Dataset Information

Feasibility of replacing the ICD-10-CM with the ICD-11 for morbidity coding: A content analysis.

ABSTRACT:

Objective

The study sought to assess the feasibility of replacing the International Classification of Diseases-Tenth Revision-Clinical Modification (ICD-10-CM) with the International Classification of Diseases-11th Revision (ICD-11) for morbidity coding based on content analysis.

Materials and methods

The most frequently used ICD-10-CM codes from each chapter covering 60% of patients were identified from Medicare claims and hospital data. Each ICD-10-CM code was recoded in the ICD-11, using postcoordination (combination of codes) if necessary. Recoding was performed by 2 terminologists independently. Failure analysis was done for cases where full representation was not achieved even with postcoordination. After recoding, the coding guidance (inclusions, exclusions, and index) of the ICD-10-CM and ICD-11 codes were reviewed for conflict.

Results

Overall, 23.5% of 943 codes could be fully represented by the ICD-11 without postcoordination. Postcoordination is the potential game changer. It supports the full representation of 8.6% of 943 codes. Moreover, with the addition of only 9 extension codes, postcoordination supports the full representation of 35.2% of 943 codes. Coding guidance review identified potential conflicts in 10% of codes, but mostly not affecting recoding. The majority of the conflicts resulted from differences in granularity and default coding assumptions between the ICD-11 and ICD-10-CM.

Conclusions

With some minor enhancements to postcoordination, the ICD-11 can fully represent almost 60% of the most frequently used ICD-10-CM codes. Even without postcoordination, 23.5% full representation is comparable to the 24.3% of ICD-9-CM codes with exact match in the ICD-10-CM, so migrating from the ICD-10-CM to the ICD-11 is not necessarily more disruptive than from the International Classification of Diseases-Ninth Revision-Clinical Modification to the ICD-10-CM. Therefore, the ICD-11 (without a CM) should be considered as a candidate to replace the ICD-10-CM for morbidity coding.

SUBMITTER: Fung KW

PROVIDER: S-EPMC8510319 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Feasibility of replacing the ICD-10-CM with the ICD-11 for morbidity coding: A content analysis.

Fung Kin Wah KW Xu Julia J McConnell-Lamptey Shannon S Pickett Donna D Bodenreider Olivier O

Journal of the American Medical Informatics Association : JAMIA 20211001 11

<h4>Objective</h4>The study sought to assess the feasibility of replacing the International Classification of Diseases-Tenth Revision-Clinical Modification (ICD-10-CM) with the International Classification of Diseases-11th Revision (ICD-11) for morbidity coding based on content analysis.<h4>Materials and methods</h4>The most frequently used ICD-10-CM codes from each chapter covering 60% of patients were identified from Medicare claims and hospital data. Each ICD-10-CM code was recoded in the ICD ...[more]

PMID: 34383897

Similar Datasets

Project description:BackgroundWe aimed to estimate the impact of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding transition on traumatic injury-related hospitalization trends among young adults across a geographically and demographically diverse group of U.S. states.MethodsInterrupted time series analyses were conducted using statewide inpatient databases from 12 states and including traumatic injury-related hospitalizations in adults aged 19-44 years in 2011-2017. Segmented regression models were used to estimate the impact of the October 2015 coding transition on external cause of injury (ECOI) completeness (percentage of hospitalizations with a documented ECOI code) and on population-level rates of injury-related hospitalizations by nature, intent, mechanism, and severity of injury.ResultsThe transition to ICD-10-CM was associated with a drop in ECOI completion in the transition month (- 3.7%; P < .0001), but there was no significant change in the positive trend in ECOI completion from the pre- to post-transition periods. There were significant increases post-transition in the measured rates of hospitalization for traumatic brain injury (TBI), unintentional injury, mild injury (injury severity score (ISS) < 9), and injuries caused by drowning, firearms, machinery, other pedestrian, suffocation, and unspecified mechanism. Conversely, there were significant decreases in October 2015 in the rates of hospitalization for assault, injuries of undetermined intent, injuries of moderate severity (ISS 9-15), and injuries caused by fire/burn, other pedal cyclist, other transportation, natural/environmental, and other specified mechanism. A significant increase in the percentage of hospitalizations classified as resulting from severe injury (ISS > 15) was observed when the general equivalence mapping maximum severity method for converting ICD-10-CM codes to ICD-9-CM codes was used. State-specific results for the outcomes of ECOI completion and TBI-related hospitalization rates are provided in an online supplement.ConclusionsThe U.S. transition from ICD-9-CM to ICD-10-CM coding led to a significant decrease in ECOI completion and several significant changes in measured rates of injury-related hospitalizations by injury intent, mechanism, nature, and severity. The results of this study can inform the design and analysis of future traumatic injury-related health services research studies that use both ICD-9-CM and ICD-10-CM coded data.Level of evidenceII (Interrupted Time Series).

