Mary Cooper

Managing the Prevention of Retained Surgical Instruments: What Is the Value of Counting?

Objective:Preventing retained foreign bodies is critical for patient safety. However, the value of counting surgical instruments and the reliability of the information provided have never been quantified. This study examines the diagnostic characteristics of counting and its impact on surgical costs. Methods:We examined data from the Medical Event Reporting System-Total HealthSystem (MERS-TH), administrative hospital, and the New York State Cardiac Surgery Report databases (2000–2004). The cost per count discrepancy was examined by studying a cohort of patients undergoing coronary artery bypass graft (CABG) surgery. Linear and logistic multivariable regression models were used for statistical analysis. Results:Of 153,263 operations, there were 1062 count discrepancies. The rate of retained items was 1 of 7000 surgeries or 1 of 70 discrepancy cases. Final count discrepancies identified 77% and prevented 54% of retained items. The sensitivity of counting was 77.2%, specificity was 99.2%, but the positive predictive value was only 1.6%. Count discrepancies increased with surgery duration, late time procedures, and number of nursing teams. Bypass time, intravenous nitroglycerin injections, or myocardial infarction in the previous 24 hours were independent predictors of count discrepancies in CABG surgery. The incremental OR cost for CABG because of a count discrepancy was

To What Extent Do Pediatricians Accept Computer-Based Dosing Suggestions?

932. Nationally, this would amount to an additional

Realizing the potential of clinical judgment : A real-time strategy for predicting outcomes and cost for medical inpatients

24 million/yr in OR CABG cost. Conclusions:This study, for the first time, quantifies the diagnostic accuracy of counting and defines the parameters against which alternative strategies of prevention should be measured, before being adopted in standard practice.

Comparison of sudden cardiac arrest resuscitation performance data obtained from in-hospital incident chart review and in situ high-fidelity medical simulation

OBJECTIVE. Pediatric medication errors occur frequently among hospitalized patients and are often related to dosing. Computerized physician order entry systems with decision support can decrease dosing errors, as well as other types of errors; however, their use in pediatrics has not been extensively studied. Our objective was to determine physician acceptance of dosing and frequency decision support elements in an inpatient pediatric computerized physician order entry system at 1 academic medical center. PATIENTS AND METHODS. We performed a retrospective analysis of all electronic medication orders entered for pediatric inpatients at a large, urban teaching hospital between April 15, 2004, and December 31, 2004. Rates of physician acceptance of computerized physician order entry system–generated dosing and frequency suggestions were determined. RESULTS. We analyzed 54413 orders in the computerized physician order entry system, of which 27313 orders had dosing or frequency decision support. Of the orders with decision support, approximately one third (8822) were accepted exactly by prescribers. Of the 18491 remaining orders, 8708 were changed for dose, 2466 for frequency, and 7317 for both. Among the 18491 orders that were changed, the majority 11322 deviated by a substantial amount (>50%) from the total daily dose initially suggested by the decision support feature. Overall, patient weight was missing 31.3% of the time, although patient age alone sometimes was sufficient for the computer to make a dosing suggestion. CONCLUSIONS. Although dosing-decision support systems have the potential to improve care, more work needs to be done to determine and optimize their effectiveness. Commercial vendors of dosing knowledge bases need to deliver effective products, because most health care organizations will not have the resources to customize decision support rules.

NewYork-Presbyterian Hospital: Translating Innovation into Practice

PURPOSEnWe sought to determine whether illness severity and anticipated level of function, as evaluated at the time of admission, were associated with outcomes and costs of care for patients admitted to the medical service.nnnMETHODSnAll 1,759 patients admitted to the medical service at a large urban academic medical center between July 1, 1997, and September 30, 1997 (excluding those admitted directly to the intensive care units or for protocol chemotherapy), were evaluated and categorized by the admitting intern by illness severity (not ill, mildly ill, moderately ill, severely ill, or moribund) and anticipated level of function at discharge (excellent, good, fair, or poor) as part of their routine sign-out process. Interns ratings were always available within 24 to 28 hours of admission. In-hospital mortality, length of stay, cost of hospitalization, and anticipated billing revenue were evaluated.nnnRESULTSnPatients who were more severely ill had significantly greater in-hospital mortality. For example, mortality was 1.1% (11 of 972) among those who were not ill or mildly ill, 3.6% (26 of 724) among those who were moderately ill, and 15% (9 of 60) among those who were severely ill. Illness severity (P = 0.003) and anticipated functional status (P < 0.01) were significant predictors of in-hospital mortality. Illness severity and function were also significant predictors of greater length of stay and greater costs of hospitalization (all P < 0.0001). The 389 patients who were moderately ill with fair or poor anticipated function were associated with the largest cumulative losses (about

In Situ Simulation Comparing In-hospital First Responder Sudden Cardiac Arrest Resuscitation Using Semiautomated Defibrillators and Automated External Defibrillators

330,000 during the 3-month period), whereas the 798 mildly ill patients with good or excellent function were associated with the largest cumulative profits (

Lack of Adherence with Preoperative B-blocker Recommendations in a Multicenter Study

550,000).nnnCONCLUSIONnPhysicians estimates of patients illness severity and anticipated function at the time of discharge, as made by interns using a system designed to help them sign out to their colleagues, predict outcomes and costs of hospitalization. Such a system may be useful in developing new approaches to management strategies based on prognosis.

