Computerized ventilator data selection: artifact rejection and data reduction

OBJECTIVE

To determine acceptable strategies for automated data acquisition and artifact rejection from computerized ventilators using the Medical Information Bus.

DESIGN

Medical practitioners were surveyed to establish 'clinically important' ventilator events. A prospective study involving frequent data collection from ventilators was also conducted.

SUBJECTS

Data from 10 adult patients were collected every 10 seconds from a Puritan Bennett 7200A ventilator for a total of 617.1 hours.

INTERVENTIONS

Twelve different computerized data selection and artifact algorithms were tested and evaluated.

MEASUREMENTS AND MAIN RESULTS

Data derived from 12 data selection algorithms were compared with each other and with data manually charted by respiratory therapists into a computerized charting system. Ventilator setting data collected by the algorithms, such as FIO2, reduced the amount of data collected to about 25% compared to manually charted data. The amount of data collected for measured parameters, such as tidal volume, from the ventilator had large variability and many artifacts. Automated data capture and selection generally increased the amount of data collected compared to manual charting, for example for the 3 minute median the increase was a modest 1.2 times.

CONCLUSION

Computerized methods for collecting ventilator setting data were relatively straightforward and more-efficient than manual methods. However, the method for automated selection and presentation of observed measured parameters is much more difficult. Based on the findings and analysis presented here, the authors recommend recording ventilator setting data after they have existed for three minutes and measured parameters using a three minute median data selection strategy. Such an algorithm rejected most artifacts, required minimal computational time, had minimal time-delay, and provided clinically acceptable data acquisition. The results presented here are but a starting point in developing automated ventilator data selection strategies.

Perspectives on development of IEEE 1073: the Medical Information Bus (MIB) standard

Automated data capture from bedside patient medical devices is now possible using a new Institute of Electrical and Electronic Engineering (IEEE) and American National Standards Institute (ANSI) Medical Information Bus (MIB) data communications standard (IEEE 1073). The first two standard documents, IEEE 1073.3.1 (Transportation Profile) and IEEE 1073.4.1 (Physical Layer), define the hardware protocol for bedside device communications. With the above noted IEEE MIB standards in place, hospitals can now start designing customized applications for acquiring data from bedside devices such as bedside monitors, i.v. pumps, ventilators, etc. for multiple purposes. The hardware 'plug and play' features of the MIB will enable nurses and physicians to establish communications with these devices simply and conveniently by plugging them into a bedside data connector. No other action will be necessary to establish identification of the device or communications with the device. Presently to connect bedside devices, technical help from hardware and software experts are required to establish such communications links. As a result of standardization of communications, it will be easy to establish a highly mobile network of bedside devices and more promptly and efficiently collect patient related data. Collection of data automatically should lead to the design of new medical computing applications that will tie in directly with the emerging mission and operations of hospitals. The MIB will permit acquisition of patient data more efficiently with greater accuracy, more completeness and more promptly. The above noted features are all essential to the development of computerized treatment protocols and should lead to improved quality of patient care. This manuscript provides the rational and historical overview of the development of the MIB standard.

Medical Information Bus usage for automated IV pump data acquisition: evaluation of usage patterns

OBJECTIVE

To identify factors which influence the choice of nurses to use automated collection of i.v. pump data from a prototype Medical Information Bus.

DESIGN

Observational study for a duration of three and one-half months.

SETTING

Four intensive care units, each with different missions, in an adult hospital.

SUBJECTS

One hundred fifty-eight registered nurses including both full and part time.

MEASUREMENTS AND MAIN RESULTS

Data were collected from the hospital information system about infusion orders including the type of medication, the number of rate changes, the method of documenting rate changes and the infusion methods. The method of documentation for infusion rate changes was defined as either automated, using a prototype Medical Information Bus (MIB), or manual, using the keyboard at a bedside computer terminal. The method of infusion was defined as either straight gravity feed without an i.v. pump ('no pump'), infusion using a pump but without connection to the hospital information system ('pump only') and infusion using a pump which was connected to the hospital information system using a prototype Medical Information Bus ('automated'). A total of 22,199 rate changes were documented during the study period and of those, 22,055 (99.35%) used the 'automated' method. Medications with the highest average rate change per single container were; Nitroprusside Sodium (9.50), Epinephrine (9.08) and Epoprostenol (7.50).

CONCLUSIONS

The nurses used automated i.v. pump data acquisition with medications which required frequent rate changes.

A preliminary assessment of intra-oral lubricating systems for dry mouth patients

OBJECTIVE

To provide extended intra-oral delivery of a saliva substitute.

