Pediatric cardiac surgery: machine learning models for postoperative complication prediction

PURPOSE

Managing children undergoing cardiac surgery with cardiopulmonary bypass (CPB) presents a significant challenge for anesthesiologists. Machine Learning (ML)-assisted tools have the potential to enhance the recognition of patients at risk of complications and predict potential issues, ultimately improving outcomes.

METHODS

We evaluated the prediction capacity of six models, ranging from logistic regression to support vector machine, using a dataset comprising 33 variables and 1364 subjects. The Area Under the Curve (AUC) and the F1 score served as the primary evaluation metrics. Our primary objectives were twofold: first, to develop an effective prediction model, and second, to create a user-friendly comprehensive model for identifying high-risk patients.

RESULTS

The logistic regression model demonstrated the highest effectiveness, achieving an AUC of 83.65%, and an F1 score of 0.7296, with balanced sensitivity and specificity of 77.94% and 76.47%, respectively. In comparison, the comprehensive three-layer decision tree model achieved an AUC of 72.84%, with sensitivity (79.41%) comparable to more complex models.

CONCLUSION

Our machine learning-assisted tools provide an additional perspective and enhance the predictive capabilities of traditional scoring methods. These tools can assist anesthesiologists in making well-informed decisions. Furthermore, we have successfully demonstrated the feasibility of creating a practical white-box model. The next steps involve conducting clinical validation and multicenter cross-validation.

TRIAL REGISTRATION

NCT05537168.

A Mobile Post Anesthesia Care Unit Order Reminder System Improves Timely Order Entry

Transition to the postanesthesia care unit (PACU) requires timely order placement by anesthesia providers. Computerized ordering enables automated order reminder systems, but their value is not fully understood. We performed a single-center, retrospective cohort study to estimate the association between automated PACU order reminders and primary outcomes (1) on-time order placement and (2) the degree of delay in placement. As a secondary post-hoc analysis, we studied the association between late order placement and PACU outcomes. We included patients with a qualifying postprocedure order from January 1, 2019, to May 31, 2023. We excluded cases transferred directly to the ICU, whose anesthesia provider was involved in the pilot testing of the reminder system, or those with missing covariate data. Order reminder system usage was defined by the primary attending anesthesiologist's receipt of a push notification reminder on the day of surgery. We estimated the association between reminder system usage and timely order placement using a logistic regression. For patients with late orders, we performed a survival analysis of order placement. The significance level was 0.05. Patient (e.g., age, race), procedural (e.g., anesthesia duration), and provider-based (e.g., ordering privileges) variables were used as covariates within the analyses. Reminders were associated with 51% increased odds of order placement prior to PACU admission (Odds Ratio: 1.51; 95% Confidence Interval: 1.43, 1.58; p ≤ 0.001), reducing the incidence of late PACU orders from 17.5% to 12.6% (p ≤ 0.001). In patients with late orders, the reminders were associated with 10% quicker placement (Hazard Ratio: 1.10; 95% CI 1.05, 1.15; p < 0.001). On-time order placement was associated with decreased PACU duration (p < 0.001), decreased odds of peak PACU pain score (p < 0.001), and decreased odds of multiple administration of antiemetics (p = 0.02). An order reminder system was associated with an increase in order placement prior to PACU arrival and a reduction in delay in order placement after arrival.

Anesthesiologists in the Ether: Technology and Telemedicine in Anesthesiology

A new frontier in veterinary anesthesia telehealth has begun. With the adoption of electronic anesthetic records and video, phone, and chat consultations, an anesthesiologist can be integrated into the care team of any patient, anywhere in the world. This article reviews the benefits of adopting an electronic anesthetic record system, and the ways that practitioners can incorporate a virtual anesthesiologist into their care team.

Anaesthesia personnels' perspectives on digital anaesthesia information management systems - a qualitative study

Background

In Norway, the anaesthesia team normally consists of a nurse anaesthetist and an anaesthetist. Digital anesthesia information management systems (AIMS) that collect patient information directly from the anaesthesia workstation, and transmit the data into documentation systems have recently been implemented in Norway. Earlier studies have indicated that implementation of digital AIMS impacts the clinical workflow patterns and distracts the anaesthesia providers. These studies have mainly had a quantitative design and focused on functionality, installation designs, benefits and challenges associated with implementing and using AIMS. Hence, the aim of this study was to qualitatively explore anaesthesia personnel’s perspectives on implementing and using digital AIMS.

Methods

The study had an exploratory and descriptive design. The study was conducted within three non-university hospitals in Southern Norway. Qualitative, individual interviews with nurse anaesthetists (n = 9) and anaesthetists (n = 9) were conducted in the period September to December 2020. Data were analysed using qualitative content analysis according to the recommendations of Graneheim and Lundman.

