Meaningful Use Is Not the Finish Line

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1 Meaningful Use Is Not the Finish Line A White Paper From Health Language CALL ONLINE

2 Meaningful Use Is Not the Finish Line Improved information exchange, reimbursement and patient care analytics require diligent medical terminology management Today the predominant focus in healthcare is on creating more efficient, collaborative and patient-centered care. Encouraging this effort are initiatives ranging from the Meaningful Use of electronic health records (EHRs) to the Physician Quality Reporting System (PQRS), as well as the transition from ICD-9-CM to ICD-10-CM/PCS. All of these programs now are compelling healthcare organizations to reassess how data is collected, managed, distributed and analyzed. In short: while earning financial incentives for achieving Meaningful Use is a worthy short-term goal, the increasingly interconnected nature of healthcare is making medical terminology management a new and essential part of long-term operations. Historically, physicians have not had to become familiar with code sets or standardized vocabularies. As long as a physician could maintain and understand their own patients medical records and the patients claims were paid, medical terminology management was not a large part of a physician s concern. How times have changed. Medical terminology management involves standardizing and updating a wide variety of continually evolving administrative and medical code sets and terminologies. Effective medical terminology management enables organizations to experience more efficient communication among providers, and potentially more accurate reimbursement with faster claims adjudication and fewer denials. Most importantly, using standardized and interoperable vocabularies will help organizations improve the quantity and quality of patient care analytics, resulting in better outcomes and reduced costs. Two sides of the interoperability coin Thanks to Meaningful Use and other initiatives, data interoperability has become increasingly important to provider organizations. Unfortunately, however, the term itself is very often misunderstood. Interoperability can be broadly defined in two ways: Structural interoperability: This is when organizations using disparate information technology (IT) systems are able to freely exchange data across IT boundaries. Semantic interoperability: This is when the data exchanged between disparate organizations shares identifying properties that allow it to be fluently understood and analyzed by all parties. Both types of interoperability are crucial to efficient data exchange. Without structural interoperability, data sits in silos, unable to be accessed by different IT systems across the care continuum. Likewise, even when IT systems are integrated and easily accessible, incompatible apples-to-oranges data cannot accurately or efficiently be used to achieve operational, financial or clinical care goals. Through Meaningful Use Stage and the ICD-10 mandate, the Centers for Medicare & Medicaid Services (CMS) has moved beyond simple data exchange to driving providers to focus on semantic interoperability. The idea is to use standards to help normalize data in other words,

3 enable apples-to-apples discussions. For example, if one provider orders a diabetes test for a patient using HBA1C and another provider captures the same test using a different code such as Hemoglobin A1C, normalization of this laboratory data would allow the system to directly compare the results. Starting in 2014, providers that wish to comply with Meaningful Use Stage 2 must build on the use of standardized terminologies such as Logical Observation Identifiers Names and Codes (LOINC), RxNorm, Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) and ICD-10 established in Meaningful Use Stage 1. These vocabularies, some of which may be relatively unfamiliar to providers, will likely become the standard terminologies for data exchange required by CMS. Commercial payers also will likely adopt these code sets and terminologies for private accountable care organizations (ACOs) or other risk-based payment models. In fact, emerging compensation structures are another driver for medical terminology management. Unlike in traditional fee-for-service reimbursement models, ACOs and similar arrangements will require providers to electronically share much more clinical and financial data with each other and with payers. The use of standardized terminologies allows for more accurate data capture, which ultimately leads to more accurate exchange of claims and performance data. Without it, providers risk inaccuracies that could lead to reduced revenue. For example, when providers are not able to capture and explain the nuances of a patient treatment or diagnosis correctly, they may face greater administrative costs due to reworking claims or generating performance reports with fragmented data. These issues will emerge more often as clinical integration increases through acquisitions, consolidations and ACO agreements. Standardization and normalization: Steps to goal achievement Regardless of the overall clinical or financial goals of a healthcare organization, the standardization fostered by medical terminology management can help achieve them. For instance, consistent terminologies can be used to help ensure accurate payment for services performed by equipping providers with the data needed to successfully prove medical necessity, condition severity, and other factors considered in reimbursement. Likewise, when contract negotiations arrive, accurate standardized historical performance data can be used to support improved outcomes and cost-effective, evidence-supported care. This analysis can be leveraged to secure more competitive compensation for physicians and hospitals. The first step in terminology management is to ensure the use of accepted standardized terminologies. Those terminologies must be kept current and accurate. The second step is to map and normalize standardized data to derive useful intelligence. Fully normalized data will allow for a level of population care analysis that is still quite rare outside of highly integrated delivery networks. Due to the limited amount of semantic interoperability currently found within most organizations, providers cannot effectively use patient data collected from unaffiliated physicians. Although there may be copious amounts of

