundant patient identification processes in place, this can increase the probability that identification problems will occur. Also, it recommends that organizations standardize technologies like electronic displays and patient identification bands, and that providers consider bar-code systems and other patient identification helps.

In addition to health IT problems, ECRI identified several clinical and process issues, including unrecognized patient deterioration, problems with managing antimicrobial drugs, opioid administration and monitoring in acute care, behavioral health issues in non-behavioral-health settings, management of new oral anticoagulants and inadequate organization systems or processes to improve safety and quality.

But clearly, resolving nagging health IT issues will be central to improving patient care. Let’s make this the year that we push past all of them!

CVS Launches Analytics-Based Diabetes Mgmt Program For PBMs

Posted on December 29, 2016 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

CVS Health has launched a new diabetes management program for its pharmacy benefit management customers designed to improve diabetes outcomes through advanced analytics.  The new program will be available in early 2017.

The CVS program, Transform Diabetes Care, is designed to cut pharmacy and medical costs by improving diabetics’ medication adherence, A1C levels and health behaviors.

CVS is so confident that it can improve diabetics’ self-management that it’s guaranteeing that percentage increases in spending for antidiabetic meds will remain in the single digits – and apparently that’s pretty good. Or looked another way, CVS contends that its PBM clients could save anywhere from $3,000 to $5,000 per year for each member that improves their diabetes control.

To achieve these results, CVS is using analytics tools to find specific ways enrolled members can better care for themselves. The pharmacy giant is also using its Health Engagement Engine to find opportunities for personalized counseling with diabetics. The counseling sessions, driven by this technology, will be delivered at no charge to enrolled members, either in person at a CVS pharmacy location or via telephone.

Interestingly, members will also have access to diabetes visit at CVS’s Minute Clinics – at no out-of-pocket cost. I’ve seen few occasions where CVS seems to have really milked the existence of Minute Clinics for a broader purpose, and often wondered where the long-term value was in the commodity care they deliver. But this kind of approach makes sense.

Anyway, not surprisingly the program also includes a connected health component. Diabetics who participate in the program will be offered a connected glucometer, and when they use it, the device will share their blood glucose levels with a pharmacist-led team via a “health cloud.” (It might be good if CVS shared details on this — after all, calling it a health cloud is more than a little vague – but it appears that the idea is to make decentralized patient data sharing easy.) And of course, members have access to tools like medication refill reminders, plus the ability to refill a prescription via two-way texting, via the CVS Pharmacy.

Expect to see a lot more of this approach, which makes too much sense to ignore. In fact, CVS itself plans to launch a suite of “Transform Care” programs focused on managing expensive chronic conditions. I can only assume that its competitors will follow suit.

Meanwhile, I should note that while I expect to see providers launch similar efforts, so far I haven’t seen many attempts. That may be because patient engagement technology is relatively new, and probably pretty expensive too. Still, as value-based care becomes the dominant payment model, providers will need to get better at managing chronic diseases systematically. Perhaps, as the CVS effort unfolds, it can provide useful ideas to consider.

Newly Released Open Source Libraries for Health Analytics from Health Catalyst

Posted on December 19, 2016 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://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.

I celebrate and try to report on each addition to the pool of open source resources for health care. Some, of course, are more significant than others, and I suspect the new healthcare.ai libraries released by the Health Catalyst organization will prove to be one of the significant offerings. One can do a search for health care software on sites such as GitHub and turn up thousands of hits (of which many are probably under open and free licenses), but for a company with the reputation and accomplishments of Health Catalyst to open up the tools it has been using internally gives healthcare.ai great legitimacy from the start.

According to Health Catalyst’s Director of Data Science Levi Thatcher, the main author of the project, these tools are tried and tested. Many of them are based on popular free software libraries in the general machine learning space: he mentions in particular the Python Scikit-learn library and the R language’s caret and and data.table libraries. The contribution of Health Catalyst is to build on these general tools to produce libraries tailored for the needs of health care facilities, with their unique populations, workflows, and billing needs. The company has used the libraries to deploy models related to operational, financial, and clinical questions. Eventually, Thatcher says, most of Health Catalyst’s applications will use predictive analytics based on healthcare.ai, and now other programmers can too.

