Jan J. van der Aa

Alarms and their limits in monitoring.

The need to incorporate alarms in monitoring systems is related to the growing complexity of monitoring and the large number of variables. For sophisticated alarms, information about the inputs to the patient is of importance; for example, clinical interventions such as drug administration and ventilation readjustment need to be known to the monitoring system. Alarms are triggered by signals or signal features that exceed thresholds. Each threshold must be seen as a level that needs to be set, either manually or automatically. The large number of levels to be set creates an extra workload for the clinician. Approaches to determine such levels automatically are discussed in this article. Most promising seems the multiple signal approach using an expert system. It seems reasonable to expect that information concerning alarm limits, needed for the operation of knowledge-based alarm systems, may come from integrated departmental data bases.

Computer-assisted capnogram analysis

Characteristic abnormal carbon dioxide waveforms from patients with mechanically ventilated lungs are observed when, for example, valves are incompetent, the airway is obstructed, the breathing circuit becomes disconnected, or a patient overrides mechanical ventilation with spontaneous breaths. Automated observation of the carbon dioxide waveform provides a uniform, concise, and consistent interpretation of the capnogram. This article describes a computer algorithm for analyzing and classifying capnograms as normal or as belonging to one of the categories above. The algorithm also generates a diagnostic message when the capnogram deviates from a learned norm for at least three consecutive waveforms (and thus reduces the influence of artifacts). Clinical experience shows reliable waveform recognition by the algorithm.

The efficiency of preoperative evaluation: a comparison of computerized and paper recording systems

