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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

Credibility↗
NASA NTRS2010

TEACH (Train to Enable/Achieve Culturally Sensitive Healthcare)

Personnel from diverse ethnic and demographic backgrounds come together in both civilian and military healthcare systems, facing diagnoses that at one level are equalizers: coronary disease is coronary disease, breast cancer is breast cancer. Yet the expression of disease in individuals from different backgrounds, individual patient experience of disease as a particular illness, and interactions between patients and providers occurring in any given disease scenario, all vary enormously depending on the fortuity of the equation of "which patient happens to arrive in whose exam room." Previously, providers' absorption of lessons-learned depended on learning as an apprentice would when exposed over time to multiple populations. As a result, and because providers are often thrown into situations where communications falter through inadequate direct patient experience, diversity in medicine remains a training challenge. The questions then become: Can simulation and virtual training environments (VTEs) be deployed to short-track and standardize this sort of random-walk problem? Can we overcome the unevenness of training caused by some providers obtaining the valuable exposure to diverse populations, whereas others are left to "sink or swim"? This paper summarizes developing a computer-based VTE called TEACH (Training to Enable/Achieve Culturally Sensitive Healthcare). TEACH was developed to enhance healthcare providers' skills in delivering culturally sensitive care to African-American women with breast cancer. With an authoring system under development to ensure extensibility, TEACH allows users to role-play in clinical oncology settings with virtual characters who interact on the basis of different combinations of African American sub-cultural beliefs regarding breast cancer. The paper reports on the roll-out and evaluation of the degree to which these interactions allow providers to acquire, practice, and refine culturally appropriate communication skills and to achieve cultural and individual personalization of healthcare in their clinical practices.

Maulitz, Russell↗
NASA NTRS2023

Implementation of A Drone Delivery System for Healthcare in Mexico: International Precedents and Domestic Considerations

One of the Mexican healthcare system’s principal problems is providing access to its rural communities. Drone delivery has repeatedly proven to be a compelling and cost-effective solution to this problem elsewhere, yet there is currently no scholarship connecting global developments in drone technology to problems in the Mexican healthcare system. This paper is to outline lessons learned from drone systems in several countries, providing information on the potential target communities, technical drone and nest specs, goods of delivery, and regulation of a drone system for healthcare in Mexico.

Drone↗
NASA NTRS2011

Theoretically-Driven Infrastructure for Supporting Healthcare Teams Training at a Military Treatment Facility

The Team Resource Center (TRC) at Naval Medical Center Portsmouth (NMCP) currently hosts a tri-service healthcare teams training course three times annually . The course consists of didactic learning coupled with simulation exercises to provide an interactive educational experience for healthcare professionals. The course is also the foundation of a research program designed to explore the use of simulation technologies for enhancing team training and evaluation. The TRC has adopted theoretical frameworks for evaluating training readiness and efficacy, and is using these frameworks to guide a systematic reconfiguration of the infrastructure supporting healthcare teams training and research initiatives at NMCP.

Turner, Robert T.↗
NASA NTRSDate not supplied

Credible Practice of Models and Simulations for Healthcare

As computational models penetrate clinical care and drive healthcare policy decisions, there is increasing need to communicate that model creation and testing follows reasonable credible practice. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. This presentation introduces the Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative multidisciplinary analysis and practitioner survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. Although some of these are common sense guidelines, many are often missed or misconstrued, even by seasoned practitioners.

credibility↗
NASA NTRSDate not supplied

Development and Future of the Ten Simple Rules for Credible Practice of Models and Simulations in HealthCare

In this session, we will review the development and implementation history of the Ten Simple Rules (TSR) for credible practice in models and simulations that support healthcare. Our focus will be initially on the need and background for the Committee on Credible Practice of Models and Simulations in Healthcare (CPMS) as well as the TSR development process and implementation. This will flow into a demonstration of how the TSR has evolved as means of communicating and understanding the model development process, likely successful application and where the model could fail. We will end this presentation with a discussion on future development avenue, the CPMS efforts to develop a comprehensive rubric supporting current TSR implementation, and efforts to support further adoption of the TSR. The audience will be encouraged to comment on the current state of the TSR, share their TSR application experiences, and provide their insights on future development.

