Paper-based Methods Research Articles

Implementing electronic data collection platform for household surveys in resource-constrained settings

Background In resource-constrained settings, quality and timeliness of data are the main concerns related to the use of information systems for decision making. Many different tools are available to improve such systems, but their usefulness is only been recently explored. In this paper, we describe our implementation of an electronic platform, open data kit (ODK) for data collection and its feasibility in data management for a population-based household health expenditure survey. Methods We evaluated the use of ODK based data collection in households located in two areas (one urban and one rural) in Vellore, Tamil Nadu, India. From each area, we selected a sample of 60 households for piloting the ODK based questionnaires. The household survey questionnaires were programmed using the Microsoft Excel for data collection in the ODK collect android application. The ODK aggregate was used for data storage and data transfer. A team of six field workers was recruited, and trained to use the ODK collect application for survey data collection. After the training, the field workers pilot tested the questionnaires, both in the form of mock surveys and real on-field testing. Results Under mock-interviews, there were no significant differences in time –to completion between the six field workers. A total of 60 households participated in field testing that showed field workers were able to complete the questionnaires in a timely manner, (mean 32 minutes (SD=18)) with minimal errors, and all field workers found the ODK form easy to use. There were no major technical issues in the ODK implementation or with electronic devices. Conclusions Results from both mock interviews and on-field testing of our data collection platform show the feasibility of using this approach in resource-constrained settings. The approach used to implement, integrate, and test this platform can benefit other health researchers in developing settings intending to move from paper-based methods toward electronic data collection systems.

Study of Baseline Cyber Security for Various Application Domains

In today’s technical life, the means of production and creation, process, storage and exchange of information and data, rather than in paper-based methods, as an alternative to electronic data and electronic means of communication. That means all information / data is done on the paper as not a written document, but in the form of digital and electronic data. A special type of computer-based system is used in preparing, receiving, processing, transmitting or storing this electronic data / information and the main feature of this computer-based system is that there is a rapid data processing by logical, arithmetic, membrane resources by the systems of electronic, magnetic or optical waves by instruction or communication, work of input, product, investment, processing or storage is done. It is very important for the common man to know about the basic security of information / data in every domain of life. This paper analyses the technical changes and cyber risks arising in various fields, as well as a detailed study of technological security efforts and measures to mitigate cyber risks in various technical areas.

Data Quality and Cost-effectiveness Analyses of Electronic and Paper-Based Interviewer-Administered Public Health Surveys: Systematic Review.

BackgroundA population-level survey (PLS) is an essential and standard method used in public health research that supports the quantification of sociodemographic events, public health policy development, and intervention designs. Data collection mechanisms in PLS seem to be a significant determinant in avoiding mistakes. Using electronic devices such as smartphones and tablet computers improves the quality and cost-effectiveness of public health surveys. However, there is a lack of systematic evidence to show the potential impact of electronic data collection tools on data quality and cost reduction in interviewer-administered surveys compared with the standard paper-based data collection system.ObjectiveThis systematic review aims to evaluate the impact of the interviewer-administered electronic data collection methods on data quality and cost reduction in PLS compared with traditional methods.MethodsWe conducted a systematic search of MEDLINE, CINAHL, PsycINFO, the Web of Science, EconLit, Cochrane CENTRAL, and CDSR to identify relevant studies from 2008 to 2018. We included randomized and nonrandomized studies that examined data quality and cost reduction outcomes, as well as usability, user experience, and usage parameters. In total, 2 independent authors screened the title and abstract, and extracted data from selected papers. A third author mediated any disagreements. The review authors used EndNote for deduplication and Rayyan for screening.ResultsOur search produced 3817 papers. After deduplication, we screened 2533 papers, and 14 fulfilled the inclusion criteria. None of the studies were randomized controlled trials; most had a quasi-experimental design, for example, comparative experimental evaluation studies nested on other ongoing cross-sectional surveys. A total of 4 comparative evaluations, 2 pre-post intervention comparative evaluations, 2 retrospective comparative evaluations, and 4 one-arm noncomparative studies were included. Meta-analysis was not possible because of the heterogeneity in study designs, types, study settings, and level of outcome measurements. Individual paper synthesis showed that electronic data collection systems provided good quality data and delivered faster compared with paper-based data collection systems. Only 2 studies linked cost and data quality outcomes to describe the cost-effectiveness of electronic data collection systems. Field data collectors reported that an electronic data collection system was a feasible, acceptable, and preferable tool for their work. Onsite data error prevention, fast data submission, and easy-to-handle devices were the comparative advantages offered by electronic data collection systems. Challenges during implementation included technical difficulties, accidental data loss, device theft, security concerns, power surges, and internet connection problems.ConclusionsAlthough evidence exists of the comparative advantages of electronic data collection compared with paper-based methods, the included studies were not methodologically rigorous enough to combine. More rigorous studies are needed to compare paper and electronic data collection systems in public health surveys considering data quality, work efficiency, and cost reduction.International Registered Report Identifier (IRRID)RR2-10.2196/10678

