Optimal Interoperability Requires More Than You Think

Optimal interoperability requires more than you think

Ken Redekop, PhD Erasmus School of Health Policy and Management Erasmus University Rotterdam Rotterdam, The Netherlands

Introduction

Discussion about interoperability often focuses on addressing software and hardware challenges. It may also focus on the organisational and legal challenges that need to be faced.

1 Ultimate goal of interoperability?

Levels of interoperability

Ref: Tolk, Syst Cybernet 2007

2 Semantic interoperability

Medical terminologies, nomenclatures, ontologies. Requires structured data (e.g., a commonly understood data model) and codification of the data (e.g., value sets, vocabularies, etc.). However, more is needed to achieve semantic interoperability. Also required: a common understanding of the clinical procedures and medical guidelines. One example of an approach for this: SNOMED CT

Link: http://www.healthcareimc.com/main/ the-rising-importance-of-organizational-interoperability

SNOMED CT (Clinical Terms) – what is it? A systematically organized computer processable collection of medical terms providing codes, terms, synonyms and definitions used in clinical documentation and reporting. The “most comprehensive, multilingual clinical healthcare terminology in the world” (Wikipedia, 2019). Can manage different languages and dialects. Currently available in American English, British English, Spanish, Danish and Swedish. Cross maps to other terminologies such as: ICD-9-CM, ICD- 10, ICD-O-3, ICD-10-AM, Laboratory LOINC and OPCS-4. Used with the WHO as the basis for the upcoming ICD-11. Supports ANSI, DICOM, HL7, and ISO standards.

Ref: Wikipedia, 2019 - “SNOMED CT”

3 SNOMED CT statistics

Ref: Wikipedia, 2019 - “SNOMED CT”

SNOMED CT – blood pressure codes

Source: http://bioportal.bioontology.org/ontologies/SNOMEDCT

4 An alternative depiction of the goal? TIME

“SPACE” (Country, Centre, Hospital, Etc.) “DATA”

What about all the rich data in free text?

Much data is found in free-text format Why not use natural language processing to transform it into a more useable format? A very promising AI application Offers both benefits and risks These can be likened to the success and failures in the use of AI in image processing.

5 Artificial intelligence – an example of the benefits

Artificial intelligence – an example of the risks

6 Major obstacle to optimaI interoperability?

Even if NLP and other techniques manage to work perfectly, we’ve still got a problem. A “GiGo” problem What if data entering the system are not good? - patient self-reporting of symptoms - poor documentation of medication use And what about missing values?

Ultimate goal of interoperability?

Can techniques like TIME AI compensate for poor-quality or missing data? QUALITY “DATA”

“SPACE” (Country, Centre, Hospital, Etc.)

7 Is birectional interoperability another goal?

Bidirectional interoperability is needed

Essential for many treatment recommendations E.g., ‘personalised’ lifestyle advice requires not just knowledge about the person’s ‘profile’ but also the context (culture, country, etc.) PREVENTOMICS: EU-funded study that will provide “personalised plans for nutrition and lifestyle habits to improve health outcomes based on individual traits (such as lifestyle, genotype, preferences) using biological and psychological mechanisms. See PREVENTOMICS.EU

8 17 Source: PREVENTOMICS, H2020 Coordination Day, 6-6-2019, Brussels

Conclusions

Interoperability is extremely valuable (individual patient care, research purposes, education). Many, many challenges need to be addressed. Major challenge = semantic interoperability. Another = dealing with many ‘real-world’ data issues (incorrect values, no values, etc.) Bidirectional interoperability is invaluable.