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Background/aims Targeted magnetic resonance imaging/ ultrasound (MRI/US) guided biopsy is an emerging technology that has the potential to change standard of care for the diagnosis and management of prostate cancer. This technology is rapidly proliferating, however quantitative analysis of these trends are unavailable. The objective of this study was to assess urologist opinions regarding implementing MRI/ US imaging into their practices. Methods A questionnaire was distributed using research electronic data capture and completed by 291 practicing urologists within the United States registered through the American Urological Association. The survey gathered information regarding demographics, changes in MRI use, opinions on targeted MRI/US guided biopsy, and barriers to implementation. The survey results were analyzed using ANOVA. Results Practice setting and geographic region were signifIcantly associated with implementation of MRI/US guided biopsy. Total 72% of urologists in academic centers report using MRI/US targeted biopsy, compared to 38% in solo private practice. In the northeast 68% of urologists report using MRI/US biopsy, compared to 44% in the western United States. Conclusion While there are some reservations about employing MRI/US guided biopsy as standard of care in all prostate biopsies, the data suggests urologists support its use, and are making efforts to introduce targeted MRI/US guided biopsy into their practice. Regional and practice setting variations exist in implementation.

Objectives Phase I - To determine the optimal dose of each candidate (or combination of candidates) entered into the platform. Phase II - To determine the efficacy and safety of each candidate entered into the platform, compared to the current Standard of Care (SoC), and recommend whether it should be evaluated further in a later phase II & III platforms. Trial design AGILE-ACCORD is a Bayesian multicentre, multi-arm, multi-dose, multi-stage open-label, adaptive, seamless phase I/II randomised platform trial to determine the optimal dose, activity and safety of multiple candidate agents for the treatment of COVID-19. Designed as a master protocol with each candidate being evaluated within its own sub-protocol (Candidate Specific Trial (CST) protocol), randomising between candidate and SoC with 2:1 allocation in favour of the candidate (N.B the first candidate has gone through regulatory approval and is expected to open to recruitment early summer 2020). Each dose will be assessed for safety sequentially in cohorts of 6 patients. Once a phase II dose has been identified we will assess efficacy by seamlessly expanding into a larger cohort. Participants Patient populations can vary between CSTs, but the main eligibility criteria include adult patients (≥18 years) who have laboratory-confirmed infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We will include both severe and mild-moderate patients defined as follows: Group A (severe disease) - patients with WHO Working Group on the Clinical Characteristics of COVID-19 infection 9-point ordinal scale of Grades 4 (hospitalised, oxygen by mask or nasal prongs), 5 (hospitalised, non-invasive ventilation or high flow oxygen), 6 (hospitalised, intubation and mechanical ventilation) or 7 (hospitalised, ventilation and additional organ support); Group B (mild-moderate disease) - ambulant or hospitalised patients with peripheral capillary oxygen saturation (SpO2) >94% RA. If any CSTs are included in the community setting, the CST protocol will clarify whether patients with suspected SARS-CoV-2 infection are also eligible. Participants will be recruited from England, North Ireland, Wales and Scotland. Intervention and comparator Comparator is the current standard of care (SoC), in some CSTs plus placebo. Candidates that prevent uncontrolled cytokine release, prevention of viral replication, and other anti-viral treatment strategies are at various stages of development for inclusion into AGILE-ACCORD. Other CSTs will be added over time. There is not a set limit on the number of CSTs we can include within the AGILE-ACCORD Master protocol and we will upload each CST into this publication as each opens to recruitment. Main outcomes Phase I: Dose limiting toxicities using Common Terminology Criteria for Adverse Events v5 Grade ≥3 adverse events. Phase II: Agreed on a CST basis depending on mechanism of action of the candidate and patient population. But may include; time to clinical improvement of at least 2 points on the WHO 9-point category ordinal scale [measured up to 29 days from randomisation], progression of disease (oxygen saturation (SaO2) Randomisation Varies with CST, but default is 2:1 allocation in favour of the candidate to maximise early safety data. Blinding (masking) For the safety phase open-label although for some CSTs may include placebo or SoC for the efficacy phase. Numbers to be randomised (sample size) Varies between CSTs. However simulations have shown that around 16 participants are necessary to determine futility or promise of a candidate at a given dose (in efficacy evaluation alone) and between 32 and 40 participants are required across the dose-finding and efficacy evaluation when capping the maximum number of participants contributing to the evaluation of a treatment at 40. Trial Status Master protocol version number v5 07 May 2020, trial is in setup with full regulatory approval and utilises several digital technology solutions, including Medidata’s Rave EDC [electronic data capture], RTSM for randomisation and patient eConsent on iPads via Rave Patient Cloud. The recruitment dates will vary between CSTs but at the time of writing no CSTs are yet open for recruitment. Trial registration EudraCT 2020-001860-27 14th March 2020 Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Background The most commonly used means to assess pain is by patient self-reported questionnaires. These questionnaires have traditionally been completed using paper-and-pencil, telephone, or in-person methods, which may limit the validity of the collected data. Electronic data capture methods represent a potential way to validly, reliably, and feasibly collect pain-related data from patients in both clinical and research settings. Objective The aim of this study was to conduct a systematic review and meta-analysis to compare electronic and conventional pain-related data collection methods with respect to pain score equivalence, data completeness, ease of use, efficiency, and acceptability between methods. Methods We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica Database (EMBASE), and Cochrane Central Register of Controlled Trials (CENTRAL) from database inception until November 2019. We included all peer-reviewed studies that compared electronic (any modality) and conventional (paper-, telephone-, or in-person–based) data capture methods for patient-reported pain data on one of the following outcomes: pain score equivalence, data completeness, ease of use, efficiency, and acceptability. We used random effects models to combine score equivalence data across studies that reported correlations or measures of agreement between electronic and conventional pain assessment methods. Results A total of 53 unique studies were included in this systematic review, of which 21 were included in the meta-analysis. Overall, the pain scores reported electronically were congruent with those reported using conventional modalities, with the majority of studies (36/44, 82%) that reported on pain scores demonstrating this relationship. The weighted summary correlation coefficient of pain score equivalence from our meta-analysis was 0.92 (95% CI 0.88-0.95). Studies on data completeness, patient- or provider-reported ease of use, and efficiency generally indicated that electronic data capture methods were equivalent or superior to conventional methods. Most (19/23, 83%) studies that directly surveyed patients reported that the electronic format was the preferred data collection method. Conclusions Electronic pain-related data capture methods are comparable with conventional methods in terms of score equivalence, data completeness, ease, efficiency, and acceptability and, if the appropriate psychometric evaluations are in place, are a feasible means to collect pain data in clinical and research settings.

