Free EMR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to EMR and HIPAA for FREE!!

Unlocking The Power of Data Science In Healthcare

Written by:

Vinod Khosla, Founder of Sun Microsystems and Khosla Ventures, recently stated that “in the next 10 years, data science and software will do more for medicine than all of the biological sciences together.”

The rise of population health and healthcare analytics companies aligns with Khosla’s claim. There are hordes of companies implementing healthcare analytics and helping providers identify at-risk populations to engage in proactive care. Despite their efforts, most of the analytics companies have been struggling to help providers actually improve outcomes.

Why?

Because data science in and of itself is meaningless. Effective data science can only provide insights. The challenge is in acting on insights provided by data. This is a widely acknowledged problem that every data science / analytics company faces; this problem has been particularly difficult in healthcare where a backwards culture and incentive structure have skewed the system towards complacency and volume rather than proactive care and value.

In healthcare, the actionability and effectiveness of data science hinge on communication between providers and patients, and on patients’ ability to act on those insights. There are a few methods of provider-to-patient communication and actionability:

At the point of care (in person or virtual visit) – providers have been educating patients at the point of care since the dawn of the profession. With advanced data analytics, providers can give more accurate, more customized education during the encounter. But the problem is that patients must act on that information at home when the doctor isn’t looking over the patient’s shoulder. Patients consistently fail to do what providers have asked them to do. The problem here is that the patient education and actionability based on education are intermediated by time and (lack of) context. Patients simply forget or are unwilling to do what their providers ask them to do in order to better care for themselves. Patients aren’t being educated in the right context. Point of care education won’t encourage patients from smoking the next cigarette, taking their meds on time, or skipping cheesecake at the office party.

Patient portals – the federal government has mandated that providers enable patients to engage with providers via patient portals. The basic premise of this mandate is that with access to their own health information, patients will take better care of themselves. Patient portals have some potential to empower patients to learn about their conditions at home and investigate conditions in more depth, but they don’t solve the context problem. Patient portals won’t do anything to help patients order a salad instead of a hamburger.

Messaging and notifications – this is the least explored, least understood, and in my opinion, the most potent communication channel to impact patient behavior. Automated notifications on iOS and Android can be presented contextually provided the device has contextual data to present notifications. Context is king. We live in the age of context. As devices learn more about their owners, devices can present contextual information to help change behavior. If your smartphone (or Google Glass, Jawbone, iWatch, etc) knows that you’re about to smoke a cigarette, it can automatically connect you with your husband/wife so that they can yell at you. If your device knows that you’re out at a steakhouse for dinner with business guests, it can remind you to order grilled chicken instead of a fried steak. The number of opportunities are endless.

To provide a better sense of the power of context, let’s examine Google and Facebook ads. Facebook ads are anything but contextual. When I’m scrolling through my news feed, I don’t care about the latest Hobbit movie, some new workout shake, or Dell’s newest laptop. I logged into Facebook to check out what my friends are up to, not to learn about the Hobbit or a laptop.

But when I Google “flight from Austin to New York January 18th” there’s a huge probability that I’m already committed to spending several hundred dollars to fly to New York, get a hotel, and spend money in NYC. With that search, only relevant advertisers – airlines, taxis, hotels, and local NYC attractions – will bid for my attention; I’m not going to see an ad for The Hobbit when searching for for a trip to NY.

This sense of context is reflected in Facebook and Google’s click through rates (CTR). 1-3% of all Google searches result in the user clicking on an ad. Between .01-.3% of FaceBook ads are clicked on. Google is measurably 10-100x more effective than Facebook. That’s the power of context.

There’s nothing wrong with emailing patients PDFs and interactive digital education tools after an encounter; there’s nothing wrong with patient portals and BlueButton. All of these communication channels fall short in that they don’t take advantage of real-time two way contextual communications. All of these channels are intrinsically one-way and lack context.

Books were the the first few-to-many communication channel. Then newspapers and magazines. Then radios. Then movies and TV. The defining characteristic of the Internet is that it is the first to enable two-way, many-to-many communications. The federal government’s healthcare communication model is fundamentally based on 20th century communication strategies. The power of data science will drive meaningful changes in patient behavior only when communication strategies leverage 21st century communication models.

