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Patient Engagement and Collaborative Care with Drex DeFord

Posted on August 7, 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.

#Paid content sponsored by Intel.

You don’t see guys like Drex DeFord every day in the health IT world. Rather than following the traditional IT career path, he began his career as a rock ‘n roll disc jockey. He then served as a US Air Force officer for 20 years — where his assignments included service as regional CIO for 12 hospitals across the southern US and CTO for Air Force Health — before focusing on private-sector HIT.

After leaving the Air Force, he served as CIO of Scripps Health, Seattle Children’s Hospital and Steward Health before forming drexio digital health (he describes himself as a “recovering CIO”). Drex is also a board member for a number of companies and was on the HIMSS National board and the Chairman of CHIME.

Given this extensive background in healthcare IT leadership, we wanted to get Drex’s insights into patient engagement and collaborative care. As organizations have shifted to value based reimbursement, this has become a very important topic to understand and implement in an organization. Have you created a culture of collaborative care in your organization? If not, this interview with Drex will shed some light on what you need to do to build that culture.

You can watch the full video interview embedded below or click from this list of topics to skip to the section of the video that interests you most:

What are you doing in your organization to engage patients? How are you using technology to facilitate collaborative care?

The B2B Vendors are Coming! The B2B Vendors are Coming!

Posted on March 10, 2017 I Written By

Colin Hung is the co-founder of the #hcldr (healthcare leadership) tweetchat one of the most popular and active healthcare social media communities on Twitter. Colin speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He is currently an independent marketing consultant working with leading healthIT companies. Colin is a member of #TheWalkingGallery. His Twitter handle is: @Colin_Hung.

It’s been a couple of weeks since the annual HIMSS conference wrapped up for 2017 and I’m just starting to emerge from the HIMSS-Haze of sleep deprivation. I doff my hat to those that recovered more quickly.

As usual there was too much to take in at HIMSS17. The keynotes were fantastic, the sessions educational and the exhibit hall had a buzz about it that was absent from last year’s event. Although the main take-away from HIMSS17 seems to be the emergence of Artificial Intelligence, I believe something else emerged from the event – something that may have far greater ramifications for HealthIT in the short term.

For me the big story at HIMSS17 was the arrival of mainstream IT companies. I have been going to HIMSS for 10 years now and I can honestly say this year was the first time that non-traditional healthcare IT vendors were a noticeable force. SAP, IBM (Watson), Intel, Google, Salesforce, Samsung and Microsoft were just a few of the B2B vendors who had large booths in the HIMSS17 exhibit hall.

Salesforce was particularly noteworthy. They made a big splash with their super-sized booth this year. It was easily five times the size of the one they had at HIMSS16 and featured a fun “cloud viewer” at its center along with a large theatre for demonstrations.

Salesforce, however, didn’t stop there. They also threw a HUGE party over at Pointe Orlando on Tuesday night. At one point, the party had a line of eager attendees that snaked out the front of the facility. Their party rivaled that of several large EHR vendors.

IBM was also back at HIMSS after an extended absence. Their “organic booth” was always busy with people curious to learn more about IBM Watson – particularly after the keynote given by CEO Ginni Rometty on Day 1.

So what does the arrival of mainstream B2B vendors mean for healthcare?

Consolidation. The EHR gold rush is over and yet companies like SAP and Salesforce are still electing to invest in healthcare. Why would they do that at a time when government incentive money has all but dried up? I believe it’s because they smell consolidation and optimization opportunities. These B2B players have large war chests and as HealthIT companies begin to struggle, they will be knights in shining armor waiting to swoop in.

More Consumer Technologies. One of the big trends in healthcare right now is consumerism. There is a drive by healthcare organizations to adopt consumer-centric technologies and workflows to service patients better. Patients are seeking providers that offer the conveniences that they are used to as consumers: online appointment booking, mobile chat, real-time price quotes, etc. Companies like Google, Samsung, IBM and Microsoft already have technologies that work well in the consumer world. With growing demand in healthcare it’s only natural that they are investing.

Standards. Maybe I’m just being optimistic, but when companies like TSYS (a very large financial transaction processor) show up at HIMSS for the first time, one can only hope that standards and interoperability will soon follow. After all, if cut-throat banks can agree on a common way to share information with each other, surely the same can happen in healthcare.

Cognitive Computing. Google, IBM, Microsoft and Intel have all made big bets on cognitive computing. I’m willing to bet that their investments in this area dwarf anything that a HealthIT company has made – including Epic and Cerner. IBM and Microsoft in particular have been aggressively seeking partners to work with them on health applications for Artificial Intelligence. Just ahead of HIMSS17, Microsoft and UPMC Enterprises announced that they would be working together to “create new products aimed at transforming care delivery”.

