Introduction Coronary artery bypass graft (CABG) surgery is a well-established, commonly performed treatment for coronary artery disease—a disease that affects over 10% of US adults and is a major cause of morbidity and mortality. In 2005, the mean cost for a CABG procedure among Medicare beneficiaries in the USA was $32 201±$23 059. The same operation reportedly costs less than $2000 to produce in India. The goals of the proposed study are to (1) identify the difference in the costs incurred to perform CABG surgery by three Joint Commission accredited hospitals with reputations for high quality and efficiency and (2) characterise the opportunity to reduce the cost of performing CABG surgery. Methods and analysis We use time-driven activity-based costing (TDABC) to quantify the hospitals’ costs of producing elective, multivessel CABG. TDABC estimates the costs of a given clinical service by combining information about the process of patient care delivery (specifically, the time and quantity of labour and non-labour resources utilised to perform each activity) with the unit cost of each resource used to provide the care. Resource utilisation was estimated by constructing CABG process maps for each site based on observation of care and staff interviews. Unit costs were calculated as a capacity cost rate, measured as a $/min, for each resource consumed in CABG production. Multiplying together the unit costs and resource quantities and summing across all resources used will produce the average cost of CABG production at each site. We will conclude by conducting a variance analysis of labour costs to reveal opportunities to bend the cost curve for CABG production in the USA. Ethics and dissemination All our methods were exempted from review by the Stanford Institutional Review Board. Results will be published in peer-reviewed journals and presented at scientific meetings.
INTRODUCTION Modification of alarm limits is one approach to mitigating alarm fatigue. We aimed to create and validate heart rate (HR) and respiratory rate (RR) percentiles for hospitalized children, and analyze the safety of replacing current vital sign reference ranges with proposed data‐driven, age‐stratified 5th and 95th percentile values. METHODS In this retrospective cross‐sectional study, nurse‐charted HR and RR data from a training set of 7202 hospitalized children were used to develop percentile tables. We compared 5th and 95th percentile values with currently accepted reference ranges in a validation set of 2287 patients. We analyzed 148 rapid response team (RRT) and cardiorespiratory arrest (CRA) events over a 12‐month period, using HR and RR values in the 12 hours prior to the event, to determine the proportion of patients with out‐of‐range vitals based upon reference versus data‐driven limits. RESULTS There were 24,045 (55.6%) fewer out‐of‐range measurements using data‐driven vital sign limits. Overall, 144/148 RRT and CRA patients had out‐of‐range HR or RR values preceding the event using current limits, and 138/148 were abnormal using data‐driven limits. Chart review of RRT and CRA patients with abnormal HR and RR per current limits considered normal by data‐driven limits revealed that clinical status change was identified by other vital sign abnormalities or clinical context. CONCLUSIONS A large proportion of vital signs in hospitalized children are outside presently used norms. Safety evaluation of data‐driven limits suggests they are as safe as those currently used. Implementation of these parameters in physiologic monitors may mitigate alarm fatigue. Journal of Hospital Medicine 2015;11:817–823. © 2015 Society of Hospital Medicine
Objectives: We describe a comprehensive care model for Alzheimer's disease (AD) that improves value within 1-3 years after implementation by leveraging targeted outpatient chronic care management, cognitively protective acute care, and timely caregiver support. Design/Setting/Participants: Using current best evidence, expert opinion, and macroeconomic modeling, we designed a comprehensive care model for AD that improves the quality of care while reducing total per-capita healthcare spending by more than 15%. Measurements: Cost savings were measured as reduced spending by payers. Cost estimates were derived from medical literature and national databases including both public and private US payers. All estimates reflect the value in 2015 dollars using a consumer price index (CPI) inflation calculator. Outcome estimates were determined at year 2, accounting for implementation and steady-state intervention costs.
BACKGROUND: Discharge delays adversely affect hospital bed availability and thus patient flow. OBJECTIVE: We aimed to increase the percentage of early discharges (EDCs; before 11 am). We hypothesized that obtaining at least 25% EDCs would decrease emergency department (ED) and postanesthesia care unit (PACU) hospital bed wait times. DESIGN: This study used a pre/postintervention retrospective analysis. SETTING: All acute care units in a quaternary care academic children's hospital were included in this study.
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