There are different aspects to interoperability, requiring different facilitative specifications depending on the interface, character, and needs. In addition to technical interoperability, in which standardized protocols are used to allow secure data transfer from one machine to another, the elements of syntactic, semantic, and organizational interoperability afford further interface functions to allow information to be exchanged and understood, and to inform (see Figure 4).
Syntactic interoperability brings standardized formats, such as the segments and elements in the HL7 Version 2 (v2) standard, for organizing the data in messages being exchanged. Specific kinds of data populate agreed-upon locations in the messages; for example, in an HL7 v2 laboratory results message, the third element of the observation/result (OBX-3) segment contains the identity of the lab test performed.
Semantic interoperability further enables more complete and specific data exchanges because an agreed-upon standard terminology is used by the data exchange partners. In the case of the lab test performed, the universal coding system LOINC (Logical Observation Identifiers Names and Codes) can be used to identify the lab test via a unique code name. For example, if the LOINC code 806–0 is in the third element of the OBX segment (OBX-3), the receiving system can automatically identify the test (i.e., leukocyte in cerebral spinal fluid by manual count) and process the rest of the message as the result of the leukocyte count.
Organizational interoperability involves the automation of workflow based on standardized business processes. In an HL7 v2 laboratory results message, for example, the eighth element of the OBX (OBX-8) segment indicates whether the result of the lab test performed is abnormal. If this element flags that the test result is outside of the normal range based on an agreed-upon clinical model, this flag can trigger a behavior in the receiving system, such as displaying an alert to the clinicians or ordering a follow-up lab test automatically.
When considered from the perspective of a health care delivery organization, Figure 5 provides a conceptual model developed by William Stead from Vanderbilt University Medical Center and the Center for Medical Interoperability for assessing the maturity of data liquidity across multiple domains of interoperability. In this assessment, health system executives may assess organizational interoperability and data liquidity status by applying these five questions:
Building on existing concepts of interoperability, the scope of interoperability covered in this report is holistic and based on the thesis that when interoperability is enabled throughout multiple levels in the health care ecosystem, the value of health technology investment can be maximized. Interoperability means the
ability to share, abstract, or link data from electronic health records, medical equipment, registries, laboratory results, records from prescriptions, and specialist consultations, as well as administrative and claims records, patient portals, even wearable and mobile devices. Figure 6, Panel A portrays the functional interoperability required across the three tiers: inter-facility (macro-tier), intra-facility (meso-tier), and point of care (micro-tier) in the health care ecosystem. It is important to note, however, that the three-tier structure represents an organizing schematic with some distinct features and stakeholders within each tier. In practice, data exchanges do and should occur across tiers. As the fully interoperable system envisioned in Figure 6, Panel B, interoperability needs to encompass all tiers to enable whole-person and whole-community care—(e.g., supporting population health management, data access by patients and families, and third-party application development, to name a few).
To illustrate the importance of all three tiers, consider a scenario where a patient is involved in a car accident. She is taken to the nearest county hospital and then needs to be transferred to a trauma center to undergo emergency surgery. The trauma center dispatches its ambulance to transport the patient. While en route, she experiences cardiac arrest. Even though the trauma center and the county hospital use different EHR vendors, the transport team and the trauma
center are able to immediately obtain initial assessments, treatments, and imaging data. Meanwhile, the trauma center staff can see vital sign data from the ambulance in real time. Once the patient arrives at the trauma center, information from a variety of medical and monitoring devices is seamlessly integrated with information from the county hospital and displayed on a visual dashboard for the entire care team.
Or consider a health care system that has been increasingly engaged in value-based contracts with various payers through bundled payment or other
shared-risk programs. A care team designated to optimize care management for patients with diabetes needs to draw data from multiple record systems within the organization to monitor their hemoglobin A1c testing and control status, making sure the patients receive annual retinal examination, achieve blood pressure control, and receive medical attention for signs of nephropathy. They will also need data automatically integrated from multiple devices when the patients visit their primary care physicians, ultimately allowing patients to upload their own data from their mobile devices. Members of the care team can receive notifications nearly in real time when a patient is admitted to the
emergency department (ED). In addition, care coordinators rely on data shared from various external partners—ranging from pharmacies to behavioral health providers and social services agencies that serve the same patients—to provide high-value, high-quality, coordinated, and timely care. Figure 6B portrays this evolving state of interoperability, and related descriptions of the three tiers are described below and summarized in Table 1.
The macro-tier, illustrated in the top portion of Figure 6, represents health data exchanges across health care systems or between a health system and another entity such as a pharmacy or public health agency, some of which occur via regional or state-level Health Information Exchanges (HIEs) or an industry-wide network such as the Sequoia Project and the CommonWell Health Alliance. Over the past few years, the Patient Protection and Affordable Care Act and the Electronic Health Record Incentive (also known as the Meaningful Use) programs provided incentives to advance the basic ability to share data across health care systems. Information at this level is typically shared through the Clinical Document Architecture (CDA) framework, which enables clinical documents to be structured in a way that allows them to be read by both humans and computers.
