OBJECTIVES:To examine the effect of severity of acute kidney injury or renal recovery on risk-adjusted mortality across different intensive care unit settings. Acute kidney injury in intensive care ...unit patients is associated with significant mortality.
DESIGN:Retrospective observational study.
SETTING:There were 325,395 of 617,927 consecutive admissions to all 191 Veterans Affairs ICUs across the country.
PATIENTS:Large national cohort of patients admitted to Veterans Affairs ICUs and who developed acute kidney injury during their intensive care unit stay.
MEASUREMENTS AND MAIN RESULTS:Outcome measures were hospital mortality, and length of stay. Acute kidney injury was defined as a 0.3-mg/dL increase in creatinine relative to intensive care unit admission and categorized into Stage I (0.3 mg/dL to <2 times increase), Stage II (≥2 and <3 times increase), and Stage III (≥3 times increase or dialysis requirement). Association of mortality and length of stay with acute kidney injury stages and renal recovery was examined. Overall, 22% (n = 71,486) of patients developed acute kidney injury (Stage I17.5%; Stage II2.4%; Stage III2%); 16.3% patients met acute kidney injury criteria within 48 hrs, with an additional 5.7% after 48 hrs of intensive care unit admission. Acute kidney injury frequency varied between 9% and 30% across intensive care unit admission diagnoses. After adjusting for severity of illness in a model that included urea and creatinine on admission, odds of death increased with increasing severity of acute kidney injury. Stage I odds ratio = 2.2 (95% confidence interval, 2.17–2.30); Stage II odds ratio = 6.1 (95% confidence interval, 5.74, 6.44); and Stage III odds ratio = 8.6 (95% confidence interval, 8.07–9.15). Acute kidney injury patients with sustained elevation of creatinine experienced higher mortality risk than those who recovered.
INTERVENTIONS:None.
CONCLUSIONS:Admission diagnosis and severity of illness influence frequency and severity of acute kidney injury. Small elevations in creatinine in the intensive care unit are associated with increased risk-adjusted mortality across all intensive care unit settings, whereas renal recovery was associated with a protective effect. Strategies to prevent even mild acute kidney injury or promote renal recovery may improve survival.
OBJECTIVES:Hyperglycemia during critical illness is common and is associated with increased mortality. Intensive insulin therapy has improved outcomes in some, but not all, intervention trials. It is ...unclear whether the benefits of treatment differ among specific patient populations. The purpose of the study was to determine the association between hyperglycemia and risk– adjusted mortality in critically ill patients and in separate groups stratified by admission diagnosis. A secondary purpose was to determine whether mortality risk from hyperglycemia varies with intensive care unit type, length of stay, or diagnosed diabetes.
DESIGN:Retrospective cohort study.
SETTING:One hundred seventy-three U.S. medical, surgical, and cardiac intensive care units.
PATIENTS:Two hundred fifty-nine thousand and forty admissions from October 2002 to September 2005; unadjusted mortality rate, 11.2%.
INTERVENTIONS:None.
MEASUREMENTS AND MAIN RESULTS:A two–level logistic regression model determined the relationship between glycemia and mortality. Age, diagnosis, comorbidities, and laboratory variables were used to calculate a predicted mortality rate, which was then analyzed with mean glucose to determine the association of hyperglycemia with hospital mortality. Hyperglycemia was associated with increased mortality independent of illness severity. Compared with normoglycemic individuals (70–110 mg/dL), adjusted odds of mortality (odds ratio, 95% confidence interval) for mean glucose 111–145, 146–199, 200–300, and >300 mg/dL was 1.31 (1.26–1.36), 1.82 (1.74–1.90), 2.13 (2.03–2.25), and 2.85 (2.58–3.14), respectively. Furthermore, the adjusted odds of mortality related to hyperglycemia varied with admission diagnosis, demonstrating a clear association in some patients (acute myocardial infarction, arrhythmia, unstable angina, pulmonary embolism) and little or no association in others. Hyperglycemia was associated with increased mortality independent of intensive care unit type, length of stay, and diabetes.
CONCLUSIONS:The association between hyperglycemia and mortality implicates hyperglycemia as a potentially harmful and correctable abnormality in critically ill patients. The finding that hyperglycemia–related risk varied with admission diagnosis suggests differences in the interaction between specific medical conditions and injury from hyperglycemia. The design and interpretation of future trials should consider the primary disease states of patients and the balance of medical conditions in the intensive care unit studied.