Model for a Merger: NewYork-Presbyterian’s Use of Service Lines to Bring Two Academic Medical Centers Together

INTRODUCTIONnHigh-fidelity medical simulation of sudden cardiac arrest (SCA) presents an opportunity for systematic probing of in-hospital resuscitation systems. Investigators developed and implemented the SimCode program to evaluate simulations ability to generate meaningful data for system safety analysis and determine concordance of observed results with institutional quality data.nnnMETHODSnResuscitation response performance data were collected during in situ SCA simulations on hospital medical floors. SimCode dataset was compared with chart review-based dataset of actual (live) in-hospital resuscitation system performance for SCA events of similar acuity and complexity.nnnRESULTSn135 hospital personnel participated in nine SimCode resuscitations between 2006 and 2008. Resuscitation teams arrived at 2.5+/-1.3 min (mean+/-SD) after resuscitation initiation, started bag-valve-mask ventilation by 2.8+/-0.5 min, and completed endotracheal intubations at 11.3+/-4.0 min. CPR was performed within 3.1+/-2.3 min; arrhythmia recognition occurred by 4.9+/-2.1 min, defibrillation at 6.8+/-2.4 min. Chart review data for 168 live in-hospital SCA events during a contemporaneous period were extracted from institutional database. CPR and defibrillation occurred later during SimCodes than reported by chart review, i.e., live: 0.9+/-2.3 min (p<0.01) and 2.1+/-4.1 min (p<0.01), respectively. Chart review noted fewer problems with CPR performance (simulated: 43% proper CPR vs. live: 98%, p<0.01). Potential causes of discrepancies between resuscitation response datasets included sample size and data limitations, simulation fidelity, unmatched SCA scenario pools, and dissimilar determination of SCA response performance by complementary reviewing methodologies.nnnCONCLUSIONnOn-site simulations successfully generated SCA response measurements for comparison with live resuscitation chart review data. Continued research may refine simulations role in quality initiatives, clarify methodologic discrepancies and improve SCA response.

Medication Safety—Reliability of Preference Cards

BACKGROUNDnNewYork-Presbyterian (NYP) Hospital, a 2,242-bed not-for-profit academic medical center, was formed by a merger of The New York Hospital and The Presbyterian Hospital in the City of New York. It is also the flagship for the NewYork-Presbyterian Healthcare System, with 37 acute care facilities and 18 others.nnnOVERALL APPROACH TO QUALITY AND SAFETYnThe hospital embeds safety in the culture through strategic initiatives and enhances service and efficiency using Six Sigma and other techniques to drive adoption of improvements. Goals are selected in alignment with the annual strategic initiatives, which are chosen on the basis of satisfaction surveys, patient and family complaints, community advisory groups, and performance measures, among other sources.nnnUSE OF INFORMATION TO SET AND EVALUATE QUALITY GOALS AND PRIORITIZE INITIATIVESnA new business intelligence system enables online, dynamic analysis of performance results, replacing static paper reports. Advanced features in the clinical information systems include computerized physician order entry; interactive clinical alerts for decision support; a real-time infection control tracking system; and a clinical data warehouse supporting data mining and analysis for quality improvement, decision making, and education.nnnAPPROACH TO ADDRESSING THE SIX IOM QUALITY AIMSnTo achieve clinical, service, and operational excellence, NYP focuses on all Institute of Medicine quality aims.

Perioperative use of beta-blocker in noncardiac surgery: a multicenter educational intervention to achieve best practice guidelines.

Introduction: Multifaceted approaches using simulation and human factors methods may optimize in-hospital sudden cardiac arrest (SCA) response. The Arrhythmia Simulation/Cardiac Event Nursing Training-Automated External Defibrillator phase (ASCENT-AED) study used in situ medical simulation to compare traditional and AED-supplemented SCA first-responder models. Methods: The study was conducted at an academic 719-bed hospital with institutional review board approval. Two simulation scenarios were developed and featured either respiratory arrest with perfusing bradycardia or ventricular fibrillation (VF) arrest. Study floors were equipped with either a semiautomated defibrillator (SD) only (control) or with both SD and AED (experimental); subjects functioned as solitary first responders and did not receive resuscitation training. Results: Fifty nurses were enrolled on control (n = 25) and experimental (n = 25) floors. The groups nonblinded performances exhibited the following differences during VF scenario: slower calls for help by the control group [mean time to completion of 25 ± 17 seconds versus 18 ± 11 seconds for the experimental group (P < 0.05)] and fewer subjects in the control group performing chest compressions [44.0% versus experimental groups 95.8% (P < 0.001)]. Eighty-eight percent of the control group defibrillated the manikin at an average of 155 ± 59 seconds, with 32.0% of those subjects using semiautomated rhythm analysis; 100% (not significant [NS]) of experimental group defibrillated at 154 ± 72 seconds (NS) with 100% AED analysis (P < 0.001). Fewer control group subjects (28.0%) were observed during the bradycardia scenarios to perform inappropriate chest compressions than the AED-supplemented subjects [69.6% (P = 0.01)]; nonindicated defibrillation was delivered during these scenarios by a single subject in the control group. Twenty-eight percent and 72% of VF scenarios were managed appropriately by control and experimental groups, respectively; bradycardia scenarios were managed without severe adverse event by 64% of control group and 28% of experimental group. Conclusions: In situ simulation can provide useful information, both anticipated and unexpected, to guide decisions about proposed defibrillation technologies and SCA response models for in-hospital resuscitation system design and education before implementation.