Results

Four categories were identified: 1) Balance between clinical assessment and monitoring, 2) Vigilance in relation to the patient, 3) The nurse-physician collaboration, and 4) Software issues. Participants described that anaesthesia included a continuous balance between clinical assessment and monitoring. They experienced that the digital AIMS had an impact on their vigilance in relation to the patient during anaesthesia. The digital AIMS affected the nurse-physician collaboration. Moreover, participants emphasised a lack of user participation and aspects of user-friendliness regarding the implementation of digital AIMS.

Conclusion

Digital AIMS impacts vigilance in relation to the patient. Hence, collaboration and acceptance of the mutual responsibility between nurse anaesthetists and anaesthetists for both clinical observation and digital AIMS administration is essential. Anaesthesia personnel should be included in development and implementation processes to facilitate implementation.

An Environmental Scan of Anesthesia Information Management Systems in the American and Canadian Marketplace

Anesthesia Information Management Systems are specialized forms of electronic medical records used by anesthesiologists to automatically and reliably collect, store, and present perioperative patient data. There are no recent academic publications that outline the names and features of AIMS in the current American and Canadian marketplace. An environmental scan was performed to first identify existing AIMS in this marketplace, and then describe and compare these AIMS. We found 13 commercially available AIMS but were able to describe in detail the features and functionalities of only 10 of these systems, as three vendors did not participate in the study. While all AIMS have certain key features, other features and functionalities are only offered by some of the AIMS. Features less commonly offered included patient portals for pre-operative questionnaires, clinical decision support systems, and voice-to-text capability for documentation. The findings of this study can inform AIMS procurement efforts by enabling anesthesia departments to compare features across AIMS and find an AIMS whose features best fit their needs and priorities. Future studies are needed to describe the features and functionalities of these AIMS at a more granular level, and also assess the usability and costs of these systems.

Comparison of the Effects of Automated and Manual Record Keeping on Anesthetists' Monitoring Performance: Randomized Controlled Simulation Study

Background

Anesthesia information management systems (AIMSs) automatically import real-time vital signs from physiological monitors to anesthetic records, replacing part of anesthetists’ traditional manual record keeping. However, only a handful of studies have examined the effects of AIMSs on anesthetists’ monitoring performance.

Objective

This study aimed to compare the effects of AIMS use and manual record keeping on anesthetists’ monitoring performance, using a full-scale high-fidelity simulation.

Methods

This simulation study was a randomized controlled trial with a parallel group design that compared the effects of two record-keeping methods (AIMS vs manual) on anesthetists’ monitoring performance. Twenty anesthetists at a tertiary hospital in Hong Kong were randomly assigned to either the AIMS or manual condition, and they participated in a 45-minute scenario in a high-fidelity simulation environment. Participants took over a case involving general anesthesia for below-knee amputation surgery and performed record keeping. The three primary outcomes were participants’ (1) vigilance detection accuracy (%), (2) situation awareness accuracy (%), and (3) subjective mental workload (0-100).

Results

With regard to the primary outcomes, there was no significant difference in participants’ vigilance detection accuracy (AIMS, 56.7% vs manual, 56.7%; P=.50), and subjective mental workload was significantly lower in the AIMS condition than in the manual condition (AIMS, 34.2 vs manual, 46.7; P=.02). However, the result for situation awareness accuracy was inconclusive as the study did not have enough power to detect a difference between the two conditions.

Conclusions

Our findings suggest that it is promising for AIMS use to become a mainstay of anesthesia record keeping. AIMSs are effective in reducing anesthetists’ workload and improving the quality of their anesthetic record keeping, without compromising vigilance.

Application of dexmedetomidine-assisted intravertebral anesthesia in hip replacement and its influence on T-lymphocyte subsets

Application of dexmedetomidine-assisted intravertebral anesthesia for elderly patients with hip replacement and its influences on T-lymphocyte subsets in peripheral blood were assessed. Eighty-six patients undergoing intravertebral anesthesia in hip replacement were treated as group A, and one hundred patients undergoing intravertebral anesthesia combined with dexmedetomidine were treated as group B. Hemodynamic changes in both groups were compared 5 min before anesthesia (T0), immediately after skin incision (T1) and after surgery (T2). General operation conditions of patients in both groups were recorded. T-lymphocyte subsets, interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), visual analogue scale (VAS) pain scores and mini-mental state examination (MMSE) cognitive function changes before surgery and 24 h after surgery were compared between the groups, and the incidence of complications in both groups after 24 h was recorded. The recovery time of patients in group B was shorter than that of group A (P<0.05). Changes of systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate fluctuations in group B were lower than those in group A (P<0.05). At 24 h after surgery, VAS scores of group B were lower than those of group A (P<0.05); levels of IL-6 and TNF-α were lower than those of group A (P<0.05); CD3⁺ cells, CD4⁺ cells, CD8⁺ cells, and CD4/CD8 ratio were higher than those of group A (P<0.05), and MMSE score was higher than that of group A (P<0.05). The incidence of gastrointestinal reactions and postoperative cognitive dysfunction (POCD) in group B was lower than that in group A (P<0.05). In conclusion, administration of dexmedetomidine can effectively shorten the recovery time of patients, stabilize intraoperative hemodynamics of patients, protect immune function, and reduce postoperative pain and POCD occurrence during anesthesia of hip replacement.

