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The Truven Health Blog


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


Doctors and Data: Working Toward the Triple Aim


By Michael L. Taylor/Thursday, July 10, 2014
Mike Taylor imageChange is rapidly occurring in most aspects of the delivery of healthcare in this country. One of the most promising developments is the understanding that healthcare should strive to achieve the “Triple Aim” – better care for individuals, improved overall health of our communities, and lowered costs. The Triple Aim goals are about delivering better value in healthcare, not just delivering more care. The implications for our healthcare providers are enormous and may represent a fundamental change in the way care is delivered and paid. And the data needs are far greater than before – this represents a major challenge.

Many experts are advocating for new data steams to help find people at risk for diseases, even using non-traditional types of data, such as credit card purchases or use of social media, to define risk levels. Privacy advocates are adamantly opposed, and these debates will continue. Many employers have used medical claims data to understand population risk, but even using these data is worrisome to privacy advocates. Recent federal government revelations about NSA data probes into personal lives have generated much criticism, and I think the outcome will be more controls over the use of data. I think the “new data streams” will be narrowly defined. But the good news is new healthcare delivery models are finding ways to effectively use data to improve patient care.

In the new models of delivery, as seen in the patient centered medical home concept (PCMH), a healthcare team, captained by the physician, now has the responsibility to care for a defined population, not just the patients who show up for an appointment. Physicians are financially incented to provide better care. This drives the need for data, and health records need to find “gaps in care,” such as overdue cancer screening exams and missing lab tests. A PCMH team member is empowered to reach out to patients to help them get the care that is needed. The team is responsible for (and incented to provide) the healthcare needed in all phases of a person’s life. This requires integrated data from all settings – all outpatient encounters, hospital data, and follow-up care, including rehabilitation and nursing home and hospice care. Integrating all these data together will have tremendous potential to improve care. As an HIE contractor, we have constructed platforms that are delivering this kind of integrated data, so we know it’s possible today, and we’re working with hospitals toward the same end. Data integration will be necessary in order to understand when high value care is being delivered by hospitals, physicians, and all healthcare providers.

But more than finding gaps in care; the new model incents better care. Take a simple example of diabetes: the medical evidence shows lower mortality and morbidity in those who achieve blood pressure, lipid, and glucose control compared to those who are not well-controlled. New payment methods will pay physicians at a higher rate when their patients achieve better control of their diabetes. In this scenario, payment is more complicated, and now lab data must be analyzed to determine payment.

Paying more for better value has promise, but also many challenges. Defining better care for diabetes can be done, but what metrics should be used in other conditions?  Physicians see literally hundreds of different conditions in the course of their work with patients; how should higher value be defined in other medical and surgical conditions? Is there value is ordering appropriate radiology exams and forgoing inappropriate tests? How can that be measured and compensated?

Medicare policy is driving much of the change in payment mechanisms, but large employers are also asking about value. Employers are tired of paying for medical treatments that don’t work or are unnecessary, and are looking for cooperative relationships with providers to incent better care. Hospitals are adjusting to focusing on providing better care, not more care. The transition is turbulent, but the result has the potential of achieving the Triple Aim. We will not achieve these results in a fee-for-service system. The changes we’ve seen in healthcare over the last decade are the start of real reform that is badly needed, and we need to continue driving change toward a higher value system. Innovative use of new data streams is vital to this effort.

Michael L. Taylor, MD, FACP
Chief Medical Officer

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

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