Chief Innovations Officer, Professor, and Vice President of Cancer Services

		John Theurer Cancer Center at Hackensack University Medical Center

President, Regional Cancer Care Associates, LLC

How can we slow down the growth of cancer costs and preserve—or better yet&mdash;enhance clinical outcomes? This question is vexing payers, providers and policy makers, and never forget, patients. In our current issue, it would appear that private industry, public efforts, and even, academia, are all aiming to solve the riddle of delivery of value-based care at scale to control cost and improve outcomes by 

. There appears to be two general approaches evolving in the market place to deliver big data to the bedside. Both hold promise to promote the Goldilocks formula: not too much care and certainly not too little care…just the right amount.

The first involves what some have called the “boil the ocean” approach. Efforts from IBM (Watson), ASCO (CancerLinQ), and Flatiron Health (OncoAnalytics) and others all plan to capture large quantities of data and distill it down to actionable information, some in real-time and some in a retrospective approach to better guide decision making, and as the theory goes, change behavior through information. Capturing and distilling vast quantities of information may show patterns of care that are less effective, or equally effective but more costly. Challenges exist with this approach, however, including but not limited to, inaccurate data in the electronic health record (estimated up to 40%), lack of specificity to individual patients with co-morbidities or specific genomic mutations, and lack of timely and focused financial information.

The second approach provides point-of-service clinical and financial information in real-time, after initial sorting of patients by clinical and molecular phenotyping has occured. Taking this approach will enable a transition from fee for service to at-risk bundle type reimbursement. It also leans more on reimbursement reform to change behavior at scale and ties clinical outcomes combined with cost to ensure value.

Cancer Outcomes, Tracking, and Analysis, or COTA, (for transparency, a company I am involved with), recently announced a strategic investment from Horizon BCBSNJ and Med-Metrix Inc. The significance of this is that a dominant payer in a large market, along with a revenue cycle financial analytics company, have teamed up with practicing and academic oncologists to build a cloud-based solution for transparent value-based care delivery. This is an unlikely trio to collaborate in a private enterprise to build something, but the effect of the partnership could be profound. Challenges to this approach remain, because the requisite infrastructure for payment reform and acceptance of a common language of sorting needs to occur.

What is most encouraging is that American ingenuity appears to be well at work to offer solutions to the marketplace to avoid the need to even discuss rationing of care. We have spent over half a century uncovering the mechanisms of cancer and designing personalized approaches that truly are improving outcomes. My greatest hope is that big data does deliver on the promise and care outcomes improve while costs modulate.

Articles

How can we slow down the growth of cancer costs and preserve-or better yet-enhance clinical outcomes? 

Big Promise From Big Data

Virtually everyone in the clinical laboratory business is now acquainted with Z-code identifiers. Each unique laboratory test should have a unique tracking code, even if more than one Z-code identifier is reported with a corresponding American Medical Association’s Current Procedural Terminology (CPT) billing code. The uniqueness of each test is determined primarily by the methodology of performing the test, although other factors, such as specimen type, may also be considered.

Z-code identifiers were created and are maintained by McKesson Corporation as the initial step in creating a single national catalog for all commercially available tests that are molecular in nature. This catalog, which is part of the McKesson Diagnostics Exchange, can be viewed by anyone who creates a free user profile at McKessonDEX.com.

Much like NDC codes for drugs, Z-code identifiers enable the consistent identification of that unique test across systems by labs, providers, payers, and policy makers. It allows healthcare stakeholders to make decisions on genetic tests based on their clinical and financial impact, which ultimately reduces disease burden and improves health outcomes.

Approximately 4,500 Z-code identifiers have now been assigned, with a steady stream of applications for new codes in the pipeline. It’s important to understand that, as a tracking code, the Z-code identifier is not validating or credentialing the test accuracy or value. It is simply a unique identifier for each unique test, as documented by the clinical laboratory requesting a code.

The significance of this tracking function can be highlighted by several examples. More than 20 different versions of KRAS testing have been documented with unique Z-code identifier assignments, based on subtle differences in test methodology. A process for confirming the equivalence of each of these test methodologies has not been established. In contrast, if a different clinical laboratory performs the same test in multiple geographical locations, following the same stringent protocol, only a single Z-code identifier is assigned.

The process for initial registration of a test can yield a Z-code identifier assignment within weeks of completing the application. However, this does not mean that a test is ready for “prime time” and immediately available for use. The clinical laboratory applying for a Z-code identifier retains some control over the submitted data and determines whether this data will be made available through the Diagnostics Exchange to other entities (eg, health plans and the AMA/CPT workgroup) for further coding, clinical coverage, and pricing considerations.

How many unique tests will we need to catalog? No one really knows. We do know that the National Institutes of Health has registered more than 16,000 assays, including experimental and investigational purposes, in its Genetic Testing Registry. This registry is limited to human gene tests only, whereas Z-code identifiers may be assigned to any test that is molecular in nature.

