Eight year’s experience with automated anesthesia record keeping: Lessons learned—new directions taken

SummaryFor the past eight years, an automated anesthesia record keeping system, COMANDAS (COMputerized ANesthesia Data Acquisition System) has been used in the cardiovascular operating rooms at Mayo Clinic. The automated anesthesia record is designed to match the traditional hand-written record and becomes part of the official medical record. COMANDAS is interfaced with the physiologic monitor and mass spectrometer in each OR, and a number of other computers within the Mayo Medical Center. Since the introduction of COMANDAS over 24,000 surgical procedures have been charted. The anesthesia record is more complete, consistent in organization, and legible when compared to a hand-written record. Recently, it was determined that the computers and peripherals that make up COMANDAS were wearing out and that the vendors would no longer support or replace the equipment. A process to find a replacement for COMANDAS was then begun. Although the cardiovascular anesthesia group was satisfied with the automated anesthesia record, there were a number of areas in which improvement was desired. A systematic evaluation of the system was begun with a survey of the users. The majority of those surveyed felt that COMANDAS was a useful system which made parts of their job easier. The user interface, method of manual data entry, time to produce the record and difficulty learning the system were the source of the greatest dissatisfaction. Artifacts, networking, interfacing with other devices and computers were also issues for the replacement system. Most commercial systems were found wanting in one or more areas of significance. The most practical solution appeared to be the modification of a currently available intensive care unit patient data management system.

[1]  C B DeVos,et al.  An evaluation of an automated anesthesia record keeping system. , 1991, Biomedical sciences instrumentation.

[2]  F E Block Normal fluctuation of physiologic cardiovascular variables during anesthesia and the phenomenon of “smoothing” , 1991, Journal of clinical monitoring.

[3]  N.V. Thakor,et al.  Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection , 1991, IEEE Transactions on Biomedical Engineering.

[4]  J. S. McDonald,et al.  Differences between handwritten and automatic blood pressure records. , 1989, Anesthesiology.

[5]  Richard I. Cook,et al.  Systematic Bias in Handwritten Anesthetic Records , 1988 .

[6]  T A Noel,et al.  Computerized anesthesia records may be dangerous. , 1986, Anesthesiology.

[7]  H. T. Nagle,et al.  A comparison of the noise sensitivity of nine QRS detection algorithms , 1990, IEEE Transactions on Biomedical Engineering.

[8]  J S Gravenstein The automated anesthesia record , 1991, Anaesthesiologie und Reanimation.

[9]  Ls Nolan,et al.  The P1073 Medical Information Bus Standard: Overview and Benefits for Clinical Users. , 1990 .

[10]  R M Zollinger,et al.  Man-made versus computer-generated anesthesia records. , 1977, The Journal of surgical research.

[11]  J. S. Graenstein The Automated anesthesia record and alarm systems , 1987 .

[12]  R. F. Gibbs,et al.  The present and future medicolegal importance of record keeping in anesthesia and intensive care: The case for automation , 1989, Journal of clinical monitoring.

[13]  R. McCarthy,et al.  ANALYSIS OF THE ACCURACY OF THE ANESTHETIC RECORD , 1987 .