The Truven Health Blog

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

Genomic Data for Oncology Research Available in Literature

By Kathleen Foley/Friday, May 30, 2014
Kathleen Foley imageData. Most of us in research are data-hungry and data-greedy. When we can’t get our hands on a certain piece of data our eyes start roaming, looking for the nearest match, like a teenage boy ravaging the fridge for the tenth time in a day. We will grab anything that resembles data, although we typically crave the hardcore, quantifiable, number-crunching data we’re used to, especially in cancer research. It’s funny, though, how in our hunger-driven craze, we can be blind to obvious sources of data.

Today, oncology researchers are all scrambling for genomic data. It’s the single most common data question I get from researchers. But genomic data are not yet available in most secondary data sources, such as administrative claims data or HIPAA-compliant electronic medical records. How then can we begin to explore the role of genomic information in cancer research? As Talia Foster points out in her opinion brief, Oncology Literature Reviews Reach a Tipping Point in Genomic Assessment, the literature is a readily available source that is prime for exploration.

The literature is a versatile source of information on genomic markers in cancer. It can be analyzed both qualitatively, as well as quantitatively, and as Ms. Foster points out, it can address a variety of questions. Rather than wait for our typical sources of cancer data to fully incorporate genomic data, we can access the genomic literature today. By leveraging this powerful and rich source of data, we can not only begin to address many of the questions about the role of genomic assessment in diagnosis, prognosis and treatment response, the prevalence of various mutations and real world use of targeted agents, but we can also begin to plan new research studies that will help us in our search to get the right treatments, to the right patients, at the right time. Are you looking for genomic data? Perhaps the time is right for you to think about the literature for your next data venture.

Kathleen Foley
Senior Director, Strategic Consulting (Life Sciences)

Impact of FDA Safety Warning on Dispensed Zolpidem Dose for Women

By Debra Irwin/Friday, May 30, 2014
Debra Irwin imageThe television show 60 Minutes recently aired a segment about gender differences in rates of drug metabolism. The program discussed a recent FDA safety warning and a recommended drug label change for Zolpidem, one of the most popular insomnia medications on the market. The safety warning was based on new data that showed women metabolize Zolpidem more slowly than men. Hence, women would require a lower dose of Zolpidem in order to avoid next morning impairment. After viewing this episode, my colleague and I became interested in the impact that the FDA safety warning had on Zolpidem dispensing patterns.

We examined the dose dispensed to new Zolpidem users before and after the FDA safety warning was issued. Women who were new users of Zolpidem were significantly more likely to receive low-dose Zolpidem after the safety warning compared to women who were new users of Zolpidem in the time period before the safety warning. However, the overall proportion of women receiving low-dose Zolpidem after the safety warning remained quite low.

Our findings may have significant public health implications for women using Zolpidem. An alarmingly high proportion of women who were new Zolpidem users were dispensed high-dose Zolpidem, despite the FDA safety warning. These findings highlight the importance of the extensive communication efforts required to effectively disseminate information concerning drug label changes to healthcare providers and patients.

Read more in our new issues brief, When Gender Matters: Impact of an FDA Safety Warning on Prescribed Zolpidem Dose.

Debra Irwin
Research Leader

The Effect of the Charge Master on Price Transparency

By David Koepke/Thursday, May 29, 2014
According to a recent article in The Hill, as part of a new rule proposed by the Centers for Medicare and Medicaid Services (CMS), hospitals will be required to release a standard list of prices for their medical services. This rule is part of the Affordable Care Act, and can also be fulfilled if hospitals allow the public access to the data after an inquiry. As consumers and other entities who play a part in the delivery and payment of healthcare services try to better understand how much healthcare costs, price transparency is increasingly important.

To an extent, hospital prices are arbitrary because they don’t expect to be paid what they charge. Each hospital has a separate payment rate from each payer which tends to be discounted to half or less than the charged amount, or more with government payers, where reimbursement is independent of charges. The hospital receives a legislated amount for a particular service regardless of charge. For each private or commercial insurer (including self-insured employers or their third-party administrator), hospitals must independently negotiate rates, which sometimes include fixed-case rates as with Medicare or Medicaid. At other times, hospitals negotiate a discounted fee for services (e.g. charges discounted 50%), usually with differing discounts for broad types of care (e.g. inpatient, outpatient, emergency and sometimes separate rates for routine care and ancillary services).  However, hospitals with high charges relative to costs or to charges of other hospitals must often agree to a larger discount. So the range of actual payments for services and supplies tends to be much smaller than the charged amounts.

