Posts Tagged ‘data’

Infographic: Harnessing the Power of Unstructured Healthcare Data

August 25th, 2017 by Melanie Matthews

Finding meaning in patient care data will require looking beyond the 20-30% that is “structured” and stored within the EHR/EMR. A complete patient record is 80% unstructured data. From imaging to lab results, photos to findings—unstructured data management, sharing, workflow and analysis will power decisions and inform outcomes. Harnessing this data and turning it into actionable intelligence is a goal of a handful of leading HIT teams, according to a new infographic by Clarity Quest.

The infographic highlights the rapid growth of unstructured content and its impact on downstream analysis and provides a listing of enterprise imaging, workflow and analysis leaders.

2016 Healthcare Benchmarks: Data Analytics and IntegrationThe 2016 Healthcare Benchmarks: Data Analytics and Integration assembles hundreds of metrics on data analytics and integration from hospitals, health plans, physician practices and other responding organizations, charting the impact of data analytics on population health management, health outcomes, utilization and cost.

2016 Healthcare Benchmarks: Data Analytics and Integration examines the goals, data types, collection processes, program elements, challenges and successes shared by healthcare organizations responding to the January 2016 Data Analytics survey by the Healthcare Intelligence Network. Click here for more information.

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Infographic: The Physician View on Patient-Generated Data

April 17th, 2017 by Melanie Matthews

The usefulness of patients sharing their data from FitBits, Apple Watches and mobile apps with physicians remains questionable, according to a new infographic of the results of a study by WebMd on the topic.

The infographic looks at how often patients share data; what happens when patients share data; and how many providers provide patients with the opportunity to send in their data via email or to a portal.

2016 Healthcare Benchmarks: Digital HealthDigital health, also referred to as ‘connected health,’ leverages technology to help identify, track and manage health problems and challenges faced by patients. Person-centric health management is slowly acknowledging the device-driven lives of patients and health plan members and incorporating these tools into care delivery and management efforts.

2016 Healthcare Benchmarks: Digital Health examines program goals, platforms, components, development strategies, target populations and health conditions, patient engagement metrics, results and challenges reported by more than 100 healthcare organizations responding to the February 2016 Digital Health survey by the Healthcare Intelligence Network.

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Rectifying System Disparities within ACO Improves Data Capture, Quality Reporting

October 30th, 2014 by Cheryl Miller

Addressing the disparity between data systems was one of the operational and information technology (IT) issues the John C. Lincoln (JCL) Accountable Care Organization (ACO) addressed at the end of its first year as a Medicare Shared Savings Program (MSSP) ACO, says Karen Furbush, business consultant with JCL ACO. Here she explains the steps taken to rectify the situation.

I was brought on board in July 2012 and was given the ‘playbook,’ or answers that John C. Lincoln provided to the Centers for Medicare and Medicaid Services (CMS) on how they would structure their ACO over the next three and a half years. It was my job to figure out from the IT perspective how to address all the new advancements with the Transition Coach program.

My job was to figure out this new EMR EPIC® system that was being installed, and how we were going to get data back out. It took us a while once we got our membership list from CMS to find addresses and do the mailing, which we decided to do. This is not required, but we wanted to get the information out to patients about what an ACO was; that we were now providing their basic primary care physician (PCP) services. And we wanted to communicate that as early as we possibly could.

Along with doing those initial mailings, we determined any additional data we needed from our system in order to respond to CMS reporting requirements for 33 quality measures. We took a two-day workshop in November 2012 and realized that not everyone was on the same EMR at the very beginning.

We have a lot of disparity between systems; not all data comes from one system to the next, due to business decisions. We had to go back and determine what we needed from each different system and how long this was going to take. Then we had to figure out how we would normalize or make sure that this data was specific for reporting back to CMS.

In this two-day workshop, we broke it down measure by measure. There are 15 different categories in which CMS places all of their reporting. We went through each — for example, for the emergency area, the hospital and in the physician practices — and asked ourselves what we were doing for each. Just because you’re on one EMR doesn’t mean the data capture model is the same. But I still needed to account for every time those things occurred; they are discretely reportable. That’s not always easy; even though you’re on one single platform, there are a lot of factors that play into why that’s very difficult to get to.

Source: Beyond the EMR: Mining Population Health Analytics to Elevate Accountable Care

http://hin.3dcartstores.com/Beyond-the-EMR-Mining-Population-Health-Analytics-to-Elevate-Accountable-Care_p_4900.html

Karen Furbush is a business consultant with John C Lincoln (JCL) Accountable Care Organization in Phoenix. She is responsible for coordinating and managing all things related to IT integration, data analysis and reporting for JCL’s CMS MSSP ACO and Employee ACO programs. She has over 20 years of technical program and IT management experience, and has held a wide variety of information technology roles in the healthcare industry.

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Adapting 3 NCQA Standards for the Patient-Centered Medical Home

January 24th, 2014 by Cheryl Miller

Coming from a group of innovators who had adopted EHRs early on and were not afraid of data, participants in the Hudson Valley medical home transformation project decided to concentrate on three out of nine NCQA standards: access and communication, inpatient self-management, and performance reporting, explains Paul Kaye, MD, medical director at Taconic IPA.

Let’s move on to the nine standards of NCQA. All of them are available at NCQA’s Web site. We found that we needed to concentrate primarily on the areas of access and communication, inpatient self-management and performance reporting. It’s not to say that the other pieces don’t warrant a challenge, but many of them reflected EHR use and the ability to report on that use rather than a radical transformation of practice.

Initial steps were to require all of our practices to take TransforMED’s medical home IQ self-examination. Then a practice work plan for each practice was created. There was a staff-wide kickoff with each practice. Scheduling that was a challenge for busy private practices, as well as for the community health centers. Regular contact occurred between the coaches with timetables and deliverables that were there for particular elements and standards that had to be met.

Our medical council met once a month. The council included the physician and non-physician leadership of each practice. We highlighted a different standard at each meeting, shared best practices and came to an agreement on the three conditions that one needs to identify for NCQA medical home recognition. There was agreement across the practices that diabetes was an important condition in our area and there was also agreement on adopting practice guidelines, which had already been worked on at the statewide level, so that was a non-controversial area to be able to tackle. We also had two full-day workshops called learning collaboratives, and continue to have these every six months. For these workshops, outside speakers of national prominence came to talk about the medical home and some of the changes that needed to be done.

With all those areas of success, we had no difficulty agreeing on a clinically important condition and on defining a few more to pick from. Agreement on practice guidelines again came easily because of work that had already occurred. Most of the practices found that the standards that required documentation of an EHR functionality, while challenging to document on a piece of paper, were already present and didn’t require much radical change in their practice. These are the low hanging fruit, and showing some of this early on started to build the spirit of cooperation among the providers.

Excerpted from Guide to Physician Performance-Based Reimbursement: Payoffs from Incentives, Data Sharing and Clinical Integration.

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