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Table. Hospitalists' Ratings of Average Workload Impact on Patient Carea
Table. Hospitalists' Ratings of Average Workload Impact on Patient Carea
1.
Kohn LT, Corrigan JM, Donaldson MS. To Err Is Human: Building a Safer Health System: A Report of The Committee on Quality of Health Care in America, Institute of Medicine. Washington, DC: National Academy Press; 2000
2.
Philibert I, Friedmann P, Williams WT.ACGME Work Group on Resident Duty Hours. Accreditation Council for Graduate Medical Education.  New requirements for resident duty hours.  JAMA. 2002;288(9):1112-111412204081PubMedGoogle ScholarCrossref
3.
Jagsi R, Weinstein DF, Shapiro J, Kitch BT, Dorer D, Weissman JS. The Accreditation Council for Graduate Medical Education's limits on residents' work hours and patient safety. A study of resident experiences and perceptions before and after hours reductions.  Arch Intern Med. 2008;168(5):493-50018332295PubMedGoogle ScholarCrossref
4.
Needleman J, Buerhaus P, Pankratz VS, Leibson CL, Stevens SR, Harris M. Nurse staffing and inpatient hospital mortality.  N Engl J Med. 2011;364(11):1037-104521410372PubMedGoogle ScholarCrossref
5.
American Nurses Association.  Nurse staffing plans and ratios. http://www.nursingworld.org/MainMenuCategories/Policy-Advocacy/State/Legislative-Agenda-Reports/State-StaffingPlansRatios. Accessed December 17, 2012
6.
Quantia Communications.  About QuantiaMD. https://secure.quantiamd.com/home/corporate_about_us?qmd_ver=2.7.110.11. Accessed January 10, 2011
7.
Li JW. Society of Hospital Medicine (SHM) 2007-2008 Productivity and compensation survey [registration required]. http://www.medscape.org/viewprogram/15751. Accessed December 17, 2012
8.
Reason JT. Managing the Risks of Organizational Accidents. Brookfield, VT: Ashgate; 1997
9.
O’Leary KJ, Liebovitz DM, Baker DW. How hospitalists spend their time: insights on efficiency and safety.  J Hosp Med. 2006;1(2):88-9317219478PubMedGoogle ScholarCrossref
Research Letter
Mar 11, 2013

Impact of Attending Physician Workload on Patient Care: A Survey of Hospitalists

Author Affiliations

Author Affiliations: Departments of Medicine (Drs Michtalik, Yeh, and Brotman), Epidemiology (Dr Yeh), and Health Policy & Management (Dr Pronovost), Johns Hopkins University, Baltimore, Maryland.

JAMA Intern Med. 2013;173(5):375-377. doi:10.1001/jamainternmed.2013.1864

Up to 98 000 patients die each year in the hospital as a result of preventable medical errors.1 Most errors are caused by well-intentioned individuals working within faulty systems, processes, or conditions. One such condition is excess clinical workload. For resident physicians, workload so heavy as to result in physician fatigue is associated with increased medical errors and has led to the implementation of work-hour restrictions.2,3 For nurses, a recent cross-sectional analysis showed a significant association between patient mortality and low staffing.4 Fourteen states have enacted legislation and/or adopted regulations to address nurse staffing.5

With increased economic pressures on hospitals and limitations on resident physician work hours, attending physician workload has likely increased. There is limited research available on the association between attending physician workload and patient safety. In this study, we examine the perceived impact of average hospitalist workload on patient safety and quality-of-care measures.

Methods

Over 4 weeks in November 2010, we electronically surveyed 890 self-identified hospitalists enrolled in an online physician community, QuantiaMD.com, the largest mobile physician community.6 We queried physician, hospital, and team characteristics; workload; frequency of an unsafe census; and what a “safe workload” would be in the given setting. We defined workload as patient encounters performed per shift, and safe workload as a workload that offered a minimal potential for error or harm.

The shifts evaluated were standard daytime shifts. Physicians rated the impact of average census on process and outcome measures of quality of care (Table) using a Likert scale ranging from 1 (never/definitely not) to 5 (very often/definitely). Quality assurance methods included data verification rules, preset ranges, and mandatory fields. The study design and questions were approved by the Johns Hopkins institutional review board.

Results

Of the 890 physicians contacted, 506 responded (57%) (eTable). Average (SD) respondent age was 38.3 (8.4) years, median time in practice was 6 years (interquartile range [IQR], 3-10 years). Practice settings were primarily urban (46.4%) or suburban (42.5%) in community (54.0%) or academic (27.9%) hospitals. The median annual compensation was $180 000 (IQR, $131 000-$200 000). Most physicians had primary inpatient clinical duties (86.9%) and 56% of attending physicians had some assistance with their clinical duties (midlevel staff [22.5%], house staff [20.7%], or both [12.4%]). Most hospitalists (71.0%) had a system for high patient volumes, primarily staffing augmentation plans (29.9%), or a fixed census cap (27.0%).

Forty percent of physicians reported that their typical inpatient census exceeded safe levels at least monthly; 36% of these reported a frequency greater than once per week. When we compared the reported workload to the estimated safe workload of individual physicians, 40% of hospitalists reported exceeding their own safe numbers. Regardless of any assistance, physicians reported that they could safely see 15 patients per shift if their effort was 100% clinical.

Hospitalists frequently reported that excess workload prevented them from fully discussing treatment options, caused delay in patient admissions and/or discharges, and worsened patient satisfaction (Table). Over 20% reported that their average workload likely contributed to patient transfers, morbidity, or even mortality.

