scholarly journals A systematic review identifying common data items in neonatal trials and assessing their completeness in routinely recorded United Kingdom national neonatal data

2019 ◽  
Author(s):  
Sena Jawad ◽  
Neena Modi ◽  
A Toby Prevost ◽  
Chris Gale
Keyword(s):  
Clinical Trials ◽  
United Kingdom ◽  
High Impact ◽  
Research Database ◽  
Electronic Patient Records ◽  
Registration Number ◽  
Recorded Data ◽  
Using Data ◽  
Common Items ◽  
High Level

Abstract Background We aimed to test whether a common set of key data items reported across high impact neonatal clinical trials could be identified, and to quantify their completeness in routinely recorded United Kingdom neonatal data held in the National Neonatal Research Database (NNRD). Methods We systematically reviewed neonatal clinical trials published in four high impact medical journals over 10 years (2006-2015) and extracted baseline characteristics, stratification items, and potential confounders used to adjust primary outcomes. Completeness was examined using data held in the NNRD for identified data items, for infants admitted to neonatal units in 2015. The NNRD is a repository of routinely recorded data extracted from neonatal Electronic Patient Records (EPR) of all admissions to National Health Service (NHS) Neonatal Units in England, Wales and Scotland. We defined missing data as an empty field or an implausible value. We reported common data items as frequencies and percentages alongside percentages of completeness. Results We identified 44 studies involving 32,095 infants and 126 data items. Fourteen data items were reported by more than 20% of studies. Gestational age (95%), sex (93%) and birth weight (91%) were the most common baseline data items. The completeness of data in the NNRD was high for these data with greater than 90% completeness found for 9 of the 14 most common items. Conclusion High impact neonatal clinical trials share common data items. In the United Kingdom, these items can be obtained at a high level of completeness from routinely recorded data held in the NNRD. The feasibility and efficiency using routinely recorded EPR data, such as that held in the NNRD, for clinical trials, rather than collecting these items anew, should be examined. Registration PROSPERO registration number CRD42016046138, registered prospectively 17 th August 2016

scholarly journals A systematic review identifying common data items in neonatal trials and assessing their completeness in routinely recorded United Kingdom national neonatal data

Trials ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Sena Jawad ◽  
Neena Modi ◽  
A. Toby Prevost ◽  
Chris Gale
Keyword(s):  
Clinical Trials ◽  
United Kingdom ◽  
High Impact ◽  
Research Database ◽  
Electronic Patient Records ◽  
Registration Number ◽  
Recorded Data ◽  
Using Data ◽  
Common Items ◽  
High Level

Abstract Background We aimed to test whether a common set of key data items reported across high-impact neonatal clinical trials could be identified, and to quantify their completeness in routinely recorded United Kingdom neonatal data held in the National Neonatal Research Database (NNRD). Methods We systematically reviewed neonatal clinical trials published in four high-impact medical journals over 10 years (2006–2015) and extracted baseline characteristics, stratification items and potential confounders used to adjust primary outcomes. Completeness was examined using data held in the NNRD for identified data items, for infants admitted to neonatal units in 2015. The NNRD is a repository of routinely recorded data extracted from neonatal Electronic Patient Records (EPR) of all admissions to National Health Service (NHS) Neonatal Units in England, Wales and Scotland. We defined missing data as an empty field or an implausible value. We reported common data items as frequencies and percentages alongside percentages of completeness. Results We identified 44 studies involving 32,095 infants and 126 data items. Fourteen data items were reported by more than 20% of studies. Gestational age (95%), sex (93%) and birth weight (91%) were the most common baseline data items. The completeness of data in the NNRD was high for these data with greater than 90% completeness found for 9 of the 14 most common items. Conclusion High-impact neonatal clinical trials share common data items. In the United Kingdom, these items can be obtained at a high level of completeness from routinely recorded data held in the NNRD. The feasibility and efficiency using routinely recorded EPR data, such as that held in the NNRD, for clinical trials, rather than collecting these items anew, should be examined. Trial registration PROSPERO registration number CRD42016046138. Registered prospectively on 17 August 2016.

