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J J van der Aa

Publications and source records attributed to J J van der Aa.

10 recordsLinked to original sources
PubMed1997

Computerized pre-anesthetic evaluation results in additional abstracted comorbidity diagnoses.

OBJECTIVE: To 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. METHODS: Nonrandomized, 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 institution's usual professional codes for ICD-9-CM discharge diagnoses and DRG assignment. RESULTS: For 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%. CONCLUSIONS: Supplemental information from a physician-entered, problem-oriented, computerized preanesthetic evaluation system improved discovery of diagnoses in the population studied.

Anesthesia↗
PubMed1995

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

The effects of positive end-expiratory 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.(ABSTRACT TRUNCATED AT 250 WORDS)

Anesthesiology↗
PubMed1994

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.

Hospital Information Systems↗
PubMed1987

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.

Airway Resistance↗
PubMed1987

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.

Algorithms↗
PubMed1985

Capnography and the Bain circuit I: A computer model.

The Mapleson D anesthesia breathing system has no valves and allows rebreathing of carbon dioxide. Its coaxial version is known as the Bain system. The interpretation of capnograms obtained during its use requires an understanding of the interrelationships of patient and system variables. Toward that end, a systematic description of mechanical ventilation with the Bain circuit was undertaken based on the physical laws of gas transport. The mathematical formulation of the model contains the relations between pressure, flow, and volume in the tube, alveolar space, and ventilator. The flows, calculated from these relations, are used to determine the CO2 concentrations in the different parts of the model. Two sets of data are used--patient and system. The patient data, used to solve the equations numerically, are lung-thorax compliance, CO2 inflow into alveolar space (CO2 production), functional residual capacity, dead space volume, airway resistance, and respiratory quotient. The ventilation system data comprise the dimensions and volumes of the Bain circuit, ventilator, connectors, and tubes; spill valve pressure; resistances to flow in the individual tube parts; ventilator settings; and fresh-gas flow rates. After incorporation of a volunteer's respiratory variables into the model, capnograms obtained from the model compared well with those obtained from the volunteer. The structure of the model is such that it permits easy introduction or changes of patient and system variables to obtain individual results or model specific circumstances. This flexibility makes it a useful tool for understanding the properties of the Bain circuit under a variety of clinical circumstances. The results may be displayed in a number of different ways.

Anesthesia, General↗
PubMed1984

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.

Anesthesiology↗
PubMedDate not supplied

Computer-modulated patient-controlled analgesia. Preliminary evaluation of a prototype.

BACKGROUND AND OBJECTIVES: To provide patients with better postoperative pain relief, the authors developed a prototype computer-controlled infusion pump capable of establishing a steady drug plasma concentration based on patient needs. METHODS: A two-compartment pharmacokinetic model was used to compute the required infusion scheme. Using known pharmacokinetic parameters, the model and the pump's accuracy were studied in four dogs. In the first part of the study, the morphine pharmacokinetic profile of each dog was analyzed and used to develop the parameters of a model tailored to that particular dog. In the second part, this tailored model was implemented to test whether the infusion device was able to achieve the desired concentration profile. RESULTS: The computer-controlled infusion device was able to achieve all the desired plasma concentrations. CONCLUSIONS: These data suggest that it is possible to refine postoperative pain management with adaptive computer algorithms implemented to establish stable plasma analgesic concentrations and to automatically wean the analgesic over time.

Algorithms↗