The Truven Health Blog

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


How one health system closed care gaps and achieved improved ACO scores

By Truven Staff

As accountable care organizations (ACOs) for the Medicare Shared Savings Program (MSSP) know all too well, just one instance of a patient missing a follow-up visit to a clinic can change that person’s risk score. And those scores are ultimately important for demonstrating the MSSP goals of increasing quality of care while decreasing costs.


Cincinnati-based Mercy Health Select faced that challenge head on. Already one of the top ACOs in the US, Mercy Health Select wanted to do even more to close gaps in care and potentially improve the system’s ACO scores. Better scores would mean better care for patients and could help the system earn greater shared savings from the MSSP affiliation, too.

First, tackling a common issue: Different EHR systems

The Mercy Health organization started with a typical challenge for ACOs: Not all of the affiliated physicians in the network used the same electronic health record (EHR) system. That made it difficult to quickly consolidate information about at-risk patients across facilities.

That’s why Mercy Health Select opted to leverage technology that allowed the system to combine and mine the disparate sources of both clinical and claims data. The platform they chose also ran analytics on the data — to identify and prioritize the most at-risk, high-cost patients for follow-up communications.

Then, solving for speed

Of course, the timeframe for producing this kind of information is critical, too. If care coordinators wait too long to reach out to an at-risk patient who has not had a recommended cancer screening, for example, the ability to impact the individual’s health decreases.

So Mercy Health Select again used technology to update EHRs and patient risk scores within 24 hours. The new structure means clinicians can click on a link in a patient’s chart and see gaps in care right away — fueling fast intervention when necessary.

Solidifying the connection

Implementation of the new approach is paying off for Mercy’s ACO. With more gaps in care closed and more at-risk patients likely on the road to better health, the organization boosted its ACO score to 97.1 percent. That score is nearly 6 percent higher than the average1, and something all ACOs may aspire to achieve. After all, with that kind of improvement in score and patient care, ACOs are setting themselves up to earn greater shared savings.

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

1 Muhlestein D, McClellan M, Saunders R. (2016, September 9) Medicare Accountable Care Organization Results For 2015: The Journey to Better Quality and Lower Costs Continues [Blog Post], retrieved from target="_blank"


ACO Executives Struggle to Estimate Degree of Financial Risk

By Truven Staff
Michael L. Taylor imageA recent survey found many executives of Accountable Care Organizations (ACOs) are struggling to properly estimate the degree of financial risk their organization can bear. These organizations would benefit from an actuarial assessment of the ACO population for which they are intending to provide care, but many ACOs don’t have the many types of data needed to properly estimate risk. There are two areas of risk to assess:

  • The cost implications for those patients with chronic disease: ACOs need to not only understand the costs associated with chronic diseases such as heart disease, diabetes and cancer, but also the prevalence of these diseases in the population for whom the ACO is assuming risk
  • The cost implications for those without a chronic disease, but at risk for illness due to lifestyle risk factors: A large volume of scientific literature has consistently shown that, in a given population, as the number of risk factors increase, medical cost rises.
Doctors may have this information for the patients for whom they are caring, but they won’t have the data for an entire population. It’s difficult to predict costs without prevalence data.

Obtaining the data necessary to do this risk analysis is therefore necessary, but can be tricky for ACOs. Multi-year administrative claims data can demonstrate the burden of chronic disease, although typically this data isn’t held by any single provider. Regarding lifestyle risk, many large employers use “self-reported” data from health risk assessments for this purpose, but ACOs generally do not have access to these data. There are other factors to consider to predict costs in a population. Socioeconomic factors, level of education, and ethnicity all impact medical costs, but ACOs may struggle to obtain these data as well.

Successful ACOs will need access to these data streams and the ability to analyze the data to make financial predictions and create viable business models. They will also need to factor in the cost of obtaining these various types of data to include in the models. They will then need to partner with doctors and hospital systems to provide high-quality, efficient care in order to be financially viable. It can be done – we have customers that are assembling and integrating multiple data streams, performing and monitoring the analytics, and sharing the results across their enterprises – with careful planning, close coordination, and transparent governance.

Michael L. Taylor, MD, FACP
Chief Medical Officer

Managing Medicaid Managed Care and Encounter Data

By Truven Staff
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
Vice President, Market Planning & Strategy

Three Reasons Why Doctors are Choosing Employment Over Independence

By Truven Staff
Mike Taylor imageA recent commentary notes the shifting of doctors from self-employment to being employed by a heath system. Fully 60% of pediatricians and family medicine physicians are now employed, with 50% of surgeons employed. The number is expected to rise to nearly 75% over the next several years. What is driving that trend? There are at least three compelling answers: debt level, work-life balance, and the hospital’s need to develop market share and control referral patterns.

A recent report states the average medical school student graduates with a debt of nearly $280,000. In 1978, the average debt was $13,000. The student may also have debt obligations from college. Newly trained physicians with that staggering level of debt often don’t want to incur more debt by starting a private practice. The average annual salary of a family medicine provider is $224,000, but for newly trained physicians in private practice, initial revenues are much lower, and it may take several years to get to the average level. Add a home and car mortgage, as well as other personal expenses, and it becomes clear why it’s becoming impossible to absorb the start up costs of a medical practice, which often run as high as $100,000 for a solo practice. By working for a hospital or health system, physicians can avoid all the office costs and the professional liability insurance, while knowing they have a guaranteed salary.

