How does the mapped ICD data in an EHR system compare to the hospital DAD data in Alberta, Canada?
Uloženo v:
| Název: | How does the mapped ICD data in an EHR system compare to the hospital DAD data in Alberta, Canada? |
|---|---|
| Autoři: | Sandhu N; Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Cal Wenzal Precision Health Building, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4Z6, Canada. namneet.sandhu@ucalgary.ca.; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. namneet.sandhu@ucalgary.ca., Onos D; Health Information Management, Alberta Health Services, Alberta, Canada., Li B; Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Cal Wenzal Precision Health Building, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4Z6, Canada.; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; Alberta Health Services, Alberta, Canada.; Alberta Strategy for Patient Oriented Research Support Unit Data Platform, Alberta, Canada.; Provincial Research Data Services, Alberta, Canada., Southern DA; Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Cal Wenzal Precision Health Building, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4Z6, Canada.; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada., Bakal JA; Alberta Health Services, Alberta, Canada.; Alberta Strategy for Patient Oriented Research Support Unit Data Platform, Alberta, Canada.; Provincial Research Data Services, Alberta, Canada., Shaheen AA; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada., Tower G; Health Information Management, Alberta Health Services, Alberta, Canada., Addison K; Health Information Management, Alberta Health Services, Alberta, Canada., Whittle S; Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Cal Wenzal Precision Health Building, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4Z6, Canada.; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada., Quan H; Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Cal Wenzal Precision Health Building, 3280 Hospital Drive NW, Calgary, Alberta, T2N 4Z6, Canada.; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. |
| Zdroj: | BMC health services research [BMC Health Serv Res] 2025 Nov 25; Vol. 25 (1), pp. 1523. Date of Electronic Publication: 2025 Nov 25. |
| Způsob vydávání: | Journal Article; Comparative Study |
| Jazyk: | English |
| Informace o časopise: | Publisher: BioMed Central Country of Publication: England NLM ID: 101088677 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6963 (Electronic) Linking ISSN: 14726963 NLM ISO Abbreviation: BMC Health Serv Res Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: London : BioMed Central, [2001- |
| Výrazy ze slovníku MeSH: | International Classification of Diseases* , Electronic Health Records*/statistics & numerical data , Clinical Coding* , Patient Discharge*/statistics & numerical data, Alberta ; Humans ; Retrospective Studies ; Databases, Factual |
| Abstrakt: | Competing Interests: Declarations. Ethics approval and consent to participate: This study (REB23-1186) was approved by the Conjoint Health Research Ethics Board (CHREB) at the University of Calgary and Alberta Health Services prior to accessing and analysing the data. Informed consent was waived by the CHREB in the Ethics approval and consent to participate. Consent for publication: Informed consent was waived by the CHREB for conducting and publishing this research study. Competing interests: The authors declare no competing interests. Background and Objective: Coding by human coders is burdensome to healthcare systems requiring advanced computerized techniques. Epic has collaborated with Intelligent Medical Objects (IMO) solution to integrate a solution where the clinical interface terminology is mapped to the International Classification of Diseases (ICD). This study assesses the agreement between the solution mapped ICD-10-CA codes in Alberta, Canada's EHR system (based on Epic) to the human coded ICD-10-CA codes in hospital Discharge Abstract Database (DAD). Design and Setting: In this retrospective analysis conducted in Alberta, Canada, we linked records in the acute care hospital DAD with the province wide EHR system for admissions between April 2021 and March 2024. Main Outcome(s) and Measure(s): The primary outcome was the level of agreement between the solution mapped ICD-10-CA codes from the 'hospital problem list' in the EHR and hospital DAD data. The analysis was conducted at 3-digit and 4-digit ICD code level for main diagnosis and any diagnosis, and further stratified by physician specialty, hospital type and location, and length-of-stay. Results: A total of 603,437 unique hospital records were linked between hospital DAD and EHR. The average level of agreement at 3-digit level of ICD-10-CA code for main diagnosis was 47.5% and any diagnosis was 37.0%. The average number of diagnoses coded by human coders in hospital DAD was higher than the solution mapped data in EHR. The agreement varied by specialty and length-of-stay with specialties with more complex patients and longer stays showing the lowest levels of agreement. Conclusion: Level of agreement between solution mapped EHR and hospital DAD for ICD-10-CA data was low, indicating significant differences between terminology mappings and the coding process. (© 2025. The Author(s).) |