January 29, 2014 I Written By

Kyle is Founder and CEO of Pristine, a company in Austin, TX that develops telehealth communication tools optimized for Google Glass in healthcare environments. Prior to founding Pristine, Kyle spent years developing, selling, and implementing electronic medical records (EMRs) into hospitals. He also writes for EMR and HIPAA, TechZulu, and Svbtle about the intersections of healthcare, technology, and business. All of his writing is reproduced at kylesamani.com

Physician Focus, Data as King, and Real Time EHR Data

Written by:


I’m a little torn on this tweet. While I agree that there is too much administrative overhead in healthcare that distracts from patients and lifelong learning, I also think that things like EMR could contribute to both. A well implemented EMR software can help doctors focus on patients and help the doctor learn. This is certainly not the way most doctors look at EMR. Is this an EMR image problem or EMR software that’s not living up to its potential?


Of course, you have to take this tweet with a grain of salt since it comes from our very own Big Data Geek, Mandi Bishop. However, it’s an interesting topic of discussion. How important is the EMR data in healthcare today?


This tweet is related to the healthcare data tweet above. We all know that the EHR data isn’t perfect. Although, it’s worth noting that the paper chart wasn’t perfect either. However, I was more interested in the idea of real-time EHR data. I don’t think we’re there yet, but I’m interested to see how we could get there.

December 1, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 5000 articles with John having written over 2000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 9.3 million times. John also recently launched two new companies: InfluentialNetworks.com and Physia.com, and is an advisor to docBeat. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and Google Plus. Healthcare Scene can be found on Google+ as well.

Is the ‘Internet of Things’ Health IT’s Next Big Thing?

Written by:

Gartner Inc. has come out with a bullish report on the “internet of things,” which it predicts will add nearly $2 trillion in value to the economy by 2020 and transform the way all businesses operate.

As many as 30 billion devices with unique IP addresses will be connected, the majority of them being products, according to Gartner. That’s compared with a 2009 figure of 2.5 billion, 80 percent of them being devices such as laptops and phones.

One of the most often quoted descriptions of the internet of things comes from Helen Duce, director of the RFID Technology Auto-ID European Centre at the University of Cambridge: “We have a clear vision: to create a world where every object — from jumbo jets to sewing needles — is linked to the Internet.”

Health care would, of course, be part of the vision, which Gartner, a Stamford, Conn.-based IT research and advisory firm, calls the Digital Industrial Economy. The sector receives prominent billing, along with retail and transportation, in Garner’s latest news release on the topic.

The thinking is that physical objects — ”from roadways to pacemakers,” as McKinsey & Co. put it in one report — will produce constant data streams that can be analyzed and acted on. The possibilities for systems such as inventory control are obvious enough, as the inventory would report on itself.

In health care, a major application could be in patient monitoring. Marketplace has quoted Dr. Anthony Jones of Philips Healthcare on the possibilities: ”If I now have a continuous monitor, and I have that data going up into a central repository, I can write algorithms and put some intelligence into that repository that allows me to look for trends. So part of what the Internet of things will allow is much more sophisticated, much more continuous monitoring.” Sounds a bit like what John described in his post “Every Organ Will Have an IP Address.”

It sounds promising. But it also sounds much more incremental than it’s being portrayed by Gartner and other consultants.

Consider how Peter Sondergaard, senior vice president at Gartner, explained the future in a recent talk covered by ZDNet:

“The Digital Industrial Economy will be built on the foundations of the Nexus of Forces (which includes a confluence and integration of cloud, social collaboration, mobile and information) and the Internet of Everything by combining the physical world and the virtual.”

The predictions — Sondergaard said every object costing more than $100 will be smart by 2020 — look optimistic. Or pessimistic, depending on how you look at it: Gartner also estimates that one in three knowledge workers will be displaced by the new technologies.

About 60 percent of respondents to Gartner’s own recent CEO survey said the idea that the internet of things would replace millions of workers over the next decade-and-a-half was a “futurist fantasy,” according to SiliconANGLE. In health care, it’s hard to imagine that CIOs have much attention to devote to the internet of things amid the Meaningful Use and ICD-10 requirements they’re up against, although, as Jennifer Dennard wrote, health IT nowadays is much more than that.

The internet of things will get here. But it will probably develop in a piecemeal fashion, not in the dramatic way that Gartner envisions. Lots of “things” will get connected as companies see business reasons to put sensors in and bring them online. It will arise ad hoc from existing projects, with some industries joining the trend earlier than others.

