1
|
Kost GJ, Füzéry AK, Caratao LKR, Tinsay S, Zadran A, Ybañez AP. Using geographic rescue time contours, point-of-care strategies, and spatial care paths to prepare island communities for global warming, rising oceans, and weather disasters. Int J Health Geogr 2023; 22:38. [PMID: 38124128 PMCID: PMC10731708 DOI: 10.1186/s12942-023-00359-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/23/2023] [Indexed: 12/23/2023] Open
Abstract
OBJECTIVES To perform geographic contour analysis of sea and land ambulance rescue times in an archipelago subject to super typhoons; to design point-of-care testing strategies for medical emergencies and weather disasters made more intense by global warming and rising oceans; and to assess needs for prehospital testing on spatial care paths that accelerate decision making, increase efficiency, improve outcomes, and enhance standards of care in island nations. METHODS We performed needs assessments, inspected healthcare facilities, and collected ambulance rescue times from professionals in the Bantayan Archipelago, Philippines. We mapped sea/land ambulance rescue routes and time contours. To reveal gaps, we statistically compared the fastest and slowest patient rescue times from islands/islets and barangays to the District Hospital on Bantayan Island. We developed spatial care paths (the fastest routes to care) for acute myocardial infarction, community care, and infectious diseases. We generated a compendium of prehospital diagnostic testing and integrated outcomes evidence, diagnostic needs, and public health goals to recommend point-of-care strategies that build geographic health resilience. RESULTS We observed limited access to COVID-19 assays, absence of blood gas/pH testing for critical care support, and spatial gaps in land and airborne rescues that worsened during inclement weather and sea swells. Mean paired differences (slowest-fastest) in ambulance rescue times to the District Hospital for both islands and barangays were significant (P < 0.0001). Spatial care path analysis showed where point-of-care cardiac troponin testing should be implemented for expedited care of acute myocardial infarction. Geospatial strengths comprised distributed primary care that can be facilitated by point-of-care testing, logical interisland transfers for which decision making and triage could be accelerated with onboard diagnostics, and healthcare networks amenable to medical advances in prehospital testing that accelerate treatment. CONCLUSIONS Point-of-care testing should be positioned upstream close to homes and island populations that have prolonged rescue time contours. Geospatially optimized point-of-need diagnostics and distributed prehospital testing have high potential to improve outcomes. These improvements will potentially decrease disparities in mortality among archipelago versus urban dwellers, help improve island public health, and enhance resilience for increasingly adverse and frequent climate change weather disasters that impact vulnerable coastal areas. [350 words].
Collapse
Affiliation(s)
- Gerald J Kost
- Fulbright Scholar 2020-2022, ASEAN Program, Point-of-Care Testing Center for Teaching and Research (POCT•CTR), Pathology and Laboratory Medicine, School of Medicine, University of California, Davis, CA, 95616, USA.
| | - Anna K Füzéry
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | | | - Samantha Tinsay
- Municipality of Bantayan, Bantayan-Santa Fe-Madridejos Primary Care Provider Network, Cebu, Philippines
| | - Amanullah Zadran
- POCT·CTR, Public Health Sciences, School of Medicine, University of California, Davis, USA
| | - Adrian P Ybañez
- Institute for Molecular Genetics, Parasitology, and Vector-Borne Diseases, and College of Veterinary Medicine, Cebu Technological University, Cebu, Philippines
| |
Collapse
|
2
|
Füzéry AK, Kost GJ. Point-of-Care Testing Practices, Failure Modes, and Risk-Mitigation Strategies in Emergency Medical Services Programs in the Canadian Province of Alberta. Arch Pathol Lab Med 2020; 144:1352-1371. [PMID: 33106860 DOI: 10.5858/arpa.2020-0268-oa] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/28/2020] [Indexed: 11/06/2022]
Abstract
CONTEXT.— Emergency medical services (EMS) programs have been using point-of-care testing (POCT) for more than 20 years. However, only a handful of reports have been published in all of that time on POCT practices in field settings. OBJECTIVE.— To provide an overview of POCT practices and failure modes in 3 of Alberta's EMS programs, and to propose risk-mitigation strategies for reducing or eliminating these failure modes. DESIGN.— Details about POCT practices, failure modes, and risk-mitigation strategies were gathered through (1) conversations with personnel, (2) in-person tours of EMS bases, (3) accompaniment of EMS personnel on missions, (4) internet searches for publicly available information, and (5) a review of laboratory documents. RESULTS.— Practices were most standardized and robust in the community paramedicine program (single service provider, full laboratory oversight), and least standardized and robust in the air ambulance program (4 service providers, limited laboratory oversight). Common failure modes across all 3 programs included device inoperability due to cold weather, analytical validation procedures that failed to consider the unique challenges of EMS settings, and a lack of real-time electronic transmission of results into the health care record. CONCLUSIONS.— A provincial framework for POCT in EMS programs is desirable. Such a framework should include appropriate funding models, laboratory oversight of POCT, and relevant expertise on POCT in EMS settings. The framework should also incorporate specific guidance on quality standards that are needed to address the unique challenges of performing POCT in field settings.
