Semantic Integration of Patient Data and Quality Indicators based on openEHR Archetypes

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  • 1. Semantic  Integration  of  Patient  Data  and  Quality   Indicators  based  on   openEHR  Archetypes Kathrin Dentler, Annette ten Teije, Ronald Cornet and Nicolette de Keizer 1  /  25
  • 2. Patient  Data   valuable,  but  semantic  gaps meaning-based integration required => archetypes! 2  /  25
  • 3. Quality  Indicators •  Should be well-formalised: executable, sharable & comparable results •  CLIF •  Research question: archetypes? 3  /  25
  • 4. Outline 1)  CLIF2)  Archetypes3)  Formalisation of indicator4)  “Archetyped” patient data5)  Case study & Lessons learned6)  Conclusions & Future work 4  /  25
  • 5. Background:  CLIF  –  Clinical  Indicator  Formalisation  Method •  Formalised indicator = query / queries •  Required: standard terminology for patient data 5  /  25
  • 6. 8  Steps  of  CLIF 1)  Encode relevant concepts in terms of a terminology2)  Define the information model <= standard3)  Formalise temporal constraints4)  Formalise numeric constraints5)  Formalise Boolean constraints6)  Group constraints by Boolean connectors7)  Formalise in- and exclusion criteria8)  Construct the denominator 6  /  25
  • 7. 2-­‐‑level  Methodology:  Reference   Model  and  Archetypes 7  /  25
  • 8. Diagnosis  Archetype 8  /  25
  • 9. Procedure  Archetype 9  /  25
  • 10. Tumour-­‐‑Lymph  node  metastases   Archetype 10  /  25
  • 11. Datatypes 11  /  25
  • 12. Introducing  Archetypes •  Computable specifications of clinical concepts.•  Constraints (e.g. occurrence, cardinality) & ontological definitions.•  Used to record, exchange and integrate patient data.•  openEHR archetypes: enthusiastic expert community; publicly available. 12  /  25
  • 13. Advantages  of  Archetypes     with  respect  to  Indicators 1)  Sharable, defined queries2)  Knowledge-level3)  Reality check 13  /  25
  • 14. Sample  Quality  Indicator Numerator: Number ofpatients who had 10 ormore lymph nodesexamined after resectionof a primary coloncarcinoma.Denominator: Number ofpatients who had lymphnodes examined afterresection of a primarycolon carcinoma.- Exclusion criteria: Previous Reasons  for  this  indicator:  Evidence-­‐‑based  radiotherapy and recurrent (correct  staging  leads  to  beYer  outcome),  colon carcinomas requires  data  from  several  sources 14  /  25
  • 15. Modelling  Quality  Indicators  in  terms  of  openEHR  Archetypes   1)  Terminology <=> information model binding: diagnosis codes <=> node “Diagnosis” of the archetype “Diagnosis” procedure codes <=> node “Procedure” of the archetype “Procedure undertaken”2)  Inter-archetype relations between bound concepts.=> Bindings and relations are the backbone ofindicators (concept-level); used to build queries. 15  /  25
  • 16. Sample  Query Patients with “Primary malignant neoplasm of colon”:SELECT DISTINCT ?patient WHERE { ?patient a patient:at0000.1_Patient . ?patient schemarm:links ?diagnosis . ?diagnosis a diagnosis:at0000.1_Diagnosis . ?diagnosis schemarm:value_element ?diagcode. ?diagcode a diagnosis:at0002.1_Diagnosis . ?diagcode a sct:SCT_93761005 .} ORDER BY ?patient 16  /  25
  • 17. Patient  Data DWH   Entities Codes Mapped  To Patient 1,672,104 Diagnosis 2,925,156 ICD-­‐‑9-­‐‑CM   SNOMED  CT   (ca.  50%) (via  crossmap) Operation 144,860 Dutch   SNOMED  CT   classification   (manually,  subset) Admission 259,005 Pathology   92,870 -­‐‑  (Dutch  free  text)   Reports •  DSCA  dataset:  e.g.  radiotherapy  &  number  of  examined  lymph   nodes.   •  Matched  based  on  based  on  sex,  year  of  birth,  operation,   discharge  date  and  procedures  =>  192/229  patients.   17  /  25
