Automated charting of physiological variables in anesthesia: A quantitative comparison of automated versus handwritten anesthesia records

RRTPurpose: To evaluate if anesthesia training and experience influenced chart completion and accuracy. Methods: One hundred and twenty-four subjects, including medical students, anesthesia residents and community and university based clinical anesthesiologists, were given a standardized patient in a simulator environment and asked to conduct induction and maintenance of anaesthesia. Three critical events were introduced resulting in changes in BP, HR, PETCO~ and SpOt. Subjects were instructed to manage the patient and the anesthetic chart, as was their customary practice. Discrepancy, calculated as the difference between the actual and charted values divided by the actual physiological value was compared by level of training with a two-way repeated measures analysis of variance (ANOVA) for all four physiological variables. The completeness of charting, defined as at least one data point recorded for each of the four physiological variables of the three critical events, was compared across level of training, age of participants and number of years in practice. Results: The overall completeness of charting remained low (<37%) with no relationship based on the anesthesiologist's age, level of training or number of years in practice. There'was discrepancy in charting for all phySiological variables (HR, BP, PETCO 2 and SpO v P < 0.0001), with a marked difference in the degree of discrepancy within each level of training. Training resulted in no differences in charting discrepancy. Conclusion: Charting of data to the anesthetic record remained incomplete and inaccurate in all groups based on level of training, age and number of years in practice.Objectff: I~valuer si la formation en anesth~sie et rexp&ience influencent la tenue de dossier et son exactitude. M~.thode 9 Cent vingt-quatre sujets, y compris des &udiants en mEdecine, des residents en anesth&ie et des anesth&iologistes de pratique priv& ou universitaire ont regu le modEle d'un patient dans un environnement simulE et on leur a demandE de procEder ~ rinduction et ~ rentretien de I'anesth&ie. On a introduit trois incidents critiques impliquant des changements de TA, FC, PFrCO 2 et SpO v On a demanda aux sujets de procEder ~. I'anesth&ie et de remplir le dossier comme ils avaient I'habitude de le faire. La discordance, calcul& ~ partir de la difference entre les valeurs rEelles et celles du dossier divisEe par la valeur physiologique veritable, &ait comparEe sur la base du niveau de formation selon une analyse de variance (ANOVA pour valeurs rEp&Ees) pour les quatre variables physiologiques. Le dossier complet, dEflni par renregistrement d'au moins une donn& pour chacune des variables physiologiques des trois incidents critiques, Etait compare selon le niveau de formation, I'~ge des participants et le nombre d'annEes d'exp&ience. l~.sultats : I'ach~vement global du dossier a EtE faible (<37 %) et ne pr&entait pas de differences bas&s sur I'~ge, la formation ou le nombre d'ann~es de pratique. II y avait des divergences d'inscription au dossier pour toutes les ...

Section: Discussionmentioning

confidence: 99%

The anesthetic record: accuracy and completeness

Rapanos

Kurrek

et al. 1999

“…[7][8][9][10] These studies predominantly relate to the accuracy of physiological data. In a recent study, completion rates were assessed for six text entry fields on AIMS records, 24 and results showed rates similar to those seen in this study; however, randomized evaluations directly comparing the completeness of text entry data between different methods of recordkeeping are lacking.…”

Section: Discussionmentioning

confidence: 99%

“…6,21 Several studies have compared the accuracy and completeness of physiologic data in handwritten and AIMS records and have found AIMS records to be superior. [7][8][9][10] This is not surprising, as electronic data from physiologic monitors lend themselves to automated capture by an AIMS. It is less clear whether AIMS technology facilitates recording information that can be obtained only by clinical observation.…”

Section: Résumémentioning

confidence: 97%

“…[1][2][3] Automation of this task can reduce the time devoted to completing anesthetic records [4][5][6] while increasing the quality of data contained in them. [7][8][9][10] Anesthesia information management system (AIMS) technology was once the domain of an enthusiastic minority, but use is increasing. 11,12 Published data have reduced concerns about the potential of AIMS to reduce vigilance and increase medico-legal exposure 5,13,14 (although there were more lapses in response to a vigilance task in a recent randomized controlled trial [RCT] in our own institution).…”

