The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools

Abstract

ObjectiveApplying the science of networks to quantify the discriminatory impact of the ICD-9-CM to ICD-10-CM transition between clinical specialties.Materials and MethodsDatasets were the Center for Medicaid and Medicare Services ICD-9-CM to ICD-10-CM mapping files, general equivalence mappings, and statewide Medicaid emergency department billing. Diagnoses were represented as nodes and their mappings as directional relationships. The complex network was synthesized as an aggregate of simpler motifs and tabulation per clinical specialty.ResultsWe identified five mapping motif categories: identity, class-to-subclass, subclass-to-class, convoluted, and no mapping. Convoluted mappings indicate that multiple ICD-9-CM and ICD-10-CM codes share complex, entangled, and non-reciprocal mappings. The proportions of convoluted diagnoses mappings (36% overall) range from 5% (hematology) to 60% (obstetrics and injuries). In a case study of 24 008 patient visits in 217 emergency departments, 27% of the costs are associated with convoluted diagnoses, with ‘abdominal pain’ and ‘gastroenteritis’ accounting for approximately 3.5%.DiscussionPrevious qualitative studies report that administrators and clinicians are likely to be challenged in understanding and managing their practice because of the ICD-10-CM transition. We substantiate the complexity of this transition with a thorough quantitative summary per clinical specialty, a case study, and the tools to apply this methodology easily to any clinical practice in the form of a web portal and analytic tables.ConclusionsPost-transition, successful management of frequent diseases with convoluted mapping network patterns is critical. The http://lussierlab.org/transition-to-ICD10CM web portal provides insight in linking onerous diseases to the ICD-10 transition.

The Transition to ICD-10-CM: Challenges for Pediatric Practice

“…After the pediatric ICD-9-CM codes were mapped to ICD-10-CM codes and labeled into the above 5 categories, 14 an initial patient visit count and cost analysis were performed for each category. To appreciate potential clinical complexity inherent in the transition to ICD-10-CM, the convoluted codes were evaluated by physicians and classified into to 1 of 4 categories: information loss, overlapping categories, inconsistent, or consistent.…”

“…A similar analysis revealed that 18% of adult oncology codes, 31% of emergency department codes, and 55% of hospital procedure codes are convoluted, showing variability in potential coding challenges by type of practice and the importance of understanding potential issues associated with codes commonly used by each specialty (A.D.B., unpublished data). 14,16 To assist with analysis of data that span the transition time frame (2015-2016), the American Medical Association suggests mapping in the direction with the most data (initially map ICD-10-CM back to ICD-9-CM; then, as more ICD-10-CM codes are used, map ICD-9-CM to ICD-10-CM). 17 However, using the GEMs files for simple transitions will miss a large number of codes: for example, if mapping from ICD-9-CM to ICD-10-CM using GEMs you map to only 24% of ICD-10-CM codes.…”

“…The ICD-9-CM codes were categorized into 5 categories on the basis of how they map to ICD-10-CM: identity (where the codes are equivalent), class-to-subclass (1 ICD-9-CM code going to multiple ICD-10-CM codes), subclass-to-class (multiple ICD-9-CM codes to 1 ICD-10-CM code), no transition (no mapping to ICD-10-CM), and convoluted (a complex mapping of ICD-9-CM to and from ICD-10-CM; see Fig 1). 14 The first 4 categories include codes where the transition is straightforward and easy to identify; however, the convoluted codes have complex mappings making the transition difficult.…”

The Transition to ICD-10-CM: Challenges for Pediatric Practice

“…5,14 The mappings were examined by pediatricians for clinical accuracy, and financial analysis of the findings was conducted. The study was approved by the University of Illinois Institutional Review Board.…”

“…Boyd et al 14 provided classification for mapping on the basis of on how codes associate with each other. The ICD-9-CM codes were categorized into 5 categories on the basis of how they map to ICD-10-CM: identity (where the codes are equivalent), class-to-subclass (1 ICD-9-CM code going to multiple ICD-10-CM codes), subclass-to-class (multiple ICD-9-CM codes to 1 ICD-10-CM code), no transition (no mapping to ICD-10-CM), and convoluted (a complex mapping of ICD-9-CM to and from ICD-10-CM; see Fig 1).…”