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Interview with Dana Sellers: Encore Pay for Perfomance (P4P) Managed Services

Posted on February 20, 2014 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 6000 articles with John having written over 3000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 13 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.

The following is an interview with Dana Sellers, CEO of Encore Health Resources about their new Pay for Performance Managed Services offering which they’ll be sharing at HIMSS 2014.
Dana Sellers
Tell us your vision for how your new P4P Managed Services will work.
Our vision is to help our clients manage performance and data components against payer contracts to maximize quality, obtain incentives, and avoid penalties. Our offering uses a combination of Encore subject-matter experts (SMEs), software tools, and methodologies that we’ve already tested and proven in large healthcare systems. P4P Managed Services lifts the burden of meeting these value-based demands off our clients’ shoulders and into Encore’s hands. As part of this innovative offering, we also share risks and rewards via multi-year partnerships. We work with clients to ensure that they have the trusted data they need to support performance improvement and obtain incentives.

Our service begins with the P4P Value-driven Roadmap, which identifies the dollars and associated measures at stake in clients’ at-risk, value-based contracts — including projections for the next few years. As input for the roadmap, we perform a data assessment of a client’s EHR and other source systems to determine if they are capturing the right data for the targeted measures. The roadmap defines the multi-year data and process program required to obtain the desired incentives.

Next, we establish this required program along with data governance, technology, and data tools. We also build the value components of the program, including EHR remediation, workflow redesign, change management, data profiling, ETL, and dashboards required to monitor performance.

Once the program foundation is established, the value-management cycle begins. Encore monitors each client’s performance, providing insight through performance analysis and suggesting needed performance improvements to meet all targeted incentives and enhance the quality of care. Also, as new contracts emerge, we work with clients to incorporate new eMeasures into the program.

By creating trusted, transparent data, Encore helps health systems transform and meet new payment-model requirements by using eMeasures to adhere to evidence-based standards. The result is better patient care and an improved bottom line. We provide the consulting expertise, unique methodologies, and our own, in-house developed software tools to help our clients succeed — as we’ve proven by our results in helping other large clients accelerate their achievements through eMeasures.

Why did you choose to offer a service like this?
We know EHR data! Our methodologies and software tools are built around EHR data and eMeasures.

Encore was founded to provide consulting services with a focus on analytics fueled by clinical data. In the broad spectrum of consulting services that we provide – from HIT and clinical advisory to implementation, go-live services, and analytics — our focus is trained on identifying and gathering the data that our clients need to improve healthcare and operational performance. Therefore, our P4P Managed Services offering is a natural extension of our mission. At-risk contracts require the ability to track eMeasures, which has been an Encore strength – and differentiator — since our founding five years ago.

Our vision for P4P Managed Services is also supported by our clients – especially CIOs and CFOs. They have told us that they need assistance with all aspects of data capture, analytics, and performance improvement. When we lift that burden from our clients’ shoulders, it frees them to focus on other critical issues, such as cost reduction, while we leverage our unique expertise and proven experience to manage the value side of the equation.

Which P4P programs do you see Encore supporting?
We support measures — quality measures that go back to incentives. These include Medicare, Medicaid, commercial P4P/Fee-for-Value type contracts, IQR, PQRS, ACO, ACAs, ACCs, NQF/CQMs, PCMH, PCQUS, clinically integrated networks, and the like.

Our methodology and tools tie the eMeasures directly to workflow, so we know how to change each client’s workflow to get better results. Our knowledge bases include over 350 eMeasures.

How much of this offering is technical and how much of it is services.
This is an important question. Encore is first and foremost a services company – a services company that is strongly differentiated by unmatched, in-house-developed software solutions that are uniquely designed to support the services we provide. So our new offering is precisely that: services supported by innovative technology and processes on a flexible, as-needed basis.