The Acceptability and Efficacy of Electronic Data Collection in a Hospital Neurodevelopmental Clinic: Pilot Questionnaire Study.

BackgroundThere is a growing need for cost-efficient and patient-centered approaches to support families in hospital- and community-based neurodevelopmental services. For such purposes, electronic data collection (EDC) may hold advantages over paper-based data collection. Such EDC approaches enable automated data collection for scoring and interpretation, saving time for clinicians and services and promoting more efficient service delivery.ObjectiveThis pilot study evaluated the efficacy of EDC for the Child Development Unit, a hospital-based diagnostic assessment clinic in the Sydney Children’s Hospital Network. Caregiver response rates and preference for EDC or paper-based methods were evaluated as well as the moderating role of demographic characteristics such as age, level of education, and ethnic background.MethodsFamilies were sent either a paper-based questionnaire via post or an electronic mail link for completion before attending their first on-site clinic appointment for assessment. A total of 62 families were provided a paper version of the questionnaire, while 184 families were provided the online version of the same questionnaire.ResultsCompletion rates of the questionnaire before the first appointment were significantly higher for EDC (164/184, 89.1%) in comparison to paper-based methods (24/62, 39%; P<.001). Within the EDC group, a vast majority of respondents indicated a preference for completing the questionnaire online (151/173, 87.3%), compared to paper completion (22/173, 12.7%; P<.001). Of the caregiver demographic characteristics, only the respondent’s level of education was associated with modality preference, such that those with a higher level of education reported a greater preference for EDC (P=.04).ConclusionsThese results show that EDC is feasible in hospital-based clinics and has the potential to offer substantial benefits in terms of centralized data collation, time and cost savings, efficiency of service, and resource allocation. The results of this study therefore support the continued use of electronic methods to improve family-centered care in clinical practices.

The enigma of cerebral blood flow and cognition.

The enigma of cerebral blood flow and cognition.

Knowledge assessment of anti-snake venom among healthcare practitioners in northern Nigeria.

Introduction:Anti-snake venom (ASV) is the standard therapy for the management of snakebite envenoming (SBE). Therefore, the knowledge of ASV among healthcare practitioners (HCPs) is essential for achieving optimal clinical outcomes in snakebite management. This study aimed to assess knowledge of ASV among the HCPs in northern Nigeria.Methods:We conducted a cross-sectional study involving eligible HCPs from different healthcare settings in northern Nigeria. The participants were recruited into the study using a combination of online (via Google Form) and face-to-face paper-based survey methods. The ASV knowledge of the respondents was measured using a validated anti-snake venom knowledge assessment tool (AKAT). Inadequate overall knowledge of ASV was defined as scores of 0–69.9%, and 70–100% were considered adequate overall knowledge scores. The predictors of ASV knowledge were determined using multiple logistic regression.Results:Three hundred and thirty-one (331) eligible HCPs were included in the study analysis (310 from online and 21 from paper-based survey). Overall, an estimated 12.7% of the participants had adequate knowledge of ASV. Adequate ASV knowledge was higher among physicians compared with other HCPs (21.7%; χ2 = 8.1; p = 0.04). Those without previous training on ASV (adjusted odds ratio [aOR], 0.37; 95% confidence interval [CI], 0.18–0.73; p = 0.004) and who have not previously administered/dispensed ASV (aOR, 0.31; 95% CI, 0.15–0.63; p < 0.001) were less likely to have adequate knowledge of ASV.Conclusion:The knowledge of ASV among healthcare practitioners in northern Nigeria is grossly inadequate. Experience with administering or dispensing ASV predicts ASV knowledge. Therefore, appropriate interventions are needed to improve ASV knowledge, particularly among the HCPs, for optimal healthcare outcomes.

Evaluation of a Mobile App to Enhance Relational Awareness and Change During Cognitive Analytic Therapy: Mixed Methods Case Series.

