Health Information System Interoperability

Chapter 4 of 11

Although the health IT sector has continued to make a significant impact in facilitating cooperation between Electronic Health Records (EHRs), it still has a long way to go in terms of simplifying healthcare interoperability. Research shows that approximately 30% of hospitals have utilized the 4 essential functions required for interoperability:

  • Data reception
  • Data gathering
  • Data distribution
  • Data integration

Nevertheless, issues remain the same, whether or not a healthcare facility is readily performing on these four critical metrics.

But what is interoperability, and what is its impact in the healthcare industry?

4.1. DEFINITION

Interoperability is the ability of different systems or components to exchange information in a meaningful way. Interoperability enables information generated by one system to be accessed by another system regardless of their technological differences.

In healthcare, interoperability is the ability of different Health Information Technology (HIT) systems to communicate, exchange data, and use health information in a meaningful way. Although the interoperability of computerized health information systems is most often used in local organizations, sharing data is also a significant concern at the federal level. These systems are not designed to communicate with other systems outside the local organization. Ideally, interoperability should follow open standards and support information exchange between different healthcare organizations, and meeting this challenge is a major concern for HIT developers and implementers.

Healthcare organizations run on disparate EHR platforms, thereby making it excruciatingly difficult to connect seamlessly with one another. This can result in avoidable difficulties with patient care.

For instance, approximately 25 percent of surveyed medical practitioners said that they still cannot make use of vital patient information that was received electronically from outside sources as presently shared outside siloed EHRs.

About 27 percent of medical record administrators stated that transmitted patient data was not presented in a workable format, which is an increase from the 22 percent of these administrators that said the same thing back in 2017.

EHRs consist of a series of heterogeneous systems built into silos that are abruptly asked to work unitedly for the good of a patient.

4.2. PURPOSE

Health information interoperability serves many purposes depending on the person who uses it:

  • For patients, interoperability helps improve the quality and safety of care by improving the quality of data flow, data exchange and access to information
  • For healthcare professionals, interoperability enhances access to health records and information anytime and anywhere
  • For health researchers, health information interoperability facilitates access to medical data
  • For health managers, interoperability improves efficiency of data collection, economic and statistical analysis

4.3. HISTORY

EHRs underwent a rapid transformation over the past 50 years. The pace of change significantly increased due to the proclamation of the HIT for Economic and Clinical Health (HITECH) Act in January 2009.

EHRs made their first appearance in the United States history in the late 1960s when multiple similar efforts sprang up around the country. The most well-known milestone of EHR development include Lockheed Corporation’s creation of a system featuring computerized physician order entry for El Camino Hospital. Other milestones of EHR development include the deployment of Health Evaluation through Logical Processing system by 3M and the creation of the Regenstrief Medical Record System in 1972.

Dr. Clem McDonald of Regenstrief Institute expected their medical record system to solve three problems in the hospital setting, namely:

  • Reduce the work of clinical bookkeeping
  • Eliminate problems associated with paper records such as unavailable or undecipherable clinical records
  • Increase medical record accessibility to clinical and epidemiological outcomes and management research

The greatest challenge to EHR system design surfaced in the 1990s when a growing number of users started adopting EHR in their medical practices. The opening of this fast-growing market tested the limits of commercial vendors. They could not quickly adapt to the new opportunity as they were too accustomed to the unique demands of different inpatient markets such as physician-specific workflows, integrated billing, manageable footprint, and intra-organizational interoperability.

While most systems advanced in hardware and software technology, EHR adoption among providers did not catch up with technical advances. Fragmentation of healthcare delivery allowed each hospital and physician to practice medicine the way they wanted to, thereby encouraging EHR system customization according to their needs. EHR systems were not standardized because neither the hospital nor private practices were standardized. System designers tried with little success to force-fit paper-oriented workflows into the computer-based system. The lack of common standards prevented the sharing of data across care settings.

