Donald B. Chalfin

Clinical practice guidelines for the sustained use of sedatives and analgesics in the critically ill adult

Judith Jacobi, PharmD, FCCM, BCPS; Gilles L. Fraser, PharmD, FCCM; Douglas B. Coursin, MD; Richard R. Riker, MD; Dorrie Fontaine, RN, DNSc, FAAN; Eric T. Wittbrodt, PharmD; Donald B. Chalfin, MD, MS, FCCM; Michael F. Masica, MD, MPH; H. Scott Bjerke, MD; William M. Coplin, MD; David W. Crippen, MD, FCCM; Barry D. Fuchs, MD; Ruth M. Kelleher, RN; Paul E. Marik, MDBCh, FCCM; Stanley A. Nasraway, Jr, MD, FCCM; Michael J. Murray, MD, PhD, FCCM; William T. Peruzzi, MD, FCCM; Philip D. Lumb, MB, BS, FCCM. Developed through the Task Force of the American College of Critical Care Medicine (ACCM) of the Society of Critical Care Medicine (SCCM), in collaboration with the American Society of Health-System Pharmacists (ASHP), and in alliance with the American College of Chest Physicians; and approved by the Board of Regents of ACCM and the Council of SCCM and the ASHP Board of Directors

Impact of delayed transfer of critically ill patients from the emergency department to the intensive care unit.

Objective:Numerous factors can cause delays in transfer to an intensive care unit for critically ill emergency department patients. The impact of delays is unknown. We aimed to determine the association between emergency department “boarding” (holding admitted patients in the emergency department pending intensive care unit transfer) and outcomes for critically ill patients. Design:This was a cross-sectional analytical study using the Project IMPACT database (a multicenter U.S. database of intensive care unit patients). Patients admitted from the emergency department to the intensive care unit (2000–2003) were included and divided into two groups: emergency department boarding ≥6 hrs (delayed) vs. emergency department boarding <6 hrs (nondelayed). Demographics, intensive care unit procedures, length of stay, and mortality were analyzed. Groups were compared using chi-square, Mann-Whitney, and unpaired Student’s t-tests. Setting:Emergency department and intensive care unit. Patients:Patients admitted from the emergency department to the intensive care unit (2000–2003). Interventions:None. Measurements and Main Results:Main outcomes were intensive care unit and hospital survival and intensive care unit and hospital length of stay. During the study period, 50,322 patients were admitted. Both groups (delayed, n = 1,036; nondelayed, n = 49,286) were similar in age, gender, and do-not-resuscitate status, along with Acute Physiology and Chronic Health Evaluation II score in the subgroup for which it was recorded. Among hospital survivors, the median hospital length of stay was 7.0 (delayed) vs. 6.0 days (nondelayed) (p < .001). Intensive care unit mortality was 10.7% (delayed) vs. 8.4% (nondelayed) (p < .01). In-hospital mortality was 17.4% (delayed) vs. 12.9% (nondelayed) (p < .001). In the stepwise logistic model, delayed admission, advancing age, higher Acute Physiology and Chronic Health Evaluation II score, male gender, and diagnostic categories of trauma, intracerebral hemorrhage, and neurologic disease were associated with lower hospital survival (odds ratio for delayed admission, 0.709; 95% confidence interval, 0.561–0.895). Conclusions:Critically ill emergency department patients with a ≥6-hr delay in intensive care unit transfer had increased hospital length of stay and higher intensive care unit and hospital mortality. This suggests the need to identify factors associated with delayed transfer as well as specific determinants of adverse outcomes.

Practice parameters for hemodynamic support of sepsis in adult patients: 2004 update

Objective:To provide the American College of Critical Care Medicine with updated guidelines for hemodynamic support of adult patients with sepsis. Data Source:Publications relevant to hemodynamic support of septic patients were obtained from the medical literature, supplemented by the expertise and experience of members of an international task force convened from the membership of the Society of Critical Care Medicine. Study Selection:Both human studies and relevant animal studies were considered. Data Synthesis:The experts articles reviewed the literature and classified the strength of evidence of human studies according to study design and scientific value. Recommendations were drafted and graded levels based on an evidence-based rating system described in the text. The recommendations were debated, and the task force chairman modified the document until <10% of the experts disagreed with the recommendations. Conclusions:An organized approach to the hemodynamic support of sepsis was formulated. The fundamental principle is that clinicians using hemodynamic therapies should define specific goals and end points, titrate therapies to those end points, and evaluate the results of their interventions on an ongoing basis by monitoring a combination of variables of global and regional perfusion. Using this approach, specific recommendations for fluid resuscitation, vasopressor therapy, and inotropic therapy of septic in adult patients were promulgated.

