Electronic Health Record Alert-Related Workload As a Predictor of Burnout in Primary Care Providers

Overview

Journal Appl Clin Inform

Publisher Thieme

Specialties Health Services
Medical Informatics

Date 2017 Jul 6

PMID 28678892

Citations 80

Authors

Megan E Gregory

Elise Russo

Hardeep Singh

Affiliations

Soon will be listed here.

Abstract

Background: Electronic health records (EHRs) have been shown to increase physician workload. One EHR feature that contributes to increased workload is asynchronous alerts (also known as inbox notifications) related to test results, referral responses, medication refill requests, and messages from physicians and other health care professionals. This alert-related workload results in negative cognitive outcomes, but its effect on affective outcomes, such as burnout, has been understudied.

Objectives: To examine EHR alert-related workload (both objective and subjective) as a predictor of burnout in primary care providers (PCPs), in order to ultimately inform interventions aimed at reducing burnout due to alert workload.

Methods: A cross-sectional questionnaire and focus group of 16 PCPs at a large medical center in the southern United States.

Results: Subjective, but not objective, alert workload was related to two of the three dimensions of burnout, including physical fatigue (p = 0.02) and cognitive weariness (p = 0.04), when controlling for organizational tenure. To reduce alert workload and subsequent burnout, participants indicated a desire to have protected time for alert management, fewer unnecessary alerts, and improvements to the EHR system.

Conclusions: Burnout associated with alert workload may be in part due to subjective differences at an individual level, and not solely a function of the objective work environment. This suggests the need for both individual and organizational-level interventions to improve alert workload and subsequent burnout. Additional research should confirm these findings in larger, more representative samples.

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References

Buchbinder S, Wilson M, Melick C, Powe N . Estimates of costs of primary care physician turnover. Am J Manag Care. 2000; 5(11):1431-8. View

Shanafelt T, Dyrbye L, Sinsky C, Hasan O, Satele D, Sloan J . Relationship Between Clerical Burden and Characteristics of the Electronic Environment With Physician Burnout and Professional Satisfaction. Mayo Clin Proc. 2016; 91(7):836-48. DOI: 10.1016/j.mayocp.2016.05.007. View

Shanafelt T, Boone S, Tan L, Dyrbye L, Sotile W, Satele D . Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med. 2012; 172(18):1377-85. DOI: 10.1001/archinternmed.2012.3199. View

Maslach C, Schaufeli W, Leiter M . Job burnout. Annu Rev Psychol. 2001; 52:397-422. DOI: 10.1146/annurev.psych.52.1.397. View

Singh H, Wilson L, Reis B, Sawhney M, Espadas D, Sittig D . Ten strategies to improve management of abnormal test result alerts in the electronic health record. J Patient Saf. 2010; 6(2):121-3. PMC: 2885732. DOI: 10.1097/PTS.0b013e3181ddf652. View

Thomas N . Resident burnout. JAMA. 2004; 292(23):2880-9. DOI: 10.1001/jama.292.23.2880. View

Hall L, Johnson J, Watt I, Tsipa A, OConnor D . Healthcare Staff Wellbeing, Burnout, and Patient Safety: A Systematic Review. PLoS One. 2016; 11(7):e0159015. PMC: 4938539. DOI: 10.1371/journal.pone.0159015. View

Brill P . The need for an operational definition of burnout. Fam Community Health. 1984; 6(4):12-24. DOI: 10.1097/00003727-198402000-00005. View

Simon S, Kaushal R, Cleary P, Jenter C, Volk L, Poon E . Correlates of electronic health record adoption in office practices: a statewide survey. J Am Med Inform Assoc. 2006; 14(1):110-7. PMC: 2215070. DOI: 10.1197/jamia.M2187. View

10.

Toker S, Biron M . Job burnout and depression: unraveling their temporal relationship and considering the role of physical activity. J Appl Psychol. 2012; 97(3):699-710. DOI: 10.1037/a0026914. View

11.

Hoonakker P, Carayon P, Gurses A, Brown R, McGuire K, Khunlertkit A . MEASURING WORKLOAD OF ICU NURSES WITH A QUESTIONNAIRE SURVEY: THE NASA TASK LOAD INDEX (TLX). IIE Trans Healthc Syst Eng. 2012; 1(2):131-143. PMC: 3388621. DOI: 10.1080/19488300.2011.609524. View

12.

Aiken L, Clarke S, Sloane D, Sochalski J, Silber J . Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA. 2002; 288(16):1987-93. DOI: 10.1001/jama.288.16.1987. View

13.

Haas J, Cook E, Puopolo A, Burstin H, Cleary P, Brennan T . Is the professional satisfaction of general internists associated with patient satisfaction?. J Gen Intern Med. 2000; 15(2):122-8. PMC: 1495336. DOI: 10.1046/j.1525-1497.2000.02219.x. View

14.

Singh H, Spitzmueller C, Petersen N, Sawhney M, Sittig D . Information overload and missed test results in electronic health record-based settings. JAMA Intern Med. 2013; 173(8):702-4. PMC: 3822526. DOI: 10.1001/2013.jamainternmed.61. View

15.

Matthews G, Reinerman-Jones L, Barber D, Abich 4th J . The psychometrics of mental workload: multiple measures are sensitive but divergent. Hum Factors. 2015; 57(1):125-43. DOI: 10.1177/0018720814539505. View

16.

Poissant L, Pereira J, Tamblyn R, Kawasumi Y . The impact of electronic health records on time efficiency of physicians and nurses: a systematic review. J Am Med Inform Assoc. 2005; 12(5):505-16. PMC: 1205599. DOI: 10.1197/jamia.M1700. View

17.

Singh H, Spitzmueller C, Petersen N, Sawhney M, Smith M, Murphy D . Primary care practitioners' views on test result management in EHR-enabled health systems: a national survey. J Am Med Inform Assoc. 2012; 20(4):727-35. PMC: 3721157. DOI: 10.1136/amiajnl-2012-001267. View

18.

Murphy D, Meyer A, Russo E, Sittig D, Wei L, Singh H . The Burden of Inbox Notifications in Commercial Electronic Health Records. JAMA Intern Med. 2016; 176(4):559-60. PMC: 4860883. DOI: 10.1001/jamainternmed.2016.0209. View

19.

McManus I, Keeling A, Paice E . Stress, burnout and doctors' attitudes to work are determined by personality and learning style: a twelve year longitudinal study of UK medical graduates. BMC Med. 2004; 2:29. PMC: 516448. DOI: 10.1186/1741-7015-2-29. View

20.

Hysong S, Sawhney M, Wilson L, Sittig D, Esquivel A, Singh S . Understanding the management of electronic test result notifications in the outpatient setting. BMC Med Inform Decis Mak. 2011; 11:22. PMC: 3100236. DOI: 10.1186/1472-6947-11-22. View