Objective. We designed and implemented a preoperative evaluation record system with seven networked computers for use by physicians and other medical staff. This study compared the efficiency of the new computerized system with that of the paper system.Methods. We reviewed data from preoperative evaluations completed from November 1990 through December 1992. Data were analyzed automatically (Borland C program) for two intervals: (1) the waiting period, defined as the time the patient entered the waiting room until he or she entered the examination room; and (2) the examination period, defined as the time the patient entered the examination room until an evaluation form was printed. Data were obtained for 2,511 evaluations on paper and 8,342 by computer.Results. The average waiting period with the paper system was 56.1 ± 44.8 min; the average waiting period with the computerized system was 59.1 ± 47.0 min. The average examination period was nearly identical for both systems: 27.5 ± 23.6 min for the paper system; 28.5 ± 22.7 min for the computerized system.Conclusion. The computerized system required no more examination time than the manual system. In addition, we speculate that time is saved at other points of patient care by the legible, instantly retrievable preoperative evaluations that the computerized system produces.RésuméObjectif. Nous avons organisé un systéme enregistreur de l’évaluation préopératoire à l’aide d’un réseau de sept ordinateurs au service des médecins et d’autre personnel médical. Cette étude compare l’efficacité de ce systéme d’enregistrement par ordinateur au systéme d’enregistrement sur papier (manuscript).Méthodes. Nous avons revu les données des évaluations préopératoires effectuées entre novembre 1990 à décembre 1992. Parmis ces données, deux intervalles furent analysés (programme Borland C): 1. la période d’attente, définie comme le laps de temps entre l’entrée du malade en salle d’attente et son entrée dans la salle d’examen; et 2. la période d’examen, définie comme le laps de temps entre l’entrée du malade dans la salle d’examen et la reproduction du document d’évaluation préopératoire. Les données de 2.511 enregistrements manuscripts et de 8.342 enregistrements par ordinateur furent obtenus.Résultats. Pour le systéme manuscript, la période d’attente moyenne fut de 56,1 ± 44,8 minutes et de 59,1 ± 47 minutes pour le systéme par ordinateur. La période d’examen moyenne fut quasi identique pour les deux systemes: 27,5 ± 23.6 minutes pour le systéme manuscript contre 28.5 ± 22,7 minutes pour le systéme par ordinateur.Conclusion. Comparé au systéme manuscript, l’enregistrement par ordinateur ne prolonge pas le temps d’examen. Nous spéculons qu’un gain de temps peut se faire à d’autres étapes des soins médicaux grâce à la disponibilité d’évaluations préopératoires lisibles, délivrées instantanément par ordinateur.AbstractZiel. Ein System für die Dokumentation der präoperativen Patientenuntersuchung (Prämedikation) zur Verwendung durch ärztliches und sonstiges medizinisches Personal wurde entworfen und implementiert basierend auf 7 vernetzten Computern. Inhalt dieser Studie ist ein Vergleich der Effizienz des neuen Computer-gestützten Systems mit dem früheren Papier—gestützten manuellen System.Methoden. Wir untersuchten Datenmaterial aus Prämedikationsprotokollen des Zeitraums von November 1990 bis Dezember 1992. Die Daten wurden bezüglich zweier Zeitdauern automatisiert analysiert (mittels eines Borland C Programms): 1.) die Wartezeit der Patienten, gegeben durch den Zeitpunkt des Eintritts in den Warteraum bis zum Eintritt in das Untersuchungszimmer und 2.) die Untersuchungszeit, gegeben durch den Eintritt in das Untersuchungszimmer bis zum Ausdruck des kompletten Prämedikationsprotokolls. Das Datenmaterial umfa\t 2,511 Papier- und 8,342 Computer-gestützte Untersuchungsprotokolle.Ergebnisse. Die durchschnittliche Wartezeit betrug (56.1 ± 44.8) min. beim Papier-gestützten System und (59.1 ± 47.0) min. beim Computer-gestützten System. Die mittlere Untersuchungszeit war in beiden Fällen nahezu gleich: (27.5 ± 23.6) min. für das Papier- und (28.5 min ± 22.7) min. für das Computer-gestützte System.Folgerungen. Präoperative Untersuchungen, bei denen die Dokumentation mittels des Computer-gesützten Systems erfolgte, benötigten nicht mehr Zeit als solche bei denen manuell dokumentiert wurde. Wir vermuten, da\ aufgrund der Leserlichkeit und sofortigen Verfügbarkeit der vom System erstellten Prämedikationsprotokolle, an anderen Stellen in der Patientenversorgung Zeit eingespart wird.ResumenObjetivo. Disenamos e implementamos un sistema de registro de evaluatión preoperatoria con siete computadores conectados para ser usado por médicos y otro personal clínico. Este estudio comparó la eficiencia del nuevo sistema computerizado con la del sistema basado en registro en papel.Métodos. Revisamos informatión referente a evaluaciones preoperatorias completadas entre noviembre 1990 y diciembre 1992. La informatión fue analizada automaticamente (Programa en C, Borland) para dos intervalos: 1. El período de espera, definido como el tiempo entre la entrada del paciente a la sala de espera hasta que el o ella ingresó a la sala de examen, y 2. El período de examen, definido como el tiempo entre el ingreso del paciente a la sala de examen hasta que se imprimió el formulario de evaluatión. Se obtuvo informatión referente a 2,511 evaluaciones en papel y 8,342 efectuadas con computador.Resultados. El periodo de espera promedio con el sistema basado en papel fue 56.1 ± 44.8 minutos y con el sistema computerizado 59.1 ± 47 minutos. El período de examen promedio fue aproximademente identico para ambos sistemas: 27.5 ± 23.6 minutos para el sistema basado en papel y 28.5 ± 22.7 para el sistema computarizado.Conclusión. El sistema computarizado no requirió más tiempo de examen que el sistema manual. Especulamos que, en otros momentos del cuidado del paciente, el sistema computarizado pudiera resultar en ahorro de tiempo, debido a mejor legibilidad y recuperatión instantánea de las evaluaciones preoperatorias.

Computerized Pre-Anesthetic Evaluation Results in Additional Abstracted Comorbidity Diagnoses

ObjectiveTo study the impact of information from a physician-entry computerized preanesthetic evaluation system on the coding of International Classification of Diseases (ICD-9-CM) diagnoses and on hospital reimbursement due to alterations in diagnosis-related group (DRG) codes.MethodsNonrandomized, unblinded trial conducted at a 570-bed university tertiary care hospital. First without and then with reference to information contained on computer-based preanesthetic evaluation reports, medical charts were coded by the study institutions usual professional coders for ICD-9-CM discharge diagnoses and DRG assignment.ResultsFor 22 of 180 charts studied (12%, 95% confidence limits 7.4% to 16.7%), at least one ICD-9-CM diagnosis was added. Three of 84 DRG-based reimbursements were altered, increasing hospital reimbursement by 1.5%.ConclusionsSupplemental information from a physician-entered, problem-oriented, computerized preanesthetic evaluation system improved discovery of diagnoses in the population studied.