Association between Critical Care Physician Management and Patient Mortality in the Intensive Care Unit

Context Critical care physicians or physicians without specialized critical care training may manage patients in intensive care units. Contribution This study described 101832 patients in 123 intensive care units in the United States. Patients managed by critical care physicians were sicker, had more procedures, and had higher hospital mortality rates than those managed by other physicians. Analyses that adjusted for severity of illness and the tendency for sicker patients to be managed by critical care specialists still showed higher mortality among patients managed by the specialists. Caution Unrecognized confounders might diminish or invalidate the unexpected finding of higher mortality among patients managed by critical care specialists. The Editors The extent of involvement and supervision by critical care physicians varies somewhat in U.S. intensive care units (ICUs) (16). Some ICUs are organized as strictly closed services, in which critical care physicians, or intensivists, assume control and decision-making ability over all aspects of patient care, whereas in some hybrid ICUs, mandated consultation and management by critical care physicians is the primary administrative model. Most ICUs, however, are structured as completely open units, in which the admitting physicians retain full clinical and decisional responsibility and thus have the option to care for their patients with or without input from critical care physicians. Evidence from several settings suggests improved outcomes when critical care physicians assume substantial responsibility over the care and triage of ICU patients (1, 722). These studies, however, have methodological limitations and limited generalizability. Most are small, use historical controls or beforeafter study designs, and are limited to specific ICUs (for example, medical or surgical) in 1 or 2 centers. They have the usual risks for confounding by illness severity commonly seen in cross-sectional studies (7, 8, 1421) and retrospective analyses of administrative databases that were limited to certain diagnostic categories (12, 13). Recognizing the limitations of previously published studies and considerable variability in critical care management (CCM) in the United States, we examined data from 123 ICUs across the United States to assess the relationship between management by critical care physicians and hospital mortality rates of critically ill patients. These data were derived from a large national project that examined resource use in intensive care (2). At the beginning of our analysis, we hypothesized that CCM would be associated with improved outcomes in critically ill patients. Methods Patients Patients were identified through Project IMPACT (Cerner, Bel Air, Maryland), a national database of ICU patients. The Project IMPACT database is a large administrative database originally developed by the Society of Critical Care Medicine in 1996. Participation is voluntary. All data are collected at each institution by on-site data collectors who are certified in advance by Project IMPACT to assure standardization and uniformity in data definitions and database definitions and entry. The database for 2000 to 2004 included 142392 patients admitted to 123 ICUs in 100 U.S. hospitals. We excluded patients with missing data for variables of interest from our analysis, leaving 111907 patients. We included only the first ICU admission, reducing the number of patients to 106623, and then excluded patients who were managed only part time during their ICU stay, reducing the total observations to 101832. Variables Our primary outcome variable was hospital mortality. Our key exposure or risk factor was the same regardless of whether a patient was managed by a critical care physician during his or her ICU stay. This was ascertained in Project IMPACT by using the survey question, Was the patient managed by a critical care physician/team? Trained data entry personnel for Project IMPACT define CCM as treatment occurring when the physician is asked to take responsibility for the overall management of a patient in the critical care unit without having to first provide expertise about a single organ system. A physician should meet 1 or more of the following criteria to be considered a critical care physician: 1) be recognized by the institution as a critical care specialist within a specialty unit, even without a specialty board certification (such as burn or neurointensivist), and must treat the total patient and not a single organ system; 2) have passed critical care medicine board examinations or be qualified to take the examination; and 3) be trained in an accredited critical care fellowship. When a patient received CCM, it was documented, regardless of whether the treatment was for all or part of the ICU stay. Covariates included patient characteristics, such as demographic characteristics, diagnosis, and clinical condition at ICU