Assessing Pregnancy, Gestational Complications, and Co-morbidities in Women With Congenital Heart Defects (Data from ICD-9-CM Codes in 3 US Surveillance Sites).
Ontology highlight
ABSTRACT:
SUBMITTER: Raskind-Hood C
PROVIDER: S-EPMC7493054 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Objective: Using inpatient data from a 1,160-bed health system, we assessed the positive predictive value (PPV) of ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) codes included in a traumatic brain injury (TBI) surveillance definition proposed by the Centers for Disease Control and Prevention (CDC) in 2016. Methods: A random sample of 196 records with ICD-10-CM TBI codes was reviewed. The PPVs for the ICD-10-CM codes' ability to capture true TBI cases were calculated as the percentage of records with confirmed clinical provider-documented TBI and reported with 95% confidence intervals [95%CIs]. Results: The estimated overall PPV was 74% [67.9%, 80.1%] when the codes were listed in any diagnostic field, but 91.5% [86.2%, 96.8%] when listed as the principal diagnosis. S06 codes (intracranial injury) had an overall PPV of 80.2% [74.3%, 86.1%] and 96.9% [93.3%, 100%] when listed as the principal diagnosis. S02.0-.1 codes (vault/base skull fractures) in any position without co-existing S06 codes had a PPV of 15.8% [0%, 33.2%]. Conclusions: Intracranial injury codes (S06) in any diagnostic position had a very high estimated PPV. Further research is needed to determine the utility of other codes included in the CDC proposed definition for TBI surveillance.
| S-EPMC7808251 | biostudies-literature
Project description:Craniofacial microsomia (CFM) is a congenital condition characterized by microtia and mandibular underdevelopment. Healthcare databases and birth defects surveillance programs could be used to improve knowledge of CFM. However, no specific International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code exists for this condition, which makes standardized data collection challenging. Our aim was to evaluate the validity of existing ICD-9-CM codes to identify individuals with CFM.Study sample eligibility criteria were developed by an expert panel and matched to 11 ICD-9-CM codes. We queried hospital discharge data from two craniofacial centers and identified a total of 12,254 individuals who had ?1 potentially CFM-related code(s). We reviewed all (n = 799) medical records identified at the University of North Carolina (UNC) and 500 randomly selected records at Seattle Children's Hospital (SCH). Individuals were classified as a CFM case or non-case.Thirty-two individuals (6%) at SCH and 93 (12%) at UNC met the CFM eligibility criteria. At both centers, 59% of cases and 95% of non-cases had only one code assigned. At both centers, the most frequent codes were 744.23 (microtia), 754.0 and 756.0 (nonspecific codes), and the code 744.23 had a positive predictive value (PPV) >80% and sensitivity >70%. The code 754.0 had a sensitivity of 3% (PPV <1%) at SCH and 36% (PPV = 5%) at UNC, whereas 756.0 had a sensitivity of 38% (PPV = 5%) at SCH and 18% (PPV = 26%) at UNC.These findings suggest the need for a specific CFM code to facilitate CFM surveillance and research.
| S-EPMC3522759 | biostudies-literature
Project description:BACKGROUND Few studies have validated ICD-9-CM diagnosis codes for surgical site infection (SSI), and none have validated coding for noninfectious wound complications after mastectomy. OBJECTIVES To determine the accuracy of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes in health insurer claims data to identify SSI and noninfectious wound complications, including hematoma, seroma, fat and tissue necrosis, and dehiscence, after mastectomy. METHODS We reviewed medical records for 275 randomly selected women who were coded in the claims data for mastectomy with or without immediate breast reconstruction and had an ICD-9-CM diagnosis code for a wound complication within 180 days after surgery. We calculated the positive predictive value (PPV) to evaluate the accuracy of diagnosis codes in identifying specific wound complications and the PPV to determine the accuracy of coding for the breast surgical procedure. RESULTS The PPV for SSI was 57.5%, or 68.9% if cellulitis-alone was considered an SSI, while the PPV for cellulitis was 82.2%. The PPVs of individual noninfectious wound complications ranged from 47.8% for fat necrosis to 94.9% for seroma and 96.6% for hematoma. The PPVs for mastectomy, implant, and autologous flap reconstruction were uniformly high (97.5%-99.2%). CONCLUSIONS Our results suggest that claims data can be used to compare rates of infectious and noninfectious wound complications after mastectomy across facilities, even though PPVs vary by specific type of postoperative complication. The accuracy of coding was highest for cellulitis, hematoma, and seroma, and a composite group of noninfectious complications (fat necrosis, tissue necrosis, or dehiscence). Infect Control Hosp Epidemiol 2017;38:334-339.
