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Efficient Remediation of Terms Inactivated by Dictionary Updates

Efficient Remediation of Terms Inactivated by Dictionary Updates. AMIA Symposium – November 8, 2017. Benjamin J. Gross, MD, MMSc, 1 David H. Dubois, MBA, PMP, 2 Mark H. Twelves MSW, LICSW, 2 Roberto A. Rocha, MD, PhD 2,3,4 1 InterSystems Corporation

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Efficient Remediation of Terms Inactivated by Dictionary Updates

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  1. Efficient Remediation of Terms Inactivated by Dictionary Updates AMIA Symposium – November 8, 2017 Benjamin J. Gross, MD, MMSc,1 David H. Dubois, MBA, PMP,2 Mark H. Twelves MSW, LICSW,2 Roberto A. Rocha, MD, PhD2,3,4 1InterSystems Corporation 2Clinical Informatics, Partners eCare, Partners Healthcare System3Brigham and Women’s Hospital 4Harvard Medical School, Boston, MA

  2. Abstract • Ongoing maintenance of a diagnosis dictionary in an electronic health record includes replacing inactivated terms with clinically equivalent terms in configuration and data records • Partners Healthcare has developed an efficient process that relies on • Detailed reports to suggest active replacement terms • Clinical review by subject matter experts • Replacements which are made manually or with the help of system tools • Learning Objectives: • Recognize dependencies of terms inactivated by dictionary updates • Formulate an approach towards remediation

  3. Background • Partners Healthcare System (PHS) • Commercial EHR • Third party diagnosis dictionary • 800,000+ clinical terms • Mapped to ICD-10-CM codes, SNOMED CT concepts • Hundreds of terms inactivated with each periodic update + PHS customization

  4. Implications of inactivating terms • Providers can usually find desired terms despite inactivations thanks to significant redundancy • After >2 years, 7% of terms accounted for 99% of usage • However, certain inactivated terms must be replaced with active terms: • Terms with “configuration dependencies” – linked to other system elements • Terms with “process dependencies” – appear in patients’ records and can be used downstream

  5. Diagnosis terms with dependencies • Configuration dependencies • Examples: questions on a form, triggers for decision support • Inactive terms cause runtime errors and functionality gaps • Terms must be replaced in advance • Process dependencies • Examples: patient’s problems, future orders • Inactive terms hinder workflows, especially billing • Providers may make replacements themselves • EHR system offers alternative terms when available • Replacing terms in advance reduces workflow interruptions and saves providers time

  6. Finding appropriate replacement terms • Mapping requires clinical expertise and each replacement requires approval • To improve efficiency, PHS developed reports to suggest multiple options for each inactivated term • Number of suggested terms for each inactive term (recent update) • Suggestions ranked by likelihood of semantic equivalence • Terminology engineers select a single optimal replacement term • Clinical subject matter experts review proposed replacements

  7. Suggestion reports • Criteria for suggesting alternative terms

  8. Configuration dependency – ProtocolChemical conjunctivitisICD-10-CM: H10.219 Acute toxic conjunctivitis, unspecified eyeSNOMED CT: 415733008 Toxic conjunctivitis (disorder)

  9. Configuration dependency – Preference listHigh myopia, bilateralICD-10-CM: H52.13 Myopia, bilateralSNOMED CT: 34187009 Severe myopia (disorder)

  10. Process dependency – Future orderDry eye syndrome, bilateralICD-10-CM: H04.123 Dry eye syndrome of bilateral lacrimal glandsSNOMED CT: 346221000119103 Tear film insufficiency of bilateral eyes (disorder) 46152009 Tear film insufficiency (disorder)

  11. Process dependency – Future orderHepatic cirrhosis, unspecified hepatic cirrhosis typeICD-10-CM: K74.60 Unspecified cirrhosis of liverSNOMED CT: 19943007 Cirrhosis of liver (disorder)

  12. Results of recent updates

  13. Effort required • Initial report design and development • 1 x Clinical Informatician (report design) • 1 x Software Engineer (report development) • Single dictionary update (x4/year): • Approximately 75 hours • 12-13 people with complementary roles and expertise • 1 x Terminology Team Lead (project management) • 1 x Clinical Informatician (project management) • 1 x Software Engineer (report delivery) • 2-3 x Terminology Engineers (selection of optimal replacement terms) • 6 x Clinical Subject Matter Experts (review of proposed replacements) • 1 x Application Coordinator (implementation)

  14. Summary This is the PHS approach for replacing terms inactivated by periodic updates of the diagnosis dictionary • Terms with “configuration dependencies” – to avoid runtime errors and functionality gaps • Terms with “process dependencies” – to reduce workflow interruptions and save providers time

  15. Conclusions • Just one example of overall effort to maintain system configuration and data integrity • Costs and expertise required may be the “Achilles heel” of complex EHR systems • EHR vendor offers few tools for knowledge management • Data integrity is only one consideration of content vendors. Others include term availability, term “friendliness”, matching multiple terminologies simultaneously • Responsibilities split between EHR vendor (search) and content vendor (content), and available solutions are limited to single domains (diagnoses, meds, procedures) • PHS has large quantities of configured content and patient data to consider • PHS has dedicated resources for knowledge management and necessary expertise. Not available at every institution

  16. Thank you Ben Gross, MD, MMSc grossdoc@gmail.com

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