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.

Prospective Assessment of the Feasibility of a Trial of Low-Tidal Volume Ventilation for Patients with Acute Respiratory Failure.

RATIONALE: Low-tidal volume ventilation (LTVV; 6 ml/kg) benefits patients with acute respiratory distress syndrome and may aid those with other causes of respiratory failure. Current early ventilation practices are poorly defined. OBJECTIVES: We observed patients with acute respiratory failure to assess the feasibility of a pragmatic trial of LTVV and to guide experimental design. METHODS: We prospectively enrolled consecutive patients with acute respiratory failure admitted to intensive care units expected to participate in the proposed trial. We collected clinical data as well as information on initial and daily ventilator settings and inpatient mortality. We estimated the benefit of LTVV using predictive linear and nonlinear models. We simulated models to estimate power and feasibility of a cluster-randomized trial of LTVV versus usual care in acute respiratory failure. RESULTS: We included 2,484 newly mechanically ventilated patients (31% with acute respiratory distress syndrome) from 49 hospitals. Hospital mortality was 28%. Mean initial tidal volume was 7.1 ml/kg predicted body weight (95% confidence interval, 7.1-7.2), with 78% of patients receiving tidal volumes less than or equal to 8 ml/kg. Our models estimated a mortality benefit of 0-2% from LTVV compared with usual care. Simulation of a stepped-wedged cluster-randomized trial suggested that enrollment of 106,361 patients would be necessary to achieve greater than 90% power. CONCLUSIONS: Use of initial tidal volumes less than 8 ml/kg predicted body weight was common at hospitals participating in the National Heart, Lung, and Blood Institute Prevention and Early Treatment of Acute Lung Injury (PETAL) Network. After considering the size and budgetary requirement for a cluster-randomized trial of LTVV versus usual care in acute respiratory failure, the PETAL Network deemed the proposed trial infeasible. A rapid observational study and simulations to model anticipated power may help better design trials.

Automated detection of physiologic deterioration in hospitalized patients.

OBJECTIVE: Develop and evaluate an automated case detection and response triggering system to monitor patients every 5 min and identify early signs of physiologic deterioration. MATERIALS AND METHODS: A 2-year prospective, observational study at a large level 1 trauma center. All patients admitted to a 33-bed medical and oncology floor (A) and a 33-bed non-intensive care unit (ICU) surgical trauma floor (B) were monitored. During the intervention year, pager alerts of early physiologic deterioration were automatically sent to charge nurses along with access to a graphical point-of-care web page to facilitate patient evaluation. RESULTS: Nurses reported the positive predictive value of alerts was 91-100% depending on erroneous data presence. Unit A patients were significantly older and had significantly more comorbidities than unit B patients. During the intervention year, unit A patients had a significant increase in length of stay, more transfers to ICU (p = 0.23), and significantly more medical emergency team (MET) calls (p = 0.0008), and significantly fewer died (p = 0.044) compared to the pre-intervention year. No significant differences were found on unit B. CONCLUSIONS: We monitored patients every 5 min and provided automated pages of early physiologic deterioration. This before-after study found a significant increase in MET calls and a significant decrease in mortality only in the unit with older patients with multiple comorbidities, and thus further study is warranted to detect potential confounding. Moreover, nurses reported the graphical alerts provided information needed to quickly evaluate patients, and they felt more confident about their assessment and more comfortable requesting help.

Multicenter implementation of a severe sepsis and septic shock treatment bundle.

RATIONALE: Severe sepsis and septic shock are leading causes of intensive care unit (ICU) admission, morbidity, and mortality. The effect of compliance with sepsis management guidelines on outcomes is unclear. OBJECTIVES: To assess the effect on mortality of compliance with a severe sepsis and septic shock management bundle. METHODS: Observational study of a severe sepsis and septic shock bundle as part of a quality improvement project in 18 ICUs in 11 hospitals in Utah and Idaho. MEASUREMENTS AND MAIN RESULTS: Among 4,329 adult subjects with severe sepsis or septic shock admitted to study ICUs from the emergency department between January 2004 and December 2010, hospital mortality was 12.1%, declining from 21.2% in 2004 to 8.7% in 2010. All-or-none total bundle compliance increased from 4.9-73.4% simultaneously. Mortality declined from 21.7% in 2004 to 9.7% in 2010 among subjects noncompliant with one or more bundle element. Regression models adjusting for age, severity of illness, and comorbidities identified an association between mortality and compliance with each of inotropes and red cell transfusions, glucocorticoids, and lung-protective ventilation. Compliance with early resuscitation elements during the first 3 hours after emergency department admission caused ineligibility, through lower subsequent severity of illness, for these later bundle elements. CONCLUSIONS: Total severe sepsis and septic shock bundle compliances increased substantially and were associated with a marked reduction in hospital mortality after adjustment for age, severity of illness, and comorbidities in a multicenter ICU cohort. Early resuscitation bundle element compliance predicted ineligibility for subsequent bundle elements.

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.

Culture of early mobility in mechanically ventilated patients.