Pharmacist-led medication reviews have been shown to improve medication management, reducing the adverse effects of polypharmacy among older adults. This paper quantitatively examines the medications, medication discrepancies and drug therapy problems of recipients in primary care. A convenience sample of 16 primary care team pharmacists in Ontario, Canada contributed data for patients with whom they conducted a medication review over a prior four-week period. Data were uploaded using electronic data capture forms and descriptive analyses were completed. Two hundred and thirty-seven patients (on average, 67.9 years old) were included in the study, taking an average of 9.2 prescription medications ( &plusmn, 4.7). Majority of these patients (83.5%) were categorized as polypharmacy patients taking at least five or more prescribed drugs per day. Just over half of the patients were classified as having a low level of medication complexity (52.3%). Pharmacists identified 2.1 medication discrepancies ( &plusmn, 3.9) and 3.6 drug therapy problems per patient ( &plusmn, 2.8). Half these patients had more than one medication discrepancy and almost every patient had a drug therapy problem identified. Medication reviews conducted by pharmacists in primary care teams minimized medication discrepancies and addressed drug therapy problems to improve medication management and reduce adverse events that may result from polypharmacy.

The paper presents the main principles of applying Research Electronic Data Capture (REDCap) system to data collection and data storage in population-based biomedical studies. Advantages and limitations of using REDCap as well as possibilities for obtaining intermediate reports, descriptive statistics and data management are presented from the point of view of research project logistics using the Eastern Siberia PCOS Epidemiology & Phenotype (ESPEP) population-based study as an example.

Background:A clinical data management system is a software supporting the data management process in clinical trials. In this system, the effective support of clinical data management dimensions leads to the increased accuracy of results and prevention of diversion in clinical trials. The aim of this review article was to investigate the dimensions of data management in clinical data management systems.Methods:This study was conducted in 2017. The used databases included Web of Science, Scopus, Science Direct, ProQuest, Ovid Medline and PubMed. The search was conducted over a period of 10 years from 2007 to 2017. The initial number of studies was 101 reaching 19 in the final stage. The final studies were described and compared in terms of the year, country and dimensions of the clinical data management process in clinical trials.Results:The research findings indicated that none of the systems completely supported the data management dimensions in clinical trials. Although these systems were developed for supporting the clinical data management process, they were similar to electronic data capture systems in many cases. The most significant dimensions of data management in such systems were data collection or entry, report, validation, and security maintenance.Conclusion:Seemingly, not sufficient attention has been paid to automate all dimensions of the clinical data management process in clinical trials. However, these systems could take positive steps towards changing the manual processes of clinical data management to electronic processes.