Price Transparency changes graph image

Source: Truven Health ActionOI®

Hospitals often have the leverage in these negotiations. Some hospitals have a unique position in a market, so the insurer has little choice but to include them in its network. On the other hand, most insurers only account for a small portion of a hospital’s revenues, even when the insurer has a large share of the private coverage. So a hospital can benefit from having relatively high charges when insurers with fewer covered lives cannot force them to accept a large discount rate. Thus the smaller insurers must often be price takers. This is an area in which greater transparency could reduce the variability of charges and payments.

The way hospitals set charges differs from hospital to hospital. Each hospital maintains a charge master, a list of nominal prices for services and supplies charged by each unit. Charge master files are difficult to compare across hospitals. The charge master is usually maintained by a committee which assigns charges for new items and periodically reviews charges for existing items. Usually the committee is supported by groups within each major patient care department in the organization that recommend charges. Often charges are set by attempting to mark up estimated costs by a particular factor (1.5x, 2x, etc.). The markup usually differs across hospital service lines, such that services like diagnostics (e.g. imaging, EKG, EEG) and routine supplies tend to have higher markups than routine patient care and clinic visits. Hospitals often have minimum charges (e.g. the legendary $5 aspirin), but also tend to mark up high-price items, such as implantable devices and certain drugs,  by less than lower cost items (e.g. a 50% markup on implantable devices vs. a 250% markup on routine supplies). Since discount rates have been increasing, hospitals have incentive to proactively raise their mark-up factor (“front-run the deductions”). Instead of marking up from costs, some hospitals attempt mark up from expected payments, since they know what proportion will be deducted.

It doesn’t have to be this way. In Maryland, the all-payer hospital payment system establishes, through negotiation, a fixed schedule of payments to all hospitals by all payers. Since each hospital will be paid the same amount for the same services and supplies, regardless of nominal charge, there is no incentive for hospitals to charge an amount appreciably different from what it expects to be paid. By applying these same transparency principles nationwide via the Affordable Care Act, the culture of undisclosed costs and mark ups could be a thing of the past.

David Koepke
Lead Scientist, Center for Healthcare Analytics

Managing Medicaid Managed Care and Encounter Data

By David Nelson/Monday, May 19, 2014
David Nelson imageMedicaid agencies have increasingly turned to managed care organizations (MCOs) to deal with the tremendous increase in enrollment driven by the Affordable Care Act (ACA). The Centers for Medicare and Medicaid Services (CMS) released an Encounter Data Toolkit in November of 2013 to assist states with the operational task of managing the data streams from their MCO contractors. 

While most states are collecting encounter data, many face challenges in assessing the quality of data, and some still lack the confidence in their data to use it for rate setting, quality improvement, or public reporting. Over the past 15 years, Truven Health has helped nearly 20 states with their managed care programs and encounter data quality and completeness. We have assisted agencies with encounter data and managed care at all points of the encounter data process, including plan selection and evaluation, data collection, edit revisions, data quality improvement, and using data for plan management.

Most states choose to collect and process managed care data using their Medicaid management information systems (MMIS), for reasons that include the following:
  • The state can leverage the electronic data collection and translation processes already used for fee-for-service (FFS) claims.
  • The MMIS transaction system allows the state to process managed care data on a record-by-record basis, performing such tasks as editing and shadow pricing using procedures/protocols that are familiar because they are also used for FFS data.  
  • All data are maintained in the same system of record. The managed care data are housed with the FFS service data, which allows the Medicaid agency to incorporate all of the data, as needed and appropriate, in federal and state reports.
However, processing managed care data through the MMIS can also have drawbacks. Other states have experienced such issues as:
  • Delays in implementing new processes for managed care data because of the competing demands from FFS claims processing and associated system change orders.
  • Over-rejection of managed care encounters when edits designed for FFS claims processing are inappropriately applied to managed care records, which have already been adjudicated by the health plan.
  • Delays in the ongoing processing of managed care encounter data because persistent data quality issues cause repeated edit failures. This problem can be exacerbated if processes for resubmitting rejected records aren’t well designed and/or well understood and followed by the plans.
  • Inaccurate use or interpretation of managed care data in reporting and analysis because the nuances of encounter data are not accounted for in standard reports or communicated to users performing ad hoc analysis.
To avoid the above problems, states can either make appropriate adjustments to their MMIS systems and processes to fully accommodate encounter data, or consider other system options. States that are planning to re-procure their MMIS systems in the near future have the additional consideration of how much to invest in the existing MMIS system. This is particularly true for states that are moving to statewide, capitated managed care.

