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OBJECTIVE: To provide guidelines for admission, discharge, and triage of adult patients to the intensive care unit (ICU), based on expert opinion and the relevant literature. DATA SOURCES: Publications relevant to the admission, discharge, and triage of patients to the ICU were obtained from the medical literature. STUDY SELECTION: Not applicable. DATA EXTRACTION: Articles were reviewed and the relevant information extracted for analysis by an expert panel. DATA SYNTHESIS: The articles were reviewed and graded levels of recommendation made based on a rating system described in the text. CONCLUSIONS: Although little scientifically rigorous data exist validating the criteria for admission, discharge, and triage of adult patients to the ICU, current literature and expert opinion support guidelines to streamline the admission, discharge, and triage process.
OBJECTIVES: To analyze the evolving role, patterns of use, and costs of critical care medicine in the United States from 2000 to 2005. DESIGN: Retrospective study of data from the Hospital Cost Report Information System (Centers for Medicare and Medicaid Services, Baltimore, Maryland). SETTING: Nonfederal, acute care hospitals with critical care medicine beds in the United States. SUBJECTS: None. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed hospital and critical care medicine beds, bed types, days, occupancy rates, payer mix (Medicare and Medicaid), and costs. Critical care medicine costs were compared with national cost indexes. Between 2000 and 2005, the total number of U.S. hospitals with critical care medicine beds decreased by 12.2% (from 3,586 to 3,150). Although the number of hospital beds decreased by 4.2% (from 655,785 to 628,409), both hospital days and occupancy rates increased by 5.1% (from 145.1 to 152.5 million) and 13.7% (from 59% to 67%), respectively. Critical care medicine beds increased by 6.5% (from 88,252 to 93,955), days by 10.6% (from 21.0 to 23.2 million), and occupancy rates by 4.5% (from 65% to 68%). The majority (90%) of critical care medicine beds were classified as intensive care, premature/neonatal, and coronary care unit beds. The percentage of critical care medicine days used by Medicare decreased by 3.8% (from 37.9% to 36.5%) compared with an increase of 15.5% (from 14.5% to 16.8%) by Medicaid. From 2000 to 2005, critical care medicine costs per day increased by 30.4% (from $2698 to $3518). Although annual critical care medicine costs increased by 44.2% (from $56.6 to $81.7 billion), the proportion of hospital costs and national health expenditures allocated to critical care medicine decreased by 1.6% and 1.8%, respectively. However, the proportion of the gross domestic product used by critical care medicine increased by 13.7%. In 2005, critical care medicine costs represented 13.4% of hospital costs, 4.1% of national health expenditures, and 0.66% of the gross domestic product. CONCLUSIONS: Critical care medicine continues to grow in a shrinking U.S. hospital system. The critical care medicine payer mix is evolving, with Medicaid increasing in its percentage of critical care medicine use. Critical care medicine is more cost controlled than other healthcare indexes, but is still using an increasing percentage of the gross domestic product. Our updated and comprehensive critical care medicine use and cost analysis provides a contemporary benchmark for the strategic planning of critical care medicine services within the U.S. healthcare system.
OBJECTIVE: Critical care medicine trainees and faculty must acquire and maintain the skills necessary to provide state-of-the art clinical care to critically ill patients, to improve patient outcomes, optimize intensive care unit utilization, and continue to advance the theory and practice of critical care medicine. This should be accomplished in an environment dedicated to compassionate and ethical care. PARTICIPANTS: A multidisciplinary panel of professionals with expertise in critical care education and the practice of critical care medicine under the direction of the American College of Critical Care Medicine. SCOPE: Physician education in critical care medicine in the United States should encompass all disciplines that provide care in the intensive care unit and all levels of training: from medical students through all levels of postgraduate training and continuing medical education for all providers of clinical critical care. The scope of this guideline includes physician education in the United States from residency through ongoing practice after subspecialization. DATA SOURCES AND SYNTHESIS: Relevant literature was accessed via a systematic Medline search as well as by requesting references from all panel members. Subsequently, the bibliographies of obtained literature were reviewed for additional references. In addition, a search of organization-based published material was conducted via the Internet. This included but was not limited to material published by the American College of Critical Care Medicine, Accreditation Council for Graduate Medical Education, Accreditation Council for Continuing Medical Education, and other primary and specialty organizations. Collaboratively and iteratively, the task force met, by conference call and in person, to construct the tenets and ultimately the substance of this guideline. CONCLUSIONS: Guidelines for the continuum of education in critical care medicine from residency through specialty training and ongoing throughout practice will facilitate standardization of physician education in critical care medicine.