Background The Pediatric Acute Care Cardiology Collaborative (PAC3 ) was established in 2014 to improve the quality, value, and experience of hospital-based cardiac acute care outside of the intensive care unit. An initial PAC3 project was a comprehensive survey to understand unit structure, practices, and resource utilization across the collaborative. This report aims to describe the previously unknown degree of practice variation across member institutions. Methods A 126-stem question survey was developed with a total of 412 possible response fields across nine domains including demographics, staffing, available resources and therapies, and standard care practices. Five supplemental questions addressed surgical case volume and number of cardiac acute care unit (CACU) admissions. Responses were recorded and stored in Research Electronic Data Capture (REDCap). Results Surveys were completed by 31 out of 34 centers (91%) with minimal incomplete fields. A majority (61%) of centers have a single dedicated CACU, which is contiguous or adjacent to the intensive care unit in 48%. A nurse staffing ratio of 3:1 is most common (71%) and most (84%) centers employed a resource nurse. Centralized wireless rhythm monitoring is used in 84% of centers with 54% staffed continuously. There was significant variation in the use of noninvasive respiratory support, vasoactive infusions, and ventricular assist devices across the collaborative. Approximately half of the surveyed centers had lesion-specific postoperative pathways and approximately two-thirds had protocols for single-ventricle patients. Conclusions The PAC3 hospital survey is the most comprehensive description of systems and care practices unique to CACUs to date. There exists considerable heterogeneity among unit composition and variation in care practices. These variations may allow for identification of best practices and improved quality of care for patients.

Background Capturing accurate clinical data in real time is a challenge during public health emergencies. The United States Critical Illness and Injury Trials Group-Program for Emergency Preparedness is committed to improving these preparedness efforts. Objectives We aimed to create an electronic Acute Physiology and Chronic Health Evaluation (APACHE) II data collection instrument that (1) leverages Research Electronic Data Capture (REDCap) automated calculations and logic, (2) may be shared across sites, (3) overcomes limitations in existing APACHE II instruments in the REDCap library, and (4) suggests changes to be made to data collection instruments during emergencies. Methods The APACHE II instrument was implemented using REDCap. Data fields were divided into four sections: age, Acute Physiology, Glasgow Coma Scale, and chronic health status. Usability testing was followed by two preliminary evaluations: a comparison to existing APACHE II instruments and a simulated emergency exercise. Results The final instrument consisted of 34 data fields. It produced an accurate APACHE II score and was faster to complete than two previous implementations (average of 97.5 seconds vs. 323.5 and 183.5 seconds). During the simulated emergency exercise, the instrument was used at 10 sites to create 34 patient records; median time to complete the instrument was 150.5 seconds. Conclusion This project demonstrated feasibility of improving the accuracy and efficiency of a data collection instrument. Future efforts should focus on expanding these methods to develop other scoring tools for use during emergencies and additional testing to ensure it is ready for use during a real emergency.

Background: Acute bilirubin encephalopathy (ABE) is a potentially devastating condition that can lead to death or life-long neurodevelopmental handicaps. ABE is particularly tragic because it is, in theory, completely preventable. Progress toward its prevention has been hampered by the perception that the extreme hyperbilirubinemia giving rise to ABE typically has no clear causation, with the majority of previous cases being labeled as “idiopathic” neonatal jaundice. Objectives: This research briefing is intended to inform readers of a new prospective study aimed at clarifying the causes of ABE. This is accomplished by identifying qualifying patients with ABE anywhere in the USA and then documenting their clinical characteristics and the results of testing 28 specific genetic associations in a web-based, institutional review board-approved, REDCap (research electronic data capture) deidentified registry. Methods: In this research briefing, we present an overview of ABE and discuss the problem that most patients in the past have been labeled as having “idiopathic” hyperbilirubinemia. We also present data supporting a new theory that most (perhaps all) ABE patients have mutations or polymorphisms in genes involved in bilirubin production or metabolism. We introduce a new registry seeking to enroll 100 neonates with ABE as a voluntary, deidentified database, with next generation sequencing of 28 genes involved in bilirubin production/metabolism provided to enrollees at no cost. Results and Conclusions: The Neonatal Acute Bilirubin Encephalopathy Registry (NABER) study will correlate deidentified clinical and genetic data in order to clarify the underlying causes of hyperbilirubinemia in current ABE patients. We maintain that the improved understanding this study produces will constitute a needed step toward devising new clinical pathways and strategies for preventing ABE in neonates.

