Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.

Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions

Clinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention-the starting point for delivery of "All the right care, but only the right care," an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.

A closed-loop controller for mechanical ventilation of patients with ARDS

Mechanical ventilators are routinely used to care for patients who cannot adequately breath on their own. Management of mechanical ventilation often involves a careful watch of the patient's arterial blood-oxygen tension and requires frequent adjustment of ventilation parameters to optimize the therapy. This situation lends itself as a candidate for closed-loop control. This report describes a closed-loop control system based on well-established protocols to systematically maintain appropriate levels of positive end-expiratory pressure (PEEP) and inspired oxygen (FiO2) in patients with Adult Respiratory Distress Syndrome (ARDS). The closed-loop control system consists of an in-dwelling arterial oxygenation (PaO2) sensor (Pfizer Continucath), coupled to a Macintosh computer that continuously controls FiO2 and PEEP settings on a Hamilton Amadeus ventilator. The implemented protocols provide continuous closed-loop control of oxygenation and a balance between patient need and minimal therapy. The controller is based on a traditional proportional-integral-derivative (PID) approach. The idea is to control, or maintain, the patient's PaO2 level at a target value determined, or set, by the patient's physician. The controller also features non-linear and adaptive characteristics that allow the system to respond more aggressively to "threatening" levels of PaO2. Another benefit of the control system is the ability to display, monitor, record and store all system parameters, settings, and control variables for future analysis and study. The system was extensively tested in the laboratory and in animal trials prior to use on human subjects. The results of a small clinical trial indicated that the system maintained control of the patient's therapy nearly 84% of the time. During the remainder of this time, the controller was interrupted primarily for suctioning, PaO2 sensor calibration or replacement. The response of the closed-loop controller was found to be appropriate, reliable and safe in patients with ARDS.

Computerized decision support for mechanical ventilation of trauma induced ARDS: results of a randomized clinical trial

BACKGROUND

Variability and logistic complexity of mechanical ventilatory support of acute respiratory distress syndrome, and need to standardize care among all clinicians and patients, led University of Utah/LDS Hospital physicians, nurses, and engineers to develop a comprehensive computerized protocol. This bedside decision support system was the basis of a multicenter clinical trial (1993-1998) that showed ability to export a computerized protocol to other sites and improved efficacy with computer- versus physician-directed ventilatory support. The Memorial Hermann Hospital Shock Trauma intensive care unit (ICU) (Houston, TX; a Level I trauma center and teaching affiliate of The University of Texas Houston Medical School) served as one of the 10 trial sites and recruited two thirds of the trauma patients. Results from the trauma patient subgroup at this site are reported to answer three questions: Can a computerized protocol be successfully exported to a trauma ICU? Was ventilator management different between study groups? Was patient outcome affected?

METHODS

Sixty-seven trauma patients were randomized at the Memorial Hermann Shock Trauma ICU site. "Protocol" assigned patients had ventilatory support directed by the bedside respiratory therapist using the computerized protocol. "Nonprotocol" patients were managed by physician orders.

RESULTS

Of the 67 trauma patients randomized, 33 were protocol (age 40 +/- 3; Injury Severity Score [ISS] 26 +/- 3; 73% blunt) and 34 were nonprotocol (age 38 +/- 2; ISS 25 +/- 2; 76% blunt). For the protocol group, the computerized protocol was used 96% of the time of ventilatory support and 95% of computer-generated instructions were followed by the bedside respiratory therapist. Outcome measures (i.e., survival, ICU length of stay, morbidity, and barotrauma) were not significantly different between groups. Fio2 > or = 0.6 and Pplateau > or = 35 cm H2O exposures were less for the protocol group.

CONCLUSION

A computerized protocol for bedside decision support was successfully exported to a trauma center, and effectively standardized mechanical ventilatory support of trauma-induced acute respiratory distress syndrome without adverse effect on patient outcome.

Clinical informatics case study. Computerized protocols for ventilator management in ARDS patients. Case study

The implementation of the computerized protocol for mechanical ventilation management should be considered successful. Of the 11 sites, only 4 encountered major difficulties. One site could be considered an implementation failure. At this site the protocol software, which was loaded onto the existing computerized patient documentation system, did not initially function smoothly and it severely affected the trust at the clinical site. At the other three sites system usage was minimal due to time requirements of the study rather than a failure to accept the decision support system. Implementation methods suggested by authors such as Whitten and Bentley were found to be successful. Methods of particular use included obtaining buy-in of key personnel, contacting and working with IS personnel early in the project, providing adequate training and reference materials for clinical and support personnel, and providing extra training for some users, thereby creating a "super-user" role. Finally, factors for success of a clinical trial to evaluate a decision support system are slightly different from those for successful use of the system. Time necessary for research functions such as patient screening and recruitment must be considered at the outset and planned for accordingly.

Clinical informatics: 2000 and beyond

Healthcare has begun to flounder in the mounting flood of data available from automated monitoring equipment, microprocessor controlled life-support equipment, such as ventilators, ever more sophisticated laboratory tests, and the myriad of minor technological wonders that every hospital and clinic seem to collect. It is no longer enough to merely display the data in a large spreadsheet or on a complex, colorful time-sequence graph. The next generation of healthcare information systems must help the clinician to assimilate the myriad of data and to make fast and effective decisions. The following is a list of features that the next generation of computer systems will have to include if they are to have a significant impact on the quality of patient care: data acquisition, data storage, information display, data processing, and decision support. By automating or streamlining repetitive or complex tasks, correlating and presenting complex and potentially confusing data, and tracking patient outcomes, the computer can augment clinicians' skills to improve patient care.