When it does get here, there’s a good chance it won’t even be called the internet of things. In 2005, after all, Gartner was calling it the “real-world web.”

It was also predicting: “By 2015, wirelessly networked sensors in everything we own will form a new Web.”

October 17, 2013 I Written By

James Ritchie is a freelance writer with a focus on health care. His experience includes eight years as a staff writer with the Cincinnati Business Courier, part of the American City Business Journals network. Twitter @HCwriterJames.

Allscripts Strikes Deal Supplying Clinical Data To Health Plans

Written by:

Allscripts has struck a deal with a health plan industry vendor under which users of its ambulatory EMR will be able to send data to payers, reports InformationWeek. Under the terms of the deal, vendor Inovalon will funnel data to payers, and providers will receive patient-level analyses of the data in return.

Inovalon aggregates claims, lab, pharmacy, durable medical equipment, functional status and patient demographic for payers, according to InformationWeek. For 10 years, Inovalon has also been collecting clinical data from providers for its health plan customers. In recent times the vendor has been collecting data from EMRs using export and “screen scraping” methods.

Allscripts customers who choose to take advantage of the Inovalon deal will be able to integrate with Inovalon’s system simply by giving permission. “When a provider or provider group authorizes the integration, they don’t have to do any more work on site,” CEO Keith Dunleavy told IW. “The back end [of Inovalon] handles the rest, coordinating the data exchanges for the providers.”

Going out of the gate, Inovalon wasn’t able to say which payers would be receiving Allscripts data. However, Inovalon already serves hundreds of health plans which collectively cover about half of the insured population, Dunleavy told IW.

So why should providers want to send data to health plans in the first place?, asks IW editor Ken Terry.  Inovalon CEO Dunleavy had several suggestions, including the following:

*  Regulatory compliance. Providers must submit clinical data regularly for varied reasons, including processes related to claims audits, and quality assessment.

* HEDIS chart reviews.  Health plans need providers to supply HEDIS data, which is required by many state insurance departments as well as CMS.

* Shared risk arrangements. As providers increasingly get into shared risk agreements with managed care plans sharing clinical and claims data effortlessly becomes critical.

I was particularly interested in the point Dunleavy made about the need for providers and insurers to share data smoothly as risk sharing arrangements mature, something that will have to happen if accountable care is to become a reality. Perhaps solutions like these will offer a more realistic approach to meeting ACOs’ data needs then the big money efforts deep pocketed industry leaders are trying out today.

September 24, 2013 I Written By

Katherine Rourke 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.

Do Hospitals Need an EDW to Participate in an ACO?

Written by:

The following is a guest blog post by Dana Sellers, Chief Executive Officer of Encore Health Resources. Dana’s comments are in response to my post titled, “Skinny Data Solves Specific Problems While BIG DATA Looks for Unseen Problems.” For more context, also check out my post on Skinny Data in Healthcare, and my video interview with Dana Sellers.
Dana-Sellers-Encore-Health-Resources
You did a great job of nailing down the kinds of problems our industry can tackle with BIG DATA on the one hand and smart, skinny data on the other in your blog last Thursday, “Skinny Data Solves Specific Problems While BIG DATA Looks for Unseen Problems.” We here at Encore Health Resources were particularly intrigued when you asked whether skinny data would be enough for ACOs, or whether hospitals will need full enterprise data warehouses – EDWs – to meet the demands of ACOs.

I’d love to take a shot at that. As I’m sure lots of your readers know, an EDW is a collection of enterprise data based on the best guess of what an organization thinks it will need over the long run. So it’s bigger than skinny data (only what we know we need now) but smaller than Big Data (every bit of data available). So now we get to your question…do hospitals need an EDW to meet the demands of participating in an ACO?

If you’ve got one, great! In large part, we know what measures ACOs want a hospital to report. If you already have a mature, well-populated EDW — fantastic! Pull the needed data, calculate the required measures, and go for it.

If not, start with skinny data. Many organizations find that they are jumping into ACOs before they have a mature EDW. So this is a great example of where skinny data is a great idea. The concept of skinny data lets you focus on the specific data required by the ACO. Instead of spending a long time trying to gather everything you might need eventually, focus on the immediate needs: quality, readmissions, unnecessary ED visits, controlling diabetes, controlling CHF, etc. Gather that quickly, and then build to a full EDW later.