OBJECTIVES: Critical care medicine is a natural environment for machine learning approaches to improve outcomes for critically ill patients as admissions to ICUs generate vast amounts of data. However, technical, legal, ethical, and privacy concerns have so far limited the critical care medicine community from making these data readily available. The Society of Critical Care Medicine and the European Society of Intensive Care Medicine have identified ICU patient data sharing as one of the priorities under their Joint Data Science Collaboration. To encourage ICUs worldwide to share their patient data responsibly, we now describe the development and release of Amsterdam University Medical Centers Database (AmsterdamUMCdb), the first freely available critical care database in full compliance with privacy laws from both the United States and Europe, as an example of the feasibility of sharing complex critical care data. SETTING: University hospital ICU. SUBJECTS: Data from ICU patients admitted between 2003 and 2016. INTERVENTIONS: We used a risk-based deidentification strategy to maintain data utility while preserving privacy. In addition, we implemented contractual and governance processes, and a communication strategy. Patient organizations, supporting hospitals, and experts on ethics and privacy audited these processes and the database. MEASUREMENTS AND MAIN RESULTS: AmsterdamUMCdb contains approximately 1 billion clinical data points from 23,106 admissions of 20,109 patients. The privacy audit concluded that reidentification is not reasonably likely, and AmsterdamUMCdb can therefore be considered as anonymous information, both in the context of the U.S. Health Insurance Portability and Accountability Act and the European General Data Protection Regulation. The ethics audit concluded that responsible data sharing imposes minimal burden, whereas the potential benefit is tremendous. CONCLUSIONS: Technical, legal, ethical, and privacy challenges related to responsible data sharing can be addressed using a multidisciplinary approach. A risk-based deidentification strategy, that complies with both U.S. and European privacy regulations, should be the preferred approach to releasing ICU patient data. This supports the shared Society of Critical Care Medicine and European Society of Intensive Care Medicine vision to improve critical care outcomes through scientific inquiry of vast and combined ICU datasets.
Intensivists are increasingly needed to care for the critically ill and manage ICUs as ICU beds, utilization, acuity of illness, complexity of care and costs continue to rise. However, there is a nationwide shortage of intensivists that has occurred despite years of well publicized warnings of an impending workforce crisis from specialty societies and the federal government. The magnitude of the intensivist shortfall, however, is difficult to determine because there are many perspectives of optimal ICU administration, patient coverage and intensivist availability and a lack of national data on intensivist practices. Nevertheless, the intensivist shortfall is quite real as evidenced by the alternative solutions that hospitals are deploying to provide care for their critically ill patients. In the midst of these manpower struggles, the critical care environment is dynamically changing and becoming more stressful. Severe hospital bed availability and fiscal constraints are forcing ICUs to alter their approaches to triage, throughput and unit staffing. National and local organizations are mandating that hospitals comply with resource intensive and arguably unproven initiatives to monitor and improve patient safety and quality, and informatics systems. Lastly, there is an ongoing sense of professional dissatisfaction among intensivists and a lack of public awareness that critical care medicine is even a distinct specialty. This article offers proposals to increase the adult intensivist workforce through expansion and enhancements of internal medicine based critical care training programs, incentives for recent graduates to enter the critical care medicine field, suggestions for improvements in the critical care profession and workplace to encourage senior intensivists to remain in the field, proactive marketing of critical care, and expanded engagement by the critical care societies in the challenges facing intensivists.