Comparison between oscillometric and invasive blood pressure monitoring during cardiac surgery

We compared values of invasive blood pressure measured intra-arterially with those measured noninvasively with an automated oscillometric monitor. Twenty-eight patients undergoing cardiac surgical procedures under general anesthesia were studied and 552 determinations were made. The two methods of measuring blood pressure correlated within the expected bounds of experimental accuracy and physiological variation. However, the correlation between invasive and noninvasive methods varied, apparently arbitrarily, with time. These disparities could not be explained by a linear combination of physiological variables recorded. Systolic determinations correlated the best and diastolic the least between the invasive and noninvasive methods. In general, the correlation was better for adults than for children, except with diastolic blood pressure.

Autoregulation in a Simulator-Based Educational Model of Intracranial Physiology

Objective.To implement a realistic autoregulation mechanism toenhance an existing educational brain model that displays in real-time thecerebral metabolic rate (CMRO2), cerebral blood flow (CBF),cerebral blood volume (CBV), intracranial pressure (ICP), and cerebralperfusion pressure (CPP). Methods.A dynamic cerebrovascular resistance(CVR) feedback loop adjusts automatically to maintain CBF within a range ofthe CPP and defines autoregulation. The model obtains physiologic parametersfrom a full-scale patient simulator. We assumed that oxygen demand andarterial partial pressure of carbon dioxide (CO2 responsivity) arethe two major factors involved in determining CBF. In addition, our brainmodel increases oxygen extraction up to 70% once CBF becomes insufficient tosupport CMRO2. The model was validated against data from theliterature. Results.The models response varied less than 9%from the literature data. Similarly, based on correlation coefficients betweenthe brain model and experimental data, a good fit was obtained for curvesdescribing the relationship between CBF and PaCO2 at a meanarterial blood pressure of 150 mm Hg (R2 = 0.92) and 100 mm Hg(R2 = 0.70). Discussion.The autoregulated brain model, withincorporated CO2 responsivity and a variable oxygen extraction,automatically produces changes in CVR, CBF, CBV, and ICP consistent withliterature reports, when run concurrently with a METI full-scale patientsimulator (Medical Education Technologies, Inc., Sarasota, Florida). Once themodel is enhanced to include herniation, vasospasm, and drug effects, itsutility will be expanded beyond demonstrating only basic neuroanesthesiaconcepts.

Capnography and the Bain circuit II: Validation of a computer model.

Validation of a computer model is described. The behavior of this model is compared both with mechanical ventilation of a test lung in a laboratory setup that uses a washout method and with manual ventilation. A comparison is also made with results obtained from a volunteer breathing spontaneously through a Bain circuit and with results published in the literature. This computer model is a multisegment representation of the Bain circuit and connecting tubing. For each segment, gas pressure, gas volume flow, and partial pressure of carbon dioxide are calculated for any number of breaths wanted. As a result, the time course of these variables can be generated for any location or, conversely, the carbon dioxide distribution in the system can be calculated for any time instant. A test lung, the human lungs, the ventilator bellows, and the reservoir bag are each represented by a single segment. The shapes of pressure and flow curves and of the capnograms taken at different locations in the Bain tubing are in good agreement. The washout study permits measurement of the time delay between the first expiration and the arrival of carbon dioxide at a particular location. The carbon dioxide level in the test lung decreases during inspiration and is stable during expiration. Quantitative agreement between model and experimental transport delays and carbon dioxide levels is such that the differences can be explained by the inaccuracy of the measurement. This is concluded from a sensitivity analysis. The study of the effect of segment size shows an almost optimal agreement between model behavior and experimental results for a 36-segment model. Execution of a thorough validation is imperative before such models can be used for clinical management and decision making or for teaching.

Pitfalls with mass spectrometry in clinical anesthesia

Mass spectrometry of respired gases puts a powerful analytic tool into the hand of the clinician. However, serious misinterpretations may result if the principle of operation and certain weaknesses of spectrometry are not appreciated. The potential pitfalls of clinical mass spectrometry are related to the need to have one unit serve many patients and to the design of the spectrometer and its algorithms.

