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The Truven Health Blog


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


Faced with a health system or hospital budget shortfall?

Peer benchmarking could lead to the answer.


By Truven Staff/Wednesday, September 13, 2017

Tell us if this health system’s challenge sounds familiar: CHRISTUS Trinity Mother Frances Health System, located in Northeast Texas, was facing a staggering potential setback when a number of payer contracts changed. The difference amounted to a $25 million shortfall in their budget’s revenue.

The system’s first reaction might have been to issue an across-the-board expense reduction mandate to make up the budget difference. We all know that can happen a lot in the industry, but it doesn’t always produce the results healthcare organizations need, and quality of care can be impacted.

Instead, this system chose a data-driven, strategic savings approach as the path forward, with an eye on long-term financial independence from these types of shortfalls.

A look at the targeted expenses

Using a comprehensive comparative database, the system was able to benchmark costs, productivity and resource utilization against best-in-class facilities of similar size and demographics.

Leaders identified cost improvement opportunities in areas such as supply, labor costs, length of stay and purchased services — areas where the system was not at the same level as high-performing peers in terms of expenditures.

The benchmarking information from the database was also used as a call to action for staff to find methods of improving processes and cost management. CHRISTUS Trinity Mother Frances leaders formed teams and assigned financial targets. Teams then used the database to answer the question, “If another health system is able to keep supply costs at this level, what can we do to bring our costs to that level with no bearing on our patient care or satisfaction?” The health system also created a dedicated project management office to help guide the process. The results of these efforts (in box below) speak for themselves.

If you’d like more information on how the health system achieved this result, please reach out to usYou can also read the full case study here.

 

 


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

Good Intentions Gone Awry: Solving for the Prescription Pain Medication Epidemic


By Tami Mark/Monday, July 29, 2013
Tami Mark imageHeroin in New England, More Abundant and Deadly” headlined an article in the July 18 edition of The New York Times that described the alarming comeback that heroin is making across the quaint towns and larger cities in New England.  Behind the growth in heroin use is a sad story of good intentions gone awry. A push to better treat patients’ pain and the introduction of oxycodone, a powerful and highly addictive pain medication, resulted in today’s massive prescription pain medication epidemic. The CDC recently reported that more people are dying from overdoses from pain medication than car accidents.

Efforts to clamp down on pain medication misuse have created the unfortunate consequence of, in effect, encouraging people with opioid addictions to substitute heroin for prescription pain medication. How can the healthcare system avoid this continuing cascade of unintended consequences? A key step is to ensure that individuals have access to a robust addiction treatment system. This effort can be enhanced with coordinated use of data and analytics.
 

Medicaid programs, for example, have established prescription drug monitoring to identify individuals who are abusing prescription drugs. However, such efforts need to be coupled with access to a robust substance abuse treatment system that includes access to the most effective medications for the treatment of opioid addiction – Suboxone® (buprenorphine/naloxone) and methadone, as well as coordinated substance abuse outpatient, inpatient, and rehabilitative services. A number of state Medicaid programs do not provide coverage of methadone treatment and many have time limits on the use of Suboxone. Analysis of de-identified Medicaid prescription and medical claims data, substance abuse treatment data, and prescription drug monitoring data can help states determine whether their systems are not only reducing misuse and diversion of prescription drugs, but are also providing access to high-quality addiction treatment that will keep their populations from substituting heroin use for pain medications that they can no longer obtain.

The total U.S. societal costs of prescription opioid abuse was recently estimated at $55.7 billion in 2009 - more than double the $24 billion that was spent on all of substance abuse treatment in 2009* as reported by Truven Health Analytics in Health Affairs. Thus, the numbers suggest greater coordination will have an economic, as well as a public health payoff.

Tami L. Mark, PhD
Vice President, Behavioral Health and Quality Research

Big Data Meets Personalized Medicine


By Ray Fabius/Thursday, January 17, 2013
Ray Fabius imageYour great-grandchildren will laugh when someone tells them that, not so long ago, all patients with the same diagnosis received the same treatment.  They will say that would be similar to all people getting the same shoe regardless of the size of their feet. 

The era of personalized medicine is emerging. Patients are beginning to receive different diagnostic tests and treatments based on their genetic makeup and metabolism.  Expanding this to all patients will require the manipulation and study of big volumes of data, including genomic and proteomic mapping as well as the integration of near real time electronic medical information. 

I celebrate that the National Institutes of Health are putting a fresh emphasis on health informatics.  Biomedical computing will foster collaboration across medical disciplines, and there is little doubt that such efforts will bring forth unique insights and generate novel analytical tools.  Truven Health Treatment Pathways is a first generation product of this movement.  With it, we have the capability to conduct comparative effectiveness research in a real world setting using large populations in a matter of weeks instead of years. 

As a treating physician, I have been struck by the nearly complete absence of information comparing treatment alternatives - most are approved against doing nothing rather than each other.  By comparing treatment regimens and outcomes, not only will doctors and patients be better informed but health plans will be able to markedly advance the field of evidence based benefit design.  For all of these reasons both public and private investment into medical big data should be endorsed and promoted. 

Ray Fabius MD
Chief Medical Officer


Announcing Truven Health Analytics


By Truven Staff/Wednesday, June 6, 2012
Truven Health Logo 2012We’re pleased to announce that the $1.25 billion sale of the Thomson Reuters Healthcare business to an affiliate of Veritas Capital was completed today.  The company’s many well-known brands, established in more than 30 years of leadership in the healthcare industry, include Advantage Suite®, Action OI®, MarketScan®, 100 Top Hospitals®, CareDiscoveryTM and Micromedex®.
The newly independent company will be known as Truven Health Analytics, a name based on the words ‘truth’ and ‘proven’ that speaks to the strength of its offerings, expertise, and people.
Truven Health Analytics provides data, analytics and performance benchmarking solutions and services to hospitals, health systems, employers, health plans, government agencies and pharmaceutical companies.  With leading assets and solutions coupled with expert services and analysis, Truven Health Analytics provides its customers with solutions to identify savings, improve outcomes, detect fraud, and more efficiently manage their healthcare operations.
Truven Health Analytics employs approximately 2,200 people worldwide and has its principal offices in Ann Arbor, Chicago and Denver.
We look forward to continuing to help you stay in tune with the issues affecting healthcare, along with our perspectives based on analysis of the data behind the trends.

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