| References: | Int J Med Inform. 2021 Sep;153:104543. (PMID: 34391016) J Biomed Inform. 2024 Apr;152:104617. (PMID: 38432534) BMC Med Inform Decis Mak. 2021 Nov 9;21(Suppl 6):206. (PMID: 34753471) JCO Clin Cancer Inform. 2022 Sep;6:e2200056. (PMID: 36179272) Health Inf Manag. 2020 Jan;49(1):5-18. (PMID: 31159578) NPJ Digit Med. 2022 Oct 22;5(1):159. (PMID: 36273236) Healthc Financ Manage. 2012 Oct;66(10):46-9. (PMID: 23088053) J Med Syst. 2020 Feb 8;44(3):62. (PMID: 32036459) CMAJ Open. 2017 Aug 15;5(3):E617-E622. (PMID: 28827414) Health Inf Manag. 2020 Jan;49(1):19-27. (PMID: 31284769) Int J Popul Data Sci. 2018 Sep 21;3(3):443. (PMID: 32935019) J Am Med Inform Assoc. 2010 Nov-Dec;17(6):646-51. (PMID: 20962126) J Am Med Inform Assoc. 2006 May-Jun;13(3):277-88. (PMID: 16501181) BMC Health Serv Res. 2017 Nov 22;17(1):766. (PMID: 29166905) Can J Public Health. 2016 Jun 27;107(1):e56-e61. (PMID: 27348111) NPJ Digit Med. 2023 Feb 3;6(1):16. (PMID: 36737496) Yearb Med Inform. 2019 Aug;28(1):56-64. (PMID: 31419816) Health Inf Manag. 2024 May;53(2):68-75. (PMID: 35838185) J AHIMA. 2013 Jul;84(7):24-7. (PMID: 23926868) J AHIMA. 2012 Jul;83(7):24-8. (PMID: 22896948) J Med Internet Res. 2024 Sep 20;26:e58278. (PMID: 39302714) Appl Clin Inform. 2020 May;11(3):415-426. (PMID: 32521555) |
| Contributed Indexing: | Keywords: Electronic health records; International Classification of Diseases (ICD); Mapped ICD codes |
| Entry Date(s): | Date Created: 20251126 Date Completed: 20251126 Latest Revision: 20251128 |
| Update Code: | 20251128 |
| PubMed Central ID: | PMC12648991 |
| DOI: | 10.1186/s12913-025-13716-3 |
| PMID: | 41291697 |
| Databáze: | MEDLINE |
Full Text 
Full Text Finder 
Nájsť tento článok vo Web of Science | Abstrakt: | Competing Interests: Declarations. Ethics approval and consent to participate: This study (REB23-1186) was approved by the Conjoint Health Research Ethics Board (CHREB) at the University of Calgary and Alberta Health Services prior to accessing and analysing the data. Informed consent was waived by the CHREB in the Ethics approval and consent to participate. Consent for publication: Informed consent was waived by the CHREB for conducting and publishing this research study. Competing interests: The authors declare no competing interests.<br />Background and Objective: Coding by human coders is burdensome to healthcare systems requiring advanced computerized techniques. Epic has collaborated with Intelligent Medical Objects (IMO) solution to integrate a solution where the clinical interface terminology is mapped to the International Classification of Diseases (ICD). This study assesses the agreement between the solution mapped ICD-10-CA codes in Alberta, Canada's EHR system (based on Epic) to the human coded ICD-10-CA codes in hospital Discharge Abstract Database (DAD).<br />Design and Setting: In this retrospective analysis conducted in Alberta, Canada, we linked records in the acute care hospital DAD with the province wide EHR system for admissions between April 2021 and March 2024.<br />Main Outcome(s) and Measure(s): The primary outcome was the level of agreement between the solution mapped ICD-10-CA codes from the 'hospital problem list' in the EHR and hospital DAD data. The analysis was conducted at 3-digit and 4-digit ICD code level for main diagnosis and any diagnosis, and further stratified by physician specialty, hospital type and location, and length-of-stay.<br />Results: A total of 603,437 unique hospital records were linked between hospital DAD and EHR. The average level of agreement at 3-digit level of ICD-10-CA code for main diagnosis was 47.5% and any diagnosis was 37.0%. The average number of diagnoses coded by human coders in hospital DAD was higher than the solution mapped data in EHR. The agreement varied by specialty and length-of-stay with specialties with more complex patients and longer stays showing the lowest levels of agreement.<br />Conclusion: Level of agreement between solution mapped EHR and hospital DAD for ICD-10-CA data was low, indicating significant differences between terminology mappings and the coding process.<br /> (© 2025. The Author(s).) |
|---|---|
| ISSN: | 1472-6963 |
| DOI: | 10.1186/s12913-025-13716-3 |