BackgroundThere has been a lack of technological innovation regarding improving the delivery of integrative psychotherapies. This project sought to evaluate an app designed to replace previous paper-based methods supporting relational awareness and change during cognitive analytic therapy (CAT).ObjectiveWe aimed to assess patients’ and therapists’ experience of using the technology (ie, the “CAT-App”) and to evaluate the relationship between app usage and clinical outcome.MethodsThe design was a mixed methods case series. Patients completed the Clinical Outcomes in Routine Evaluation-Outcome Measure pre- and post-CAT. Mood data plus the frequency and effectiveness of relational awareness and change were collected via the app. Therapists and patients were interviewed about their experiences using the app.ResultsTen patients (treated by 3 therapists) were enrolled; seven completed treatment and 4 had a reliable improvement in their mental health. App usage and mood change did not differ according to clinical outcome, but there was a statistically significant difference in app usage between completers and dropouts. The qualitative themes described by the therapists were (1) the challenge of incorporating the technology into their clinical practice and (2) the barriers and benefits of the technology. Clients’ themes were (1) data protection, (2) motivation and engagement, and (3) restrictions versus flexibility.ConclusionsThe CAT-App is capable of supporting relational awareness and change and is an upgrade on older, paper-based formats. Further clinical evaluation is required.

Patients undergoing surgery for lumbar degenerative spinal disorders favor smartphone-based objective self-assessment over paper-based patient-reported outcome measures

Background ContextSmartphone-based applications enable new prospects to monitor symptoms and assess functional outcome in patients with lumbar degenerative spinal disorders. However, little is known regarding patient acceptance and preference towards new modes of digital objective outcome assessment. PurposeTo assess patient preference of an objective smartphone-based outcome measure compared to conventional paper-based subjective methods of outcome assessment. Study designProspective observational cohort study. Patient sampleFourty-nine consecutive patients undergoing surgery for lumbar degenerative spinal disorder. Outcome measuresPatients completed a preference survey to assess different methods of outcome assessment. A 5-level Likert scale ranged from strong disagreement (2 points) over neutral (6 points) to strong agreement (10 points) was used. MethodsPatients self-determined their objective functional impairment using the 6-minute Walking Test application (6WT-app) and completed a set of paper-based patient-reported outcome measures (PROMs) before and 6 weeks after surgery. Patients were then asked to rate the methods of outcome assessment in terms of suitability, convenience, and responsiveness to their symptoms. ResultsThe majority of patients considered the 6WT-app a suitable instrument (median 8.0, interquartile range [IQR] 4.0). Patients found the 6WT more convenient (median 10.0, IQR 2.0) than the Zurich Claudication Questionnaire (ZCQ; median 8.0, IQR 4.0, p=.019) and Core Outcome Measure Index (COMI; median 8.0, IQR 4.0, p=.007). There was good agreement that the 6WT-app detects change in physical performance (8.0, IQR 4.0). 78 % of patients considered the 6WT superior in detecting differences in symptoms (vs. 22% for PROMs). Seventy-six percent of patients would select the 6WT over the other, 18% the ZCQ and 6% the COMI. Eighty-two percent of patients indicated their preference to use a smartphone app for the assessment and monitoring of their spine-related symptoms in the future. ConclusionsPatients included in this study favored the smartphone-based evaluation of objective functional impairment over paper-based PROMs. Involving patients more actively by means of digital technology may increase patient compliance and satisfaction as well as diagnostic accuracy.

Can an online exercise prescription tool improve adherence to home exercise programmes in children with cerebral palsy and other neurodevelopmental disabilities? A randomised controlled trial

ObjectiveDetermine the adherence to and effectiveness of an 8-week home exercise programme for children with disabilities delivered using Physitrack, an online exercise prescription tool, compared with traditional paper-based methods.DesignSingle-blinded, parallel-groups,...

Electronic student feedback management system based on web development

Nowadays, operation management performed by electronic systems in different life sectors is distributed and expanded swiftly due to several advantages that can be achieved, such as time reduction process, simplicity, and high accuracy of running operations. In the educational sector, performing student feedback electrolytically (using PC, Tablet, or Mobile) rather than the ordinary paper-based methods saves staff and students' time and makes managing the data easier. This paper proposes a new approach for the Electronic Student Feedback Management System based on web programming, which consists of input, process, store, and retrieves information using a database. The system is based on the Accreditation Board for Engineering and Technology (ABET) questionnaire model, which is implemented using web development tools (HTML, CSS, Javascript, MySQL, and PHP with Apache web-server). As a result, the proposed system was implemented successfully. The Electronic Engineering College officially adopted it at Ninevah University to perform the student feedback for the academic year 2018-2019, in which 4,282 student feedback applications (SFA) have been recorded. After that, statistical operations were done for extracting useful information effortlessly and accurately. As a result, more than 800 students made 4282 records have participated in the proposed system. This information can be quickly recorded and utilized to identify the weaknesses to address them in the next academic year.