Umbilical catheters and arterial blood pressure monitoring

The natural frequencies, damping coefficients, and accuracies of umbilical artery catheters were determined. The damping coefficients for the 3.5, 5.0, and 8.0 French catheters were 0.40 ± 0.04 (mean ± SD), 0.42 ± 0.05, and 0.19 ± 0.02, respectively. The natural frequencies were 24.2 ± 3.2 Hz (mean ± SD), 18.4 ± 3.5 Hz, and 26.8 ± 2.9 Hz, respectively. Measurements obtained with 3.5 and 8.0 French catheters were within 6% of the reference pressure at all pressures and rates tested. With the 5.0 French catheter, however, error greater than 10% from the reference pressure occurred when the rate was 200 pulses per minute or greater and the applied maximum pressure was 100 mm Hg or more.

Positive end-expiratory pressure and lung compliance : effect on delivered tidal volume

The effects of positive endexpiratory pressure (PEEP) and lung compliance (CL) on delivered tidal volume (VTdel) and ventilator output were evaluated in the following anaesthesia machine/ ventilator systems: Narkomed III with a Model AV-E ventilator (III/AV-E system) and an Ohmeda Modulus II with either a 7810 anaesthesia ventilator (II/7810 system) or a Model 7000 anaesthesia ventilator (II/7000 system). With a standard circle anaesthesia breathing circuit connected to a test lung simulating CL gas flow was measured and integrated over time at each combination of VT settings (VTset), 500 ml or 1000 ml; CL settings, 0.15 to 0.01 L · cm H2O−1 decreased incrementally; and PEEP settings, 0 to 30 cm H2O increased in 5- cm H2O increments. The integral of gas flow at the Y- piece of the breathing circuit was recorded as VTdel and at the output of the ventilator bellows as ventilator output. As CL decreased to 0.01 L · cm H2O− 1 and PEEP increased to 30 cm H2O, at VTset of 500 ml and 1000 ml, respective VTdel, decreased linearly to 251 ± 6 ml and 542 ± 7 with the III/AV- E, 201 ± 5 and 439 ± 5, with the II/7810, and 181 ± 4 and 433 ± 7 ml with the II/7000 (P < 0.05 among the three systems). Loss in VTdel due to PEEP alone, which increased only slightly when VTset was increased, accounted for an increasingly greater percentage of VTset as it was decreased, which was less pronounced with low CL. Effects of PEEP and CL on ventilator output were similar to those on VTdel but of lesser magnitude. During PEEP, VTset must be increased to compensate for loss in VTdel and expired VT must be monitored to prevent hypoventilation.RésuméLes effets de la pression expiratoire positive (PEEP) et de la compliance pulmonaire (CL) sur le volume courant généré (VTdel) et le débit du ventilateur mécanique sont évalués sur les appareils d’anesthésie équipés d’un ventilateur: Narkomed III avec un ventilateur AV- E (système III/AV- E) et un appareil d’anesthésie Ohmeda Modulus II équipé d’un ventilateur d’anesthésie 7810 (système 11/7810 ou d’un ventilateur d’anes thésie 7000 (système 11/7000). Avec une circuit standard avec absorption branché sur un poumon artificiel simulant la CL, le débit gazeux et mesuré et intégré par rapport au temps pour chacune des combinaisons de réglage du VT (VTset), 500 ml ou 1000 ml; de réglage de la CL de 0,15 à 0,01 L · cm H2O− 1 diminuée par plateau; réglage du PEEP augmenté par plateau de 0 à 30 cm H2O. Lorsque que la CL à 0,01 L · cm H2O− 1 et que le PEEP augmente à 30 cm H2O, aux VTset de 500 ml et 1000 ml, le VTdel diminue linéairement à 251 ± 6 ml et 542 ± 7 ml avec le III/AV- E, à 201 ± 5 et 439 ± 5 avec le II/7810, et à 181 ± 4 et 433 ± 7 ml avec le II/7000 (P < 0,05 entre les trois systèmes.) La perte de VTdel due au PEEP seul, qui n’augmente que légèrement quand le VTset est augmenté, explique un plus grand pourcentage de VTset, quand celuici est diminué, ce qui est moins prononcé quand la CL est basse. Les effets du PEEP et de la CL, sur le débit du ventilateur sont les mêmes que ceux notés sur le VTdel mais de moindre importance. Pendant le PEEP, VTset doit être augmenté pour compenser pour la perte de VTdel. Le VT expiré doit être monitoré pour prévenir l’hypoventilation.