OBJECTIVES: The American College of Critical Care Medicine provided 2002 and 2007 guidelines for hemodynamic support of newborn and pediatric septic shock. Provide the 2014 update of the 2007 American College of Critical Care Medicine "Clinical Guidelines for Hemodynamic Support of Neonates and Children with Septic Shock." DESIGN: Society of Critical Care Medicine members were identified from general solicitation at Society of Critical Care Medicine Educational and Scientific Symposia (2006-2014). The PubMed/Medline/Embase literature (2006-14) was searched by the Society of Critical Care Medicine librarian using the keywords: sepsis, septicemia, septic shock, endotoxemia, persistent pulmonary hypertension, nitric oxide, extracorporeal membrane oxygenation, and American College of Critical Care Medicine guidelines in the newborn and pediatric age groups. MEASUREMENTS AND MAIN RESULTS: The 2002 and 2007 guidelines were widely disseminated, translated into Spanish and Portuguese, and incorporated into Society of Critical Care Medicine and American Heart Association/Pediatric Advanced Life Support sanctioned recommendations. The review of new literature highlights two tertiary pediatric centers that implemented quality improvement initiatives to improve early septic shock recognition and first-hour compliance to these guidelines. Improved compliance reduced hospital mortality from 4% to 2%. Analysis of Global Sepsis Initiative data in resource rich developed and developing nations further showed improved hospital mortality with compliance to first-hour and stabilization guideline recommendations. CONCLUSIONS: The major new recommendation in the 2014 update is consideration of institution-specific use of 1) a "recognition bundle" containing a trigger tool for rapid identification of patients with septic shock, 2) a "resuscitation and stabilization bundle" to help adherence to best practice principles, and 3) a "performance bundle" to identify and overcome perceived barriers to the pursuit of best practice principles.
With the rapid development of artificial intelligence (AI), large language models (LLMs) have shown strong capabilities in natural language understanding, reasoning, and generation, attracting amounts of research interest in applying LLMs to health and medicine. Critical care medicine (CCM) provides diagnosis and treatment for critically ill patients who often require intensive monitoring and interventions in intensive care units (ICUs). Can LLMs be applied to CCM? Are LLMs just like stochastic parrots or ICU experts in assisting clinical decision-making? This scoping review aims to provide a panoramic portrait of the application of LLMs in CCM. Literature in seven databases, including PubMed, Embase, Scopus, Web of Science, CINAHL, IEEE Xplore, and ACM Digital Library, were searched from January 1, 2019, to June 10, 2024. Peer-reviewed journal and conference articles that discussed the application of LLMs in critical care settings were included. From an initial 619 articles, 24 were selected for final review. This review grouped applications of LLMs in CCM into three categories: clinical decision support, medical documentation and reporting, and medical education and doctor-patien
OBJECTIVES: The Society of Critical Care Medicine and four other major critical care organizations have endorsed a seven-step process to resolve disagreements about potentially inappropriate treatments. The multiorganization statement (entitled: An official ATS/AACN/ACCP/ESICM/SCCM Policy Statement: Responding to Requests for Potentially Inappropriate Treatments in Intensive Care Units) provides examples of potentially inappropriate treatments; however, no clear definition is provided. This statement was developed to provide a clear definition of inappropriate interventions in the ICU environment. DESIGN: A subcommittee of the Society of Critical Care Medicine Ethics Committee performed a systematic review of empirical research published in peer-reviewed journals as well as professional organization position statements to generate recommendations. Recommendations approved by consensus of the full Society of Critical Care Medicine Ethics Committees and the Society of Critical Care Medicine Council were included in the statement. MEASUREMENTS AND MAIN RESULTS: ICU interventions should generally be considered inappropriate when there is no reasonable expectation that the patient will improve sufficiently to survive outside the acute care setting, or when there is no reasonable expectation that the patient's neurologic function will improve sufficiently to allow the patient to perceive the benefits of treatment. This definition should not be considered exhaustive; there will be cases in which life-prolonging interventions may reasonably be considered inappropriate even when the patient would survive outside the acute care setting with sufficient cognitive ability to perceive the benefits of treatment. When patients or surrogate decision makers demand interventions that the clinician believes are potentially inappropriate, the seven-step process presented in the multiorganization statement should be followed. Clinicians should recognize the limits of prognostication when evaluating potential neurologic outcome and terminal cases. At times, it may be appropriate to provide time-limited ICU interventions to patients if doing so furthers the patient's reasonable goals of care. If the patient is experiencing pain or suffering, treatment to relieve pain and suffering is always appropriate. CONCLUSIONS: The Society of Critical Care Medicine supports the seven-step process presented in the multiorganization statement. This statement provides added guidance to clinicians in the ICU environment.