Some states have recently asked Truven Health about collecting encounter data directly from their managed care organizations. States could use their data warehouse decision support system (DW/DSS) to collect and process encounter data as either an interim approach or as a longer term process independent of the MMIS. Factors in support of loading the data directly into the DW/DSS include:
  • The DW/DSS is designed to incorporate managed care data – the data model and analytic reporting applications already anticipate the inclusion of managed care data. The DW/DSS provides a single, integrated repository for FFS and managed care data, capable of supporting transformed Medicaid statistical information systems (T-MSIS) and other federal reporting, as well as state-specific reporting needs.
  • By outsourcing this specialized function to a vendor like Truven Health that is highly experienced with encounter data, a state might help speed the availability of the quality data needed for performance monitoring, rate-setting, and public accountability. 
  • Our experience with the validation of managed care data will also help speed improvements in data integrity and increase credibility of the information.
Specifically, Truven Health’s managed care encounter data services, using the DW/DSS would include:
  • Receiving, processing, and translating managed care encounter data
  • Editing encounter data and providing feedback reports to managed care plans for resubmission
  • Storing encounter data and making it accessible for analysis alone or with FFS data
  • Incorporating encounter data into select federal reports
  • Validating and improving encounter data accuracy and completeness
  • An annual in-depth study of the quality of encounter data and development of a Data Quality Improvement Plan with each managed care organization
As Medicaid agencies turn to MCOs to deal with the tremendous increase in enrollment driven by the ACA, they have a partner in their DW/DSS contractors to implement the best practices outlined in the Encounter Data Toolkit. For more information you can contact me at david.nelson@truvenhealth.com.

David Nelson
Vice President, Market Planning & Strategy

Population Health: Economics and Leadership 101

By Byron C. Scott/Monday, May 12, 2014
Byron Scott imageIn a recent article in Healthcare IT News, the author did an excellent job of summarizing several key components of a successful population health program, illustrated by a short case study about how finance leaders at Legacy Health in Portland, OR partnered with physicians to educate them on the financial impact of cost drivers. When discussing population health, I find it helpful to remember the Kindig and Stoddart definition of population health from 2003: “Health outcomes of a group of individuals, including the distribution of such outcomes within the group.” This really helps summarize any framework and takes into account the end result of health improvement – how to monitor variability and the associated cost.

In order to have streamlined reporting, you need data. This sounds easy, but is often complex when extracting information from various health information systems (HIS) within a hospital or physician group. Many health systems have different electronic health record systems and having the tools and software to provide interconnectivity is essential. The data extracted must also be reliable, not only for clinicians, but for any other end user in the system that has a role in managing population health. Within hospitals, having this data will be essential when trying to reduce cost and variability in one key aspect of population health –  supply chain cost. In the article, the author mentioned reducing the use of more expensive implants in the operating room, but this is the tip of the iceberg. The continued streamlining of pharmaceuticals and other medical devices will be paramount in reducing overall cost.

As a physician, I believe partnering with physicians is essential. Some may call it being aligned, but I think calling it partnering is more collegial. Reducing physician variability requires reliable data that physicians can trust. Physicians are scientists and are often competitive, and if you provide them with trusted data, they will make improvements. However, it doesn’t just happen unless you provide physician leaders to guide them, and this requires investing in order to get a return. In other words, hospitals, health systems, and physician groups must continue to invest in physician leadership education and training to provide financially-astute leaders in the era of the Affordable Care Act.

Byron C. Scott, MD, MBA, FACPE
Medical Director, National Clinical Medical Leader