Literature DB >> 22561713

Efficiency of International Classification of Diseases, Ninth Revision, billing code searches to identify emergency department visits for blood or body fluid exposures through a statewide multicenter database.

Lisa M Rosen1, Tao Liu, Roland C Merchant.   

Abstract

BACKGROUND: Blood and body fluid exposures are frequently evaluated in emergency departments (EDs). However, efficient and effective methods for estimating their incidence are not yet established.
OBJECTIVE: Evaluate the efficiency and accuracy of estimating statewide ED visits for blood or body fluid exposures using International Classification of Diseases, Ninth Revision (ICD-9), code searches.
DESIGN: Secondary analysis of a database of ED visits for blood or body fluid exposure.
SETTING: EDs of 11 civilian hospitals throughout Rhode Island from January 1, 1995, through June 30, 2001. PATIENTS: Patients presenting to the ED for possible blood or body fluid exposure were included, as determined by prespecified ICD-9 codes.
METHODS: Positive predictive values (PPVs) were estimated to determine the ability of 10 ICD-9 codes to distinguish ED visits for blood or body fluid exposure from ED visits that were not for blood or body fluid exposure. Recursive partitioning was used to identify an optimal subset of ICD-9 codes for this purpose. Random-effects logistic regression modeling was used to examine variations in ICD-9 coding practices and styles across hospitals. Cluster analysis was used to assess whether the choice of ICD-9 codes was similar across hospitals.
RESULTS: The PPV for the original 10 ICD-9 codes was 74.4% (95% confidence interval [CI], 73.2%-75.7%), whereas the recursive partitioning analysis identified a subset of 5 ICD-9 codes with a PPV of 89.9% (95% CI, 88.9%-90.8%) and a misclassification rate of 10.1%. The ability, efficiency, and use of the ICD-9 codes to distinguish types of ED visits varied across hospitals.
CONCLUSIONS: Although an accurate subset of ICD-9 codes could be identified, variations across hospitals related to hospital coding style, efficiency, and accuracy greatly affected estimates of the number of ED visits for blood or body fluid exposure.

Entities:  

Mesh:

Year:  2012        PMID: 22561713      PMCID: PMC5065064          DOI: 10.1086/665722

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  21 in total

1.  Identification and validation of lupus nephritis cases using administrative data.

Authors:  L B Chibnik; E M Massarotti; K H Costenbader
Journal:  Lupus       Date:  2010-02-23       Impact factor: 2.911

2.  Evaluation of factors influencing accuracy of principal procedure coding based on ICD-9-CM: an Iranian study.

Authors:  Mehrdad Farzandipour; Abbas Sheikhtaheri
Journal:  Perspect Health Inf Manag       Date:  2009-05-07

3.  Positive predictive value of ICD-9 codes 410 and 411 in the identification of cases of acute coronary syndromes in the Saskatchewan Hospital automated database.

Authors:  Cristina Varas-Lorenzo; Jordi Castellsague; Mary Rose Stang; Luis Tomas; Jaume Aguado; Susana Perez-Gutthann
Journal:  Pharmacoepidemiol Drug Saf       Date:  2008-08       Impact factor: 2.890

4.  ICD-9-CM classification coding in psychiatry.

Authors:  P M Dingemans
Journal:  J Clin Psychol       Date:  1990-03

5.  Measuring diagnoses: ICD code accuracy.

Authors:  Kimberly J O'Malley; Karon F Cook; Matt D Price; Kimberly Raiford Wildes; John F Hurdle; Carol M Ashton
Journal:  Health Serv Res       Date:  2005-10       Impact factor: 3.402

6.  Blood or body fluid exposures and HIV postexposure prophylaxis utilization among first responders.

Authors:  Roland C Merchant; Jacob E Nettleton; Kenneth H Mayer; Bruce M Becker
Journal:  Prehosp Emerg Care       Date:  2009 Jan-Mar       Impact factor: 3.077

7.  Predictors of the initiation of HIV postexposure prophylaxis in Rhode Island emergency departments.

Authors:  Roland C Merchant; Kenneth H Mayer; Bruce M Becker; Allison K Delong; Joseph W Hogan
Journal:  AIDS Patient Care STDS       Date:  2008-01       Impact factor: 5.078

8.  Adult sexual assault evaluations at Rhode Island emergency departments, 1995-2001.

Authors:  Roland C Merchant; Tse Chiang Lau; Tao Liu; Kenneth H Mayer; Bruce M Becker
Journal:  J Urban Health       Date:  2008-09-17       Impact factor: 3.671

9.  Intraobserver and interobserver agreement of International Classification of Diseases, Ninth Revision codes in classifying shoulder instability.

Authors:  Thomas W Throckmorton; Warren Dunn; Tara Holmes; John E Kuhn
Journal:  J Shoulder Elbow Surg       Date:  2008-12-19       Impact factor: 3.019

10.  ICD-9-CM coding of emergency department visits for food and insect sting allergy.

Authors:  Sunday Clark; Theodore J Gaeta; Geeta S Kamarthi; Carlos A Camargo
Journal:  Ann Epidemiol       Date:  2006-03-03       Impact factor: 3.797

View more
  2 in total

1.  Combining structured and unstructured data to identify a cohort of ICU patients who received dialysis.

Authors:  Swapna Abhyankar; Dina Demner-Fushman; Fiona M Callaghan; Clement J McDonald
Journal:  J Am Med Inform Assoc       Date:  2014-01-02       Impact factor: 4.497

2.  Use of the International Classification of Diseases, 9th revision, coding in identifying chronic hepatitis B virus infection in health system data: implications for national surveillance.

Authors:  Reena Mahajan; Anne C Moorman; Stephen J Liu; Loralee Rupp; R Monina Klevens
Journal:  J Am Med Inform Assoc       Date:  2013-03-05       Impact factor: 4.497

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.