EHR satisfaction: User characteristics matter

Family Practice Management

Volumn 17, Issue 4, 2010, Pages 22-25

  Adler, Kenneth G ^a,b   Shields, Joel ^c   Edsall, Robert L ^b  

^a Family Practice Management Board ^*

^b Family Practice Management Board   (United States)

^c AMERICAN ACADEMY OF FAMILY PHYSICIANS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYSIS OF VARIANCE; ARTICLE; COMPUTER INTERFACE; CONFIDENCE INTERVAL; ELECTRONIC MEDICAL RECORD; EVALUATION; HEALTH CARE SURVEY; HUMAN; JOB SATISFACTION; MANAGEMENT; ORGANIZATION AND MANAGEMENT; PRODUCTIVITY; STATISTICAL MODEL; STATISTICS;

ANALYSIS OF VARIANCE; CONFIDENCE INTERVALS; EFFICIENCY; EFFICIENCY, ORGANIZATIONAL; HEALTH CARE SURVEYS; HUMANS; JOB SATISFACTION; LINEAR MODELS; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; PRACTICE MANAGEMENT, MEDICAL; STATISTICS AS TOPIC; USER-COMPUTER INTERFACE;

EID: 85048354342     PISSN: 10695648     EISSN: 15311929     Source Type: Journal    
DOI: None     Document Type: Article

References (5)

1. Edsall RL, Adler KG. An EHR user-satisfaction survey: advice from 408 family physicians. Fam Pract Manag. October 2005:29-35. http://www.aafp.org/fpm/2005/1000/p29.html.
2. Edsall RL, Adler KG. User satisfaction with EHRs: report of a survey of 422 family physicians. Fam Pract Manag. February 2008:25-32. http://www.aafp.org/fpm/2008/0200/p25.html.
3. Edsall RL, Adler KG. The 2009 EHR user satisfaction survey: responses from 2,012 family physicians. Fam Pract Manag. November/December 2009:10-16. http://www.aafp.org/fpm/2009/1100/p10.html.
4. Adler KG, Edsall RL. The third FPM survey of user satisfaction with EHR systems. Fam Pract Manag. May/June 2009:12-14. http://www.aafp.org/fpm/2009/0500/p12.html.
5. Given that covariation was a concern in the initial bivariate analyses, a diagnostic tool known as the variance inflation factor (VIF) was used to determine whether or not the regression model had any problems in that regard. Generally, problems with collinearity are indicated by a VIF of 4 or greater on the predictor variables. Our model's VIFs ranged from 1.12 to 2.024, suggesting that collinearity was not a problem within the regression model.