Effectiveness of an information broker service

The many disparate databases existing within the same health care organization create confusion and frustration for the consumer trying to get integrated information. The purpose of this research was to create a regional service that would provide a customer oriented information broker service with a single point of contact and guaranteed performance. From 1/98-6/99 there were 34 requests made. 23 were completed on time, eight still in progress and three were late (86.46% on time, average late time 0.76 days). 13 clinical departments used the service. Data was integrated from twelve different data sources. The requests produced about 2 Gigabytes of integrated data (416,666 single spaced pages). The resources required were approximately 1.3 FTE ($65K in direct costs). The cost/page of integrated information was 19 cents. The benefit to cost ratio was at least 3 and most likely higher. Surveys of customers indicated high satisfaction with services and would both utilize the service again and recommend it to others.

Efficacy of computerized decision support for mechanical ventilation: results of a prospective multi-center randomized trial

200 adult respiratory distress syndrome patients were included in a prospective multicenter randomized trial to determine the efficacy of computerized decision support. The study was done in 10 medical centers across the United States. There was no significant difference in survival between the two treatment groups (mean 2 = 0.49 p = 0.49) or in ICU length of stay between the two treatment groups when controlling for survival (F(1df) = 0.88, p = 0.37.) There was a significant reduction in morbidity as measured by multi-organ dysfunction score in the protocol group (F(1df) = 4.1, p = 0.04) as well as significantly lower incidence and severity of overdistension lung injury (F(1df) = 45.2, p < 0.001). We rejected the null hypothesis. Efficacy was best for the protocol group. Protocols were used for 32,055 hours (15 staff person years, 3.7 patient years or 1335 patient days). Protocols were active 96% of the time. 38,546 instructions were generated. 94% were followed. This study indicates that care using a computerized decision support system for ventilator management can be effectively transferred to many different clinical settings and significantly improve patient morbidity.

Evaluation of compliance with a computerized protocol: weaning from mechanical ventilator support using pressure support

STUDY OBJECTIVES

To use a computerized consultation system to evaluate the feasibility of a mechanical ventilator weaning protocol which used the rapid shallow breathing index to guide adjustments in pressure support. A program to monitor user compliance and reasons for noncompliance was built into the computerized consultation system.

METHODS

A total of nine critically ill patients (ten weaning episodes) were enrolled in the protocol. The respiratory therapists performed routine computer charting in the electronic database. They accepted or declined the explicit instructions generated by the computerized protocol and displayed on the bedside terminal. The consultation program monitored whether accepted instructions were implemented by the user.

RESULTS

Patient's therapy was controlled by protocol for a total of 1075 h (mean 108 h, range 4 to 339 h) and 94.8% (1321/1394) of instructions were followed by the clinical staff. Of the 42 instructions clinical staff refused to follow, 23 (55%) were extubation instructions. There were 52 (3.7%) incorrect instructions generated with 24 software errors, 21 errors in underlying logic, and seven user misunderstanding errors.

CONCLUSIONS

A high level of user compliance with this protocol was achieved. The methods described herein to monitor compliance and reasons for noncompliance within a protocol are reusable in the domain of mechanical ventilation and possibly in other domains.

Automated key process monitors for patient care documentation

Complete, accurate and timely patient care documentation is an essential part of the practice of medicine. As with any other process in medicine or industry, continuous quality improvement (CQI) is essential to assure the highest quality at the lowest cost. CQI requires objective key process measures that can be assessed routinely. A set of key process monitors designed to assess completeness, accuracy and timeliness were created based on local, regional and national standards. Feasibility was assessed in the LDS Hospital Emergency Department using 31,429 patient visits in the 18 months from June 1995 to November 1996. The logic of the score was programmed into SQL scripts and run against an Oracle database containing the patient care documentation. The results indicate that the chosen key process monitors can be used to provide real time assessment of the patient care documentation process. The general concepts of the key process measures of completeness, accuracy and timeliness are generalizable to many areas of medicine. The overall score provides one method of easily tracking departmental performance while the overall process monitoring database allows powerful, in-depth analysis of individual components of the process. It is recommended that such automated process monitoring tools be integrated into future clinical information systems.

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.

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.

Testing and validation of computerized decision support systems

Systematic, through testing of decision support systems (DSSs) prior to release to general users is a critical aspect of high quality software design. Omission of this step may lead to the dangerous, and potentially fatal, condition of relying on a system with outputs of uncertain quality. Thorough testing requires a great deal of effort and is a difficult job because tools necessary to facilitate testing are not well developed. Testing is a job ill-suited to humans because it requires tireless attention to a large number of details. For these reasons, the majority of DSSs available are probably not well tested prior to release. We have successfully implemented a software design and testing plan which has helped us meet our goal of continuously improving the quality of our DSS software prior to release. While requiring large amounts of effort, we feel that the process of documenting and standardizing our testing methods are important steps toward meeting recognized national and international quality standards. Our testing methodology includes both functional and structural testing and requires input from all levels of development. Our system does not focus solely on meeting design requirements but also addresses the robustness of the system and the completeness of testing.