admission. We also controlled for ICU and hospital characteristics. Severity of illness was measured by the Simplified Acute Physiology Score (SAPS) II. Through use of recently published work on SAPS (23), we added additional variables to SAPS II and modified coefficients in the logit model to derive a better fit. These included the patients age (<40 years, 40 to 59 years, 60 to 69 years, 70 to 79 years, and >79 years), sex, duration of hospital stay before ICU admission (<24 hours, 1 day, 2 days, 3 to 9 days, >9 days), patients location before ICU (transfer from outside emergency department, rehabilitation or skilled nursing facility, wards, or another hospital), clinical category (medical patient or other), and intoxication (yes or no). For this expanded SAPS II, the HosmerLemeshow goodness-of-fit P value was 0.38. (The Appendix provides more detail on the expanded SAPS II.) Supplement. Appendix Statistical Analysis We divided ICUs into 3 groups based on the percentage of patients receiving CCM for the entire stay: 95% of patients or more, 5% to 95% of patients, and 5% of patients or fewer. We excluded 4793 patients who received CCM for only part of the ICU stay from the analysis, leaving 2 patient management types: CCM for the entire stay and no CCM. For each of the 6 categories defined by the combination of patient management type and ICU group, we computed expected and actual mortality rates. Expected mortality was the mean SAPS II probability of mortality. Actual mortality was the percentage of patients who did not survive the hospital stay. We computed the standardized mortality ratio and its 95% CI, based on an exact Poisson distribution, as the ratio of actual to expected mortality. We developed a score to measure the propensity that a patient would be selected for CCM. We derived our score from a logistic regression model, with CCM as the dependent variable. The model was estimated on patients only from ICUs not mandating CCM. We screened all available patient characteristics known at the time of ICU admission and ICU characteristics for inclusion in the model. A propensity score was then estimated for each patient. Variables used to create the propensity score were age, Glasgow Coma Score, number of licensed hospital beds, insurance (commercial, Medicaid or Medicare, or self-pay), ventilation at ICU admission, tracheostomy at ICU admission, gastrointestinal bleeding, noninvasive ventilation at ICU admission, cerebrovascular event, chronic immunosuppression, chronic respiratory disease, acute renal failure, hospital location (rural, suburban, or urban), continuous sedation, and admission source (emergency department, another hospital, invasive procedures, or other non-ICU location). Figure 1 shows the proportion of patients managed by critical care physicians. Hospital mortality rates tend to increase from the first decile to the last decile of propensity and SAPS II. More details of the score and the sensitivity of results to changes in the propensity score are shown in the Appendix. Figure 1. Critical care management ( CCM ) and mortality. SAPS= Simplified Acute Physiology Score. We performed random-effects logistic regressions on the entire sample, using hospital death as the dependent variable. This method uses the within- and between-ICU variability inherent in the nesting of the patients into 123 ICUs. The crude model included only the risk factor CCM for the entire stay versus no CCM. Severity of illness (as measured by the expanded SAPS II score) and likelihood of selection for CCM (as measured by the propensity score) were then added to the model as control variables, along with all interactions of the control variables and risk factor. Where a statistically significant interaction term indicated that a control variable was an effect modifier, the regression was estimated within each quartile of the control variable. We repeated random-effects logistic regression analysis of mortality on several subsamples. The no-choice subsample included 2 groups of patients: those from ICUs in which 95% or more or 5% or fewer patients received CCM. In addition, the following subsamples were examined: patients not transferred from another hospital, patients with a respiratory diagnosis with ventilator support at ICU admission, patients with respiratory diagnosis without ventilator support at ICU admission, patients with ventilator support at ICU admission, patients with a diagnosis other than respiratory and no ventilator at ICU admission, patients with a circulatory diagnosis, patients with a diagnosis of infection, patients with at least 1 ICU procedure, and patients with no ICU procedures. The Appendix presents additional details of regression analyses. Role of the Funding Source Eli Lilly and the Department of Bioethics at the National Institutes of Health Clinical Center funded the study. The funding services had no role in the design, conduct, and analysis of the study and did not participate in the decision to submit the manuscript for publication.

