Data and Edits in Healthcare Information Management

Article ID

41943

Data and Edits in Healthcare Information Management

Sajeesh Kumar
Sajeesh Kumar University of Tennessee Health Science Center
DOI

Abstract

This studydetermine which job function causes or creates a large number of Edit/ Data Overwrites within health care. The study is based on data extracted from the Monthly Reports reported by the Team staff. Out of the 2736 Potential Identity Changes, 115 actually resulted in a CE. The number of CEs created by each job title ranged from 1% by Employee Health Clerk to 28% by Eligibility Clerk. Out of the 115 CEs created, a total of 32 were created by the Eligibility Clerks. The next highest job title was the Enrollment/Registration Clerks with 21 CEs created. Of the 4% of CEs reported, Eligibility Clerks created 28% of those CEs and Enrollment/Registration Clerks created 18% of CEs reported during this time period. The findings provide insight to thestaff as well as other managers for the users who need additional training or realignment in the workflow. Further work is required to expand and identify factors contributing to incidents causing CEs.

Data and Edits in Healthcare Information Management

This studydetermine which job function causes or creates a large number of Edit/ Data Overwrites within health care. The study is based on data extracted from the Monthly Reports reported by the Team staff. Out of the 2736 Potential Identity Changes, 115 actually resulted in a CE. The number of CEs created by each job title ranged from 1% by Employee Health Clerk to 28% by Eligibility Clerk. Out of the 115 CEs created, a total of 32 were created by the Eligibility Clerks. The next highest job title was the Enrollment/Registration Clerks with 21 CEs created. Of the 4% of CEs reported, Eligibility Clerks created 28% of those CEs and Enrollment/Registration Clerks created 18% of CEs reported during this time period. The findings provide insight to thestaff as well as other managers for the users who need additional training or realignment in the workflow. Further work is required to expand and identify factors contributing to incidents causing CEs.

Sajeesh Kumar
Sajeesh Kumar University of Tennessee Health Science Center

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Sajeesh Kumar. 2015. “. Global Journal of Medical Research – K: Interdisciplinary GJMR-K Volume 15 (GJMR Volume 15 Issue K2): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjmra

Print ISSN 0975-5888

e-ISSN 2249-4618

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GJMR-K Classification: NLMC Code: QT 180
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Data and Edits in Healthcare Information Management

Sajeesh Kumar
Sajeesh Kumar University of Tennessee Health Science Center

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