BACKGROUND: The Institute of Medicine calls for the use of clinical guidelines and practice parameters to promote "best practices" and to improve patient outcomes. OBJECTIVE: 2007 update of the 2002 American College of Critical Care Medicine Clinical Guidelines for Hemodynamic Support of Neonates and Children with Septic Shock. PARTICIPANTS: Society of Critical Care Medicine members with special interest in neonatal and pediatric septic shock were identified from general solicitation at the Society of Critical Care Medicine Educational and Scientific Symposia (2001-2006). METHODS: The Pubmed/MEDLINE literature database (1966-2006) was searched using the keywords and phrases: sepsis, septicemia, septic shock, endotoxemia, persistent pulmonary hypertension, nitric oxide, extracorporeal membrane oxygenation (ECMO), and American College of Critical Care Medicine guidelines. Best practice centers that reported best outcomes were identified and their practices examined as models of care. Using a modified Delphi method, 30 experts graded new literature. Over 30 additional experts then reviewed the updated recommendations. The document was subsequently modified until there was greater than 90% expert consensus. RESULTS: The 2002 guidelines were widely disseminated, translated into Spanish and Portuguese, and incorporated into Society of Critical Care Medicine and AHA sanctioned recommendations. Centers that implemented the 2002 guidelines reported best practice outcomes (hospital mortality 1%-3% in previously healthy, and 7%-10% in chronically ill children). Early use of 2002 guidelines was associated with improved outcome in the community hospital emergency department (number needed to treat = 3.3) and tertiary pediatric intensive care setting (number needed to treat = 3.6); every hour that went by without guideline adherence was associated with a 1.4-fold increased mortality risk. The updated 2007 guidelines continue to recognize an increased likelihood that children with septic shock, compared with adults, require 1) proportionally larger quantities of fluid, 2) inotrope and vasodilator therapies, 3) hydrocortisone for absolute adrenal insufficiency, and 4) ECMO for refractory shock. The major new recommendation in the 2007 update is earlier use of inotrope support through peripheral access until central access is attained. CONCLUSION: The 2007 update continues to emphasize early use of age-specific therapies to attain time-sensitive goals, specifically recommending 1) first hour fluid resuscitation and inotrope therapy directed to goals of threshold heart rates, normal blood pressure, and capillary refill <or=2 secs, and 2) subsequent intensive care unit hemodynamic support directed to goals of central venous oxygen saturation >70% and cardiac index 3.3-6.0 L/min/m.
Large Language Models have been tested on medical student-level questions, but their performance in specialized fields like Critical Care Medicine (CCM) is less explored. This study evaluated Meta-Llama 3.1 models (8B and 70B parameters) on 871 CCM questions. Llama3.1:70B outperformed 8B by 30%, with 60% average accuracy. Performance varied across domains, highest in Research (68.4%) and lowest in Renal (47.9%), highlighting the need for broader future work to improve models across various subspecialty domains.
OBJECTIVE: To introduce to the pediatric critical care medicine community a new program in pediatric critical care medicine at the National Institutes of Health. DATA SOURCE: Summary of literature review and conference proceedings. DATA SYNTHESIS: At the National Institute of Child Health and Human Development (NICHD), a new program in pediatric critical care and rehabilitation research has been established in the National Center for Medical Rehabilitation Research. The program is directed by a pediatric intensivist and is focused on developing research directed toward improving long-term outcomes in pediatric critical care and on incorporating pediatric rehabilitation medicine as a partner in this goal. To provide strategic direction for the new program, the NICHD sponsored a planning conference May 3-4, 2002, at the NICHD in Bethesda, MD. The conference invitees represented a broad range of pediatric critical care medicine clinical and research interests, expertise, and career stages. It also included individuals with expertise in rehabilitation research. CONCLUSION: The composition of the new program, including its link to physical medicine and rehabilitation, is discussed. In addition, recommendations by the conference participants and program director are provided to foster the development of more randomized, controlled clinical trials and to develop successful clinician scientists in pediatric critical care medicine.
