SMART on FHIR: a standards-based, interoperable apps platform for electronic health records

By Joshua C. Mandel, David A. Kreda, Kenneth D. Mandl, Isaac S. Kohane, Rachel Badovinac Ramoni. J. Am. Medical Informatics Assoc., 2016

715 citations recorded by the source corpus.

Objective In early 2010, Harvard Medical School and Boston Children’s Hospital began an interoperability project with the distinctive goal of developing a platform to enable medical applications to be written once and run unmodified across different healthcare IT systems. The project was called Substitutable Medical Applications and Reusable Technologies (SMART). Methods We adopted contemporary web standards for application programming interface transport, authorization, and user interface, and standard medical terminologies for coded data. In our initial design, we created our own openly licensed clinical data models to enforce consistency and simplicity. During the second half of 2013, we updated SMART to take advantage of the clinical data models and the application-programming interface described in a new, openly licensed Health Level Seven draft standard called Fast Health Interoperability Resources (FHIR). Signaling our adoption of the emerging FHIR standard, we called the new platform SMART on FHIR. Results We introduced the SMART on FHIR platform with a demonstration that included several commercial healthcare IT vendors and app developers showcasing prototypes at the Health Information Management Systems Society conference in February 2014. This established the feasibility of SMART on FHIR, while highlighting the need for commonly accepted pragmatic constraints on the base FHIR specification. Conclusion In this paper, we describe the creation of SMART on FHIR, relate the experience of the vendors and developers who built SMART on FHIR prototypes, and discuss some challenges in going from early industry prototyping to industry-wide production use.

Subfields: General Health Professions, Health Information Management, Surgery

View Paper: https://www.semanticscholar.org/paper/4744fe3b6182274f29f608cb6c820dd2a3be926a

How researchers see this paper

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In Health Information Management

1. Timothy Miller
2. Dianbo Liu
3. Kenneth D. Mandl

In Surgery

1. Timothy Miller
2. Dianbo Liu

Citations in the corpus

• Key challenges for delivering clinical impact with artificial intelligence (2019, positive): “Adoption of unified data formats, such as Fast Healthcare Interoperability Resources [84], offer the potential for better aggregation of data, although improved interoperability does not necessarily fix the problem of inconsistent semantic coding in EHR data [85].”
• Blockchain Technology for Healthcare: Facilitating the Transition to Patient-Driven Interoperability (2018, background): “Clinical data standards like Fast Healthcare Interoperability Resources (FHIR), as well as practical implementation consortiums like the Argonaut project, will further reduce barriers to data exchange [29].”
• Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective (2020, background): “If EHR reminded clinicians that a patient may miss their follow-up, measures can be taken such as offering a virtual appointment, engage in suitable local community support services which offer support with transport and other social services.”
• Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020, background): “Standards and initiatives that seek to consolidate the best practices and provide a complete set of medical information for patients are being implemented [248]–[250].”
• FADL: Federated-Autonomous Deep Learning for Distributed Electronic Health Record (2018, background): “However, healthcare data transfers are complex because of strict regulations and sensitivity of the data [15].”