INTERVENTION

Three different types of prostheses containing saliva substitute were designed and assessed: a two-part device resembling a mandibular complete denture sealed by cobalt-samerium magnets, a one-part clear resin device for the edentate patients and a flexible mouth guard type of appliance containing a lubricant releasing bubble for the dentate patients.

SETTING

A teaching hospital Oral Medicine and Rheumatology Clinic.

SUBJECTS

8 edentate and 3 dentate Sjogren Syndrome sufferers.

OUTCOME MEASURES

Subjective dryness after a week of wearing the lubricating appliance.

RESULTS

The majority of the subjects wore the appliances for 6-12 hours during each 24 hours. The initial dryness severity diminished after wearing the lubricating prosthesis. The patients preferred to wear the appliance at night.

CONCLUSION

All criteria were fulfilled on designing a saliva substitute lubricating appliance and some of the subjects have worn this prosthesis successfully for up to 3 years. Particular benefit was obtained by night-time wear.

Misconceptions about classical psychophysics and the measurement of response bias

Misconceptions exist about the ability of classical psychophysical techniques to measure separately the sensory and nonsensory (response bias) factors in a discrimination task. The views of the early researchers in psychophysics are reviewed. The manner in which the method of constant stimuli gives separate measures of sensory sensitivity and response bias is illustrated. Modern derivatives of classical psychophysical techniques which estimates sensory and nonsensory components are described. Finally, data indicating a correspondence between sensory and nonsensory factors obtained with various psychological techniques are reviewed.

Current status of mechanical ventilation decision support systems: a review

Objectives of computerized decision support systems for mechanical ventilation are discussed. Questions considered are: Why is computerized decision support for mechanical ventilation important? What parameter(s) should be optimized? What are the differences between a single attribute and a multiattribute value function used for optimization? How is it possible to achieve optimization in clinical practice with existing ventilators? How does one solve the problem of acquiring measurement of data needed for closed loop control? The possibilities and limitations of three existing decision support systems are discussed. 1) Computerized protocols from LDS Hospital in Salt Lake City, Utah, USA. 2) Optimization Program (OPTPROG) developed jointly at the Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland and Medical Intensive Care Unit, Department of Medicine at Karolinska Institute, South Hospital, Stockholm, Department of Medical Informatics Linkoping University, Sweden. 3) Ventilator Therapy Planner (VENT-PLAN) from the Section on Medical Informatics at Stanford University, Palo Alto, California, USA. Strategies leading to an optimal computerized decision support system are proposed. These strategies include development of better measurement methods for blood gases and cardiac output, improvement of man-machine and machine-machine interaction and the selection of optimization criteria. Finally, research directed towards building quantitative, dynamic patient models based on computerized databases of mechanically ventilated patients are discussed.

Methodological issues in assessment of the perceptual component of body image disturbance

An individual's body image consists of both a perceptual and an attitudinal (subjective) component. Methodological issues relative to the measurement of the perceptual component of body image are discussed. Traditionally, research in body image has employed psychophysical techniques and analyses which confound these two components. Psychophysical techniques which allow for a separate measurement of these two components are discussed, including method of constant stimuli, signal detection theory and adaptive probit estimation. The results of research utilizing these techniques are described and the importance of separately measuring perceptual and attitudinal components is discussed.

Accuracy and reliability of disposable pressure transducers coupled with modern pressure monitors

OBJECTIVE

To determine the bedside accuracy of direct patient pressure monitoring when used with new and clinically used disposable blood pressure (BP) transducers.

DESIGN

Prospective study.

SETTING

Laboratory bench and critical care units in an adult and children's hospital.

SUBJECTS

Seventy-five bedside patient monitors (25 Marquette Electronics, 25 Spacelab Medical, and 25 Hewlett-Packard), and 100 disposable transducers (50 from Utah Medical Products and 50 from Abbott Critical Care Systems [25 new, 25 clinically used of each manufacturer]) were tested.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A +/- 2% accuracy requirement for bedside monitors and the +/- 3% American National Standards Institute accuracy standard for disposable BP transducers were used. To test the accuracy of the bedside monitors, a certified transducer simulator was used to apply 100 mm Hg to each bedside monitor. To test the accuracy of the disposable BP transducers, a very accurate (+/- 0.05%) pneumatic dead weight tester was used to apply pressures to the transducer. A digital power supply and a 6 1/2 digit voltmeter were used. The average output of the bedside monitors when 100 mm Hg was applied was 99.90 +/- 0.83 mm Hg, with the worst cases being 98 and 103 mm Hg. For all 100 disposable pressure transducers, the average output was 100.03 +/- 0.55 mm Hg, with the worst cases being 98.53 and 101.36 when 100 mm Hg was applied. There was no important difference in the accuracy of the transducers obtained from the two vendors nor whether the transducers had been used clinically.