Project description:PurposeWidespread electronic health record adoption has generated a large volume of data and emphasized the need for standardized terminology to describe clinical concepts. Here, we undertook a systematic concept coverage analysis to determine the representation of clinical concepts in ophthalmic infection and ophthalmic trauma among standardized medical terminologies, including the Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), the International Classification of Diseases (ICD) version 10 with clinical modifications (ICD-10-CM), and ICD version 11 (ICD-11).DesignExtraction of concepts related to ophthalmic infection and ophthalmic trauma and structured search in terminology browsers.Data sourcesThe American Academy of Ophthalmology Basic and Clinical Science Course (BCSC), SNOMED-CT, and ICD-10-CM terminologies from the Observational Health Data Sciences and Informatics Athena browser, and the ICD-11 terminology browser.MethodsConcepts pertaining to ophthalmic infection and ophthalmic trauma were extracted from the 2022 BCSC free text and index terms. We searched terminology browsers to identify corresponding codes and classified the extent of semantic alignment as equal, wide, narrow, or unmatched in each terminology. The overlap of equal concepts in each terminology was represented in a Venn diagram.Main outcome measuresProportions of clinical concepts with corresponding codes at various levels of semantic alignment.ResultsA total of 443 concepts were identified: 304 concepts related to ophthalmic infection and 139 concepts related to ophthalmic trauma. The SNOMED-CT had the highest proportion of equal coverage, with 82.0% (249 of 304) among concepts related to ophthalmic infection and 82.0% (115 of 139) among concepts related to ophthalmic trauma. Across all concepts, 28% (124 of 443) were classified as equal in ICD-10-CM and 52.8% (234 of 443) were classified as equal in ICD-11.ConclusionsThe SNOMED-CT had significantly better semantic alignment than ICD-10-CM and ICD-11 for ophthalmic infections and ophthalmic trauma. This demonstrates opportunity for continuing advancement of representation of ophthalmic concepts in standardized medical terminologies.