I’m very excited by the arrival of these B2B technology vendors. I think it signals the start of a maturation phase in the HealthIT industry, one in which consolidation and collaboration break down legacy silos. At the very least, traditional HealthIT companies like Cerner, Epic, athenahealth and NextGen will now have to step up their game in order to fend off these large, well-funded entrants.

Exciting times!

UCSF Partners With Intel On Deep Learning Analytics For Health

Posted on January 30, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

UC San Francisco’s Center for Digital Health Innovation has agreed to work with Intel to deploy and validate a deep learning analytics platform. The new platform is designed to help clinicians make better treatment decisions, predict patient outcomes and respond quickly in acute situations.

The Center’s existing projects include CareWeb, a team-based collaborative care platform built on Salesforce.com social and mobile communications tech; Tidepool, which is building infrastructure for next-gen smart diabetes management apps; Health eHeart, a clinical trials platform using social media, mobile and realtime sensors to change heart disease treatment; and Trinity, which offers “precision team care” by integrating patient data with evidence and multi-disciplinary data.

These projects seem to be a good fit with Intel’s healthcare efforts, which are aimed at helping providers succeed at distributed care communication across desktop and mobile platforms.

As the two note in their joint press release, creating a deep learning platform for healthcare is extremely challenging, given that the relevant data is complex and stored in multiple incompatible systems. Intel and USCF say the next-generation platform will address these issues, allowing them to integrate not only data collected during clinical care but also inputs from genomic sequencing, monitors, sensors and wearables.

To support all of this activity obviously calls for a lot of computing power. The partners will run deep learning use cases in a distributed fashion based on a CPU-based cluster designed to crunch through very large datasets handily. Intel is rolling out the computing environment on its Xeon processor-based platform, which support data management and the algorithm development lifecycle.

As the deployment moves forward, Intel leaders plan to study how deep learning analytics and machine-driven workflows can optimize clinical care and patient outcomes, and leverage what they learn when they create new platforms for the healthcare industry. Both partners believe that this model will scale for future use case needs, such as larger convolutional neural network models, artificial networks patterned after living organizations and very large multidimensional datasets.

Once implemented, the platform will allow users to conduct advanced analytics on all of this disparate data, using machine learning and deep learning algorithms. And if all performs as expected, clinicians should be able to draw on these advanced capabilities on the fly.

This looks like a productive collaboration. If nothing else, it appears that in this case the technology platform UCSF and Intel are developing may be productized and made available to other providers, which could be very valuable. After all, while individual health systems (such as Geisinger) have the resources to kick off big data analytics projects on their own, it’s possible a standardized platform could make such technology available to smaller players. Let’s see how this goes.

Paris Hospitals Use Big Data To Predict Admissions

Posted on December 19, 2016 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Here’s a fascinating story in from Paris (or par-ee, if you’re a Francophile), courtesy of Forbes. The article details how a group of top hospitals there are running a trial of big data and machine learning tech designed to predict admission rates. The hospitals’ predictive model, which is being tested at four of the hospitals which make up the Assistance Publiq-Hopitaux de Paris (AP-HP), is designed to predict admission rates as much as 15 days in advance.

The four hospitals participating in the project have pulled together a massive trove of data from both internal and external sources, including 10 years’ worth of hospital admission records. The goal is to forecast admissions by the day and even by the hour for the four facilities participating in the test.

According to Forbes contributor Bernard Marr, the project involves using time series analysis techniques which can detect patterns in the data useful for predicting admission rates at different times.  The hospitals are also using machine learning to determine which algorithms are likely to make good predictions from old hospital data.

The system the hospitals are using is built on the open source Trusted Analytics Platform. According to Marr, the partners felt that the platform offered a particularly strong capacity for ingesting and crunching large amounts of data. They also built on TAP because it was geared towards open, collaborative development environments.

The pilot system is accessible via a browser-based interface, designed to be simple enough that data science novices like doctors, nurses and hospital administration staff could use the tool to forecast visit and admission rates. Armed with this knowledge, hospital leaders can then pull in extra staffers when increased levels of traffic are expected.

Being able to work in a distributed environment will be key if AP-HP decides to roll the pilot out to all of its 44 hospitals, so developers built with that in mind. To be prepared for the future, which might call for adding a great deal of storage and processing power, they designed distributed, cloud-based system.

“There are many analytical solutions for these type of problems, [but] none of them have been implemented in a distributed fashion,” said Kyle Ambert, an Intel data scientist and TAP contributor who spoke with Marr. “Because we’re interested in scalability, we wanted to make sure we could implement these well-understood algorithms in such a way that they work over distributed systems.”

To make this happen, however, Ambert and the development team have had to build their own tools, an effort which resulted in the first contribution to an open-source framework of code designed to carry out analysis over scalable, distributed framework, one which is already being deployed in other healthcare environments, Marr reports.