With passage of the HITECH Act, two highly disruptive market forces, Medicaid and Medicare, further disturbed the equation. The Centers for Medicare and Medicaid Services (CMS) recognized this cap in EHR capabilities and decided to offer incentives to physicians who chose to invest in the systems. Since physicians were not demanding EHR systems on their own, CMS was able to motivate the fragmented customer base to act as a single customer with a coherent demand, thereby promoting standardization in the healthcare industry. Interoperability with other systems and EHR features became the main requirements of EHR meaningful use.

4.4. COMPONENTS

Health information interoperability has a three-layered structure or components:

  • Foundational interoperability – Allows data exchange from one Information Technology (IT) system to be received by another. There is no requirement for the receiving information system to interpret the data. This might involve sending an image, free text, or a pdf document.
  • Structural interoperability – Defines the structure or format of the message format standards (syntax). This is used when the data being exchanged is standardized and uniform between the sending and receiving systems, and therefore, the clinical or operational meaning of the data remains intact. Structural interoperability ensures that data exchanges between systems can be interpreted at the data field level.
  • Semantic interoperability – Provides interoperability at the highest level that delivers shared meaning between different systems. This approach leverages the structure and degree of codification of the data, including vocabulary, which allows the receiving system to interpret the incoming data. In most cases, two different EHR systems do not use the same terminology. For example, one system defines a blood test as Fasting Glucose, while another system defines the same test, Fasting Blood Sugar. Semantic interoperability provides the vocabulary translation between systems making meaningful data exchange possible between disparate EHR systems, business information systems, medical devices, and mobile technologies.

4.5. TOOLS & TECHNIQUES
4.5.1. MODEL-DRIVEN HEALTH TOOLS

Model-driven health tools are essential for the establishment of a modeling framework and infrastructure. They are needed to develop seamless nationwide health IT standards for model sharing, open communication, and standard development within the healthcare sector and the HIT community. By using model-driven health tools, health information can have automated validation tools, an automated publication of implementation guides, and JAVA implementation API for the models. Furthermore, development time and cost will be reduced by providing clear documentation of healthcare initiatives and supporting implementation resources.

4.5.2. ELECTRONIC HEALTH RECORDS (EHRS)

EHRs are the digital version of patients’ charts. EHRs go beyond the use of paper-based patient records by including patients’ medical history, diagnosis, and treatment plan, as well as their laboratory results and radiology images. Aside from these, EHRs give healthcare providers access to evidence-based tools that enable them to make better decisions regarding their patients’ healthcare needs. EHRs are the focus of health information interoperability experts. Achieving EHR interoperability will facilitate better workflow and efficient data transfer between EHR systems and promote smoother healthcare delivery.

4.5.3. INTERNATIONAL STATISTICAL CLASSIFICATION (ICD) – 10

ICD-10 is the tenth revision of the International Statistical Classification of Diseases and Related Health Problems. It is the new medical classification list released by the World Health Organization (WHO) after ICD-9 became obsolete. As endorsed by AHIMA, ICD-10 is essential to improve the quality of health information needed to meet the demands of a growing global and electronic healthcare environment. Modern EHRs and interoperable information systems require a modern health classification such as ICD-10 for reporting data and summarizing healthcare information. ICD-10 is now considered an integral part of EHR systems to achieve information interoperability in all levels of the healthcare sector.

4.5.4. SNOMED-CT

AHIMA called for the implementation of SNOMED-CT as the new standard clinical terminology to facilitate health information exchange within the national health information network. The new standard will improve the interoperable exchange of health information between different systems using standard EHRs. AHIMA expects that this new standard in clinical terminology will help improve access to legible clinical data that links to medical knowledge to support real-time decision-making of healthcare practitioners. The standard will also expedite care delivery, reduce duplicate testing and prescribing, and identify relevant patient information to facilitate automatic patient reminders and practitioner alerts. This will improve the ability to perform queries to review the quality of care for benchmarking, interpreting the effectiveness, and measuring quality improvement.