| S-EPMC5490368 | biostudies-literature
Project description:BACKGROUND:The 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). OBJECTIVE:The 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. METHODS:We 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. RESULTS:We 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]). CONCLUSIONS:This 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.
| S-EPMC6911227 | biostudies-literature
Project description:Background:The International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) Injury Severity Score (ICISS) is a risk adjustment model when injuries are recorded using ICD-9-CM coding. The trauma mortality prediction model (TMPM-ICD9) provides better calibration and discrimination compared with ICISS and injury severity score (ISS). Though TMPM-ICD9 is statistically rigorous, it is not precise enough mathematically and has the tendency to overestimate injury severity. The purpose of this study is to develop a new ICD-10-CM injury model which estimates injury severities for every injury in the ICD-10-CM lexicon by a combination of rigorous statistical probit models and mathematical properties and improves the prediction accuracy. Methods:We developed an injury mortality prediction (IMP-ICDX) using data of 794,098 patients admitted to 738 hospitals in the National Trauma Data Bank from 2015 to 2016. Empiric measures of severity for each of the trauma ICD-10-CM codes were estimated using a weighted median death probability (WMDP) measurement and then used as the basis for IMP-ICDX. ISS (version 2005) and the single worst injury (SWI) model were re-estimated. The performance of each of these models was compared by using the area under the receiver operating characteristic (AUC), the Hosmer-Lemeshow (HL) statistic, and the Akaike information criterion statistic. Results:IMP-ICDX exhibits significantly better discrimination (AUCIMP-ICDX, 0.893, and 95% confidence interval (CI), 0.887 to 0.898; AUCISS, 0.853, and 95% CI, 0.846 to 0.860; and AUCSWI, 0.886, and 95% CI, 0.881 to 0.892) and calibration (HLIMP-ICDX, 68, and 95% CI, 36 to 98; HLISS, 252, and 95% CI, 191 to 310; and HLSWI, 92, and 95% CI, 53 to 128) compared with ISS and SWI. All models were improved after the extension of age, gender, and injury mechanism, but the augmented IMP-ICDX still dominated ISS and SWI by every performance. Conclusions:The IMP-ICDX has a better discrimination and calibration compared to ISS. Therefore, we believe that IMP-ICDX could be a new viable trauma research assessment method.
| S-EPMC6787998 | biostudies-literature
Project description:BACKGROUND:Bronchiolitis is a common respiratory disorder in children. Although there are specific ICD-9-CM diagnosis codes for bronchiolitis, the illness is often coded using broader diagnosis codes. This creates the potential for subject misclassification if researchers rely on specific diagnosis codes when assembling retrospective cohorts. Here we challenge the common research practice of relying on specific diagnosis codes for bronchiolitis. METHODS:We examined the use of diagnosis codes for the first episode of bronchiolitis, bronchitis, acute asthma, and bronchospasm and wheezing, in children younger than six and 24 months in the State of California Medic-Aid database. We categorized codes as narrow or broad diagnosis codes. We compared patient, geographic, and temporal characteristics of the different diagnoses codes. RESULTS:We identified visits from 48,732 children for first episode of wheezing illness. We retained 48,269 who had the diagnosis codes and data of interest. Diagnosis codes for acute asthma were widely used, even in children younger than six months in whom a diagnosis code for bronchiolitis would have been anticipated. The temporal pattern was similar across all diagnoses. Antipyretics were prescribed more often in those with diagnosis codes for bronchiolitis and bronchitis. Other statistically significant differences were too small to usefully distinguish the groups. There was substantial geographic variability in the diagnosis codes selected. CONCLUSION:Users of Medic-Aid administrative data should generally favor broad rather than narrow definitions of bronchiolitis and should perform sensitivity analysis comparing broad and narrow definitions.
