Differences in Administrative Claims Data for Coronary Artery Bypass Grafting Between International Classification of Diseases, Ninth Revision and Tenth Revision Coding.
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SUBMITTER: Schaffer JM
PROVIDER: S-EPMC8190691 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
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Differences in Administrative Claims Data for Coronary Artery Bypass Grafting Between International Classification of Diseases, Ninth Revision and Tenth Revision Coding.
Schaffer Justin M JM Squiers John J JJ Banwait Jasjit K JK Hale Sarah S Ryan William H WH Mack Michael J MJ DiMaio J Michael JM
JAMA cardiology 20210901 9
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Project description:The Faurot frailty index (FFI) is a validated algorithm that uses enrollment and International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)-based billing information from Medicare claims data as a proxy for frailty. In October 2015, the US health-care system transitioned from the ICD-9-CM to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM). Applying the Centers for Medicare and Medicaid Services General Equivalence Mappings, we translated diagnosis-based frailty indicator codes from the ICD-9-CM to the ICD-10-CM, followed by manual review. We used interrupted time-series analysis of Medicare data to assess the comparability of the pre- and posttransition FFI scores. In cohorts of beneficiaries enrolled in January 2015-2017 with 8-month frailty look-back periods, we estimated associations between the FFI and 1-year risk of aging-related outcomes (mortality, hospitalization, and admission to a skilled nursing facility). Updated indicators had similar prevalences as pretransition definitions. The median FFI scores and interquartile ranges (IQRs) for the predicted probability of frailty were similar before and after the International Classification of Diseases transition (pretransition: median, 0.034 (IQR, 0.02-0.07); posttransition: median, 0.038 (IQR, 0.02-0.09)). The updated FFI was associated with increased risks of mortality, hospitalization, and skilled nursing facility admission, similar to findings from the ICD-9-CM era. Studies of medical interventions in older adults using administrative claims should use validated indices, like the FFI, to mitigate confounding or assess effect-measure modification by frailty.
| S-EPMC10988220 | biostudies-literature
Project description:BackgroundAdministrative claims for aortic stenosis (AS) regurgitation may be useful, but their accuracy and ability to identify individuals at risk for valve-related outcomes have not been well characterized.MethodsUsing echocardiographic (transthoracic echocardiogram [TTE]) reports linked to US Medicare claims, 2017 to 2018, the performance of candidate International Classification of Diseases, Tenth Revision claims to ascertain AS/aortic regurgitation was evaluated. The optimal performing algorithm was tested against outcomes at 1-year after TTE in a separate 100% sample of US Medicare claims, 2017 to 2019.ResultsOf those included in the derivation (N=5497, mean age 74.4±11.0 years, 49.7% female), any AS or aortic regurgitation was present in 24% and 38.8%, respectively. The sensitivity and specificity of International Classification of Diseases, Tenth Revision code I35.0 for identification of any AS was 53.1% and 94.8%, respectively. Among those with an I35.0 code, 40.3% had severe AS. Claims were unable to distinguish disease severity (ie, severe versus nonsevere) or subtype (eg, bicuspid or rheumatic AS), and were insensitive and nonspecific for aortic regurgitation of any severity. Among all beneficiaries who received a TTE (N=4 033 844), adjusting for age, sex, and 27 comorbidities, those with an I35.0 code had a higher adjusted risk of all-cause mortality (adjusted hazard ratio, 1.33 [95% CI, 1.31-1.34]), heart failure hospitalization (adjusted hazard ratio, 1.37 [95% CI, 1.34-1.41]), and aortic valve replacement (adjusted hazard ratio, 34.96 [95% CI, 33.74-36.22]).ConclusionsAmong US Medicare beneficiaries receiving a TTE, International Classification of Diseases, Tenth Revision claims, though identifying a population at significant greater risk of valve-related outcomes, failed to identify nearly half of individuals with AS and were unable to distinguish disease severity or subtype. These results argue against the widespread use of International Classification of Diseases, Tenth Revision claims to screen for patients with AS and suggests the need for improved coding algorithms and alternative systems to extract TTE data for quality improvement and hospital benchmarking.