4.6. BEST PRACTICES

Best practices and standards for health information interoperability exist to facilitate the communication between health information systems in a uniform manner across systems, organizations, states, and national boundaries. Following the standard practices at the regional and national level boosts the potential power to share health information between healthcare organizations and enables eHealth initiatives.

4.6.1. INTEROPERABILITY LEVELS

Interoperability has various levels, and each level indicates the complexity of health information exchange.

  • Non-electronic information – Non-electronic information uses minimal technology to share data, and most of the health information gathered is recorded on paper. An example of this type of health information exchange is the referral from a primary care unit to a secondary care unit using a paper-based referral letter.
  • Machine-transportable Information – This type of health information exchange transmits non-standardized data using the most basic form of IT. The most recognized example of this kind of information sharing is paper-based health information through fax or email attachments.
  • Machine-organizable Information – Machine-organizable information is the use of structured electronic messages to transmit non-standardized data. An interface is required for this type of information exchange to transfer data across one or more systems.
  • Machine-interpretable Information – Machine-interpretable information uses structured messages with coded and standardized data to transmit data across different systems. This type of health information exchange uses a format and a vocabulary that is easily understood by the receiver even without an interface to decode such information.

4.6.2. INTEROPERABILITY DIMENSIONS

Health information professionals should first understand the type and level of operability that is needed for proper planning to share health information. This will facilitate the integration of any system and achieve the desired outcomes. Interoperability has six dimensions. These dimensions provide the framework for the types of interoperability needed when developing an integrated healthcare solution. It helps providers select the level and type of interoperability required to achieve the desired exchange of health information.

  • Uniform movement: Healthcare information should be preserved when transmitted between systems.
  • Uniform presentation: Different providers using different systems should view healthcare information in the same visual format when needed.
  • Uniform visual interface controls: Consistent context and navigational control should be established across various systems.
  • Uniform safeguarding of data security and integrity: IT professionals should ensure that only authorized users and programmers have access to data in transmission between systems.
  • Uniform protection of confidentiality: Confidentiality should always be protected by ensuring healthy information governance controls across organizations involved in healthcare information sharing.
  • Uniform assurance of a typical degree of system service quality: IT professionals should always ensure that interoperable systems are reliable. They should make sure that emergency plans are in place in case a breakdown of communication occurs between systems.

4.6.3. INTEROPERABILITY STANDARDS

Interoperability depends on both syntax and semantics. HIT professionals should always ensure that interoperability standards address the requirements of these two types of interoperability. The following are the standard categories applied in healthcare:

  • Messaging standards – Messaging standards guide the formulation of structure, content, and data requirements needed for the electronic message, the unit of information sent from one system to another, by enabling the effective and accurate sharing of healthcare information.
  • Terminology standards – These are a set of standards that provide specific codes for terminologies and classifications of clinical concepts such as medications and diseases. Terminology systems assign a unique code to each particular disease or entity, and these terminologies, in turn, are used to capture clinical information at the point of care.
  • Document standards – Document standards classify the type of information included in a document. In the healthcare sector, this information may be in the form of Subjective, Objective, Assessment, Plan (SOAP) standard, Health Level 7 (HL7) Clinical Document Architecture used for electronic sharing of documents, HL7 continuity of care document, and discharge summary.
  • Conceptual Standards – Conceptual standards ensure that neither the meaning nor context of information is lost during its transmission between systems.
  • Application standards – These standards ensure the implementation of business rules for software systems when systems interact with each other.
  • Architecture standards – These standards define the generic model for health information systems. They guide the planning and designing of new systems by allowing the integration of health information systems.

4.7. HEALTH INFORMATION SYSTEM INTEROPERABILITY
4.7.1. FOUR CHALLENGES TO ATTAINING HEALTHCARE INTEROPERABILITY

True interoperability between HIT businesses, vendors, technology, systems, and healthcare information is one of the substantial requirements when it comes to providing quality care. It is difficult to achieve as it cannot adequately meet the respective goals of operators in the sector.