In this report, implementation of a MRSA bundle (nasal surveillance for MRSA, contact precautions for patients with MRSA, hand hygiene, and an institutional culture change whereby infection control ...was everyone's responsibility) was associated with a significant decline in MRSA transmission.
Methicillin-resistant
Staphylococcus aureus
(MRSA) infections are a problem in the United States
1
and elsewhere. MRSA is one of the most common causes of ventilator-associated pneumonia, bloodstream infection associated with central venous catheters, and surgical-site infections.
1
,
2
In 2001, the Veterans Affairs (VA) Pittsburgh Healthcare System began working with the Pittsburgh Regional Healthcare Initiative and the Centers for Disease Control and Prevention (CDC) to eliminate health care–associated MRSA infections with the use of a “MRSA bundle.” The bundle, which was based on published guidelines, comprised universal nasal surveillance for MRSA colonization, contact precautions for patients who were carriers of MRSA, hand . . .
In addition to providing new capabilities, the introduction of technology in complex, sociotechnical systems, such as health care and aviation, can have unanticipated side effects on technical, ...social, and organizational dimensions. To identify potential accidents in the making, the authors looked for side effects from a natural experiment, the implementation of bar code medication administration (BCMA), a technology designed to reduce adverse drug events (ADEs).
Cross-sectional observational study of medication passes before (21 hours of observation of 7 nurses at 1 hospital) and after (60 hours of observation of 26 nurses at 3 hospitals) BCMA implementation.
Detailed, handwritten field notes of targeted ethnographic observations of in situ nurse-BCMA interactions were iteratively analyzed using process tracing and five conceptual frameworks.
Ethnographic observations distilled into 67 nurse-BCMA interactions were classified into 12 categories. We identified five negative side effects after BCMA implementation: (1) nurses confused by automated removal of medications by BCMA, (2) degraded coordination between nurses and physicians, (3) nurses dropping activities to reduce workload during busy periods, (4) increased prioritization of monitored activities during goal conflicts, and (5) decreased ability to deviate from routine sequences.
These side effects might create new paths to ADEs. We recommend design revisions, modification of organizational policies, and "best practices" training that could potentially minimize or eliminate these side effects before they contribute to adverse outcomes.
Evidence-based practices in preventive care and chronic disease management are inconsistently implemented. Computerized clinical reminders (CRs) can improve compliance with these practices in ...outpatient settings. However, since clinician adherence to CR recommendations is quite variable and declines over time, we conducted observations to determine barriers and facilitators to the effective use of CRs.
We conducted an observational study of nurses and providers interacting with CRs in outpatient primary care clinics for two days in each of four geographically distributed Veterans Administration (VA) medical centers.
Three observers recorded interactions of 35 nurses and 55 physicians and mid-level practitioners with the CRs, which function as part of an electronic medical record. Field notes were typed, coded in a spreadsheet, and then sorted into logical categories. We then integrated findings across observations into meaningful patterns and abstracted the data into themes, such as recurrent strategies. Several of these themes translated directly to barriers and facilitators to effective CR use.
Optimally using the CR system for its intended purpose was impeded by (1) lack of coordination between nurses and providers; (2) using the reminders while not with the patient, impairing data acquisition and/or implementation of recommended actions; (3) workload; (4) lack of CR flexibility; and (5) poor interface usability. Facilitators included (1) limiting the number of reminders at a site; (2) strategic location of the computer workstations; (3) integration of reminders into workflow; and (4) the ability to document system problems and receive prompt administrator feedback.
We identified barriers that might explain some of the variability in the use of CRs. Although these barriers may be difficult to overcome, some strategies may increase user acceptance and therefore the effectiveness of the CRs. These include explicitly assigning responsibility for each CR to nurses or providers, improving visibility of positive results from CRs in the electronic medical record, creating a feedback mechanism about CR use, and limiting the overall number of CRs.
Nursing shortages and patient safety mandates require nursing managers and administrators to consider new ways of understanding the complexity of healthcare provider work in actual situations. The ...authors report findings from a study guided by an innovative research approach to explore factors affecting registered nurse performance during real work on acute care medical-surgical units. Our findings suggest beginning targets for interventions to improve patient safety, as well as recruitment and retention, through support for registered nurse work.
