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1.
Stud Health Technol Inform ; 290: 309-313, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1879405

ABSTRACT

The rapid growth of clinical trials launched in recent years poses significant challenges for accurate and efficient trial search. Keyword-based clinical trial search engines require users to construct effective queries, which can be a difficult task given complex information needs. In this study, we present an interactive clinical trial search interface that retrieves trials similar to a target clinical trial. It enables user configuration of 13 clinical trial features and 4 metrics (Jaccard similarity, semantic-based similarity, temporal overlap and geographical distance) to measure pairwise trial similarities. Among 1,007 coronavirus disease 2019 (COVID-19) trials conducted in the United States, 91.9% were found to have similar trials with the similarity threshold being 0.85 and 43.8% were highly similar with the threshold 0.95. A simulation study using 3 groups of similar trials curated by COVID-19 clinical trial reviews demonstrates the precision and recall of the search interface.


Subject(s)
COVID-19 , Benchmarking , Data Collection , Humans , Search Engine , Semantics
2.
Bone Joint J ; 104-B(6): 721-728, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1875055

ABSTRACT

AIMS: The aim of this study was to explore current use of the Global Fragility Fracture Network (FFN) Minimum Common Dataset (MCD) within established national hip fracture registries, and to propose a revised MCD to enable international benchmarking for hip fracture care. METHODS: We compared all ten established national hip fracture registries: England, Wales, and Northern Ireland; Scotland; Australia and New Zealand; Republic of Ireland; Germany; the Netherlands; Sweden; Norway; Denmark; and Spain. We tabulated all questions included in each registry, and cross-referenced them against the 32 questions of the MCD dataset. Having identified those questions consistently used in the majority of national audits, and which additional fields were used less commonly, we then used consensus methods to establish a revised MCD. RESULTS: A total of 215 unique questions were used across the ten registries. Only 72 (34%) were used in more than one national audit, and only 32 (15%) by more than half of audits. Only one registry used all 32 questions from the 2014 MCD, and five questions were only collected by a single registry. Only 21 of the 32 questions in the MCD were used in the majority of national audits. Only three fields (anaesthetic grade, operation, and date/time of surgery) were used by all ten established audits. We presented these findings at the Asia-Pacific FFN meeting, and used an online questionnaire to capture feedback from expert clinicians from different countries. A draft revision of the MCD was then presented to all 95 nations represented at the Global FFN conference in September 2021, with online feedback again used to finalize the revised MCD. CONCLUSION: The revised MCD will help aspirant nations establish new registry programmes, facilitate the integration of novel analytic techniques and greater multinational collaboration, and serve as an internationally-accepted standard for monitoring and improving hip fracture services. Cite this article: Bone Joint J 2022;104-B(6):721-728.


Subject(s)
Hip Fractures , Benchmarking , Germany , Hip Fractures/epidemiology , Hip Fractures/surgery , Humans , Registries , Spain
3.
BMC Bioinformatics ; 23(1): 210, 2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1874993

ABSTRACT

BACKGROUND: Due to the growing amount of COVID-19 research literature, medical experts, clinical scientists, and researchers frequently struggle to stay up to date on the most recent findings. There is a pressing need to assist researchers and practitioners in mining and responding to COVID-19-related questions on time. METHODS: This paper introduces CoQUAD, a question-answering system that can extract answers related to COVID-19 questions in an efficient manner. There are two datasets provided in this work: a reference-standard dataset built using the CORD-19 and LitCOVID initiatives, and a gold-standard dataset prepared by the experts from a public health domain. The CoQUAD has a Retriever component trained on the BM25 algorithm that searches the reference-standard dataset for relevant documents based on a question related to COVID-19. CoQUAD also has a Reader component that consists of a Transformer-based model, namely MPNet, which is used to read the paragraphs and find the answers related to a question from the retrieved documents. In comparison to previous works, the proposed CoQUAD system can answer questions related to early, mid, and post-COVID-19 topics. RESULTS: Extensive experiments on CoQUAD Retriever and Reader modules show that CoQUAD can provide effective and relevant answers to any COVID-19-related questions posed in natural language, with a higher level of accuracy. When compared to state-of-the-art baselines, CoQUAD outperforms the previous models, achieving an exact match ratio score of 77.50% and an F1 score of 77.10%. CONCLUSION: CoQUAD is a question-answering system that mines COVID-19 literature using natural language processing techniques to help the research community find the most recent findings and answer any related questions.