Physical deconditioning and prolonged motor weakness accompanying critical illness have profound and lasting consequences for both patients and their informal caregivers. The etiology is multifactorial and the effects may be mitigated by an early mobility process. Early mobility is facilitated by change in intensive care unit culture that requires clinicians to: 1) reorganize and manage current practices that have the potential to interfere with mobility; 2) create a strategy to improve the level of teamwork; and 3) link effective practice intervention and teamwork with short- and long-term patient-centered outcomes.

Assessing data quality in manual entry of ventilator settings.

OBJECTIVE: To evaluate the data quality of ventilator settings recorded by respiratory therapists using a computer charting application and assess the impact of incorrect data on computerized ventilator management protocols. DESIGN An analysis of 29,054 charting events gathered over 12 months from 678 ventilated patients (1,736 ventilator days) in four intensive care units at a tertiary care hospital. MEASUREMENTS: Ten ventilator settings were examined, including fraction of inspired oxygen (Fio (2)), positive end-expiratory pressure (PEEP), tidal volume, respiratory rate, peak inspiratory flow, and pressure support. Respiratory therapists entered values for each setting approximately every two hours using a computer charting application. Manually entered values were compared with data acquired automatically from ventilators using an implementation of the ISO/IEEE 11073 Medical Information Bus (MIB). Data quality was assessed by measuring the percentage of time that the two sources matched. Charting delay, defined as the interval between data observation and data entry, also was measured. RESULTS: The percentage of time that settings matched ranged from 99.0% (PEEP) to 75.9% (low tidal volume alarm setting). The average charting delay for each charting event was 6.1 minutes, including an average of 1.8 minutes spent entering data in the charting application. In 559 (3.9%) of 14,263 suggestions generated by computerized ventilator management protocols, one or more manually charted setting values did not match the MIB data. CONCLUSION: Even at institutions where manual charting of ventilator settings is performed well, automatic data collection can eliminate delays, improve charting efficiency, and reduce errors caused by incorrect data.

Guidelines for critical care medicine training and continuing medical education.

OBJECTIVE: Critical care medicine trainees and faculty must acquire and maintain the skills necessary to provide state-of-the art clinical care to critically ill patients, to improve patient outcomes, optimize intensive care unit utilization, and continue to advance the theory and practice of critical care medicine. This should be accomplished in an environment dedicated to compassionate and ethical care. PARTICIPANTS: A multidisciplinary panel of professionals with expertise in critical care education and the practice of critical care medicine under the direction of the American College of Critical Care Medicine. SCOPE: Physician education in critical care medicine in the United States should encompass all disciplines that provide care in the intensive care unit and all levels of training: from medical students through all levels of postgraduate training and continuing medical education for all providers of clinical critical care. The scope of this guideline includes physician education in the United States from residency through ongoing practice after subspecialization. DATA SOURCES AND SYNTHESIS: Relevant literature was accessed via a systematic Medline search as well as by requesting references from all panel members. Subsequently, the bibliographies of obtained literature were reviewed for additional references. In addition, a search of organization-based published material was conducted via the Internet. This included but was not limited to material published by the American College of Critical Care Medicine, Accreditation Council for Graduate Medical Education, Accreditation Council for Continuing Medical Education, and other primary and specialty organizations. Collaboratively and iteratively, the task force met, by conference call and in person, to construct the tenets and ultimately the substance of this guideline. CONCLUSIONS: Guidelines for the continuum of education in critical care medicine from residency through specialty training and ongoing throughout practice will facilitate standardization of physician education in critical care medicine.

Computers in the ICU: where we started and where we are now.

The first use of computers in critical care units were described in the mid 1960s. They reported the use of very large mainframe computers that filled entire rooms yet had very limited memory and processing capacities by today's standards. These were limited to only a few institutions until microprocessors were developed increasing computation speed and expanding memory capacity by many magnitudes. This allowed smaller more affordable stand alone systems to be developed and the inclusion of microprocessors into bedside devices. As the capacity expanded uses broadened. Simple results review developed into a more complete electronic medical record. Databases were created allowing population analysis for research and systems quality improvement activities. Decision support started as simple alerting of potential errors and dangers and expanded into more sophisticated clinical decision-making support. With this came problems that needed solutions. As the amount of information became overwhelming to the bedside clinician, methods to filter and display data made it more useful. Security and confidentiality became major concerns. Data input solutions had to be found including interfaces between computers, bedside devices and instruments designed to automate data input like scanners, bar coders, and other devices. The biggest issue of all however, was developing acceptance among clinicians and creating the cultural change required for successful implementation of electronic medical records. This paper will explore these issues.

Monitoring outcomes with relational databases: does it improve quality of care?

There are 3 key ingredients in improving quality of medial care: 1) using a scientific process of improvement, 2) executing the process at the lowest possible level in the organization, and 3) measuring the results of any change reliably. Relational databases when used within these guidelines are of great value in these efforts if they contain reliable information that is pertinent to the project and used in a scientific process of quality improvement by a front line team. Unfortunately, the data are frequently unreliable and/or not pertinent to the local process and is used by persons at very high levels in the organization without a scientific process and without reliable measurement of the outcome. Under these circumstances the effectiveness of relational databases in improving care is marginal at best, frequently wasteful and has the potential to be harmful. This article explores examples of these concepts.