| S-EPMC6249877 | biostudies-other
Project description:ObjectiveTo develop, test, and validate the performance of ICD-10-CM claims-based case definitions for identifying children with sickle cell anemia (SCA).Data sourcesMedicaid administrative claims (2016) for children <18 years with potential SCA (any D57x diagnosis code) and newborn screening records from Michigan and New York State.Study designThis study is a secondary data analysis.Data collection/extraction methodsUsing specific SCA-related (D5700, D5701, and D5702) and nonspecific (D571) diagnosis codes, 23 SCA case definitions were applied to Michigan Medicaid claims (2016) to identify children with SCA. Measures of performance (sensitivity, specificity, area under the ROC curve) were calculated using newborn screening results as the gold standard. A parallel analysis was conducted using New York State Medicaid claims and newborn screening data.Principal findingsIn Michigan Medicaid, 1597 children had ≥1 D57x claim; 280 (18 percent) were diagnosed with SCA. Measures of performance varied, with sensitivities from 0.02 to 0.97 and specificities from 0.88 to 1.0. The case definition of ≥1 outpatient visit with a SCA-related or D571 code had the highest area under the ROC curve, with a sensitivity of 95 percent and specificity of 92 percent. The same definition also had the highest performance in New York Medicaid (n = 2454), with a sensitivity of 94 percent and specificity of 86 percent.ConclusionsChildren with SCA can be accurately identified in administrative claims using this straightforward case definition. This methodology can be used to monitor trends and use of health services after transition to ICD-10-CM.
| S-EPMC7080376 | biostudies-literature
Project description:BACKGROUND:Validation of administrative databases for cerebrovascular diseases is crucial for epidemiological, outcome, and health services research. The aim of this study was to validate ICD-9 codes for hemorrhagic or ischemic stroke in administrative databases, to use them for a comprehensive assessment of the burden of disease in terms of major outcomes, such as mortality, hospital readmissions, and use of healthcare resources. METHODS:We considered the hospital discharge abstract database of the Umbria Region (890,000 residents). Source population was represented by patients aged >18 discharged from hospital with a diagnosis of hemorrhagic or ischemic stroke between 2012 and 2014 using ICD-9-CM codes in primary position. We randomly selected and reviewed medical charts of cases and non-cases from hospitals. For case ascertainment we considered symptoms and instrumental tests reported in the medical charts. Diagnostic accuracy measures were computed using 2x2 tables. RESULTS:We reviewed 767 medical charts for cases and 78 charts for non-cases. Diagnostic accuracy measures were: subarachnoid hemorrhage: sensitivity (SE) 100% (95% CI: 97%-100%), specificity (SP) 96% (90-99), positive predictive value (PPV) 98% (93-100), negative predictive value (NPV) 100% (95-100); intracerebral hemorrhage: SE 100% (97-100), SP 98% (91-100), PPV 98% (94-100), NPV 100% (95-100); other and unspecified intracranial hemorrhage: SE 100% (97-100), SP 96% (90-99), PPV 98% (93-100), NPV 100% (95-100); ischemic stroke due to occlusion and stenosis of precerebral arteries: SE 99% (94-100), SP 66 (57-75), PPV 70% (61-77), NPV 99% (93-100); occlusion of cerebral arteries: SE 100% (97-100), SP 87% (78-93), PPV 91% (84-95), NPV 100% (95-100); acute, but ill-defined, cerebrovascular disease: SE 100% (97-100), SP 78% (69-86), PPV % 83 (75-89), NPV 100% (95-100). CONCLUSIONS:Case ascertainment for both ischemic and hemorrhagic stroke showed good or high levels of accuracy within the regional healthcare databases in Umbria. This database can confidently be employed for epidemiological, outcome, and health services research related to any type of stroke.