Standardization of clinical decision making for the conduct of credible clinical research in complicated medical environments

The likelihood that past experience will produce correct guides to current practice depends on the signal-to-noise ratio for the clinical problem of interest. If the signal-to-noise ratio is high, the decision will be sound and patient benefit likely to occur. If the signal-to-noise ratio is low, as is commonly the case with difficult clinical decisions, then personal experience and the best intentions will not assure sound clinical decisions. When the probability of benefit cannot be quantified, clinicians in complex settings are in danger of being misled by data and experience. Quantifiable probabilities established by group experiment or observation will be necessary for clinical decisions that can be expected to confer benefit on the patient. Explicit methods are necessary for interventions that can be replicated in experiments or in practice. Computerized protocols force the articulation of explicit clinical care methods and standardize clinical decision making. We have developed explicit, rule-based protocols, implemented them in our hospital, exported them to other hospitals, and successfully achieved a rigorous experimental environment in the clinical ICU. Exportation of such explicit methods may narrow the gap between efficacy (university hospital) and effectiveness (community hospital) research results.

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.

A successful protocol for the use of pulse oximetry to classify arterial oxygenation into four fuzzy categories

Pulse oximetry is widely used in critical care medicine to noninvasively estimate arterial hemoglobin oxygen saturation. Despite the obvious benefits of using pulse oximetry to detect life threatening desaturations, it is unknown how well pulse oximetry is able to predict the finer graduations of arterial oxygenation needed for clinical decision making. A computerized protocol was developed for the use of pulse oximetry to classify arterial oxygenation into four fuzzy categories and tested in a prospective clinical trial which compared the oxygenation category assigned by the protocol to one assigned by a respiratory therapist. In 3,742 classifications from 15 patients over a seven month period, the protocol showed 96% agreement with the therapists in the direction of therapy and 75% agreement with the oxygenation classes assigned by the therapists.

Verification & validation algorithms for data used in critical care decision support systems

A decision support system is only as good as the data generating that decision support system. If the data is incorrect, doesn't relate to the other pieces of data, is missing or is not consistent, the decision support system conclusions may be incorrect and inconsistent. While collecting data from several sites during a multicenter randomized clinical trial, we found that some critical data elements were missing, out of correct ranges, totally illogical, and/or inconsistently recorded. In order to get consistent, correct, and dependable information from a our decision support system, the data elements used in that system had to be checked for completeness, valid values, consistent units of measurement, and relationships to other items. Development of data quality assurance rules and the application of those rules is imperative to using the data to generate daily scores for multiple organ failure, sepsis, and barotrauma.

Medical informatics academia and industry: a symbiotic relationship that may assure survival of both through health care reform

There are often clear lines drawn identifying the demilitarized zone between medical informatics academics and industry. Academics were "pure" intellectuals sequestered in ivory towers that effectively shielded them from the realities of the world. Industry has historically focused on creating effective products that produce financial return to the corporation. Both the paradigms of academia and industry are quickly becoming dinosaurs in the era of health care reform where both medical informatics academia and industry are under increasing pressure to develop and prove that medical informatics has a positive impact on health care both in terms of the quality of care as well as cost. Unfortunately, neither academia or industry alone are going to be able to successfully complete this task. The purpose of this paper is to describe such a collaborative effort that has produced a computerized decision support system for the management of mechanical ventilation in patients with the Adult Respiratory Distress Syndrome (ARDS) that is now installed and supported on three different commercial CIS platforms. This collaborative effort has allowed us to successfully mount a large multi-center clinical trial designed to determine efficacy.

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.

Randomized clinical trial of pressure-controlled inverse ratio ventilation and extracorporeal CO2 removal for adult respiratory distress syndrome

The impact of a new therapy that includes pressure-controlled inverse ratio ventilation followed by extracorporeal CO2 removal on the survival of patients with severe ARDS was evaluated in a randomized controlled clinical trial. Computerized protocols generated around-the-clock instructions for management of arterial oxygenation to assure equivalent intensity of care for patients randomized to the new therapy limb and those randomized to the control, mechanical ventilation limb. We randomized 40 patients with severe ARDS who met the ECMO entry criteria. The main outcome measure was survival at 30 days after randomization. Survival was not significantly different in the 19 mechanical ventilation (42%) and 21 new therapy (extracorporeal) (33%) patients (p = 0.8). All deaths occurred within 30 days of randomization. Overall patient survival was 38% (15 of 40) and was about four times that expected from historical data (p = 0.0002). Extracorporeal treatment group survival was not significantly different from other published survival rates after extracorporeal CO2 removal. Mechanical ventilation patient group survival was significantly higher than the 12% derived from published data (p = 0.0001). Protocols controlled care 86% of the time. Average PaO2 was 59 mm Hg in both treatment groups. Intensity of care required to maintain arterial oxygenation was similar in both groups (2.6 and 2.6 PEEP changes/day; 4.3 and 5.0 FIO2 changes/day). We conclude that there was no significant difference in survival between the mechanical ventilation and the extracorporeal CO2 removal groups. We do not recommend extracorporeal support as a therapy for ARDS. Extracorporeal support for ARDS should be restricted to controlled clinical trials.

Ethical implications of standardization of ICU care with computerized protocols

Ethical issues related to the use of computerized protocols to control mechanical ventilation of patients with Acute Respiratory Distress Syndrome (ARDS) are identical to the ethical issues surrounding the use of any therapy or intervention. Four ethical principles must be considered: nonmaleficence, beneficence, autonomy, and distributed justice. The major ethical challenges to computerized protocol use as a specific application of clinical decision support tools are found within the principles of nonmaleficence and of beneficence. The absence of credible outcome data on which ARDS patient survival probabilities with different therapeutic options could be based is a constraint common to most ICU clinical decision making. Clinicians are thus deprived of the knowledge necessary to define benefit and are limited to beneficent intention in clinical decisions. Computerized protocol controlled decision making for the clinical management of mechanical ventilation for ARDS patients is ethically defensible. It is as well supported as most ICU therapy options.