What does the cost structure look like for this service?
As described earlier, the P4P Managed Services cost structure is based upon a roadmap we define with each client to quantify the value-based, at-risk dollars and the client’s capabilities to manage the quality-performance components of their at-risk contracts. Contract details, therefore, will vary with each client’s situation. The bottom line is that Encore is willing to manage our P4P Managed Services contracts while working with clients to define a risk-sharing arrangement that incents everyone to achieve.

Why would an organization choose to outsource the P4P to Encore as opposed to doing it in-house?
The process of managing performance against eMeasures across a health system is complex, and many clients have not put together a disciplined approach to performance improvement. Further, many of our clients are telling us that they simply do not have the full complement of expertise, resources, technology, and program-management disciplines available to move fast enough against a dizzying array of government and commercial at-risk contracts. But we do, and we – especially our skilled eMeasures experts — have a track record that proves it.

Also, an increasing number of health systems are recognizing that they’ll have to enter a world of eMeasures that is growing every year. With P4P Managed Services, we bring the expertise, skills, tools, and methodology that can take this eMeasure world and our clients under our wing. Our new service provides clients the breathing room to focus on multiple fronts simultaneously – and not leave any dollars on the table as a result.

A third reason for choosing our new offering is because it’s a cost-conscious solution. We eliminate the need for clients to hire more architects, eMeasures specialists, analysts, and report builders.

Finally, P4P Managed Services can preserve endangered species. That is, we supplement our clients’ existing IT department with some of the hardest resources to find: clinicians and operational SMEs with an understanding of data; eMeasures experts; and, technical SMEs with an understanding of the clinical and the operational worlds.

How much accountability is Encore taking on with these P4P Managed Services? Where do you draw the line?
Our new offering is a full life-cycle solution that we approach as a partnership. We nail down the amount of accountability – the risk that we’re able to share – on a case-by-case basis through the roadmap. Depending upon what we learn, we then determine the degree of accountability that both we and our clients can share to incent the highest levels of achievement.

Is there some risk on Encore’s part that the client will fall short on what they need to accomplish for Encore to provide the P4P services? Encore can’t go in and do the documentation for the doctor.
This is precisely what our new service is in place to define. As with every engagement, we use a thorough, careful assessment process to ascertain the nature of the challenges involved. With P4P Managed Services, that means understanding:
• The incentives involved
• The risk involved if our clients can’t achieve optimal revenue reimbursement – say with Medicare and Medicaid contracts
• The risk involved for Encore if those contractual incentives are not earned
Bottom line: we both win, or we both lose. With P4P managed services, we are convinced that we can define on a case-by-case basis the mix of Encore services, solutions, and client resources that Encore will manage to produce a win or multiple wins for both sides.

This feels similar to revenue cycle management (RCM) applied to P4P programs. Can you apply some of the RCM learnings to this type of offering?
Yes, similarities do exist between RCM and the management of quality performance components of at-risk contracts. The way we see it, RCM has been responsible for collecting patient data and getting claims ready for a long time. It remains fairly unchanged and encompasses the management of people, processes, and technology across health systems to improve revenue collection. By tying eMeasures to clinical rather than latent claims data, performance issues can be corrected within a few days. That is because the use of EHR data literally “moves the needle” in real time. Beyond claims data, we use EHR clinical data to affect change that meets the required quality measures thresholds.

At present, there is an increased focus on traditional cost monitoring, which informs RCM. This typically happens at the service line and department level; not at the episode-of-care level. Although direct, indirect, fixed, and ad-hoc costs are certainly important and are included, value-based cost control and reduction efforts must focus on the clinical processes, just like the quality performance components. Both will require tracking the costs and quality across the entire continuum of care, constantly analyzing performance and applying adjustments. And the revenue cycle is a significant piece of this. So the discipline and techniques needed for RCM can certainly inform a health system’s approach to fee-for-value focused management.

Do you see this as the start of offering even more Managed Services offerings?
Yes. We are now working on another offering – it’s in the packaging stages – around Meta-Data Management. Stay tuned for more details later this year.

Can Big Data Do What Vendors Claim?

Posted on December 6, 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.