Interoperability is a serious problem throughout healthcare as different complex processes, clinical standards, as well as vendors, create enormous barriers to the delivery of improved patient experiences along with better patient care outcomes.

Reduced Medicare compensations, rising costs, a shift to value-based care, and intensified pressure to enhance patient experience imply that the entire healthcare industry, including providers, must move toward better healthcare operability. Those creators of information systems, HIT, payers, providers, and other healthcare stakeholders be able to communicate with one another to accomplish an effective or interoperable healthcare system.

Healthcare must address these challenges but there are a number of difficulties that need to be resolved otherwise interoperability in healthcare will continue to remain nothing more than an intellectual talking point.

The following are the four significant challenges that are faced in the healthcare industry:

Lack of Criteria for Sending, Receiving, and Managing Information between Health Systems

Simply sharing or coping information from one healthcare technology or EHR software to another, as furnished by today’s vendors, is extremely difficult. Proprietary formats, mismatched fonts, as well as external data fields, is an indication that data must be manipulated carefully and modified before it can be exported to another system.

The adoption as well as the use of health data standards is the basis for enabling interoperability between EHR systems and across organizations. According to the Office of the National Coordinator (ONC), standards are conventional methods that connect systems, and these standards may pertain to data transport, security, data structure or format, terminology connotations, or code definitions. With standards in place, predictive analytics systems, health information exchanges, and other information exchange efforts can be foundationally established.

Throughout healthcare, several disparate Standards Development Organizations (SDOs) create, update, and even maintain health data standards via collaborative processes involving HIT users but a single, unified standard does not exist. With billions of dollars already spent on EHR implementation, a health system must be able to find efficient ways of connecting fragmented patient data, which is an increasingly consistent effort as the United States transfers from fee-to-services to the value-based healthcare system that focuses primarily on populations and outcomes. There is no interoperability standard whatsoever. This lack of common criteria or standard for capturing, receiving, transmitting, storing, and managing patient data causes significant inaccuracies as well as delays. This is a major obstacle to interoperability efforts.

Blocking of Information by Vendors

A lack of shared data in the healthcare industry is one of the challenges affecting healthcare interoperability. The practice of information blocking by some EHR vendors is a significant impediment that cannot be overlooked. And even if the information is eventually shared, a number of these technology companies end up charging exorbitant fees for transmitting data outside their system.

Without any doubt, such practices are profoundly disruptive to the flow of essential healthcare data. But many vendors continue this practice despite new efforts to end it.

For instance, the executive director of Health IT Now, Joel White, is calling for the publication of any authoritative rule on information blocking, which is required by the 21st Century Cures Act legislation. In an op-ed that was recently published in STAT, the executive director of the coalition of healthcare and technology companies stated that “More than 600 days after the enactment of the Cures Act, not one regulation has been passed or issued on information blocking.”

The ONC for HIT is responsible for publishing the regulation as well as the implementation of specific duties as required under the 21st Century Cures Act that was signed into law in December 2016.

The major components in the legislation include patient access to health data and promoting the interoperability of EHRs while discouraging the blocking of information. The law is presently receiving lots of positive attention due to its potential ability to free up the lanes for genuine data interoperability.

Lack of Uniformity When Identifying Patients

There is presently no consistent way of identifying patients across the healthcare spectrum, a network of providers, or even throughout prominent healthcare systems.

Patients are identified by their names, date of birth, as well as Social Security number. But the issue is that information is stored in different systems in different ways. This implies that patient identification can be subject to a lot of errors.

Numerous patient advocacy groups have asserted that the creation of a national, particularized patient identifier would be a great solution to this problem. The patient identifier, according to the groups, could be designed in a similar manner with the patient’s Social Security number and would be theirs throughout their lifetimes. This identifier will be utilized at any point of care in the course of the patient’s life.