A model-based simulator for testing rule-based decision support systems for mechanical ventilation of ARDS patients

A model-based simulator was developed for testing rule-based decision support systems that manages ventilator therapy of patients with the Adult Respiratory Distress Syndrome (ARDS). The simulator is based on a multi-compartment model of the human body and mathematical models of the gas exchange abnormalities associated with ARDS. Initial testing of this system indicates that model-based simulators are a viable tool for testing rule-based expert systems used in health-care.

Clinical performance of a rule-based decision support system for mechanical ventilation of ARDS patients

We developed a clinical decision support system--ventilation protocols--that managed tidal volume and ventilator rate settings during mechanical ventilation of patients with the Adult Respiratory Distress Syndrome (ARDS). We applied these protocols for a total of 10,903 hours in 40 ARDS patients. The clinical staff suspended the protocols for only 5% of the total application time due to medical procedures, surgeries, transient clinical problems not addressed by the protocols, or because of attending physician request. Of 3,148 instructions generated by the ventilation protocols, the clinical staff followed 2,932 (93%). The staff did not follow some instructions because of patient data errors, computer software and protocol logic errors, inability of the clinical staff to implement protocol instructions because of more pressing duties, and clinical staff objections to specific instructions. Sixty percent of the patients treated by the ventilation protocols survived. Our results demonstrate that the ventilation protocols provided a practical and safe decision support system for the mechanical ventilation of ARDS patients.

Digital electronic communication between ICU ventilators and computers and printers

Although many modern ICU ventilators offer the option of electronic communication, most of these systems are not used because there is a huge communication gap between the ventilator and the computer it might be connected to. When such systems are now used, a large part of what is communicated is artifactual and misleading. We need to overcome both legal and knowledge barriers in the effort to provide seamless communication between ventilators and computers. With regard to the specific issues raised in this paper, here are our answers. Issue #1: Is it essential to have a digital electronic communication port on an ICU ventilator?

ANSWER

No, it is not essential. The purpose of the mechanical ventilator is to support pulmonary ventilation by supplying gas and pressure. There is no vital role for digital communication in the gas-delivery function of the ventilator; however, in the future it will be essential to have effective electronic communication in order to guarantee accurate and timely charting. Issue #2: What impact does electronic communication between a ventilator and a computer have on patient outcome?

ANSWER

Our preliminary data show that electronic communication can reduce the number of charting errors and can improve the timeliness of data entry. However, there is little evidence, other than anecdotal, that this has any impact on patient outcome. Automated charting has been shown to reduce the time spent on charting. This time-savings could be used to increase time spent in direct patient care, but there is no conclusive evidence that this occurs. In fact, one report on computerized charting systems indicates that the result is less time spent in direct patient care. Issue #3: If electronic communication is to be effective in the future, how should these interfaces be configured for mechanical ventilation?

ANSWER

We recommend an optimal algorithm for automated respiratory care charting that has been suggested. Sampling frequency: Sample data from the ventilator every 10 seconds. Ventilator-setting changes: Report every new setting if change lasts more than 3 minutes. Measured respiratory care data: Filter raw MIB-collected data with a 3-minute moving-median filter. Report one filtered value every hour for each variable. In addition, use a threshold table (Table 3) to define significant events. Report changes that remain above threshold more than 3 minutes. Report all measured respiratory-care data 1 minute following any ventilator-mode changes.

A successful computerized protocol for clinical management of pressure control inverse ratio ventilation in ARDS patients

We have developed a computerized protocol that provides a systematic approach for management of pressure control-inverse ratio ventilation (PCIRV). The protocols were used for 1,466 h in ten around-the-clock PCIRV evaluations on seven patients with severe adult respiratory distress syndrome (ARDS). Patient therapy was controlled by protocol 95 percent of the time (1,396 of 1,466 h) and 90 percent of the protocol instructions (1,937 of 2,158) were followed by the clinical staff. Of the 221 protocol instructions, 88 (39 percent) not followed were due to invalid PEEPi measurements. Compared with preceding values during CPPV, the expired minute ventilation was reduced by 27 percent during PCIRV while maintaining a pH that was not clinically different (mean difference in pH = 0.02). There was no difference in the PaO2, PEEPi, or the FIO2 between PCIRV and CPPV. The PEEP setting was reduced by 33 percent from 9 +/- 0.05 to 6 +/- 0.6 and the I:E ratio increased from 0.64 +/- 0.04 to 2.3 +/- 0.10. Peak airway pressure was reduced by 24 percent (from 59 +/- 1.5 to 45 +/- 0.6) and mean airway pressure increased by 27 percent (from 22 +/- 0.8 to 28 +/- 0.6) in PCIRV. Right atrial and pulmonary artery pressures were higher and cardiac output lower in PCIRV but blood pressure was unchanged. The success of this protocol has demonstrated the feasibility of using PEEPi as a primary control variable for oxygenation. This computerized PCIRV protocol should make the future use of PCIRV less mystifying, simpler, and more systematic.

Computers in the ICU: panacea or plague?

The introduction of the intensive care unit (ICU) in the 1960s with its demands for management of large volumes of patient data drove the initial introduction of computers into the ICU. Since the mid-1960s computer systems for the ICU have evolved into the highly sophisticated bedside workstations commercially available today. Despite all of the technologic advances in computers, their application in ICUs in the United States continues to spread very slowly. One of the largest problems is justifying the cost of systems primarily designed to automate data charting and generation of care plans. Although the existing commercial systems do an excellent job, few conclusive studies prove that these systems have a favorable cost-to-benefit ratio. Research systems have demonstrated that if one extends these systems to incorporate a fully integrated database, decision-support tools, automation of data acquisition, and more sophisticated display and user-interface technology, then these ICU computer systems can have a significant impact on improving the quality and reducing the costs of patient care. For computers to be embraced in the ICU environment, commercial systems of the future must move beyond merely gathering and displaying information. They must help the clinician at the bedside assimilate the vast array of ICU data and help him to make more effective decisions.