Within each provider organization or health system, patient records are collated and made accessible through a centralized data aggregating and distribution entity (i.e., HIEs) and then shared across systems through information exchange gateways. Significant progress has been made in this tier, but the most recent data found that less than 30 percent of hospitals were able to find, send, receive, and integrate electronic patient information from outside providers (Holmgren, Patel et al., 2017). This means sizable challenges still exist: patient matching or identity management, fragmented records from multiple providers, attribution of the physician, and the potential for redundancy represent some of the usability and quality issues associated with data passed through the macro-tier. Providers and payers are also discovering new challenges in exchanging data outside the health care sector as they strive to address population health.
Here are three examples of macro-tier data exchange that are currently in play, though with significant gaps:
sharing, as well as managing access from public health agencies and behavioral health providers.
The meso-tier in Figure 6B represents interoperability within a health care organization, in which information was exchanged between an EHR and other information management systems such as those used in clinical laboratories, pharmacies, food services, facility management, and patient administration (admission/discharge/transfer). Interoperability at this tier facilitates the operational workflow and coordination throughout the entire episode of care, supporting both clinical and administrative activities with a coherent picture of the patient’s care processes and condition over time. Ensuring data elements are consistent across these systems not only reduces administrative burden but also improves patient experience with their care.
Currently, many hospitals procure locally hosted technologies such as pharmacy, laboratory, and other systems that enable varying degrees of integration with their respective EHR system. Some hospitals also acquire component technologies that aggregate data from these disparate IT systems before funneling that data to their EHR system for documentation of services and other purposes. Whether
intra-facility interoperability is driven by individual health systems or through partnerships, the ability to exchange data among different health IT modules is typically provided through vendor-to-vendor agreements. Integration based on numerous unique, stand-alone agreements requires significant resource investment, technical expertise, and maintenance over each IT module’s life cycle. This approach typically is not scalable, is costly, and is not sustainable as a long-term solution for the industry.
The following examples illustrate the value of enhancing meso-tier data exchange:
The micro-tier represents the data and information exchanged at the point of patient care (Figure 6)—whether at a particular care site (e.g., equipment and monitors in an intensive care unit) or generated by patients themselves (e.g.,
wearable or mobile health applications). Interoperability within this tier has great potential for improving patient safety, reducing medical errors, and reducing costs; it is also the level at which health systems have significant control and accountability through their procurement processes. At the point of care, data streams may be quite disparate and heterogeneous, ranging from verbal communications to medical record entries, device settings, image data, traditional laboratory results (e.g., blood type), and nontraditional data such as genomics and other patient-specific data. As with the other tiers, the data can consist of a combination of structured data, unstructured data, free text, and verbal communications.
Currently, micro-tier data exchange still largely relies on clinical staff (Figure 6, Panel A). Data generated by a medical device that are not exported to other systems means clinical staff must interpret the data, manually transcribe relevant values into the medical record, and possibly initiate an adjustment to the course of treatment. Transcription errors are common; one study found an error rate as high as 19 percent when clinical staff manually transcribe vital signs onto paper and then subsequently enter them into EHR (Fieler et al. 2013). In comparison, the use of electronic vital signs documentation systems resulted in significantly fewer errors and shorter elapsed time. The lack of true interoperability at the point of care, coupled with the advances in medical technologies that make clinical decision making increasingly complex, puts a tremendous burden on providers and poses great risk of medical errors and eventually, patient harm.
For example:
disease severity, and comorbidity), available technology has not provided an automated visual display of the conformity of a care regimen to recommended protocols. To fill this gap, researchers at Johns Hopkins Medicine (Romig, Tropello et al., 2015) used a systems engineering approach and developed a technology platform that integrated a variety of data elements from the EHR and from other sensor devices, which then graphically displayed the data on a tablet in real time to trigger and monitor the implementation of patient harm prevention measures.