Since the patient identifier will be something akin to a code, it will categorize as well as identify any individual no matter what provider or system is used. But the efforts for moving this impressive campaign forward appears to be locked in a political stalemate.

Advocacy groups such as CHIME and HIMSS, along with several other organizations, have been pushing for a national patient identifier for the past few years. They argue that as the exchange of health data continues to evolve, the need for an accurately consistent way of identifying patient health records is becoming increasingly pressing. As a result, this lack of a uniform patient identification system, which would be recognized nationally, has led to health data exchange inefficiencies, increased healthcare facility costs, and patient safety threats, among other problems.

The introduction of the Health Insurance Portability and Accountability Act (HIPAA) of 1996 called for the creation of the coveted unique patient identifier. Congress overruled this mandate due to patient privacy concerns. An extremely vocal minority retain fears that industry or the Government will utilize patient data in a way that makes privacy even much harder to protect, especially if a patient identifier were to be used.

Nevertheless, without an identifier in place, it will be quite challenging to link heterogeneous data in order to obtain a complete picture of patient healthcare experiences. Therefore, before industry-wide and nationwide interoperability can become a reality, federal agencies need to sit up and prioritize the standardization of every aspect of patient health record exchange.

The Difficulty with Measurement, Analytic Thinking, and Transformation between Healthcare Systems

When healthcare systems do not communicate with each other in purposeful ways, it becomes difficult to readily quantify error rate, costs, and other created issues. Without the ability to track or measure outcomes, health systems, and healthcare organizations will not be able to improve its most crucial processes, and no genuine interoperability can be achieved.

The challenge confronting providers, their payers, and vendor partners is the lack of a regularized way to measure or evaluate the impact of interoperability failure and delays. As soon as providers can accurately measure issues throughout the entire healthcare chain, they will be able to analyze problem areas and make necessary changes. They will also be in the best position to keep tabs on how these changes can raise the quality of care as well as patient outcomes.

Data analytics is quickly becoming one of the most challenging undertakings in the healthcare industry today. Some providers are not yet conversant with the management and operation of their EHRs. However, they are asked to obtain critical insights from the clinical data right within the technology.

For organizations that can successfully integrate data-driven insights and bring them into their operational and clinical processes, the rewards – such as lower costs, visibility performance, potentially healthier patients, and higher patient and staff satisfaction – are astonishingly abundant.

4.7.2. HOW TO SIMPLIFY INTEROPERABILITY IN HEALTHCARE

Choosing Appropriate Health Information Technologies

One of the best ways to simplify interoperability in healthcare is to select the best technology that helps to channel multiple data sources onto an amalgamated platform. Some healthcare organizations that stick to the use of outdated or inefficient technologies for integrating data will find it incredibly difficult to make the transition.

This is because their technology interface may not be compatible with innovative or up-to-date cloud technologies. Also, they may notice that their outdated system does not support modern data formats. These are everyday issues that require advanced and reliable solutions such as the proven API solution from Integrate, which provides turnkey or ready-to-use integration across EHRs.

Enhancing EHR Integration for Greater Point-of-care Solutions

One of the most crucial use cases in healthcare interoperability is EHR integration. HIT solutions will be highly effective if they can be promptly delivered to clinicians that use the EHR at the point of care. Interoperability eliminates the need for clinicians to work with different interfaces in order to obtain the data they need.

According to health IT specialists, doctors are far more likely to alter or increase their treatment protocols as long as they are provided with applicable substantiating data at the point of care instead of the usual practice of receiving the same data in a process improvement group meeting.

More Extensive Adoption of Data Standards

A GAO (Government Accountability Office) report on healthcare interoperability has stated that, though the standards for the digital exchange of data exist between EHR systems, they are grossly inadequate and cannot be relied on to achieve genuine interoperability.