A strategy for development of computerized critical care decision support systems

It is not enough to merely manage medical information. It is difficult to justify the cost of hospital information systems (HIS) or intensive care unit (ICU) patient data management systems (PDMS) on this basis alone. The real benefit of an integrated HIS or PDMS is in decision support. Although there are a variety of HIS and ICU PDMS systems available there are few that provide ICU decision support. The HELP system at the LDS Hospital is an example of a HIS which provides decision support on many different levels. In the ICU there are decision support tools for antibiotic therapy, nutritional management, and management of mechanical ventilation. Computer protocols for the management of mechanical ventilation (respiratory evaluation, ventilation, oxygenation, weaning and extubation) in patients with adult respiratory distress syndrome ((ARDS) have already been developed and clinically validated at the LDS Hospital. These protocols utilize the bedside intensive care unit (ICU) computer terminal to prompt the clinical care team with therapeutic and diagnostic suggestions. The protocols (in paper flow diagram and computerized form) have been used for over 40,000 hours in more than 125 adult respiratory distress syndrome (ARDS) patients. The protocols controlled care for 94% of the time. The remainder of the time patient care was not protocol controlled was a result of the patient being in states not covered by current protocol logic (e.g. hemodynamic instability, or transport for X-Ray studies). 52 of these ARDS patients met extra corporal membrane oxygenation (ECMO) criteria. The survival of the ECMO criteria ARDS patients was 41%, four times that expected (9%) from historical data (p less than 0.0002).(ABSTRACT TRUNCATED AT 250 WORDS)

Real time data acquisition: recommendations for the Medical Information Bus (MIB)

Care of the acutely ill patient requires rapid acquisition, recording and communications of data. In the modern hospital it is not unusual for a patient to be connected to several monitoring and recording devices simultaneously. Each of these devices is typically made by a different manufacturer who may specialize in one sort of measurement, for example, pulse oximetry. Most of the modern monitoring and recording devices are micro-processor based and have communication capabilities. Unfortunately, there is no operable standard communication technology available from all devices. In addition different clinical staff (physicians, nurses, or respiratory therapists) may be responsible for collecting data. As a result there is a need to develop methods, standards, and strategies for timely and automatic collection of data from these monitoring and recording devices. We report on more than 5 years of clinical experience of automated ICU data collection using a prototype of the Medical Information Bus (MIB).

Performance of computerized protocols for the management of arterial oxygenation in an intensive care unit

Computerized protocols were created to direct the management of arterial oxygenation in critically ill ICU patients and have now been applied routinely, 24 hours a day, in the care of 80 such patients. The protocols used routine clinical information to generate specific instructions for therapy. We evaluated 21,347 instructions by measuring how many were correct and how often they were followed by the clinical staff. Instructions were followed 63.9% of the time in the first 8 patients and 92.3% in the subsequent 72 patients. Instruction accuracy improved after the initial 8 patients, increasing from 71.5% of total instructions to 92.8%. Instruction inaccuracy was primarily caused by software errors and inaccurate and untimely entry of clinical data into the computer. Software errors decreased from 7.2% in the first 8 patients to 0.8% in subsequent patients, while data entry problems decreased from 7.5% to 4.2%. We also assessed compliance with the protocols in a subset of 12 patients (2637 instructions) as a function of 1) the mode of ventilatory support, 2) whether the instruction was to increase or decrease the intensity of therapy or to wait for an interval of time and 3) whether the instruction was 'correct' or 'incorrect'. The mode of ventilatory support did not affect compliance with protocol instructions. Instructions to wait were more likely to be followed than instructions to change therapy. Ninety-seven percent of the correct instructions were followed and 27% of the incorrect instructions were followed.(ABSTRACT TRUNCATED AT 250 WORDS)

Knowledge engineering using retrospective review of data: a useful technique or merely data dredging?

The process of extracting the knowledge or rules for medical decision making is not an easy task. One approach to knowledge engineering is to carefully review how decisions were made in the past with the goal of extracting the rules. The purpose of this project was to use previously collected data from ICU patients to derive the rules for the definition of hemodynamic stability. 97 ICU patients between 9/9/86 and 7/29/90 were included in the analysis. All of these patients had adult respiratory distress syndrome. Their mechanical ventilation was managed by a set of computerized protocols. We retrospectively searched the HELP system database for instructions that were not followed due to hemodynamic reasons. For each patient, we also chose one randomly selected therapy instruction which was followed to act as a control. For each instruction we then selected the corresponding hemodynamic data set. The data was then used in a stepwise logistic regression to determine the rules used for defining hemodynamic instability. We found that several of the hemodynamic parameters we had anticipated to be important were not even measured most of the time. The blood pressures and heart rate were almost identical between the hemodynamicly stable and unstable data sets. We conclude that the decision making process used by physicians has great variation, both between and within physicians. This makes knowledge engineering using retrospective techniques such as this prone to error and probably not very fruitful.