OBJECTIVE: To develop consensus statements for the diagnosis and management of corticosteroid insufficiency in critically ill adult patients. PARTICIPANTS: A multidisciplinary, multispecialty task force of experts in critical care medicine was convened from the membership of the Society of Critical Care Medicine and the European Society of Intensive Care Medicine. In addition, international experts in endocrinology were invited to participate. DESIGN/METHODS: The task force members reviewed published literature and provided expert opinion from which the consensus was derived. The consensus statements were developed using a modified Delphi methodology. The strength of each recommendation was quantified using the Modified GRADE system, which classifies recommendations as strong (grade 1) or weak (grade 2) and the quality of evidence as high (grade A), moderate (grade B), or low (grade C) based on factors that include the study design, the consistency of the results, and the directness of the evidence. RESULTS: The task force coined the term critical illness-related corticosteroid insufficiency to describe the dysfunction of the hypothalamic-pituitary-adrenal axis that occurs during critical illness. Critical illness-related corticosteroid insufficiency is caused by adrenal insufficiency together with tissue corticosteroid resistance and is characterized by an exaggerated and protracted proinflammatory response. Critical illness-related corticosteroid insufficiency should be suspected in hypotensive patients who have responded poorly to fluids and vasopressor agents, particularly in the setting of sepsis. At this time, the diagnosis of tissue corticosteroid resistance remains problematic. Adrenal insufficiency in critically ill patients is best made by a delta total serum cortisol of < 9 microg/dL after adrenocorticotrophic hormone (250 microg) administration or a random total cortisol of < 10 microg/dL. The benefit of treatment with glucocorticoids at this time seems to be limited to patients with vasopressor-dependent septic shock and patients with early severe acute respiratory distress syndrome (PaO2/FiO2 of < 200 and within 14 days of onset). The adrenocorticotrophic hormone stimulation test should not be used to identify those patients with septic shock or acute respiratory distress syndrome who should receive glucocorticoids. Hydrocortisone in a dose of 200 mg/day in four divided doses or as a continuous infusion in a dose of 240 mg/day (10 mg/hr) for > or = 7 days is recommended for septic shock. Methylprednisolone in a dose of 1 mg x kg(-1) x day(-1) for > or = 14 days is recommended in patients with severe early acute respiratory distress syndrome. Glucocorticoids should be weaned and not stopped abruptly. Reinstitution of treatment should be considered with recurrence of signs of sepsis, hypotension, or worsening oxygenation. Dexamethasone is not recommended to treat critical illness-related corticosteroid insufficiency. The role of glucocorticoids in the management of patients with community-acquired pneumonia, liver failure, pancreatitis, those undergoing cardiac surgery, and other groups of critically ill patients requires further investigation. CONCLUSION: Evidence-linked consensus statements with regard to the diagnosis and management of corticosteroid deficiency in critically ill patients have been developed by a multidisciplinary, multispecialty task force.
Virtual reality (VR) and augmented reality (AR) are aspiring, new technologies with increasing use in critical care medicine. While VR fully immerses the user into a virtual three-dimensional space, AR adds overlaid virtual elements into a real-world environment. VR and AR offer great potential to improve critical care medicine for patients, relatives and health care providers. VR may help to ameliorate anxiety, stress, fear, and pain for the patient. It may assist patients in mobilisation and rehabilitation and can improve communication between all those involved in the patient's care. AR can be an effective tool to support continuous education of intensive care medicine providers, and may complement traditional learning methods to acquire key practical competences such as central venous line placement, cardiopulmonary resuscitation, extracorporeal membrane oxygenation device management or endotracheal intubation. Currently, technical, human, and ethical challenges remain. The adaptation and integration of VR/AR modalities into useful clinical applications that can be used routinely on the ICU is challenging. Users may experience unwanted side effects (so-called "cybersickness") during VR/AR sessions, which may limit its applicability. Furthermore, critically ill patients are one of the most vulnerable patient groups and warrant special ethical considerations if new technologies are to be introduced into their daily care. To date, most studies involving AR/VR in critical care medicine provide only a low level of evidence due to their research design. Here we summarise background information, current developments, and key considerations that should be taken into account for future scientific investigations in this field.