Anesthesia Information Management Systems: Evolution of the Paper Anesthetic Record to a Multisystem Electronic Medical Record Network That Streamlines Perioperative Care

Initially devised in the 1890s, the traditional anesthetic record comprises physiological changes, crucial anesthetic or surgical events, and medications administered during the perioperative period. The timely collection of quality data facilitates situational awareness and point-of-care clinical decision making. The burgeoning volume and complexity of data in conjunction with financial incentives and the push for improved clinical documentation by regulatory bodies have prompted the transition away from paper records. Anesthesia Information Management Systems (AIMS) are specialized electronic health record networks that allow the anesthesia record to interface with hospital clinical data repositories, resulting in improvements in quality of care, patient safety, operations management, reimbursement, and translational research. Like most new technological advances, adoption was slow at first due to the challenges of integrating complex systems into daily clinical practice, questions about return on investment, and medicolegal liability. Recent technological advances, coupled with government incentives, have allowed AIMS adoption to reach an acceleration phase among US academic medical centers; widespread utilization of AIMS by 84% of US academic medical centers is expected by 2018-2020. Adoption among nonacademic US and European medical centers still remains low; information concerning Asian countries is limited to literature describing only single-hospital center experiences.

What we can learn from Big Data about factors influencing perioperative outcome

PURPOSE OF REVIEW

This narrative review will discuss what value Big Data has to offer anesthesiology and aims to highlight recently published articles of large databases exploring factors influencing perioperative outcome. Additionally, the future perspectives of Big Data and its major pitfalls will be discussed.

RECENT FINDINGS

The potential of Big Data has given an incentive to create nationwide and anesthesia-initiated registries like the MPOG and NACOR. These large databases have contributed in elucidating some of the rare perioperative complications, such as declined cognition after exposure to general anesthesia and epidural hematomas in parturients. Additionally, they are useful in finding patterns such as similar outcome in subtypes of beta-blockers and lower incidence of pneumonia in preoperative influenza vaccinations in the elderly.

SUMMARY

Big Data is becoming increasingly popular with the collaborative collection of registries offering anesthesia a way to explore rare perioperative complications and outcome to encourage further hypotheses testing. Although Big Data has its flaws in security, lack of expertise and methodological concerns, the future potential of analytics combined with genomics, machine learning and real-time decision support looks promising.

Man vs machine in emergency medicine - a study on the effects of manual and automatic vital sign documentation on data quality and perceived workload, using observational paired sample data and questionnaires

BACKGROUND

Emergency medicine is characterized by a high patient flow where timely decisions are essential. Clinical decision support systems have the potential to assist in such decisions but will be dependent on the data quality in electronic health records which often is inadequate. This study explores the effect of automated documentation of vital signs on data quality and workload.

METHODS

An observational study of 200 vital sign measurements was performed to evaluate the effects of manual vs automatic documentation on data quality. Data collection using questionnaires was performed to compare the workload on wards using manual or automatic documentation.

RESULTS

In the automated documentation time to documentation was reduced by 6.1 min (0.6 min vs 7.7 min, p <  0.05) and completeness increased (98% vs 95%, p <  0.05). Regarding workflow temporal demands were lower in the automatic documentation workflow compared to the manual group (50 vs 23, p <  0.05). The same was true for frustration level (64 vs 33, p <  0.05). The experienced reduction in temporal demands was in line with the anticipated, whereas the experienced reduction in frustration was lower than the anticipated (27 vs 54, p < 0.05).

DISCUSSION

The study shows that automatic documentation will improve the currency and the completeness of vital sign data in the Electronic Health Record while reducing workload regarding temporal demands and experienced frustration. The study also shows that these findings are in line with staff anticipations but indicates that the anticipations on the reduction of frustration may be exaggerated among the staff. The open-ended answers indicate that frustration focus will change from double documentation of vital signs to technical aspects of the automatic documentation system.

Peri-Operative Anaesthetic Documentation: A Report of Three Sequential Audits on the Quality of Outcomes, with an Insight Into Surrounding Legal Issues

Objective

The aim of the audits was to assess contemporary performance, with comparison of the same against previous outcomes, to gauge trends in clinical practice. This allowed for completion of the audit cycle, as well as the ability to analyse and consistently improve the quality of care delivered to our patients.