BackgroundThe COVID-19 pandemic has impacted over 1 million people across the globe, with over 330,000 cases in the United States. To help limit the spread in Massachusetts, the Department of Public Health required that all healthcare workers must be screened for symptoms daily – individuals with symptoms may not work. We rapidly created a digital COVID-19 symptom screening tool for a large, academic, integrated healthcare delivery system, Partners HealthCare, in Boston, Massachusetts.ObjectiveWe describe the design and development of the COVID-19 symptom screening application and report on aggregate usage data from the first week of use across the organization.MethodsUsing agile principles, we designed, tested and implemented a solution over the span of a week using progressively custom development approaches as the requirements and use case become more solidified. We developed the minimum viable product (MVP) of a mobile responsive, web-based self-service application using REDCap (Research Electronic Data Capture). For employees without access to a computer or mobile device to use the self-service application, we established a manual process where in-person, socially distanced screeners asked employees entering the site if they have symptoms and then manually recorded the responses in an Office 365 Form. A custom .NET Framework application was developed solution as COVID Pass was scaled. We collected log data from the .NET application, REDCap and Office 365 from the first week of full enterprise deployment (March 30, 2020 – April 5, 2020). Aggregate descriptive statistics including overall employee attestations by day and site, employee attestations by application method (COVID Pass automatic screening vs. manual screening), employee attestations by time of day, and percentage of employees reporting COVID-19 symptomsResultsWe rapidly created the MVP and gradually deployed it across the hospitals in our organization. By the end of the first week of enterprise deployment, the screening application was being used by over 25,000 employees each weekday. Over the first full week of deployment, 154,730 employee attestation logs were processed across the system. Over this 7-day period, 558 (0.36%) employees reported positive symptoms. In most clinical locations, the majority of employees (∼80-90%) used the self-service application, with a smaller percentage (∼10-20%) using manual attestation. Hospital staff continued to work around the clock, but as expected, staff attestations peaked during shift changes between 7-8am, 2-3pm, 4-6pm, and 11pm-midnight.ConclusionsUsing rapid, agile development, we quickly created and deployed a dedicated employee attestation application that gained widespread adoption and use within our health system. Further, we have identified over 500 symptomatic employees that otherwise would have possibly come to work, potentially putting others at risk. We share the story of our implementation, lessons learned, and source code (via GitHub) for other institutions who may want to implement similar solutions.

Background Being able to generalize research findings to a broader population outside of the study sample is an important goal in surveys on the internet. We conducted a nationwide, cross-sectional, web-based survey with vignettes illustrating different levels of patient involvement to investigate men’s preferences regarding participation in health care decision-making. Following randomization into vignette variants, we distributed the survey among men aged 45 to 70 years through the state-authorized digital mailbox provided by the Danish authorities for secure communication with citizens. Objective This study aimed to investigate the sociodemographic representativeness of our sample of men obtained in a nationwide web-based survey using the digital mailbox. Methods Response rate estimates were established, and comparisons were made between responders and nonresponders in terms of age profiles (eg, average age) and municipality-level information on sociodemographic characteristics. Results Among 22,288 men invited during two waves, a total of 6756 (30.31%) participants responded to the survey. In adjusted analyses, responders’ characteristics mostly resembled those of nonresponders. Response rates, however, were significantly higher in older men (odds ratio [OR] 2.83 for responses among those aged 65-70 years compared with those aged 45-49 years, 95% CI 2.58-3.11; P Conclusions Overall, the general population of men aged 45 to 70 years was represented very well by the responders to our web-based survey. However, the imbalances identified highlight the importance of supplementing survey findings with studies of the representativeness of other characteristics of the sample like trait and preference features, so that proper statistical corrections can be made in upcoming analyses of survey responses whenever needed.