There’s no doubt about it — the air is ringing with the sounds of vendors promising big things from big data, from population health to clinical support to management of bundled payments. But can they really offer these blessings?  According to enterprise health IT architect Michael Planchart (known to many as @theEHRGuy), there’s a lot of snake oil sales going on.

In his experience, many of the experts on what he calls Big Bad Data either weren’t in healthcare or have never touched healthcare IT until the big data trend hit the industry. And they’re pitching the big data concept to providers that aren’t ready, he says:

  • Most healthcare providers haven’t been collecting data in a consistent way with a sound data governance model.
  • Most hospitals have paper charts that collect data in unstructured and disorganized ways.
  • Most hospitals — he asserts — have spent millions or even billions of dollars on EMRs but have been unable to implement them properly. (And those that have succeeded have done so in “partial and mediocre ways,” he says.)

Given these obstacles,  where is big data going to come from today? Probably not the right place, he writes:

Well, some geniuses from major software vendors thought they could get this data from the HL7 transactions that had been moving back and forth between systems.  Yes, indeed.  They used some sort of “aggregation” software to extract this data out of HL7 v2.x messages.  What a disaster!  Who in their sane mind would think that transactional near real time data could be used as the source for aggregated data?

As Planchart sees it, institutions need quality, pertinent, relevant and accurate data, not coarsely aggregated data from any of the sources hospitals and providers have. Instead of rushing into big data deals, he suggests that CIOs start collecting discrete, relevant and pertinent data within their EMRs, a move which will pay off over the next several years.

In the mean time, my colleague John Lynn suggests, it’s probably best to focus on “skinny data” – a big challenge in itself given how hard it can be to filter out data “noise” — rather than aggregate a bunch of high volume data from all directions.

NC Health System Uses Big Data To Improve Care

Posted on November 22, 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.

While everybody talks about the potential for so-called “big data” in healthcare, there seems to be more smoke than fire at this point. To date, health payers have been a lot more engaged with using big data than providers, according to IDC Health Insights.

That being said, there are some providers out there who have been able to get their arms around big data projects which improve careFierceHealthIT reports.

One example is the University of North Carolina Health Care (UNCHC), a health system based in Chapel Hill, N.C., where they’ve begun programs to leverage big data in improving the quality of care and reporting, according to FierceHealthIT.

As the UNCHC system has grown, it’s seen a dramatic increase in the amount of data each facility was holding — and making things even more challenging, 80 percent of the data was unstructured, according to Carlton Moore, MD, associate professor of medicine at UNCHC.

As Dr. Moore notes, it’s difficult to use unstructured data to meet accountable care objectives. For example, when patients get cancer screenings at another institution, physicians write that in the unstructured notes, but don’t check off that they’ve  had the study because it wasn’t done there.

But UNCHC has taken on the mass of data under its roof. It’s developed a unique algorithm inserted into a natural language processing plan which allows researchers to find and address abnormal results on pap smears and mammography screenings.

While this is just a beginning, UNCHC has bigger plans. It intends to take next steps in analyzing and using its mass of data such as analyzing medication compliance and determining the number of clinic visits associated with bad health outcomes.

Kudos to UNHCH on their progress. But I don’t expect to see a ton of these projects showing up in the public arena; there’s just too much involved, particularly with ICD-10 and Meaningful Use draining resources like crazy.

In the mean time, though, providers may want to embrace “skinny” healthcare data, argues my colleague John Lynn.  The concept:  instead of creating a huge enterprise data warehouse for all purposes, why not focus on smaller problems?  That might be a faster path to results, and a decent preparation for the big data future, no?

Partners Launches Major Data Integration Project

Posted on October 8, 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.

Partners HealthCare is launching a major data integration project which should bring it closer to its goal of implementing a single EMR across the entire Partners network over the next few years.

About a year ago, Partners announced that it would be integrating all electronic health information management into a single system that would serve the whole organization by 2017.