Are Z-code identifiers competing with CPT or HCPCS codes? The simple answer is, “No.” Think of Z-code identifiers as tracking codes only for the unique identification of each test. The appropriate CPT or Healthcare Common Procedure Coding System (HCPCS) code is still required on a medical claim for reimbursement purposes. On an 837 electronic claim, the Z-code is reported in the free text claim line comment field and the CPT or HCPCS charge code is reported in the usual procedure code location.

The CPT code set is also evolving to meet the challenge of molecular diagnostic coding. The CPT Editorial Panel recently added “Tier 1” codes, where each CPT code specifies the gene and methodology for commonly ordered tests. They also created “Tier 2” codes for less commonly ordered tests, where nine levels (or families) of codes are defined, based on the testing methodology and similar work effort. Approximately 500 tests are now identified as Tier 1 or Tier 2 tests. But this is just a fraction of the 4,500 Z-code identifiers that have already been assigned.

A crucial component of the process for assigning a CPT code is to establish a clear, evidence- based justification for any code in the CPT set. This is a slower, more methodical process than assigning a Z-code identifier. For emerging technology, it can take some time to develop the objective evidence needed for a CPT code justification. For the special challenges of the new frontier in molecular diagnosis, using Z-code identifiers provides a new pathway for code development. By using incremental steps, a test inventor can now obtain a unique identifier during the clinical evidence justification process. This permits specific communication and publication of data and documentation regarding the new technology during the evidence development phase.

This is significant. Now test inventors can talk specifically about new technology, the evidence needed to establish clinical validity and clinical utility, and pricing, well in advance of documenting requirements for a full-fledged CPT or HCPCS code.

Lastly, the CPT process has acknowledged some of the features of emerging laboratory technology by creating an accelerated protocol for evaluating clinical evidence. This process, named CPT Code- Bridge, will:

		Evaluate test inventor data submitted in the initial application for a Z-code identifier.

		Consider additional research and utilization data as it becomes available.

		Map the Z-code identifier to the appropriate CPT code, with published updates three times a year, instead of annually, as occurs now. Prior to a CodeBridge mapping, a laboratory can still bill an unmapped code using the unlisted molecular diagnostic CPT code, 81479.

Using this approach, clinical laboratories may shorten the time it takes to get a new Z-code identifier from years to months (potentially). The value to payers can be a significant jump-start in evaluating and embracing new technology, and a reduction in administrative costs and hassles. The value to physicians is rapid access to credible, objective information about a test and what it does, when documentation and clinical indications for the new test is published along with the listing.

And most importantly, the value to patients is that they can receive the most appropriate and evidence-based diagnostic tests.

Virtually everyone in the clinical laboratory business is now acquainted with Z-code identifiers. Each unique laboratory test should have a unique tracking code, even if more than one Z-code identifier is reported with a corresponding American Medical Association's Current Procedural Terminology (CPT) billing code. 

Z-Code Identifiers Give Providers Objective Information About Molecular Tests

It seems like big data is everywhere these days. It’s being touted as a solution for physicians and practices who would like to participate in Accountable Care Organizations (ACOs) and accountable care-like contracts with payers. But what is it and how can it help practicing oncologists and hematologists?

Big data is a term used to describe both structured and unstructured data that can be obtained from multiple sources: patient records, insurer databases, physician offices, hospitals, Medicare/Medicaid records, and even personal sensors and smartphones. The data that are collected can be used to help physicians make more intelligent decisions about quality, treatment protocols, reimbursement, and even improve their own practice’s efficiencies. With the advances in information technology and data computing, population-based research can take advantage of these linked databases that can lead to discoveries and insights.

Big data promises “to deliver better research at the population level for comparative effectiveness and outcomes research—and to better understand issues concerning disparities in care, access, and burden of disease,” said Anne-Marie Meyer, PhD, an assistant professor in the department of epidemiology at the Gillings School of Global Public Health at the University of North Carolina. Meyer is the faculty director of the North Carolina’s Integrated Cancer Information and Surveillance System (ICISS).

ICISS assembles, links, and harmonizes big data to facilitate high impact, cancer-focused research that spans all facets of the cancer continuum by relating data sets, systems, and methods. One advantage big data may have over other forms of data collections—for example, clinical trials&mdash;is access. Meyer points out that patients who are enrolled in a clinical trial have access to care. “These are patients who are already interfacing with the health care system in a very high-quality way,” said Meyer.

With big data, however, researchers can “look at populations who are not represented in clinical trials and who may not be represented in cohort studies or other types of clinical or epidemiologic design studies,” she emphasized.

Peter Yu, MD, FACP, FASCO, a practicing hematologist/ oncologist at the Palo Alto Medical Foundation in California and president of the American Society of Clinical Oncology (ASCO) concurs.

“We know that only 3% of cancer patients go on clinical trials and hence that data is nonrepresentative of the entire cancer population,” he said. “For example, clinical trials tend to draw a younger patient population with fewer comorbid medical problems. By studying how closely the findings of clinical trials are replicated in real world patients, we will be better able to determine the true value of treatments and understand what is the best way to adapt those treatments, potentially leading to better overall results,” said Yu.

In today’s healthcare reform environment, practicing oncologists and hematologists are being asked to document that they are delivering quality care to their patients.