Methods

We undertook three prospective audits on the quality of peri-operative anaesthetic documentation in the years 2009, 2011 and 2014, respectively. Anaesthetic records for patients undergoing elective as well as emergency surgical procedures were assessed for 'adequacy of peri-operative documentation' based on a combination of select criteria outlined by the Royal College of Anaesthetists and the Australian and New Zealand College of Anaesthetists.

Results

A total of 1000 anaesthetic records were analysed in 2009, followed by a review of 412 records and 376 documents in 2011 and 2014 respectively. In the year 2014, 43.8% of pre-operative anaesthetic records were 'appropriately' documented. This was in stark comparison to 16.3% and 25.9% in the years 2009 and 2011, respectively. The quantity of 'adequately' documented intra-operative records increased to 35.1% in 2014, in comparison to 25.5% and 22.7% in 2009 and 2011, respectively. There was an overall improvement in the standards of peri-operative documentation in consecutive audits.

Conclusion

We propose that regular audits on 'anaesthetic record keeping' can lead to an improvement in the standards of this often overlooked, but essential scope of our practice.

In- and out-hospital mortality rate in surgical patients

BACKGROUND

Death rates after surgery are increasingly analysed for clinical audit and quality assessment. Many studies commonly provide information only on deaths that occur during hospital stay, known as in-hospital death rates. By using hospital data set linked to death certificate registry, we recorded in- and out-hospital deaths within 30 and 60 post-operative days.

METHODS

The study included all consecutive surgical procedures (denominator) under general or locoregional anaesthesia in adult patients admitted for elective or non-elective inpatient surgery. Patients undergoing planned day-case surgery or obstetrical procedures were excluded. The primary outcome was 30- and 60-day post-operative mortality rate (numerator) whether before or after discharge.

RESULTS

The study material consisted of a sample of 36,494 surgical procedures corresponding to 28,202 patients. At 30-day, 384 (crude mortality rate of 1.1%) patients died, 314 (82%) during their hospitalisation and 70 (18%) after discharge. Factors that were associated with in-hospital mortality are ASA scores, emergency, duration of surgery and rate of admission to critical care unit. Within the 30-60 days interval, we recorded 231 supplemental deaths, 103 (45%) after discharge.

CONCLUSION

In-hospital mortality alone is an incomplete measure of mortality even within 30 days of care. To identify the missing deaths, hospital records need to be linked to data from death certificate. This connection with the national death registry will allow obtaining the rate of in-hospital and out-hospital death.

Vital Recorder-a free research tool for automatic recording of high-resolution time-synchronised physiological data from multiple anaesthesia devices

The current anaesthesia information management system (AIMS) has limited capability for the acquisition of high-quality vital signs data. We have developed a Vital Recorder program to overcome the disadvantages of AIMS and to support research. Physiological data of surgical patients were collected from 10 operating rooms using the Vital Recorder. The basic equipment used were a patient monitor, the anaesthesia machine, and the bispectral index (BIS) monitor. Infusion pumps, cardiac output monitors, regional oximeter, and rapid infusion device were added as required. The automatic recording option was used exclusively and the status of recording was frequently checked through web monitoring. Automatic recording was successful in 98.5% (4,272/4,335) cases during eight months of operation. The total recorded time was 13,489 h (3.2 ± 1.9 h/case). The Vital Recorder's automatic recording and remote monitoring capabilities enabled us to record physiological big data with minimal effort. The Vital Recorder also provided time-synchronised data captured from a variety of devices to facilitate an integrated analysis of vital signs data. The free distribution of the Vital Recorder is expected to improve data access for researchers attempting physiological data studies and to eliminate inequalities in research opportunities due to differences in data collection capabilities.

A Perioperative Systems Design to Improve Intraoperative Glucose Monitoring Is Associated with a Reduction in Surgical Site Infections in a Diabetic Patient Population

BACKGROUND

Diabetic patients receiving insulin should have periodic intraoperative glucose measurement. The authors conducted a care redesign effort to improve intraoperative glucose monitoring.

METHODS

With approval from Vanderbilt University Human Research Protection Program (Nashville, Tennessee), the authors created an automatic system to identify diabetic patients, detect insulin administration, check for recent glucose measurement, and remind clinicians to check intraoperative glucose. Interrupted time series and propensity score matching were used to quantify pre- and postintervention impact on outcomes. Chi-square/likelihood ratio tests were used to compare surgical site infections at patient follow-up.