CONCLUSIONS

All disposable BP transducers tested were much more accurate than the American National Standards Institute standard for accuracy. Even the worst case transducers were twice as accurate as required by the American National Standards Institute standard. Only one bedside monitor was outside the +/- 2% accuracy range (103 mm Hg). Based on these findings, this author recommends that fixed calibration disposable transducers and fixed calibration bedside pressure monitoring systems be used. The clinical risks of air embolism and infection from the calibrating mercury manometer and the complexity of the calibration task are the overriding factors for making these recommendations.

Equivalence of fast flush and square wave testing of blood pressure monitoring systems

BACKGROUND

The accurate recording of intraarterial pressure depends upon an appropriate dynamic response of the monitoring system. Generation of a square wave (SW) at the catheter tip is the engineering and in vitro laboratory gold standard. Fast flush (FF) testing is the clinical test of choice. Results from these two test methods have been assumed equal but have not been empirically confirmed.

METHODS

We studied three different 5.1 cm catheter sizes (16 G, 18 G, 20 G Becton Dickinson, Sandy, UT) attached to three different lengths of arterial pressure tubing (36 in, 91.4 cm; 72 in, 182.9 cm; 108 in, 274.3 cm). An arterial recording system was assembled in the standard fashion by attaching a catheter to arterial pressure tubing, which was attached to a transducer (TXX-R, Ohmeda, formerly Viggo-Spectramed, Oxnard, CA) whose signal was recorded by a strip chart recorder (Gould 2400, Rolling Meadows, IL). The system was attached to a pressurized saline flush. The catheter tip was inserted into one port of a pressure generator. With the other port of the pressure generator open to atmosphere, FF tests were performed by activating the flush device of the transducer. Subsequent step response signals from the FF tests were then recorded from which natural frequency (fn) and damping coefficient (zeta) were calculated. Next, square waves were generated by closing the port that was open to atmosphere and attaching a signal generator to a pressure generator. Square waves so generated were recorded as described above and natural frequency and damping coefficients calculated. These procedures were repeated after 0.05 cc of air was introduced in the transducer and repeated again in a system containing a damping device (R.O.S.E., Resonant OverShoot Eliminator, Viggo-Spectramed, Oxnard, CA).

RESULTS

There was no significant difference between fn and zeta as calculated from the step response generated from the FF test versus fn and zeta as calculated from the square wave (SW) test in systems without air. However, in systems containing air, fn by FF testing was always less than fn by SW testing for all catheter sizes and extension tubing lengths (p < 0.05). Damping was also always greater by FF testing than by SW testing in systems with air for all catheter sizes and extension tubing lengths (p < 0.05). The R.O.S.E device created marked qualitative differences, although exact fn and zeta could not be quantified.

CONCLUSIONS

For the characterization of dynamic response of invasive blood pressure monitoring systems, the FF test and SW test yield identical results. However, under certain conditions-air, R.O.S.E device-dynamic response as measured by FF testing was not equivalent to dynamic response as measured by the gold standard-the SW test. Specifically, small amounts of air in fluid-filled invasive blood pressure monitoring systems cause a slightly worse dynamic response as measured by FF testing versus the laboratory gold standard-the SW test.

The role of sensory and nonsensory factors in body size estimations of eating disorder subjects

Body size distortion of anorectic and bulimic subjects was compared to controls via a video-distortion technique. Subjects judged the whole body, chest, hips and stomach regions. A adaptive probit estimation (APE) methodology examined separately the sensory and nonsensory components of body image distortion. Eating disorder subjects overestimated body size more than control subjects. There were no significant differences between eating disorder groups, although there was more variability in eating disorder subjects. Subjects overestimated more on whole body as compared to body regions. There were no differences in sensory sensitivity to detecting size differences between groups. Results indicate that differences in body size distortion between eating disorder and control subjects are due exclusively to affective, nonsensory factors.

Comparison of three psychophysical techniques for estimating body-size perception

Perception of body size was recorded for 63 university students (M age = 25.3 yr., 41 women) who estimated their own body size using three methods. Using the method of adjustment, subjects over- or underestimated their body size. A signal-detection analysis indicated that subjects were sensitive to detecting a 4% distortion in body size and that there was no systematic bias for reporting distortion as present or absent. Scores on the adaptive probit estimation task were significantly correlated with values for point of subjective equality and the size judgements with the method of adjustment. Over-all, this experiment demonstrated adaptive probit estimation as a reliable indicator of perceived body size, sensitivity in detecting size distortion, and response bias in making body-size judgements.