“In order to provide and demonstrate value-based care, oncologists need to understand and have access to data that are not currently available, said Bobby Green, MD, vice president of oncology for Flatiron Health, a health care technology company based in New York City.

The problem with these data is that it exists in different forms, is often unstructured, and is stored in different places in the treatment continuum. Some reside in a practice’s electronic medical record or billing system, some in a hospital system, and some with the payers.

“All this information is stored in silos,” said Green. “It’s in all these different areas and sometimes a lot of it sits in the unstructured notes of the physician, making it difficult to collect and analyze.” Green said that the silos have no inherent reason to share, and that it’s very important when sharing data to strictly adhere to patient privacy laws, but that this creates barriers. “That’s the landscape that we have to navigate. So it’s much easier to share what you bought on Amazon, rather than any part of a patient’s medical records—and appropriately so,” he added. “But we have to find a way to aggregate the data, and at the same time, respect patient privacy.”

It’s an overwhelming challenge to collect and analyze big data. But finding a way to use it can be a powerful tool on many levels: clinical, operational, and financial.

“For clinicians, if they are going to be making clinical decisions, they will want to know the source of the data, if it’s complete, if it’s trustworthy, and if it’s accurate,” said Sean Hogan, vice president of health care at IBM.

For the benefits of big data to be recognized, information needs to flow freely, so that the patient sees his data, and his physician can see that information. “But we want to make sure that the data are secure and privacy is not violated,” said Hogan. “We are just on the edge of allowing systems to talk or connect to one another,” adds Hogan.

Big data clearly has the potential to benefit patient care, but it can also benefit the individual practice by improving practice efficiencies from an operational standpoint said Green. “There is a lot of consolidation of small practices into larger hospital systems” said Green. “We want to enable practices to use data to provide business intelligence and insight into how they are functioning from a financial and operational standpoint. We view big data and analytics as a tool that helps practices thrive and survive.”

The clinical information collected can also be used to improve best practices, as well as practice operations, said Hogan. An infusion center might have streams of data coming in through patient monitors. The data stream in without being populated in a database. In effect the provider can review the data “on the fly, as it comes in,” Hogan said. A physician could be alerted to any complications immediately, and a therapeutic plan of action can be quickly formulated and put into effect.

“The data could be used from an operational standpoint also,” said Hogan. “The data could provide insight into how to adequately staff the center,” he said. “So this is an operational question that uses big data to come up with an answer.”

Health systems, insurers, and private practices are being asked to manage populations at risk. “So the question is ‘Where is the best place to deploy your limited resources?’” Hogan asked. In this instance, big data can shed some light, provide guidance, and business intelligence.

A mix of organizations and businesses are proposing platforms that can aggregate this data, provide insights to help clinicians, and uncover patterns to improve care.

A brief overview of 4 examples from the American Society of Clinical Oncology’s CancerLinQ initiative, Cancer Outcomes Tracking and Analysis (COTA), Flatiron Health’s OncoAnalytics, and IBM’s Watson follows.

There are three issues that characterize big data— volume, variety, and velocity&mdash;said Yu, the ASCO president. Before the emergence of big data, the mechanisms used to collect information were static&mdash; think registries or individual patient records.

ASCO’s platform, called CancerLinQ, is designed to “accept data from any electronic health record regardless of which vendor was used to create it,” said Yu. He cautions that it is not a registry, in which specific pieces of data are reported to the registry, like a patient’s histology, or staging.

With CancerLinQ “the entire health record, both structured and unstructured data, is absorbed,” he said. CancerlinQ collects all the data from all the sources in real time. The data are not collected once a month or once a year and then compiled.

“CancerLinQ will evolve in multiple versions that ASCO plans on updating every 3 to 6 months, with an expected initial launch in 2015,” said Yu.

In the interest of full disclosure, Andrew Pecora, MD, is executive chairman and founder of Cancer Outcomes, Tracking and Analysis (COTA) and also editor-in-chief of Oncology Business Management. COTA is also a real-time, cloud-based platform that provides point-of-service clinical and financial information to the oncologist, after sorting patients by clinical and molecular phenotyping. Once sorted and categorized, COTA can analyze the data for a variety of relevant and actionable clinical and cost outcomes.

As a platform built by oncologists and hematologists, COTA will enable clinicians to group patient characteristics with much greater specificity so the appropriate care can be delivered to each patient and oncologists can enter into value-based reimbursement models.

Flatiron Health’s founders come from a technology, not a medical background, and approached the problem of big data from that standpoint. They noticed that most cancer centers, physicians, and researchers did not have access to the most basic of data and analytical tools that other industries take for granted, and they decided to do something.

“Our mission is to take the world’s oncology data, organize it, and make it useful for patients, doctors, life sciences, and researchers,” said Green. Flatiron is helping oncologists understand “their patient population, how patients in a given scenario are treated elsewhere, and what the outcomes are,” said Green. The goal is to leverage the data that sits in these disparate systems to make it readily available to the oncologist so that he can practice better and more value-based medicine.

“Historically, no one has approached using the data from this angle,” said Green. “Technology has focused on health from the physician documentation standpoint for billing purposes, not necessarily focusing on patient care and making the delivery of care better,” he continued.