Background Transvenous lead extractions (TLEs) in Japan have grown to become the standard therapy since the approval of the laser extraction system in 2008. However, little is known about the current indications, methods, success rate, and acute complications in the real‐world setting. Methods The Japanese Lead EXtraction (J‐LEX) registry is a nationwide, multicenter, observational registry, performed by the Japanese Heart Rhythm Society (JHRS) in collaboration with the National Cerebral and Cardiovascular Center. This study is a nationwide registry ordered by the JHRS and its data are collected prospectively using the Research Electronic Data Capture (REDCap) system. The acute success rate at discharge and complications associated with TLEs will be collected in all cases. Based on the provided information, the annual incidence and predictive factors for the outcomes will be investigated by the Event Assessment Committee (EAC). This registry started in July 2018 and the number of participating medical institutions will be more than 50 hospitals and the target number of procedures will be 500‐1000 per year. We will also compare the results with other registries in foreign countries. Result The results of this study are currently under investigation. Conclusion The J‐LEX registry will provide real‐world data regarding the results and complications of TLEs for the various types of indications, methods, and performing hospitals in Japan., The Japanese Lead EXtraction (J‐LEX) registry is a nationwide, multicenter, observational registry, performed by Japanese Heart Rhythm Society (JHRS), collaborated with National Cerebral and Cardiovascular Center (NCVC). This study is a nationwide registry ordered by the JHRS and its data are collected prospectively using the Research Electronic Data Capture (REDCap) system.

Objectives Fecal microbiota transplantation (FMT) has emerged as an effective treatment option for Clostridioides difficile infection (CDI) and is considered an investigational therapy for a number of other diseases. Social media has facilitated widespread exposure of the public to the gut microbiome and FMT, ultimately acting as a catalyst for the Do-It-Yourself (DIY)-FMT movement. The aims of this study were to identify factors that influenced willingness to pursue DIY-FMT including common indications, screening processes, sample preparation, and self-reported efficacy and safety outcomes. Methods A twenty-five-point cross-sectional survey was posted online through the websites and social media pages of the Peggy Lillis Foundation, The Fecal Transplant Foundation, and The Power of Poop. Responses were cataloged through the Research Electronic Data Capture tool, and descriptive analyses were performed. Results Eighty-four respondents completed the survey between January 2018 and February 2019. The majority were female (71%) and white (92%). Most (80%) reported performing FMT on themselves; 87% used Internet resources to assist in the process, and 92% knew their stool donor. Inflammatory bowel disease (35%) and irritable bowel syndrome (29%) were the 2 most common conditions that respondents attempted to treat. Only 12% reported adverse events, whereas 82% reported improvement in their condition. Discussion DIY-FMT is being used for many indications, including those for which there is little evidence. There was a high self-reported success rate among respondents with few adverse events. There is a need for increased awareness around DIY-FMT and research around this phenomenon, which may impact public health.

Purpose To describe the feasibility and benefits of implementing a custom radiation oncology electronic data capture (EDC) system in a large academic radiation oncology practice. Patients and Methods A Web-based point-and-click EDC known as Brocade was internally developed and implemented systemwide in 2016. Brocade captures key data elements, such as stage, histology, and patient and treatment characteristics; links this information to radiation dose data extracted from the record and verify system; and creates clinical notes that are automatically exported to the hospital electronic health record. We report the number of unique radiation episodes captured by Brocade in its first full year of implementation and describe the notes generated, toxicities captured, compliance with staging and quality assurance, and time of day in which documentation occurred with Brocade versus our prior human transcription system. Results A median of 756 radiation episodes per month was captured for a total of 9,283 unique episodes captured in the first full year of implementation. The most common notes were for on-treatment visits (29,913) and simulations (13,220). Stage was captured for 92.2% of Brocade episodes (8,513 of 9,236) versus 29.7% of courses pre-Brocade (3,025 of 10,170; P < .001). Quality assurance was documented for 96.3% of completed courses (7,601 of 7,892). The most common grade ≥1 toxicities were pain (10,031), fatigue (7,490), and dermatitis (6,172). Brocade implementation was associated with a reduction in off-hours documentation and increase in the proportion of documentation created between 8:00 am and 12:00 pm. Conclusion Brocade is a reliable Web-based EDC tool that improves clinical documentation without detracting from clinical workflow. Moreover, Brocade has the advantage of capturing data in a structured manner that facilitates real-time analytics and outcome reporting.

Purpose Diagnostic testing for dry eye disease (DED) in Sjogren's syndrome (SS) is well described. Little is published about monitoring this systemic autoimmune DED. We analyzed the SS related DED tests used in North American optometric practices and compared academic settings to private practice settings. Methods A retrospective chart review of 123 SS charts from 6 optometric practices in North America was conducted. Testing done during the first examination following a SS diagnosis was recorded on Research Electronic Data Capture (REDCap) database. The complete data file was reviewed and testing type and methodology were compared. Results Symptoms of DED (98.4% of charts),meibomian gland dysfunction (76.4% of charts), corneal staining with fluorescein (75.6% of charts) and anterior blepharitis (73.2% of charts) were the most frequently recorded variables. Clinicians used different methodologies to measure and grade these variables. Private practitioners were more likely to use symptom questionnaires and grading scales and to describe anterior blepharitis. Academic settings were more likely to record TBUT and tear meniscus height. Conclusions The monitoring of DED in SS is not uniform in optometric offices across North America. Creating accepted standards of testing will improve the ability of clinicians and researchers to communicate and understand the course of DED in SS.

