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.

A replicable method for blood glucose control in critically Ill patients.

CONTEXT: To ensure interpretability and replicability of clinical experiments, methods must be adequately explicit and should elicit the same decision from different clinicians who comply with the study protocol. OBJECTIVE: The objective of this study was to determine whether clinician compliance with protocol recommendations exceeds 90%. DESIGN: We developed an adequately explicit computerized protocol (eProtocol-insulin) for managing critically ill adult patient blood glucose. We monitored clinician compliance with eProtocol-insulin recommendations in four intensive care units in four hospitals and compared blood glucose distributions with those of a simple clinical guideline at one hospital and a paper-based protocol at another. All protocols and the guideline used intravenous insulin and 80 to 110 mg/dL (4.4-6.1 mmol/L) blood glucose targets. SETTING: The setting for this study was four academic hospital intensive care units. PATIENTS: This study included critically ill adults requiring intravenous insulin. INTERVENTION: Intervention used in this study was a bedside computerized protocol for managing blood glucose. MAIN OUTCOME MEASURE: The main outcome measure was clinician compliance with eProtocol-insulin recommendations. RESULTS: The number of patients was 31 to 458 and the number of blood glucose measurements was 2,226 to 19,925 among the four intensive care units. Clinician compliance with eProtocol-insulin recommendations was 91% to 98%. Blood glucose distributions were similar in the four hospitals (generalized linear model p = .18). Compared with the simple guideline, eProtocol-insulin glucose measurements within target increased from 21% to 39%, and mean blood glucose decreased from 142 to 115 mg/dL (generalized linear model p < .001). Compared with the paper-based protocol, eProtocol-insulin glucose measurements within target increased from 28% to 42%, and mean blood glucose decreased from 134 to 116 mg/dL (generalized linear model p = .001). CONCLUSIONS: The 91% to 98% clinician compliance indicates eProtocol-insulin is an exportable instrument that can establish a replicable experimental method for clinical trials of blood glucose management in critically ill adults. Control of blood glucose was better with eProtocol-insulin than with a simple clinical guideline or a paper-based protocol.

Clinicians' perceptions about use of computerized protocols: a multicenter study.

PURPOSE: Implementation of evidence-based techniques, such as explicit computerized protocols, has achieved limited success among clinicians. In this study, we describe the development and validation of an instrument for assessing clinicians' perceptions about use of explicit computerized protocols. METHODS: Qualitative assessment of semi-structured interviews with clinicians gave rise to a cognitive model evaluating the factors that motivate clinicians to use explicit computerized protocols. Using these constructs we developed a 35-item instrument which was administered to 240 clinicians (132 nurses, 53 physicians and 55 respiratory therapists), in three health-care institutions. RESULTS: Factor analysis identified nine factors that accounted for 66% of the total variance cumulatively. Factors identified were: Beliefs regarding Self-Efficacy, Environmental Support, Role Relevance, Work Importance, Beliefs regarding Control, Attitude towards Information Quality, Social Pressure, Culture, and Behavioral Intention. The strongest predictor was Beliefs regarding Self-Efficacy, which accounted for 26% of the total variance of intention to use explicit computerized protocols. Results supported the reliability and construct validity of the instrument. CONCLUSIONS: Clinicians' perceptions play a critical role in determining their intention to use explicit computerized protocols in routine clinical practice. Behavioral theories will help us understand factors predicting clinicians' intention to use explicit computerized protocols and recognize the implications of these factors in the design and implementation of these protocols.

Evaluation and comparison of IV insulin-treatment protocols using data from critically ill patients in the ICU.

In critically ill patients control of blood sugar levels with IV insulin has been shown to improve clinical outcomes in the intensive care units. We have developed an analytical framework with which to evaluate and compare IV insulin-treatment models and protocols. Performance of the analytical framework is demonstrated using protocols published by others and new protocols under development by our group.

Using a diabetes data mart in individualizing diabetes management.

Constantly changing diabetes care standards makes it challenging to deliver care adapted to the unique condition of the individual patient. The availability of large amounts of data from patient's electronic medical records makes it possible to individualize diabetes management. Initial design of a "patient-specific" hybrid system (physiological-causal probabilistic) of adaptive diabetes models and insulin treatment algorithms will be presented. The system is uniquely derived and tested using a diabetes data mart of about 33,000 patients.

An electronic protocol for translation of research results to clinical practice: a preliminary report.

INTRODUCTION: We evaluated the feasibility of using an electronic protocol developed for research use (Research-eProtocol-insulin) for blood glucose management in usual intensive care unit clinical practice. METHODS: We implemented the rules of Research-eProtocol-insulin in the electronic medical record of the Intermountain Healthcare hospital system (Clinical-eProtocol-insulin) for use in usual clinical practice. We evaluated the performance of Clinical-eProtocol-insulin rules in the intensive care units of seven Intermountain Healthcare hospitals and compared this performance with the performance of Research-eProtocol-insulin at the LDS Hospital Shock/Trauma/Respiratory Intensive Care Unit. RESULTS: Clinician (nurse or physician) compliance with computerized protocol recommendations was 95% (of 21,325 recommendations) with Research-eProtocol-insulin and 92% (of 109,458 recommendations) with Clinical-eProtocol-insulin. The blood glucose distribution in clinical practice (Clinical-eProtocol-insulin) was similar to the research use distribution (Research-eProtocol-insulin); however, the mean values (119 mg/dl vs 113 mg/dl) were statistically different (P = 0.0001). Hypoglycemia rates in the research and practice settings did not differ: the percentage of measurements < or =40 mg/dl (0.11% vs 0.1%, P = 0.65) and the percentage of patients with at least one blood glucose < or =40 mg/dl (4.2% vs 3%, P = 0.23) were not statistically significantly different. CONCLUSION: Our electronic blood glucose protocol enabled translation of a research decision-support tool (Research-eProtocol-insulin) to usual clinical practice (Clinical-eProtocol-insulin).

Cognitive evaluation of the predictors of use of computerized protocols by clinicians.

We describe a cognitive approach to evaluating the factors that motivate clinicians to use computerized protocols. Using Value-Expectancy theories we developed an open-ended interview to assess clinicians' beliefs and experiences about the use of computerized protocols. Using a qualitative methodology, 3 reviewers independently identified key concepts raised by 13 interviewees. These concepts were aggregated and independently sorted into 39 categories. Then final categories were chosen by consensus. Analysis of the concepts showed consistency across clinician specialties of physicians, nurses and respiratory therapists. Inter-rater reliability calculated using Cohen's Kappa was 0.474. Identified constructs from Value-Expectancy and Intrinsic Motivation theories were: Work Importance, Perception of Situation, Role Relevance, Beliefs regarding Control, Beliefs regarding Normative Expectations, Beliefs regarding Self-Efficacy, Attitude, Habit, Environmental Support and Pre-Behavior. This model will form the basis for an instrument to assess the beliefs and expectations of clinical use regarding the use of computerized protocols.