At its core, IBM’s Watson approaches problems using contextual language and deals with probability and uncertainty, said Hogan. It approaches problems, not with a definitive answer, but rather an array of answers and provides a confidence level for each possible answer.

In many ways, it works much like a clinician who is searching for a diagnosis but only is presented with a partial list of symptoms. From those symptoms a clinician has to piece together the whole picture, Hogan said.

In addition to clinical trial data collected, literature searches, and EMRs, Watson also gathers institution-specific knowledge from cancer centers like Memorial Sloan Kettering or the University of Texas MD Anderson Cancer Center, said Hogan.

“Watson can pull all that information together in a point-of-care concept,” Hogan said.

Proponents of big data say it is here to stay, and 2015 will be a year of significant strides in the healthcare IT arena. But there’s still plenty of progress that needs to be made, so keep in mind that there are shortfalls associated with this tool.

For one, tools that are based on big data can be gamed, and the results of big data analysis may be less robust. Consider Google’s Flu Trends—once a poster child for big data. In 2009, Google reported that by analyzing flu-related search queries, it had been able to detect the spread of the flu as accurately as and more quickly than the Centers for Disease Control and Prevention. A few years later, though, Google Flu Trends began to falter. In the past 2 years, it has made more bad predictions than good ones. Also, the Google search engine constantly changes, so patterns in data collected at one time do not necessarily apply to data collected at another. Another worry is the risk of too many correlations.

Statisticians point out that if you examine 2 variables 100 times, there is a chance of identifying 5 bogus correlations between the variables that can appear statistically significant. This requires careful analysis because the magnitude of big data can amplify these types of errors.

Meyer also points out that data sets also have inherent strengths and limitations. “The sensitivity and specificity of every variable in every table could have a different intent initially when compared to how we are going to use it now,” said Meyer. It’s a problem of primary data collection versus secondary analysis or use she said. “Data could be collected for one purpose, but down the line, it could be analyzed for another purpose, other than the intent that it was initially collected. It’s important to incorporate that complexity,” she said.

As progress is made in this field, there are still questions remaining. Perhaps the biggest one is can big data deliver on all its promises? For now, the answer remains to be seen.

			Ward JS, Barker A. Undefined by data: a survey of big data definitions. Published September 20, 2013. http://arxiv.org/pdf/1309.5821v1.pdf

It seems like big data is everywhere these days. It's being touted as a solution for physicians and practices who would like to participate in Accountable Care Organizations (ACOs) and accountable care-like contracts with payers. 

The Promise of Big Data Gets Closer to Fulfillment

The Affordable Care Act (ACA) is bringing unprecedented changes to how health care is paid for in the US, and both primary care physicians and specialists need to understand how these changes will affect their revenues. Reductions in Medicare and Medicaid payments, constraints on payer contracts and negotiations, and a fundamental change that emphasizes a risk-based and shared-savings reimbursement model have many practices scrambling to catch up.

It is unclear which reimbursement model—or which combination of models&mdash;will ultimately dominate. Further complicating revenue cycle management is that many health organizations are transitioning into being part of an Accountable Care Organization (ACO), in which caregivers are rewarded for both quality and value, rather than for volume.

At its core, the ACA has expanded coverage to a formerly uninsured population through state and health information exchanges and Medicaid expansion. What does this mean for a private practice hematologist from a revenue cycle perspective?

“It means an increased focus on insurance verification and an emphasis on point of service collections,” said Dan Clark, director of revenue cycle for McGladrey, a provider of accounting, tax, and consulting services. “The pressure to determine insurance coverage and ensure accurate insurance information currently falls to the front-office staff when the patient calls or presents for the office visit,” Clark said.

Because denial of claims is a significant problem, using business intelligence software could be an option providers might consider. Clark said that he frequently works with physician practices to help them understand the denials process. McGladrey uses business intelligence software 

to augment system reporting and “pull data from the host system for detailed analysis in order to help physicians and practice managers understand where the denials are coming from.” He pointed to the front end of the patient workflow as a primary source of denials.

	The Affordable Care Act (ACA) requires that the Centers for Medicare & Medicaid Services (CMS) implement a value-based payment modifier that would apply to Medicare fee-for-service payments starting with select physicians on January 1, 2015, and applying to all physicians and groups by January 1, 2017. The value-based modifier is intended to pay physicians differentially based on the quality and cost of their care.

	According to the CMS web site, physicians in groups of 100 or more eligible professionals (EPs) who submit claims to Medicare under a single tax ID number will be subject to the value-based modifier, based on their performance in calendar year 2013. In 2013, these groups needed to self-nominate/register and choose 1 of 3 PQRS group reporting methods available in 2013: the web-interface group reporting option, a registry, or request that CMS calculate the group’s performance on quality measures from administrative claims, in order to avoid an automatic negative 1% value modifier adjustment to 2015 payment under the Medicare Physician Fee Schedule.

