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AAOS Now

Published 7/1/2015
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Jared L. Harwood, MD; Andrew Pugely, MD; Frank G. Opelka, MD, FACS

The Interoperability of Health Data

At the 2014 AAOS-sponsored Orthopaedic Quality Institute (OQI), cochairs Kevin J. Bozic, MD, MBA, and Thomas C. Barber, MD, brought together a wide range of external stakeholders to focus on topics relevant to the quality movement in orthopaedic surgery. Among those topics, healthcare data informatics stood out as a field undergoing explosive changes. One presentation in particular, by coauthor Frank G. Opelka, MD, addressed the need and benefits of creating an enriched clinical data ecosystem to leverage clinical informatics for better health care.

A data ecosystem is a new way of drawing data together from disparate systems. It coordinates data from different sources—rather than simply cobbles together different sources of data. As a result, the data become accessible and useable quickly and efficiently.

New clinical data ecosystems are a critical part of the infrastructure needed if surgeons are to optimize electronic health records (EHRs) in clinical workflows and registries. Then, information can be pulled from any EHR and repurposed for performance measurement, maintenance of certification, performance improvement, research, and other uses.

Additionally, many organizations—including the Departments of Defense, Health and Human Services, and Veterans Affairs—have endorsed the “Blue Button” initiative, which was born out of a desire to make patients more like health information participants than merely health information recipients. Websites and EHRs with the Blue Button symbol enable patients to download their own personal health records in a readable format. Further enhancements will enable automated data exchanges among provider systems and ways for researchers and other stakeholders to access and analyze the data.

Ideally, most physicians and hospitals store digital information in EHRs and other primary data sources, such as intensive care unit and anesthesia records. Using informatics technology known as service-oriented architecture, a common data infrastructure could be built, similar to Android or iOS operating systems. This platform could pull information from the EHRs to provide the data required to improve workflow and quality efforts.

Background
The quest for improved health information technology began in 2004, with the appointment of the nation’s first national health information technology coordinator. Five years later, the Health Information Technology for Economic and Clinical Health (HITECH) Act was passed to promote the adoption and meaningful use of health IT. Since then, the Centers for Medicare & Medicaid Services (CMS) and the Office of the National Coordinator for Health IT (ONC) have worked to advance EHR implementation nationwide.

CMS coordinates the EHR Incentive Program while the ONC manages the EHR Certification Program. The EHR Incentive Program evolved into three stages of meaningful use; in each stage eligible hospitals and providers must demonstrate meet selected core and menu items to be eligible for incentive payments. (See “Meeting the Challenges of Meaningful Use Stage 2” and “Meeting Meaningful Use: One Practice’s Experiences.)

The meaningful use rollout began in 2011; providers initially had concerns about the efficacy, the logistics, and the cost of implementing EHRs. Stage 1 focused on the basic functions of an EHR, such as storing demographics and e-prescribing. In 2014, stage 2, focused on enhancing patient engagement, interoperability, and health information exchange, was introduced.

This year (2015), providers and hospitals that have not participated in the EHR incentive program will begin to incur reimbursement penalties of 1 percent; penalties will increase to 3 percent by 2017, when stage 3 is slated to begin. By 2018, stage 3 will be mandatory.

Despite the rollout difficulties and cost concerns, EHR utilization has accelerated significantly in recent years. The percentage of physicians using an advanced EHR increased from 17 percent in 2008 to more than 50 percent in 2013. During that same time, the number of hospitals using EHRs increased from 9 percent to more than 80 percent.

Without the HITECH Act, the Congressional Budget Office (CBO) has estimated in 2009 that about 45 percent of hospitals and 65 percent of physicians would adopt qualifying health IT by 2019. The HITECH incentive mechanism was estimated to increase those numbers to about 70 percent and 90 percent respectively. In actuality, the percentage of physicians using an advanced EHR increased from 17 percent in 2008 to more than 50 percent in 2013. During that same time, the number of hospitals using EHRs increased from 9 percent to more than 80 percent.

This suggests that the HITECH incentive mechanism has accelerated the implementation of EHRs by both hospitals and physicians . The CBO estimated that savings from this accelerated adoption would exceed federal outlays paid to encourage it.

Under the HITECH Act, each eligible professional could receive as much as $44,000 through Medicare and $63,750 through Medicaid for installing computer systems that meet federal standards. However, several studies have estimated that the cost of purchasing and installing an EHR ranges from $15,000 to $70,000 per provider. Although hospitals could qualify for incentive payments totaling more than $2 million, outlays for a large health system could amount to several hundred million dollars.