HL7 has gained comprehensive adoption, yet there is an indication that shows there is significant discrepancy when it comes to how these standards are carried out. FHIR (fast healthcare interoperability resources) is a newer specification that was developed by HL7 and has proven to make a few strides. Yet, experts notice that it still shares some of the same concerns existing with the HL7 standards. Vendors, for instance, may not utilize the complete APIs or all FHIR APIs. Both scenarios forbid true interoperability.

The key to simplifying healthcare information or data Interoperability is a much broader appropriation of data standards. A considerable number of vendors and healthcare organizations continue to work within outdated concepts of data ownership instead of sharing patient information. A few innovative or forward-thinking organizations are more than ready to share healthcare data, but they don’t have the capabilities to do so. The primary goal is to go from isolated data and take part in the industrial process of establishing an interoperable healthcare ecosystem. The draft rule published recently by ONC & CMS that encourage FHIR and promote the free flow of clinical data is a considerable step in the right direction.

4.8. OUTCOMES

The application of interoperability in healthcare information across different organizations and levels reaps many benefits including:

4.8.1. IMPROVEMENT OF RISK MANAGEMENT

Proper application of interoperability in healthcare information results in a reduction of patient risks, improvement in patient safety and better patient management outcomes. With interoperability between systems, the aggregation, analysis, and communication of patient information become more efficient. Interoperability enables evidence-based decision-making by healthcare providers while preventing the occurrence of adverse events.

4.8.2. IMPROVEMENT OF PATIENT HEALTH OUTCOMES AND QUALITY PATIENT CARE

Healthcare providers who take advantage of the interoperability feature of electronic health information and access the health information of the entire population of patients their organization has can evaluate the needs of their patients more meaningfully, according to the specific health problems they face. Providers can also formulate preventive measures for public health issues. By using standardized EHRs, they can better manage patients and specific risk factors for more desirable patient outcomes.

4.9. CITATIONS

  1. OpenClinical (2013b). Interoperability in health information systems. Retrieved from http://www.openclinical.org/interoperability.html
  2. Ibid.
  3. Tripathi, M. (2015). EHR Evolution: Policy and Legislation Forces Changing the EHR. Retrieved from http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_049747.hcsp?dDocName=bok1_049747
  4. Ibid.
  5. Ibid.
  6. Ibid.
  7. Ibid.
  8. Kubicek, H., & Cimander, R. (2011). Layers of Interoperability. In Organizational interoperability in e-government lessons from 77 European good-practice cases (pp. 85-96). Berlin: Springer.
  9. Fridsma, D. (2012, April 20). Model-driven health tools support EHR interoperability. HealthITBuzz. Retrieved from http://www.healthit.gov/buzz-blog/ehr-case-studies/model-driven-health-tools-mdht/
  10. HealthIT.gov. (2013). What is EHR Interoperability and Why is it Important? Retrieved from https://www.healthit.gov/faq/what-ehr-interoperability-and-why-it-important
  11. AdvaMed, American Health Information Management Association (AHIMA), & American Medical Informatics Association (AMIA) (n.d.). Summary of Joint Position on Adoption of ICD-10. Retrieved from https://www.amia.org/sites/default/files/files_2/icd-10-jointstatement.pdf.
  12. AHIMA (2005). Implementation of SNOMED-CT Needed to Facilitate Interoperable Exchange of Health Information. Journal of AHIMA 76, no.9 (October 2005): 30, 32. Retrieved from http://library.ahima.org/doc?oid=58508#.XTn-t02os54
  13. HealthIT.gov. (2019). Standards Collaboration. Retrieved from https://www.healthit.gov/topic/interoperability/standards-collaboration
  14. Ibid.
  15. HealthIT.gov. (2019). Improved Diagnostics & Patient Outcomes. Retrieved from https://www.healthit.gov/topic/health-it-and-health-information-exchange-basics/improved-diagnostics-patient-outcomes