Computers in critical care

This article reviews the current state-of-the-art and future applications of computers in critical care, with particular attention to ventilator and drug-delivery applications. Automated charting, alerts and alarms, and tools for decision support (such as expert systems and closed-loop control) are discussed also.

Integrating computerized anesthesia charting into a hospital information system

BACKGROUND

Systems for computerization of anesthesia records have typically been 'stand-alone' computers many times connected to monitoring devices in the operating theater. A system was developed and tested at LDS Hospital in Salt Lake City, Utah, USA that was an integral part of the Health Evaluation through Logical Processing (HELP) hospital information system.

METHODS

The system was evaluated using time and motion studies to assess impact of the system on the anesthesiologists use of time, an assessment for completeness of the anesthesia record was conducted, and a questionnaire was used to assess anesthesiologists attitudes. Timing studies were performed on 44 surgical cases before computerization and 41 surgical cases after computerization. For both before and after computerization, about 80% of procedures were D&C, vaginal hysterectomy, laparoscopy, tubal ligation, or A&P repair.

RESULTS

The study showed a major reduction in time required for charting from 20.4% to 13.4% which was statistically significant (p = 0.0001). Other significant factors were a reduction in the time spent scanning the entire area which dropped from 10.5% to 5.6% (p = 0.001), patient preparation time increased from 10.1% to 13.1% (p = 0.02), the time spent arranging equipment increased from 6.4% to 8.1%, and the average time spent on non-anesthesia activities increased from 6.3% to 11.3%. The computerized anesthesia record was more legible, and complete than the manual record. The overall assessment of computer charting by anesthesiologists questionnaire was positive. The computerized anesthesia charting was preferred by the anesthesiologists, who, after one or two training sessions, used the system on their own.

CONCLUSIONS

It appears that having a computerized anesthesia charting system that is an integral part of a hospital information system not only saves anesthesiologists charting time, but also improves the quality of the record and was well accepted by busy private practice anesthesiologists.

Factors impacting the success of computerized preadmission screening

Many approaches to controlling costs under managed care rely on the ability to prospectively identify the type or level of service a patient requires at the time of presentation. Although computers may effectively predict these factors, the impact of such a computer system is greatly dependent on its integration into the admission process. Three factors that influence the effectiveness of predictive screening using a computer were identified. They are detection, intervention and compliance. The effect of these factors was then measured in a prospective randomized trial evaluating the effectiveness of computerized preadmission screening for predicting the appropriateness of inpatient care. This paper examines the three factors and their impact on the effectiveness of the system. A mathematical model that relates the factors to the overall effectiveness of computerized preadmission screening is proposed and considered in a more general context.

Nurses, pagers, and patient-specific criteria: three keys to improved critical value reporting

At LDS Hospital, we have developed and evaluated a computerized critical value reporting system based on digital pagers. Criteria used to identify critical values are patient-specific. An evaluation of the system was conducted from October 23, 1993 to January 21, 1994. Results showed that 100% of all critical values (497 values in the form of 335 alerts) were reported to clinicians within an average of 38.6 minutes, and that 51% of all alerts were received within 12 minutes. Data also showed that 92% of the alerts were considered valid, that 76% were communicated directly to the primary care nurse, and that 67% of the time nurses were previously unaware of the critical value(s).

Decision support in medicine: examples from the HELP system

Computerized health information systems can contribute to the care received by patients in a number of ways. Not the least of these is through interactions with health care providers to modify diagnostic and therapeutic decisions. Since its beginning, developers have used the HELP hospital information system to explore computerized interventions into the medical decision making process. By their nature these interventions imply a computer-directed interaction with the physicians, nurses, and therapists involved in delivering care. In this paper we describe four different approaches to this intervention. These include: (1) processes that respond to the appearance of certain types of clinical data by issuing an alert informing caregivers of these data's presence and import, (2) programs that critique new orders and propose changes in those orders when appropriate, (3) programs that suggest new orders and procedures in response to patient data suggesting their need, and (4) applications that function by summarizing patient care data and that attempt to retrospectively assess the average or typical quality of medical decisions and therapeutic interventions made by health care providers. These approaches are illustrated with experience from the HELP system.