Using AI for Mental Health Analysis and Prediction in School Surveys

Abstract Background Childhood and adolescence are critical stages of life for mental health and well-being. Schools are a key setting for mental health promotion and illness prevention. One in five children and adolescents have a mental disorder, about half of mental disorders beginning before the age of 14. Beneficial and explainable artificial intelligence can replace current paper-based and online approaches to school mental health surveys. This can enhance data acquisition, interoperability, data-driven analysis, trust and compliance. This paper presents a model for using chatbots for non-obtrusive data collection and supervised machine learning models for data analysis; and discusses ethical considerations pertaining to the use of these models. Methods For data acquisition, the proposed model uses chatbots which interact with students. The conversation log acts as the source of raw data for the machine learning. Pre-processing of the data is automated by filtering for keywords and phrases. Existing survey results, obtained through current paper-based data collection methods, are evaluated by domain experts (health professionals). These can be used to create a test dataset to validate the machine learning models. Supervised learning can then be deployed to classify specific behaviour and mental health patterns. Results We present a model that can be used to improve upon current paper-based data collection and manual data analysis methods. An open-source GitHub repository contains necessary tools and components of this model. Privacy is respected through rigorous observance of confidentiality and data protection requirements. Critical reflection on these ethics and law aspects is included in the project. Conclusions This model strengthens mental health surveillance in schools. The same tools and components could be applied to other public health data. Future extensions of this model could also incorporate unsupervised learning to find clusters and patterns of unknown effects. Key messages This model uses artificial intelligence to improve mental health surveillance and evaluation in school settings. Artificial intelligence can be applied more broadly in public health to harness the potential of predictive models.

Technology-Assisted Self-Monitoring of Lifestyle Behaviors and Health Indicators in Diabetes: Qualitative Study.

BackgroundSelf-monitoring is key to successful behavior change in diabetes and obesity, and the use of traditional paper-based methods of self-monitoring may be time-consuming and burdensome.ObjectiveThis study aimed to explore participant experiences while using technology-assisted self-monitoring of lifestyle behaviors and health indicators among overweight or obese adults with type 2 diabetes.MethodsQualitative data collected from the intervention group of a 6-month, three-arm (control, paper diary, and technology-assisted self-monitoring groups) randomized clinical trial were analyzed. Study participants in the intervention group monitored their diet, exercise, and weight using the LoseIt! app, and their blood glucose levels using a glucometer and the Diabetes Connect app. Semistructured group discussions were conducted at 6 weeks (n=10) from the initiation of the behavioral lifestyle intervention and again at 6 months (n=9). All group interviews were audiotaped and transcribed verbatim. Using a combination of thematic and comparative analysis approaches, two trained professionals coded the transcriptions independently and then discussed and concluded common themes for the 6-week and 6-month discussions separately.ResultsThe sample (n=10), which primarily involved African American participants (n=7) and female participants (n=8), had a mean age of 59.4 years. The following eight themes emerged: (1) perceived benefits of technology-assisted self-monitoring; (2) perceived ease of use (eg, barriers: technical difficulties and lack of self-discipline; facilitators: help from family, friends, and the program); (3) use of technology-assisted self-monitoring; (4) facilitators of engaging in healthy lifestyle behaviors (eg, visualization and awareness of calorie input/expenditure); (5) positive lifestyle change; (6) barriers of engaging in healthy lifestyle behaviors (eg, event influence); (7) learning curve; and (8) monitored data sharing. The first six of these themes were shared between the 6-week and 6-month timepoints, but the codes within these themes were not all the same and differed slightly between the two timepoints. These differences provide insights into the evolution of participant thoughts and perceptions on using technology for self-monitoring and subsequent behavioral lifestyle changes while participating in lifestyle interventions. The findings from the 6-week and 6-month data helped to paint a picture of participant comfort and the integration of technology and knowledge overtime, and clarified participant attitudes, difficulties, behavioral processes, and modifications, as well as health indicators that were experienced throughout the study.ConclusionsAlthough there were some barriers, participants were able to identify various individual and external facilitators to adjust to and engage in technology-assisted self-monitoring, and it was concluded that the technology-assisted self-monitoring approach was beneficial, safe, and feasible to use for positive lifestyle change. These patient perspectives need to be considered in future research studies when investigating the effectiveness of using technology-assisted self-monitoring, as well as in clinical practice when recommending technology-assisted self-monitoring of lifestyle behaviors and health indicators to improve health outcomes.