model↗
NASA NTRS2011

Ambulatory Healthcare Utilization in the United States: A System Dynamics Approach

Ambulatory health care needs within the United States are served by a wide range of hospitals, clinics, and private practices. The Emergency Department (ED) functions as an important point of supply for ambulatory healthcare services. Growth in our aging populations as well as changes stemming from broader healthcare reform are expected to continue trend in congestion and increasing demand for ED services. While congestion is, in part, a manifestation of unmatched demand, the state of the alignment between the demand for, and supply of, emergency department services affects quality of care and profitability. The central focus of this research is to provide an explanation of the salient factors at play within the dynamic demand-supply tensions within which ambulatory care is provided within an Emergency Department. A System Dynamics (SO) simulation model is used to capture the complexities among the intricate balance and conditional effects at play within the demand-supply emergency department environment. Conceptual clarification of the forces driving the elements within the system , quantifying these elements, and empirically capturing the interaction among these elements provides actionable knowledge for operational and strategic decision-making.

Diaz, Rafael↗
NASA NTRS2014

HRP's Healthcare Spin-Offs Through Computational Modeling and Simulation Practice Methodologies

Spaceflight missions expose astronauts to novel operational and environmental conditions that pose health risks that are currently not well understood, and perhaps unanticipated. Furthermore, given the limited number of humans that have flown in long duration missions and beyond low Earth-orbit, the amount of research and clinical data necessary to predict and mitigate these health and performance risks are limited. Consequently, NASA's Human Research Program (HRP) conducts research and develops advanced methods and tools to predict, assess, and mitigate potential hazards to the health of astronauts. In this light, NASA has explored the possibility of leveraging computational modeling since the 1970s as a means to elucidate the physiologic risks of spaceflight and develop countermeasures. Since that time, substantial progress has been realized in this arena through a number of HRP funded activates such as the Digital Astronaut Project (DAP) and the Integrated Medical Model (IMM). Much of this success can be attributed to HRP's endeavor to establish rigorous verification, validation, and credibility (VV&C) processes that ensure computational models and simulations (M&S) are sufficiently credible to address issues within their intended scope. This presentation summarizes HRP's activities in credibility of modeling and simulation, in particular through its outreach to the community of modeling and simulation practitioners. METHODS: The HRP requires all M&S that can have moderate to high impact on crew health or mission success must be vetted in accordance to NASA Standard for Models and Simulations, NASA-STD-7009 (7009) [5]. As this standard mostly focuses on engineering systems, the IMM and DAP have invested substantial efforts to adapt the processes established in this standard for their application to biological M&S, which is more prevalent in human health and performance (HHP) and space biomedical research and operations [6,7]. These methods have also generated substantial interest by the broader medical community though institutions like the National Institutes of Health (NIH) and the Food and Drug Administration (FDA) to develop similar standards and guidelines applicable to the larger medical operations and research community. DISCUSSION: Similar to NASA, many leading government agencies, health institutions and medical product developers around the world are recognizing the potential of computational M&S to support clinical research and decision making. In this light, substantial investments are being made in computational medicine and notable discoveries are being realized [8]. However, there is a lack of broadly applicable practice guidance for the development and implementation of M&S in clinical care and research in a manner that instills confidence among medical practitioners and biological researchers [9,10]. In this presentation, we will give an overview on how HRP is working with the NIH's Interagency Modeling and Analysis Group (IMAG), the FDA and the American Society of Mechanical Engineers (ASME) to leverage NASA's biomedical VV&C processes to establish a new regulatory standard for Verification and Validation in Computational Modeling of Medical Devices, and Guidelines for Credible Practice of Computational Modeling and Simulation in Healthcare.

Mulugeta, Lealem↗
NASA NTRS2007

Space Medicine Issues and Healthcare Systems for Space Exploration Medicine

This viewgraph presentation reviews issues of health care in space. Some of the issues reviewed are: (1) Physiological adaptation to microgravity, partial gravity, (2) Medical events during spaceflight, (3) Space Vehicle and Environmental and Surface Health Risks, (4) Medical Concept of Operations (CONOPS), (4a) Current CONOPS & Medical Hardware for Shuttle (STS) and ISS, (4b) Planned Exploration Medical CONOPS & Hardware needs, (5) Exploration Plans for Lunar Return Mission & Mars, and (6) Developing Medical Support Systems.