	Groups of 100 or more EPs who self-nominated/registered for, and then participated in, any of the above-mentioned methods of reporting on clinical performance but did not elect quality tiering will have a neutral value modifier in 2015, which results in no impact on 2015 payments. In 2015, the value-based modifier will apply to both participating and nonparticipating Medicare physicians in groups of 100 or more EPs.

“Denials are often due to inaccurate demographic and coverage information or lack of authorizations for services. We are seeing more and more requirements for authorizations of services put in place, especially around managed Medicaid,” said Clark. This makes the shift to improving front-end resources and front-end education all the more important.

Medical practices should use a check sheet or script guide to be sure all pertinent information is collected at the point when the revenue cycle starts—when the patient schedules an appointment.

At the minimum, knowing the type of insurance the patient carries will help the scheduler know what information to collect. Responsibilities of the front-office staff should include informing the patient if the provider is not in the patient’s insurance network, providing information about what the patient should bring to the appointment, explaining to the patient that payment for copayments is expected at the time of the visit, and noting the arrival time of the patient if paperwork needs to be completed before the appointment.

The office practice’s financial policy should be in writing, reviewed by legal counsel, and signed by the patient. It should provide guidance to the patient about collection of copayments, accepted forms of payment, financial arrangements for unpaid balances, charity care or financial assistance arrangements, methods of payment not covered by insurance, and a description when prepayment of services is required.

The front-office staffer should be someone who is “capable of speaking to your patients about their responsibilities on deductibles, copayments, or coinsurance,” said Clark. “In my experience, physician practices have been slow to adopt the approach of collecting from patients when they present, but this responsible approach will become increasingly important to improve revenue and reduce expenses related to collections as higher deductible plans take effect. I estimate that thirty to forty percent of revenues in physician practices will be collected directly from patient responsibility.”

In this age of health reform, the responsibilities of the patient have changed as well. “It really is up to practices and to the medical industry to educate patients about their responsibility,” said Clark. And with the ACA and qualified health plans, it’s possible that many new patients will be enrolled in ‘bronze’ plans, which carry lower premiums but high deductibles and copayments that the physician office will be expected to collect. According to Clark, he has not met an oncologist who wouldn’t see a patient for lack of payment, but he emphasized that there is increased responsibility on the patient side and the physician needs to be aware of it.

Under health reform, the physician payment model is moving towards value-based payments and away from fee-for-service payments. This transition requires a number of changes, said Clark, including adequate information technology (IT) and the use of integrated electronic health records (EHRs).

“We have to be certain that EHRs are capable of handling things like ICD-10,” Clark said  of the revision of the ICD-9-CM system, which physicians and other providers now use to code all diagnoses, symptoms, and procedures recorded in hospitals and physician practices. The ICD-10-CM revision has more than 68,000 diagnostic codes, compared to the 13,000 found in ICD-9-CM, according to CMS. Looking ahead, Clark said to keep in mind that “the value-based modifier will be here in 2016 and 2017 from the Centers for Medicare & Medicaid Services (CMS).” Actually, the modifier starts in 2015 for “providers in large groups of more than 100 physicians,” he said. (See Value-Based Modifier in the sidebar.)

Practices that are considering an EHR should make sure the system can identify and report on the physician reporting quality metrics that will be required in order to receive incentive payments and avoid penalties.

“You have to be able to report on these quality metrics to participate in these programs that the ACA is mandating,” said Clark. Some physicians have been less aggressive in investing in technology or adopting new technology. “If your system can’t pull that information out and you can’t report on it, your practice will be subject to future CMS payment penalties,” Clark warned.

But investing in any new technology must have a return on investment. How do practices make sure that what they purchase is not obsolete in 6 months?

“I would look to the Meaningful Use and Physician Quality Reporting System (PQRS) requirements,” said Clark, referring to a reporting program that uses a combination of incentive payments and payment adjustments to promote reporting of quality information by eligible professionals. The requirements are available on the CMS web site.

Clark said practice managers should be aware of the eventual roll out of a merit-based incentive payment system called MIPS. “It is going to be a combination of EHR, meaningful use dollars, the PQRS, physician quality reporting system dollars, and the value-based modifier dollars,” Clark explained.

To gain this actionable insight, practices need tools that can help them manage their networks and patient populations, regardless of the payment model. A traditional data warehouse or static health information exchange (HIE) can’t deliver this insight. What is required is an application that harmonizes data from multiple systems (EHRs, practice management, claims) and turns it into insight that can then become action directly in an organization’s existing workflows. By converting information into action, organizations can align providers to achieve clinical and financial integration.

As part of this overall strategy, revenue cycle management applications should provide features such as:

		Consolidated network revenue cycle and productivity data

		Analytical tools that display information clearly and accessibly

		Actionable insight into collections, referrals, denials, etc.

		The ability to easily slice and dice data and share performance results

		Key performance information data filtered by location, department, or role

		Benchmark tracking and performance comparison by practice, specialty, or geography

The ACA has contributed complexities to revenue cycle operations, but it also presents an opportunity for providers to improve, excel, and differentiate. Providers who can adapt their revenue cycle management processes to take advantage of the current post-reform, consumer-driven environment will be in a position to benefit. Physicians should discuss these issues with their revenue cycle management vendor to ensure that their system can run more sophisticated reports to comply with evolving reimbursement requirements.