| S-EPMC9588616 | biostudies-literature
Project description:Background Administrative data permit analysis of large cohorts but rely on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), and International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes that may not reflect true congenital heart defects (CHDs). Methods and Results CHDs in 1497 cases with at least 1 encounter between January 1, 2010 and December 31, 2019 in 2 health care systems, identified by at least 1 of 87 ICD-9-CM/ICD-10-CM CHD codes were validated through medical record review for the presence of CHD and CHD native anatomy. Interobserver and intraobserver reliability averaged >95%. Positive predictive value (PPV) of ICD-9-CM/ICD-10-CM codes for CHD was 68.1% (1020/1497) overall, 94.6% (123/130) for cases identified in both health care systems, 95.8% (249/260) for severe codes, 52.6% (370/703) for shunt codes, 75.9% (243/320) for valve codes, 73.5% (119/162) for shunt and valve codes, and 75.0% (39/52) for "other CHD" (7 ICD-9-CM/ICD-10-CM codes). PPV for cases with >1 unique CHD code was 85.4% (503/589) versus 56.3% (498/884) for 1 CHD code. Of cases with secundum atrial septal defect ICD-9-CM/ICD-10-CM codes 745.5/Q21.1 in isolation, PPV was 30.9% (123/398). Patent foramen ovale was present in 66.2% (316/477) of false positives. True positives had younger mean age at first encounter with a CHD code than false positives (22.4 versus 26.3 years; P=0.0017). Conclusions CHD ICD-9-CM/ICD-10-CM codes have modest PPV and may not represent true CHD cases. PPV was improved by selecting certain features, but most true cases did not have these characteristics. The development of algorithms to improve accuracy may improve accuracy of electronic health records for CHD surveillance.
| S-EPMC10492959 | biostudies-literature
Project description:BackgroundEvaluation of large-scale data sets is needed to better understand the epidemiology, cost, and burden of atopic dermatitis (AD). We sought to validate the use of ICD-9-CM codes for identifying AD.MethodsPatients from a large metropolitan quaternary care medical center with a diagnostic code of either 691.8 (AD) or 692.9 (eczema and contact dermatitis) were queried. Medical records were reviewed for demographics, Hanifin & Rajka (H&R) and United Kingdom Working Party (UKWP) criteria. Sensitivity, specificity, and positive predictive values (PPV) of the codes were calculated.ResultsOf 43 278 patients identified with associated ICD-9 codes of 691.8 or 692.9, 519 and 253 with 691.8 and 692.9 were randomly selected for chart review. There was extensive overlap: 34.3% had ≥1 occurrences of 691.8 and 692.9 and 25.6% had multiple occurrences of both codes. Among patients with ≥1 occurrence of 691.8, 29.9% and 30.8% met the H&R and UKWP criteria, respectively. Similarly, among patients with ≥1 occurrence of 692.9, 33.7% and 32.2% met the H&R and UKWP criteria. Increased PPV was associated with concomitant diagnoses of asthma, hay fever, and food allergy and increased disease severity.ConclusionsIn the outpatient setting, the ICD-9-CM codes 691.8 and 692.9 alone have poor PPV. Incorporation of diagnoses of asthma, hay fever, and food allergy improves PPV and specificity. In the inpatient setting, a primary discharge diagnosis of 691.8 had excellent PPV. Although ICD-10 has been adopted in Europe and more recently in the USA, the same systematic errors would likely occur unless providers standardize their coding.
| S-EPMC5461190 | biostudies-literature
Project description:Objective The aim of the study was to investigate the feasibility of using administrative data to screen adverse events in Korea. Methods We used a diagnosis-related groups claims data set and the information of the checklist of healthcare quality improvement (a part of the value incentive program) to verify adverse events in fiscal year 2018. Adverse events were identified using patient safety indicator (PSI) clusters and a present on admission indicator (POA). The PSIs consisted of 19 clusters representing subcategories of adverse events, such as hospital-acquired infection. Among the adverse events identified using PSI clusters, “POA = N,” which means not present at the time of admission, was only deemed as the case in the final stage. We compared the agreement on the occurrence of adverse events from claims data with a reference standard data set (i.e., checklist of healthcare quality improvement) and presented them by PSI cluster and institution. Results The cases of global PSI for any adverse event numbered 27,320 (2.32%) among all diagnostic codes in 2018. In terms of institutional distribution, considerable variation was observed throughout the clusters. For example, only 13.2% of institutions (n = 387) reported any global PSI for any adverse event throughout the whole year. The agreement between the reference standard and the claims data was poor, in the range of 2.2% to 10.8%, in 3 types of adverse events. The current claims data system (i.e., diagnostic codes coupled to POA indicators) failed to capture a large majority of adverse events identified using the reference standard. Conclusions Our results imply that the coding status of International Classification of Diseases, Tenth Revision, codes and POA indicators should be refined before using them as quality indicators.