Scheuring, Richard A.↗
NASA NTRSDate not supplied

A METHOD TO REDUCE BIOBURDEN IN ASTROMATERIALS CURATION FACILITIES WITHOUT INTRODUCING UNWANTED CONTAMINATION

Introduction: NASA curates its Astromaterials collections in cleanrooms that are carefully monitored for particulate, inorganic and trace metal contamination. Current sample collections are not particularly susceptible to organic contamination or biological alteration. However, new collections like those from the OSIRIS-REx and Hayabusa2 missions will have organic contamination requirements and are susceptible to biodegradation. It will be necessary sterilize or at least disinfect curation labs, as well as tools and equipment in a manner that does not introduce additional contamination and does not affect the samples 1. Current curation cleaning procedures utilize isopropyl alcohol which offers some bioburden reduction, but is not effective against spore-forming bacteria or fungal spores 2. We present a modified disinfection method that uses ultrapure hydrogen peroxide to reduce bioburden inside curation labs and glove boxes without introducing contamination or damaging curation equipment. We tested this method in the meteorite processing lab as well as on a glovebox being cleaned for use in processing ANGSA (Apollo Next Generation Sample Analysis) samples and present the results of those tests. We discuss the limitations of this method and describe potential situations in which it will not be applicable. The CDC guidelines for disinfection andsterilization in healthcare facilities discusses over 15different methods for reducing bioburden in hospitalsettings 3. The most common method, steamsterilization, is well suited to sterilizing curationprocessing tools but cannot easily be used to sterilizecleanroom surfaces or large equipment likegloveboxes. Chemical sterilization with bleach(NaOCl) is also a common strategy in healthcare andpharmaceutical settings that presents materialcompatibility issues as well as serious inorganiccontamination concerns for curation facilities.Introducing a new source of Na and Cl into curationlabs is not acceptable. Other chemical methods likeethylene oxide, formaldehyde, iodophors andquaternary ammonium compounds could introduceorganic and inorganic contamination. We chose tofocus on hydrogen peroxide because it is generallycompatible with commonly used curation materialslike stainless steel, aluminum and Teflon and becauseit decomposes to oxygen and water. The CDCguidelines for hydrogen peroxide specify using a 7.5wt% solution at 25 ̊C with a contact time of 30 minutesfor high level disinfection and 6 hours for sterilization.High level disinfection is defined as a technique thatwill kill all microorganisms except large numbers ofbacterial spores 3. Methods: We prepared a solution of 7.5 wt%hydrogen peroxide from a stock solution of ultrapure30 wt% peroxide (JT Baker) and curation gradeultrapure water. This ultrapure water is already used incuration cleaning procedures and thus is not consideredand additional source of contamination. We conducteda materials compatibility test by exposing unanodizedand anodized 6061 T6 Al alloy to the peroxide solutionfor up to six hours and periodically inspecting thesurfaces for visible defects. We used this peroxide todisinfect the floor of the meteorite processing lab andthe interior of a curation glovebox by exposing thesesurfaces to the peroxide solution for 30 min. Thesurfaces were swabbed with a dry macrofoam swabbefore (Puritan Brand 2518051PFRNDFD) and afterperoxide treatment to collect microbes present on thesurfaces. Microbes were extracted by sonication fromthe swab into 15 ml of PBS (phosphate buffered saline)and inoculated onto the following media: TSA (trypticsoy agar) BA (blood agar), R2A (Reasoners 2 agar),Potato Dextrose Agar, Saboraud Dextrose Agar andSaboraud Dextrose Agar with 0.1 mg/ mlchloramphenicol. Four TSA plates and two BA plateswere inoculated with 0.1 ml of PBS each andincubated at 35 and 37 for 48 hours. Two R2A°C°Cplates (0.1 ml of PBS each) were incubated at 25 .°CThe remaining plates were inoculated with 0.2ml ofPBS and incubated at 30 ̊C for seven days. Afterincubation bacterial and fungal isolates were countedand transferred to new plates for identification usingthe VITEK24 automated system or by sequencing aportion of the barcode gene (16S rRNA for bacteria,small subunit gene for fungi) on an ABI 3500 Sangersequencer. Negative controls consisted of swabs thatwere opened in the sampling environment andanalyzed alongside the experimental samples.Results: A 6 hour exposure to hydrogen peroxideresulted in visible pitting on un-anodized 6061 Al, butnot on anodized surfaces. No visible pitting occurredafter a 30 minute exposure. Therefore, we decided tolimit our experimental tests to 30 min. exposures. 17bacterial CFU (colony forming units) representing 4distinct organisms were isolated from the meteorite processing lab floor prior to hydrogen peroxidetreatment. We were unable culture any organisms afterperoxide treatment. In the glovebox we were able toculture three bacterial CFU representing three distinctspecies, including a spore forming bacterium prior todisinfection with peroxide. After the peroxidetreatment we were unable to culture any organisms.Routine monitoring of the meteorite processing lab andthe glovebox did not indicate any increase in unwantedinorganic contamination after these peroxidetreatments. Discussion: A 30 minute treatment with 7.5 wt%peroxide appears to be an effective method forreducing bioburden on typical cleanroom surfaces. Themethod does not introduce unwanted organic orinorganic contamination and is compatible withcommonly used curation materials like stainless steel,Teflon and anodized aluminum alloys. Special careshould be taken with un-anodized aluminum.Prolonged exposure to hydrogen peroxide can causepitting on this material. We recommend using thismethod to disinfect curation labs and equipment whenbiological alteration is a concern. This method iseffective at room temperature and cannot be used todisinfect labs and equipment where the ambienttemperature is < 0 ̊C. Astromaterials samples shouldbe removed from the area where disinfection is tooccur. Hydrogen peroxide is a powerful oxidizingagent and will react with any organic carbon present inthe sample. References: [1.] Mccubbin, F. M. et al.Sp. Sci Rev(2019) doi:10.1007/s11214-019-0615-9. [2.] Mogul, R.et al.Astrobiology 18, ast.2017.1814 (2018). [3.]Rutala, W. A. & Weber, D. J. Guideline for Disinfection and Sterilization in Healthcare Facilities, 2008. [4.] Pincus, D. H. in Encyclopedia of Rapid Microbiological Methods (2005).