The Affordable Care Act (ACA) is bringing unprecedented changes to how health care is paid for in the US, and both primary care physicians and specialists need to understand how these changes will affect their revenues. 

Revenue Cycle Management in a Post-ACA World

Just a few years ago, Clifford A. Hudis, MD, FACP, chief of the breast cancer medicine service at Memorial Sloan Kettering Cancer Center and a professor of medicine at Weill Cornell Medical College, both in New York City, gave a presentation at the 2009 American Society of Clinical Oncology (ASCO) meeting about how oncologists could stay up to date on the explosion of medical information and knowledge available. At the time, Hudis was a member of ASCO’s board of directors; he subsequently became ASCO president in 2013-14. In the webinar, he advocated establishing RSS feeds so that users could receive stories, abstracts, and research directly to one’s email inbox, and he urged attendees to “figure out an efficient way to get what you want. It’s easy to set up in a world where we are inundated with information.”

In 2014, the amount of medical and other information has only increased, and mobile devices such as smartphones and tablets make it even easier to access that data. “Today is not any different than before, but there are more channels of information, more sources,” said Hudis, now immediate past president of ASCO, in a recent phone interview. “Because of electronic publication, the medical information comes at us faster. The doctor has to be even more skilled to determine what is important and what is important in the context of clinical care.”

Understanding that context is crucial for helping cancer patients receive the best medical care available, while following what have become standards of that cancer care. Staying current involves paying attention to evolving guidelines, written using transparent rules, and knowing what the erudite cancer organizations are saying, said Hudis. Such standards “allow for an informed starting point. They are treatment guidelines but allow doctors to use their skills to know where to deviate” from the standards when necessary.

Everyone has the same 24 hours in a day to get things done. Once the day has been portioned off into time for sleep, personal care, family time and work, which can include patient care, administrative tasks, research, and more, how does staying current fit into the mix?

“We do not just rely on our desktop computers anymore,” said Rogerio Lilenbaum, the chief medical officer for Smilow Cancer Hospital at Yale New Haven and a practicing thoracic oncologist. “It’s incredibly easy to access this information from anywhere on a mobile. It’s more—I don’t want to say it’s passive, because it does take active management to filter what is important to you. But it’s not how it used to be. When was the last time a physician walked into a library, for God’s sake? It just doesn’t happen anymore.”

Historically, physicians depended on textbooks and journal articles to learn about emerging data, and attended annual meetings from ASCO, and other professional associations such as the American Society of Hematology and the American Society for Radiation Oncology, said Lilenbaum, who has been practicing medicine for about two decades. Continuing medical education courses and other events helped disseminate new information about the field. But since around 1998 or 2000, Lilenbaum said, the Internet has transformed everything.  “People still care about journal articles, but access them online instead of in print,” he said. “People still go to ASCO, but the meetings have a different value. They’re more about networking and getting to know other people and institutions, rather than about obtaining information. And textbooks, I think, have lost a lot of their applicability except as a source for a subject review.”

Instead, Lilenbaum and others rely on daily email roundups from organizations like ASCO, journal abstracts sent electronically, and access other updates from online resources such as Medscape. Searching PubMed, a database of more than 24 million biomedical citations from medical journals, books, and other resources, for clinical updates on specialized topics is another way to stay informed, said Amer Zeidan, MBBS, MHS, an assistant professor of medicine in the section of hematology in the department of internal medicine at Yale University in New Haven, Connecticut, who specializes in myelodysplastic syndromes. “I go to PubMed regularly and look up any recent papers in my area to make sure I stay updated,” he said. “Trying to keep up with recent review articles is a wonderful way to summarize the new knowledge in the last couple of years.”

Zeidan says he multitasks by reading his mobile phone or from print medical journals or printouts while exercising on an elliptical machine. “If I have some free time, instead of sitting at home, I try to do that at the gym, and this way, I kill two birds with one stone, as they say.” Last year, he wrote an article for OncLive.com (Oncology Business Management’s host website) about “How Do I Keep Up With the Literature?” while he was an oncology fellow at Johns Hopkins University. Since that piece published in January, 2013, he says he relies much more on his phone to read, particularly while traveling, than he did while on a laptop as a fellow.

Both Zeidan and Lilenbaum advocate blocking out a specific time each day or week to catch up on reading, perhaps 30-60 minutes a day or one to two hours each week. “Close the door, and go through journals and abstract information that is important to your clinical practice,” said Lilenbaum. “It may be different for people in training, who need to devote more time to acquiring clinical information, or for those in practice for a long time. I think it’s good for absorbing information,” he said. For general oncologists, rather than specialists, Zeidan suggested reading about different topics each day, such as spending one day on breast cancer, one day on lung cancer, and so on. “This way, they can get up to date” on a variety of cancer topics necessary for a general oncologist to know.