Project description:ObjectivesUnderstand the continuity and changes in headache not-otherwise-specified (NOS), migraine, and post-traumatic headache (PTH) diagnoses after the transition from ICD-9-CM to ICD-10-CM in the Veterans Health Administration (VHA).BackgroundHeadache is one of the most commonly diagnosed chronic conditions managed within primary and specialty care clinics. The VHA transitioned from ICD-9-CM to ICD-10-CM on October-1-2015. The effect transitioning on coding of specific headache diagnoses is unknown. Accuracy of headache diagnosis is important since different headache types respond to different treatments.MethodsWe mapped headache diagnoses from ICD-9-CM (FY 2014/2015) onto ICD-10-CM (FY 2016/2017) and computed coding proportions two years before/after the transition in VHA. We used queries to determine the change in transition pathways. We report the odds of ICD-10-CM coding associated with ICD-9-CM controlling for provider type, and patient age, sex, and race/ethnicity.ResultsOnly 37%, 58% and 34% of patients with ICD-9-CM coding of NOS, migraine, and PTH respectively had an ICD-10-CM headache diagnosis. Of those with an ICD-10-CM diagnosis, 73-79% had a single headache diagnosis. The odds ratios for receiving the same code in both ICD-9-CM and ICD-10-CM after adjustment for ICD-9-CM and ICD-10-CM headache comorbidities and sociodemographic factors were high (range 6-26) and statistically significant. Specifically, 75% of patients with headache NOS had received one headache diagnoses (Adjusted headache NOS-ICD-9-CM OR for headache NOS-ICD-10-CM = 6.1, 95% CI 5.89-6.32. 79% of migraineurs had one headache diagnoses, mostly migraine (Adjusted migraine-ICD-9-CM OR for migraine-ICD-10-CM = 26.43, 95% CI 25.51-27.38). The same held true for PTH (Adjusted PTH-ICD-9-CM OR for PTH-ICD-10-CM = 22.92, 95% CI: 18.97-27.68). These strong associations remained after adjustment for specialist care in ICD-10-CM follow-up period.DiscussionThe majority of people with ICD-9-CM headache diagnoses did not have an ICD-10-CM headache diagnosis. However, a given diagnosis in ICD-9-CM by a primary care provider (PCP) was significantly predictive of its assignment in ICD-10-CM as was seeing either a neurologist or physiatrist (compared to a generalist) for an ICD-10-CM headache diagnosis.ConclusionWhen a veteran had a specific diagnosis in ICD-9-CM, the odds of being coded with the same diagnosis in ICD-10-CM were significantly higher. Specialist visit during the ICD-10-CM period was independently associated with all three ICD-10-CM headaches.

Project description:BackgroundImplementation of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) in the U.S. on October 1, 2015 was a significant policy change with the potential to affect established injury morbidity trends. This study used data from a single state to demonstrate 1) the use of a statistical method to estimate the effect of this coding transition on injury hospitalization trends, and 2) interpretation of significant changes in injury trends in the context of the structural and conceptual differences between ICD-9-CM and ICD-10-CM, the new ICD-10-CM-specific coding guidelines, and proposed ICD-10-CM-based framework for reporting of injuries by intent and mechanism. Segmented regression analysis was used for statistical modeling of interrupted time series monthly data to evaluate the effect of the transition to ICD-10-CM on Kentucky hospitalizations' external-cause-of-injury completeness (percentage of records with principal injury diagnoses supplemented with external-cause-of-injury codes), as well as injury hospitalization trends by intent or mechanism, January 2012-December 2017.ResultsThe segmented regression analysis showed an immediate significant drop in external-cause-of-injury completeness during the transition month, but returned to its pre-transition levels in November 2015. There was a significant immediate change in the percentage of injury hospitalizations coded for unintentional (3.34%) and undetermined intent (- 3.39%). There were immediate significant changes in the level of injury hospitalization rates due to poisoning, suffocation, struck by/against, other transportation, unspecified mechanism, and other specified not elsewhere classifiable mechanism. Significant change in slope after the transition (without immediate level change) was identified for assault, firearm, cut/pierce, and motor vehicle traffic injury rates. The observed trend changes reflected structural and conceptual features of ICD-10-CM coding (e.g., poisoning and suffocations are now captured via diagnosis codes only), new coding guidelines (e.g., requiring coding of injury intent as "accidental" if it is unknown or unspecified), and CDC proposed external-cause-of-injury code groupings by injury intent and mechanism. Researchers can replicate this methodology assessing trends in injuries or other ICD-10-CM-coded conditions using administrative billing data sets.ConclusionsThe CDC 's Proposed Framework for Presenting Injury Data Using ICD-10-CM External Cause of Injury Codes provided a logical transition from the ICD-9-CM-based matrix on injury hospitalization trends by intent and mechanism. Our findings are intended to raise awareness that changes in the ICD-10-CM coding system must be understood to assure accurate interpretation of injury trends.