RESULTS

The authors analyzed 15,895 cases (3,994 preintervention and 11,901 postintervention; similar patient characteristics between groups). Intraoperative glucose monitoring rose from 61.6 to 87.3% in cases after intervention (P = 0.0001). Recovery room entry hyperglycemia (fraction of initial postoperative glucose readings greater than 250) fell from 11.0 to 7.2% after intervention (P = 0.0019), while hypoglycemia (fraction of initial postoperative glucose readings less than 75) was unchanged (0.6 vs. 0.9%; P = 0.2155). Eighty-seven percent of patients had follow-up care. After intervention the unadjusted surgical site infection rate fell from 1.5 to 1.0% (P = 0.0061), a 55.4% relative risk reduction. Interrupted time series analysis confirmed a statistically significant surgical site infection rate reduction (P = 0.01). Propensity score matching to adjust for confounders generated a cohort of 7,604 well-matched patients and confirmed a statistically significant surgical site infection rate reduction (P = 0.02).

CONCLUSIONS

Anesthesiologists add healthcare value by improving perioperative systems. The authors leveraged the one-time cost of programming to improve reliability of intraoperative glucose management and observed improved glucose monitoring, increased insulin administration, reduced recovery room hyperglycemia, and fewer surgical site infections. Their analysis is limited by its applied quasiexperimental design.

An automated real-time method for the detection of patients at risk for malignant hyperthermia

BACKGROUND

Malignant hyperthermia (MH) is a rare anesthetic pharmacogenetic disorder that can be difficult to detect in its earliest phases. Prompt treatment is known to improve outcomes. The modern anesthesia information management systems (AIMS) collect enormous amounts of data. However, data lack context and are not able to provide real-time guidance. Utilizing our AIMS, we developed the capacity to incorporate decision support.

AIMS

We describe the creation and evaluation of a real-time detection tool for MH.

METHODS

Cases of MH from 2003 to 2013 were retrospectively reviewed to confirm the diagnosis of MH and to calculate a MH clinical grading scale score. The index cases were utilized to develop four electronic data Rules, based on endtidal CO2 (ETCO2 ) and temperature criteria. The Rules were then applied retrospectively to the index cases and to a full cohort of general operating room (OR) patients from January 2012 to June 2012. If criteria for possible MH was met, the detection tool generated an alert on the monitor at the patient's bedside.

RESULTS

We identified seven patients with confirmed MH with MH Scores ranging from 28 to 70. Using four data Rules, all of our seven index cases were captured and generated an appropriate alert. Median time from MH computer alert time to dantrolene administration time among our index cases was 23 min (IQR 17-77). There were 938 false-positive alerts for possible MH (1.8%) when the Rules were applied to a general OR cohort of 51 579 total cases from January 2012 to June 2012.

CONCLUSIONS

We demonstrated a real-time MH detection tool based on established physiologic criteria that is sensitive enough to capture cases suspicious for MH, while limiting false positives to prevent alarm fatigue. This has the potential to notify the provider of possible MH such that treatment may be rapidly initiated.

A systematic review of near real-time and point-of-care clinical decision support in anesthesia information management systems

Anesthesia information management systems (AIMS) are sophisticated hardware and software technology solutions that can provide electronic feedback to anesthesia providers. This feedback can be tailored to provide clinical decision support (CDS) to aid clinicians with patient care processes, documentation compliance, and resource utilization. We conducted a systematic review of peer-reviewed articles on near real-time and point-of-care CDS within AIMS using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Studies were identified by searches of the electronic databases Medline and EMBASE. Two reviewers screened studies based on title, abstract, and full text. Studies that were similar in intervention and desired outcome were grouped into CDS categories. Three reviewers graded the evidence within each category. The final analysis included 25 articles on CDS as implemented within AIMS. CDS categories included perioperative antibiotic prophylaxis, post-operative nausea and vomiting prophylaxis, vital sign monitors and alarms, glucose management, blood pressure management, ventilator management, clinical documentation, and resource utilization. Of these categories, the reviewers graded perioperative antibiotic prophylaxis and clinical documentation as having strong evidence per the peer reviewed literature. There is strong evidence for the inclusion of near real-time and point-of-care CDS in AIMS to enhance compliance with perioperative antibiotic prophylaxis and clinical documentation. Additional research is needed in many other areas of AIMS-based CDS.

Comparison of minute distribution frequency for anesthesia start and end times from an anesthesia information management system and paper records

Use of an anesthesia information management system (AIMS) has been reported to improve accuracy of recorded information. We tested the hypothesis that analyzing the distribution of times charted on paper and computerized records could reveal possible rounding errors, and that this effect could be modulated by differences in the user interface for documenting certain event times with an AIMS. We compared the frequency distribution of start and end times for anesthesia cases completed with paper records and an AIMS. Paper anesthesia records had significantly more times ending with "0" and "5" compared to those from the AIMS (p < 0.001). For case start times, AIMS still exhibited end-digit preference, with times whose last digits had significantly higher frequencies of "0" and "5" than other integers. This effect, however, was attenuated compared to that for paper anesthesia records. For case end times, the distribution of minutes recorded with AIMS was almost evenly distributed, unlike those from paper records that still showed significant end-digit preference. The accuracy of anesthesia case start times and case end times, as inferred by statistical analysis of the distribution of the times, is enhanced with the use of an AIMS. Furthermore, the differences in AIMS user interface for documenting case start and case end times likely affects the degree of end-digit preference, and likely accuracy, of those times.