The CAPTRA-Lung study (NCT03334864) is a prospective observational study that will capture real-world data of patients with advanced or metastatic non-small cell lung cancer (NSCLC) across China. The study aims to complement the results from current therapeutic regimens to improve the standard of diagnosis and treatment, evaluate the effectiveness and safety of systemic therapy, and determine the factors influencing the outcomes and responses to treatment. From January 2018 to December 2023, eligible patients with advanced or metastatic NSCLC who are receiving treatment and participating in follow-up at 16 institutions in China, will be enrolled. The demographic, clinical, laboratory, and treatment characteristics and responses to treatment will be recorded in a case report form and transcribed into an electronic data capture system. Overall survival, progression-free survival, overall response rate, and incidence of adverse events will be calculated from the time of initial enrolment until progression evaluated by physicians, last contact, date of death, or analysis cutoff date, respectively. Based on the disease characteristics and treatment strategies, four sub-cohorts will also be established. This study cohort could serve as a pool of patients with advanced or metastatic NSCLC to support further research.

Ankylosing spondylitis (AS) is characterized by inflammation of the spine and sacroiliac joints causing pain and stiffness and, in some patients, ultimately new bone formation, and progressive joint ankyloses. The classical definition of AS is based on the modified New York (mNY) criteria. Limited data have been reported regarding data quality assurance procedure for multicenter or multisite prospective cohort of patients with AS. Since 2002, 1272 qualified AS patients have been enrolled from five sites (4 US sites and 1 Australian site) in the Prospective Study Of Ankylosing Spondylitis (PSOAS). In 2012, a Data Management and Statistical Core (DMSC) was added to the PSOAS team to assist in study design, establish a systematic approach to data management and data quality, and develop and apply appropriate statistical analysis of data. With assistance from the PSOAS investigators, DMSC modified Case Report Forms and developed database in Research Electronic Data Capture (REDCap). DMSC also developed additional data quality assurance procedure to assure data quality. The error rate for various forms in PSOAS databases ranged from 0.07% for medications data to 1.1% for arthritis activity questionnaire-Global pain. Furthermore, based on data from a sub study of 48 patients with AS, we showed a strong level (90.0%) of agreement between the two readers of X-rays with respect to modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). This paper not only could serve as reference for future publications from PSOAS cohort but also could serve as a basic guide to ensuring data quality for multicenter clinical studies. Keywords: Ankylosing spondylitis, Data quality, Harmonization, PSOAS cohort, Reliability of data

Quantifying the global burden of pediatric neurosurgical disease—and current efforts addressing it—is challenging, particularly in the absence of uniform terminology. We sought to establish bellwether procedures for pediatric neurosurgery, in order to standardize terminology, establish priorities, and facilitate goal-oriented capacity building. Members of international pediatric neurosurgical and pediatric surgical societies were surveyed via the Research Electronic Data Capture (REDCap) platform. Among 15 proposed neurosurgical procedures, respondents assigned numerical grades of surgical necessity and selected hospital-level designation within a three-tiered system. A procedure was considered a bellwether if (a) the majority of respondents deemed it necessary for either a primary- or secondary-level hospital and (b) the procedure was graded at or above the 90th percentile on a continuous scale of essentiality. Data were compiled and analyzed using Stata software. Complete responses were obtained from 459 surgeons from 76 countries, the majority of whom practiced in a tertiary referral hospital (88%), with a primarily public patient population (64%). Six bellwether procedures were identified for pediatric neurosurgery: shunt for hydrocephalus, myelomeningocele closure, burr holes, trauma craniotomy, external ventricular drain (EVD) insertion, and cerebral abscess evacuation. Few differences in bellwether criteria designations were observed among respondents from different World Health Organization regions and World Bank income groups. The six bellwether procedures identified can be used as markers of infrastructure capacity at various hospital levels, hence allowing targeted neurosurgical capacity-building in low-resource settings in order to avert disability and death from childhood neurosurgical disease.