Currently, Health Catalyst is providing libraries for R and Python. Moving them from internal projects to open source was not particularly difficult, according to Thatcher: the team mainly had to improve the documentation and broaden the range of usable data connections (ODBC and more). The packages can be installed in the manner common to free software projects in these language. The documentation includes guidelines for submitting changes, so that an ecosystem of developers can build up around the software. When I asked about RESTful APIs, Thatcher answered, “We do plan on using RESTful APIs in our work—mainly as a way of integrating these tools with ETL processes.”

I asked Thatcher one more general question: why did Health Catalyst open the tools? What benefit do they derive as a company by giving away their creative work? Thatcher answers, “We want to elevate the industry and educate it about what’s possible, because a rising tide will lift all boats. With more data publicly available each year, I’m excited to see what new and open clinical or socio-economic datasets are used to optimize decisions related to health.”

Columbia-Affiliated Physician Group Plans Rollout Of Mobile Engagement Platform

Posted on December 15, 2016 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

A massive multispecialty medical practice associated with Columbia University has decided to implement a mobile patient engagement platform, as part of a larger strategy aimed at boosting patient satisfaction and ease of access to care.

The vendor behind the technology, HealthGrid, describes its platform as offering the physicians the ability to “provide actionable care coordination, access to critical health information and to enable [patient] self-care management.” HealthGrid also says that its platform will help the group comply with the requirements of Meaningful Use and MIPS.

The group, ColumbiaDoctors, includes more than 1,700 physicians, surgeons, dentists and nurses, and offers more than 230 specialty and subspecialty areas of care. All of the group’s clinicians are affiliated with New York-Presbyterian hospital and serve as faculty at Columbia University Medical Center.

The group is investing heavily in making its services more accessible and patient-friendly. In April, for example, ColumbiaDoctors agreed to roll out the DocASAP platform, which is designed to offer patients advanced online scheduling capabilities, including features allowing patients to find and book patients via mobile and desktop channels, tools helping patients find the best provider for their needs and analytics tools for business process improvement.

HealthGrid, for its part, describes itself as a CRM platform whose goal is to “meet patients where they are.” The vendor has developed a rules engine, based on clinical protocols, that connects with patients at key points in the care process. This includes reaching out to patients regarding needed appointments, education, medications and screening, both before and after they get care. The system also allows patients to pay their co-pays via mobile channels.

Its other features include automated mobile check-in – with demographic information auto-populated from the EMR – which patients can update from their mobile phones. The platform allows patients to read, update and sign off on forms such as HIPAA documentation and health information using any device.

While I’d never heard of HealthGrid before, it sounds like it has all the right ideas in place for consumer engagement. Clearly it impressed ColumbiaDoctors, which must be spending a fair amount on its latest addition. I’m sure the group’s leaders feel that if it increases patient alignment with treatment goals and improves the condition of the population it serves, they’ll come out ahead.

But the truth is, I don’t think anyone knows yet whether health organizations can meet big population health goals by interacting more with patients or spending more time in dusty back rooms fussing over big data analytics. To be sure, if you have enough money to spend they can both reach out directly to patients and invest heavily in next-generation big data infrastructure. However, my instinct is that very few institutions can focus on both simultaneously.

Without a doubt, sophisticated health IT leaders know that it pays to take smart chances, and ColumbiaDoctors is probably wise to pick its spot rather than play catch-up. Still, it’s a big risk as well. I’ll be most eager to see whether tools like HealthGrid actually impact patients enough to be worth the expense.