Simultaneous comparison of intraarterial, oscillometric, and finapres monitoring during anesthesia

In 30 patients (15 with normal peripheral vascular status and 15 with peripheral vascular disease, hypertension, or a heavy smoking history), systolic, mean, and diastolic arterial pressures were recorded simultaneously every 5 min using a radial arterial catheter, an oscillometric arm cuff, and a Finapres finger cuff during 1-6 h of anesthesia and operation. The average accuracy of oscillometric and Finapres pressure measurements was good. Comparisons of arterial, oscillometric, and Finapres pressures showed only a small bias in the oscillometric and Finapres pressure estimations. Finapres pressures underestimated arterial pressures by 1 mm Hg more than oscillometric pressures did. Peripheral vascular status had no effect on comparisons made between pressures measured with these two techniques. Although bias was small, precision was often lacking as shown by the large variability of the difference between individual values from the three monitors. However, the precision of Finapres pressure measurements was about the same order of magnitude as that of oscillometric measurements.

Respiratory effects of clonidine alone and combined with morphine, in humans

Because only limited and controversial data exist concerning the respiratory effects of clonidine in humans, the authors evaluated the respiratory effects of clonidine alone and in combination with morphine, in 12 healthy adult males. Subjects received clonidine (0.3-0.4 mg orally), morphine (0.21 mg/kg intramuscularly), or the same doses of the two drugs combined, at three separate sessions in a randomized fashion. The study was balanced for all possible sequences of drug administration. Blood pressure, heart rate, hemoglobin oxygen saturation via finger pulse oximetry, and ventilatory and occlusion pressure responses to CO2 were obtained before and 20, 40, 60, 90, 120, 180, 240, 300, and 360 min after administration of drug or drug combination. Systolic blood pressure decreased significantly only in the clonidine and clonidine plus morphine groups (P less than 0.05). Hemoglobin oxygen saturation decreased by a statistically significant (P less than 0.05), though clinically minor, degree only in the morphine or morphine plus clonidine groups. Clonidine alone did not depress the slope of either the ventilatory or the occlusion pressure response to CO2. In addition, clonidine did not significantly worsen morphine-induced depression of the slope of the ventilatory and occlusion pressure responses in the drug combination group. Both the ventilatory and occlusion pressure responses to CO2 were shifted to the right in all three drug groups (P less than 0.05) but were shifted to a significantly lesser degree by clonidine alone than by morphine and morphine plus clonidine. In healthy young adult males, clonidine alone produces little respiratory depression and does not significantly potentiate morphine-induced respiratory depression.

Real time data acquisition: experience with the Medical Information Bus (MIB)

Care of the acutely ill patient requires rapid acquisition, recording and communications of data. In the modern hospital it is not unusual for a patient to be connected to several monitoring and recording devices simultaneously. Each of these devices is typically made by a different manufacturer who may specialize in one sort of measurement, for example, pulse oximetry. Most of the modern monitoring and recording devices are micro-processor based and have communications capabilities. Unfortunately, there is no operable standard communications technology available from all devices. In addition different clinical staff (physicians, nurses, or respiratory therapists) may be responsible for collecting data. As a result there is a need to develop methods, standards, and strategies for timely and automatic collection of data from these monitoring and recording devices. We report on more than 5 years of clinical experience of automated ICU data collection using a prototype of the Medical Information Bus (MIB).

Differences in magnitude and duration of opioid-induced respiratory depression and analgesia with fentanyl and sufentanil

The magnitude and duration of analgesia and respiratory depression induced by fentanyl (1.0, 2.0, and 4.0 micrograms/kg) and sufentanil (0.1, 0.2, and 0.4 microgram/kg) after intravenous administration over 30 s were measured in 30 healthy young adult male volunteers divided into three groups and studied in a double-blind, randomized fashion. Each volunteer received one dose of fentanyl or sufentanil and no sooner than 48 h later, the corresponding equipotent dose of the other opioid. End-tidal CO2 and ventilatory and occlusion pressure responses to CO2 rebreathing were used to measure drug-induced respiratory effects. Analgesic effects were assessed by changes in the pain threshold to electric shock applied to the forearm. Plasma levels of fentanyl and sufentanil were measured by radioimmunoassay. Testing and sampling intervals were 5, 30, 60, 90, 120, 240, 300, and 360 min after drug administration. The magnitude and duration of depression of the ventilatory and occlusion pressure response were significantly less with sufentanil compared with fentanyl, irrespective of dose. Ventilatory and occlusion pressure responses returned to control values by 30 and 30 min, respectively, after sufentanil and by 240 and 120 min, respectively, after fentanyl. Statistically significant elevations of the pain threshold were, however, greater and longer lasting after sufentanil compared with fentanyl. Pain threshold returned to control values 180 min after sufentanil but only 90 min after fentanyl. These results suggest that sufentanil may provide better patient comfort with less respiratory depression than does fentanyl.

Automated sulfur hexafluoride washout functional residual capacity measurement system for any mode of mechanical ventilation as well as spontaneous respiration

A new sulfur hexafluoride (SF6) washout functional residual capacity (FRC) measurement system has been developed which will work with any mode of mechanical ventilation, as well as with spontaneous respiration. This system was evaluated in three different human studies. In the first two studies, the accuracy of the system was compared with He dilution and body plethysmography in 12 spontaneously breathing normal volunteers and in 12 spontaneously breathing chronic obstructive pulmonary disease (COPD) patients. In the third study, the reproducibility and efficacy of using the system in the ICU was tested in 12 adult respiratory distress syndrome (ARDS) patients who were mechanically ventilated with PEEP. In the normal volunteers, there was no significant difference between the three measurement techniques. In the COPD group, there was an overall significant difference between measurement techniques (F[2,28] = 17.18, p less than .0001) and the rank of the magnitude of the FRC measurements from lowest to highest was SF6 washout, He dilution, and body plethysmography. There was a significant difference in accuracy between the COPD and normal volunteer groups (F[2,28] = 12.24, p less than .0002). There were a total of 1,227 FRC measurements made on the 12 ARDS patients. The number of FRC measurements per patient was 102 +/- 13 (SEM). The "stable" periods were 14 +/- 2 h long and ranged from 60 min to 63.5 h. The reproducibility for all 12 patients was 188 +/- 17 ml or 11.7 +/- 0.7%. This automated SF6 washout system should make routine FRC measurements in patients who are being mechanically ventilated simple and easy to do.(ABSTRACT TRUNCATED AT 250 WORDS)