Non-vitamin K antagonist oral anticoagulant (NOAC) use and dosing in Canadian practice: Insights from the optimising pharmacotherapy in the management approach to lowering risk in atrial fibrillation (OPTIMAL AF) Programme.

To estimate the rate of non-vitamin K oral anticoagulant (NOAC) dosing that is lower- and higher-than-recommended and to describe the reasons for NOAC dose discordance with Health Canada prescribing information. The OPTIMAL AF Programme was an observational cohort quality assessment initiative in which primary and specialty care physicians in eight provinces provided a snapshot of their anticoagulated non-valvular atrial fibrillation (NVAF) patients through either an electronic medical record (EMR) system or standardised, paper-based data collection methods. Data on 1681 NVAF patients receiving oral anticoagulation (OAC) for stroke prevention was provided by 102 physicians. A NOAC was prescribed in 1379 patients (8%). The standard recommended dose was prescribed in 849 (76%) and reduced dose in 264 (24%). Concordance of the reduced dose with Health Canada prescribing information occurred in 154 patients (58%). The standard dose was concordant in 805 (95%). The main reasons for the use of discordant reduced doses were age of 80years or more, elevated creatinine, prior bleeding or dose recommended by specialist. The vast majority of Canadian patients meeting the Canadian Cardiovascular Society (CCS) guideline recommendations for OAC to decrease AF-related stroke risk were receiving product monograph-concordant NOAC dosing (85%). Nonetheless, this highlights the fact that an important proportion of patients were prescribed doses that are discordant and opportunities remain to improve NOAC dosing to optimise stroke prevention.

Development and evaluation of a computerized clinical outcome assessment tool for head and neck cancer patients.

Paper-based clinical outcome data collection methods have practical limitations when used in clinical settings, as the data are often not summarized in time to facilitate patient–physician communications and therefore cannot be used in clinical decision making. This study aimed to develop a computerized clinical outcome assessment tool (COAT) and evaluate its acceptability, feasibility, and potential clinical applications during clinical encounters for patients with head and neck cancer (HNC).The traditional Chinese (TChi) character version of the Functional Assessment of Cancer Therapy-Head and Neck (FACT-H&N) questionnaire was first transcribed and implemented into a touch-screen computerized administration and reporting system (COAT-HNC for short). Each HNC patient was invited to complete the COAT-HNC during their scheduled clinic visits as part of their clinical care. Upon completion, a structured summary report was generated, and subsequently used for treatment evaluation and planning.A cohort of 385 HNC patients were enrolled. Each scale of the computerized TChi FACT-H&N questionnaire demonstrated acceptable internal consistency, with Cronbach coefficient alpha ranging from 0.74 to 0.90. The touch-screen-based and audio-capable COAT-HNC was reported to be easy to use. Patients and physicians were able to utilize the summary report during their clinical encounters to discuss treatment progress and to plan care.It is practically feasible to design, develop, and implement the COAT-HNC system in routine HNC care. The COAT-HNC has the potential to become a valuable tool for data collection and management of clinical outcomes, and appears useful for HNC patients. However, larger studies to demonstrate its clinical usefulness are still needed.

Application of paper-based microfluidics in point-of-care testing

Point-of-care testing (POCT) is a test method performed on the sampling site or patient bedside. Accurate results can be achieved rapidly by the application of portable analytical instruments and compatible reagents. It has been widely used in the field of in vitro diagnosis (IVD). Paper-based microfluidics technology has great potential in developing POCT due to its advantages in low cost, simple operation, rapid detection, portable equipment, and unrestricted application conditions. In recent years, the development of paper-based microfluidic technology and its integration with various new technologies and methods have promoted the substantial development of POCT technology and methods. The classification and characteristic of the paper are summarized in this review. Paper-based microfluidic sample pretreatment methods, the flow control in the process of reaction and the signal detecting and analyzing methods for the testing results are introduced. The research progress of various kinds of microfluidic paper-based analytical devices (μPADs) toward POCT in recent years is reviewed. Finally, remaining problems and the future prospects in POCT application of paper-based microfluidics are discussed.