Vendor Study Says Wearables Can Promote Healthy Behavior Change

Posted on November 28, 2016 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

A new study backed by a company that makes an enterprise health benefits platform has concluded that wearables can encourage healthy behavior change, and also, serve as an effective tool to engage employees in their health.

The data from the study, which was sponsored by Mountain View, CA-based Jiff, comes from a two-year research project on employer-sponsored wearables. Rajiv Leventhal, who wrote about the study for Healthcare Informatics, argues that these findings challenge common employer beliefs about these type of programs, including that participation is typically limited to young and healthy employees, and that engagement with these rules can’t be sustained over time.

The data, which was drawn from 14 large employers with 240,000 employees, apparently suggests that wearable adoption and long-term engagement is possible for employees of all ages. The company reported that among the employers offered the wearables program via its enterprise health platform, 53% of employees under 40 years old participated, and 36% of employees over 50 years participated as well.

Jiff researchers also found that employee engagement had not measurably fallen for more than nine months following the program rollout, and that for one employer, levels of engagement have been progressively increasing for more than 18 months, the company reported.

According to Jiff, they have helped sustain employee engagement by employing three tactics:  Using “challenges,” time-bound immersive and social games that encourage healthy actions, “device credits,” subsidies that offset the cost of purchasing wearables and “behavioral incentives,” rewards for taking healthy actions such as walking a minimum number of steps per day.

The thing is, as interesting as these numbers might be — and they do, if nothing else, underscore the role of engaging consumers rather than waiting for them to engage with healthier behaviors on their own — the story doesn’t address one absolutely crucial issue, to wit, what concrete health impact are companies seeing from employee use of these devices.

I don’t think I’m asking for too much here when I demand some quantitative data suggesting that the setup can actually achieve measurable health results. Everything I’ve read about employee wellness initiatives to date suggests that they’ve been a giant bust, with few if any accomplishing anything measurable.

And here we have Jiff, a venture-backed hotshot company, which I’m guessing had the resources to report on results if it found any. After all, if I understand the study right, with their researchers had access to 540,000 employees for significant amount of time.  So where are the health conclusions that can be drawn from this population?

And by the way, no, I don’t accept that patient engagement (no matter how genuine) can be used as a proxy or predictive factor for health improvement. It’s a promising step in the right direction but it isn’t the real thing yet.

So, I shared the study with you because I thought you might find it interesting. I did. But I wouldn’t take it too seriously when it comes to signs of real change — either for wearables used for employee wellness initiatives. At this point both are more smoke than substance.

Are Healthcare Data Streams Rich Enough To Support AI?

Posted on November 21, 2016 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

As I’ve noted previously, artificial intelligence and machine learning applications are playing an increasingly important role in healthcare. The two technologies are central to some intriguing new data analytics approaches, many of which are designed to predict which patients will suffer from a particular ailment (or progress in that illness), allowing doctors to intervene.

For example, at New York-based Mount Sinai Hospital, executives are kicking off a predictive analytics project designed to predict which patients might develop congestive heart failure, as well as to care for those who’ve are done so more effectively. The hospital is working with AI vendor CloudMedx to make the predictions, which will generate predictions by mining the organization’s EMR for clinical clues, as well as analyzing data from implantable medical devices, health tracking bands and smartwatches to predict the patient’s future status.

However, I recently read an article questioning whether all health IT infrastructures are capable of handling the influx of data that are part and parcel with using AI and machine learning — and it gave me pause.

Artificial intelligence, the article notes, functions on collected data, and the more data AI solution has access to, the more successful the implementation will be, contends Elizabeth O’Dowd in HIT Infrastructure. And there are some questions as to whether healthcare IT departments can integrate this data, especially Internet of Things datapoints such as wearables and other personal devices.

After all, O’Dowd notes, for the AI solution to crawl data from IoT wearables, mobile apps and other connected devices, the data must be integrated into the patient’s medical record in a format which is compatible with the organization’s EMR technology. Otherwise, the organization’s data analytics solution won’t be able to process the data, and in turn, the AI solution won’t be able to evaluate it, she writes.