Challenges and opportunities for computerizing the anesthesia record

Most observers would agree that the goal of computerizing the anesthesia record is a worthy one. Despite the fact that several academic groups and vendors have attempted to develop and provide computerized anesthesia charting, the practice is not widespread. In this review article, we attempt to outline the reasons for this reluctance to use computers for anesthesia charting. Where there are problems to be solved, there also are opportunities. We discuss the development of strategies to solve these problems and thus present opportunities for medical informatics professionals and anesthesiologists to work toward joint solutions. Solving these problems includes the development of consensus standards and working out technical, social, and educational difficulties. Details of the approaches recommended are outlined.

Evaluation of user acceptance of a clinical expert system

OBJECTIVE

To measure the attitudes of physicians and nurses who use the Health Evaluation through Logical Processing (HELP) clinical information system.

DESIGN

Questionnaire survey of 360 attending physicians and 960 staff nurses practicing at the LDS Hospital. The physicians' responses were signed, permitting follow-up for nonresponse and use of demographic data from staff files. The nurses' responses were anonymous and their demographic data were obtained from the questionnaires.

MEASUREMENTS

Fixed-choice questions with a Likert-type scale, supplemented by free-text comments. Question categories included: computer experience; general attitudes about impact of the system on practice; ranking of available functions; and desired future capabilities.

RESULTS

The response rate was 68% for the physicians and 39% for the nurses. Age, specialty, and general computer experience did not correlate with attitudes. Access to patient data and clinical alerts were rated highly. Respondents did not feel that expert computer systems would lead to external monitoring, or that these systems might compromise patient privacy. The physicians and nurses did not feel that computerized decision support decreased their decision-making power.

CONCLUSION

The responses to the questionnaire and "free-text comments" provided encouragement for future development and deployment of medical expert systems at LDS Hospital and sister hospitals. Although there has been some fear on the part of medical expert system developers that physicians would not adapt to or appreciate recommendations given by these systems, the results presented here are promising and may be of help to other system developers and evaluators.

Representative charting of vital signs in an intensive care unit

An automatic vital signs charting system had been operational in the intensive care units of our hospital for over 10 years, but the system was susceptible to non-representative transients in the data. A median selection rule was implemented to make the system less susceptible to transients. After implementation of the median rule, we examined (1) the agreement of the resulting medians and the values that would have been reported using the previous "real-time" system and (2) the frequency of occurrence of "out-of-range" values for each system. The median value system was found to improve the representativeness of the recorded data. Improved representativeness will enhance the usefulness of reports, but more importantly will enable us to use the resulting data as inputs to computerized practice protocols and other computerized decision support applications.

Computerized detection of nosocomial infections in newborns

Hospital-acquired infections are responsible for an increase in patient mortality and costs. Their detection is essential to permit better infection control. We developed an expert system specifically to detect infections in pediatric patients. The expert system is implemented at LDS Hospital that has a level three newborn intensive care unit and well baby units. We describe how the knowledge base of the expert system was developed, implemented, and validated in a retrospective study. The results of the system were compared to manual reviewer results. The expert system had a sensitivity of 84.5% and specificity of 92.8% in detecting hospital-acquired infections when compared to a physician reviewer. The Cohen's kappa between the expert system and the physician reviewer was 0.62 (p < .001).

Computerized decision support for concurrent utilization review using the HELP system

OBJECTIVE

Development and evaluation of computerized concurrent utilization review (UR) support taking advantage of a clinically rich computerized patient database.

DESIGN

The Automated Support System for Utilization Review (ASSURE) applies the Appropriateness Evaluation Protocol (AEP) Day of Care criteria to computerized patient data in the HELP hospital information system. This paper reports the development, verification, and validation of ASSURE.

MEASUREMENTS

Implementation correctness was verified by measuring agreement with a nurse reviewer, using separate sample sets for all 20 criteria for a total of 560 current inpatients. Usefulness in detecting inappropriate days of care was validated by two nurse reviewers who were crossed with manual and computer-assisted review methods in a blocked design for 168 current inpatients. Agreement with reviewers, sensitivity, specificity, positive predictive value, and negative predictive value were measured.

RESULTS

Agreement was very good for satisfaction of criteria, and good for appropriateness of day of care. A patient day identified by ASSURE as potentially inappropriate would be twice as likely to be judged inappropriate by a reviewer as a randomly selected patient day. Review of the 10% of patient days identified as potentially inappropriate by ASSURE would identify approximately 21% of the inappropriate days of care.

CONCLUSION

ASSURE is a clinically useful tool for screening adult acute care patients for inappropriate days of care, and promises to make a major contribution to reducing health care costs. The prognosis for successful routine clinical use is good.