TABLE 1 | Definitions, applications, and the current state of interoperability
| INTER-FACILITY EXCHANGE (MACRO-TIER) | INTRA-FACILITY EXCHANGE (MESO-TIER) | POINT OF CARE EXCHANGE (MICRO-TIER) | |
|---|---|---|---|
| Definition | Exchange of information among organizations and networks. | Exchange of information among care units within an organization or network, including operations and administrative IT systems. | Point-of-care exchange at which care devices, equipment, records, and clinical staff interact with patients. |
| Example Clinical Applications | Continuity of care across different providers and types of facilities (e.g., providers in different geographical areas, multiple pharmacies); population health management in accountable care models through addressing medical, behavioral, and social needs; information exchange with public health agencies. | Consolidation and automatic exchange of patient records across laboratory and radiology with EHR; data exchanges among scheduling, billing, quality reporting, and care delivery IT systems; continuity of care across facilities within the network (e.g., outpatient clinics, EDs, in-patient services, and postacute care facilities). | Automatic data exchanges from bedside monitors to the EHR; programmable infusion pumps with safety interlock that allow signals from patient vital signs monitors; postdischarge patient monitoring through wearable devices. |
| Current State | Some progress in data exchange standards, regional HIEs, and direct exchanges across providers. Challenges remain in workflow integration. | Some progress through software interfaces, but manual handling and duplication of records are common. | Clinical staff performs the majority of data exchange. Adoption of custom middleware solutions to enable connections between two proprietary interfaces. |
| Future State | Fast and secure data exchanges across care providers; coordinated data aggregation across clinical, behavioral health, public health, and social service agencies in support of population health management; access and control by patients for their own care record. | Integrated IT infrastructure within the health care provider systems that allow seamless application of risk management analytics, workflow integration, quality improvement and reporting, and cybersecurity protection. | Integrated patient care devices and IT system based on open architecture connectivity and nonproprietary standards; modular upgrades to plug- and-play components and devices as needed; integrated telemedicine capabilities, connected mobile health technology, and patient portals to augment in-person clinical encounters. |
Currently, medical device vendors lack the market imperative to ensure interoperability, partly because providers bear most of the costs of integrating these devices and because there is an absence of an aligned demand to drive change in the technology ecosystem. Some health care providers achieve some level of medical device integration, particularly to support data to EHR integration. However, in the perceived absence of a prominent value proposition, many devices are not integrated with other technologies at all. Although it is unlikely that medical device and IT vendors will spontaneously and proactively move toward standardized “plug-and-play” device interoperability, clearly clinicians have significant motivation for demanding medical device data liquidity and interoperability. Solutions are urgently needed to address the efficiency, capacity, and cost issues faced by health care providers under the pressure to shift toward value-based payment models.
The community of health IT vendors has evolved primarily into two categories: companies that support the ambulatory market, and those targeting the hospital market. There was initially little crossover between these two groups, but more recently, vendors have moved toward providing health IT solutions capable of functioning in both domains. Health IT solutions for the in-patient setting are more complex, and far fewer vendors service that market, which is dominated by Epic Systems, Cerner, and MEDITECH. The market is also segmented by size and complexity; academic medical centers and large integrated delivery networks select vendors that are different from those selected by small critical access hospitals. For smaller or independent practices, less expensive or less resource-intensive platforms such as athenahealth and eClinicalWorks lead in market share. This breakdown is evolving, however, as large EHR vendors have been retooling their offerings to be more competitive in different market segments.
In contrast, as indicated in Figure 7, the ambulatory market is characterized by a much larger number of vendors (684 as of July 2017) with Epic again demonstrating significant market share, followed by Allscripts and eClinicalWorks. Nevertheless, the amount of consolidation and the number of developers leaving the market is increasing. This trend creates difficulty for individual physicians and small practices that lack the infrastructure support to make transitions to an alternative vendor, which can be time consuming and costly, and provide an opportunity for clinical errors. Of note, recognizing the need, the ONC developed technical support resources targeted at smaller providers within its Health IT Playbook
(Office of the National Coordinator for Health Information Technology,) and the EHR Contracting Guide (Office of the National Coordinator for Health Information Technology, 2016). Finally, an increasing percentage of users are choosing to have their data hosted in a secure cloud by their vendors. The vendor provides the security, infrastructure, backup, and maintenance of the software and data that many find difficult to manage in small practice settings. In addition, cloud-based technologies are much easier and less costly to update.
With broad recognition of the importance and value of interoperability in health care, various governmental and industry entities have collectively made progress across all three tiers of interoperability. What follows are some exemplary national and consortium efforts:
proven principles for success in designing and implementing IT to advance patient safety (National Research Council, 2012).
in the form of specifications, software reference implementations, and an interoperability testing and certification program.
prevent, or materially discourage access, exchange or use of electronic health information.” The act calls for, “without special efforts,” open APIs based on modern standards such as JSON and FHIR. In addition, the act requires the federal government to develop a Trusted Exchange Framework and Common Agreement (TEFCA) to provide a single “on-ramp” to nationwide interoperability while achieving a competitive, sustainable market (114th Congress, 2015).
Taken together, these milestone efforts pave the way toward better interoperability on several fronts: the development of data exchange standards, promoting open API, combating information blocking, building data partnerships with the social services sector and public health, embracing open platform and exchange capabilities at the delivery system level, and integrating claims, EHR, and pharmacy data.
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