title: Leveraging the NLM map from SNOMED CT to ICD-10-CM to facilitate adoption of ICD-10-CM.
abstract: OBJECTIVE
  Develop and test web services to retrieve and identify the most precise ICD-10-CM code(s) for a given clinical encounter. Facilitate creation of user interfaces that 1) provide an initial shortlist of candidate codes, ideally visible on a single screen; and 2) enable code refinement.
  
  
  METHODS
  To satisfy our high-level use cases, the analysis and design process involved reviewing available maps and crosswalks, designing the rule adjudication framework, determining necessary metadata, retrieving related codes, and iteratively improving the code refinement algorithm.
  
  
  RESULTS
  The Partners ICD-10-CM Search and Mapping Services (PI-10 Services) are SOAP web services written using Microsoft's.NET 4.0 Framework, Windows Communications Framework, and SQL Server 2012. The services cover 96% of the Partners problem list subset of SNOMED CT codes that map to ICD-10-CM codes and can return up to 76% of the 69,823 billable ICD-10-CM codes prior to creation of custom mapping rules.
  
  
  CONCLUSIONS
  We consider ways to increase 1) the coverage ratio of the Partners problem list subset of SNOMED CT codes and 2) the upper bound of returnable ICD-10-CM codes by creating custom mapping rules. Future work will investigate the utility of the transitive closure of SNOMED CT codes and other methods to assist in custom rule creation and, ultimately, to provide more complete coverage of ICD-10-CM codes.
  
  
  CONCLUSIONS
  ICD-10-CM will be easier for clinicians to manage if applications display short lists of candidate codes from which clinicians can subsequently select a code for further refinement. The PI-10 Services support ICD-10 migration by implementing this paradigm and enabling users to consistently and accurately find the best ICD-10-CM code(s) without translation from ICD-9-CM.
authors.affiliation: Information Systems, Partners HealthCare System, Wellesley, MA PCARTAGENA@partners.org.
authors.forename: F Phil
authors.initials: FP
authors.lastname: Cartagena
authors.affiliation: Information Systems, Partners HealthCare System, Wellesley, MA.
authors.forename: Molly
authors.initials: M
authors.lastname: Schaeffer
authors.affiliation: Information Systems, Partners HealthCare System, Wellesley, MA.
authors.forename: Dorothy
authors.initials: D
authors.lastname: Rifai
authors.affiliation: Information Systems, Partners HealthCare System, Wellesley, MA.
authors.forename: Victoria
authors.initials: V
authors.lastname: Doroshenko
authors.affiliation: Information Systems, Partners HealthCare System, Wellesley, MA Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA Harvard Medical School, Boston, MA.
authors.forename: Howard S
authors.initials: HS
authors.lastname: Goldberg
mesh_terms: D057286:Electronic Health Records; D006801:Humans; D038801:International Classification of Diseases; D009317:National Library of Medicine (U.S.); D039061:Systematized Nomenclature of Medicine; D014481:United States
keywords: ICD-10 Transition; ICD-10-CM; Medical Informatics; Medical Informatics Applications; SNOMED CT