‘Big data’ is defined by ‘7 V’s’: volume (most frequently cited1), velocity, veracity, variety, volatility, validity and value. In healthcare, ‘big data’ is associated with a step-change in the way information is gathered, analysed and used to facilitate disease management and prevention. With greater electronic data capture, there is enthusiasm for increased safety, efficiency and effectiveness in health and social care through, for example, machine learning and other forms of artificial intelligence (AI). However, factors maintaining and widening the gap between the promise and the reality need to be addressed. Current best practice has its foundation in evidence-based healthcare, with growth in publications, but poorly managed scientific insights, poor recording of care and poor use of evidence.2 Big data could improve the status quo and support learning health systems (LHS).3 Computational methods can contribute to evidence management with automation of literature searching, critical appraisal and guidelines.4 5 Similarly, big data already contribute to aetiological, diagnostic, prognostic and therapeutic research, from -omics to electronic health records (EHR) trials.6 Critics emphasise lack of quality and validation of routinely collected clinical data, and risk of bias in observational studies, where scale cannot compensate for poor design.7 Conversely, data-driven approaches could transform a predominantly retrospective into a prospective or real-time paradigm, across disease boundaries. Infrastructure and analytic tools are necessary but often poorly understood and underdeveloped. Automated extraction of necessary data fields in pseudonymised/anonymised format into curated warehouses is required with robust metadata catalogues and understanding of clinical context. To be available at the point-of-care for clinicians, data will have to be extracted, cleaned and processed promptly. Medicine grapples with conflicting challenges of overdiagnosis and overtreatment as well as underdiagnosis and undertreatment. Widening inequalities also manifest across many health systems, despite improving medications and technologies. Efforts to optimise healthcare delivery …

The problem that often occurs in malls or supermarkets is the use of EDC as a non-cash payment tool for alternative customers. However, the use of EDC machines sometimes experiences problems, namely when customers enter data so that transactions take longer, so this study aims to analyze the optimization of EDC placement in shopping center buildings. This research method is to measure the parameters, namely the RSCP and the closest antenna coverage from the EDC. In this study, three samples were taken, namely Cassa 1, 2 and 3 at Matahari Department Store Malang Town Square. The results of this study were obtained that the Drive Test in the Matahari room showed that Cassa-1, Cassa-2 and Cassa-3 received RSCP with green color which means good. Two of the three tools, namely Drive Test and Mobile can display RSCP with a value that is not too much difference. Especially for EDC is only able to visually display the RSCP and the results of previous calculations, the value of ten antennas which is in the Matahari room has a coverage area below 10 m. And the UG-12 antenna, which is the closest antenna to Cassa-3, that is outside the antenna coverage, while the UG-08 antenna can still reach the Cassa-3 area. This shows that the placement of EDC has met the requirements to get adequate signal quality and the position of the Cassa table can be moved according to the antenna coverage calculation on the Link budget and Path Loss calculations

Automated data capture has become a dominant logic in organizing clinical trial management. This research examines the deployment of electronic data capture (EDC) in clinical trials in China and the potential for Chinese firms to capture value from EDC. Employing a single-case study involving a clinical trial company, data for our empirical enquiry was collected using semi-structured interviews and supplemented organizational documents and questionnaires. We found that managerial understanding of the organizing logics of EDC system is fundamental to the deployment and subsequent capture of value from the system. Furthermore, we identified what we call the rhetoric of legitimation EDC, and the active separation of knowledge forms of the old system as a salient discursive practice that has the potential to impede maximum value capture from EDC deployment. We conclude with a discussion of the managerial implications, limitations of our research, and some directions for future research.

Purpose The aims of this study were to (a) describe the information provided in author guidelines in nursing journals, (b) assess the completeness of this information, and (c) identify the extent and types of reporting guidelines used in nursing journals. Design Content analysis of author guidelines for 245 nursing journals included in the Directory of Nursing Journals maintained at the International Academy of Nursing Editors website. Methods Using Research Electronic Data Capture, data on 19 criteria for completeness were extracted from published author guidelines. Additional details about journal requirements, such as allowed length of manuscripts and format for the abstract, were also recorded. Reliability was established by simultaneous review of 25 journals (10%) by the research assistant and a senior member of the research team. Findings Author guidelines were easily accessible at journal websites or through links to download the information. A majority (73.5%) had completeness scores of 75% or higher; six journals had guidelines that were 100% complete. Half of the journals used the American Psychological Association reference style, and 26.3% used the American Medical Association style. Less than one fourth had stated requirements to use reporting guidelines such as Consolidated Standards of Reporting Trials (CONSORT) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Conclusions Author guidelines for nursing journals are generally complete and informative. Although specific reporting guidelines such as CONSORT and PRISMA improve the accuracy and completeness of manuscripts on various types of studies, most nursing journals do not indicate use of these for manuscript preparation. Editors who want to improve their author guidelines should use the 19 criteria for completeness as a gauge for updating and revision. Clinical relevance Nurses rely on the published literature to inform their practice and ensure that it is based on evidence. Guidelines for publishing in the scholarly literature assist clinicians and scholars to ensure that published articles are complete, current, concise, and accurate.

