Physician Work, Workload, and Stress in the ED: Implications for Patient Safety Dan France, Ph.D., MPH Scott Levin, B.S. 23 July 2004

Specific Aims 1.Characterize ED physician work and communication patterns in the presence of an advanced ED information system 2.Compare workload and stress in ED attending and resident physicians 3.Explore methods to quantify effects of system factors on provider and patient outcomes

Emergency Medicine in U.S. How Many ED Visits? Source: National Center for Health Statistics, National Hospital Ambulatory Medical Care Survey, ,000 80,000 85,000 90,000 95, , , , , % increase Number of visits (in thousands)

Emergency Medicine in U.S.

Background – Emergency Medicine  Complex, chaotic, interrupt-driven,…  Patient Safety: 53% to 82% of ED adverse events (AE) are preventable compared to 27-51% for in-hospital AEs (Fordyce 2003),  Risk Management: 43% of ED claims due to failures in team communication (Risser 1999)  Patient Satisfaction: Ranks high for patient dissatisfaction/complaints (Taylor 2002)

The Burden on Physicians  Residents experience stress and depression uniformly through training (Whitley 1991)  25-60% of physicians surveyed felt burned out (Doan- Wiggins, Zautcke, etc 1995)  22% of physicians thought they would practice beyond 50 (Losek 1994)  Stress may cause anxiety disorders (Laposa 2003)  Why? Intense clinical workload vs. inefficiencies in workflow, information flow, and communication

Swiss Cheese Model Reason (1990): Human Error

Artichoke Model Bogner (2004): Misadventures in Healthcare

Performance Shaping Factors  Individual factors Experience, training, physiological, psychological state  Task-related factors Workload, vigilance  Equipment/Tools Human-computer/device interaction  Interpersonal factors Teamwork  Care environment factors Facility design/layout  Organizational/Cultural factors

A Systems Engineering Approach – “the Inner Ring” How do you adequately measure the “forces” acting on ED physicians from the physicians’ perspectives?

“The Outer Ring” Approach Other hospitals have tried to cope with crowding by expanding the ER, only to find it doesn't solve the problem. Busy Boston Medical Center eases delays by keeping 'customers' moving “emergency room delays are a symptom of poor hospital management”

Creating a Methodology  Study methods from other “high risk” industries and disciplines Nuclear power, aviation, anesthesiology Human factors, psychology, industrial engineer  Call your friends Medicine and Biomedical Eng. – Kong Chen, Ph.D. Biomedical informatics – Domink Aronsky, M.D., Ph.D, Biostatistics – Dan Byrne, M.S., Chang Yu, Ph.D. Emergency Medicine – Robin Hemphill, M.D. Dorsey Rickard, Renee Makowski (Med students) Ted Speroff, Ph.D., Bob Dittus, M.D., MPH (Mentors)

Creating a Methodology  Call people you want to be friends with: Bruce Hallbert, M.S. – Idaho National Environmental Laboratory (Human Factors expert in Nuclear power) Matt Weinger, M.D. – UCSD, anesthesiologist and patient safety expert. Call your friends

Study Design - Conceptual Diagram  Subjects: 10 Faculty 5 PGY-3 5 PGY-2  180-minute observations  Afternoon observations

Primary Task Analysis  Primary tasks: Answering EMS calls Charting Dictating Direct Patient Care Electronic Whiteboard Interaction (eWB) eWB Viewing Exchanging Patient info. Phone calls/Pages Verbal Orders to Provider Teaching/Learning Supervising  Task Outcomes: End Task Break in Task Temporary interruption Interruption types: Face-to-Face Physician Face-to-face Nurse Face-to-face other Phone call/Page Locating lost charts Equipment malfunction Other

Time in Motion Study 180 minute observation

Physiological Measurements Kong Chen, Ph.D. How does physical activity / physiological stress relate mental workload/stress?

Subjective Workload Assessment  NASA Task Load Index (TLX) – result of 20 years of research in aviation/space  6 Dimensions of NASA-TLX Mental demand Physical demand Temporal demand Effort Performance Frustration Level

Electronic Whiteboard  ED Occupancy  Diversion status  Patient wait times  Patient LOS  Managing physician  Total # of pts  Max # of pts  Other system level data Dominik Aronsky, M.D., Ph.D

Results  50 hours of physician work activity observed  Physicians averaged tasks per observational period  Physicians walked about 0.8 miles  Interruption rates Faculty: every 9.6 minutes PGY3: every 8.8 minutes PGY2: every 13 minutes

Patient Load by Training Level

Tasks by Training Level

Distribution of Tasks

More about Tasks  Faculty perform 8% more exchanging info, 12% more dictation tasks than residents  Residents perform 10% more charting tasks than faculty  Residents performed 59% of all direct patient care tasks

Distribution of Interruptions

More about Interruptions  Uninterrupted Task Duration: 0:1:21(hour:minutes:seconds)  Interrupted Task Duration: 0:2:00 (excluding duration of interruption)  Tasks are interrupted about 1 minute after they are started  Temporary interruptions last 33 seconds  9% of direct patient care tasks interrupted

What Tasks do Interruptions Interrupt?  Face-to-face physicians interruptions: Charting (29%) eWB interaction (22%) Exchanging pt. info (12%)  Face-to-face nurse interruptions: Exchanging pt. info (23%) eWB interaction (22%) Charting (16%)  Telephone interruptions: Exchanging pt info (22%); direct pt. care (17%), charting(15%)

Task before/After eWB Activity Note: eWB activity represented nearly 20% of all tasks observed

Subjective Workload by Task

Subjective Workload Dimensions *Statistically significant difference at alpha = 0.05 level Frustration Temporal demands Biggest driver of workload for all physicians

Workload Summary  Faculty supervise; manage information/communication flow  PGY-3 residents are the “work horses” of the ED Most tasks; Most patient care; most interruptions  PGY-2 residents – charting;consults; direct patient care

Workload Summary  ED physicians attribute mental workload to: 1.Time demands 2.Effort 3.Mental demands  Residents have higher workload than faculty Results primarily from frustration; effort

Implications – Safety/Efficiency  Physicians working in ED equipped with IT system (eWB) * Are 34% more efficient (tasks performed) Spend 10% more time on direct patient care Experience 52% less interruptions  The eWB appears to help distribute ED workload fairly evenly  The eWB appears to improve situational awareness Increase in direct patient care after viewing eWB *Compare to results reported by Chisholm, Coiera, Hollingsworth

Implications – Safety/Efficiency  Temporary interruptions occur twice as often as breaks in tasks  Interrupted tasks are 33% longer than uninterrupted tasks  Interruptions affect provider-provider communication more than provider-patient communication  IT improves information / communication flow but interruptions still prevalent Command and control center of ED *Compare to results reported by Chisholm, Coiera, Hollingsworth

Next Steps  Explore Time-based analyses Workload density Physiological stress Linear mixed effects modeling  Framework Assessing Notorious Contributing Influences for Error (FRANCIE) NASA/INEEL tool for aviation safety Modeling human performance and error Input: Our task analysis data and error taxonomy for ED  Study association between human factors and patient/provider outcomes

Data over time

Task or Task Step for Analysis Omission Commission Error Types Generic Errors General Performance shaping factors Intermediate PSFs Specific PSFs, PSF characteristics, PSF examples FRANCIE – Core Error and Contributing Influences

The Future  Doubling size of Adult ED  New Children’s Hospital ED  Other settings – OR, Oncology clinics

Questions?