A history of health information technology and the future of interoperability

Health information technology (HIT), particularly the electronic health record (EHR), plays an important role in how payors measure quality, and therefore, in how surgeons are reimbursed. This article looks at the evolving role of HIT, the challenges of achieving interoperability, and how Congress is working to ensure improved data exchange. It describes surgeons’ frustrations with the current data exchange system and what the American College of Surgeons (ACS) Division of Advocacy and Health Policy is doing to address these concerns. It outlines the significant amount of time the ACS has spent educating members of Congress, Health and Human Services (HHS), the Centers for Medicare & Medicaid Services (CMS), and the Office of the National Coordinator (ONC) about the challenges related to EHR interoperability.

Background on meaningful use

In 2004, President George W. Bush created the ONC for HIT, which is charged with synchronizing HIT in the U.S. health care sector.1 The Health Information Technology for Economic and Clinical Health (HITECH) Act was passed as part of the larger American Recovery and Reinvestment Act of 2009.2 In 2011, the meaningful use (MU) component of HITECH was implemented to expand the adoption of HIT and facilitate the use of EHRs.2

The HITECH Act authorized CMS to establish the Medicare and Medicaid EHR Incentive Programs. These programs paid approximately $35 billion in incentive payments to eligible professionals, hospitals, and critical access hospitals to adopt, implement, upgrade, and demonstrate the use of certified EHR technology (CEHRT).3 The reporting requirements involve the ability of an EHR to perform such functions as generating problem lists, exchanging patient clinical data, or e-prescribing.3

The MU program launched in stages beginning in 2011. The focus of Stage 1 was data capture and sharing. In 2014, the ONC created Stage 2, which sought to extend the requirements of Stage 1 and promote more advanced clinical processes. Stage 3 began this year and extends into 2018. Its focus is on improving overall outcomes, and the MU program is now a component of the Merit-based Incentive Payment System—specifically the Advancing Care Information performance category—under the Quality Payment Program (QPP).3,4

Data blocking or a language problem?

EHRs have remained siloed in their data exchanges and have proven highly inefficient for machine-readable information shared among providers caring for a patient. The real impact of digital information has yet to reach a level adequate to enrich patient care outcomes or greatly increase surgical decision making. Some EHR systems have been accused of data blocking and adding service costs for providers seeking more effective means of data sharing.

When digital systems seamlessly exchange data with each other, it is referred to as interoperability. More specifically, true interoperability occurs when information held in one EHR transfers through a standardized wire format to a separate EHR in such a way that the information exchanged proves to be machine readable by the accepting EHR. Once that information is accepted in transfer, the receiving EHR should have enough appreciation of the content and the context of the data shared to be able to represent the information appropriately in the workflow of the clinicians using the transferred information.

The challenge is that each EHR vendor presents information in its own way, using its own terminology and values. High-level exchange information requires a decoding function that translates the sending EHR’s terminology and values along with the clinical context into a standard that crosses the wire format for the receiving EHR to read. The accepting EHR must interpret and represent the content in the right context using its own terminology and values. However, for many different reasons, often EHR developers, hospitals, health care organizations, and even providers intentionally and unintentionally block the exchange of electronic health data. The result is that digital health information is not seamlessly available for the multiple-use cases a surgeon could imagine for shared information. Fully shared information would increase physicians’ workflows, and that would enhance care, aid research, and provide cost savings.

Even the simplest data exchanges can prove to be challenging. Imagine trying to identify a patient with the most common surname in the U.S., “Smith.” To ensure that patient Smith is the same patient so that information can be transferred from one EHR to the next requires identification matching and a secure trust framework.5 At present, no HIT industry standards for reliable patient identification matching have been established.

Many members of Congress believe most interoperability shortfalls are associated with data blocking. Although data blocking is a concern, most EHR vendors meet the minimum requirements for sharing information. However, the evidence suggests that even though EHR vendors are meeting these minimum requirements, they are not optimally facilitating the data exchanges to accelerate interoperability.6 Complexity, lack of standards, and costs are the primary roadblocks vendors offer when asked to expedite interoperability solutions. To comply with the law, vendors often provide even the most basic information in PDF files, which are not easily interpreted by other EHRs, for transfer. Such transfers may be interpreted as minimum compliance with patient needs and may be viewed as an element of data blocking.

It is more likely that the complexity of information necessary to exchange has resulted in a lack of agreement over standards. The ONC, therefore, is unprepared to set such standards as requirements for CEHRT. The sooner the health information profession and clinical aspects of medicine come together and standardize the information fit for transfer, the more promptly the ONC can act to require standards in CEHRT that facilitate interoperability.