Expected to update in 2015 after launching as a prototype in 2013, ASCO’s CancerLinQ will be what Hudis believes will be “the way doctors will keep up in the future.” Built as a database of how millions of cancer patients have been treated in the past, CancerLinQ is an electronic system that will allow oncologists to see the collective information of how other cancer patients have been treated, and how that knowledge can be applied to a physician’s current mix of patients, using what ASCO describes as “real-time quality feedback to providers, personalized insights, and uncovering patterns that that can improve care.” 

“CancerLinQ will aggregate care and decisions and outcomes for those patients getting care,” said Hudis. “It seems like a foreign concept, but it will be a lot like the rest of our lives. When you type into a Google search box, you don’t even type in the search term—Google already knows what you are searching for and populates the search terms, because Google learned the likely search terms that people are searching for. Why isn’t medicine doing the same kind of thing? I think this application will help doctors keep up and will help them understand and provide us with a more nuanced way of practicing medicine.”

Such data won’t provide all answers right away, but it will be a start, providing alerts for potential drug interactions for example. Hudis believes that after using such a system, physicians will say, “I can’t believe we didn’t already do this.”

Medical professionals, as a whole, have other areas of intense focus, and haven’t been on the cutting edge of technology, said Hudis. “Doctors have been relatively closed about new technology, and while I love this stuff, we were often dragging doctors along into the modern era. Earlier ASCO sessions would help people get on to WiFi, or how to use their personal digital assistants, like Palm Pilots. Technology is expensive, time-consuming, there were always accuracy and legal issues. For good reason, medicine has been relatively slow to the tech world.”

But consider the alternative, he said. “If you are a patient today, if you have open heart surgery at one New York City institution, and you cross the street to get cancer care at another New York City institution, how do you transfer the information? Right now, the electronic health records systems don’t talk to each other, so you have to copy the information and walk it across the street. People are worried about security, but how secure is the binder of paper crossing the street?”

With technological advances, such data are simply packaged differently, and in many cases, the basics of medicine and patient care remain the same: “Physicians need to read, and need to be critical thinkers,” said Hudis. “The fundamentals will never change. An abstract on a smart phone is the same as an abstract in a print issue of a 1987 

. The tools we have now can be used to make all of us more efficient and help us be smarter, which helps us give better care to our patients."

In 2014, the amount of medical and other information has only increased, and mobile devices such as smartphones and tablets make it even easier to access that data. 

How Oncologists Stay Current in Today's Medical Landscape

In July, UnitedHealthcare (UHC) reported that an innovative program using bundled payment for cancer care resulted in an impressive 34% reduction in medical costs when compared with costs for a control group. Moreover, 

 that patient outcomes were the same in both groups. 

The study yielded important lessons to oncologists about delivering care under bundled payment. Leaders at 2 clinics in the study, Lee S. Schwartzberg, MD, a senior partner and medical director at the West Clinic in Memphis, Tennessee, and Barry Russo, CEO of the Center for Cancer and Blood Disorders in Fort Worth, Texas, said they learned that their success with bundled payment would not have been possible without also delivering care in a patient-centered medical home.

“We would have had trouble delivering care in this way if we were not organized as a patient-centered medical home,” said Schwartzberg. His practice has 33 physicians in 9 offices and was recently designated a Patient-Centered Specialty Practice by the National Committee for Quality Assurance.

Under the medical home model, the practice gets paid an additional fee to hire nurses or case managers to care for patients between visits to the oncologists. They ensure that patients get the care they need to prevent high-cost emergency department visits and hospital stays.

“In this program, the entire staff of the West Clinic participated and was able to steer patients away from needless emergency room (ER) visits and inpatient care,” Schwartzberg said. “One of the lessons we learned was that when you take out the costs for chemotherapy, the other highest costs are generated through ER visits and hospitalizations. That’s why we intensified our efforts to put more navigating power and resources into the medical home to keep patients out of the ER and out of the hospital.”

Another significant lesson the West Clinic physicians learned was the importance of standardizing care by identifying what each patient needed and then choosing and following the appropriate treatment pathway for each, Schwartzberg said.

Identifying patients’ needs also was critical to his group’s success in improving patient outcomes. UHC shared the extensive data it had on each patient’s history and course of treatment, helping the physicians to understand all patients’ treatment needs.

“UnitedHealthcare has records on all patients’ treatment. We don’t have the hospital records on these patients or records from the ER. It makes sense that the payer would share that data with us, but they don’t normally do that,” Schwartzberg said. “They had staff working full time on this project,” he added. “It would be difficult for any practice to collect and analyze the data that UHC had on its patients.”

The bundled payment program also helped the practice develop a close working relationship with UHC, he added. Such relationships are rare because usually practices and payers argue about coverage and payment for cancer care.

“In the past, there was a great degree of uncertainty and suspicion between physicians and health plans. But since we launched this bundled payment project, the entire attitude has shifted,” Schwartzberg said. “Now, it’s clear that insurers and providers have to work together in a way that is patient-centered.”

For Russo’s group, the infrastructure needed to support its medical home effort allowed the practice to deliver care to patients in the bundled payment successfully. The center has 19 physicians in 9 offices and is participating in the Come Home project for Medicare patients and a shared-savings program for Aetna patients.