scholarly journals A systematic review identifying common data items in neonatal trials and assessing their completeness in routinely recorded United Kingdom national neonatal data

2019 ◽  
Author(s):  
Sena Jawad ◽  
Neena Modi ◽  
A Toby Prevost ◽  
Chris Gale
Keyword(s):  
Clinical Trials ◽  
United Kingdom ◽  
High Impact ◽  
Research Database ◽  
Electronic Patient Records ◽  
Registration Number ◽  
Recorded Data ◽  
Using Data ◽  
Common Items ◽  
High Level

Abstract Background We aimed to test whether a common set of key data items reported across high impact neonatal clinical trials could be identified, and to quantify their completeness in routinely recorded United Kingdom neonatal data held in the National Neonatal Research Database (NNRD). Methods We systematically reviewed neonatal clinical trials published in four high impact medical journals over 10 years (2006-2015) and extracted baseline characteristics, stratification items, and potential confounders used to adjust primary outcomes. Completeness was examined using data held in the NNRD for identified data items, for infants admitted to neonatal units in 2015. The NNRD is a repository of routinely recorded data extracted from neonatal Electronic Patient Records (EPR) of all admissions to National Health Service (NHS) Neonatal Units in England, Wales and Scotland. We defined missing data as an empty field or an implausible value. We reported common data items as frequencies and percentages alongside percentages of completeness. Results We identified 44 studies involving 32,095 infants and 126 data items. Fourteen data items were reported by more than 20% of studies. Gestational age (95%), sex (93%) and birth weight (91%) were the most common baseline data items. The completeness of data in the NNRD was high for these data with greater than 90% completeness found for 9 of the 14 most common items. Conclusion High impact neonatal clinical trials share common data items. In the United Kingdom, these items can be obtained at a high level of completeness from routinely recorded data held in the NNRD. The feasibility and efficiency using routinely recorded EPR data, such as that held in the NNRD, for clinical trials, rather than collecting these items anew, should be examined. Registration PROSPERO registration number CRD42016046138, registered prospectively 17 th August 2016

scholarly journals A systematic review identifying common data items in neonatal trials and assessing their completeness in routinely recorded United Kingdom national neonatal data

2019 ◽  
Author(s):  
Sena Jawad ◽  
Neena Modi ◽  
A Toby Prevost ◽  
Chris Gale
Keyword(s):  
Clinical Trials ◽  
United Kingdom ◽  
High Impact ◽  
Research Database ◽  
Electronic Patient Records ◽  
Registration Number ◽  
Recorded Data ◽  
Using Data ◽  
Common Items ◽  
High Level

Abstract Background We aimed to test whether a common set of key data items reported across high impact neonatal clinical trials could be identified, and to quantify their completeness in routinely recorded United Kingdom neonatal data held in the National Neonatal Research Database (NNRD). Methods We systematically reviewed neonatal clinical trials published in four high impact medical journals over 10 years (2006-2015) and extracted baseline characteristics, stratification items, and potential confounders used to adjust primary outcomes. Completeness was examined using data held in the NNRD for identified data items, for infants admitted to neonatal units in 2015. The NNRD is a repository of routinely recorded data extracted from neonatal Electronic Patient Records (EPR) of all admissions to National Health Service (NHS) Neonatal Units in England, Wales and Scotland. We defined missing data as an empty field or an implausible value. We reported common data items as frequencies and percentages alongside percentages of completeness. Results We identified 44 studies involving 32,095 infants and 126 data items. Fourteen data items were reported by more than 20% of studies. Gestational age (95%), sex (93%) and birth weight (91%) were the most common baseline data items. The completeness of data in the NNRD was high for these data with greater than 90% completeness found for 9 of the 14 most common items. Conclusion High impact neonatal clinical trials share common data items. In the United Kingdom, these items can be obtained at a high level of completeness from routinely recorded data held in the NNRD. The efficiency of neonatal clinical trials could be increased by using high quality, routinely recorded EPR data such as that held in the NNRD rather than collecting these items anew. Registration PROSPERO registration number CRD42016046138, registered prospectively 17th August 2016

scholarly journals Interventions to Ameliorate the Psychosocial Effects of the COVID-19 Pandemic on Children—A Systematic Review