Prioritizing the organization and management of intensive care services in the United States: The PrOMIS Conference

Objective:Adult critical care services are a large, expensive part of U.S. health care. The current agenda for response to workforce shortages and rising costs has largely been determined by members of the critical care profession without input from other stakeholders. We sought to elicit the perceived problems and solutions to the delivery of critical care services from a broad set of U.S. stakeholders. Design:A consensus process involving purposive sampling of identified stakeholders, preconference Web-based survey, and 2-day conference. Setting:Participants represented healthcare providers, accreditation and quality-oversight groups, federal sponsoring institutions, healthcare vendors, and institutional and individual payers. Subjects:We identified 39 stakeholders for the field of critical care medicine. Thirty-six (92%) completed the preconference survey and 37 (95%) attended the conference. Interventions:None. Measurements and Main Results:Participants expressed moderate to strong agreement with the concerns identified by the critical care professionals and additionally expressed consternation that the critical care delivery system was fragmented, variable, and not patient-centered. Recommended solutions included regionalizing the adult critical care system into “tiers” defined by explicit triage criteria and professional competencies, achieved through voluntary hospital accreditation, supported through an expanded process of competency certification, and monitored through process and outcome surveillance; implementing mechanisms for improved communication across providers and settings and between providers and patients/families; and conducting market research and a public education campaign regarding critical care’s promises and limitations. Conclusions:This consensus conference confirms that agreement on solutions to complex healthcare delivery problems can be achieved and that problem and solution frames expand with broader stakeholder participation. This process can be used as a model by other specialties to address priority setting in an era of shifting demographics and increasing resource constraints.

Rapid Diagnosis of Infection in the Critically Ill, a Multicenter Study of Molecular Detection in Bloodstream Infections, Pneumonia, and Sterile Site Infections*

Objective: Early identification of causative microorganism(s) in patients with severe infection is crucial to optimize antimicrobial use and patient survival. However, current culture-based pathogen identification is slow and unreliable such that broad-spectrum antibiotics are often used to insure coverage of all potential organisms, carrying risks of overtreatment, toxicity, and selection of multidrug-resistant bacteria. We compared the results obtained using a novel, culture-independent polymerase chain reaction/electrospray ionization-mass spectrometry technology with those obtained by standard microbiological testing and evaluated the potential clinical implications of this technique. Design: Observational study. Setting: Nine ICUs in six European countries. Patients: Patients admitted between October 2013 and June 2014 with suspected or proven bloodstream infection, pneumonia, or sterile fluid and tissue infection were considered for inclusion. Interventions: None. Measurements and Main Results: We tested 616 bloodstream infection, 185 pneumonia, and 110 sterile fluid and tissue specimens from 529 patients. From the 616 bloodstream infection samples, polymerase chain reaction/electrospray ionization-mass spectrometry identified a pathogen in 228 cases (37%) and culture in just 68 (11%). Culture was positive and polymerase chain reaction/electrospray ionization-mass spectrometry negative in 13 cases, and both were negative in 384 cases, giving polymerase chain reaction/electrospray ionization-mass spectrometry a sensitivity of 81%, specificity of 69%, and negative predictive value of 97% at 6 hours from sample acquisition. The distribution of organisms was similar with both techniques. Similar observations were made for pneumonia and sterile fluid and tissue specimens. Independent clinical analysis of results suggested that polymerase chain reaction/electrospray ionization-mass spectrometry technology could potentially have resulted in altered treatment in up to 57% of patients. Conclusions: Polymerase chain reaction/electrospray ionization-mass spectrometry provides rapid pathogen identification in critically ill patients. The ability to rule out infection within 6 hours has potential clinical and economic benefits.

Age and utilization of intensive care unit resources of critically ill cancer patients

Older patients, patients with malignancies, and those admitted to ICUs utilize a disproportionate amount of hospital resources. To evaluate the combined impact of age and a diagnosis of malignancy on ICU utilization and outcome, we reviewed the care provided to all 1,212 patients admitted to a medical/surgical ICU in a hospital specializing in the treatment of cancer between January 1, 1986 and December 31, 1987. Patients between 19 and 64 yr (young) were compared with those between 65 and 74 yr (young-old) and with those greater than or equal to 75 yr (old-old) with respect to utilization of nutritional support (total parenteral nutrition [TPN]), mechanical ventilation (MV), pulmonary artery (PA) catheterization, dialysis (D), and blood products (B). Mean length of stay (LOS) in the ICU, primary diagnosis, outcome, and average daily severity of illness scores (ADTIS) were also compared. Old-old patients represented 14% of all ICU patients and young-old patients represented 28%; 64% of old-old and 61% of young-old patients had solid tumors, compared with 36% of younger patients. The ICU mortality of the two older groups was significantly lower than that of the younger patients (17%, 27%, and 30%, respectively). The use of TPN, PA catheters, and D was similar for all three groups, but older patients used less MV and B than the younger patients (p less than .0001, chi2 analysis). The two older groups also had similar LOS and lower average daily Therapeutic Intervention Scoring Systems (TISS) scores than their younger cohort.(ABSTRACT TRUNCATED AT 250 WORDS)

How to use the results of an economic evaluation.