My feeling is that there’s no reason American hospitals can’t experiment with this approach. In fact, maybe they already are. Readers, are you aware of any US facilities which are doing something similar? (Or are most still focused on “skinny” data?)

UPMC Kicks Off Mobility Program

Posted on July 1, 2014 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

If you’re going to look at how physicians use health IT in hospitals, it doesn’t hurt to go to doctors at the University of Pittsburgh Medical Center, a $10 billion collosus with a history of HIT innovation. UPMC spans 21 hospitals and employs more than 3,500 physicians, and it’s smack in the middle of a mobile rollout.

Recently, Intel Health & Life Sciences blogger Ben Wilson reached to three UPMC doctors responsible for substantial health IT work, including Dr. Rasu Shrestha, Vice President of Medical Information for all of UPMC, Dr. Oscar Marroquin, a cardiologist responsible for clinical analytics and new care model initiatives, and Dr. Shivdev Rao, an academic cardiologist.

We don’t have space to recap all of the stuff Wilson captured in his interview, but here’s a few ideas worth taking away from the doctors’ responses:

Healthcare organizations are “data rich and information poor”: UPMC, for its part, has 5.4 petabytes of data on hand, and that store of data is doubling every 18 months. According to Dr. Shrestha, hospitals must find ways to find patterns and condense data in a useful, intelligent, actionable manner, such as figuring out whether there are specific times you must alert clinicians, and determine whether there are specific sensors tracking to specific types of metrics that are important from a HIM perspective.

Mobility has had a positive impact on patient care:  These doctors are enthusiastic about the benefits of mobility.  Dr. Marroquin notes that not only do mobile devices put patient care information at his finger tips and allow for intelligent solutions, it also allows him to share information with patients, making it easier to explain why he’s doing a give test or treatment.

BYOD can work if sensitive information is protected:  UPMC has been supporting varied mobile devices that physicians bring into its facilities, but has struggled with security and access. Dr. Shrestha notes that he and his colleagues have been very careful to evaluate all of the devices and different operating systems, making sure data doesn’t reside on a mobile device without some form of security.

On the self-promotion front, Wilson asks the doctors about a pilot  project (an Intel and Microsoft effort dubbed Convergence) in which clinicians use Surface tablets powered by Windows 8. Given that this is an Intel blog, you won’t be surprised to read that Dr. Shrestha is quite happy with the Surface tablet, particularly the form factor which allows doctors to flip the screen over and actually show patients trends.

Regardless, it’s interesting to hear from doctors who are gradually changing how they practice due to mobile tech. Clearly, UPMC has solved neither its big data problems nor phone/tablet security issues completely, but it seems that its management is deeply engaged in addressing these issues.

Meanwhile, it will be interesting to see how far Convergence gets. Right now, Convergence just involves giving heart doctors at UPMC’s Presbyterian Hospital a couple dozen Microsoft Surface Pro 3 tablets, but HIT leaders plan to eventually roll out 2,000 of the tablets.

EHRs Can Generate Meaningful Return On Investment

Posted on September 27, 2013 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Well-implemented EMRs can certainly generate Meaningful Use incentive payoffs, but that’s far from the only way that they can help a practice generate return on their EHR investment.

According to “Return on Investment in EHRs,” a whitepaper sponsored by GBS, HP, Intel and Nextgen, properly implemented EHRs can do a great deal to generate ROI for medical practice above and beyond qualifying them for MU payoffs.

The paper notes that many practices have achieved a return on investment in their EHRs without receiving external incentives. As it points out, a Health Affairs study from 2005 found that while initial EHR costs averaged $44,000 per full-time equivalent, and ongoing costs averaged $8,500 per provider per year, the average practice paid for EHR costs in 2.5 years and generated a profit after that.

Eleven of the 14 practices studied by Health Affairs had “tightly integrated” EHR and practice management systems, a factor the paper contends was highly relevant to their success with their EHR implementation. Not only did providers use the EHR for common tasks, almost all used it to help with billing. Ten of the practices no longer pull paper charts at all, the study noted.

EHRs also improve efficiency and productivity in the following ways, the paper argues:

* More appropriate coding: Properly-designed EHRs help physicians with coding by displaying the appropriate code based on the documentation entered during a patient encounter. This avoids costly undercoding.

* Greater efficiency: The use of point-and-click templates lessens and in some cases eliminates transcription costs, which can be up to 11 percent of collections.

* Reduction in soft costs: Fully-enabled EHRs also remove many “soft costs” that practices occur, such as the time it takes to call in prescriptions. Also, once doctors learn how to use the EHR, they can complete most of the notes during or between patient visits, leaving them with time to either see more patients or go home earlier.

It’s great to think that medical practices can generate ROI on their EHR investment, but given that the sponsors of this paper have their own agenda, I’m not taking everything they say at face value. What do you think, readers? Have you seen situations in which practice EHRs generate significant ROI independently of what they take in in Meaningful Use dollars?