| S-EPMC9329045 | biostudies-literature
Project description:BackgroundComputer-assisted clinical coding (CAC) tools are designed to help clinical coders assign standardized codes, such as the ICD-10 (International Statistical Classification of Diseases, Tenth Revision), to clinical texts, such as discharge summaries. Maintaining the integrity of these standardized codes is important both for the functioning of health systems and for ensuring data used for secondary purposes are of high quality. Clinical coding is an error-prone cumbersome task, and the complexity of modern classification systems such as the ICD-11 (International Classification of Diseases, Eleventh Revision) presents significant barriers to implementation. To date, there have only been a few user studies; therefore, our understanding is still limited regarding the role CAC systems can play in reducing the burden of coding and improving the overall quality of coding.ObjectiveThe objective of the user study is to generate both qualitative and quantitative data for measuring the usefulness of a CAC system, Easy-ICD, that was developed for recommending ICD-10 codes. Specifically, our goal is to assess whether our tool can reduce the burden on clinical coders and also improve coding quality.MethodsThe user study is based on a crossover randomized controlled trial study design, where we measure the performance of clinical coders when they use our CAC tool versus when they do not. Performance is measured by the time it takes them to assign codes to both simple and complex clinical texts as well as the coding quality, that is, the accuracy of code assignment.ResultsWe expect the study to provide us with a measurement of the effectiveness of the CAC system compared to manual coding processes, both in terms of time use and coding quality. Positive outcomes from this study will imply that CAC tools hold the potential to reduce the burden on health care staff and will have major implications for the adoption of artificial intelligence-based CAC innovations to improve coding practice. Expected results to be published summer 2024.ConclusionsThe planned user study promises a greater understanding of the impact CAC systems might have on clinical coding in real-life settings, especially with regard to coding time and quality. Further, the study may add new insights on how to meaningfully exploit current clinical text mining capabilities, with a view to reducing the burden on clinical coders, thus lowering the barriers and paving a more sustainable path to the adoption of modern coding systems, such as the new ICD-11.Trial registrationclinicaltrials.gov NCT06286865; https://clinicaltrials.gov/study/NCT06286865.International registered report identifier (irrid)DERR1-10.2196/54593.
| S-EPMC10966438 | biostudies-literature
Project description:Importance:On October 1, 2015, the US transitioned to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for recording diagnoses, symptoms, and procedures. It is unknown whether this transition was associated with changes in diagnostic category prevalence based on diagnosis classification systems commonly used for payment and quality reporting. Objective:To assess changes in diagnostic category prevalence associated with the ICD-10-CM transition. Design, Setting, and Participants:This interrupted time series analysis and cross-sectional study examined level and trend changes in diagnostic category prevalence associated with the ICD-10-CM transition and clinically reviewed a subset of diagnostic categories with changes of 20% or more. Data included insurance claim diagnoses from the IBM MarketScan Commercial Database from January 1, 2010, to December 31, 2017, for more than 18 million people aged 0 to 64 years with private insurance. Diagnoses were mapped using 3 common diagnostic classification systems: World Health Organization (WHO) disease chapters, Department of Health and Human Services Hierarchical Condition Categories (HHS-HCCs), and Agency for Healthcare Research and Quality Clinical Classification System (AHRQ-CCS). Data were analyzed from December 1, 2018, to January 21, 2020. Exposures:US implementation of ICD-10-CM. Main Outcomes and Measures:Monthly rates of individuals with at least 1 diagnosis in a diagnostic classification category per 10 000 eligible members. Results:The analytic sample contained information on 2.1 billion enrollee person-months with 3.4 billion clinically assigned diagnoses; the mean (range) monthly sample size was 22.1 (18.4 to 27.1 ) million individuals. While diagnostic category prevalence changed minimally for WHO disease chapters, the ICD-10-CM transition was associated with level changes of 20% or more among 20 of 127 HHS-HCCs (15.7%) and 46 of 282 AHRQ-CCS categories (16.3%) and with trend changes of 20% or more among 12 of 127 of HHS-HCCs (9.4%) and 27 of 282 of AHRQ-CCS categories (9.6%). For HHS-HCCs, monthly rates of individuals with any acute myocardial infarction diagnosis increased 131.5% (95% CI, 124.1% to 138.8%), primarily because HHS added non-ST-segment-elevation myocardial infarction diagnoses to this category. The HHS-HCC for diabetes with chronic complications increased by 92.4% (95% CI, 84.2% to 100.5%), primarily from including new diabetes-related hypoglycemia and hyperglycemia codes, and the rate for completed pregnancy with complications decreased by 54.5% (95% CI, -58.7% to -50.2%) partly due to removing vaginal birth after cesarean delivery as a complication. Conclusions and Relevance:These findings suggest that the ICD-10-CM transition was associated with large prevalence changes for many diagnostic categories. Diagnostic classification systems developed using ICD-9-CM may need to be refined using ICD-10-CM data to avoid unintended consequences for disease surveillance, performance assessment, and risk-adjusted payments.