Paperless anesthesia: uses and abuses of these data

Demonstrably accurate records facilitate clinical decision making, improve patient safety, provide better defense against frivolous lawsuits, and enable better medical policy decisions. Anesthesia Information Management Systems (AIMS) have the potential to improve on the accuracy and reliability of handwritten records. Interfaces with electronic recording systems within the hospital or wider community allow correlation of anesthesia relevant data with biochemistry laboratory results, billing sections, radiological units, pharmacy, earlier patient records, and other systems. Electronic storage of large and accurate datasets has lent itself to quality assurance, enhancement of patient safety, research, cost containment, scheduling, anesthesia training initiatives, and has even stimulated organizational change. The time for record making may be increased by AIMS, but in some cases has been reduced. The question of impact on vigilance is not entirely settled, but substantial negative effects seem to be unlikely. The usefulness of these large databases depends on the accuracy of data and they may be incorrect or incomplete. Consequent biases are threats to the validity of research results. Data mining of biomedical databases makes it easier for individuals with political, social, or economic agendas to generate misleading research findings for the purpose of manipulating public opinion and swaying policymakers. There remains a fear that accessibility of data may have undesirable regulatory or legal consequences. Increasing regulation of treatment options during the perioperative period through regulated policies could reduce autonomy for clinicians. These fears are as yet unsubstantiated.

Exploring the past, present and future of care home medicine management systems: pharmacists' perceptions of multicompartment compliance aids

Objectives

Medicines maintain and improve care home (CH) residents' health and therefore, it is imperative that CH medicine management systems are regularly evaluated to ensure they continually provide a high standard of care. Multicompartment compliance aid (MCA) medicine management systems are often used to assist United Kingdom CH staff with managing the large volume of medicines used by residents. This study aimed to identify the factors that led to the widespread adoption of MCAs into United Kingdom CHs, limitations associated with their current use and their relevance in the future.

Method

In June and July 2014 semi-structured interviews were conducted with eight pharmacists who were purposively selected for their expertise in CH medicine management systems in the United Kingdom. A qualitative thematic approach was employed in the analysis of data.

Key findings

Findings indicated that MCAs were introduced into CHs to address unsafe medicine administration practices and because of pharmacy commercial interest. Identified limitations included reduced staff alertness during medicine administration, restricted ability to identify medicines, and medicine wastage. Participants predicted continued use of MCAs in the future due to their perceived benefits of improved safety and efficiency, although some pharmacists recommended that they be removed and CH staff trained to administer medicines from original packaging.

Conclusion

These findings can contribute towards information used by health care providers when deciding on the relevance of MCAs in their current medicine management systems. Additionally, they can contribute towards information used by policy makers when revising United Kingdom CH medicine management guidelines.

A case study evaluation of a Critical Care Information System adoption using the socio-technical and fit approach

BACKGROUND

Clinical information systems have long been used in intensive care units but reports on their adoption and benefits are limited. This study evaluated a Critical Care Information System implementation.

METHODS

A case study summative evaluation was conducted, employing observation, interview, and document analysis in operating theatres and 16-bed adult intensive care units in a 400-bed Malaysian tertiary referral centre from the perspectives of users (nurses and physicians), management, and information technology staff. System implementation, factors influencing adoption, fit between these factors, and the impact of the Critical Care Information System were evaluated after eight months of operation.

RESULTS

Positive influences on system adoption were associated with technical factors, including system ease of use, usefulness, and information relevancy; human factors, particularly user attitude; and organisational factors, namely clinical process-technology alignment and champions. Organisational factors such as planning, project management, training, technology support, turnover rate, clinical workload, and communication were barriers to system implementation and use. Recommendations to improve the current system problems were discussed. Most nursing staff positively perceived the system's reduction of documentation and data access time, giving them more time with patients. System acceptance varied among doctors. System use also had positive impacts on timesaving, data quality, and clinical workflow.

CONCLUSIONS

Critical Care Information Systems is crucial and has great potentials in enhancing and delivering critical care. However, the case study findings showed that the system faced complex challenges and was underutilised despite its potential. The role of socio-technical factors and their fit in realizing the potential of Critical Care Information Systems requires continuous, in-depth evaluation and stakeholder understanding and acknowledgement. The comprehensive and specific evaluation measures of the Human-Organisation-Technology Fit framework can flexibly evaluate Critical Care Information Systems.

