• Review the evidence base on erroneous actions related to shift changes.
• Understand the limits of standardizing handoffs in preventing errors at shift change.
• Explain basic assumptions about human expertise and error.
• Learn three heuristics for effective coordination: Reduce, Reveal, Focus.

A 3-month-old infant was admitted with a respiratory syncytial virus (RSV) infection to a pediatric medical unit. Although she was initially stable (without oxygen requirements), her breathing soon became labored, with an increased respiratory rate and subcostal retractions. Providers determined that she would benefit from a higher level of care and initiated the transfer process. This transfer happened to coincide with a shift change for both the nursing staff and the physicians involved.

The off-going nurse assumed that the transfer would take place immediately and signed out her patients to the next nurse before the patient was physically moved. The outgoing physician sent a text page to his incoming colleague with similar sign-out. Approximately 45 minutes later, the unit clerk called the infant's bedside nurse to report that the infant's parents believed their child was in significant distress. The nurse was surprised that the patient had not yet been transferred and, after an initial evaluation, immediately called the rapid response team. The evening physician was also contacted and was equally surprised by the series of events. She had been told that the patient was being transferred "non-emergently" to a unit for closer observation. The patient was transferred to the intensive care unit (ICU), where she made a full recovery, after a prolonged hospitalization.

The hospital performance improvement committee reviewed the case and determined that improper delegation and lack of communication between staff members contributed to the delay in treatment, and that improved policies should be required for shift changes.

Challenges at Shift Change

Shift change updates are widely believed to be a point of vulnerability in complex systems with high consequences for failure. They may also increase resilience by providing an opportunity to detect erroneous assessments and actions made by the outgoing personnel.(1-2) One study reported that sign-out–related problems with internal medicine physicians in one hospital occur at a rate of 7.5 per 100 patient-days of care.(3) Erroneous actions stemming from shift changes have caused a wide variety of problems (4), including inaccurate medication prescriptions (5-6), inaccurate evaluations (6), longer lengths of stay, and increased use of laboratory tests.(6-8) Moreover, transfers during times of reduced physician staffing may lead to lower billing accuracy, longer lengths of stay, and higher patient mortality.

This case highlights a common scenario: a planned patient transfer that gets delayed until after a shift change. The decision to delay a patient transfer is in most situations locally rational. Two off-going nurses, and in this case the outgoing physicians as well, would need to coordinate the transfer, including the update, during a busy period when they are trying to complete activities to avoid handing them off to the next practitioner; the latter is a strong social norm that reduces the chances of the "ball getting dropped." By delaying the transfer until after shift change, the receiving nurse can focus on assessing and stabilizing the patient and avoid an additional handoff update, which can potentially introduce inaccuracies and gaps in the communication exchange. In addition, transfers conducted during a shift change risk the receiving personnel having an interrupted or curtailed handoff update. These risks are traded off against the potential benefits of the additional care provided by ICU nurses and specialized monitoring technology. In the case of an unstable infant patient believed to be in significant respiratory distress, waiting 45 minutes is likely an undesirable weighting of associated risks and benefits.

Standardizing Shift Change Communication

The recommendation of the hospital's performance improvement committee to implement improved shift change policies is a laudable goal. Ideally, the policy would provide guidance to "sharp end" practitioners about how the organization would like to trade off the associated risks for this and related scenarios. To my knowledge, few existing hospital policies fully accomplish this goal. Instead of providing guidance on desired risk trade-offs in particular scenarios, settings, disciplines, and clinical categories, most policies currently recommend a "blanket" approach to standardization of content or format (e.g., Situation-Background-Assessment-Recommendation, or SBAR [9]). The primary benefit of this approach is to increase the information conveyed about every patient (10) in either verbal or written format. In some cases, this strategy could prove vitally important in supporting anticipatory thinking about how to best provide safe patient care. On the other hand, the opportunity costs stemming from dedicating providers' resources uniquely to the shift change update might potentially decrease the attention focused on the exchange itself, largely by "hiding" insightful deviations from typical narratives ("stories") in a series of uninformative and potentially irrelevant data pieces. For example, see Table 1 for a comparison of a narrative-based update vs. an SBAR-based update in the context of the case presented. The SBAR example is based upon the worksheet tool provided by the Institute for Healthcare Improvement, which was originally designed for nurses calling physicians to report critical situations, but is also recommended for adaptation to other updates.

Moving Beyond Standardization

Given the limits of standardization with regard to complex systems with constant trade-offs in decision-making, additional strategies may be warranted to ensure patient safety. If asked to provide guidance to a hospital improvement committee, a first step would be to synthesize what is available from decades of research in other complex, sociotechnical settings with high consequences for failure.