Think about a skinny data appliance. One of the problems I’m seeing across the country is that organizations are rarely talking about just one ACO. These days, it’s multiple ACOs, and each one requires a different set of metrics. I talked with an organization last week that is abandoning its current business intelligence strategy and seeking a new one because they didn’t feel the old strategy was going to be able to accommodate the explosion of measures that are required by all the ACOs and commercial contracts and Federal initiatives coming down the road. The problem is that you don’t have to just report all these measures- you actually need to perform against these measures, or you won’t be reimbursed in this new world.

One way to deal with this is to establish a sound EDW strategy but supplement it with a skinny data appliance. I doubt that’s an official term, but my mother never told me I couldn’t make up words. To me, a skinny data appliance is something that sits on top of your EDW and gives you the ability to easily extract, manipulate, report, and monitor smaller subsets of data for a special purpose. As the demands of ACOs, commercial contracts, and Federal regulations proliferate, the ability to be quick and nimble will be critical — and being nimble without an army of programmers will be important. One large organization I know estimates that the use of a smart skinny data appliance may save them several FTEs (full time equivalents) per year, just in the programming of measures.

Bottom line – I believe skinny data will support current ACO requirements. Eventually, an EDW will be useful, and skinny data is a good way to get started. Many large organizations will go the EDW route, and they will benefit from a skinny data appliance.

John, as always, I love talking with you!

July 29, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 5000 articles with John having written over 2000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 9.3 million times. John also recently launched two new companies: InfluentialNetworks.com and Physia.com, and is an advisor to docBeat. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and Google Plus. Healthcare Scene can be found on Google+ as well.

What’s Ahead After TEDMED 2013

Written by:

Last week, a number of TEDMED attendees and myself participated in a Google+ Hangout sponsored by Xerox to take a look back at our unique experiences at TEDMED 2013. The discussion included the following people:

  • Markus Fromherz, chief innovation officer of Xerox Healthcare
  • Benjamin Miller, assistant professor at the University of Colorado Denver School of Medicine
  • Nick Dawson, chief experience officer at Frontier Health Consulting
  • John Lynn, editor and founder of the Healthcare Scene blog network

We made it a really focused 15 minute discussion of the key takeaways from TEDMED. Some of the topics we discussed included: healthcare big data, multidisciplinary collaboration, citizen science, patient centered care, and a look at TEDMED topics 5-10 years from now. It was a really great discussion, and I encourage you to watch the TEDMED recap video embedded below.

Read more coverage from TEDMED from Xerox on the Real Business at Xerox Blog and follow @XeroxHealthcare.

May 15, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 5000 articles with John having written over 2000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 9.3 million times. John also recently launched two new companies: InfluentialNetworks.com and Physia.com, and is an advisor to docBeat. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and Google Plus. Healthcare Scene can be found on Google+ as well.

How Do You Improve the Quality of EHR Data for Healthcare Analytics?

Written by:

A month or so ago I wrote a post comparing healthcare big data with skinny data. I was introduced to the concept of skinny data by Encore Health Resources at HIMSS. I absolutely love the idea of skinny data that provides meaningful results. I wish we could see more of it in healthcare.

However, I was also intrigued by something else that James Kouba, HIT Strategist at Encore Health Resources, told me during our discussion at HIMSS. James has a long background in doing big data in healthcare. He told me about a number of projects he’d worked on including full enterprise data warehouses for hospitals. Then, he described the challenge he’d faced on his previous healthcare data warehouse projects: quality data.

Anyone that’s participated in a healthcare data project won’t find the concept of quality data that intriguing. However, James then proceeded to tell me that he loved doing healthcare data projects with Encore Health Resources (largely a consulting company) because they could help improve the quality of the data.

When you think about the consulting services that Encore Health Resources and other consulting companies provide, they are well positioned to improve data quality. First, they know the data because they usually helped implement the EHR or other system that’s collecting the data. Second, they know how to change the systems that are collecting the data so that they’re collecting the right data. Third, these consultants are often much better at working with the end users to ensure they’re entering the data accurately. Most of the consultants have been end users before and so they know and often have a relationship with the end users. An EHR consultant’s discussion with an end user about data is very different than a big data analyst trying to convince the end user why data matters.

I found this to be a really unique opportunity for companies like Encore Health Resources. They can bridge the gap between medical workflows and data. Plus, if you’re focused on skinny data versus big data, then you know that all of the data you’re collecting is for a meaningful purpose.

