Literature DB >> 34975359

CHDA CERTIFICATION EXAM SUCCESS FACTORS.

Renae Spohn, William Schweinle Iii, Carole South-Winter, David DeJong.   

Abstract

This study explored possible success factors for passing the Certified Health Data Analyst Administration (CHDA) certification exam. According to the American Health Information Management Association (AHIMA), in 2019, only 10 percent of first-time test-takers passed the CHDA exam. Literature review offered insight into factors related to passing certification exams. Sources included existing, relevant peer-reviewed, and published literature since 1990 within 87 educational and health/medicine databases and 62 other articles and journal databases available at the University of South Dakota library. A correlational design was used in the study. Data was retrieved from AHIMA, cleaned, and data analysis was completed using binary logistic regression analysis. The CHDA study results indicate that candidates between ages 30 and 49 are less likely to pass the exam than those ages 50 and above, and those candidates with a master's degree are more likely to pass the exam than those with an associate or bachelor's degree. This new information will help improve the exam pass rates, provide a foundation for CHDA exam research, and add new knowledge in the HIM professional body of research.
Copyright © 2021 by the American Health Information Management Association.

Entities:  

Keywords:  certification exam success factors; certified health data analyst; health information management

Mesh:

Year:  2021        PMID: 34975359      PMCID: PMC8649699     

Source DB:  PubMed          Journal:  Perspect Health Inf Manag        ISSN: 1559-4122


  13 in total

1.  NCLEX-RN performance: predicting success on the computerized examination.

Authors:  P B Beeman; J K Waterhouse
Journal:  J Prof Nurs       Date:  2001 Jul-Aug       Impact factor: 2.104

2.  The in-service examination score as a predictor of success on the American Board of Preventive Medicine certification examination.

Authors:  Sheryl A Bedno; Michele A Soltis; James D Mancuso; Daniel G Burnett; Timothy M Mallon
Journal:  Am J Prev Med       Date:  2011-12       Impact factor: 5.043

3.  An Electronic Health Record-Based Real-Time Analytics Program For Patient Safety Surveillance And Improvement.

Authors:  David Classen; Michael Li; Suzanne Miller; Drew Ladner
Journal:  Health Aff (Millwood)       Date:  2018-11       Impact factor: 6.301

4.  G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences.

Authors:  Franz Faul; Edgar Erdfelder; Albert-Georg Lang; Axel Buchner
Journal:  Behav Res Methods       Date:  2007-05

5.  Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

Authors:  Franz Faul; Edgar Erdfelder; Axel Buchner; Albert-Georg Lang
Journal:  Behav Res Methods       Date:  2009-11

Review 6.  A review of dashboards for data analytics in nursing.

Authors:  Bryan A Wilbanks; Patsy A Langford
Journal:  Comput Inform Nurs       Date:  2014-11       Impact factor: 1.985

7.  The Odds of Success: Predicting Registered Health Information Administrator Exam Success.

Authors:  Diane Dolezel; Alexander McLeod
Journal:  Perspect Health Inf Manag       Date:  2017-01-01

8.  Unlocking Big Data for better health.

Authors:  Steven Munevar
Journal:  Nat Biotechnol       Date:  2017-07-12       Impact factor: 54.908

9.  Can Big Data Deliver on Its Promises?-Leaps but Not Bounds.

Authors:  Ithan D Peltan; Sarah J Beesley; Samuel M Brown
Journal:  JAMA Netw Open       Date:  2018-12-07

10.  Relationship of residency program characteristics with pass rate of the American Board of Internal Medicine certifying exam.

Authors:  Amporn Atsawarungruangkit
Journal:  Med Educ Online       Date:  2015-09-29
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