| S-EPMC7142382 | biostudies-literature
Project description:BackgroundDetermining the accuracy of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9) codes for postpartum hemorrhage (PPH) is vital for reaching valid conclusions about the epidemiology of PPH. Our primary objectives were to assess the performance characteristics of ICD-9 PPH codes against a reference standard using estimated blood loss (EBL) among a cohort undergoing Cesarean delivery.Study design and methodsWe analyzed maternal discharge and EBL data from women who underwent Cesarean delivery at Kaiser Permanente Northern California facilities between 2010 and 2013. We defined PPH as an EBL of at least 1000 mL. In a secondary analysis, ICD-9 performance characteristics were assessed using an EBL of at least 1500 mL to classify severe PPH.ResultsWe identified 35,614 hospitalizations for Cesarean delivery. Using EBL of at least 1000 mL as the "gold standard," PPH codes had a sensitivity of 27.8%, specificity of 97%, positive predictive value (PPV) of 74.5%, and a negative predictive value (NPV) of 80.9%. The prevalence of a PPH code (9%) was lower than the prevalence using a blood loss of at least 1000 mL (24%). Using a reference standard of EBL of at least 1500 mL, PPH codes had a sensitivity of 61.7%, specificity of 93.8%, PPV of 34.2%, and NPV of 97.9%.ConclusionPPH ICD-9 codes have high specificity, moderately high PPVs and NPVs, and low sensitivity. An EBL of at least 1500 mL as a reference standard has higher sensitivity. Our findings suggest that, for women undergoing Cesarean delivery, quality improvement efforts are needed to enhance PPH ICD-9 coding accuracy in administrative data sets.
| S-EPMC5893374 | biostudies-literature
Project description: Not available
| S-EPMC8202141 | biostudies-literature
Project description:BackgroundThe Functional Comorbidity Index (FCI) was developed for community-based adult populations, with function as the outcome. The original FCI was a survey tool, but several International Classification of Diseases (ICD) code lists-for calculating the FCI using administrative data-have been published. However, compatible International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and ICD-10-CM versions have not been available.ObjectiveWe developed ICD-9-CM and ICD-10-CM diagnosis code lists to optimize FCI concordance across ICD lexicons.Research designWe assessed concordance and frequency distributions across ICD lexicons for the FCI and individual comorbidities. We used length of stay and discharge disposition to assess continuity of FCI criterion validity across lexicons.SubjectsState Inpatient Databases from Arizona, Colorado, Michigan, New Jersey, New York, Utah, and Washington State (calendar year 2015) were obtained from the Healthcare Cost and Utilization Project. State Inpatient Databases contained ICD-9-CM diagnoses for the first 3 calendar quarters of 2015 and ICD-10-CM diagnoses for the fourth quarter of 2015. Inpatients under 18 years old were excluded.MeasuresLength of stay and discharge disposition outcomes were assessed in separate regression models. Covariates included age, sex, state, ICD lexicon, and FCI/lexicon interaction.ResultsThe FCI demonstrated stability across lexicons, despite small discrepancies in prevalence for individual comorbidities. Under ICD-9-CM, each additional comorbidity was associated with an 8.9% increase in mean length of stay and an 18.5% decrease in the odds of a routine discharge, compared with an 8.4% increase and 17.4% decrease, respectively, under ICD-10-CM.ConclusionThis study provides compatible ICD-9-CM and ICD-10-CM diagnosis code lists for the FCI.
| S-EPMC7717170 | biostudies-literature