Computerized artifact detection for ventilatory inductance plethysmographic apnea monitors

Ventilatory inductive plethysmography allows noninvasive monitoring of patient ventilation. Patient movements unrelated to breathing introduce severe errors in ventilator inductive plethysmographic measurements and restrict its usefulness. The purpose of this research was to develop and test a microprocessor-based real-time digital signal processor that uses an adaptive filter to detect patient movements unrelated to breathing. The adaptive filter processor was tested for retrospective identification of artifacts in 20 male volunteers who performed the following specific movements between epochs of quiet, supine breathing: raising arms and legs (slowly, quickly, once, and several times), sitting up, breathing deeply and rapidly, and rolling from a supine to a lateral decubitus position. Flow was simultaneously measured directly with a pneumotachography attached to a mouthpiece. A multilinear regression was used to continuously calculate the calibration constants that relate the pneumotachographic and ventilatory inductive plethysmographic signals. Ventilatory inductive plethysmographic data were then processed, and results scored. There were a total of 166 movements. The calibration coefficients changed dramatically in 146 (88%) of the 166 movements. These movements would have significant errors on ventilatory inductive plethysmographic flow calculation. The changes lasted for the duration of the movements and returned to baseline within two to three breaths. The changes in the coefficients were five or more times larger than the variability around baseline during quiet, supine breathing. All of the total body movements and changes in breathing patterns were detected accurately. The filter detected 46 of 53 upper body movements, 34 of 36 lower body movements, 38 of 38 total body movements, and 19 of 19 breathing pattern changes where the calibration changed.(ABSTRACT TRUNCATED AT 250 WORDS)

Functional residual capacity as a noninvasive indicator of optimal positive end-expiratory pressure

We hypothesized that functional residual capacity (FRC) could be used as a noninvasive indicator of "optimal" positive end-expiratory pressure (PEEP), the level of PEEP that results in venous admixture below 15% with an inspired oxygen fraction less than 0.5. We compared several variables for PEEP optimization--oxygen transport, total respiratory system compliance, FRC-based compliance, mixed venous oxygen saturation, end-tidal to arterial carbon dioxide tension difference, and arterial oxygen saturation--by producing four different PEEP levels, 0, 5, 10 and 15 cm H2O, in 24 mongrel dogs in which pulmonary injury was produced. The data were regressed versus PEEP by using analysis of variance for regression. Venous admixture (F1,23 = 149.3; P less than 0.0001), end-tidal to arterial carbon dioxide tension difference (F1,23 = 64.9; P less than 0.0001), and oxygen transport (F1,23 = 95.1; P less than 0.0001) decreased linearly with PEEP. FRC (F1,23 = 248.1; P less than 0.0001) and arterial oxygen saturation (F1,23 = 66.9; P less than 0.0001) increased linearly with PEEP. Total respiratory system compliance (F1,23 = 66.6; P less than 0.0001) and mixed venous oxygen saturation (F1,23 = 12.2; P less than 0.002) had a quadratic relationship with respect to PEEP with a peak at 5 cm H2O. FRC-based compliance did not have a significant relationship to PEEP. The maximum values of total respiratory system compliance, FRC-based compliance, mixed venous oxygen saturation, and oxygen transport did not occur at PEEP levels that corresponded to a venous admixture below 15% ("optimal" PEEP).(ABSTRACT TRUNCATED AT 250 WORDS)

Computer-controlled positive end-expiratory pressure titration for effective oxygenation without frequent blood gases

We have previously designed a computerized system to automatically deliver PEEP to maintain functional residual capacity (FRC) at a desired value. The purpose of this study was to compare the computerized PEEP titration system with a standard clinical PEEP titration algorithm in the animal adult respiratory distress syndrome (ARDS) model. Thirty mongrel dogs were anesthetized, paralyzed, intubated, and ventilated. An acute pulmonary injury was produced using 0.09 ml/kg of oleic acid. The animals were then given PEEP for 5 h. Arterial and venous blood gases, BP, thermodilution cardiac output, heart rate, body temperature, total respiratory system compliance (Ctr), and end-tidal CO2 were measured every 30 min. FRC was measured using an automated sulfur hexafluoride washout system every 15 min. The animals were allocated randomly to three ten-animal groups. The first group had PEEP titrated using a standard clinical protocol; the remaining two groups had PEEP updated at 15-min intervals under computer control to maintain FRC at 1.4 times the postanesthetized, postparalyzed, preinjury value. The second group received fixed 3-cm H2O PEEP steps. The third group had variable size PEEP steps depending on the output of a proportional, integral, and derivative (PID) controller. PaCO2 was maintained at 35.8 +/- 3.4 (SD) torr. There was a significant difference in PEEP delivered between the three groups (p = .0006) and in FRC (p = .005). There was no significant difference in PaO2 (p = .80) or venous admixture (Qva/Qt) (p = .84) between the three groups.(ABSTRACT TRUNCATED AT 250 WORDS)

Automated measurement of functional residual capacity by sulfur hexafluoride washout