I’d love to hear other methods you use to improve the quality of the EHR data. What have you seen work? Is the garbage in leads to garbage out the key to quality data? Many of the future healthcare IT innovations are going to come from the use of healthcare data. What can we do to make sure the healthcare data is worth using?

May 8, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 5000 articles with John having written over 2000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 9.3 million times. John also recently launched two new companies: InfluentialNetworks.com and Physia.com, and is an advisor to docBeat. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and Google Plus. Healthcare Scene can be found on Google+ as well.

EMR and Health IT Development – Interview with Chetu

Written by:

Craig Schmidt - Chetu
Craig Schmidt is the Director of Global Sales for Healthcare & Pharmaceuticals at Chetu. Craig’s focus at Chetu is understanding the top healthcare industry challenges, creating relationships with HIT leaders and developing Information Technology solutions to address those challenges. Craig has, for over 15 years, held a variety of Sales and Sales Management positions with increasing responsibility in the Healthcare and Information Technology Industries.

Tell us more about Chetu and your work in the healthcare market.

It would not be an exaggeration to say that Chetu has experience in nearly every section of Healthcare IT. In our 13 years we have developed solutions for Providers, Payers, HIT Vendors and others. Just a few of the things with which we have helped customers include: complete EMR and Practice Management design and development, ePrescribing, Drug Database integration, Revenue Cycle Management (835/837 & 270/275 engines).

When does someone in healthcare look to Chetu versus doing the work in house?

The two main reasons are: they do not have the particular HIT experience in-house & they do not have enough “bandwidth” to develop in-house and do not want to hire and train permanent staff.

What’s the most challenging thing about developing applications in healthcare?

Healthcare in general and Healthcare IT are bound by many Federal, State and other rules and regulations, e.g., Meaningful Use, Affordable Care Act, HIPAA, etc. There are also a variety of standards for interoperability such as HL7, CCD/CCR.

Do you mostly do one off projects or long term contracts with your clients?

We strive to be the “Back End, Long-term” IT Partner for our clients. We offer complete solutions from application development and support to maintenance and management of applications and systems. In Healthcare we have many (over 60%) clients that have been working with Chetu for multiple years. Many of these have been with Chetu for over 5 years – which is very long-term in this market

What’s your view on SaaS vs. in house client server applications? Do you have a preferred technology stack? What do you see being used most in healthcare?

For the past several years organizations have been rapidly moving to the “Cloud.” And, there are obvious advantages for being cloud based. However, client server applications have advantages of speed and stability that can’t always be achieved with SaaS. We are now seeing a slight movement to applications that are hybrids – combining the best of both approaches.

In healthcare, there is no clear preferred technology stack. It is all over the place. We have worked in .NET, HTML5, Java, PHP, Native Mobile Apps (iOS, Android), Python, C++, Foxpro, VB, Mirth. Cobol, MUMPS and many more. Healthcare IT has traditionally seen a very fragmented approach. Chetu has the great advantage of being agnostic. We can and will work with nearly any platform or tool.

EMR usability (or lack thereof) has been a major topic of discussion. How do you manage this with your EHR clients?

We have had the opportunity to work with dozens of different EMRs; ambulatory and hospital based. Many of these EMRs are the product of individual physicians or physician groups that are unhappy with their current EMR and have not seen any existing EMRs that meet their usability needs. They have come to us with their ideas about developing an EMR from scratch. We have developed ENT, Ophthalmology, Plastic Surgery and other specialty focused EMRs stemming from this issue.

What are you seeing happening with mobile in healthcare?

There is a tremendous rush to mobile in Healthcare right now. Over the past several years our Healthcare mobile development has grown tenfold. There are many, many great mobile applications developed with patients, physicians, nurses, home health providers and others in mind. These apps have been and will continue to make providers, payers and patients lives easier and make delivering healthcare more efficient and productive.

You’ve worked with a lot of the various healthcare standards. How do they compare to the standards you work with in other industries?

There really is no parallel to the standards that guide healthcare in other industries. From my limited experience I would say that the Banking/Financial industry comes closest. But even then the amount and complexity of the standards are a fraction of what is found in Healthcare and Pharma.

Tell us about some of your work on the major hospital platforms like Siemens Soarian, Meditech and Epic. Is it a challenge working with these large companies?

