C. Jane Wallace

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 protocollogic (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<0.0002). The success of these computer protocols and their acceptance by the clinical staff clearly establishes the feasibility of controlling the therapy of severely ill patients.Over the last four years we have refined the process which we use for generating computerized protocols. The purpose of this paper is to present the six step development strategy which we are successfully using to produce computerized critical care protocols.

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. The major problem in creating the protocols was obtaining clinician agreement on protocol logic and their commitment to utilize it clinically. The major problem in implementing the protocols was obtaining accurate and timely data entry. We conclude that computerized protocols can direct the clinical care of critically ill patients in a manner that is acceptable to clinicians.

Clinical evaluation of computer-based respiratory care algorithms

A collection of computer-based respiratory care algorithms were implemented as a prototype computer-based patient advice system (COMPAS) within the existing HELP hospital information system. Detailed medical logic recommended ventilator adjustments for 5 different modes of ventilation: assist/control (A/C). intermittent mandatory ventilation (IMV), continuous positive airway pressure (CPAP), pressure controlled inverted ratio ventilation (PC-IRV), and extracorporeal carbon dioxide removal (ECCO2R). Suggestions for adjusting the mode of ventilation, fraction of inspired oxygen (FiO2), positive end-expiratory pressure (PEEP), peak inspiratory pressure, and several other therapeutic measures related to the treatment of severe arterial hypoxemia in adult respiratory distress syndrome (ARDS) patients were automatically presented to the clinical staff via bedside computer terminals. COMPAS was clinically evaluated for 624 hours of patient care on the first 5 ARDS patients in a randomized clinical trial. The clinical staff carried out 84% (320/379) of the computerized therapy suggestions. In response to a questionnaire distributed to clinical users of the system, 86% judged the system to be potentially valuable. Through implementation of COMPAS, a computer-based ventilatory therapy advice system, we have laid the groundwork for standardization of ventilator management of arterial hypoxemia in critically ill ARDS patients.

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 Patients 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.

The evolution of eProtocols that enable reproducible clinical research and care methods

Unnecessary variation in clinical care and clinical research reduces our ability to determine what healthcare interventions are effective. Reducing this unnecessary variation could lead to further healthcare quality improvement and more effective clinical research. We have developed and used electronic decision support tools (eProtocols) to reduce unnecessary variation. Our eProtocols have progressed from a locally developed mainframe computer application in one clinical site (LDS Hospital) to web-based applications available in multiple languages and used internationally. We use eProtocol-insulin as an example to illustrate this evolution. We initially developed eProtocol-insulin as a local quality improvement effort to manage stress hyperglycemia in the adult intensive care unit (ICU). We extended eProtocol-insulin use to translate our quality improvement results into usual clinical care at Intermountain Healthcare ICUs. We exported eProtocol-insulin to support research in other US and international institutions, and extended our work to the pediatric ICU. We iteratively refined eProtocol-insulin throughout these transitions, and incorporated new knowledge about managing stress hyperglycemia in the ICU. Based on our experience in the development and clinical use of eProtocols, we outline remaining challenges to eProtocol development, widespread distribution and use, and suggest a process for eProtocol development. Technical and regulatory issues, as well as standardization of protocol development, validation and maintenance, need to be addressed. Resolution of these issues should facilitate general use of eProtocols to improve patient care.

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. We recently went to the bedside of a critically ill patient and counted the current information categories (not repeated measures) that were reviewed for physician decision making. The total was in excess of 236! Dr. Eddy summarized it best: “It is simply unrealistic to think that individuals can synthesize in their head scores of pieces of evidence, accurately estimate the outcomes of different options, and accurately judge the desirability of those outcomes for patients…. All confirm what would be expected from common sense: The complexity of modern medicine exceeds the inherent limitations of the unaided human mind.” Although there are a variety of HIS and ICU PDMS systems available there are few that provide ICU decision support.