Subject(s)
Benchmarking , COVID-19 , Algorithms , Humans , Language , Natural Language Processing
4.
J Paediatr Child Health ; 58(5): 940, 2022 05.
Article in English | MEDLINE | ID: covidwho-1861466
5.
BMC Infect Dis ; 22(1): 458, 2022 May 13.
Article in English | MEDLINE | ID: covidwho-1846800

ABSTRACT

BACKGROUND: Prospective observational data show that infected persons with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain polymerase chain reaction (PCR) positive for a prolonged duration, and that detectable antibodies develop slowly with time. We aimed to analyze how these effects can bias key epidemiological metrics used to track and monitor SARS-CoV-2 epidemics. METHODS: An age-structured mathematical model was constructed to simulate progression of SARS-CoV-2 epidemics in populations. PCR testing to diagnose infection and cross-sectional surveys to measure seroprevalence were also simulated. Analyses were conducted on simulated outcomes assuming a natural epidemic time course and an epidemic in presence of interventions. RESULTS: The prolonged PCR positivity biased the epidemiological measures. There was a lag of 10 days between the true epidemic peak and the actually-observed peak. Prior to epidemic peak, PCR positivity rate was twofold higher than that based only on current active infection, and half of those tested positive by PCR were in the prolonged PCR positivity stage after infection clearance. Post epidemic peak, PCR positivity rate poorly predicted true trend in active infection. Meanwhile, the prolonged PCR positivity did not appreciably bias estimation of the basic reproduction number R0. The time delay in development of detectable antibodies biased measured seroprevalence. The actually-observed seroprevalence substantially underestimated true prevalence of ever infection, with the underestimation being most pronounced around epidemic peak. CONCLUSIONS: Caution is warranted in interpreting PCR and serological testing data, and any drawn inferences need to factor the effects of the investigated biases for an accurate assessment of epidemic dynamics.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Benchmarking , Bias , COVID-19/diagnosis , COVID-19/epidemiology , Cross-Sectional Studies , Humans , Polymerase Chain Reaction , SARS-CoV-2/genetics , Seroepidemiologic Studies
6.
Can J Public Health ; 113(2): 196-203, 2022 04.
Article in English | MEDLINE | ID: covidwho-1841734

ABSTRACT

OBJECTIVE: Although vaccines are one of the most cost-effective, low-risk healthcare approaches that save thousands of lives every year, paradoxical fear about vaccine safety is a major roadblock for achieving widespread vaccination coverage. The objective of this study is to change public perception of vaccine safety by presenting real-world incidence of adverse events following immunization (AEFIs). METHODS: In this study, we used Canadian post-market adverse events data to estimate the real-world risk of AEFI and benchmarked them against five commonly used drug types-ACE inhibitors, beta2 adrenergic receptors, penicillins, proton pump inhibitors, and HMG-CoA reductase inhibitors. RESULTS: Our analysis shows that post-market AEFIs are rare, and vaccination generally carries a significantly lower risk compared to some commonly used medicinal product types. CONCLUSION: Despite some limitations with using post-trial adverse events data, we believe that the evidence presented in this study, especially the comparative risk analysis between vaccines and medicinal products, when communicated through proper channels, can help vaccine-hesitant individuals overcome their perceived safety concerns with regard to vaccines.


RéSUMé: OBJECTIFS: Bien que les vaccins soient l'une des approches de soins de santé les plus rentables et à faible risque qui sauvent des milliers de vies chaque année, la peur paradoxale de la sécurité des vaccins est un obstacle majeur à la réalisation d'une couverture vaccinale généralisée. L'objectif de cette étude est de changer la perspective publique de la sécurité des vaccins en présentant l'incidence actuelle des événements indésirables post-commercialisation après la vaccination. MéTHODES: Dans cette étude, nous avons utilisé les données canadiennes sur les événements indésirables post-commercialisation pour estimer le risque réel d'événements indésirables après la vaccination et les avons comparés à cinq types de médicaments couramment utilisés ­ inhibiteurs de l'ECA (enzyme de conversion de l'angiotensine), récepteur bêta-2-adrénergique, pénicillines, inhibiteurs de la pompe à protons et inhibiteurs de l'HMG-CoA réductase. RéSULTATS: Notre analyse montre que les événements indésirables post-commercialisation après la vaccination sont rares et que la vaccination comporte généralement un risque significativement plus faible par rapport à certains types de médicaments couramment utilisés. CONCLUSION: Malgré certaines limites à l'utilisation des données sur les événements indésirables post-essai, nous pensons que les preuves présentées dans cette étude, en particulier l'analyse comparative des risques entre les vaccins et les médicaments, lorsqu'elle est communiquée par des canaux appropriés, peuvent aider les personnes hésitantes à surmonter leurs préoccupations perçues en matière d'innocuité des vaccins.


Subject(s)
Benchmarking , Vaccines , Adverse Drug Reaction Reporting Systems , Canada , Humans , Vaccination , Vaccines/adverse effects
7.
Comput Biol Med ; 146: 105572, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1814281

ABSTRACT

BACKGROUND: The SARS-CoV-2 main protease (Mpro) is an attractive target in the COVID-19 drug development process. It catalyzes the polyprotein's translation from viral RNA and specifies a particular cleavage site. Due to the absence of identical cleavage specificity in human cell proteases, targeting Mpro with chemical compounds can obstruct the replication of the virus. METHODS: To explore the potential binding mechanisms of 1,2,3-triazole scaffolds in comparison to co-crystallized inhibitors 11a and 11b towards Mpro, we herein utilized molecular dynamics and enhanced sampling simulation studies. RESULTS AND CONCLUSION: All the 1,2,3-triazole scaffolds interacted with catalytic residues (Cys145 and His41) and binding pocket residues of Mpro involving Met165, Glu166, Ser144, Gln189, His163, and Met49. Furthermore, the adequate binding free energy and potential mean force of the topmost compound 3h was comparable to the experimental inhibitors 11a and 11b of Mpro. Overall, the current analysis could be beneficial in developing the SARS-CoV-2 Mpro potential inhibitors.


Subject(s)
COVID-19 , Molecular Dynamics Simulation , Benchmarking , COVID-19/drug therapy , Coronavirus 3C Proteases , Cysteine Endopeptidases/chemistry , Humans , Molecular Docking Simulation , Protease Inhibitors/chemistry , Protease Inhibitors/pharmacology , SARS-CoV-2 , Triazoles , Viral Nonstructural Proteins/chemistry
9.
Acute Med ; 21(1): 19-26, 2022.
Article in English | MEDLINE | ID: covidwho-1766395

ABSTRACT

INTRODUCTION: The Society for Acute Medicine Benchmarking Audit 2021 (SAMBA21) took place on 17th June 2021, providing the first assessment of performance against the Society for Acute Medicine's Clinical Quality Indicators (CQIs) within acute medical units since the start of the COVID-19 pandemic. METHODS: All acute hospitals in the UK were invited to participate. Data were collected on unit structure, and for patients admitted to acute medicine services over a 24-hour period, with follow-up at 7 days. RESULTS: 158 units participated in SAMBA21, from 156 hospitals. 8973 patients were included. The number of admissions per unit had increased compared to SAMBA19 (Sign test p<0.005). An early warning score was recorded within 30 minutes of hospital arrival in 77.4% of patients. 87.4% of unplanned admissions were seen by a tier 1 clinician within 4 hours of arrival. Overall, the medical team performed the initial clinician assessment for 36.4% of unplanned medical admissions. More than a third of medical admissions had their initial assessment in Same Day Emergency Care (SDEC) in 25.4% of hospitals. 62.1% of unplanned admissions were seen by two other clinical decision makers prior to consultant review. Of those unplanned admissions requiring consultant review, 67.8% were seen within the target time. More than a third of unplanned admissions were discharged the same day in 41.8% of units. CONCLUSION: Performance against the CQIs for acute medicine was maintained in comparison to previous rounds of SAMBA, despite increased admissions. There remains considerable variation in unit structure and performance within acute medical services.


Subject(s)
Benchmarking , COVID-19 , COVID-19/epidemiology , Hospitalization , Humans , Medical Audit , Pandemics
10.
Clin Chem Lab Med ; 60(6): 830-841, 2022 05 25.
Article in English | MEDLINE | ID: covidwho-1765561

ABSTRACT

OBJECTIVES: Medical laboratory performance is a relative concept, as are quality and safety in medicine. Therefore, repetitive benchmarking appears to be essential for sustainable improvement in health care. The general idea in this approach is to establish a reference level, upon which improvement may be strived for and quantified. While the laboratory community traditionally is highly aware of the need for laboratory performance and public scrutiny is more intense than ever due to the SARS-CoV-2 pandemic, few initiatives span the globe. The aim of this study was to establish a good practice approach towards benchmarking on a high abstraction level for three key dimensions of medical laboratory performance, generate a tentative snapshot of the current state of the art in the region of Europe, Middle East, and Africa (EMEA), and thus set the stage for global follow-up studies. METHODS: The questionnaire used and previously published in this initiative consisted of 50 items, roughly half relating to laboratory operations in general with the other half addressing more specific topics. An international sample of laboratories from EMEA was approached to elicit high fidelity responses with the help of trained professionals. Individual item results were analyzed using standard descriptive statistics. Dimensional reduction of specific items was performed using exploratory factor analysis and assessed with confirmatory factor analysis, resulting in individual laboratory scores for the three subscales of "Operational performance", "Integrated clinical care performance", and "Financial sustainability". RESULTS: Altogether, 773 laboratories participated in the survey, of which 484 were government hospital laboratories, 129 private hospital laboratories, 146 commercial laboratories, and 14 were other types of laboratories (e.g. research laboratories). Respondents indicated the need for digitalization (e.g. use of IT for order management, auto-validation), automation (e.g. pre-analytics, automated sample transportation), and establishment of formal quality management systems (e.g. ISO 15189, ISO 9001) as well as sustainably embedding them in the fabric of laboratory operations. Considerable room for growth also exists for services provided to physicians, such as "Diagnostic pathways guidance", "Proactive consultation on complex cases", and "Real time decision support" which were provided by less than two thirds of laboratories. Concordantly, the most important kind of turn-around time (TAT) for clinicians, sample-to-result TAT, was monitored by only 40% of respondents. CONCLUSIONS: Altogether, the need for stronger integration of laboratories into the clinical care process became apparent and should be a main trajectory of future laboratory management. Factor analysis confirmed the theoretical constructs of the questionnaire design phase, resulting in a reasonably valid tool for further benchmarking activities on the three aimed-for key dimensions.


Subject(s)
COVID-19 , Laboratories, Hospital , Benchmarking , COVID-19/diagnosis , Europe , Humans , Laboratories , SARS-CoV-2 , Surveys and Questionnaires
11.
J Arthroplasty ; 37(7S): S408-S412, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1763578

ABSTRACT

BACKGROUND: Shifts in demand, capacity, and site of service have impacted total hip arthroplasty (THA) volumes and revenues over the 2019-2021 time period. Moving THA off the inpatient-only (IPO) list and the COVID-19 pandemic has caused a shift in delivery away from inpatient services and a decrease in demand. METHODS: Medicare claims data were surveyed for the latest period available (April 1, 2020 to September 2020) and compared with a similar period in 2019 prior to THA removal from the IPO list and before the COVID-19 pandemic. Length of stay (LOS), admission status, site of service, discharge status, cost to CMS (Centers of Medicaid and Medicare Services), and racial disparities were analyzed. RESULTS: From 2019 to 2020, changes in primary THA metrics occurred (overall change in total joint arthroplasty [THA plus total knee arthroplasty metrics]): CMS THA volume decreased from 78,691 to 65,360, -16% (-22%); THA performed as an outpatient increased from 0% to 51% (141%); THA performed as same-day discharge increased from 3% to 12%, 325% (221%); overall LOS decreased from 1.91 to 1.46, -23% (-11%); inpatient LOS increased from 1.92 to 2.05, 7% (16%); outpatient LOS increased from 0.92 to 0.93, 1% (-12%); discharge home increased from 82% to 91%, 12.8% (11%); and CMS spending decreased from $1,033 million to $751 million, -27% (-27%). CONCLUSION: Medicare payments, LOS, discharge to facilities, and volume declined from 2019 to 2020 and were accelerated by IPO list changes and COVID-19 issues. Same-day discharge and hospital outpatient department cases also increased. THA metrics were not affected by race.


Subject(s)
Arthroplasty, Replacement, Hip , COVID-19 , Aged , Benchmarking , COVID-19/epidemiology , Humans , Length of Stay , Medicaid , Medicare , Pandemics , Patient Discharge , Patient Readmission , Retrospective Studies , United States/epidemiology
12.
J Comput Biol ; 29(5): 453-464, 2022 May.
Article in English | MEDLINE | ID: covidwho-1758600

ABSTRACT

In this work, we investigate using Fourier coefficients (FCs) for capturing useful information about viral sequences in a computationally efficient and compact manner. Specifically, we extract geographic submission location from SARS-CoV-2 sequence headers submitted to the GISAID Initiative, calculate corresponding FCs, and use the FCs to classify these sequences according to geographic location. We show that the FCs serve as useful numerical summaries for sequences that allow manipulation, identification, and differentiation via classical mathematical and statistical methods that are not readily applicable for character strings. Further, we argue that subsets of the FCs may be usable for the same purposes, which results in a reduction in storage requirements. We conclude by offering extensions of the research and potential future directions for subsequent analyses, such as the use of other series transforms for discreetly indexed signals such as genomes.


Subject(s)
COVID-19 , SARS-CoV-2 , Benchmarking , Genome, Viral , Humans , Phylogeny , SARS-CoV-2/genetics
13.
J Stroke Cerebrovasc Dis ; 31(5): 106315, 2022 May.
Article in English | MEDLINE | ID: covidwho-1747727

ABSTRACT

BACKGROUND: During the first wave of the pandemic, stroke care suffered globally and there were reduced stroke admissions and delays in time metrics. Stroke care was reorganized during the second wave learning from the experience of previous wave. This study shares our experience in stroke time metrics during the second wave of pandemic compared to the first wave. METHODS: We did a single-center prospective study, where consecutive acute ischemic stroke patients within 24 hours of the onset of symptoms and aged more than 18 years, who presented to Stroke Unit, Department of Neurology, Government Medical College, Thiruvananthapuram from June 1st to 31st August, 2020 and June 1st to 31st August in 2021 were included. In-hospital time metrics (door to CT time and door to Needle time) were compared during the two time periods. We also compared functional outcomes at discharge and in-hospital mortality during the two periods. Functional outcome at discharge was assessed by modified Rankin scale (mRS). RESULTS: From June to August 2021 (second wave of the COVID 19 pandemic), compared to the same months during the first wave (2020), our study demonstrated better in-hospital time metrics (door to CT time and door to needle time). We also found lower admission systolic blood pressure and higher baseline CT early ischemic changes during the second wave. There was no difference in functional outcome at discharge and in-hospital mortality. Intravenous thrombolysis rates also remained the same during the two periods. CONCLUSION: Our study has confirmed that time metrics in stroke care can be improved through system rearrangement even during the pandemic. Acute stroke treatments are time-dependent and hospital administrators must stick to the maxim "Time is Brain" while restructuring stroke workflows during future challenges.


Subject(s)
Brain Ischemia , COVID-19 , Ischemic Stroke , Stroke , Benchmarking , Brain Ischemia/diagnosis , Brain Ischemia/epidemiology , Brain Ischemia/therapy , Humans , Ischemic Stroke/diagnosis , Ischemic Stroke/epidemiology , Ischemic Stroke/therapy , Prospective Studies , Stroke/diagnosis , Stroke/epidemiology , Stroke/therapy , Tertiary Care Centers , Thrombolytic Therapy , Time-to-Treatment , Treatment Outcome
15.
Brief Bioinform ; 23(2)2022 03 10.
Article in English | MEDLINE | ID: covidwho-1704326

ABSTRACT

Protein lysine crotonylation (Kcr) is an important type of posttranslational modification that is associated with a wide range of biological processes. The identification of Kcr sites is critical to better understanding their functional mechanisms. However, the existing experimental techniques for detecting Kcr sites are cost-ineffective, to a great need for new computational methods to address this problem. We here describe Adapt-Kcr, an advanced deep learning model that utilizes adaptive embedding and is based on a convolutional neural network together with a bidirectional long short-term memory network and attention architecture. On the independent testing set, Adapt-Kcr outperformed the current state-of-the-art Kcr prediction model, with an improvement of 3.2% in accuracy and 1.9% in the area under the receiver operating characteristic curve. Compared to other Kcr models, Adapt-Kcr additionally had a more robust ability to distinguish between crotonylation and other lysine modifications. Another model (Adapt-ST) was trained to predict phosphorylation sites in SARS-CoV-2, and outperformed the equivalent state-of-the-art phosphorylation site prediction model. These results indicate that self-adaptive embedding features perform better than handcrafted features in capturing discriminative information; when used in attention architecture, this could be an effective way of identifying protein Kcr sites. Together, our Adapt framework (including learning embedding features and attention architecture) has a strong potential for prediction of other protein posttranslational modification sites.


Subject(s)
Computational Biology , Deep Learning , Lysine/metabolism , Protein Processing, Post-Translational , Software , Algorithms , Benchmarking , Computational Biology/methods , Computational Biology/standards , Databases, Factual , Neural Networks, Computer , Phosphorylation , ROC Curve , Reproducibility of Results , User-Computer Interface
16.
World Neurosurg ; 161: e495-e499, 2022 May.
Article in English | MEDLINE | ID: covidwho-1692807

ABSTRACT

INTRODUCTION: COVID-19 has accelerated the use of telemedicine in all aspects of health care delivery, including initial surgical evaluation. No existing literature investigates the safety and efficacy of telemedicine to preoperatively evaluate spine surgery candidates. Our objectives were: (1) Compare the change in visual analogue scale (VAS) scores between the telemedicine preoperative visit and in-person preoperative visit groups. (2) Compare the average surgical time, estimated blood loss (EBL), length of hospital stay (LOS), rates of intraoperative complications, rates of readmission, and rates of reoperation between the telemedicine preoperative visit and in-person preoperative visit groups. METHODS: The previously stated metrics were collected for 276 patients, 138 who were exclusively evaluated preoperatively with telemedicine and 138 historical controls who were evaluated preoperatively in person. We used χ2 and independent samples t tests to determine significance. RESULTS: There were no significant differences in the mean change in VAS scores (-2.7 ± 3.1 telemedicine vs. -2.2 ± 3.7 in-person, P = 0.317), mean percentage change in VAS scores (-40.5% ± 54.3% vs. -39.5% ± 66.6%, P = 0.811), mean surgical time (2.4 ± 1.4 hours vs. 2.3 ± 1.3 ours, P = 0.527), mean EBL (150.4 ± 173.3 mL vs. 156.7 ± 255.0 mL, P = 0.811), mean LOS (3.3 ± 2.4 days vs. 3.3 ± 2.5 days, P = 0.954), intraoperative complication rates (0.7% vs. 1.4%, P = 0.558), reoperation rates (7.9% vs. 4.3%, P = 0.208), or readmission rates (10.1% vs. 5.1%, P = 0.091) between the telemedicine preoperative visit and in-person preoperative visit groups. CONCLUSIONS: Preoperative evaluation via telemedicine leads to the same short-term surgical outcomes as in-person evaluation with no increased risk of surgical complications.


Subject(s)
COVID-19 , Telemedicine , Benchmarking , COVID-19/epidemiology , Humans , Intraoperative Complications , Length of Stay
17.
J Proteome Res ; 20(12): 5227-5240, 2021 12 03.
Article in English | MEDLINE | ID: covidwho-1683909

ABSTRACT

The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.


Subject(s)
Benchmarking , Proteome , Databases, Protein , Humans , Mass Spectrometry/methods , Proteome/analysis , Proteome/genetics , Proteomics/methods
18.
Am J Health Syst Pharm ; 79(11): 904-908, 2022 05 24.
Article in English | MEDLINE | ID: covidwho-1684521

ABSTRACT

PURPOSE: Because of rising concern about coronavirus disease 2019 transmission, there has been a large shift from face-to-face, in-office visits to a virtual care model. The purpose of this article is to explain how Ascension Florida Gulf Coast was able to maximize the utility of ambulatory care pharmacists (ACPs) in the primary care setting during the pandemic and to provide guidance for creating a sustainable billing and practice model in the event of another global health crisis. SUMMARY: By employing telehealth services, our ACPs were able to continue to co-manage chronic disease states for documented diagnoses while still maintaining health-system revenue in the midst of a global health crisis. Utilizing various virtual platforms, ACPs were able to accommodate the needs of our patients while addressing concerns related to the compatibility and user friendliness of the platforms for our diverse patient population. ACPs used traditional incident-to evaluation and management services current procedural terminology billing codes with a virtual visit modifier for billing and tracking purposes. CONCLUSION: Utilizing various virtual care platforms, our ACPs completed 447 patient encounters within the first 7 months of the pandemic. During this time, our ACPs addressed various population health metrics, specifically for patients diagnosed with diabetes without an active claim for a cholesterol-lowering medication, in addition to performing chronic disease management. Our ACPs had a 23% success rate for statin initiation in patients reviewed and contacted. By adopting virtual care options, our ACPs were able to effectively co-manage and educate patients while improving quality metrics and generating $50,662.24 in billable encounters for the health system during a global health crisis. The addition of ACP virtual encounters to primary care clinics both increases access to healthcare and improves patient care quality and outcomes while limiting revenue losses in our local health system.


Subject(s)
COVID-19 , Telemedicine , Benchmarking , Chronic Disease , Humans , Pandemics , Pharmacists
19.
Int J Health Serv ; 52(2): 212-224, 2022 04.
Article in English | MEDLINE | ID: covidwho-1673675

ABSTRACT

Nursing homes faced serious challenges with large COVID-19 resident infection rates and deaths during the pandemic. This descriptive case study examined the structure, operations, strategies, care outcomes, and owners of The Ensign Group Inc. the second largest U.S. for-profit chain, between 2007 and 2021. Ensign, as a holding company, has a complex organizational structure that uses more than 430 corporate entities to manage its 228 nursing homes and senior living facilities. With mostly Medicare and Medicaid revenues and favorable government COVID-19 relief, Ensign grew rapidly, even during the pandemic, to $2.5 billion (all amounts in U.S. Dollars) in revenues with a market capitalization of $4.5 billion and strong profits and financial metrics in 2020 to 2021. The company used real estate purchasing, debt financing, and spin-off companies, and tax arbitrage to optimize shareholder value. Before and during the pandemic, its 198 nursing homes had low registered nurse and total nurse staffing levels and regulatory violations with below-average ratings, and they had high COVID-19 infection rates during the pandemic. Ensign's small board, executives, and institutional investors protected and enhanced shareholder interests rather than ensuring that its nursing homes met professional standards and regulatory requirements.


Subject(s)
COVID-19 , Aged , Benchmarking , COVID-19/epidemiology , Humans , Medicare , Nursing Homes , SARS-CoV-2 , United States/epidemiology
20.
Water Res ; 212: 118070, 2022 Apr 01.
Article in English | MEDLINE | ID: covidwho-1621092

ABSTRACT

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.


Subject(s)
COVID-19 , Pandemics , Benchmarking , Humans , RNA, Viral , SARS-CoV-2 , Waste Water , Wastewater-Based Epidemiological Monitoring
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