BACKGROUND Given the high costs of delivering care to critically ill patients, practitioners and policymakers are beginning to scrutinize the costs and outcomes associated with intensive care. Health economics is a discipline concerned with determining the best way of using resources to maximize the health of the community. This involves addressing questions such as which procedure, test, therapy, or program should be provided, and to whom, given available resources. PURPOSE The purpose of this article is to review general economic principles that will help intensivists to better interpret published economic evaluations. DATA SOURCES Selected articles from the health economics and critical care literature. RESULTS In this article, we use an economic evaluation that examines sedation strategies in critically ill patients. We discuss how learning to critically appraise an economic evaluation is only part of the task for end users. Determining whether and how to apply the results of economic evaluations to local settings presents bigger challenges and remains largely a matter of judgment. CONCLUSIONS Economic evaluations use analytic techniques to systematically consider all possible costs and consequences of clinical actions. Although they should never form the sole basis for clinical decisions for individual patients, economic evaluations offer potentially useful information at different levels of decision-making.

The critical care crisis in the United States: A report from the profession

Background:The demand for critical care services in the United States is likely to increase as a result of the aging of the population and standards from the Leapfrog Group for intensivist physician staffing. However, the demand for critical care physicians, nurses, and other health professionals will significantly outpace supply because of severe shortages. Participants:This article summarizes recommendations from the Framing Options for Critical Care in the United States (FOCCUS) Task Force, a group comprised of representatives from the Society of Critical Care Medicine, the American Association of Critical-Care Nurses, the College of Chest Physicians, and the American Thoracic Society, to prevent a crisis in American critical care services. Data Sources and Process:Relevant literature was systematically searched by the representatives of each of the professional societies and synthesized with other sources, including official policy statements and guidelines from each of the professional societies, published review articles, expert opinion, nonrandomized historical cohort investigations, and other pertinent studies and sources. Consensus to identify the likely causes of the impending shortfall in critical care personnel, approaches to redesign of critical care practice, and the promotion of critical care excellence was reached via collaboration in direct meetings, telephone conferences, and electronic communications. Four major recommendations were subsequently agreed on to address the projected shortfall in critical care professionals and to improve the quality of critical care delivery. Conclusions:The future demand for critical care services will likely exceed the capacities of the current delivery system. The professional societies and policy makers need to expeditiously intervene and act on these recommendations to ensure that the delivery of critical care services and care to the critically ill does not suffer.

The economic impact and cost-effectiveness of urinary neutrophil gelatinase-associated lipocalin after cardiac surgery.

BACKGROUND Acute kidney injury (AKI) is common after cardiac surgery, and expeditious recognition with specific biomarkers may help improve outcome. OBJECTIVE Because the economic impact of a biomarker-based diagnostic strategy is unknown, we assessed the cost-effectiveness of using urinary neutrophil gelatinase-associated lipocalin (NGAL) for the diagnosis of AKI after cardiac surgery compared with current diagnostic methods. METHODS A decision analysis model was developed using the societal perspective to evaluate the cost-effectiveness of NGAL. Cost per quality-adjusted life-year (QALY) was determined for NGAL and standard strategies. The base case was a 67-year-old male patient undergoing coronary artery bypass graft surgery in the United Kingdom. Multiple sensitivity analyses were performed to determine how cost-effectiveness would vary with changes in the underlying clinical and economic variables. RESULTS The base case yielded expected costs of £4244 and 11.86 QALYs for the NGAL strategy compared with £4672 and 11.79 QALYs for the standard therapy. The cost-effectiveness ratio for the NGAL strategy was £358/QALY compared with £396/QALY for the standard regimen. Cost-effectiveness increased as the treatment effect-defined as the ability to prevent progression of established AKI (kidney injury or failure)-for the therapy triggered by an elevated NGAL level rose. Sensitivity analysis demonstrated that the model was most responsive to the probability of developing AKI and least sensitive to the test cost for NGAL. Probabilistic sensitivity analysis supported the NGAL strategy as the most cost-effective option. Because this study was a decision analysis model incorporating a nonspecific treatment for AKI (as opposed to an observational study or controlled trial), model structural assumptions may therefore have underestimated mortality and the likelihood of developing AKI, although these were tested in multiple sensitivity analyses. Indirect costs were also not explicitly factored. CONCLUSION The use of urinary NGAL after cardiac surgery appears to be cost-effective in the early diagnosis of AKI.