Without a doubt, O’Dowd has raised some important issues here. But the real question, as I see it, is whether such data integration is really the biggest bottleneck AI and machine learning must pass through before becoming accessible to a wide range of users. For example, healthcare AI-based Lumiata offers a FHIR-compliant API to help organizations integrate such data, which is certainly relevant to this discussion.

It seems to me that giving the AI every possible scrap of data to feed on isn’t the be all and end all, and may even actually less important than the clinical rationale developers uses to back up its work. In other words, in the case of Lumiata and its competitors, it appears that creating a firm foundation for the predictions is still as much the work of clinicians as much is AI.

I guess what I’m getting to here is that while AI is doubtless more effective at predicting events as it has access to more data, using what data we have with and letting skilled clinicians manage it is still quite valuable. So let’s not back off on harvesting the promise of AI just because we don’t have all the data in hand yet.

Vocera Aims For More Intelligent Hospital Interventions

Posted on November 14, 2016 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://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.

Everyday scenes that Vocera Communications would like to eliminate from hospitals:

  • A nurse responds to an urgent change in the patient’s condition. While the nurse is caring for the patient, monitors continue to go off with alerts about the situation, distracting her and increasing the stress for both herself and the patient.

  • A monitor beeps in response to a dangerous change in a patient’s condition. A nurse pages the physician in charge. The physician calls back to the nurse’s station, but the nurse is off on another task. They play telephone tag while patient needs go unmet around the floor.

  • A nurse is engaged in a delicate operation when her mobile device goes off, distracting her at a crucial moment. Neither the patient she is currently working with nor the one whose condition triggered the alert gets the attention he needs.

  • A nurse describes a change in a patient’s condition to a physician, who promises to order a new medication. The nurse then checks the medical record every few minutes in the hope of seeing when the order went through. (This is similar to a common computing problem called “polling”, where a software or hardware component wakes up regularly just to see whether data has come in for it to handle.)

Wasteful, nerve-racking situations such as these have caught the attention of Vocera over the past several years as it has rolled out communications devices and services for hospital staff, and have just been driven forward by its purchase of the software firm Extension Healthcare.

Vocera Communications’ and Extension Healthcare’s solutions blend to take pressures off clinicians in hospitals and improve their responses to patient needs. According to Brent Lang, President and CEO of Vocera Communications, the two companies partnered together on 40 customers before the acquisition. They take data from multiple sources–such as patient monitors and electronic health records–to make intelligent decisions about “when to send alarms, whom to send them to, and what information to include” so the responding nurse or doctor has the information needed to make a quick and effective intervention.

Hospitals are gradually adopting technological solutions that other parts of society got used to long ago. People are gradually moving away from setting their lights and thermostats by hand to Internet-of-Things systems that can adjust the lights and thermostats according to who is in the house. The combination of Vocera and Extension Healthcare should be able to do the same for patient care.

One simple example concerns the first scenario with which I started this article. Vocera can integrate with the hospital’s location monitoring (through devices worn by health personnel) that the system can consult to see whether the nurse is in the same room as the patient for whom the alert is generated. The system can then stop forwarding alarms about that patient to the nurse.

The nurse can also inform the system when she is busy, and alerts from other patients can be sent to a back-up nurse.

Extension Healthcare can deliver messages to a range of devices, but the Vocera badge and smartphone app work particularly well with it because they can deliver contextual information instead of just an alert. Hospitals can define protocols stating that when certain types of devices deliver certain types of alerts, they should be accompanied by particular types of data (such as relevant vital signs). Extension Healthcare can gather and deliver the data, which the Vocera badge or smartphone app can then display.

Lang hopes the integrated systems can help the professionals prioritize their interventions. Nurses are interrupt-driven, and it’s hard for them to keep the most important tasks in mind–a situation that leads to burn-out. The solutions Vocera is putting together may significantly change workflows and improve care.