Comment

This is the first study to assess perception of unsafe workload by a direct question, to compare self-reported safe and actual census numbers, and to evaluate the potential impact of inpatient attending physician workload on patient outcomes. Forty percent of hospitalists reported unsafe workloads at least monthly. Nearly one-quarter of hospitalists reported that excess workload adversely impacted patient outcomes by preventing full discussion of treatment options and worsening patient satisfaction. Twenty-two percent of physicians reported ordering potentially unnecessary tests, procedures, or consults because of not having adequate time to evaluate patients in person. Given the large number of patients cared for by hospitalists, the frequency with which workload exceeds safe levels, and the perceived impact of workload on patient outcomes, hospital administrators, researchers, and policymakers should focus attention on attending physician workload.

We recognize that there are some limitations for our study. First, our survey results may be influenced by self-selection; however, our surveyed population mirrors the national characteristics of hospitalists.7 Second, we do not know the extent to which perceptions of risks and worsened patient outcomes correlate with true risks and outcomes. However, substantial evidence suggests that front-line operators' perceptions correlate with true risks.8

This study has significant policy implications. First, hospitals need to routinely evaluate workloads of attending physicians, create standards for safe levels of work, and develop mechanisms to maintain workloads at safe levels. Second, society needs to reduce health care costs but do so wisely. The main mechanism for reducing costs is to pay less for services, assuming that providers and institutions will increase productivity and efficiency. Hospital administrators largely respond to payment reduction by increasing workload. However, excessively increasing the workload may lead to suboptimal care and less direct patient care time,9 which may paradoxically increase, rather than decrease, costs. Payers, providers, and researchers need to collaborate to improve productivity while maintaining a safe workload. Further research is needed to better understand attending physician workload and its determinants, the correlation between workload and objective outcomes, and how best to respond when a safe workload is exceeded.

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Article Information

Correspondence: Dr Michtalik, Division of General Internal Medicine, Hospitalist Program, 1830 E Monument St, Ste 8017, Baltimore, MD 21287 (hmichta1@jhmi.edu).

Published Online: January 28, 2013. doi:10.1001/jamainternmed.2013.1864

Author Contributions: Drs Michtalik and Brotman had full access to all of the data in the study and take responsibility for the integrity of the data and accuracy of the data analysis. Study concept and design: Michtalik, Pronovost, and Brotman. Acquisition of data: Michtalik and Brotman. Analysis and interpretation of data: Michtalik, Yeh, Pronovost, and Brotman. Drafting of the manuscript: Michtalik and Brotman. Critical revision of the manuscript for important intellectual content: Michtalik, Yeh, Pronovost, and Brotman. Statistical analysis: Michtalik and Yeh. Obtained funding: Brotman. Administrative, technical, and material support: Michtalik and Pronovost. Study supervision: Michtalik and Brotman.

Conflict of Interest Disclosures: Dr Brotman has received compensation from Quantia Communications, not exceeding $10 000 annually, for developing educational content.

Funding/Support: Dr Michtalik was supported by National Institutes of Health (NIH) grant T32 HP10025-17-00 and NIH/Johns Hopkins Institute for Clinical and Translational Research KL2 Award 5KL2RR025006. The Johns Hopkins Hospitalist Scholars Fund provided funding for survey implementation and data acquisition by Quantia Communications.

Role of the Sponsors: Quantia Communications had no role in the design, analysis, and interpretation of the data; or the preparation, review, or approval of the manuscript.

Additional Contributions: The authors thank the Johns Hopkins Clinical Research Network Hospitalists and General Internal Medicine Research in Progress Physicians for their comments on the survey design and content. They also thank Michael Paskavitz, BA, and Brian Driscoll, BA, for all of their technical assistance in administering the survey.

References
1.
Kohn LT, Corrigan JM, Donaldson MS. To Err Is Human: Building a Safer Health System: A Report of The Committee on Quality of Health Care in America, Institute of Medicine. Washington, DC: National Academy Press; 2000
2.
Philibert I, Friedmann P, Williams WT.ACGME Work Group on Resident Duty Hours. Accreditation Council for Graduate Medical Education.  New requirements for resident duty hours.  JAMA. 2002;288(9):1112-111412204081PubMedGoogle ScholarCrossref
3.
Jagsi R, Weinstein DF, Shapiro J, Kitch BT, Dorer D, Weissman JS. The Accreditation Council for Graduate Medical Education's limits on residents' work hours and patient safety. A study of resident experiences and perceptions before and after hours reductions.  Arch Intern Med. 2008;168(5):493-50018332295PubMedGoogle ScholarCrossref
4.
Needleman J, Buerhaus P, Pankratz VS, Leibson CL, Stevens SR, Harris M. Nurse staffing and inpatient hospital mortality.  N Engl J Med. 2011;364(11):1037-104521410372PubMedGoogle ScholarCrossref
5.
American Nurses Association.  Nurse staffing plans and ratios. http://www.nursingworld.org/MainMenuCategories/Policy-Advocacy/State/Legislative-Agenda-Reports/State-StaffingPlansRatios. Accessed December 17, 2012
6.
Quantia Communications.  About QuantiaMD. https://secure.quantiamd.com/home/corporate_about_us?qmd_ver=2.7.110.11. Accessed January 10, 2011
7.
Li JW. Society of Hospital Medicine (SHM) 2007-2008 Productivity and compensation survey [registration required]. http://www.medscape.org/viewprogram/15751. Accessed December 17, 2012
8.
Reason JT. Managing the Risks of Organizational Accidents. Brookfield, VT: Ashgate; 1997
9.
O’Leary KJ, Liebovitz DM, Baker DW. How hospitalists spend their time: insights on efficiency and safety.  J Hosp Med. 2006;1(2):88-9317219478PubMedGoogle ScholarCrossref
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