Anesthesia information management systems in the ambulatory setting: benefits and challenges

Adopting an anesthesia information management system (AIMS) is a challenge for anesthesia departments. The transition requires a physician champion and the support of members in every section. This change can be facilitated by visiting similar institutions that are already using AIMS, shadow charting for a sufficient period of time, and understanding that optimization continues after the go-live date. Once implemented, the benefits outweigh the challenges, but understanding where the potential obstacles lie is critical to removing them efficiently and effectively. As different AIMS continue to spread throughout the medical world, so will their benefits.

Technological advances in perioperative monitoring: Current concepts and clinical perspectives

Minimal mandatory monitoring in the perioperative period recommended by Association of Anesthetists of Great Britain and Ireland and American Society of Anesthesiologists are universally acknowledged and has become an integral part of the anesthesia practice. The technologies in perioperative monitoring have advanced, and the availability and clinical applications have multiplied exponentially. Newer monitoring techniques include depth of anesthesia monitoring, goal-directed fluid therapy, transesophageal echocardiography, advanced neurological monitoring, improved alarm system and technological advancement in objective pain assessment. Various factors that need to be considered with the use of improved monitoring techniques are their validation data, patient outcome, safety profile, cost-effectiveness, awareness of the possible adverse events, knowledge of technical principle and ability of the convenient routine handling. In this review, we will discuss the new monitoring techniques in anesthesia, their advantages, deficiencies, limitations, their comparison to the conventional methods and their effect on patient outcome, if any.

Accuracy of manual entry of drug administration data into an anesthesia information management system

PURPOSE

Data on drug administration are entered manually into anesthesia information management systems (AIMS). This study examined whether these data are accurate regarding drug name, dose administered, and time of administration, and whether the stage of anesthesia influences data accuracy.

METHODS

Real-time observational data on drug administration during elective operations were compared with computerized information on drug administration entered by anesthesiologists. A trained observer (K.D.) performed the observations.

RESULTS

Data were collected during 57 operations which included 596 separate occasions of drug administration by 22 anesthesiologists. No AIMS records were found for 90 (15.1%) occasions of drug administration (omissions), while there were 11 (1.8%) AIMS records where drug administration was not observed. The AIMS and observer data matched for drug name on 495 of 596 (83.1%) occasions, for dose on 439 of 495 (92.5%) occasions, and for time on 476 of 495 (96.2%) occasions. Amongst the 90 omitted records, 34 (37.8%) were for vasoactive drugs with 24 (27.7%) for small doses of hypnotics. Omissions occurred mostly during maintenance: 50 of 153 (24.6%), followed by induction: 30 of 325 (9.2%) and emergence: 10 of 57 (17.5%) (P < 0.001). Time and dose inaccuracies occurred mainly during induction, followed by maintenance and emergence; time inaccuracies were 7/325 (8.3%), 10/203 (4.9%), and 0/57 (0%), respectively (P = 0.07), and dose inaccuracies were 15/325 (4.6%), 3/203 (1.5%), and 1/57 (1.7%), respectively (P = 0.11).

CONCLUSION

The range of accuracy varies when anesthesiologists manually enter drug administration data into an AIMS. Charting omissions represent the largest cause of inaccuracy, principally by omissions of records for vasopressors and small doses of hypnotic drugs. Manually entered drug administration data are not without errors. Accuracy of entering drug administration data remains the responsibility of the anesthesiologist.

Adapting the design of Anesthesia Information Management Systems to innovations depicted in Industrial Property documents

The purpose of this paper is to present the design and the current development status of an Anesthesia Information Management System (AIMS). For this system, the physical and technical advances, depicted in relevant, recently published Industrial Property documents, have been taken into account. Additional innovative sensors create further data-load to be managed. Novel wireless data-transmission modes demand eventually compliance to further proper standards, so that interoperability between AIMS and the existing Hospital Information Systems is being sustained. We attempted to define, the state-of-the-art concerning the functions, the design-prerequisites and the relevant standards and of an "emerging" AIMS that is combining hardware innovation, real-time data acquisition, processing and displaying and lastly enabling the necessary interoperability with the other components of the existing Hospital Information Systems. Finally, we report based on this approach, about the design and implementation status, of our "real-world" system under development and discuss the multifarious obstacles encountered during this still on-going project.

Are anesthesia start and end times randomly distributed? The influence of electronic records

STUDY OBJECTIVE

To perform a frequency analysis of start minute digits (SMD) and end minute digits (EMD) taken from the electronic, computer-assisted, and manual anesthesia billing-record systems.

DESIGN

Retrospective cross-sectional review.

SETTING

University medical center.

MEASUREMENTS

This cross-sectional review was conducted on billing records from a single healthcare institution over a 15-month period. A total of 30,738 cases were analyzed. For each record, the start time and end time were recorded. Distributions of SMD and EMD were tested against the null hypothesis of a frequency distribution equivalently spread between zero and nine.

