Original ContributionA better way to estimate adult patients' weights☆
Introduction
It is estimated that medication errors cost billions of dollars and harm 1.5 million people per year [1]. Although the exact incidence is difficult to determine, it is estimated based on previous studies that per 1000 orders, 0.61 to 53 prescribing errors are made [1]. These include errors in weight-based dosing of medications. Weight-based medication therapy is integral in caring for patients in critical situations. Many lifesaving treatments—including thrombolytics, anticoagulants, vasopressors, and intravenous fluids—are dosed based on a patient's weight. The safety and efficacy of these interventions is adversely affected by inappropriate dosing, which can easily occur if the wrong weight is estimated and used.
Limitations of resources, physical space, and time often preclude providers from obtaining measured weights. Although patients can usually accurately predict their weight, a large proportion of patients who are critically ill are unable to provide this important information. Furthermore, health care providers have been shown to poorly estimate weights [2], [3], [4]. Corbo et al [4] found that physicians and nurses were able to estimate a patient's weight within 10% of their actual weight only approximately 50% of the time. A more recent study by Kahn et al [5] showed that providers were able to estimate within 5% of true weight in only 33% of estimates. Physician accuracy did not improve with experience or specialty [4].
A rapid, reliable weight estimation tool could be invaluable to reduce errors in the delivery of various medications and fluids used in the emergency department (ED). Anthropometric parameters such as midarm circumference, knee height, demi-span, and other body measurements have been used to create nomograms and equations derived from statistical modeling to estimate patients' weights. Generally, these tools have been developed for use in nonemergent settings. Furthermore, no such tool has gained wide acceptance nor has any been tested specifically and prospectively validated in an ED population. In this study, we selected a practical, relatively simple tool and tested it in an ED population.
Section snippets
Study subjects
A prospective cohort of consecutive, eligible, consented patients at a tertiary care academic facility were enrolled for an 11-month period when the study principal investigator was present and available to enroll patients in the ED. We included ambulatory and nonambulatory adult patients who agreed to be weighed in the ED or upon admission. This included obtunded, lethargic, and unconscious patients, who were consentable by health care proxy. We excluded nonambulatory patients who were
Results
Over the course of the study, 274 patients were asked to participate. Of these, 39 refused or could not be consented and 235 patients were enrolled. The demographic and clinical characteristics are summarized in Table 1.
Fig. 1 summarizes the key results of our study. This weight estimation tool predicted weight within 10% accuracy of a patient's actual weight in 69% (95% confidence interval [CI], 63%-75%) of patients, which was significantly better than estimates by physicians and nursing
Discussion
Our study showed that self-report is the most accurate method of weight estimation, and if that is not possible, a simple weight estimation tool can significantly improve the accuracy of physician and nurse estimates by 15%. This improved accuracy has potentially profound implications for patient safety by avoiding adverse and potentially lethal medication errors.
Of provider estimates, our study shows provider accuracy that is similarly poor as compared with other studies. In the study of Corbo
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Work previously presented at Mediterranean Emergency Medicine Congress, Sorrento, Italy, September 2007.