  • 18. Mapping  between  local  Data   Structure  and  Archetypes   Table Column Archetype Node Patient Identifier   Patient   Name   Admission   Admission  Date   Patient  Admission   Admission  Date   Discharge  Date   Discharge  Date Diagnosis   Code Diagnosis   Diagnosis   Operation   Code Procedure  undertaken   Procedure   DSCA Radiotherapy   Procedure  undertaken   Procedure:   fixed  SCT  code Multidisciplinary   Procedure  undertaken   Procedure:   meeting   fixed  SCT  code Pathology Procedure  undertaken   Procedure:   fixed  SCT  code Number  of  exam.   Tumour-­‐‑  Lymph  node   Number  of  nodes   lymph  nodes metastases   examined   18  /  25
  • 19. Archetypes  &     Patient  Data  in  OWL  2 •  Re-used archetype ontologizer.•  Transformed patient data into OWL based on mapping.•  Loaded closure of SNOMED CT, archetypes & patient data into OWLIM-SE 5.0 19  /  25
  • 20. Sample  Patient  Graph ihtsdo:SCT_50774009 procedure:at0002_Procedure ihtsdo:SCT_284427004 type type exactly_1 type type data:SCT_50774009 procedure:at0000_Procedure_undertaken data:SCT_284427004 rm:DV_DATE_TIME value_element type type value_element type type data:procedureTime_132_50774009 data:examinationTime_132 time timedata:procedure_132_50774009 hasTime hasTime data:lymphnodeexamination_132 2010_05_26T00:00:00 2010_05_27T00:00:00 links links links links data:patient132 linksdata:diagnosis_132_93761005 type 12 data:metastases_132 type value_element patient:at0000.1_Patient hasNumber itemsdiagnosis:at0000.1_Diagnosis data:SCT_93761005 data:nodeNumber_132 type type type exactly_1 type ln_metastases:at0001_Number_of_nodes_examined ihtsdo:SCT_93761005 max_1diagnosis:at0002.1_Diagnosis ln_metastases:at0000_Tumour-_Lymph_node_metastases 20  /  25
  • 21. Proof  of  Concept:     Calculating  the  Indicators Indicator  /   Our  Result   DSCA   Publicly  Reported   Results   Lymph  nodes   85,71%  (42/49)   80,00%  (43/54)   -­‐‑ Meeting   91,66%  (22/24)   100%  (21/21)   -­‐‑ Re-­‐‑operation   1,66%  (1/60)   9%  (7/75)   8,33%  (20/240)   One  of  the  problems  (meeting  indicator):   DSCA:  Colon  sigmoideum  <=>  DWH:  “Malignant  neoplasm  of  rectosigmoid  junction”  mapped  to  both  colon  and  rectum  via  crossmap…   21  /  25
  • 22. Lessons  Learned  from  Case  Study •  High coverage of Clinical Knowledge Manager; extending an archetype straightforward•  Intuitive mapping/modelling at knowledge-level•  Archetype Ontologizer useful, OWL easy to work with•  Minor difficulties with datatypes; inter-archetype relationships?•  High data quality required for re-use; problem- oriented patient model•  UMLS mapping better 22  /  25
  • 23. Conclusions •  Archetypes are suitable to bridge the gap between clinical quality indicators and patient data. 23  /  25
  • 24. Future  Work •  Effect of data quality on reliability/validity of indicator results•  Sharable queries: Who wants to run these or other indicators on his/her archetyped data?•  New opportunities for automated reasoning at: •  patient-data level (infer implicit knowledge; validate data based on archetypes; data-driven, bottom-up data entry), •  archetype-level (infer subsumption and equivalence relationships between archetypes) and on the •  boundary between both: detect semantically equivalent constructs!•  And: More bindings required => next presentation! 24  /  25
  • 25. Questions? k.dentler@vu.nl  -­‐‑  hYp://www.few.vu.nl/  ̃kdr250/archetypes/   25  /  25