Section: Résumémentioning

confidence: 99%

See 1 more Smart Citation

A randomized comparison between records made with an anesthesia information management system and by hand, and evaluation of the Hawthorne effect

Edwards

Hagen

Hannam

et al. 2013

Purpose Anesthesia information management system (AIMS) technology is designed to facilitate high-quality anesthetic recordkeeping. We examined the hypothesis that no difference exists between AIMS and handwritten anesthetic records in regard to the completeness of important information contained as text data. We also investigated the effect of observational research on the completeness of anesthesiologists' recordkeeping. Methods As part of a larger randomized controlled trial, participants were randomized to produce 400 anesthetic records, either handwritten (n = 200) or using an AIMS (n = 200). Records were assessed against a 32-item checklist modified from a clinical guideline. Intravenous agent and bolus recordings were quantified, and data were compared between handwritten and AIMS records. Records produced with intensive research observation during the initial phase of the study (n = 200) were compared with records produced with reduced intensity observation during the final phase of the study (n = 200). Results The AIMS records were more complete than the handwritten records (mean difference 7.1%; 95% confidence interval [CI] 5.6 to 8.6%; P \ 0.0001), with higher completion rates for six individual items on the checklist (P \ 0.0001). Drug annotation data were equal between arms. The records completed early in the study, during a period of more intense observation, were more thorough than subsequent records (87.3% vs 81.6%, respectively; mean difference 5.7%; 95% CI 4.2 to 7.3%; P \ 0.0001). Conclusions The AIMS records were more complete than the handwritten records for 32 predefined items. The potential of observational research to influence professional behaviour in an anesthetic context was confirmed. This trial was registered at the Australian New Zealand Clinical Trials Registry No 12608000068369.

“…Lerou et al evaluated automated charting using the Ohmeda Modulus II TM Anesthesia System vs handwritten records by comparing the acquisition of eight physiological variables in 30 elective eye surgeries. 37 Two records were compared for each patient, the handwritten record and that recorded by AARK. Anesthesiologists had two advantages; there was a centralized unit that displayed all eight variables on one screen, and they knew beforehand that their handwritten records would be compared with the automated record.…”

Section: Anesthesia Information Management Systems (Aims)mentioning

confidence: 99%

Review article: The evolving role of information technology in perioperative patient safety

Stabile

Cooper

2012

Purpose The adoption of new technologies in medicine is frequently met with both enthusiasm and resistance. The universal adoption of health information technology (IT) and anesthesia information management systems (AIMS) remains low despite the potential benefits. Electronic medical records, and hence AIMS, are at the intersection of patient safety. This article highlights advantages and barriers to adoption and implementation of IT in general and AIMS in particular, with a focus on clinical decision support systems (CDSS) and computerized physician order entry (CPOE) as hallmarks that may lead to improvement in patient safety and quality in the perioperative setting. Principal findings The advantages of health IT and AIMS include improved legibility of documentation; the ability to integrate new scientific evidence into practice; enhanced management and exchange of complex health information; the ability to standardize order sets, incorporate computerized physician order entry, and provide clinical decision support; and the ability to capture data for management, research, and quality monitoring and reporting. While not foolproof, AIMS have been shown to improve safety, quality, and patient outcomes. Barriers to the adoption of health IT and AIMS include costs, lack of truly interoperable AIMS components in health-system IT solutions, and lack of clinician involvement in implementation, planning, design, and installation of many IT or AIMS products. Conclusions Health IT and AIMS are at the intersection of patient safety and technology. Anesthesiologists are perfectly positioned to be the physician leaders of adoption, design, implementation, and integration, not only for AIMS but also for health-system IT solutions in general.