We have constructed a computerized, totally automated system for measuring functional residual capacity (FRC) during mechanical ventilation, at any positive end-expiratory pressure (PEEP) and fraction of inspired oxygen. This system uses washout of a small amount (0.5 to 1.0%) of an insoluble, nontoxic tracer gas, sulfur hexafluoride, to measure FRC. It requires no modification of the ventilator and only minimal changes in the breathing circuit; it can be programmed to make measurements routinely without manual intervention. The system was evaluated with three tests. The prototype sulfur hexafluoride analyzer characteristic curve was determined, and the analyzer was evaluated to determine carbon dioxide interference. A comparison with nitrogen washout FRC measurements was made in an extensive bench test with a Plexiglas lung model. The bench test was designed to determine the effects of changing gas composition and minute volume. A study was done in six healthy dogs to determine reproducibility of the FRC measurements at four PEEP levels (0, 5, 10, and 15 cm H2O: two repetitions in each animal). The sulfur hexafluoride analyzer was well characterized by an exponential equation with a multiple r2 = 0.996. The analyzer was not affected by the presence of carbon dioxide (paired t test, t19 = 1.23, P greater than 0.10). The bench test indicated that FRC (measured) = 0.969 X FRC (true) - 5.3 ml. (Multiple r2 = 0.979.) This was significantly better than the nitrogen washout system, whose regression equation was also a function of minute volume.(ABSTRACT TRUNCATED AT 250 WORDS)

Microcomputer data acquisition and control

In medicine and biology there are many tasks that involve routine well defined procedures. These tasks are ideal candidates for computerized data acquisition and control. As the performance of microcomputers rapidly increases and cost continues to go down the temptation to automate the laboratory becomes great. To the novice computer user the choices of hardware and software are overwhelming and sadly most of the computer sales persons are not at all familiar with real-time applications. If you want to bill your patients you have hundreds of packaged systems to choose from; however, if you want to do real-time data acquisition the choices are very limited and confusing. The purpose of this chapter is to provide the novice computer user with the basics needed to set up a real-time data acquisition system with the common microcomputers. This chapter will cover the following issues necessary to establish a real time data acquisition and control system: Analysis of the research problem: Definition of the problem; Description of data and sampling requirements; Cost/benefit analysis. Choice of Microcomputer hardware and software: Choice of microprocessor and bus structure; Choice of operating system; Choice of layered software. Digital Data Acquisition: Parallel Data Transmission; Serial Data Transmission; Hardware and software available. Analog Data Acquisition: Description of amplitude and frequency characteristics of the input signals; Sampling theorem; Specification of the analog to digital converter; Hardware and software available; Interface to the microcomputer. Microcomputer Control: Analog output; Digital output; Closed-Loop Control. Microcomputer data acquisition and control in the 21st Century--What is in the future? High speed digital medical equipment networks; Medical decision making and artificial intelligence.

Computer-controlled optimization of positive end-expiratory pressure

Positive end-expiratory pressure (PEEP) is a standard treatment for patients with refractory hypoxemia due to an acute restrictive pathology. The therapeutic range of PEEP can be quite narrow. PEEP therapy has been optimized using invasive variables such as oxygen transport and pulmonary shunt, and noninvasive variables such as compliance; however, the measurements are complex. We constructed a computerized PEEP-optimization system consisting of a Siemens 900C ventilator, Siemens prototype sulfur hexafluoride analyzer, Siemens 940 lung mechanics analyzer, and a DEC 11/23 microcomputer. The user may choose from three different noninvasive PEEP titration algorithms: maximizing static total respiratory system compliance (CTR), maximizing functional residual capacity(FRC)-based compliance (CFRC), and normalizing FRC. The device was tested in six dogs with pulmonary injury induced by oleic acid. The system was constrained to 3-cm H2O PEEP steps at 20-min intervals. The algorithm normalizing FRC reached optimal PEEP levels in 40 min, with a mean difference from the desired FRC of 15 +/- 48 (SEM) ml. This corresponds to a mean percent error of 1.0% +/- 2.63%. The CFRC and CTR algorithms reached optimal PEEP levels in 60 and 40 min, respectively, and maintained a maximal compliance for 85% of the time. This system provides fully automated noninvasive PEEP titration and is flexible enough to incorporate easily any other PEEP titration algorithms. It should improve patient care by guaranteeing that PEEP therapy is truly optimized throughout the patient's recovery.

Lateral positioning with differential lung ventilation and unilateral PEEP following unilateral acid aspiration in the dog

Body position can significantly alter the efficiency of gas exchange following unilateral lung injury. We systematically examined three positions during differential lung ventilation with unilateral positive end-expiratory pressure (PEEP) following unilateral hydrochloric acid aspiration in the dog. Twelve mongrel dogs were intubated with a double-lumen endobronchial tube and mechanically ventilated with a microcomputer-controlled pair of ventilators. A tidal volume of 7.5 ml/kg was delivered to each lung. The PaCO2 was maintained at 4.67 kPa. A unilateral injury was induced with an injection of 0.1 N hydrochloric acid (2.5 ml/kg) into one lumen of the endobronchial tube. 0.984 kPa PEEP was applied to the injured lung and the dogs were placed sequentially in one of three positions (supine, lateral decubitus with injured lung non-dependent, and lateral decubitus with injured lung dependent) for 1 h apiece. There was no significant difference between the three positions with regard to PaO2 (F (2, 10) = 1.60, P = 0.25) of venous admixture (F (2, 10) = 0.49, P = 0.63). Our data indicated that position did not alter oxygenation. This was probably due to the use of differential ventilation with unilateral PEEP which eliminated redistribution of ventilation between the two lungs and minimized position-dependent changes in pulmonary blood flow.