I believe a strong second reason physicians are choosing employment rather than independent practice relates to the difference in lifestyle and work life balance. Most newly trained physicians were born after 1980, and the prospect of managing an outpatient practice and hospitalized patients 24/7 is just not appealing for many of these younger physicians. Working as an employee in a healthcare system that provides a guaranteed salary, utilizes hospitalists, and covers all practice-related expenses is too compelling to turn down. Young physicians also find having personal time off from work very important.

A third reason is the changing market itself. As the country moves away from a fee-for-service payment model to a value-based system, hospitals are moving into risk contracting or capitated payments. The best strategy for hospitals and health systems is to exert more control over the markets in which they serve. By employing physicians, hospitals can transfer office-based services into their own outpatient labs and radiology suites. Hospitals with employed physicians can more effectively direct patient admission choices. As Accountable Care Organizations (ACOs) mature, they will assume financial responsibility across the entire care continuum, from outpatient services to admissions, rehabilitation and long-term care. ACOs will drive the need for more efficient care with less wasteful spending. Hospitals can drive that efficiency with smart IT investments, treatment guidelines and care coordination. This can be done without employing physicians, but it’s more efficient to employ physicians and have them be a part of the process. To fully support care, a newer trend is for hospitals to employ specialists in addition to primary care physicians.

One potential advantage of employing physicians is the opportunity to reduce the variation in medical care that is rampant in the U.S. today. Reducing variation should improve the quality of care and reduce costs by avoiding wasteful and unneeded treatments that may be costing the U.S. up to 30% of the total medical spend. Aligning physicians and hospitals to the triple aim – better care for individuals, better care for the population, and slowing medical inflation is best accomplished in an organized approach – and individually owned practices are less likely to deliver on that promise.

Michael L. Taylor, MD, FACP
Chief Medical Officer

Illustrating How ACOs Could Save $380 Million in First Year

By Truven Staff
Mike Taylor imageA recent article in USA Today, “New Care Organizations Save $380 Million in First Year,” stated that Affordable Care Organizations (ACOs) saved approximately $380M in their first year of operation, exceeding Centers for Medicare & Medicaid Services (CMS) expectations. ACOs were conceived as part of the Affordable Care Act passed in 2010, and there are currently 114 Medicare ACOs in existence. Interestingly, the ACOs mentioned in the article are reporting lower costs than Medicare as a whole. ACOs also outperformed traditional Medicare on quality measures that evaluate the quality of care received. This is encouraging news, and I hope the number is confirmed.

The promise of an ACO is to provide healthcare in a fundamentally different way from traditional fee-for-service (FFS) Medicare. I believe the most fundamental reason healthcare is so expensive in the U.S. is the FFS payment model, in which doctors and hospitals are paid based on the volume of services delivered. ACOs are completely disruptive to the FFS model. ACOs are centered on the patient, not the provider – meaning the ACO receives a certain payment per patient, and payments increase when the quality of care is demonstrably improved over certain benchmarks. There are a variety of payment models in ACOs, but a common characteristic is the payment is linked to the outcome, not the volume of services delivered. This payment method encourages use of medical treatments that have been proven to work, discourages unnecessary medical care, and incentivizes for higher quality care.

Consider the traditional way care has been delivered: an elderly patient falls at home, developing severe hip pain. An ambulance takes the patient to an emergency department (ED). The physician examines the patient, orders and x-ray. The radiologist reads the film showing a fracture, and communicates back to the ED physician. The patient’s primary care doctor (or a hospitalist) is notified, the patient is admitted. An orthopedist is consulted, repairs the fracture under anesthesia delivered by an anesthesiologist and sends the patient to an inpatient bed. Physical therapy is ordered, medications are given and after a few days, the patient is transferred to a skilled nursing facility (SNF) for more rehabilitation. After two weeks there, the patient is not able to return home, so the patient is admitted to a nursing home.

In this example, think about all the care transitions as the patient goes through the system – there were at least nine transitions, and seven physicians were involved along the way. Every transition is an opportunity for an error to occur, or a miscommunication to happen – and they do happen. If any error leads to a complication, the medical costs increase. There is no coordination of care, and the payment has no bearing on the quality of care delivered.

In the ACO model, the ACO physician provider organization receives a certain dollar amount to care for this patient. Now, the physician thinks differently about the case, in a much more patient-centered approach. The physician brings together a clinical team to care for the population, and the team develops a home assessment process for all the high-risk elderly patients for whom they are giving care. The electronic health record data are leveraged to study the population. There is now an incentive to analyze patient data to predict who has a high risk of falling.  A case worker is given the patient name, does a home safety assessment, removing all loose floor rugs and looking for other safety hazards. The case worker finds the patient has poor balance, so he orders home physical therapy under the direction of the physician, who has evidence-based guidelines informing what type of therapy has been shown to reduce falls in the elderly. The patient gets stronger, never falls and continues to live at home. All the costs and pain derived from the fall never develop. Medicare paid the physician a pre-determined amount – much less than the cost of the hip fracture.

Which outcome do you want for you and your family? The point of the example is that ACOs have the potential (and financial incentive) to provide this high level of service; in a FFS world, the physician is not paid until an event occurs. Physicians desire to give the highest level of care to their patients, but our FFS system assures their failure. In a FFS model, physicians may provide excellent care to the patients they see, but they have no infrastructure or incentive to care for their population. There is no money set aside to encourage this type of preventive approach to a population. In an ACO environment, physicians and hospitals are paid based on how well they care for the population. Multiply this case for all the Medicare patients, and it’s easy to see how $380M might be saved.

Michael L. Taylor, MD, FACP
Chief Medical Officer