+1,1,1
Search

Blog


The Truven Health Blog


The latest healthcare topics from a trusted, proven, and unbiased source.


Using Data to Improve Healthcare


By Michael L. Taylor/Thursday, July 3, 2014
Mike Taylor imageAs other have pointed out repeatedly, our healthcare system is badly broken. In fact, we don’t have a healthcare system in this country – it’s a series of independent businesses, often competing with each other in the goal of making more profit. The three constituencies in the healthcare business are the customers (patients), the providers (doctors and hospitals), and the payers (health plans, employers and the government). These three groups all have perfectly misaligned incentives. Patients want care at minimal cost, providers make more money by providing more care (whether it is needed or not), and payers want to minimize payments. The payment mechanism drives more care at higher cost, and the result is the U.S. pays 18% of its GDP for healthcare – more than twice as much as any other country on the planet.

How does smarter use of data help this picture? In my opinion, more intelligent use of data is an important part of the answer. Data is a powerful tool to help physicians make better decisions. In the hospital setting, physicians should have access to ALL of a patient’s medical record, not just information gathered during a single hospital stay. In most Emergency Departments, doctors often don’t have unfettered access to outpatient medical records that may provide important clues to making correct diagnoses. Tests are needlessly repeated, incorrect medications are given and diagnostic errors are made all too often.  Electronic medical records (EMRs) should be helping this problem, but unfortunately most EMRs are simply digitized versions of the old paper record. We need EMRs to be longitudinal electronic health records, aggregating all of a person’s health information into a single record to be used by all providers of care. A unified health record then needs analytic tools to be able to use the comprehensive record to improve care, provide guidelines for evidence-based medical care, prevent incorrect medication use, stop dosing errors, and have prompts in the analytic tool to stop repeat tests and x-rays- in sum, improve the care.

A unified, single, health record for a patient would be a great tool to help improve care, but in the U.S., we have more fundamental problems than a lack of accessible data. In today’s residency training programs, physicians should be taught how to use the data and EMRs to make better decisions. An evaluation of a patient should always start with the physician sitting with the patient, taking a probing history by knowing what questions to ask, and how to elicit symptoms. This information is supplemented by knowing how to properly examine a patient and understand how to put all the information together to formulate a diagnosis. We cannot rely on an EMR or CT scans to do this job – it must start with a thorough history and a proper physical. One of the most impactful lessons I was taught in residency was that if I finished taking a patient’s medical history and yet still didn’t have a series of probable diagnoses to consider, I needed to take more history. Unfortunately, in today’s hospitals, finding a diagnosis is all too often done by ordering more testing, and in a fee-for-service payment environment, more testing means more revenue. More procedures mean more revenue. Hospitals and physicians should be paid for providing a higher level of quality, not by volume. 

I am a strong advocate of using medical data and providing better analytic tools to help physicians and patients, but tools are just tools. Physicians and other caregivers need these tools to improve care, but providers of care also need to listen to patients, think critically in making diagnostic assessments, care passionately about improving care, and use sound judgment at all times. They cannot be effective in a fee-for-service world. Providers do need to improve the care they provide, but the U.S. needs a sound healthcare strategy to solve our issues. Technology is part of that solution.

Michael L. Taylor, MD, FACP
Chief Medical Officer

Using Big Data in the Best Interest of the Patient


By Kathleen Foley/Wednesday, December 11, 2013
Kathleen Foley imageThe recent USA Today article, ‘Analysis of huge data sets will reshape health care’ highlighted many of the ways in which ‘big data’ are being used to improve healthcare in the United States. The linkage of data across hospitals, insurance claims, electronic medical record systems, and genomics databases are helping to identify more efficient treatments and high-cost patients, and determine best practices for treating patients with particular conditions.

Despite these benefits and many others, the creation of ‘big data’ assets is fraught with difficulties that may be limiting the true potential of existing data. In addition to privacy concerns and constraints which limit what types of data can be linked and by whom, there are issues around ownership and access to big data. Who should pay for the creation of these large data assets, and once created, who should have access? The answers are not straightforward and require the development of trust and a shared vision across many stakeholders.

Truven Health is actively involved in the development of data infrastructures to both create big data and facilitate analyses while guiding appropriate interpretation. One of the first areas of focus is the creation of cancer data assets. To facilitate research that will truly answer important questions for patients, providers, and payers, we are exploring all avenues for linking various data from claims data to EMRs to cancer registries. Only by combining data sources can we finally begin to address questions that will get the right treatment to the right patient at the right time. It isn’t just about generating big data, it’s also about knowing how to use it to generate knowledge that is a game changer.

Kathleen Foley
Senior Director, Strategic Consulting (Life Sciences)

Barriers to Adoption of Clinical Data Analytics for Population Health


By Larry Yuhasz/Saturday, August 3, 2013
Larry Yuhasz imageIn the recent article, Data Analytics Continues Upward Trend, the authors discuss the growth potential of healthcare analytics and the factors that will enable or inhibit this growth. Although the clinical data analytics trend is casting upward, momentum is being held back by a few key factors. First of all, the lack of electronic medical record (EMR) interoperability tends to silo clinical data by care setting and facility. Many analytic requirements to develop predictive risk scores, prevent readmissions, and measure risk require the ability to analyze clinical data across care settings and facilities. The demands of payment reform will ultimately prevail, yet Integrating the Healthcare Enterprise (IHE) vendor protection of proprietary formats remains strong.

Second, the majority of the U.S. health system is operating in a fee-for-service business model. Not until the majority of revenue shifts to at-risk models will the requirements for population health analytics really blossom. This is happening in enlightened pockets across the country and requires leadership education and changing HIT investment strategies to take root.

Third, many hospital systems are not operationally experienced in implementing enterprise-wide decision support. Unlike health plans and carriers who have been leveraging information to manage their business for decades, hospitals have tended to manage their operations along siloed service lines, with their physician network ultimately calling the shots on resource requirements. Payment reform fundamentally changes this dynamic and sees many more physicians being employed by physicians and connected with analytical platforms that can guide not only point of care decision making, but also retrospective review of clinical and cost performance.

Finally, all healthcare data emanates from patient encounters. Claims data is triggered via coding work flow to optimize billing, whereas clinical data is captured based upon proprietary EMR data entry requirements.  In today’s fee-for-service world, the clinical coding leveraged for claims purposes may or may not jive with the clinical data fields entered for EMR collection purposes. This creates downstream data aggregation and analytical methodology challenges. Over time, as payment reform stimulates a higher percentage of value-based care, the collection of administrative and clinical data must not only become more efficient at the encounter level, but also more analytically relevant for real time and retrospective analytical purposes.

Ultimately, the pace of analytical growth will be enabled through a combination of payment reform, operational change across all healthcare stakeholder groups, and technical innovation that overcomes barriers to data flow and utility.

Read more about our comprehensive suite of solutions for improving care and managing population health.

Larry Yuhasz
Director for Strategy and Business Development

RSS