2021 ◽  
Vol 18 (5) ◽  
pp. 2361
Author(s):  
Katharina Boldt ◽  
Michaela Coenen ◽  
Ani Movsisyan ◽  
Stephan Voss ◽  
Eva Rehfuess ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trials ◽  
Health Management ◽  
Psychosocial Interventions ◽  
Well Being ◽  
World Health ◽  
Research Database ◽  
Psychosocial Effects ◽  
Global Database ◽  
Study Protocols

The aim of this study was to identify interventions targeting children and their caregivers to reduce psychosocial problems in the course of the COVID-19 pandemic and comparable outbreaks. The review was performed using systematic literature searches in MEDLINE, Embase, PsycINFO and COVID-19-specific databases, including the CDC COVID-19 Research Database, the World Health Organisation (WHO) Global Database on COVID-19 Research and the Cochrane COVID-19 Study Register, ClinicalTrials.gov, the EU Clinical Trials Register and the German Clinical Trials Register (DRKS) up to 25th September 2020. The search yielded 6657 unique citations. After title/abstract and full text screening, 11 study protocols reporting on trials planned in China, the US, Canada, the UK, and Hungary during the COVID-19 pandemic were included. Four interventions targeted children ≥10 years directly, seven system-based interventions targeted the parents and caregivers of younger children and adolescents. Outcome measures encompassed mainly anxiety and depressive symptoms, different dimensions of stress or psychosocial well-being, and quality of supportive relationships. In conclusion, this systematic review revealed a paucity of studies on psychosocial interventions for children during the COVID-19 pandemic. Further research should be encouraged in light of the expected demand for child mental health management.

scholarly journals Risk factors for severity on admission and the disease progression during hospitalisation in a large cohort of patients with COVID-19 in Japan

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e047007
Author(s):  
Mari Terada ◽  
Hiroshi Ohtsu ◽  
Sho Saito ◽  
Kayoko Hayakawa ◽  
Shinya Tsuzuki ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mechanical Ventilation ◽  
Chronic Respiratory Disease ◽  
Major Effect ◽  
Secondary Outcome ◽  
Healthcare Facilities ◽  
Wide Range ◽  
Registration Number ◽  
Using Data ◽  
Obesity Hypertension

ObjectivesTo investigate the risk factors contributing to severity on admission. Additionally, risk factors of worst severity and fatality were studied. Moreover, factors were compared based on three points: early severity, worst severity and fatality.DesignAn observational cohort study using data entered in a Japan nationwide COVID-19 inpatient registry, COVIREGI-JP.SettingAs of 28 September 2020, 10480 cases from 802 facilities have been registered. Participating facilities cover a wide range of hospitals where patients with COVID-19 are admitted in Japan.ParticipantsParticipants who had a positive test result on any applicable SARS-CoV-2 diagnostic tests were admitted to participating healthcare facilities. A total of 3829 cases were identified from 16 January to 31 May 2020, of which 3376 cases were included in this study.Primary and secondary outcome measuresPrimary outcome was severe or nonsevere on admission, determined by the requirement of mechanical ventilation or oxygen therapy, SpO2 or respiratory rate. Secondary outcome was the worst severity during hospitalisation, judged by the requirement of oxygen and/orinvasive mechanical ventilation/extracorporeal membrane oxygenation.ResultsRisk factors for severity on admission were older age, men, cardiovascular disease, chronic respiratory disease, diabetes, obesity and hypertension. Cerebrovascular disease, liver disease, renal disease or dialysis, solid tumour and hyperlipidaemia did not influence severity on admission; however, it influenced worst severity. Fatality rates for obesity, hypertension and hyperlipidaemia were relatively lower.ConclusionsThis study segregated the comorbidities influencing severity and death. It is possible that risk factors for severity on admission, worst severity and fatality are not consistent and may be propelled by different factors. Specifically, while hypertension, hyperlipidaemia and obesity had major effect on worst severity, their impact was mild on fatality in the Japanese population. Some studies contradict our results; therefore, detailed analyses, considering in-hospital treatments, are needed for validation.Trial registration numberUMIN000039873. https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000045453