These large companies have invested millions of dollars building and improving the very complex systems. So, they are rightfully concerned and selective about how and who is allowed to work in their systems. It can be a challenge, but not impossible to work with these companies. An added challenge comes from the hospitals themselves. There is the attitude that these systems are so unique that only company trained personnel have the capability to work in them.

Chetu, having worked in the Soarian, Meditech, Epic, Cerner, McKesson and other hospital platforms understands that the underlying technology in all of these systems are the same or very similar. Although each system may have unique capabilities – we recognize that the goal is the same for each. And, in getting past the UI or getting “under the hood” so to speak, we see mostly the same technologies at work.

What are the most innovative healthcare IT projects you see out there that you like working on?

Right now we are seeing a rush to capitalize on the tremendous amount of data that EMRs are generating. Data analytics using this great resource is helping pharmaceutical companies, scientists and researchers, Accountable Care Organizations – nearly everyone on the healthcare continuum provide better and less expensive patient care. This is an area that is in its infancy but we see growing rapidly.

What types of data analytics projects have you done in healthcare? Do you do just the programming component or can you do every part of a data analytics project?

Chetu has been involved in numerous healthcare analytics projects. We have helped our customers with data warehousing, data mining, OLAP, business analysis, automated report generation, multi-dimensional information “cubes”, custom reporting solutions using tools like Informatica, DTS / SSIS, Datastage and SSRS, SSAS, Cognos, Microstrategy, Crystal, OBIEE.

We have developed solutions across the complete data analytics process. From data mining and ETL to data cube and data modeling and report generation we have the experience and the people that can handle nearly any healthcare analytics project.

Full Disclosure: Chetu is an advertiser on EMR and HIPAA.

April 25, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 5000 articles with John having written over 2000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 9.3 million times. John also recently launched two new companies: InfluentialNetworks.com and Physia.com, and is an advisor to docBeat. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and Google Plus. Healthcare Scene can be found on Google+ as well.

Analytics-Driven Compassionate Healthcare at El Camino Hospital

Written by:

Given its location in the heart of Silicon Valley, it may not be remarkable that El Camino Hospital was the first hospital in the US to implement EMR. What IS remarkable is that El Camino implemented EMR 51 years ago, leveraging an IBM mainframe system that Lockheed Martin refactored for healthcare from its original intended use for the space program.

Take a moment to process that. El Camino didn’t need PPACA, Meaningful Use, HITECH, or HIPAA to tell them health data is critical. El Camino saw the value in investing in healthcare IT for electronic data capture and communication without federal incentive programs or lobbyists. With that kind of track record of visionary leadership, it’s no wonder they became early analytics program adopters, and recently turned to Health Care DataWorks (HCD) as a trusted partner.

When I sat down with executive leadership from El Camino and HCD to discuss the journey up Tom Davenport‘s analytics maturity scale from rudimentary operational reporting to advanced analytics, I expected a familiar story of cost pressure, clinical informatics, quality measure incentives or alternative payment models as the business drivers for new insights development. Instead, I heard the burgeoning plan for a visionary approach to patient engagement and “analytics-driven compassionate care”.

Greg Walton, CIO of El Camino Hospital, admitted that initial efforts to implement an analytics program had resulted in “textbook errors”: “’Competing on Analytics’ was easier to write than execute,” he said. Their early efforts to adopt and conform to a commercially-available data model were hindered by the complexity of the solution and the philosophy of the vendor. “One of the messages I would give to anybody is: do NOT attempt this at home,” Greg laughed, and El Camino decided to change their approach. They sought a “different type of company…a real-life company with applicable lessons learned in this space.”

“The most important thing to remember in this sector: you’re investing in PEOPLE. This is a PEOPLE business,” Greg said. “And that if there’s any aspect of IT that’s the most people-oriented, it’s analytics. You have to triangulate between how much can the organization absorb, and how fast they can absorb it.” In HCD, El Camino found an analytics organization partner whose leadership and resources understand healthcare challenges first, and technology second.

To address El Camino’s need for aggregated data access across multiple operational systems, HCD is implementing their pioneering KnowledgeEdge Enterprise Data Warehouse solution,including its enterprise data model, analytic dashboards, applications and reports. HCD’s technology, implementation process, and culture is rooted in their deep clinical and provider industry expertise.

