Feedback Mechanisms Including Real-Time Electronic Alerts to Achieve Near 100% Timely Prophylactic Antibiotic Administration in Surgical Cases

Nair, Bala G.; Newman, Shu Fang; Peterson, Gene N.; Wu, Wei Ying; Schwid, Howard A.

doi:10.1213/ane.0b013e3181f46d89

Cited by 95 publications

(67 citation statements)

References 20 publications

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“…Smart Anesthesia Messenger (SAM) alert screen overlaid on anesthesia information management system screen. (Nair et al, 2010) In the course of the study period -june 2008 -jan 2010 -the weekly antibiotic compliance improved steadily, reaching a near 100% compliance at the end of step 4. (Fig.…”

Section: Decision Support Systems In Anesthesiamentioning

confidence: 97%

“…(Fig.10) Another group used the AIMS in combination with e-mail feedback of missed documentation, monthly summary reports and real-time electronic alerts to achieve a near 100% timely antibiotic prophylaxis; without filling out the antibiotic note, the AIMS anesthesia chart cannot be closed. (Nair et al, 2010) (Nair et al, 2010) This was combined with 'smart messages". (Fig.…”

Section: Decision Support Systems In Anesthesiamentioning

confidence: 99%

“…AIMS _ Anesthesia Information Management Systems; SAM _ Smart Anesthesia Messenger. (Nair et al, 2010) Another example of an anesthetic DSS is the creation of an electronic algorithm for detecting insufficient depth of anesthesia based on computing different MAC values of volatile anesthetics with different intravenous sedative or hypnotic agents administered concomitantly. (Mashour et al, 2009).…”

Section: Decision Support Systems In Anesthesiamentioning

confidence: 99%

See 2 more Smart Citations

Decision Support Systems in Anesthesia, Emergency Medicine and Intensive Care Medicine

Hemmerling¹

2011

Efficient Decision Support Systems - Practice and Challenges in Biomedical Related Domain

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Section: Decision Support Systems In Anesthesiamentioning

confidence: 97%

Section: Decision Support Systems In Anesthesiamentioning

confidence: 99%

Section: Decision Support Systems In Anesthesiamentioning

confidence: 99%

See 1 more Smart Citation

Decision Support Systems in Anesthesia, Emergency Medicine and Intensive Care Medicine

Hemmerling¹

2011

Efficient Decision Support Systems - Practice and Challenges in Biomedical Related Domain

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“…As for the second item, vigilantly following the different components of a glucose management protocol can often be difficult in a busy operating room where the anesthesia provider is responsible for multiple and concurrent patient care tasks. Not only in the context of glucose management, but also in relation to other clinical care items, the problem of keeping vigilance during a busy surgical procedure has been previously reported by us [24][25][26][27][28][29][30] and others [31][32][33][34][35]. Previously, real time decision support systems have been shown to be useful in improving the quality of care and patient safety [27][28][29][30][31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 97%

Intraoperative blood glucose management: impact of a real-time decision support system on adherence to institutional protocol

Nair

Grunzweig

Peterson

et al. 2015

J Clin Monit Comput

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Poor perioperative glycemic management can lead to negative surgical outcome. Improved compliance to glucose control protocol could lead to better glucose management. An Anesthesia Information Management System based decision support system-Smart Anesthesia Manager™ (SAM) was used to generate real-time reminders to the anesthesia providers to closely adhere to our institutional glucose management protocol. Compliance to hourly glucose measurements and correct insulin dose adjustments was compared for the baseline period (12 months) without SAM and the intervention period (12 months) with SAM decision support. Additionally, glucose management parameters were compared for the baseline and intervention periods. A total of 1587 cases during baseline and 1997 cases during intervention met the criteria for glucose management (diabetic patients or non-diabetic patients with glucose level >140 mg/dL). Among the intervention cases anesthesia providers chose to use SAM reminders 48.7 % of the time primarily for patients who had diabetes, higher HbA1C or body mass index, while disabling the system for the remaining cases. Compliance to hourly glucose measurement and correct insulin doses increased significantly during the intervention period when compared with the baseline (from 52.6 to 71.2 % and from 13.5 to 24.4 %, respectively). In spite of improved compliance to institutional protocol, the mean glucose levels and other glycemic management parameters did not show significant improvement with SAM reminders. Real-time electronic reminders improved intraoperative compliance to institutional glucose management protocol though glycemic parameters did not improve even when there was greater compliance to the protocol.

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“…6 Without real-time clinical decision support systems (CDSS) or further data analysis, AIMS may not necessarily improve quality or safety. 7 The purpose of this article is to highlight advantages and barriers to the adoption and implementation of IT in general and AIMS in particular, with a focus on CDSS and computerized physician order entry (CPOE) as hallmarks that may lead to improvement in patient safety and quality in the perioperative setting.…”

Section: Introduction and Purposementioning

confidence: 99%

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

Stabile

Cooper

2012

Can J Anesth/J Can Anesth

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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.

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Feedback Mechanisms Including Real-Time Electronic Alerts to Achieve Near 100% Timely Prophylactic Antibiotic Administration in Surgical Cases

Cited by 95 publications

References 20 publications

Decision Support Systems in Anesthesia, Emergency Medicine and Intensive Care Medicine

Decision Support Systems in Anesthesia, Emergency Medicine and Intensive Care Medicine

Intraoperative blood glucose management: impact of a real-time decision support system on adherence to institutional protocol

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

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