| S-EPMC6952250 | biostudies-literature
Project description:ContextComorbidity measures are designed to exclude complications when they map International Classification of Diseases (ICD-9-CM) codes to diagnostic categories. The use of data fields that indicates whether each secondary diagnosis was present at the time of hospital admission may lead to the more accurate identification of preexisting conditions.ObjectiveTo examine the rate of misclassification of ICD-9-CM codes into diagnostic categories by the Dartmouth-Manitoba adaptation of the Charlson index and by the Elixhauser comorbidity algorithm.Data sourceAnalysis of 178,838 patients in the California State Inpatient Database (CA SID) admitted in 2000 for one of seven major medical and surgical conditions. The CA SID includes a condition present at admission (CPAA) modifier for each ICD-9-CM code.Study designThe Dartmouth/Charlson index and the Elixhauser comorbidity measure were used to map the ICD-9-CM codes into diagnostic categories for patients in each study population. We calculated the misclassification rate for each mapping algorithm, using information from the CPAA as the "gold standard."Principal findingsThe Dartmouth/Charlson index underestimated the prevalence of hemiplegia/paraplegia by 70 percent, cerebrovascular disease by 70 percent, myocardial infarction by 65 percent, congestive heart failure (CHF) by 45 percent, and peptic ulcer disease by 34 percent. The Elixhauser algorithm misclassified complications as preexisting conditions for 43 percent of the coagulopathies, 25 percent of the fluid and electrolyte disorders, 18 percent of the cardiac arrhythmias, 18 percent of the cardiac arrhythmias, and 9 percent of the cases of CHF.ConclusionAdding the CPAA modifier to administrative data would significantly enhance the ability of the Dartmouth/Charlson index and of the Elixhauser algorithm to map ICD-9-CM codes to diagnostic categories accurately.
| S-EPMC1681527 | biostudies-literature
Project description:BACKGROUND:Many public health surveillance programs utilize hospital discharge data in their estimation of disease prevalence. These databases commonly use the International Classification of Diseases (ICD) coding scheme, which transitioned from the ICD-9 clinical modification (ICD-9-CM) to ICD-10-CM on October 1, 2015. This study examined this transition's impact on the prevalence of major birth defects among infant hospitalizations. METHODS:Using data from the Agency for Health Care Research and Quality-sponsored National Inpatient Sample, hospitalizations during the first year of life with a discharge date between January 1, 2012 and December 31, 2016 were used to estimate the monthly national hospital prevalence of 46 birth defects for the ICD-9-CM and ICD-10-CM timeframes separately. Survey-weighted Poisson regression was used to estimate 95% confidence intervals for each hospital prevalence. Interrupted time series framework and corresponding segmented regression was used to estimate the immediate change in monthly hospital prevalence following the ICD-9-CM to ICD-10-CM transition. RESULTS:Between 2012 and 2016, over 21 million inpatient hospitalizations occurred during the first year of life. Among the 46 defects studied, statistically significant decreases in the immediate hospital prevalence of five defects and significant increases in the immediate hospital prevalence of eight defects were observed after the ICD-10-CM transition. CONCLUSIONS:Changes in prevalence were expected based on changes to ICD-10-CM. Observed changes for some conditions may result from variation in monthly hospital prevalence or initial unfamiliarity of coders with ICD-10-CM. These findings may help birth defects surveillance programs evaluate and interpret changes in their data related to the ICD-10-CM transition.
| S-EPMC7194333 | biostudies-literature