4 information available, shared patient reports may display duplicate figures and medications, incomplete diagnoses, or an assortment of data not mapped to any standard. On the other hand, through a combination of medical terminology management and data normalization, data can be efficiently collected, scrubbed and aggregated to conduct trending analyses. Providers can more easily see how a patient, or population of patients, is responding to the care protocols in question. Complex mappings need robust solutions Mapping and normalizing data is an intensive process, as the ICD-10 transition illustrates. Free General Equivalence Mappings (GEMs) are available from CMS to assist providers with converting from ICD-9 to ICD-10. However, organizations are discovering these GEMs files often are incomplete and difficult to use. For example, the single ICD-9 code (Extrinsic asthma, unspecified) is mapped to four ICD-10 codes in the CMS GEM conversion. This translation, however, omits more than eight other potential ICD-10 codes that are clinically relevant. There are many other examples, which indicate that using the CMS GEMs alone might not adequately or accurately reflect a provider s potential ICD-10 coding scenarios. While the repercussions might be minimal, they might also put the provider at risk for negative financial or patient care ramifications. In fact, the ICD-10 Executive Communications Sub Group of the Health Information and Management Systems Society (HIMSS) states: The GEMs are not a one-to-one match in many instances Crosswalks may be a part of the solution, but they will not enable use of the greater information contained in the ICD-10 codes. 1 In addition, these free GEMs only exist for the ICD-10 conversion, not for the numerous other terminologies organizations need to comply with Meaningful Use Stage 2, such as SNOMED-CT, LOINC or RxNorm. To ease the use of multiple evolving terminologies, provider organizations must undertake a more comprehensive medical terminology normalization and management implementation. This initiative needs to start with senior leadership; CEOs, CFOs, CIOs and CMOs need to recognize the enterprise-wide clinical and financial value of terminology normalization and champion the benefits to supervisors and managers. First, of course, provider organizations must understand their current data management strategies including the input and established initiatives for financial, clinical and other 1 HIPAA 5010/ICD-10 Frequently Asked Questions (FAQs) for C-Suite at Healthcare Provider Organizations. gyfocus pdf

5 departments. By no means an exhaustive list, organizations should ask the following questions during a holistic medical terminology management needs assessment: Are acute, ambulatory and post-acute facilities using the most recent versions of the industry-accepted code sets, such as ICD-10, SNOMED-CT, LOINC, RxNorm, and others? What terminologies do active unaffiliated providers use to communicate with the organization? Which application or system upgrades need to occur for terminologies to be consistent across the enterprise? How will clinical and financial workflows be impacted by the introduction of new code sets? What processes are in place to monitor the terminology standards bodies so that versions are updated in a timely manner? Who needs to be trained on the new vocabularies and code sets? What terminology management tools are available to assist with standardizing and updating multiple systems in multiple locations? Are these standards accessible and current in various health IT applications, including the EMRs? Rather than implementing numerous health information system add-ons or application upgrades, providers should consider a centralized, enterprise-wide medical terminology management solution to accelerate and solidify the normalization initiative. These tools can serve as a consolidated source for all administrative code and medical terminology updates, simplifying the standardization process, and reducing the cost of maintaining controlled vocabularies. Small steps toward the future While provider organizations may still be in the midst of trying to implement ICD-10-CM/PCS and the code sets such as SNOMED-CT and LOINC mandated by Meaningful Use Stage 2, they can perhaps begin to view these projects with a new perspective. With a new mindset, providers can see that medical terminology normalization and management efforts like these are crucial to the ultimate achievement of their financial and patient care goals. As organizations integrate and consolidate, disparate systems and databases will need to be equipped to conduct financial and care quality analytics. Without standard administrative code sets and medical terminologies, these essential functions will not be possible without consuming enormous time, staff and financial resources. Moreover, in the coming years, providers and payers will continue to forge more accountable care and risk-based payment agreements that make efficient and accurate data exchange crucial. Standardizing and normalizing an organization s terminologies will reduce financial risk in these ACO agreements by ensuring that the data reported to payers reflects actual performance and cost reductions.

6 Provider organizations already faced with numerous quality improvement initiatives spurred by Meaningful Use can ease these transitions by taking advantage of medical terminology management solutions that can convert outdated administrative codes and vocabularies and incorporate updates in a timely manner. In the end, making medical terminology management an integral part of operations will result in an organization better equipped to face not only the next stages of Meaningful Use, but the as-yet-unknown future challenges of an everchanging healthcare industry.

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