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Figure.
Upper extremity musculoskeletal symptoms (UEMSs) (assessed on a visual analog scale [VAS]) as a function of electronic medical record (EMR)–using clinic sessions per week (A) and computer hours per week (B).

Upper extremity musculoskeletal symptoms (UEMSs) (assessed on a visual analog scale [VAS]) as a function of electronic medical record (EMR)–using clinic sessions per week (A) and computer hours per week (B).

1.
Punnett  LWegman  DH Work-related musculoskeletal disorders: the epidemiologic evidence and the debate. J Electromyogr Kinesiol 2004;14 (1) 13- 23
PubMedArticle
2.
Bureau of Labor Statistics, Nonfatal Occupational Injuries and Illnesses Requiring Days Away From Work, 2007.  Washington, DC Bureau of Labor Statistics November20 2008;[reissued in March 2009]
3.
Gerr  FMonteilh  CPMarcus  M Keyboard use and musculoskeletal outcomes among computer users. J Occup Rehabil 2006;16 (3) 265- 277
PubMedArticle
4.
Baldwin  MLButler  RJ Upper extremity disorders in the workplace: costs and outcomes beyond the first return to work. J Occup Rehabil 2006;16 (3) 303- 323
PubMedArticle
5.
Gerr  FMarcus  MEnsor  C  et al.  A prospective study of computer users: I. Study design and incidence of musculoskeletal symptoms and disorders. Am J Ind Med 2002;41 (4) 221- 235
PubMedArticle
6.
Kryger  AIAndersen  JHLassen  CF  et al.  Does computer use pose an occupational hazard for forearm pain; from the NUDATA study. Occup Environ Med 2003;60 (11) e14
PubMedArticle
7.
Gerr  FMarcus  MMonteilh  C Epidemiology of musculoskeletal disorders among computer users: lesson learned from the role of posture and keyboard use. J Electromyogr Kinesiol 2004;14 (1) 25- 31
PubMedArticle
8.
Norman  KNilsson  THagberg  MTornqvist  EWToomingas  A Working conditions and health among female and male employees at a call center in Sweden. Am J Ind Med 2004;46 (1) 55- 62
PubMedArticle
9.
Scalzi  T The VA leads the way in electronic innovations. Nursing 2007;37 (9) 26- 27
PubMedArticle
10.
Gummesson  CWard  MMAtroshi  I The shortened disabilities of the arm, shoulder and hand questionnaire (QuickDASH): validity and reliability based on responses within the full-length DASH. BMC Musculoskelet Disord May18 2006;744
PubMedArticle
11.
Becker  JNora  DBGomes  I  et al.  An evaluation of gender, obesity, age and diabetes mellitus as risk factors for carpal tunnel syndrome. Clin Neurophysiol 2002;113 (9) 1429- 1434
PubMedArticle
12.
Griffiths  KLMackey  MGAdamson  BJ The impact of a computerized work environment on professional occupational groups and behavioural and physiological risk factors for musculoskeletal symptoms: a literature review. J Occup Rehabil 2007;17 (4) 743- 765
PubMedArticle
13.
Marcus  MGerr  FMonteilh  C  et al.  A prospective study of computer users, II: postural risk factors for musculoskeletal symptoms and disorders. Am J Ind Med 2002;41 (4) 236- 249
PubMedArticle
14.
Baum  NJackson  JDrappi  LG Transitioning to an EMR system without pain. J Med Pract Manage 2007;23 (1) 16- 18
PubMed
15.
Shute  N How an electronic medical record can help keep your family healthy. US News World Rep March2009;17
16.
Bhanoo  S Obama: all medical records computerized by 2014. The Industry Standard January12 2009;
Citations 0
Research Letters
Health Care Reform
April 12, 2010

Electronic Medical Records and Upper Extremity Symptoms: Pain With the Gain?

Author Affiliations

Author Affiliations: Departments of Medicine (Drs Golomb, Yaghmai, and Ramsdell and Ms Renvall) and Family and Preventive Medicine (Dr Golomb), University of California, San Diego, School of Medicine, San Diego.

Arch Intern Med. 2010;170(7):655-657. doi:10.1001/archinternmed.2010.55

Upper extremity musculoskeletal symptoms (UEMSs) lead workplace injuries nationwide,1 incur the longest absence among service sector workplace injuries (28 days median, exceeding fractures and amputations),2,3 and can foster multiple spells of lost work time, so that work loss per episode underestimates the impact of UEMSs (by approximately 32% at 5 years).4 Numerous studies link computer use to UEMSs.3,58 However, to our knowledge, whether such symptoms affect physicians practicing at facilities using integrated electronic medical records (EMRs) has not been assessed. We evaluated the prevalence of UEMSs attributed to computer workstation use in 2 medical facilities with different EMR systems.