Government fixes

Members of Congress realize that interoperability is crucial in today’s health care environment. On April 16, 2015, President Obama signed the Medicare Access and CHIP (Children’s Health Insurance Program) Reauthorization Act (MACRA) of 2015 into law.4 The primary purpose of this legislation was to permanently repeal the flawed sustainable growth rate formula used to calculate Medicare physician payment updates and replace it with the QPP. However, Congress also declared achieving widespread exchange of health information through interoperable certified EHR technology by December 31, 2018, as a national objective in MACRA. MACRA states that there shall be “widespread interoperability” and established metrics to determine whether, and to what extent, objectives have been met by this time.4

MACRA defined interoperability as “the ability of two or more health information systems or components to exchange clinical and other information and use the information that has been exchanged by means of common standards to provide access to longitudinal information for health care providers to facilitate coordinated care and improve patient outcomes.”4

Specifically, MACRA defines “widespread interoperability” as interoperability between CEHRT systems employed by meaningful EHR users under the Medicare and Medicaid EHR Incentive Programs and other clinicians and health care providers on a nationwide basis.4

The Secretary of HHS delegated authority to carry out this section of MACRA to the ONC. If the Secretary determines that these objectives have not been reached by December 31, 2018, the Secretary must submit a report to Congress identifying barriers and provide recommended actions the federal government can take to achieve them by December 31, 2019.

In addition, the ONC has determined that two measures are the most appropriate indicators of having fulfilled the widespread interoperability MACRA requirement:

  • Measure 1: Proportion of health care providers who are electronically engaging in the following core domains of interoperable exchange of health information: sending; receiving; finding (querying); and integrating information received from outside sources4
  • Measure 2: Proportion of health care providers who report using the information that they electronically receive from outside providers and sources for clinical decision making4

On December 13, 2016, Congress passed the 21st Century Cures Act, which revised a definition of interoperability with three characteristics:7

  • Enables the secure exchange of electronic health information with, and use of electronic health information from, other HIT without special effort on the part of the user
  • Allows for complete access, exchange, and use of all electronically accessible health information for authorized use under applicable state or federal law
  • Does not constitute information blocking as defined in section 3022(a)

Like MACRA, the 21st Century Cures Act mandates support for interoperable network exchange to be spearheaded by the ONC in collaboration with the National Institute of Standards and Technology and other divisions of HHS. This work includes establishing and publishing details about a trusted exchange framework along with a directory of participating health information networks and rules for these networks to apply. It also calls for the establishment of a new HIT Advisory Committee to make recommendations to the ONC on the development of a policy framework to advance an interoperable HIT infrastructure. The new committee will replace the existing HIT Policy and Standards Committees.7

This new committee also will be responsible for submitting annual progress reports on interoperability advancements to HHS and Congress, including recommendations for realizing improvements to interoperability in the health care industry. One new feature is that the ONC must implement a standardized process for receiving complaints about HIT lack of interoperability, and report those individuals or groups responsible for information blocking. The bill also requires HHS to designate standards for health data exchange that improve interoperability.7

The 21st Century Cures Act takes aim at several policy changes and gives authority to the HHS Office of the Inspector General to investigate and penalize information blocking.7

Both MACRA and 21st Century Cures have the potential to improve interoperability. Both mandate that if interoperability goals are not accomplished in a timely manner, the HHS Secretary shall submit a report to Congress identifying barriers and provide recommendations to correct them.

Effects on practice

Surgeons are frustrated when EHR requirements demand more data entry, leaving less face time with patients. More and more, surgeons find themselves managing digital health information from all its various sources. Many surgeons point to EHR frustrations as a large contributor to burnout, adding to the physician wellness conundrum. EHRs should have workflow services built for patients and surgeons that fit the clinical circumstances and advance care.

Clinical care models are growing increasingly complex. The continuum of care for a patient frequently crosses several phases provided by multiple clinicians, each with unique EHRs. In surgery, these phases include preoperative evaluation, preoperative readiness, intraoperative care, postoperative care, and postdischarge follow-up care. To realize the full benefit of digital health information, we will need truly meaningful data following the patient through this continuum.

Information flows that track patients across these phases are now key to optimal quality and safe, affordable surgical care. The surgical care team involves a broad array of providers acting over time across the care continuum beginning with the decision to operate, long before the day of an operation. Complex patients require a team of physicians playing definitive roles in readying a patient for a surgical procedure and anesthesia. Often, these roles extend beyond the day of surgical care into the postoperative recovery period. Patients receive care longitudinally over time, and not always in one facility or under one EHR. Complex clinical care models track patients over time and space.