Basic assumptions and lessons distilled from the cognitive systems engineering literature (11-14) are outlined in Table 2. Overall, they highlight a number of important lessons that can be applied to health care settings.

For the specific case of designing policies for shift changes, a productive approach would involve efforts to reduce complexity wherever possible to minimize the potential for erroneous actions. This approach also increases the ability to detect and recover from such actions. Based on research about how to cope with complexity, there are three heuristics (15) for designing effective coordination that can serve as a general guide for shift change updates:

Heuristic 1: Reduce complexity.

• Reduce transfers by:
  • Proactively "bumping" patients (e.g., moving them to another unit) in advance of a pending patient's arrival.
  • Directly transferring patients to planned specialties (e.g., skip the emergency department of a second hospital).
  • Minimizing "boarding" practices in emergency departments.
  • Minimizing changes in providers to meet quality of worklife goals for practitioners (e.g., 14-day staffing rather than use weekend coverage; eliminate substitutions to attend meetings or give lectures).
  • Assigning patients to nurses who provided care to them recently.
  • Delaying tasks/breaks for nursing personnel who are providing on-call care for another nurse until the original nurse returns to the unit.
• Eliminate redundant documentation.
• Eliminate or streamline data entry for use at a later time by distant parties (e.g., billing, legal, quality improvement personnel).
• "Chunk" together related information that can be tailored to a particular perspective (e.g., group together nursing notes with vital sign information).

Heuristic 2: Reveal by rendering work observable.

Provide an overview "at a glance" visual display of the current status of a work process. An example of this approach is the Post Anesthesia Care Unit (PACU) Dashboard developed by Massachusetts General Hospital (MGH) in collaboration with LiveData (Figure).

Although every "at a glance" display will appear different based on the specific context, the information can be described abstractly in order to aid translation to other settings:

• Differences from routine assessments and plans (e.g., contact precautions).
• Relation of real-time events to planned milestones.
• Hazards (e.g., patients with a history of allergic reaction to anesthetics).
• Outliers, threshold crossings, and trends in sensored data.
• Constraints and couplings for alternatives to current plans (e.g., status of readiness of future patients).

Heuristic 3: Focus attention.

• Stratify time and attentional resources during the update based on patient instability and level of uncertainty around a diagnosis and treatment plan (e.g., "Save the sick, do the others quick" strategy [16]) as well as speeding up and truncating aspects of the handoff in preparation for anticipated events that will likely take precedence (e.g., "New demand, change the plan" strategy [16]).
• Enable peripheral detection of unexpected events and actions while performing primary tasks, such as by grouping patients under the care of a particular provider in one place and enabling peripheral monitoring via audio cues or centralized displays.
• Highlight the need to expedite tasks, including transfers (e.g., patients in significant respiratory distress being transferred to critical care units).
• Automatically compile data into printed paperwork that can be highlighted, annotated, and discussed verbally during the update.

It could be argued that the heuristics provided here do not directly address all of the issues raised by the specific case. In particular, nothing that is recommended specifically ensures that an infant patient with RSV having significant respiratory distress will avoid delays in being transferred to the ICU following a shift change handoff. In my opinion, the common and human desire to "ensure that this never happens again" following an unfortunate outcome can serve as a barrier to making health care systems safer, less costly, more effective, more efficient, and more patient-centered. In fact, I recommend avoiding basing design decisions strictly on an individual case. An alternative approach is to encourage desired trade-off weightings across a range of routine and exceptional cases that practitioners are anticipated to encounter. This approach explicitly recognizes that some amount of undesired outcomes is unavoidable in a world that does not have the benefit of hindsight knowledge about which risk trade-offs will dominate in a particular case.

Take-Home Points

• The evidence base for interventions to improve shift changes is weak.
• Alternatives to standardization of shift change update content should be pursued.
• Coordination heuristics suggest productive directions to explore.

Emily S. Patterson, PhD
Research Scientist

Institute for Ergonomics

The Ohio State University

Faculty Disclosure: Dr. Patterson has declared that neither she, nor any immediate member of her family, has a financial arrangement or other relationship with the manufacturers of any commercial products discussed in this continuing medical education activity. In addition, her commentary does not include information regarding investigational or off-label use of pharmaceutical products or medical devices.

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Table 1. Comparison of a Narrative vs. SBAR Update about the Patient

Table 2. Assumptions and Lessons from the Literature

Figure. Example of "At a Glance" Visual Display: PACU Dashboard.

Click to enlarge.

Figure reprinted with permission from Patient Safety & Quality Healthcare. In: Cieielski S, Daily B, Levine WC. A dashboard for the PACU. Patient Saf Qual Healthc (PSQH). Sept/Oct 2008;5:44-47. Available at: http://www.psqh.com/sepoct08/pacu.html.