Theme Issue Editorial
Measuring team performance in healthcare: Review of research and implications for patient safety

https://doi.org/10.1016/j.jcrc.2007.12.005Get rights and content

Abstract

Effective team performance is important to measure in order to determine how clinicians should be trained for safe and effective patient care. Team performance is challenging to measure. In this paper, we describe different methodologies used to capture team performance metrics including clinical surveys, direct observation, and video-based analyses of real-life clinical performance. Despite much effort, the instruments reported thus far suffer from a variety of shortcomings that prevent their wide application in assessing team behaviors and performance. A consensus is needed on a conceptual model of clinical team performance that can encompass many real and simulated healthcare settings and account for interdependencies of their outcome criteria.

Introduction

In this article, we discuss measures developed to study team performance in healthcare, based on (1) clinician surveys; (2) direct observation; and, (3) video-based analysis.

The strengths and weaknesses of these methods are presented, alongside future directions for improved measurement of performance of medical teams. The role of measurement of team behaviors in simulation and nontechnical skills training efforts is described. The increasing need for accurate performance-based criteria for teams in healthcare is highlighted.

The patient safety literature is littered with accounts of poor teamwork leading to adverse events. Increasing organizational and public demands have added pressure for change to occur; the inadequacy of clinician response has been compounded by growing complexity and interactions with technology in healthcare.

Although high reliability theory and advanced industries such as aviation provide lessons and tools to assist in the assessment and development of healthcare teams, the unique challenges in healthcare leave the industry lagging. In spite of these challenges (eg, transient teams and engrained medical cultures of autonomy and hierarchy), it is clear that quality interactions across, as well as within, teams are essential for patient safety.

Tested and proven methodologies for assessing and evaluating team performance are vital to enable measurement and monitoring of medical team effectiveness and results of training. Moreover, it is crucial for us to understand how to best educate the healthcare workforce in teamwork skills and how to subsequently maintain these skills. The first step is to determine the criteria that make “good” teams and good outcomes in the real world—before exploiting the potential that simulation promises for team training across healthcare.

Within this article a number of fundamental messages are discussed.

A richer understanding of team dynamics and effectiveness can benefit patient safety by assisting in team training development and can boost individual and team competencies in nontechnical aspects of care, such as prioritization, leadership, and decision making. The nature of anesthesiology makes it a rich test bed for team measurement because within the operating room environment, activities and decision making must be coordinated between anesthesiologists, surgeons and procedurists, and nurses, all of whom have their own group cultures and team dynamics.

The real world is the ultimate test bed for creating teamwork measures. These measures enable assessment of team behaviorial changes after medical team training has occurred. The questions to answer with regard to team training effectiveness is what would be the best way to train people to effect behavioral change—that is, behave more efficiently, consistently, and safely—within the real clinical environment and what would be the best method to measure such change? Examination of real-world behavior in the clinical domain can help us identify problem performance areas that can be recreated in a simulated environment which, in turn, would help us learn more about team dynamics in the real world.

The available tools are growing in number, in response to increasing need and demand for team performance measurement and monitoring. However, all remain rather rudimentary and most are, as yet, unable to appropriately inform team training schemes owing to a lack of reliability, validity, and ability to generalize.

Video recording enhances systematic feedback and performance review by providing precise analysis and repeated reviews by multiple observers (including the clinician's whose care is recorded). Direct observation cannot compete with such benefits, but is less intrusive and generally more accepted by clinicians.

Many team performance measurement tools are designed to be context or specialist service specific. For example, tools used to measure team performance for the operating room are different than those created for teams in the neonatal unit. As a result, comparison between tools is difficult and establishing generic processes and the supporting behaviors consistent with “good” teamwork is required. A consensus on a theoretical framework or model of team performance would provide researchers with the ability to describe and test hypotheses concerning the interrelationships of various performance measures, as well as the interdependencies of the predictors and the outcome criteria, across healthcare settings.

Even experienced health care professionals require continuous training and competency assessment to ensure patient safety and improvement and maintenance of performance standards. Team dynamics such as composition, coordination, and communication are fundamental skills to be incorporated into such training curricula, particularly through simulation involving interdisciplinary teams. There is also an understanding that expertise occurs independently of experience.

In the context of measuring team performance in the management of trauma patients for example, outcome measures are recorded at the point of discharge. This is in spite of the fact that the most intense and crucial teamwork functions occur in the initial resuscitation period (ie, up to 30 minutes after admission). During the succeeding period, a multitude of confounding variables makes the process of linking initial management with outcomes difficult. However, process-based measures may enable more effective correlation with team performance scores. These process measures might include time to execute key decisions or the number of repeated instructions or requests for clarity.

Section snippets

Team terminology

There is a general consensus that a team consists of 2 or more individuals, who have specific roles, perform interdependent tasks, are adaptive, and share a common goal [1]. Team work is distinct from task work and is defined as the set of interrelated knowledge, skills, and attitudes that facilitate coordinated, adaptive performance [2]. Team performance is then simply how effectively the team fulfils the function/s it serves [3].

Numerous medical team training programs have been developed and

Measuring healthcare teams

Team performance measurement is important to help determine how best to train clinicians for safe and effective patient care, in both real and simulated environments. Performance measurement before and after training must be comprehensive and accurate. Metrics should include all the dimensions that contribute to effective team work within specific clinical domains. Measures must be both reliable (ie, it should measure teamwork in a consistent manner) and valid (ie, it should be able to predict

Conclusions

Healthcare professionals recognize the importance of educating clinicians in nontechnical and teamwork skills. But the best ways to ensure that these competencies can be routinely and consistently measured in real and/or simulated environments have not been established. Impaired decision making, absence of situation awareness (or the “big picture”), and failures in interpersonal communication all contribute to failures that endanger patient safety in healthcare systems [11].

Anesthesia is prone

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