Collapse
Affiliation(s)
- Anna K Füzéry
- From the Point of Care Testing Department, Alberta Precision Laboratories, Edmonton, Alberta, Canada (Füzéry).,the Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada (Füzéry)
| | - Gerald J Kost
- and the Point-of-Care Testing Center for Teaching and Research (POCT·CTR), Department of Pathology and Laboratory Medicine, School of Medicine, University of California, Davis (Kost)
| |
Collapse
|
3
|
Soenksen LR, Martínez-Corona DA, Iñiguez de Gante S, Phabmixay PS, Marongiu Maggi MJ. Low-Cost Thermal Shield for Rapid Diagnostic Tests Using Phase Change Materials. J Med Device 2018. [DOI: 10.1115/1.4038898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
The shelf life of point-of-care and rapid diagnostic tests (POC-RDTs) is commonly compromised by abrupt temperature changes during storage, transportation, and use. This situation is especially relevant in tropical regions and resource-constrained settings where cold chain may be unreliable. Here, we report the use of novel and low-cost passive thermal shield (TS) made from laminated phase change material (PCM) to reduce thermal overload in POC-RDTs. Validation of the proposed design was done through numerical simulation and testing of an octadecane shield prototype in contact with a lateral flow immunoassay. The use of our TS design provided 30–45 min delay in thermal equilibration under constant and oscillating heat load challenges resembling those of field use. The addition of a thin PCM protection layer to POC-RDTs can be a cost-effective, scalable, and reliable solution to provide additional thermal stability to these devices.
Collapse
Affiliation(s)
- Luis R. Soenksen
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139 e-mail:
| | - David A. Martínez-Corona
- Department of Animal Sciences, Universitat Politecnica de Valencia Camí de Vera, s/n, València 46022, Spain e-mail:
| | - Sofía Iñiguez de Gante
- School of Design, National College of Art and Design, Ireland100 Thomas St, Merchants Quay D08, Dublin 8, Ireland e-mail:
| | - Pierre S. Phabmixay
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139 e-mail:
| | | |
Collapse
|
4
|
Pratumvinit B, Charoenkoop N, Niwattisaiwong S, Kost GJ, Tientadakul P. The Effects of Temperature and Relative Humidity on Point-of-Care Glucose Measurements in Hospital Practice in a Tropical Clinical Setting. J Diabetes Sci Technol 2016; 10:1094-100. [PMID: 26908568 PMCID: PMC5032940 DOI: 10.1177/1932296816633485] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Hospitals in tropical countries experience conditions that exceed manufacturer temperature and humidity limits for point-of-care (POC) glucose reagents. Our goal was to assess the effects of out-of-limits storage temperature, operating temperature, and operating humidity on POC glucose measurement reliability. METHODS Quality control measurements were performed monthly using glucose test strips stored under controlled conditions and in inpatient wards under ambient conditions. Glucose test strips were evaluated in groups organized by operating temperatures of 24-25 (group 1), 28-29 (group 2), and 33-34°C (group 3), and relative humidity (RH) of ≤70 (group A), ~80 (group B), and ~90% (group C). RESULTS Glucose results for different storage conditions were inconsistent. Measurements at higher operating temperatures had lower values with mean differences of -2.4 (P < .001) and -36.5 (P < .001) mg/dL (28-29 vs 24-25°C), and -3.6 (P < .001) and -37.4 (P < .001) mg/dL (33-34 vs 24-25°C) for low and high control levels, respectively. Measurements at higher RH had lower values with mean differences of -4.0 (P < .001) and -13.2 (P < .001) mg/dL (~80 vs ≤70% RH), and -5.8 (P < .001) and -16.6 (P < .001) mg/dL (~90 vs ≤70% RH) for low and high levels, respectively. CONCLUSIONS High temperature and high RH decreased glucose concentrations for the POC oxidase-based system we evaluated. We recommend that individual hospitals perform stress testing, then determine if maximum absolute differences, which represent highest risk for patients, are clinically significant for decision making by using error grid analysis.