MAIN RESULTS

SMD and EMD aggregate distributions each differed from equivalency (P < 0.0001). When stratified by type of anesthetic record, no differences were found between the recorded and expected equivalent distribution patterns for electronic anesthesia records for start minute (P < 0.98) or end minute (P < 0.55). Manual and computer-assisted records maintained nonequivalent distribution patterns for SMD and EMD (P < 0.0001 for each comparison). Comparison of cumulative distributions between SMD and EMD distributions suggested a significant difference between the two patterns (P < 0.0001).

CONCLUSION

An electronic anesthesia record system, with automated time capture of events verified by the user, produces a more unified distribution of billing times than do more traditional methods of entering billing times.

Technology diffusion of anesthesia information management systems into academic anesthesia departments in the United States

BACKGROUND

Anesthesia information management systems (AIMS) are electronic health records that automatically import vital signs from patient monitors and allow for computer-assisted creation of the anesthesia record. When most recently surveyed in 2007, it was estimated that at least 16% of U.S. academic hospitals (i.e., with an anesthesia residency program) had installed an AIMS. At least an additional 28% reported that they were in the process of implementing, or searching for an AIMS. In this study, we updated the adoption figures as of May 2013 and examined the historical trend of AIMS deployment in U.S. anesthesia residency programs from the perspective of the theory of diffusion of technologic innovations.

METHODS

Questionnaires were sent by e-mail to program directors or their identified contact individuals at the 130 U.S. anesthesiology residency programs accredited as of June 30, 2012 by the Accreditation Council for Graduate Medical Education. The questionnaires asked whether the department had an AIMS, the year of installation, and, if not present, whether there were plans to install an AIMS within the next 12 months. Follow-up e-mails and phone calls were made until responses were obtained from all programs. Results were collected between February and May 2013. Implementation percentages were determined using the number of accredited anesthesia residency programs at the start of each academic year between 1987 and 2013 and were fit to a logistic regression curve using data through 2012.

RESULTS

Responses were received from all 130 programs. Eighty-seven (67%) reported that they currently are using an AIMS. Ten programs without a current AIMS responded that they would be installing an AIMS within 12 months of the survey. The rate of AIMS adoption by year was well fit by a logistic regression curve (P = 0.90).

CONCLUSIONS

By the end of 2014, approximately 75% of U.S. academic anesthesiology departments will be using an AIMS, with 84% adoption expected between 2018 and 2020. Historical adoption of AIMS has followed Roger's 1962 formulation of the theory of diffusion of innovation.

Evaluation of the clinical process in a critical care information system using the Lean method: a case study

Background

There are numerous applications for Health Information Systems (HIS) that support specific tasks in the clinical workflow. The Lean method has been used increasingly to optimize clinical workflows, by removing waste and shortening the delivery cycle time. There are a limited number of studies on Lean applications related to HIS. Therefore, we applied the Lean method to evaluate the clinical processes related to HIS, in order to evaluate its efficiency in removing waste and optimizing the process flow. This paper presents the evaluation findings of these clinical processes, with regards to a critical care information system (CCIS), known as IntelliVue Clinical Information Portfolio (ICIP), and recommends solutions to the problems that were identified during the study.

Methods

We conducted a case study under actual clinical settings, to investigate how the Lean method can be used to improve the clinical process. We used observations, interviews, and document analysis, to achieve our stated goal. We also applied two tools from the Lean methodology, namely the Value Stream Mapping and the A3 problem-solving tools. We used eVSM software to plot the Value Stream Map and A3 reports.

Results

We identified a number of problems related to inefficiency and waste in the clinical process, and proposed an improved process model.

Conclusions

The case study findings show that the Value Stream Mapping and the A3 reports can be used as tools to identify waste and integrate the process steps more efficiently. We also proposed a standardized and improved clinical process model and suggested an integrated information system that combines database and software applications to reduce waste and data redundancy.

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

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.

New technologies in pediatric anesthesia

This article reviews potential pediatric applications of 3 new technologies. (1) Pulse oximetry-based hemoglobin determination: Hemoglobin determination using spectrophotometric methods recently has been introduced in adults with varied success. This non-invasive and continuous technology may avoid venipuncture and unnecessary transfusion in children undergoing surgery with major blood loss, premature infants undergoing unexpected and complicated emergency surgery, and children with chronic illness. (2) Continuous cardiac output monitoring: In adults, advanced hemodynamic monitoring such as continuous cardiac output monitoring has been associated with better surgical outcomes. Although it remains unknown whether similar results are applicable to children, current technology enables the monitoring of cardiac output non-invasively and continuously in pediatric patients. It may be important to integrate the data about cardiac output with other information to facilitate therapeutic interventions. (3) Anesthesia information management systems: Although perioperative electronic anesthesia information management systems are gaining popularity in operating rooms, their potential functions may not be fully appreciated. With advances in information technology, anesthesia information management systems may facilitate bedside clinical decisions, administrative needs, and research in the perioperative setting.