Methods

A cross-sectional survey assessed work-related computer use and symptoms in primary care clinics at 2 academically affiliated centers in San Diego, California, with distinct EMRs. The US Department of Veterans Affairs (VA) San Diego Healthcare System group converted to the VA CPRS/VISTA EMR9 8 years prior to the survey, and the University of California, San Diego (UCSD) Medical group practice adopted the EpicCare EMR 1 year prior to the survey. Both systems require extensive physician keyboarding and/or mouse clicks. Fifty-nine physicians (87% of those targeted) completed the 20-minute survey. A visual analog scale (VAS) assessed UEMSs attributed to computer use (scale, 0-100), validated against the QuickDash measure of UEMSs, not specific to computer use.10 Demographic variables reported to predict UEMSs (age, sex, and body mass index [BMI] components [weight and height])11 and computer use (EMR-using clinical sessions per week and hours per week of computer use) were elicited, as were institution, years of computer use, and years of EMR use. Bivariable relations of dichotomized VAS scores to categorical variables were assessed by χ2 analysis. Multivariable regression evaluated prediction of UEMSs (continuous VAS) by computer variables, adjusted for UEM predictors of age, sex, and BMI.11 A 2-sided α level of .05 was used to indicate statistical significance. This project was approved by the UCSD Human Research Protection Program & San Diego VA Research Compliance office.

Results

Moderate or severe reported UEMSs attributed to computer use were common: 48% (29 of 59) reported VAS scores of 25 or higher. Mean (SD) VAS was 29 (25) (range, 0-100). The correlation of VAS to QuickDASH was 0.61 (P < .001), supporting convergent and construct validity for VAS.

Electronic medical record–using clinic sessions per week (defined as half-days in clinic) ranged from 1 to 9. A total of 18 clinicians (30%) had 5 or fewer clinic sessions per week, 8 of whom (44%) worked full time.

On bivariable analyses, higher VAS scores related to more EMR-using clinic sessions per week (P = .02) and more computer hours per week (P = .04).Other variables individually, including sex, age, and BMI, as well as institution and years of EMR use and employment, bore no significant relation to dichotomized VAS in this sample, suggesting a more powerful relationship of EMR-using clinic sessions or computer hours than other potential UEMS predictors.

The prediction of UEMSs by computer hours per week and particularly by EMR-using clinic sessions per week was preserved or strengthened in analysis adjusted for age, sex, and BMI (computer hours per week: β = 13.9, SE = 6.48 [P = .04]; EMR-using clinic sessions per week: β = 4.30, SE = 1.56 [P = .008]) (Figure).

Comment

High prevalence of UEMSs attributed to EMR use was reported among physicians at 2 facilities with integrated EMRs. Economic and personal losses arise irrespective of employment type, but “costs” from UEMS disability are arguably amplified for physicians by the investment years of education required to practice medicine.

Our findings parallel those for nonphysician computer users: indeed, UEMSs are an emerging concern in professional occupations.12 More than half of computer users reported musculoskeletal symptoms during the first year after starting a job.5 One review found that the most consistent predictor was hours keying.3 However, mouse use may more strongly predict UEMS development.6,13 The apparently stronger association to UEMSs of EMR-using clinic sessions per week (vs computer hours per week) might be speculated to reflect relatively high mousing requirements of EMR systems during patient-relevant activities and/or reduced discretionary (nonclinic) computer use among those with UEMSs. Future studies may evaluate whether modifications of EMR systems to minimize mouse use reduce the risk of clinic session–associated UEMSs.

The generalizability of findings must await replication in other settings; however, findings were consistent across 2 physician groups with distinct EMRs. Our findings may underreflect the true impact, since prior injury and work modification were not captured and reduced clinic sessions engendered by UEMSs may produce strong bias to the null. (We are aware that at least 4 physicians received surgery, had clinic reductions, and/or used specialized voice/foot pedal–operated workstations because of UEMSs.)

Ergonomics have received little attention in discussions of EMR implementation. (“Transitioning to an EMR System Without Pain”14 refers to protection against figurative rather than literal discomfort.) This is perhaps ironic because health care institutions are in the business of understanding risk factors for, and promoting prophylaxis against, illness and injury.

To our knowledge, ours is the first assessment of this issue for physicians. If high rates of UEMSs among physicians using EMRs are replicated and extend to other settings, the impact of physician symptoms and disability on health-related quality of life, work time lost, patient care continuity, and costs for health care institutions warrant assessment. Proactive attention to ergonomics may be merited, as integrated EMRs are increasingly adopted at health care institutions.