scholarly journals A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach

2020 ◽  
Vol 4 (1) ◽  
pp. 13-27 ◽  
Author(s):  
Lynn Rochester ◽  
Claudia Mazzà ◽  
Arne Mueller ◽  
Brian Caulfield ◽  
Marie McCarthy ◽  
...  
Keyword(s):  
Health Care ◽  
Clinical Trials ◽  
Health Care Professionals ◽  
Digital Health ◽  
Disease Status ◽  
Proximal Femoral Fracture ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Physical Mobility ◽  
High Level

Health care has had to adapt rapidly to COVID-19, and this in turn has highlighted a pressing need for tools to facilitate remote visits and monitoring. Digital health technology, including body-worn devices, offers a solution using digital outcomes to measure and monitor disease status and provide outcomes meaningful to both patients and health care professionals. Remote monitoring of physical mobility is a prime example, because mobility is among the most advanced modalities that can be assessed digitally and remotely. Loss of mobility is also an important feature of many health conditions, providing a read-out of health as well as a target for intervention. Real-world, continuous digital measures of mobility (digital mobility outcomes or DMOs) provide an opportunity for novel insights into health care conditions complementing existing mobility measures. Accepted and approved DMOs are not yet widely available. The need for large collaborative efforts to tackle the critical steps to adoption is widely recognised. Mobilise-D is an example. It is a multidisciplinary consortium of 34 institutions from academia and industry funded through the European Innovative Medicines Initiative 2 Joint Undertaking. Members of Mobilise-D are collaborating to address the critical steps for DMOs to be adopted in clinical trials and ultimately health care. To achieve this, the consortium has developed a roadmap to inform the development, validation and approval of DMOs in Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease and recovery from proximal femoral fracture. Here we aim to describe the proposed approach and provide a high-level view of the ongoing and planned work of the Mobilise-D consortium. Ultimately, Mobilise-D aims to stimulate widespread adoption of DMOs through the provision of device agnostic software, standards and robust validation in order to bring digital outcomes from concept to use in clinical trials and health care.

scholarly journals Using electronic patient records to assess the effect of a complex antenatal intervention in a cluster randomised controlled trial—data management experience from the DESiGN Trial team

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Sophie Relph ◽  
◽  
Maria Elstad ◽  
Bolaji Coker ◽  
Matias C. Vieira ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Data Quality ◽  
Data Management ◽  
Randomised Control Trial ◽  
Data Dictionary ◽  
Patient Records ◽  
Electronic Patient Records ◽  
Cluster Randomised ◽  
Quality Checks ◽  
Data Harmonisation

Abstract Background The use of electronic patient records for assessing outcomes in clinical trials is a methodological strategy intended to drive faster and more cost-efficient acquisition of results. The aim of this manuscript was to outline the data collection and management considerations of a maternity and perinatal clinical trial using data from electronic patient records, exemplifying the DESiGN Trial as a case study. Methods The DESiGN Trial is a cluster randomised control trial assessing the effect of a complex intervention versus standard care for identifying small for gestational age foetuses. Data on maternal/perinatal characteristics and outcomes including infants admitted to neonatal care, parameters from foetal ultrasound and details of hospital activity for health-economic evaluation were collected at two time points from four types of electronic patient records held in 22 different electronic record systems at the 13 research clusters. Data were pseudonymised on site using a bespoke Microsoft Excel macro and securely transferred to the central data store. Data quality checks were undertaken. Rules for data harmonisation of the raw data were developed and a data dictionary produced, along with rules and assumptions for data linkage of the datasets. The dictionary included descriptions of the rationale and assumptions for data harmonisation and quality checks. Results Data were collected on 182,052 babies from 178,350 pregnancies in 165,397 unique women. Data availability and completeness varied across research sites; each of eight variables which were key to calculation of the primary outcome were completely missing in median 3 (range 1–4) clusters at the time of the first data download. This improved by the second data download following clarification of instructions to the research sites (each of the eight key variables were completely missing in median 1 (range 0–1) cluster at the second time point). Common data management challenges were harmonising a single variable from multiple sources and categorising free-text data, solutions were developed for this trial. Conclusions Conduct of clinical trials which use electronic patient records for the assessment of outcomes can be time and cost-effective but still requires appropriate time and resources to maximise data quality. A difficulty for pregnancy and perinatal research in the UK is the wide variety of different systems used to collect patient data across maternity units. In this manuscript, we describe how we managed this and provide a detailed data dictionary covering the harmonisation of variable names and values that will be helpful for other researchers working with these data. Trial registration Primary registry and trial identifying number: ISRCTN 67698474. Registered on 02/11/16.

