Potential Cost-effectiveness of Early Identification of Hospital-acquired Infection in Critically Ill Patients.

Abstract

RATIONALE: Limitations in methods for the rapid diagnosis of hospital-acquired infections often delay initiation of effective antimicrobial therapy. New diagnostic approaches offer potential clinical and cost-related improvements in the management of these infections. OBJECTIVES: We developed a decision modeling framework to assess the potential cost-effectiveness of a rapid biomarker assay to identify hospital-acquired infection in high-risk patients earlier than standard diagnostic testing. METHODS: The framework includes parameters representing rates of infection, rates of delayed appropriate therapy, and impact of delayed therapy on mortality, along with assumptions about diagnostic test characteristics and their impact on delayed therapy and length of stay. Parameter estimates were based on contemporary, published studies and supplemented with data from a four-site, observational, clinical study. Extensive sensitivity analyses were performed. The base-case analysis assumed 17.6% of ventilated patients and 11.2% of nonventilated patients develop hospital-acquired infection and that 28.7% of patients with hospital-acquired infection experience delays in appropriate antibiotic therapy with standard care. We assumed this percentage decreased by 50% (to 14.4%) among patients with true-positive results and increased by 50% (to 43.1%) among patients with false-negative results using a hypothetical biomarker assay. Cost of testing was set at $110/d. MEASUREMENTS AND MAIN RESULTS: In the base-case analysis, among ventilated patients, daily diagnostic testing starting on admission reduced inpatient mortality from 12.3 to 11.9% and increased mean costs by $1,640 per patient, resulting in an incremental cost-effectiveness ratio of $21,389 per life-year saved. Among nonventilated patients, inpatient mortality decreased from 7.3 to 7.1% and costs increased by $1,381 with diagnostic testing. The resulting incremental cost-effectiveness ratio was $42,325 per life-year saved. Threshold analyses revealed the probabilities of developing hospital-acquired infection in ventilated and nonventilated patients could be as low as 8.4 and 9.8%, respectively, to maintain incremental cost-effectiveness ratios less than $50,000 per life-year saved. CONCLUSIONS: Development and use of serial diagnostic testing that reduces the proportion of patients with delays in appropriate antibiotic therapy for hospital-acquired infections could reduce inpatient mortality. The model presented here offers a cost-effectiveness framework for future test development.

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Citation

Published Version (Please cite this version)

10.1513/AnnalsATS.201504-205OC

Publication Info

Tsalik, Ephraim L, Yanhong Li, Lori L Hudson, Vivian H Chu, Tiffany Himmel, Alex T Limkakeng, Jason N Katz, Seth W Glickman, et al. (2016). Potential Cost-effectiveness of Early Identification of Hospital-acquired Infection in Critically Ill Patients. Ann Am Thorac Soc, 13(3). pp. 401–413. 10.1513/AnnalsATS.201504-205OC Retrieved from https://hdl.handle.net/10161/12538.

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Scholars@Duke

Tsalik

Ephraim Tsalik

Adjunct Associate Professor in the Department of Medicine

My research at Duke has focused on understanding the dynamic between host and pathogen so as to discover and develop host-response markers that can diagnose and predict health and disease.  This new and evolving approach to diagnosing illness has the potential to significantly impact individual as well as public health considering the rise of antibiotic resistance.

With any potential infectious disease diagnosis, it is difficult, if not impossible, to determine at the time of presentation what the underlying cause of illness is.  For example, acute respiratory illness is among the most frequent reasons for patients to seek care. These symptoms, such as cough, sore throat, and fever may be due to a bacterial infection, viral infection, both, or a non-infectious condition such as asthma or allergies.  Given the difficulties in making the diagnosis, most patients are inappropriately given antibacterials.  However, each of these etiologies (bacteria, virus, or something else entirely) leaves a fingerprint embedded in the host’s response. We are very interested in finding those fingerprints and exploiting them to generate new approaches to understand, diagnose, and manage disease.

These principles also apply to sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Just as with acute respiratory illness, it is often difficult to identify whether infection is responsible for a patient’s critical illness.  We have embarked on a number of research programs that aim to better identify sepsis; define sepsis subtypes that can be used to guide future clinical research; and to better predict sepsis outcomes.  These efforts have focused on many systems biology modalities including transcriptomics, miRNA, metabolomics, and proteomics.  Consequently, our Data Science team has utilized these highly complex data to develop new statistical methods, furthering both the clinical and statistical research communities.

These examples are just a small sampling of the breadth of research Dr. Tsalik and his colleagues have conducted.  

In April 2022, Dr. Tsalik has joined Danaher Diagnostics as the VP and Chief Scientific Officer for Infectious Disease, where he is applying this experience in biomarkers and diagnostics to shape the future of diagnostics in ID. 

Chu

Vivian Hou Chu

Professor of Medicine

Dr. Chu's clinical research is focused on staphylococci and endocarditis (IE).  She is the director of the International Collaboration on Endocarditis (ICE), a group of investigators from 78 sites in 32 countries worldwide that is dedicated to further the understanding of infective endocarditis.  The ICE database comprises > 5000 cases of endocarditis and is designed to answer questions that could not be answered from a single-center study. The current focus of this group is surgical-decision making in the treatment of endocarditis. Another major focus of Dr. Chu's research is on the relationship between oral hygiene and risk for developing infective endocarditis.

Limkakeng

Alexander Tan Limkakeng

Professor of Emergency Medicine

Dr. Alexander T. Limkakeng, Jr., MD, MHSc, FACEP is a Professor of Emergency Medicine, Vice Chair of Clinical Research, Director of the Acute Care Research Team, and Director of the Resident Research Fellowship for the Department of Emergency Medicine in the Duke University School of Medicine in Durham, North Carolina.

Dr. Limkakeng has served as chair of the American College of Emergency Physicians (ACEP) Research Committee, and been the Course Director of the ACEP Research Forum from 2016-2018, the largest emergency medical research platform in the nation. He is also the Assistant Director of ACEP’s Emergency Medicine Basic Research Skills course. He was elected to the Nominating Committee of the Society of Academic Emergency Medicine.

As a researcher, Dr. Limkakeng has led multiple clinical trials and interdepartmental sponsored projects and is author on over 100 peer-reviewed manuscripts. These include studies in emergency conditions such as COVID-19, traumatic brain injury, hypertension, heart failure, thrombosis, stroke, envenomations, and septic shock. His research has been funded by grants and contracts totaling over $9 million dollars. He has lectured internationally on acute coronary syndrome, responsible conduct of research, design of clinical trials, and precision medicine in emergency care. He has led Duke’s involvement in NIH-funded research networks and in industry-funded work that led to FDA approval for multiple high-sensitivity cardiac troponin assays and point-of-care COVID-19 diagnostic tests. He has servesd as Co-PI for the Duke U24 Hub in the NIH Early Phase Pain Investigation Clinical Network (EPPIC-Net) (1U24NS114416) and now serves as a co-PI on the Duke U24 Hub award (1U24NS129498) in the NIH Strategies to Innovate Emergency Care Clinical Trials (SIREN) Network and in the NIH NINDS Strokenet network (1U24NS135250)

His personal research interest is finding new ways to diagnose acute coronary syndrome. In particular, he is interested in novel biomarkers and precision medicine approaches to this problem. The common element throughout this work is a focus on time-sensitive health conditions.

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