These findings are timely, given the current efforts, extending to the presidential level, to hasten nationalized implementation of EMRs.15,16

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Article Information

Correspondence: Dr Golomb, Department of Medicine, University of California, San Diego, 9500 Gilman Dr, MC 0995, La Jolla, CA 92093-0995 (bgolomb@ucsd.edu).

Author Contributions:Study concept and design: Yaghmai and Ramsdell. Acquisition of data: Yaghmai and Ramsdell. Analysis and interpretation of data: Golomb, Yaghmai, Renvall, and Ramsdell. Drafting of the manuscript: Golomb and Renvall. Critical revision of the manuscript for important intellectual content: Yaghmai, Ramsdell. Statistical analysis: Golomb, Yaghmai, and Renvall. Administrative, technical, and material support: Golomb and Ramsdell. Study supervision: Ramsdell.

Financial Disclosure: None reported.

Previous Presentations: A poster of this study was presented at the Society of General Internal Medicine annual meeting, April 25-28, 2007; Toronto, Ontario, Canada.

Additional Contributions: Sabrina Koperski provided excellent editorial and administrative assistance. We thank the physicians who kindly took the time to complete the survey.

References
1.
Punnett  LWegman  DH Work-related musculoskeletal disorders: the epidemiologic evidence and the debate. J Electromyogr Kinesiol 2004;14 (1) 13- 23
PubMedArticle
2.
Bureau of Labor Statistics, Nonfatal Occupational Injuries and Illnesses Requiring Days Away From Work, 2007.  Washington, DC Bureau of Labor Statistics November20 2008;[reissued in March 2009]
3.
Gerr  FMonteilh  CPMarcus  M Keyboard use and musculoskeletal outcomes among computer users. J Occup Rehabil 2006;16 (3) 265- 277
PubMedArticle
4.
Baldwin  MLButler  RJ Upper extremity disorders in the workplace: costs and outcomes beyond the first return to work. J Occup Rehabil 2006;16 (3) 303- 323
PubMedArticle
5.
Gerr  FMarcus  MEnsor  C  et al.  A prospective study of computer users: I. Study design and incidence of musculoskeletal symptoms and disorders. Am J Ind Med 2002;41 (4) 221- 235
PubMedArticle
6.
Kryger  AIAndersen  JHLassen  CF  et al.  Does computer use pose an occupational hazard for forearm pain; from the NUDATA study. Occup Environ Med 2003;60 (11) e14
PubMedArticle
7.
Gerr  FMarcus  MMonteilh  C Epidemiology of musculoskeletal disorders among computer users: lesson learned from the role of posture and keyboard use. J Electromyogr Kinesiol 2004;14 (1) 25- 31
PubMedArticle
8.
Norman  KNilsson  THagberg  MTornqvist  EWToomingas  A Working conditions and health among female and male employees at a call center in Sweden. Am J Ind Med 2004;46 (1) 55- 62
PubMedArticle
9.
Scalzi  T The VA leads the way in electronic innovations. Nursing 2007;37 (9) 26- 27
PubMedArticle
10.
Gummesson  CWard  MMAtroshi  I The shortened disabilities of the arm, shoulder and hand questionnaire (QuickDASH): validity and reliability based on responses within the full-length DASH. BMC Musculoskelet Disord May18 2006;744
PubMedArticle
11.
Becker  JNora  DBGomes  I  et al.  An evaluation of gender, obesity, age and diabetes mellitus as risk factors for carpal tunnel syndrome. Clin Neurophysiol 2002;113 (9) 1429- 1434
PubMedArticle
12.
Griffiths  KLMackey  MGAdamson  BJ The impact of a computerized work environment on professional occupational groups and behavioural and physiological risk factors for musculoskeletal symptoms: a literature review. J Occup Rehabil 2007;17 (4) 743- 765
PubMedArticle
13.
Marcus  MGerr  FMonteilh  C  et al.  A prospective study of computer users, II: postural risk factors for musculoskeletal symptoms and disorders. Am J Ind Med 2002;41 (4) 236- 249
PubMedArticle
14.
Baum  NJackson  JDrappi  LG Transitioning to an EMR system without pain. J Med Pract Manage 2007;23 (1) 16- 18
PubMed
15.
Shute  N How an electronic medical record can help keep your family healthy. US News World Rep March2009;17
16.
Bhanoo  S Obama: all medical records computerized by 2014. The Industry Standard January12 2009;
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