HIM 500 Module 4 Standards Short Paper Example

Arriving but Not Understood: Interoperability Standards and Transfer Records at Bramble Bay Medical Center

[Student Name]

Southern New Hampshire University

HIM 500: Healthcare Informatics

Module Four Short Paper

[Instructor Name]

[Date]

The organization, setting and figures below are a composite written as a model document. No real employer, client, colleague or patient is described.

Arriving but Not Understood: Interoperability Standards and Transfer Records at Bramble Bay Medical Center

Bramble Bay Medical Center accepts about 140 transfer patients a month from six regional hospitals. For four of them, no electronic records arrive at all; staff wait for faxes. For the other two, a summary document arrives through the exchange, but its laboratory results appear as text that cannot be graphed beside Bramble Bay's own results, and medications do not reconcile automatically. The hospital's problem is not only whether data arrive but whether they arrive in a form its systems and clinicians can understand. This paper uses that problem to explain the main interoperability standards and recommend a path forward.

Two Kinds of Interoperability

It helps to separate two layers. The first is moving data: a transport and format that let one system send and another receive. The second is meaning: codes and structures that let the receiving system know that a value is a potassium result in millimoles per liter, not just a number next to a label. Bramble Bay's two connected neighbors achieve the first layer but only part of the second. Standards exist for both, and most failures in practice come from partial use of them.

Terminology: Making Data Mean the Same Thing

Terminology standards give each concept a shared code. LOINC identifies laboratory tests and clinical observations, SNOMED CT identifies clinical findings, problems and procedures and RxNorm identifies medications at the level of ingredient, strength and form. McDonald et al. (2003) described how LOINC was built to replace the local codes that each laboratory invented, which made results from different sources impossible to combine automatically. Bodenreider et al. (2018) reviewed recent development of SNOMED CT, LOINC and RxNorm and noted their growing role in national data requirements, along with the ongoing work needed to keep mappings current.

A small audit illustrates the issue. Of the 60 most common laboratory tests in documents received from the two connected hospitals, 49 carried a LOINC code and 11 carried only local codes, so those 11 results, including a troponin assay, could not be matched to Bramble Bay's own tests. Asking the sending hospitals to map those codes would fix more than any new software.

Messaging and Documents

Two older standards still carry most clinical data. HL7 version 2 messages move events such as admissions, orders and results between systems inside and between organizations, usually in real time, and nearly every hospital laboratory interface uses them. Consolidated Clinical Document Architecture, or C-CDA, packages a patient's summary into a structured document with sections for problems, medications, allergies and results. Documents are well suited to transitions of care, but they arrive as a bundle; a receiving system must parse each section, and when coded values are missing, information falls back to text, as Bramble Bay has seen.

FHIR Interfaces

HL7 FHIR takes a different approach. Instead of sending whole documents, it defines small units called resources, such as Patient, Condition, Observation and MedicationRequest, that a system can request individually through web interfaces. Mandel et al. (2016) showed how the SMART on FHIR platform adds standard authorization and application launch on top of FHIR, allowing one application to run across many record systems. Ayaz et al. (2021) reviewed FHIR implementations and found broad and growing use in patient access, clinical decision support and research, along with challenges such as inconsistent implementation, security and the need for profiles that constrain how resources are used. In the United States, the US Core profiles define how resources should carry the federal core data set, which reduces that inconsistency.

Federal Data Sets and National Exchange

Two federal efforts shape Bramble Bay's options. The United States Core Data for Interoperability defines the data classes, such as problems, medications, laboratory results and clinical notes, that certified systems must be able to exchange using specified standards. National trusted exchange, the federal framework and agreement that took effect in recent years, connects networks through designated qualified networks so that a hospital joining one can query records held by participants in others. Joining would let Bramble Bay request records from all six regional hospitals, not only the two on its current exchange. Holmgren and Adler-Milstein (2017) painted a national picture in which full engagement across locating, sending, receiving and integrating outside information was uncommon, and integration, the step Bramble Bay struggles with, lagged the rest.

Comparing the Options

Table 1 compares the standards Bramble Bay uses or could use for transfer records.

Table 1. Standards for Transfer Records Compared

Note. Assessment by the author based on Bramble Bay's exchange review.

A Standards Roadmap

The recommended roadmap has three steps. First, join a qualified network under national trusted exchange so that records from all six hospitals can be queried, with a target of outside records available for 80% of transfers within six months. Second, work with the two connected hospitals to map the remaining local laboratory codes to LOINC, and configure Bramble Bay's system to import coded results into flowsheets. Third, pilot FHIR-based retrieval of problems, medications and recent results for transfer patients as neighbors enable their interfaces, measuring how often clinicians reconcile outside medications electronically rather than by hand.

Conclusion

Bramble Bay's transfer problem shows that interoperability depends on both moving data and sharing meaning. Terminology standards give data meaning, messaging and documents move them and FHIR interfaces allow precise retrieval, while federal data sets and national exchange widen the network. Using the standards fully, not partially, is the hospital's most direct route to transfer records that clinicians can use.

References

Ayaz, M., Pasha, M. F., Alzahrani, M. Y., Budiarto, R., & Stiawan, D. (2021). The Fast Health Interoperability Resources (FHIR) standard: Systematic literature review of implementations, applications, challenges and opportunities. JMIR Medical Informatics, 9(7), Article e21929. https://doi.org/10.2196/21929

Bodenreider, O., Cornet, R., & Vreeman, D. J. (2018). Recent developments in clinical terminologies: SNOMED CT, LOINC, and RxNorm. Yearbook of Medical Informatics, 27(1), 129-139. https://doi.org/10.1055/s-0038-1667077

Holmgren, A. J., & Adler-Milstein, J. (2017). Health information exchange in US hospitals: The current landscape and a path to improved information sharing. Journal of Hospital Medicine, 12(3), 193-198. https://doi.org/10.12788/jhm.2704

Mandel, J. C., Kreda, D. A., Mandl, K. D., Kohane, I. S., & Ramoni, R. B. (2016). SMART on FHIR: A standards-based, interoperable apps platform for electronic health records. Journal of the American Medical Informatics Association, 23(5), 899-908. https://doi.org/10.1093/jamia/ocv189

McDonald, C. J., Huff, S. M., Suico, J. G., Hill, G., Leavelle, D., Aller, R., Forrey, A., Mercer, K., DeMoor, G., Hook, J., Williams, W., Case, J., & Maloney, P. (2003). LOINC, a universal standard for identifying laboratory observations: A 5-year update. Clinical Chemistry, 49(4), 624-633. https://doi.org/10.1373/49.4.624