BackgroundElimination of hospital-acquired infections is an important patient safety goal.SettingAll 174 medical, cardiac, surgical and mixed Veterans Administration (VA) intensive care units ...(ICUs).InterventionA centralised infrastructure (Inpatient Evaluation Center (IPEC)) supported the practice bundle implementation (handwashing, maximal barriers, chlorhexidinegluconate site disinfection, avoidance of femoral catheterisation and timely removal) to reduce central line-associated bloodstream infections (CLABSI). Support included recruiting leadership, benchmarked feedback, learning tools and selective mentoring.Data collectionSites recorded the number of CLABSI, line days and audit results of bundle compliance on a secure website.AnalysisCLABSI rates between years were compared with incidence rate ratios (IRRs) from a Poisson regression and with National Healthcare Safety Network referent rates (standardised infection ratio (SIR)). Pearson's correlation coefficient compared bundle adherence with CLABSI rates. Semi-structured interviews with teams struggling to reduce CLABSI identified common themes.ResultsFrom 2006 to 2009, CLABSI rates fell (3.8–1.8/1000 line days; p<0.01); as did IRR (2007; 0.83 (95% CI 0.73 to 0.94), 2008; 0.65 (95% CI 0.56 to 0.76), 2009; 0.47 (95% CI 0.40 to 0.55)). Bundle adherence and CLABSI rates showed strong correlation (r=0.81). VA CLABSI SIR, January to June 2009, was 0.76 (95% CI 0.69 to 0.90), and for all FY2009 0.88 (95% CI 0.80 to 0.97). Struggling sites lacked a functional team, forcing functions and feedback systems.ConclusionCapitalising on a large healthcare system, VA IPEC used strategies applicable to non-federal healthcare systems and communities. Such tactics included measurement through information technology, leadership, learning tools and mentoring.
BACKGROUND:A valid metric is critical to measure and report intensive care unit (ICU) outcomes and drive innovation in a national system.
OBJECTIVES:To update and validate the Veterans Affairs (VA) ...ICU severity measure (VA ICU).
RESEARCH DESIGN:A validated logistic regression model was applied to two VA hospital data sets36,240 consecutive ICU admissions to a stratified random sample of moderate and large hospitals in 1999–2000 (cohort 1) and 81,964 cases from 42 VA Medical Centers in fiscal years 2002–2004 (cohort 2). The model was updated by adding diagnostic groups and expanding the source of admission variables.
MEASURES:C statistic, Hosmer-Lemeshow goodness-of-fit statistic, and Brierʼs score measured predictive validity. Coefficients from the 1997 model were applied to predictors (fixed) in a logistic regression model. A 10 × 10 table compared cases with both VA ICU and National Surgical Quality Improvement Performance metrics. The standardized mortality ratios divided observed deaths by the sum of predicted mortality.
RESULTS:The fixed model in both cohorts had predictive validity (cohort 1C statistic = 0.874, Hosmer-Lemeshow goodness-of-fit C statistic chi-square = 72.5; cohort 20.876, 307), as did the updated model (cohort 2C statistic = 0.887, Hosmer-Lemeshow goodness-of-fit C statistic chi-square = 39). In 7,411 cases with predictions in both systems, the standardized mortality ratio was similar (1.04 for VA ICU, 1.15 for National Surgical Quality Improvement Performance), and 92% of cases matched (±1 decile) when ordered by deciles of mortality. The VA ICU standardized mortality ratio correlates with the National Surgical Quality Improvement Performance standardized mortality ratio (r = .74). Variation in discharge and laboratory practices may affect performance measurement.
CONCLUSION:The VA ICU severity model has face, construct, and predictive validity.
Resilience, the ability to adapt or absorb disturbance, disruption, and change, may be increased by team processes in a complex, socio-technical system. In particular, collaborative cross-checking is ...a strategy where at least two individuals or groups with different perspectives examine the others' assumptions and/or actions to assess validity or accuracy. With this strategy, erroneous assessments or actions can be detected quickly enough to mitigate or eliminate negative consequences. In this paper, we seek to add to the understanding of the elements that are needed in effective cross-checking and the limitations of the strategy. We define collaborative cross-checking, describe in detail three healthcare incidents where collaborative cross-checks played a key role, and discuss the implications of emerging patterns. PUBLICATION ABSTRACT
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