To fix this problem, Congress and regulatory agencies have tapped EHR vendors for solutions. However, this is a costly misstep, as interoperability problems cannot solely be solved by developing a better EHR. Many clinical institutions are looking beyond the EHR and are considering cloud-based solutions that operate outside the EHR firewalls. These cloud solutions enable tracking of patients across the continuum, providing inputs from patients, clinicians, insurers, and others. Interoperability could extend to medical devices, smartphones, laptops, and so on. If all digital health information partners complied with the same strict standards and terminologies for data elements, interoperable data would be more than just EHR. It would, in turn, encompass clinical data to move in EHRs, mobile devices, clouds, patient records, registries, and more. This level of interoperability would enable the industry to leverage digital health information for better health, improved care, and optimal cost-effectiveness.

ACS action

The ACS is working with Health Level Seven (HL7), an American National Standards Institute-accredited standards developing organization, and the Health Services Platform Consortium (HSPC) to create a framework for working interoperability in order to track patients across their care continuum with digital health information specific to their care needs.8,9 This interoperability framework is extremely complex. Individual patient models must define all workflows for clinical care, step by step. The care models must be mapped out for every instance and option for care. Each element of these models must be translated into specific clinical definitions all providers agree to accept. Then those definitions are assigned machine-readable terminologies from known standards held in recognized libraries such as the Systematized Nomenclature of Medicine–Clinical Terms (SNOMED CT), and assigned logical observation identifiers names and codes (LOINC) and RXNorm.10-12 When appropriate, those terminologies need to be bound to a value set from the U.S. National Library of Medicine.13 Upon completion of these steps, the ACS plans to ask HL7 to accept these clinical definitions with their assigned terminologies and bound value sets to become an acceptable standard.

Once acceptable standards are agreed upon by the clinical community and the HL7 technology community, the final step will depend on the ONC and CMS requiring that these standards be part of EHR certification so that the information is available for an interoperable wire format exchange.8 The ACS believes that this affirmation by CMS should be at a scale large enough to set the de facto standard for EHR interoperability across payors.

Even though Congress has developed many pieces of legislation and programs to address interoperability concerns, our clinical care models remain complex and in need of change. The digital health care information needed to optimize modern care models must use standardized data that operates between EHRs, registries, and other smart HIT devices across the surgical care continuum. Clinicians and HIT engineers across the clinical domains must come together to ascribe clinical definitions that map to machine-readable formats using common terminologies and values. Additionally, the government must demand these aspects of interoperability be mandated as nationally required standards. To achieve this goal, the ACS will work with both the regulatory and legislative sides of government to implement effective, meaningful change.


  1. The American Presidency Project. Executive Order 13335—Incentives for the Use of Health Information Technology and Establishing the Position of the National Health Information Technology Coordinator. Available at: www.presidency.ucsb.edu/ws/?pid=61429. Accessed September 22, 2017.
  2. U.S. Department of Health & Human Service. HITECH Act Enforcement Interim Final Rule. Available at: www.hhs.gov/hipaa/for-professionals/special-topics/HITECH-act-enforcement-interim-final-rule/index.html. Accessed September 22, 2017.
  3. Centers for Medicare & Medicaid Services. Electronic Health Records (EHR) Incentive Programs. Available at: www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/index.html?redirect=/ehrincentiveprograms. Accessed September 22, 2017.
  4. Congress.gov. H.R.2—Medicare Access and Chip Reauthorization Act of 2015. Available at: www.congress.gov/bill/114th-congress/house-bill/2/text. Accessed September 22, 2017.
  5. National HIE Governance Forum: Trust Framework for Health Information Exchange. Available at: www.healthit.gov/sites/default/files/trustframeworkfinal.pdf. Accessed September 22, 2017.
  6. The Office of the National Coordinator for Health Information Technology (ONC) Department of Health and Human Services. Report on Health Information Blocking. Available at: www.healthit.gov/sites/default/files/reports/info_blocking_040915.pdf. Accessed September 22, 2017.
  7. Congress.gov. H.R.34—21st Century Cures Act. Available at: www.congress.gov/bill/114th-congress/house-bill/34. Accessed September 22, 2017.
  8. Health Level Seven International. Introduction to HL7 standards. Available at: www.hl7.org/implement/standards/. Accessed September 22, 2017.
  9. Healthcare Services Platform Consortium. Our approach. Available at: http://hspconsortium.org/about/our-story/. Accessed September 22, 2017.
  10. U.S. National Library of Medicine NIH. Health IT Home. SNOMED CT. Available at: www.nlm.nih.gov/healthit/snomedct/. Accessed September 22, 2017.
  11. LOINC. The Universal standard for identifying health measurement, observations, and documents. Available at: https://loinc.org/. Accessed September 22, 2017.
  12. U.S. National Institutes of Health National Library of Medicine.Unified Medical Language System (UMLS). RxNorm. Available at: www.nlm.nih.gov/research/umls/rxnorm/. Accessed September 22, 2017.
  13. U.S. National Institutes of Health National Library of Medicine. Databases. Available at: www.nlm.nih.gov/. Accessed September 22, 2017.

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