OBJECTIVES: To review the existing literature and task force opinions on regionalization of critical care services, and to synthesize a judgement on possible costs, benefits, disadvantages, and strategies. DATA SOURCES: Pertinent literature in the English language. STUDY SELECTION: One hundred forty-six English language papers were studied to determine possible ramifications of regionalization of critical care or other similar services. DATA EXTRACTION: Information on possible influence on the care of the critically ill was sought and integrated with the opinions of task force members. Possible costs, benefits, as well as disadvantages to the patient, transferring and receiving institutions, and region as a whole were sought. DATA SYNTHESIS: Regionalization of critical care services was thought to be advantageous to the patient. The larger academic institutions tend to have more resources, better subspecialty availability, and expertise in the care of the critically ill. Efficiency and safety during transport need to be in place. Disadvantages of overutilization, possible costliness to both the referring institution as well as to the receiving institution were outlined. It was agreed that pediatric critical care medicine was a separate issue. CONCLUSIONS: Regionalization of critical care medicine probably is beneficial and the concept should be explored.
RATIONALE: A guideline that both evaluates current practice and provides recommendations to address sedation, pain, and delirium management with regard for neuromuscular blockade and withdrawal is not currently available. OBJECTIVE: To develop comprehensive clinical practice guidelines for critically ill infants and children, with specific attention to seven domains of care including pain, sedation/agitation, iatrogenic withdrawal, neuromuscular blockade, delirium, PICU environment, and early mobility. DESIGN: The Society of Critical Care Medicine Pediatric Pain, Agitation, Neuromuscular Blockade, and Delirium in critically ill pediatric patients with consideration of the PICU Environment and Early Mobility Guideline Taskforce was comprised of 29 national experts who collaborated from 2009 to 2021 via teleconference and/or e-mail at least monthly for planning, literature review, and guideline development, revision, and approval. The full taskforce gathered annually in-person during the Society of Critical Care Medicine Congress for progress reports and further strategizing with the final face-to-face meeting occurring in February 2020. Throughout this process, the Society of Critical Care Medicine standard operating procedures Manual for Guidelines development was adhered to. METHODS: Taskforce content experts separated into subgroups addressing pain/analgesia, sedation, tolerance/iatrogenic withdrawal, neuromuscular blockade, delirium, PICU environment (family presence and sleep hygiene), and early mobility. Subgroups created descriptive and actionable Population, Intervention, Comparison, and Outcome questions. An experienced medical information specialist developed search strategies to identify relevant literature between January 1990 and January 2020. Subgroups reviewed literature, determined quality of evidence, and formulated recommendations classified as "strong" with "we recommend" or "conditional" with "we suggest." Good practice statements were used when indirect evidence supported benefit with no or minimal risk. Evidence gaps were noted. Initial recommendations were reviewed by each subgroup and revised as deemed necessary prior to being disseminated for voting by the full taskforce. Individuals who had an overt or potential conflict of interest abstained from relevant votes. Expert opinion alone was not used in substitution for a lack of evidence. RESULTS: The Pediatric Pain, Agitation, Neuromuscular Blockade, and Delirium in critically ill pediatric patients with consideration of the PICU Environment and Early Mobility taskforce issued 44 recommendations (14 strong and 30 conditional) and five good practice statements. CONCLUSIONS: The current guidelines represent a comprehensive list of practical clinical recommendations for the assessment, prevention, and management of key aspects for the comprehensive critical care of infants and children. Main areas of focus included 1) need for the routine monitoring of pain, agitation, withdrawal, and delirium using validated tools, 2) enhanced use of protocolized sedation and analgesia, and 3) recognition of the importance of nonpharmacologic interventions for enhancing patient comfort and comprehensive care provision.
