Objective: To develop, test, and validate the performance of ICD-10-CM claims-based case definitions for identifying children with sickle cell anemia (SCA).
Data Sources: Medicaid 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 Design: This study is a secondary data analysis.
Data Collection/extraction Methods: Using 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 Findings: In 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.
Conclusions: Children 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.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080376 | PMC |
http://dx.doi.org/10.1111/1475-6773.13257 | DOI Listing |
Objectives: To describe the epidemiology, patient characteristics and comorbidities in patients with Wilson disease (WD) in the USA.
Design: Retrospective, population-based study.
Setting: The study used the US Komodo claims database containing records regarding medical claims for over 120 million individuals.
BMC Med Inform Decis Mak
January 2025
Higher Institute of Medical Technology, Yaoundé, Cameroon.
Background: In Cameroon, like in many other resource-limited countries, data generated by health settings including morbidity and mortality parameters are not always uniform. In the absence of a national guideline necessary for the standardization and harmonization of data, precision of data required for effective decision-making is therefore not guaranteed. The objective of the present study was to assess the reporting style of morbidity and mortality data in healthcare settings.
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
Pathology Department, Beijing Youan Hospital, Capital Medical University, Beijing, 100000, China.
In the context of chronic liver diseases, where variability in progression necessitates early and precise diagnosis, this study addresses the limitations of traditional histological analysis and the shortcomings of existing deep learning approaches. A novel patch-level classification model employing multi-scale feature extraction and fusion was developed to enhance the grading accuracy and interpretability of liver biopsies, analyzing 1322 cases across various staining methods. The study also introduces a slide-level aggregation framework, comparing different diagnostic models, to efficiently integrate local histological information.
View Article and Find Full Text PDFSchizophr Bull
January 2025
Orygen, Parkville, Victoria 3052, Australia.
Background: Although attention deficit hyperactivity disorder (ADHD) is known to be common in psychotic disorders, reported prevalence rates vary widely, with limited understanding of how different factors (eg, assessment methods, geographical region) may be associated with this variation. The aim was to conduct a systematic review and meta-analysis to determine the prevalence of ADHD in psychotic disorders and factors associated with the variability in reported rates.
Study Design: Searches were conducted in MEDLINE, Embase, PsycINFO, CINAHL, and Scopus in May 2023.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!