Identifying clinically disruptive international classification of diseases 10th revision clinical modification conversions to mitigate financial costs using an online tool

Neeta K. Venepalli, Yusuf Qamruzzaman, Jianrong Li, Yves A Lussier, Andrew D. Boyd

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Purpose: To quantify coding ambiguity in International Classification of Diseases Ninth Revision Clinical Modification conversions (ICD-9-CM) to ICD-10-CM mappings for hematologyoncology diagnoses within an Illinois Medicaid database and an academic cancer center database (University of Illinois Cancer Center [UICC]) with the goal of anticipating challenges during ICD-10-CM transition. Methods: One data set of ICD-9-CM diagnosis codes came from the 2010 Illinois Department of Medicaid, filtered for diagnoses generated by hematology-oncology providers. The other data set of ICD-9-CM diagnosis codes came from UICC. Using a translational methodology via the Motif Web portal ICD-9-CM conversion tool, ICD-9-CM to ICD-10-CM code conversions were graphically mapped and evaluated for clinical loss of information. Results: The transition to ICD-10-CM led to significant information loss, affecting 8% of total Medicaid codes and 1% of UICC codes; 39 ICD-9-CM codes with information loss accounted for 2.9% of total Medicaid reimbursements and 5.3% of UICC billing charges. Conclusion: Prior work stated hematology-oncology would be the least affected medical specialty. However, information loss affecting 5% of billing costs could evaporate the operating margin of a practice. By identifying codes at risk for complex transitions, the analytic tools described can be replicated for oncology practices to forecast areas requiring additional training and resource allocation. In summary, complex transitions and diagnosis codes associated with information loss within clinical oncology require additional attention during the transition to ICD-10-CM.

Original languageEnglish (US)
Pages (from-to)97-103
Number of pages7
JournalJournal of Oncology Practice
Volume10
Issue number2
DOIs
StatePublished - 2014
Externally publishedYes

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International Classification of Diseases
Costs and Cost Analysis
Medicaid
Hematology
Neoplasms
Databases
Medical Oncology
Resource Allocation
Medicine

ASJC Scopus subject areas

  • Oncology
  • Oncology(nursing)
  • Health Policy
  • Medicine(all)

Cite this

Identifying clinically disruptive international classification of diseases 10th revision clinical modification conversions to mitigate financial costs using an online tool. / Venepalli, Neeta K.; Qamruzzaman, Yusuf; Li, Jianrong; Lussier, Yves A; Boyd, Andrew D.

In: Journal of Oncology Practice, Vol. 10, No. 2, 2014, p. 97-103.

Research output: Contribution to journalArticle

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abstract = "Purpose: To quantify coding ambiguity in International Classification of Diseases Ninth Revision Clinical Modification conversions (ICD-9-CM) to ICD-10-CM mappings for hematologyoncology diagnoses within an Illinois Medicaid database and an academic cancer center database (University of Illinois Cancer Center [UICC]) with the goal of anticipating challenges during ICD-10-CM transition. Methods: One data set of ICD-9-CM diagnosis codes came from the 2010 Illinois Department of Medicaid, filtered for diagnoses generated by hematology-oncology providers. The other data set of ICD-9-CM diagnosis codes came from UICC. Using a translational methodology via the Motif Web portal ICD-9-CM conversion tool, ICD-9-CM to ICD-10-CM code conversions were graphically mapped and evaluated for clinical loss of information. Results: The transition to ICD-10-CM led to significant information loss, affecting 8{\%} of total Medicaid codes and 1{\%} of UICC codes; 39 ICD-9-CM codes with information loss accounted for 2.9{\%} of total Medicaid reimbursements and 5.3{\%} of UICC billing charges. Conclusion: Prior work stated hematology-oncology would be the least affected medical specialty. However, information loss affecting 5{\%} of billing costs could evaporate the operating margin of a practice. By identifying codes at risk for complex transitions, the analytic tools described can be replicated for oncology practices to forecast areas requiring additional training and resource allocation. In summary, complex transitions and diagnosis codes associated with information loss within clinical oncology require additional attention during the transition to ICD-10-CM.",
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