Background Driving restrictions in epilepsy are intended to safeguard public and personal safety; however, these limitations inhibit socialization, restrict employment, and reduce self-esteem in patients with seizures. A large proportion of patients with seizures continue to drive, and factors leading to noncompliance with driving regulations are poorly understood. Thus, the patients' perspective on driving safety is not incorporated into the existing counseling tools on driving safety in epilepsy. The present study assessed social, economic, and psychological perceptions related to driving restrictions in patients with refractory and pharmacotherapy-controlled seizures at the single epilepsy center and identified impediments for safe driving. Methods Data were obtained from an anonymous survey completed by 25 adult patients in the presurgical group (PG) with refractory epilepsy and 46 patients in the ambulatory group (AG) with confirmed epilepsy which did not meet criteria for refractoriness. The questionnaire (administered via Research Electronic Data Capture (REDCap)) addressed seizure and driving history, knowledge of driving restrictions, and social consequences of losing driving privileges. Results Eighty-seven percent of all responders experienced seizures with alteration of awareness; however, 34% of patients continued to drive during the time when they were legally restricted, and 6% had accidents related to seizures. All responders reported their seizure status accurately to the treating physician, and 93% understood state-based driving restrictions. The median time from the last seizure was shorter, and the duration of last driving restriction was longer in the PG compared with the AG (1 vs. 20 weeks, and 12 vs. 24 weeks, respectively). Despite that, the proportions of patients driving at the time of survey were not significantly different between the two groups. Nearly 80% of all patients stated that driving restrictions reduced their quality of life, and 70% believed that these restrictions carry a social stigma. Employment was chosen to be the most affected by driving restrictions from a list of four social domains by the majority of patients in both groups. Notably, the employment rate was 26% higher in the AG compared with the PG. The lack of public transportation was regarded as a hurdle by more than 60% of patients in each group with greater than two-thirds of patients relying on other drivers for transportation. Conclusions These findings suggest that patients with refractory and pharmacotherapy-controlled seizures are similarly likely to drive a vehicle, disregarding a practitioner's advice and state restrictions. The lack of public transportation is a shared constraint and likely leads to reduced compliance with driving regulations. Driving restrictions carry social stigma and limit the employment of patients with epilepsy, regardless of the refractory seizure status.

Fibromyalgia (FM) is a chronic pain condition characterized by widespread musculoskeletal pain with significant movement-evoked pain. Transcutaneous electrical nerve stimulation (TENS), a non-pharmacological treatment, is efficacious for reduction of pain and fatigue in FM. While physical therapists are trained in the use of TENS, it is an underutilized tool in physical therapy (PT) clinics. To this end, we designed a pragmatic clinical trial to test if using TENS in a PT setting is feasible and if FM patients using TENS show reduced movement-evoked pain, improved adherence to PT, are more likely to reach their therapeutic goals. During a 1-year planning period the study team designed and set up procedures to implement the trial into 24 physical therapy clinics within 5 healthcare systems. Surveys and interviews with PT sites and interactions with the NIH Collaboratory group guided design of this pragmatic trial. The 24 PT clinics will be cluster-randomized and stratified by healthcare system into two groups: (1) No TENS (PT usual care) or (2) TENS+ (TENS plus PT usual care) with a goal of enrolling 600 participants the trial. Assessments will be collected at baseline then at 30-, 60-, 90- and 180-days from randomization through electronic data capture from participants directly and from the electronic health record. The primary outcome is a reduction in movement-evoked pain during a sit and stand test (baseline to 60 days) with secondary outcomes across multiple domains including pain, fatigue, sleep, disease impact, medication usage, psychosocial variables, patient-specific functional goals, and adherence to PT. Successful completion of this trial will provide generalizable effectiveness data on TENS for referring providers, physical therapists, patients, and insurers and will inform future pragmatic trials of non-pharmacological treatments conducted in PT practices. NIH; 4UH3AR076387-02 REVISED.