scholarly journals Understanding employee turnover in humanitarian organizations

2016 ◽  
Vol 48 (4) ◽  
pp. 208-214 ◽  
Author(s):  
Rameshwar Dubey ◽  
Angappa Gunasekaran ◽  
Nezih Altay ◽  
Stephen J Childe ◽  
Thanos Papadopoulos
Keyword(s):  
Employee Turnover ◽  
Factor Loading ◽  
Personal Factors ◽  
Related Factors ◽  
Content Type ◽  
Factors Affecting ◽  
Work Related ◽  
Humanitarian Organizations ◽  
Using Data ◽  
High Level

Purpose – At a time when the number and seriousness of disasters seems to be increasing, humanitarian organizations find that besides their challenging work they are faced with problems caused by a high level of turnover of staff. The paper aims to discuss these issues. Design/methodology/approach – Based on the 24 variables leading to employee turnover identified by Cotton and Tuttle (1986) the authors analyse the work-related, external and personal factors affecting employee turnover in humanitarian organizations, using a survey of members of the Indian National Institute of Disaster Management. Findings – Results indicated that the three factors are present. Of the external factors, only employment perception had a factor loading over 0.7; of the work-related factors, all were significant; of the personal factors, biographical information, marital status, number of dependants, aptitude and ability and intelligence had the highest loadings. It was also shown that behavioural intentions and net expectation were not significant. Originality/value – Only a few studies reported on employee turnover and its reasons are not well understood in the context of humanitarian organizations. To address this need, the aim of this paper is to explore the personal reasons impacting employee turnover in humanitarian organizations. In the study the authors have adopted 24 variables used in Cotton and Tuttle (1986) and classified into constructs to explain turnover, and further tested the model using data gathered from humanitarian organizations.

Child care needs of parents in paid work: An interpretation of findings from Australia's Welfare 1993: Services and Assistance

1995 ◽  
Vol 20 (2) ◽  
pp. 10-13
Author(s):  
Graeme Vaughan
Keyword(s):  
Child Care ◽  
Informal Support ◽  
Care Needs ◽  
Work Arrangements ◽  
Care Services ◽  
Paid Employment ◽  
Formal Services ◽  
Using Data ◽  
Australian Bureau Of Statistics ◽  
High Level

The extent to which the child care needs of parents in paid employment are adequately met is an important matter. This paper examines the issue using data published in the recent report from the Australian Institute of Health and Welfare, Australia's Welfare 1993: Services and Assistance. Data from recent surveys by the Australian Bureau of Statistics are used to supplement the report's findings.While families with both parents or the sole parent in paid employment are the major users of formal child care services many of them continue to experience difficulties in obtaining child care that meets their needs. Many of these families need to arrange their domestic and working lives to care for children within the family or rely on informal support by other family members, friends and neighbours. Many adopt a mix of strategies-formal services, informal support and flexible work arrangements-to meet their child care needs. These families show a high level of unmet demand for formal services; mothers in these families experience difficulties in balancing the competing demands of caring for children and paid employment.

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