Project description:BackgroundThe phecode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) using the electronic health record (EHR).ObjectiveThe goal of this paper was to develop and perform an initial evaluation of maps from the International Classification of Diseases, 10th Revision (ICD-10) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes to phecodes.MethodsWe mapped ICD-10 and ICD-10-CM codes to phecodes using a number of methods and resources, such as concept relationships and explicit mappings from the Centers for Medicare & Medicaid Services, the Unified Medical Language System, Observational Health Data Sciences and Informatics, Systematized Nomenclature of Medicine-Clinical Terms, and the National Library of Medicine. We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM phecode map by investigating phenotype reproducibility and conducting a PheWAS.ResultsWe mapped >75% of ICD-10 and ICD-10-CM codes to phecodes. Of the unique codes observed in the UKBB (ICD-10) and VUMC (ICD-10-CM) cohorts, >90% were mapped to phecodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease for phenotypes sourced from the ICD-10-CM phecode map. Using the ICD-9-CM and ICD-10-CM maps, we conducted a PheWAS with a Lipoprotein(a) genetic variant, rs10455872, which replicated two known genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P<.001; odds ratio (OR) 1.60 [95% CI 1.43-1.80] vs ICD-10-CM: P<.001; OR 1.60 [95% CI 1.43-1.80]) and chronic ischemic heart disease (ICD-9-CM: P<.001; OR 1.56 [95% CI 1.35-1.79] vs ICD-10-CM: P<.001; OR 1.47 [95% CI 1.22-1.77]).ConclusionsThis study introduces the beta versions of ICD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for PheWAS in the EHR.

Project description:ImportanceSurveillance of severe maternal morbidity (SMM) is critical for monitoring maternal health and evaluating clinical quality improvement efforts.ObjectiveTo evaluate national and state trends in SMM rates from 2012 to 2019 and potential disruptions associated with the transition to International Classification of Diseases, 10th Revision, Clinical Modification and Procedure Coding System (ICD-10-CM/PCS) in October 2015.Design, setting, and participantsThis repeated cross-sectional analysis examined delivery hospitalizations from 2012 through 2019 in the Healthcare Cost and Utilization Project's National Inpatient Sample and State Inpatient Databases, an all-payer compendium of hospital discharge records from community, nonrehabilitation hospitals. Trends were evaluated using segmented linear binomial regression models that allowed for discontinuities across the ICD-10-CM/PCS transition. Analyses were completed from April 2021 through March 2022.ExposuresTime, ICD-10-CM/PCS coding system, and state.Main outcomes and measuresSMM rates, excluding blood transfusion, per 10 000 delivery hospitalizations, overall and by indicator.ResultsFrom 2012 to 2019, there were 5 964 315 delivery hospitalizations in the national sample representing a weighted total of 29.8 million deliveries with a mean (SD) maternal age of 28.6 (5.9) years. SMM rates increased from 69.5 per 10 000 in 2012 to 79.7 per 10 000 in 2019 (rate difference [RD], 10.2; 95% CI, 5.8 to 14.6) without a significant change across the ICD-10-CM/PCS transition (RD, -3.2; 95% CI, -6.9 to 0.6). Of 20 SMM indicators, rates for 10 indicators significantly increased while 3 significantly decreased; 5 of these changes were associated with ICD-10-CM/PCS transition. Acute kidney failure had the largest increase, from 6.4 to 15.3 per 10 000 delivery hospitalizations (RD, 8.9; 95% CI, 7.5 to 10.3) with no change associated with ICD transition (RD, -0.1; 95% CI, -1.2 to 1.1). Disseminated intravascular coagulation had the largest decrease from 31.3 to 21.2 per 10 000 (RD, 10.2; 95% CI, -12.8 to -7.5), with a significant drop associated with ICD transition (RD, -7.9; 95% CI, -10.2 to -5.6). State SMM rates significantly decreased for 1 state and significantly increased for 21 states from 2012 to 2019 and associations with ICD transition varied.Conclusions and relevanceIn this cross-sectional study, overall US SMM rates increased from 2012 to 2019, which was not associated with the ICD-10-CM/PCS transition. However, data for certain indicators and states may not be comparable across coding systems; efforts are needed to understand SMM increases and state variation.

Dataset Information

Feasibility of replacing the ICD-10-CM with the ICD-11 for morbidity coding: A content analysis.

Objective

Materials and methods

Results

Conclusions

Publications

Feasibility of replacing the ICD-10-CM with the ICD-11 for morbidity coding: A content analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets