scholarly journals COVID-19 patient accounts of illness severity, treatments and lasting symptoms

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Moriah E. Thomason ◽  
Denise Werchan ◽  
Cassandra L. Hendrix
Keyword(s):  
Public Health ◽  
Social Stress ◽  
Contextual Information ◽  
Patients Âgés ◽  
Patient Reports ◽  
Health History ◽  
Patient Reported ◽  
Novel Coronavirus ◽  
Reported Data ◽  
Survey Responses

AbstractFirst-person accounts of COVID-19 illness and treatment can complement and enrich data derived from electronic medical or public health records. With patient-reported data, it is uniquely possible to ascertain in-depth contextual information as well as behavioral and emotional responses to illness. The Novel Coronavirus Illness Patient Report (NCIPR) dataset includes complete survey responses from 1,584 confirmed COVID-19 patients ages 18 to 98. NCIPR survey questions address symptoms, medical complications, home and hospital treatments, lasting effects, anxiety about illness, employment impacts, quarantine behaviors, vaccine-related behaviors and effects, and illness of other family/household members. Additional questions address financial security, perceived discrimination, pandemic impacts (relationship, social, stress, sleep), health history, and coping strategies. Detailed patient reports of illness, environment, and psychosocial impact, proximal to timing of infection and considerate of demographic variation, is meaningful for understanding pandemic-related public health from the perspective of those that contracted the disease.

scholarly journals COVID-19 patient accounts of illness severity, treatments and lasting symptoms

2021 ◽  
Author(s):  
Moriah Thomason ◽  
Denise Werchan ◽  
Cassandra Hendrix
Keyword(s):  
Public Health ◽  
Social Stress ◽  
Contextual Information ◽  
Patients Âgés ◽  
Patient Reports ◽  
Health History ◽  
Patient Reported ◽  
Novel Coronavirus ◽  
Reported Data ◽  
Survey Responses

First-person accounts of COVID-19 illness and treatment complement and enrich data derived from electronic medical or public health records. With patient-reported data, it is uniquely possible to ascertain in-depth contextual information as well as behavioral and emotional responses to illness. The Novel Coronavirus Illness Patient Report (NCIPR) dataset includes complete survey responses from 1,592 confirmed COVID-19 patients ages 18 to 98. NCIPR survey questions address symptoms, medical complications, home and hospital treatments, lasting effects, anxiety about illness, employment impacts, quarantine behaviors, vaccine-related behaviors and effects, and illness of other family/household members. Additional questions address financial security, perceived discrimination, pandemic impacts (relationship, social, stress, sleep), health history, and coping strategies. Detailed patient reports of illness, environment, and psychosocial impact, proximal to timing of infection and considerate of demographic variation, is meaningful for understanding pandemic-related public health from the perspective of those that contracted the disease.

scholarly journals The early scientific literature response to the novel Coronavirus outbreak: who published what?

2020 ◽  
Author(s):  
Davide Gori ◽  
Erik Boetto ◽  
Maria Pia Fantini
Keyword(s):  
Public Health ◽  
Scientific Literature ◽  
Health Concern ◽  
Primary Data ◽  
The Novel ◽  
Epidemic Outbreak ◽  
Emerging Pathogens ◽  
Pubmed Database ◽  
Novel Coronavirus ◽  
Reported Data

AbstractIntroductionRecent events highlight how emerging and re-emerging pathogens are becoming global challenges for public health. In December 2019, a novel coronavirus has emerged. This has suddenly turned out into global health concern.ObjectivesAim of this research is to focus on the bibliometric aspects in order to measure what is published in the first 30-days of a global epidemic outbreakMethodsWe searched PubMed database in order to find all relevant studies in the first 30-days from the first publication.ResultsFrom the initial 442 identified articles, 234 were read in-extenso. The majority of papers come from China, UK and USA. 63.7% of the papers were commentaries, editorials and reported data and only 17.5% of the sources used data directly collected on the field. Topics mainly addressed were “epidemiology”, “preparedness” and “generic discussion”. NNR showed a reduction for both the objectives assessed from January to February.Conclusions“Diagnosis” and effective preventive and therapeutic measures were the fields in which more research is still needed. The vast majority of scientific literature in the first 30-days of an epidemic outbreak is based on reported data rather than primary data. Nevertheless, the scientific statements and public health decisions rely on these data.Strengths of our studyThis is the first bibliometric research in Pubmed Database on the first 30 days of publications regarding the novel Coronavirus (SARS-nCoV-2) outbreak of 2019.The vast majority of publication in the first 30-days of an epidemic outbreak are reported data or comments, and only a small fraction of the papers have directly collected data.Limitations of our studyOur research is only PubMed based. It ill be auspicable to consult more than one relevant database in future papers.In addition, we excluded non-English publications leading to a potential bias due to the fact that the outbreak started in China.

scholarly journals Research on COVID-19 through patient-reported data: a survey for observational studies in the COVID-19 pandemic

2020 ◽  
pp. 1-5
Author(s):  
Shefali Setia Verma ◽  
Wendy K. Chung ◽  
Scott Dudek ◽  
Jennifer L. Williamson ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Observational Studies ◽  
Scientific Community ◽  
Patient Survey ◽  
Host Factors ◽  
Health Records ◽  
Patient Reports ◽  
Clinical Investigations ◽  
Patient Reported ◽  
Testing Site ◽  
Reported Data

Abstract Understanding the clinical risk factors for COVID-19 disease severity and outcomes requires a combination of data from electronic health records and patient reports. To facilitate the collection of patient-reported data, as well as accelerate and standardize the collection of data about host factors, we have constructed a COVID-19 survey. This survey is freely available to the scientific community to send electronically for patients to complete online. This patient survey is designed to be comprehensive, yet not overly burdensome, to gather data useful for a range of clinical investigations, and to accommodate a wide variety of implementation settings including at a COVID-19 testing site, at home during infection or after recovery, and/or for individuals while they are hospitalized. A widely adopted standardized survey that can be implemented online with minimal resources can serve as a critical tool for combining and comparing data across studies to improve our understanding of COVID-19 disease.

scholarly journals Patient Reports of Night Noise in Hospitals Are Associated With Unplanned Readmissions Among Older Adults

2020 ◽  
Vol 7 (6) ◽  
pp. 1425-1431
Author(s):  
Kyle A Kemp ◽  
Hude Quan ◽  
Paul Fairie ◽  
Maria J Santana
Keyword(s):  
Chronic Conditions ◽  
Hospital Readmissions ◽  
Unplanned Readmission ◽  
Discharge Abstract Database ◽  
Cross Sectional ◽  
Survey Question ◽  
Patient Reports ◽  
Patient Reported ◽  
Survey Responses ◽  
Discharge From Hospital

Objective: Sleep disturbance is a key contributor to posthospital syndrome; a transient period of vulnerability following discharge from hospital. We sought to examine the relationship between patient-reported hospital quietness at night, via a validated survey, and unplanned hospital readmissions among hospitalized seniors (ages 65 and older) in Alberta, Canada. Design: Retrospective, cross-sectional analysis of survey responses, linked with administrative inpatient records. Setting: Using the Canadian Patient Experiences Survey—Inpatient Care and Discharge Abstract Database, patients aged 65 and older, and living with one or more chronic conditions were identified. Participants: Of all, 25 674 respondents discharged from hospital between April 2014 and December 2017. Main Outcome Measure: All-cause, unplanned readmission within 30 or 90 days (yes vs no). Results: Approximately half (50.5%) of the respondents reported that the area around their room was always quiet at night. Eight (8.1%) percent of respondents (2066) were readmitted within 30 days (2241 total readmissions), while 15.6% (4000) were readmitted within 90 days (5070 total readmissions). When controlling for a variety of demographic and clinical factors, patients not reporting “always” to the survey question regarding hospital quietness at night had slightly greater odds of readmission within 30 (adjusted odds ratio [aOR] = 1.32, 95% confidence interval [CI]: 1.20-1.45) and 90 days (aOR = 1.14, 95% CI: 1.06-1.23). Conclusion: Our results demonstrate a clear association between patient-reported hospital quietness at night and subsequent readmission within the first 30 and 90 days following discharge. Efforts to minimize hospital noise, particularly at night, may help promote a restful environment, while reducing readmissions among older patients living with chronic conditions.

scholarly journals What does the patient have to say? Valuing the patient experience to improve the patient journey

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Raffaella Gualandi ◽  
Cristina Masella ◽  
Michela Piredda ◽  
Matteo Ercoli ◽  
Daniela Tartaglini
Keyword(s):  
Patient Experience ◽  
University Hospital ◽  
Hospital Patient ◽  
Patient Journey ◽  
Patient Reports ◽  
Patient Reported ◽  
Improve Hospital ◽  
Potential Improvement ◽  
Reported Data ◽  
Clinical Conditions

Abstract Background Patient-reported data—satisfaction, preferences, outcomes and experience—are increasingly studied to provide excellent patient-centred care. In particular, healthcare professionals need to understand whether and how patient experience data can more pertinently inform the design of service delivery from a patient-centred perspective when compared with other indicators. This study aims to explore whether timely patient-reported data could capture relevant issues to improve the hospital patient journey. Methods Between January and February 2019, a longitudinal survey was conducted in the orthopaedics department of a 250-bed Italian university hospital with patients admitted for surgery; the aim was to analyse the patient journey from the first outpatient visit to discharge. The same patients completed a paper-and-pencil questionnaire, which was created to collect timely preference, experience and main outcomes data, and the hospital patient satisfaction questionnaire. The first was completed at the time of admission to the hospital and at the end of hospitalisation, and the second questionnaire was completed at the end of hospitalisation. Results A total of 254 patients completed the three questionnaires. The results show the specific value of patient-reported data. Greater or less negative satisfaction may not reveal pathology-related needs, but patient experience data can detect important areas of improvement along the hospital journey. As clinical conditions and the context of care change rapidly within a single hospital stay for surgery, collecting data at two different moments of the patient journey enables researchers to capture areas of potential improvement in the patient journey that are linked to the context, clinical conditions and emotions experienced by the patient. Conclusion By contributing to the literature on how patient-reported data could be collected and used in hospital quality improvement, this study opens the debate about the use of real-time focused data. Further studies should explore how to use patient-reported data effectively (including what the patient reports are working well) and how to improve hospital processes by profiling patients’ needs and defining the appropriate methodologies to capture the experiences of vulnerable patients. These topics may offer new frontiers of research to achieve a patient-centred healthcare system.

Ergebnisse der COVID-19-Umfrage der Deutschen Gesellschaft für Rehabilitationswissenschaften e.V. (DGRW)

2020 ◽  
Vol 59 (05) ◽  
pp. 315-317
Author(s):  
Thorsten Meyer ◽  
Elain Posthumus ◽  
Keyword(s):  
Public Health ◽  
Global Literature ◽  
Novel Coronavirus

Hintergrund und ZielCOVID-19 stellt eine substanzielle Bedrohung der Gesundheit und in der Folge auch der Lebensbedingungen der Menschen weltweit dar. Die Erkrankung entsteht infolge einer Infektion mit dem neuartigen Coronavirus SARS-CoV-2. Erkenntnisse über molekulare Grundlagen, Pathophysiologie, klinische Charakteristika, Epidemiologie, aber auch Ressourcenbedarf und Outcomes (z. B. Karagiannidis et al. 2020; zur Übersicht s. Website der WHO: https://search.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/) wachsen in beispiellos kurzem Zeitraum weltweit an, auch im Feld der Rehabilitation (vgl. Negrini et al. 2020). Die Erkenntnisse münden in Leitlinien, Policy Briefs oder konkreten Handlungsempfehlungen (vgl. Publikationen des Kompetenznetz Public Health COVID-19, www.public-health-covid19.de).

Application of Inherent Risk of Contagion (IRC) framework & modelling to aid local Covid-19 response & mitigation: Viewpoint (Preprint)

2020 ◽  
Author(s):  
Helmi Zakariah ◽  
Fadzilah bt Kamaluddin ◽  
Choo-Yee Ting ◽  
Hui-Jia Yee ◽  
Shereen Allaham ◽  
...  
Keyword(s):  
Public Health ◽  
Public Health Problem ◽  
Analytical Framework ◽  
Vulnerable Population ◽  
Contact Tracing ◽  
Global Public Health ◽  
Inherent Risk ◽  
Transmission Area ◽  
Current Outbreak ◽  
Novel Coronavirus

UNSTRUCTURED The current outbreak of coronavirus disease 2019 (COVID-19) caused by the novel coronavirus named SARS-CoV-2 has been a major global public health problem threatening many countries and territories. Mathematical modelling is one of the non-pharmaceutical public health measures that plays a crucial role for mitigating the risk and impact of the pandemic. A group of researchers and epidemiologists have developed a machine learning-powered inherent risk of contagion (IRC) analytical framework to georeference the COVID-19 with an operational platform to plan response & execute mitigation activities. This framework dataset provides a coherent picture to track and predict the COVID-19 epidemic post lockdown by piecing together preliminary data on publicly available health statistic metrics alongside the area of reported cases, drivers, vulnerable population, and number of premises that are suspected to become a transmission area between drivers and vulnerable population. The main aim of this new analytical framework is to measure the IRC and provide georeferenced data to protect the health system, aid contact tracing, and prioritise the vulnerable.