The Partners eCare initiative, massive by any standards, is the largest program of its kind in the history of the institution, Healthcare IT News reports. eCare’s mission is to enable systems that offer “one patient, one record, one team, one Partners statement.” eCare is ultimately intended to achieve some transformative goals, including redesigning patient care models and advancing population health management.

For this part of the project, partner InterSystems will replace several existing integration engines and enable the health system to consolidate its financial and clinical technologies into a single EMR platform, Healthcare IT News says. In doing so it will be working closely with Epic, Partners’ EMR vendor.

This is only the latest InterSystems deal for Partners, which uses the vendor’s Cache database for its existing EMR and hundreds of apps used by thousands of clinicians throughout its network, HIN notes. Partners also uses InterSystems’ Ensemble rapid integration software, which has enabled integration of its library of services and applications.

As this is going on, Partners’ division The Center for Connected Health is breaking ground on delivering new forms of patient care outside of standard medical settings. One experiment going on now is an effort in which Partners channels remotely-collected patient health data in its EMR. As of June, the Center’s remote monitoring database stored over 1.2 million patient vital signs.

With the Center working to change how and where care is delivered, and Partners corporate building an EMR capable (presumably) of making some use of this data, it’ll be interesting to see the end result. To date, EMRs have not been equipped to integrate remote monitoring data smoothly — but perhaps Partners will pull it off.

Big Data, Predictive Analytics Priorities For Healthcare Organizations

Posted on August 16, 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.

Leveraging big data and healthcare analytics are key initiatives for C-suite healthcare executives, but barriers to making progress still remain, according to an item in iHealthBeat.

According to a survey by the eHealth Initiative and the College of Health Information Management Executives, about 80 percent of CIOs and other C-suite healthcare executives see big data and predictive analytics use as important goals for their organizations, iHealthBeat reports.

But it won’t come easy. In fact, 84 percent of respondents said that implementing these strategies and tools are a challenge for their organization. And only 45 percent said they had a plan in place to manage the growing volume of electronic data.

The survey, which questioned 102 executives in May and June, found that 90 percent of respondents used analytics for quality improvement, 90 percent used analytics for revenue cycle management, and 66 percent used analytics for fraud prevention. Also, 82 percent of survey respondents said that population health management is important to their analytic strategy.

Meanwhile, 82 percent of those responding said that health information exchange is important, according to iHealthBeat.

As for data sources, administrative- and claims-based data were most used, at 77 percent and 75 percent respectively. Eighteen percent of respondents’ staff were trained to handle the data, and 16 percent used third-party organizations to overcome staff shortages for data analysis.

Despite execs’ enthusiasm for big data/predictive analytics use, however, significant obstacles remain to rolling out such programs, iHealthBeat reports.  According to a separate CIC Advisory survey, budget strain and lack of needed skills is delaying the use of analytics at many healthcare organizations.

According to that survey, building an enterprise analytics system is held back by the difficulty of integrating different analytic systems. Moreover, most organizations don’t have a dedicated analytics or business intelligence team, and many rely on outside analytics consultants.

All of that being said, it seems guaranteed that hospitals and other healthcare organizations will eventually find a way to leverage big data. Healthcare organizations expect to keep ramping up their spending on data discovery and predictive analytics in coming months and years, research suggests.

In the mean time, however, there’s a ton of work to do, staff to be hired and trained and integration to be done. It’s going to be an uphill battle.

Trusting Healthcare Data

Posted on August 9, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 6000 articles with John having written over 3000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 13 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.

Healthcare is generating data at an unprecedented rate. EHR software is becoming a large repository of healthcare data. Patient portals are starting to get data from patients. Labs are creating large amounts of data. Insurance companies have been collecting and playing with data for years. We’re surrounded by healthcare data. The question is: How do we make sure they trust the data?

Anyone who has worked with an Enterprise Data Warehouse (EDW) realizes what a challenge it is to make sure that the day you pull in from multiple systems can be trusted. It’s really hard to trust data that’s coming from a system that you don’t understand or use regularly. When you use the system regularly you have an idea of how it captures the data and the strengths and weaknesses of the data. When the data is in the EDW, you don’t often know those details.

