LONG-TERM ADAPTATION OF THE INTRODUCTION OF A MEDICAL INFORMATION SYSTEM.

M. A. Counte; K. H. Kjerulff; J. C. Salloway; B. C. Campbell

LONG-TERM ADAPTATION OF THE INTRODUCTION OF A MEDICAL INFORMATION SYSTEM.

M. A. Counte, K. H. Kjerulff, J. C. Salloway, B. C. Campbell

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The authors contrast variables that affect employee responses to a medical information system (MIS) six months vs. one year postimplementation. Data were collected from 45 employees who remained in the panel for 15 months. Multiple regression techniques were used to model factors that significantly influence variability in adaptation. Most of the independent variables that were previously demonstrated to influence short-term reactions were also important when examined six months later. In particular, personality traits, educational level, job mobility, age, and work shift appear to be key explanatory variables.

Original language	English (US)
Title of host publication	Proceedings - Annual Symposium on Computer Applications in Medical Care
Editors	Michael J. Ackerman
Publisher	IEEE
Pages	414-417
Number of pages	4
ISBN (Print)	0818606479
State	Published - 1985

Publication series

Name	Proceedings - Annual Symposium on Computer Applications in Medical Care
ISSN (Print)	0195-4210

All Science Journal Classification (ASJC) codes

General Engineering

Cite this

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title = "LONG-TERM ADAPTATION OF THE INTRODUCTION OF A MEDICAL INFORMATION SYSTEM.",

abstract = "The authors contrast variables that affect employee responses to a medical information system (MIS) six months vs. one year postimplementation. Data were collected from 45 employees who remained in the panel for 15 months. Multiple regression techniques were used to model factors that significantly influence variability in adaptation. Most of the independent variables that were previously demonstrated to influence short-term reactions were also important when examined six months later. In particular, personality traits, educational level, job mobility, age, and work shift appear to be key explanatory variables.",

author = "Counte, {M. A.} and Kjerulff, {K. H.} and Salloway, {J. C.} and Campbell, {B. C.}",

year = "1985",

language = "English (US)",

isbn = "0818606479",

series = "Proceedings - Annual Symposium on Computer Applications in Medical Care",

publisher = "IEEE",

pages = "414--417",

editor = "Ackerman, {Michael J.}",

booktitle = "Proceedings - Annual Symposium on Computer Applications in Medical Care",

}

LONG-TERM ADAPTATION OF THE INTRODUCTION OF A MEDICAL INFORMATION SYSTEM. / Counte, M. A.; Kjerulff, K. H.; Salloway, J. C. et al.
Proceedings - Annual Symposium on Computer Applications in Medical Care. ed. / Michael J. Ackerman. IEEE, 1985. p. 414-417 (Proceedings - Annual Symposium on Computer Applications in Medical Care).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - LONG-TERM ADAPTATION OF THE INTRODUCTION OF A MEDICAL INFORMATION SYSTEM.

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AU - Kjerulff, K. H.

AU - Salloway, J. C.

AU - Campbell, B. C.

PY - 1985

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N2 - The authors contrast variables that affect employee responses to a medical information system (MIS) six months vs. one year postimplementation. Data were collected from 45 employees who remained in the panel for 15 months. Multiple regression techniques were used to model factors that significantly influence variability in adaptation. Most of the independent variables that were previously demonstrated to influence short-term reactions were also important when examined six months later. In particular, personality traits, educational level, job mobility, age, and work shift appear to be key explanatory variables.

AB - The authors contrast variables that affect employee responses to a medical information system (MIS) six months vs. one year postimplementation. Data were collected from 45 employees who remained in the panel for 15 months. Multiple regression techniques were used to model factors that significantly influence variability in adaptation. Most of the independent variables that were previously demonstrated to influence short-term reactions were also important when examined six months later. In particular, personality traits, educational level, job mobility, age, and work shift appear to be key explanatory variables.

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T3 - Proceedings - Annual Symposium on Computer Applications in Medical Care

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PB - IEEE

ER -

LONG-TERM ADAPTATION OF THE INTRODUCTION OF A MEDICAL INFORMATION SYSTEM.

Abstract

Publication series

All Science Journal Classification (ASJC) codes

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