The effect of computer-generated reminders on charting deficiencies in the ICU.

OBJECTIVE: To examine the effect of computer-generated reminders on nurse charting deficiencies in two intensive care units. DESIGN: Nurses caring for a group of 60 study patients received patient-specific paper reminder reports when charting deficiencies were found at mid-day. Nurses caring for a group of 60 control patients received no reminders. A group of 60 retrospective patients was also formed. MEASUREMENTS: The average numbers of charting deficiencies at the end of the shift in each of the three groups were compared using two planned orthogonal contrasts. RESULTS: The average in the study group patients was 1.02 deficiencies per day per patient, whereas the control group the average was 1.40 deficiencies per day per patient (p = 0.001). The average number of end-of-shift deficiencies in the pooled prospective (study/control) population was 1.21 deficiencies per day per patient, compared with the average in the retrospective group of 1.56 deficiencies per day per patient (p < 0.001). CONCLUSION: The decrease was likely due both to the appropriate response of the nurses to the reminders and to a learned attentiveness to the tasks on the part of the nurses who cared for study patients. Greater gains were hindered by incomplete "coupling" of the reminders to the end-of-shift deficiencies and by inaccuracies in the reminders.

Implementation of an electronic logbook for intensive care units.

Logbooks of patients treated in acute care units are commonly maintained; the data may be used to justify resource use, analyze patient outcomes, and encourage clinical research. We report herein the conversion of a paper-based logbook to an electronic logbook in three hospital intensive care units. The major difference between the paper logbook and electronic logbook data was the addition of clinician-entered data to the electronic logbook. Despite extensive computerization of patient information extant in the participating units, there was considerable reluctance to replace the paper-based logbook. The project's success can be attributed to the use of feedback from the clinical users in the development and implementation process to create accessible, high quality data. These data provide clinicians with the capability to monitor trends in a variety of patient groups. Advantages of the electronic logbook include more efficient data access, higher data quality and increased ability to conduct quality improvement and clinical research activities.

Hyperbaric oxygen for acute carbon monoxide poisoning.

BACKGROUND: Patients with acute carbon monoxide poisoning commonly have cognitive sequelae. We conducted a double-blind, randomized trial to evaluate the effect of hyperbaric-oxygen treatment on such cognitive sequelae. METHODS: We randomly assigned patients with symptomatic acute carbon monoxide poisoning in equal proportions to three chamber sessions within a 24-hour period, consisting of either three hyperbaric-oxygen treatments or one normobaric-oxygen treatment plus two sessions of exposure to normobaric room air. Oxygen treatments were administered from a high-flow reservoir through a face mask that prevented rebreathing or by endotracheal tube. Neuropsychological tests were administered immediately after chamber sessions 1 and 3, and 2 weeks, 6 weeks, 6 months, and 12 months after enrollment. The primary outcome was cognitive sequelae six weeks after carbon monoxide poisoning. RESULTS: The trial was stopped after the third of four scheduled interim analyses, at which point there were 76 patients in each group. Cognitive sequelae at six weeks were less frequent in the hyperbaric-oxygen group (19 of 76 [25.0 percent]) than in the normobaric-oxygen group (35 of 76 [46.1 percent], P=0.007), even after adjustment for cerebellar dysfunction and for stratification variables (adjusted odds ratio, 0.45 [95 percent confidence interval, 0.22 to 0.92]; P=0.03). The presence of cerebellar dysfunction before treatment was associated with the occurrence of cognitive sequelae (odds ratio, 5.71 [95 percent confidence interval, 1.69 to 19.31]; P=0.005) and was more frequent in the normobaric-oxygen group (15 percent vs. 4 percent, P=0.03). Cognitive sequelae were less frequent in the hyperbaric-oxygen group at 12 months, according to the intention-to-treat analysis (P=0.04). CONCLUSIONS: Three hyperbaric-oxygen treatments within a 24-hour period appeared to reduce the risk of cognitive sequelae 6 weeks and 12 months after acute carbon monoxide poisoning.

Telemedicine and international disaster Response : Medical consultation to Armenia and Russia vía a telemedicine spacebridge

The telemedicine spacebridge a satellite mediated audio-video-fax link between four US and two armenia and Russia medical centers,permitted remote american consultants to assist Armenian and Russia physicians in the management of medical problems following the December 1988 earthquake in Armenia and the June 1989 gas explosion near Ufa. Methods: during 12 weeks of operations, 247 Armenian and Russian and 175 American medical professionals participated in 34 half-day clinica conferences. 209 patients were discussed. Conclusion: These results suggest that interactive consultation by remote specialists can provide valuable assistance to onsite physicians and favorably influence clinical decisions in the aftermath of major disaster (AU)