Graham Pegler.  National ED Termset for Presenting Problem and Diagnosis  NEHTA announces SNOMED CT for the Electronic Health Record  FirstNet module.

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Presentation transcript:

Graham Pegler

 National ED Termset for Presenting Problem and Diagnosis  NEHTA announces SNOMED CT for the Electronic Health Record  FirstNet module for the NSW EMR ◦ Rapid development / implementation  Intensive workshops and quick turnarounds 2

Recording a diagnosis ED across NSW Health were reporting ICD10/ICD9 and local values No “coders” available in ED SNOMED CT – an opportunity No knowledge of coding needed at the point of capture Was provided as part of the Cerner EMR package Component for implementation of Electronic Discharge Summaries SNOMED CT - adopted for capturing patient diagnosis in an ED No review of SNOMED CT, no real knowledge of SNOMED CT in the development team, short timeframes THIS IS A STORY OF A JOURNEY 3

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Starting position observations: - Clinicians access to SNOMED CT unrestricted - any term in SNOMED CT: Terms: ~1,000,000; Concepts: ~ 300, including non-human, including organisms, path tests, …. - Steps taken: - Configuration of the user interface - Default search operation “Begins with” - Supports a “favourites” list that can be tailored to site/ clinician - Favourites can only be set up and maintained by manual entry - Requires to commence search - Training of users - in SNOMED CT - Search function and usability - Setting favourites 5

FirstNet live Issues raised – a call for help / advice on SNOMED CT Diagnosis data is rubbish! Inability to analyse it Analysis of the situation Understanding the constraints of the system - meeting with implementers/ developers Looking at the data – through the HIE data warehouse Meeting with clinicians, users 6

Analysis Short term goals - How to work within the existing capabilities to improve outcomes Long term goals - Depending on success of above, what further change can be introduced to improve acceptance 7

Getting to know SNOMED CT Configuration Developing a recommended set of favourites Building a data base of SNOMED CT to understand it Using tools – eg CliniClue Search defaults Restrictions leveraging off existing favourites harvesting commonly used terms 8

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Development of a more limited set - Developed from an initial list from one ED Director - harvesting of appropriate commonly selected items from all EDs - seeking to incorporate items in the NSW Set not (yet) in the National ED Termset - adding items to SNOMED CT-Au 14

Feedback processes Compliance Profiles Issuing a NSW ED Termset for favourites – but no compliance enforcement mechanism Further issues Management of FirstNet implementations and control of set up (Does not reset back to defaults) Packaging of SNOMED CT releases - International vs Australian 15

Frequency of specific diagnosis by a hospital (A202) by month - July 934 different diagnosis codes reported in one month 2534 cases assigned a diagnosis - very specific diagnoses (rich data), some “bad” data Abdominal pain (finding) Chest pain (finding) Viral disease (disorder) Pneumonia (disorder) Gastroenteritis (disorder) Backache (finding) Asthma (disorder) Urinary tract infectious disease (disorder) Vomiting (disorder) Croup (disorder) Bronchiolitis (disorder) Dyspnea (finding) Acute gastroenteritis (disorder) Fracture of bone (disorder) Chronic obstructive lung disease (disorder)22

COMPLIANCE PROFILES Analysis 17

FirstNet review SNOMED CT Ref Set – trial of the EDRS ED Activity –based funding based on URG - issues for data analysts 18

Success or failure? Survival - Based on goodwill/professionalism of clinicians, notwithstanding resistance - the promise of … discharge summaries, PC EHR Training & Support – not just at the user interface User interface design Informatics is not just IT 19