Collapse
Affiliation(s)
- Busadee Pratumvinit
- Department of Clinical Pathology, Faculty of Medicine Siriraj hospital, Mahidol University, Bangkok, Thailand
| | - Nattakom Charoenkoop
- Department of Clinical Pathology, Faculty of Medicine Siriraj hospital, Mahidol University, Bangkok, Thailand
| | - Soamsiri Niwattisaiwong
- Department of Clinical Pathology, Faculty of Medicine Siriraj hospital, Mahidol University, Bangkok, Thailand
| | - Gerald J Kost
- Point-of-Care Testing Center for Teaching and Research, School of Medicine, University of California and Knowledge Optimization®, Davis, CA, USA
| | - Panutsaya Tientadakul
- Department of Clinical Pathology, Faculty of Medicine Siriraj hospital, Mahidol University, Bangkok, Thailand
| |
Collapse
|
5
|
Performance Evaluation of a Glucose Monitoring System for Point-of-Care Testing With the Critically Ill Patient Population—A Multicenter Study. POINT OF CARE 2015. [DOI: 10.1097/poc.0000000000000045] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
6
|
Kovatchev BP, Wakeman CA, Breton MD, Kost GJ, Louie RF, Tran NK, Klonoff DC. Computing the surveillance error grid analysis: procedure and examples. J Diabetes Sci Technol 2014; 8:673-84. [PMID: 25562887 PMCID: PMC4764239 DOI: 10.1177/1932296814539590] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The surveillance error grid (SEG) analysis is a tool for analysis and visualization of blood glucose monitoring (BGM) errors, based on the opinions of 206 diabetes clinicians who rated 4 distinct treatment scenarios. Resulting from this large-scale inquiry is a matrix of 337 561 risk ratings, 1 for each pair of (reference, BGM) readings ranging from 20 to 580 mg/dl. The computation of the SEG is therefore complex and in need of automation. The SEG software introduced in this article automates the task of assigning a degree of risk to each data point for a set of measured and reference blood glucose values so that the data can be distributed into 8 risk zones. The software's 2 main purposes are to (1) distribute a set of BG Monitor data into 8 risk zones ranging from none to extreme and (2) present the data in a color coded display to promote visualization. Besides aggregating the data into 8 zones corresponding to levels of risk, the SEG computes the number and percentage of data pairs in each zone and the number/percentage of data pairs above/below the diagonal line in each zone, which are associated with BGM errors creating risks for hypo- or hyperglycemia, respectively. To illustrate the action of the SEG software we first present computer-simulated data stratified along error levels defined by ISO 15197:2013. This allows the SEG to be linked to this established standard. Further illustration of the SEG procedure is done with a series of previously published data, which reflect the performance of BGM devices and test strips under various environmental conditions. We conclude that the SEG software is a useful addition to the SEG analysis presented in this journal, developed to assess the magnitude of clinical risk from analytically inaccurate data in a variety of high-impact situations such as intensive care and disaster settings.
Collapse
Affiliation(s)
- Boris P Kovatchev
- University of Virginia, Center for Diabetes Technology, Charlottesville, VA, USA
| | - Christian A Wakeman
- University of Virginia, Center for Diabetes Technology, Charlottesville, VA, USA
| | - Marc D Breton
- University of Virginia, Center for Diabetes Technology, Charlottesville, VA, USA
| | - Gerald J Kost
- University of California, Davis, Point-of-Care Testing Center for Teaching and Research, Davis, CA, USA
| | - Richard F Louie
- University of California, Davis, Point-of-Care Testing Center for Teaching and Research, Davis, CA, USA
| | - Nam K Tran
- University of California, Davis, Point-of-Care Testing Center for Teaching and Research, Davis, CA, USA
| | | |
Collapse
|