A. B. Regberg↗
NASA NTRS1989

Clean Room Apparel

American Hospital Supply Corporation (AHSC), Baxter Healthcare Corporation's predecessor, used the NASA informational base on contamination control technology to improve industrial contamination control technology. When a study determined that microscopic body particles escaping through tiny "windows" in woven garments worn by workers were the greatest source of contamination, AHSC developed TYVEK. This non-woven material filters 99% of all particulate matter larger than half a micron. Baxter Healthcare added a polyimide coating which seals and ties down any loose fibers, providing greater durability. Stress points along seams have been minimized to make the garment almost tearproof. Micro-Clean 212 garments are individually packaged and disposable.

Source record↗
NASA NTRS2001

Evolution of telemedicine in the space program and earth applications

Remote monitoring of crew, spacecraft, and environmental health has always been an integral part of the National Aeronautics and Space Administration's (NASA's) operations. Crew safety and mission success face a number of challenges in outerspace, including physiological adaptations to microgravity, radiation exposure, extreme temperatures and vacuum, and psychosocial reactions to space flight. The NASA effort to monitor and maintain crew health, system performance, and environmental integrity in space flight is a sophisticated and coordinated program of telemedicine combining cutting-edge engineering with medical expertise. As missions have increased in complexity, NASA telemedicine capabilities have grown apace, underlying its role in the field. At the same time, the terrestrial validation of telemedicine technologies to bring healthcare to remote locations provides feedback, improvement, and enhancement of the space program. As NASA progresses in its space exploration program, astronauts will join missions lasting months, even years, that take them millions of miles from home. These long-duration missions necessitate further technological breakthroughs in tele-operations and autonomous technology. Earth-based monitoring will no longer be real-time, requiring telemedicine capabilities to advance with future explorers as they travel deeper into space. The International Space Station will serve as a testbed for the telemedicine technologies to enable future missions as well as improve the quality of healthcare delivery on Earth.

long duration↗