Domain-specific foundation models for healthcare have expanded rapidly in recent years, yet foundation models for critical care time series remain relatively underexplored due to the limited size and availability of datasets. In this work, we introduce an early-stage pre-trained foundation model for critical care time-series based on the Bi-Axial Transformer (BAT), trained on pooled electronic health record datasets. We demonstrate effective transfer learning by fine-tuning the model on a dataset distinct from the training sources for mortality prediction, where it outperforms supervised baselines, particularly for small datasets ($<5,000$). These contributions highlight the potential of self-supervised foundation models for critical care times series to support generalizable and robust clinical applications in resource-limited settings.
End-stage renal disease patients face a complicated sociomedical situation and rely on various forms of infrastructure for life-sustaining treatment. Disruption of these infrastructures during disasters poses a major threat to their lives. To improve patient access to dialysis treatment, there is a need to assess the potential threat to critical care facilities from hazardous events. In this study, we propose optimization models to solve critical care system resilience problems including patient and medical resource allocation. We use human mobility data in the context of Harris County (Texas) to assess patient access to critical care facilities, dialysis centers in this study, under the simulated hazard impacts, and we propose models for patient re-allocation and temporary medical facility placement to improve critical care system resilience in an equitable manner. The results show (1) the capability of the optimization model in efficient patient re-allocation to alleviate disrupted access to dialysis facilities; (2) the importance of large facilities in maintaining the functioning of the system. The critical care system, particularly the network of dialysis centers, is heavily re
The medical ecosystem consists of the training of new clinicians and researchers, the practice of clinical medicine, and areas of adjacent research. There are many aspects of these domains that could benefit from the application of task automation and programmatic assistance. Machine learning and artificial intelligence techniques, including large language models (LLMs), have been promised to deliver on healthcare innovation, improving care speed and accuracy, and reducing the burden on staff for manual interventions. However, LLMs have no understanding of objective truth that is based in reality. They also represent real risks to the disclosure of protected information when used by clinicians and researchers. The use of AI in medicine in general, and the deployment of LLMs in particular, therefore requires careful consideration and thoughtful application to reap the benefits of these technologies while avoiding the dangers in each context.
In the much-celebrated book Deep Medicine, Eric Topol argues that the development of artificial intelligence for health care will lead to a dramatic shift in the culture and practice of medicine. In the next several decades, he suggests, AI will become sophisticated enough that many of the everyday tasks of physicians could be delegated to it. Topol is perhaps the most articulate advocate of the benefits of AI in medicine, but he is hardly alone in spruiking its potential to allow physicians to dedicate more of their time and attention to providing empathetic care for their patients in the future. Unfortunately, several factors suggest a radically different picture for the future of health care. Far from facilitating a return to a time of closer doctor-patient relationships, the use of medical AI seems likely to further erode therapeutic relationships and threaten professional and patient satisfaction.
In critical care settings such as the Intensive Care Unit, clinicians face the complex challenge of balancing conflicting objectives, primarily maximizing patient survival while minimizing resource utilization (e.g., length of stay). Single-objective Reinforcement Learning approaches typically address this by optimizing a fixed scalarized reward function, resulting in rigid policies that fail to adapt to varying clinical priorities. Multi-objective Reinforcement Learning (MORL) offers a solution by learning a set of optimal policies along the Pareto Frontier, allowing for dynamic preference selection at test time. However, applying MORL in healthcare necessitates strict offline learning from historical data. In this paper, we benchmark three offline MORL algorithms, Conditioned Conservative Pareto Q-Learning (CPQL), Adaptive CPQL, and a modified Pareto Efficient Decision Agent (PEDA) Decision Transformer (PEDA DT), against three scalarized single-objective baselines (BC, CQL, and DDQN) on the MIMIC-IV dataset. Using Off-Policy Evaluation (OPE) metrics, we demonstrate that PEDA DT algorithm offers superior flexibility compared to static scalarized baselines. Notably, our results ext