scholarly journals P89 Patient reported comorbidity is not a reliable data source: a systematic review of the literature

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
Chung Mun Alice Lin ◽  
Alexander Orman ◽  
Nicholas D Clement ◽  
David J Deehan ◽  
Chung M A Lin
Keyword(s):  
Medical Record ◽  
Meta Analysis ◽  
Analysis Data ◽  
Fundamental Factor ◽  
Resource Limitations ◽  
Patient Reported ◽  
Data Source ◽  
Reported Data ◽  
Operative Assessment ◽  
Source Of Information

Abstract Introduction There is currently an increased demand for elective orthopaedic surgery. However, due to the ever-growing financial, time and resource limitations, there is a pressing need to identify those who would benefit most from surgery but with the lowest risk of complications. Comorbidities are a fundamental factor in this decision and the traditional way to ascertain this is through medical record data abstraction during pre-operative assessment. However, this can be time consuming and expensive. We therefore set out to establish whether patient reported comorbidities are reliable as a principal source of information. Method Searches were performed on PubMed and Medline, and citations independently screened. Included studies were published between 2010 to 2020 assessing the reliability of at least one patient reported comorbidity against their medical record or clinical assessment as gold standard. Cohen’s kappa coefficient values were grouped into systems and a meta-analysis performed comparing the reliability between studies. Results Meta-analysis data showed poor-to-moderate reliability for diseases in cardiovascular, musculoskeletal, neurological and respiratory systems as well as for malignancy and depression. Endocrine diseases showed good-to-excellent reliability. Factors found to affect the concordance included sex, age, ethnicity, education, living alone, marital status, number or severity of comorbidities, mental health and disability. Conclusion Our study showed poor-to-moderate reliability for all systems except endocrine, consisting of thyroid disease and diabetes mellitus, which demonstrated good-to-excellent reliability. Although patient reported data is useful and can facilitate a complete pre-operative overview of the patient, it is not reliable enough to be used as a standalone measure.

scholarly journals What is the optimal outcome after endoscopic sinus surgery in the treatment of chronic rhinosinusitis? A consultation of Canadian experts

2021 ◽  
Vol 50 (1) ◽  
Author(s):  
Nadim Saydy ◽  
Sami P. Moubayed ◽  
Marie Bussières ◽  
Arif Janjua ◽  
Shaun Kilty ◽  
...  
Keyword(s):  
Chronic Rhinosinusitis ◽  
Endoscopic Sinus Surgery ◽  
Patient Reported Outcome ◽  
Sinus Surgery ◽  
Structured Interviews ◽  
Subjective Data ◽  
Operative Outcomes ◽  
Patient Reported ◽  
Definition Of Success ◽  
Reported Data

Abstract Objectives Many experts feel that in the absence of well-defined goals for success, they have an easier time identifying failure. As success ought to not be defined only by absence of failure, we aimed to define optimal outcomes for endoscopic sinus surgery (ESS) in chronic rhinosinusitis (CRS) by obtaining expert surgeon perspectives. Methods A total of 12 surgeons participated in this targeted consultation. Face to face semi-structured interviews were performed with expert surgeons in the field of CRS and ESS. General impressions and personal definitions of acceptable operative success and optimal operative outcomes were compiled and summarized. Results According to an expert survey, patients’ main objectives are an improvement in their chief complain, a general improvement in quality of life (QoL), and a better overall symptomatic control. The most important aspects of endoscopy for defining a successful intervention were an adequate mucus circulation, a healthy mucosa, minimal edema, and patency of all explored cavities or ostia. In the assessment of surgical outcomes, it was determined that both objective and patient reported data must be carefully examined, with more attention given to subjective outcomes. Conclusions According to data gathered from a Canadian expert consultation, a definition of success must be based on both subjective data and nasal endoscopy. We propose to define an acceptable outcome as either a subjective improvement of at least the minimal clinically improvement difference of a validated patient reported outcome questionnaire, along with a satisfactory endoscopic result (1) or a complete subjective resolution with a sub-optimal endoscopy (2). Graphical abstract

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