|
|
![Picture](/uploads/2/6/3/9/26393715/9743575.png?436)
Medstar Washington Hospital Center is one of many hospitals that have newly integrated an EMR system into their infrastructure. While patient records have become more accessible to various clinicians and staff, real-time data of vital signs is still an issue. Vital signs play an important role in determining the plan of care for a patient and accurate representation of a patient’s current status is of utmost importance. Having to manually input vital signs into an EMR opens up greater risk for error and misrepresentation of patient status. Figure 1 and Table 1 show data reported in a study by Smith et al, addressing the reduction in errors for vital signs when comparing inputs via paper, EMRs, and automated systems. It is easy to see that the automated systems, such as the one we propose, show the smallest amount of error rate
An important aspect of this project is to improve patient safety. There is evidence that accurate and early recognition of changes in vital signs will help prevent negative outcomes in patients in hospital settings. Hillman, Bristow, Chey, Daffurn, Jacques, Norman & Simmons (2001) published a study describing antecedents to death within three major hospitals. A large percentage of patients showed early signs of vital sign deterioration 8-48 hours prior to death as displayed in the table below.
![Picture](/uploads/2/6/3/9/26393715/7699666.png?303)
Additional studies that support the use of automated vital sign documentation include a recent study by Wood & Finkelstein (2013). This cross-over study found that the mean time when vital signs data was made available on the EHR was considerably less with automated documentation than with manual collection and documentation. The mean times in which vital signs data became available in the EHR after manual and automated documentation were 68 minutes and 2.6 minutes respectively. (2013) That is a dramatic 26 fold reduction in lag time using automated documentation as displayed in Figure 2. Furthermore, the study found that 30% of manual vital signs entry contained at least one error, while automated data transmission had zero error. (2013) This study also provided evidence to support increased user satisfaction and efficiency. There was a significant increase(10.3 +/- 3.9 vs 16.5+/-3.4) in nursing satisfaction scores when comparing manual and automated documentation respectively. (2013) While the GE Dinamap system is the best fit for Centricity EMR, other studies using similar automated documentation systems support evidence of error reduction, improved efficiency and increased user satisfaction. One such system, CoViSTA, was evaluated in a study by Arora, Falsafi, Al-Ibrahim, Sawyer, Siegel, Joshi & Finkelstein published in 2005 with evidence supporting the use of automated documentation of vital signs in a hospital setting.