Literature DB >> 28566986

Differences in Sociocognitive Beliefs between Involved and Noninvolved Employees during the Implementation of an Electronic Health Record System.

Nicola Esther Stanczyk1, Rik Crutzen2, Nikki Sewuster1, Elwin Schotanus1, Merijn Mulders1, Henricus Paul Cremers1.   

Abstract

BACKGROUND: Electronic health records (EHRs) can improve quality and efficiency in patient care. However, the intention to work with such a new system is often relatively low among employees because the work processes of the healthcare organization may change. Involving employees in an EHR implementation may increase their beliefs and perceived capabilities concerning the new system. The current study aimed to assess the role of involvement and its effects on sociocognitive beliefs regarding the implementation of a new EHR system.
METHODS: The study was performed in June 2015 among all eligible employees of a hospital in the Netherlands. Both involved and noninvolved employees were invited to complete a paper-based questionnaire concerning their sociocognitive beliefs (i.e., attitude, social influence, self-efficacy, and intention) related to the EHR implementation. Independent sample t-tests were used to assess potential differences in sociocognitive beliefs between employees who were involved in the implementation process and those who were not. Effect sizes (Cohen's d) were calculated to indicate the standardized difference between the means.
RESULTS: A total of 359 participants completed the paper-based questionnaire and were included in the analyses. Involved employees (n = 94) reported significantly higher levels of attitude (p < .001, d = .62), perceived self-efficacy (p = .01, d = .31), social support (p < .001, d = .68), and a higher intention to work with the new EHR system (p < .001, d = .60), compared with the group of employees who were not involved in the implementation process (n = 265).
CONCLUSION: Involving employees during an EHR implementation appears to enhance employees' sociocognitive beliefs and increases their intention to work with the new system.

Entities:  

Keywords:  electronic health record; implementation; intention; sociocognitive beliefs

Mesh:

Year:  2017        PMID: 28566986      PMCID: PMC5430131     

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


  30 in total

1.  Scale quality: alpha is an inadequate estimate and factor-analytic evidence is needed first of all.

Authors:  Rik Crutzen; Gjalt-Jorn Ygram Peters
Journal:  Health Psychol Rev       Date:  2015-12-28

2.  Electronic health records documentation in nursing: nurses' perceptions, attitudes, and preferences.

Authors:  Linda E Moody; Elaine Slocumb; Bruce Berg; Donna Jackson
Journal:  Comput Inform Nurs       Date:  2004 Nov-Dec       Impact factor: 1.985

Review 3.  Development and initial validation of an instrument to measure physicians' use of, knowledge about, and attitudes toward computers.

Authors:  R D Cork; W M Detmer; C P Friedman
Journal:  J Am Med Inform Assoc       Date:  1998 Mar-Apr       Impact factor: 4.497

4.  The association between EHRs and care coordination varies by team cohesion.

Authors:  Ilana Graetz; Mary Reed; Stephen M Shortell; Thomas G Rundall; Jim Bellows; John Hsu
Journal:  Health Serv Res       Date:  2013-12-21       Impact factor: 3.402

Review 5.  Health information systems - past, present, future.

Authors:  Reinhold Haux
Journal:  Int J Med Inform       Date:  2005-09-19       Impact factor: 4.046

6.  Factors in medical student beliefs about electronic health record use.

Authors:  Christopher A Harle; Laura A Gruber; Marvin A Dewar
Journal:  Perspect Health Inf Manag       Date:  2014-01-01

7.  Effect of a multifaceted intervention on documentation of vital signs and staff communication regarding deteriorating paediatric patients.

Authors:  Heather McKay; Imogen A Mitchell; Kam Sinn; Heather Mugridge; Tony Lafferty; Chris Van Leuvan; Sarah Mamootil; Mohamed E Abdel-Latif
Journal:  J Paediatr Child Health       Date:  2012-12-02       Impact factor: 1.954

8.  EHR-based Visualization Tool: Adoption Rates, Satisfaction, and Patient Outcomes.

Authors:  Randi E Foraker; Bobbie Kite; Marjorie M Kelley; Albert M Lai; Caryn Roth; Marcelo A Lopetegui; Abigail B Shoben; Michael Langan; Nicole L Rutledge; Philip R O Payne
Journal:  EGEMS (Wash DC)       Date:  2015-06-18

Review 9.  Barriers to implement Electronic Health Records (EHRs).

Authors:  Sima Ajami; Razieh Arab-Chadegani
Journal:  Mater Sociomed       Date:  2013

10.  The effect of electronic health records adoption on patient visit volume at an academic ophthalmology department.

Authors:  Jocelyn G Lam; Bryan S Lee; Philip P Chen
Journal:  BMC Health Serv Res       Date:  2016-01-13       Impact factor: 2.655

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.