“The people (at HCD) have all worked in hospitals, and many still work there occasionally. Laypersons do not have the same understanding; HCD’s exposure to the healthcare provider environment and their level of experience provides a differentiator,” Greg explained. HCD impressed with their willingness to roll up their sleeves and work with the hospital stakeholders to address macro and micro program issues, from driving the evaluation and prioritization of analytics projects to identifying the business rules defining discharge destination. And both the programmers and staff are “thrilled,” Greg says: “My programmers are so happy, they think they’ve died and gone to heaven!”

This collaborative approach to adopting analytics as a catalyst for organizational and cultural change has lit a fire to address the plight of the patient using data as a critical tool. Greg expounded upon his vision to achieve what Aggie Haslup, Vice President of Marketing for HCD, termed “analytics-driven compassionate care”:

We need to change the culture about data without losing, and in fact enhancing, our culture around compassion. People get into healthcare because they’re passionate about compassion. Data can help us be more compassionate. US Healthcare Satisfaction scores have been basically flat over the last 10 years. Lots of organizations have tried to adopt other service industry tools: LEAN,6S; none of those address the plight of the patient. We’ve got to learn that we have to go back to our roots of compassion. We need to get back to the patient, which means “one who suffers in pain.” We want (to use data) to help understand more about person who’s suffering. My (recent) revelation: what do you do w/ guests in your house? Clean the house, put away the pets, get food, do everything you can to make guests comfortable. We want to know more about patients’ ethnicity, cultural heritage, the CONTEXT of their lives because when you’re in pain, what do you fall back on? Cultural values. We want a holistic view of the patient, because we can provide better, compassionate care through knowing more about patients. We want to deploy a contextual longitudinal view of the patient…and detect trends in satisfaction with demographics, clinical, medical data.

What a concept. Imagine the possibilities when a progressive healthcare provider teams with an innovative analytics provider to harness the power of data to better serve the patient population. I will definitely keep my eye on this pairing!

March 25, 2013 I Written By

Mandi Bishop is a healthcare IT consultant and a hardcore data geek with a Master's in English and a passion for big data analytics, who fell in love with her PCjr at 9 when she learned to program in BASIC. Individual accountability zealot, patient engagement advocate, innovation lover and ceaseless dreamer. Relentless in pursuit of answers to the question: "How do we GET there from here?" More byte-sized commentary on Twitter: @MandiBPro.

ACOs Want Advanced Analytics, Data Warehousing, But Are They Ready?

Written by:

ACOs are gunning to acquire advanced analytics tools and data warehousing capabilities, according to a report in iHealthBeat.  This conclusion comes from a new report from IDC Health Insights, which did a May 2012 survey of 40 hospitals and health insurance companies plus interviews with vendors and industry talking heads.

As part of the survey, IDC asked about ACOs’ top investment priorities, and found 50 percent most want advanced analytics capabilities, while 46 percent cited data warehousing.

The report also noted that ACO-involved entities are picking up analytics capabilities by acquiring infrastructure and software, as well as bringing informatics and data analysis experts on staff.

When asked what kind of information they’d like to review using analytics, they stated the following, according to iHealthBeat:

  • 73% of survey respondents cited clinical structured data
  • 70% cited care management data
  • 57% cited claims data
  • 42% cited data from mobile devices
  • 32% cited data from social media sources
  • 29% cited unstructured clinical data

And when asked what functions they’d put the analytics data to use on, they responded as follows, iHealthBeat said:

  • 66% of survey respondents cited identifying at-risk patients
  • 64% cited tracking clinical outcomes
  • 57% cited clinical decision-making at the point of care

All that being said, it’s not clear that the ACO participants know how to put these visions into action, argues John Moore of Chilmark Research. In a post-HIMSS wrap-up, Moore argues that the market for healthcare analytics tools is “hyped beyond imagination,” and that beyond the hype, many providers are actually clueless as to what they want from analytics.

At HIMSS, he says,  he found a “very immature” buyers’ market in which providers aren’t even sure what they’re asking for in analytics, or why they need these tools in the first place. In fact, Moore notes, he talked to many vendors who have stopped responding to “horrible” RFPs which suggest that institutions aren’t at all ready to pursue an analytics solution.

This wouldn’t be the first time that the hype factor exceeded the industry’s actual understanding of a product or technology.  But buying analytics tools before you have a clue how to use them is a particularly serious financial and strategic mistake, wouldn’t you say?

March 18, 2013 I Written By

Katherine Rourke 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.