Potential benefits
Despite some frustration among healthcare providers, EHRs are here to stay and offer several potential strengths. Although paper records allowed for adequate in-office patient care, EHRs enable health systems to better serve the population at large. For example, EHRs make it easy to list patients who are overdue for a postoperative visit.

Yet, to fully unlock the data available in EHRs, the information needs to be standardized in a vendor-neutral format. Overcoming this interoperability hurdle is the next big challenge. Indeed, the evolution of EHRs has contributed to data silos that make it very difficult for individual providers and health systems to exchange useful information. Patients still carry folders of haphazardly printed medical records to their consultant or institution.

This lack of interoperability is most obvious in medical research. Collecting research data is still cumbersome, and sharing data with other institutions, as is required in multicenter collaborative research, requires duplicative data entry into multiple systems, which is both time- and resource-intense.

Advances in healthcare informatics may facilitate health information exchange in both research and clinical settings. For example, registries—an intermediate step in the process—are becoming more common. Last year, CMS began to accept participation in qualified clinical data registries (of which there were 36 as of June 2014) for payment programs. This is an important step that encourages participation in registries and begins to provide orthopaedics with more useful information. Participation in qualified clinical registries can allow easy reporting of quality metrics for CMS payment programs and help physicians qualify for metric-based quality payments.

Although costly to establish and maintain, clinical registry data enable more precise benchmarking and quality assessment than traditional administrative claims data. The success of the American College of Surgeons’ National Surgical Quality Improvement Program (NSQIP) is just one example that shows how amassing relevant data can improve outcomes. The program touts impressive results, claiming that participating hospitals on average prevent 250 to 500 complications and save 12 to 36 lives as well as millions of dollars per year. Under a pilot project with NSQIP, the AAOS is starting to amass clinically relevant data in the care of hip fractures and outpatient rotator cuff surgeries.

Although the NSQIP requires a full-time champion at each site responsible for data collection and entry into the system, most registries must still deal with several EHRs that pull data from multiple sources and vendors. Again, improved intraoperability would simplify and speed data collection and analysis.

New models
Health information exchanges (HIE) or “platform as a service” constructs use a common cloud- or Internet-based data infrastructure that enables health information to be pooled and queried in a much simpler manner. Many HIEs are surfacing around the country to facilitate the sharing of healthcare information across regions, communities, and hospital systems. Several regional health information organizations are emerging to develop and maintain HIE standards for constituents within a geographic area. Earlier this year, the ONC chief released an interoperability roadmap calling for a system that allows most providers to send, receive, and use a common set of clinical information by the end of 2017. This interoperability requires systems to “speak” the same language.

Health Level Seven International (HL7) is a nonprofit, standards-developing organization that aims to provide a comprehensive framework for the transfer of electronic health information. Emerging application-programming interfaces enable third parties to develop applications that can reach across health systems and pool data in real time and with minimal disruption to workflow. HL7 has produced several iterations of its clinical document architecture (CDA), which standardizes the encoding, structure, and semantics of clinical documents for exchange. Similar standards have been developed for medical imaging data (digital imaging and communications in medicine, or DICOM).

Some nonprofit consortiums, such as Integrating the Healthcare Enterprise (IHE), have been working to optimize standards for CDA and DICOM using “profiles” that allow for vendor-neutral interoperability between systems. IHE also hosts annual “connectathons” in Asia, Europe, and North America that enable vendors to test and showcase their interoperability and integration. The Healthcare Services Platform Consortium is striving to create an activity-based EHR around a service-oriented architecture with subapplications to allow real-time feedback and knowledge generation.

Despite the acronyms and tech-heavy jargon, the take-home message is that EHRs are being adopted at a dizzying pace. With multiple EHR systems in use, the next big challenge is interoperability, which has the ability to unleash the true potential of EHRs in both the clinical and research arenas. Only after the inoperability hurdles are overcome will all the cost and effort be truly “meaningful.”

Jared L. Harwood, MD, and Andrew Pugely, MD, were the 2014–2015 AAOS Washington Health Policy Fellows. Frank Opelka, MD, FACS, is a colorectal surgeon working at Louisiana State University, the medical director for quality and health policy at the American College of Surgeons, and the executive vice president of LSU Health in Baton Rouge, La.

Bottom Line

  • Common data infrastructures and clinical data ecosystems are necessary to fully realize the benefits of electronic health records (EHRs).
  • EHRs are becoming more ubiquitous in medical offices, but the lack of standardization makes unlocking and linking the data they hold difficult.
  • New standards-developing organizations and consortiums are addressing this issue in a variety of ways.
  • Once interoperability hurdles are overcome, physicians will truly be able to make “meaningful use” of EHR data.