With all of this said, the EDW is a walk in the park when it comes to trusting the data when you compare it to data coming from an outside source. One example is from an HIE, from the patient, or even from some patient device. The irony is that doctors have trusted outside data for quite a while. They receive chart notes faxed over from a specialty doctor all of the time. They trust that note and act on the data presented in the note. So, we shouldn’t act like the idea of trusting outside data is impossible. We just have to learn from the existing sources of trusted data and see how we can make that data flow easily and in a trusted way.

A great example of this is with HL7 lab interfaces. For some reason those interfaces have reached a level of trust where doctors receive lab results and trust that the data in those results is correct. I think we’ll get there with other forms of data transfer from outside entities. It will just take time to build up those networks of trust.

Being able to trust the data that a doctor receives or that’s stored in their data warehouse is one of the most important things we can do. Without the trust in the data, the data has little to no value and won’t provide the benefit to healthcare that we need it to produce. Healthcare big data is happening, but we need trusted big data.

Big Data Could Generate $450 Billion For Healthcare System

Posted on April 16, 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.

Here’s some information that should give all of us something to chew on  this week, courtesy of the always-interesting Jane Sarasohn-Kahn at the HealthPopuli blog.  In a recent piece, Sarasohn-Kahn pulls data from McKinsey & Company suggesting that if big data is properly harnessed, it can produce nearly — wait for it — $450 billion in value for the healthcare system.

As always, however, there’s a catch. This value explosion can’t happen, McKinsey says, unless big data is leveraged across five dimensions of care. These dimensions, which McKinsey calls “new value pathways,” offer opportunities for better efficiencies and economies of scale for the health system, HealthPopuli notes.

The five dimensions include:

Right living, in which big data is used to help patients take an  active role in staying healthy, by such mechanisms as daily health reminders and getting patients to seek care early when problems do arise.

Right care, in which big data tools, particularly coordination of data across providers and settings, make sure that patients get the right care at the right time.

*  Right provider, in which data analytics matches patients with the ideal provider for their situation, sometimes to lower-cost providers that can provide appropriate care.

*  Right value, which uses big data analysis to reward providers who produce the best outcomes.

*  Right innovation, a pathway in which big data is mined to promote continuous improvement and productivity in healthcare processes as well as R&D.

Sounds great, doesn’t it?  Well, maybe not so much given what has to change. To travel down these pathways, McKinsey notes, it will take re-aligning several key forces in the healthcare system, including privacy and data security, a shift to  value-based reimbursement, partnerships across industry segments currently found in deep silos (such as payors and providers), and data analysis capabilities current lacking in the health IT workforce. Sigh. And  I was feeling hopeful there for a bit.

As Sarasohn-Kahn notes, one way McKinsey sees to meet some of these goals more quickly would be to promote transparency as a cultural norm. But honestly, the silos we see today exist for important institutional and competitive reasons. If we want key partners in the big data effort to cooperate, it’ll probably take a governmental club to that head. Hey, ONC, are you ready to get rough with those who don’t want to play in the same data sandbox?

Healthcare Big Data vs Skinny Data

Posted on April 2, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 6000 articles with John having written over 3000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 13 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.

I have heard a number of people talk about healthcare big data was all the buzz in the healthcare IT world. There’s little doubt that there’s a lot of conversation happening around big data and analytics in healthcare. While I think there’s tremendous value to be found in healthcare big data, I’ve been more intrigued by what Encore Health Resources calls skinny data.

You can read more about the Encore Health Resources CoreANALYTICS announcement, but the approach is what I find really interesting. Instead of trying to create a huge enterprise data warehouse that can be all healthcare data for everything, they instead decided to focus on created a smaller solution that just focused on one major problem: meaningful use.