“To make bundled payment work financially you have to do a medical home because you have to have the infrastructure, meaning the staff and the hours, to manage the costs. If you’re in a bundled payment or shared-savings arrangement, you’re getting a flat rate. That means you have do a medical home to make that work because you need a way to manage costs,” he said.

“The UnitedHealthcare program began in 2009, when we were just learning how to deliver value-based care. Since then, we learned that we need specific triage and case management functions to manage this population better, and adding those functions costs money,” Russo added.

Through the medical home projects, the center gets additional funds from the Come Home medical home program and an Aetna shared savings contract to hire 3 to 4 nurse-care managers and to stay open until 8 PM on weeknights and from 10 AM to 2 PM on weekends.

“By having nurse-care managers doing triage on the phone, we can get patients into the office if needed. We’re open longer so that we can manage those patients better here in our practice, which keeps them out of the ER and out of the hospital,” he said.

Every oncology practice has a triage system, but Russo’s practice uses triage to manage patient care more closely than most.

“We revised our metrics to base our triage success on how many patients we could keep out of the ER and how many patients we could get into the clinic so we could solve problems before they became bigger problems,” he said. “That’s a different metric than typical triage, which is a nurse working in the chemotherapy area making sure everyone is fine,” he said. “It’s a mindset change.”

Like the West Clinic, the center got extensive data and expert data analysis from UHC.

“Under this program, physicians aren’t making decisions on what drugs to use based on reimbursement because the reimbursement is capped. Instead, they are making decisions based on what is right for the patient. On top of that, we had a micro focus on our patients through case management and aggressive triage. Putting in all those steps successfully improves patient management and reduces costs,” Russo explained.

Most practices don’t add staff or micromanage patient care because doing so is costly, he said. “In the typical shared savings or medical home program, you get a case management fee so that you can recover the costs you’ve incurred to micromanage patients. If you don’t get reimbursed for the infrastructure you need, then you would have no way to pay for the additional staff or the longer hours,” Russo explained.

“Compared with the savings possible from micromanaging patient care, the costs are minimal. That’s why I believe the medical home idea of being responsible for managing all the needs of each cancer patient is where cancer care will be moving in the future,” he said.

It’s possible to produce savings from a bundled-payment or shared-savings program without a medical home, but the savings would not be sustained over time, he said.

“If you don’t put in new processes and procedures to optimize patient care, there will be no shared savings. Or, if there are savings, they will be short-lived. When you change your processes so that you can micromanage each patient’s case, then you can start to get long-term value out of shared savings or bundled payment,” he concluded.

		Unexpected Outcome Found in UHC Bundled Payment Project

	The bundled payment project that UnitedHealthcare launched in 2009 was effective at reducing the cost of cancer care while also delivering quality care. But one result from the initiative was surprising: while it aimed to keep chemotherapy costs under control, those costs rose.

	“You have to look carefully at the results of this pilot program,” commented Debra A. Patt, MD, MPH, a medical oncologist and hematologist at Texas Oncology in Austin. She also is medical director of Healthcare Informatics for McKesson Specialty Health and The US Oncology Network where she leads a team of physicians and researchers in health economic and outcomes research.

	“One goal of the program was to remove physician incentives for prescribing chemotherapy. That’s important because in many practices—not all&mdash;the physician compensation depends directly on chemotherapy revenue,” she said.

	Because the bundled payment project sought to remove incentives for increased utilization, but also not reward inappropriate decreased utilization, the UnitedHealthcare study is important for oncologists seeking new ways to pay for cancer care, she added.

	“Recognizing that chemotherapy is a real driver of costs in cancer care, it is an important step to remove the perverse incentives for chemotherapy prescribing,” Patt commented. “But what this study actually found was that while costs were reduced by having an episode of care model of payment, the practices didn’t actually decrease chemotherapy cost. Instead, costs were reduced in ER visits and hospitalizations.”

	Another important aspect of the project pilot was that it measured and reported on quality of care in addition to cost.     

	“It is important to not address the cost aspect alone, but [also] the value of the care being provided. A value assessment cannot be accomplished without also evaluating the quality of care provided,” Patt said.

	“As many people seek to control costs and answer the question of how do we provide value, which is really outcome over cost, how can we do so through cost cutting?” she asked. “In this study, whenever they sought to control the costs of care, they also had some measurements of quality of care, which is significant, especially for a study done by a payer.”

	Any innovative payment model for cancer care likely will focus on what the physicians addressed in the UnitedHealthcare project: chemotherapy costs, ER visits and hospitalizations, she said. In addition, Patt added, oncologists also should focus on costs at the end of life.

	“For care surrounding the end of life, we need to ensure that it is appropriate, thought out in advance, and respecting the values of the patients,” she said.

	In conclusion, she offered a suggestion that any oncologist would welcome. “For a physician in a practice with patients who contract with many different payers, it would be difficult to operate under different systems of payment reform for different payers. What might be easier is if there is a more universal strategy to control the levers influencing cancer costs,” she said.

In July, UnitedHealthcare (UHC) reported that an innovative program using bundled payment for cancer care resulted in an impressive 34% reduction in medical costs when compared with costs for a control group

October 2014 | Oncology Business News®

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