Encore Health Resources was open about the reason why they chose to go with a skinny data model as opposed to a full enterprise data warehouse model, time and budget constraints. They basically were asked to produce a result with a limited budget and so there wasn’t time or money to do anything but achieve the desired results. One of the architects of the system said, “If you can give me the extra data for free, then give it to me. If it costs [time or money] more to get that data, then don’t do it. Although, if you don’t give me these other data elements, then I’m going to have issues.”

It seems like a pretty simple concept to me that makes me wonder why I haven’t seen more of it in healthcare. Encore has taken these concepts and started to expand beyond meaningful use and into other areas like at-risk populations, clinical analytics for care coordination, and financial analytics.

I asked them if CoreANALYTICS would eventually grow into what essentially becomes an enterprise data warehouse. They suggested that it wouldn’t likely ever get that large, but I can see a path to that type of result.

What I do love about skinny data is that it’s user the information a hospital has available and creating actual results. It’s one thing to have the data, but it’s what you do with that data that really matters.

Healthcare Big Data Trends Leading To Analytics Spending

Posted on March 26, 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.

Ready to exploit big data? So are your competitors, and they’re preparing to spend big bucks in areas where they’ve historically been weak, such as predictive analytics and data discovery, reports  HealthcareITNews.

Technology vendor Lavastorm Analytics recently surveyed more than 600 technology professionals in healtlhcare and other industries about their IT investment plans for this ear.

Right now, researchers found, three-quarters of respondents still routinely use Excel for self-service analytics processes, and 35 percent use the R programming language.  Of the remaining 24 self-service analytics tools listed by the survey, 17 of them were used by less than 10 percent of the audience. In other words, once you get past R and Excel for analytics, there’s little agreement as to what works best.

But the coming months should bring some big changes in this landscape, Lavastorm’s research suggests. As the desire to exploit big data grows, providers are planning investments that will allow them to exploit it. Nearly 60 percent of respondents plan to increase their investments in areas where their capacity is limited.

Those areas include gleaning insights from data (25 percent), accessing data (22 percent) and having the ability to integrate and manipulate data (19 percent), HealthcareITNews says.

To meet those goals, providers intend to invest in predictive analytics (51 percent), big data (35 percent), dashboards (32 percent), reporting (31 percent) and data exploration and discovery (30 percent). At the same time, 27 percent said that they’d invest in advanced visualization tools and 24 percent self-service analytics tools for business users.

All this being said, my hunch that providers probably aren’t particularly sure where they’re headed with this technology yet.  I’d like to have seen Lavastorm ask which clinical or business goals, specifically, they hoped to meet by making these investments, wouldn’t you?

DoD, VA Plan To Streamline EMR Integration Effort

Posted on February 12, 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.

The Department of Defense and VA have decided to change the way they integrate their two EMRs, in an effort they say will lower the cost and speed the pace of interoperating.  The new approach is expected to offer at least partial functionality by 2014, rather than forcing the two agencies to wait until 2017, reports FederalNewsRadio.com.

Rather than sticking to their current course, which involves a massive effort to integrate their respective EMRs into a single system, health IT leaders will attempt to make more short term  progress.

To date, the DoD and VA have been working on common requirements and data standards and developing a shared enterprise service bus, all in the service of creating a single system. Agency leaders had estimated that the existing project would cost $4 billion.

The new plan, while keeping the larger goal of integrating by 2017, will include efforts to use existing solutions to get to interoperability quickly. Leaders expect their new direction to be considerably cheaper.

By the end of this year, the two departments will begin sharing a common UI, with the rollout beginning in seven DoD and VA wounded warrior polytrauma centers. Then, by  2014, the VA and DoD expect to be exchanging seven types of critical data, including lab results, clinical notes and allergies. The VA and DoD will accomplish this by standardizing the day their systems currently use, the VA’s chief information officer told FederalNewsRadio.com.

Another key component of the two agencies’ efforts is establishing a common system for identity management.  The identity management system is drawing on the massive Defense Manpower Data Center storehouse of personnel informaton operated by the DoD.