An Enhanced Computational Fusion Technique for Security of Authentication of Electronic Voting System

The detection of a false individual who had not been enrolled as a genuine participant in an election could be potentially detected in electronic voting systems as against paper-based methods. In recent time, one-time password and biometrics have been used to curtail false acceptance of imposters. However, imposters had unlawfully stolen the credentials of genuine individuals, gained unauthorized access, and polled illegitimate votes due to poor authentication methodology. The accuracy of a multi-biometric system is a function of the data type used and fusion method adopted. This paper presented a computational fusion approach that involved the use of fingerprint and randomly generated voter identification number to effectively satisfy the authentication security requirement of the electronic voting system. New architectural and mathematical equations on the proposed approach were presented to tackle the problem of false acceptance rate and improve on the true acceptance rate of a biometric system. Algorithm to achieve the proposed approach was presented in this paper as well.

A mobile digital technology (Fionet™) to improve accuracy, completeness and timeliness of research data compared with a non-digital system in Kenya

The World Health Organization’s Global Malaria Program implemented a multi-country study to assess the entomological and epidemiological impact of long-lasting insecticide treated nets (LLINs) and indoor residual spray (IRS). Study activities included home visits to perform a LLIN survey and malaria testing of children in the household. In Kenya, Fionet™, a technology for automated malaria Rapid Diagnostic Test (mRDT) processing and interpretation at point-of-care, was evaluated against traditional paper-based methods and manual mRDT processing. Objective: To measure and compare the accuracy of diagnosis, completeness, and timeliness of data transmission between a digital mobile solution (Fionet™) and a paper-based system. Methodology: A randomised cluster sampling design of two cohorts: 1) an Active Infection Detection cohort, and 2) an Active Case Detection cohort was undertaken between November 2013 and April 2014. Community Health Workers (CHWs) visited rural households to: 1) measure malaria prevalence in children under the age of five using mRDTs, and 2) survey the use and physical status of LLINs in the household. Ten clusters were randomly assigned to Fionet™ to perform automated testing, interpretation, and survey data capture. Fionet™ transmitted all the tests and survey data to a cloud-based database. Results: A total of 1770 households were visited, 437 children tested, and 742 LLINs inspected. Fionet™ significantly improved the quality of data gathered; a two-fold increase in adherence to study protocols using Fionet™ resulted in more accurate data, data completeness was 10 times higher than with paper-based collection methods, and 87% of data were available in less than one day. Fionet™ significantly improved data quality and management, which enhanced the health system’s ability to meet the research objectives. This technology can help ensure accurate, complete, and timely availability of data. Future studies should incorporate mobile technologies such as Fionet™ to improve RDT based diagnostics of malaria and data quality.

Understanding the scope of downtime threats: A scoping review of downtime-focused literature and news media.

Electronic health record downtimes are any period where the computer systems are unavailable, either for planned or unexpected events. During an unexpected downtime, healthcare workers are rapidly forced to use rarely-practiced, paper-based methods for healthcare delivery. In some instances, patient safety is compromised or data exposed to parties seeking profit. This review provides a foundational perspective of the current state of downtime readiness as organizations prepare to handle downtime events. A search of technical news media related to healthcare informatics and a scoping review of the research literature were conducted. Findings ranged from theoretical exploration of downtime to empirical direct comparison of downtime versus normal operation. Overall, 166 US hospitals experienced a total of 701 days of downtime in 43 events between 2012 and 2018. Almost half (48.8%) of the published downtime events involved some form of cyber-attacks. Downtime contingency planning is still predominantly considered through a top-down organizational focus. We propose that a bottom-up approach, involving the front-line clinical staff responsible for executing the downtime procedure, will be beneficial. Significant new research support for the development of contingency plans will be needed.

Early SARS-CoV-2 outbreak detection by sewage-based epidemiology

Sewage can be used to determine the scale of COVID-19 outbreak. Sewage Epidemiology or Waste Based Epidemiology (WBE) approach has been successfully used to track and provide early warnings of outbreaks of pathogenic viruses such as Hepatitis A, Poliovirus and Norovirus. In untreated wastewater COVID-19 (excreted via faeces then introduced to wastewater) can survive from hours to days. Detection of COVID-19 can be carried out with nucleic acid−based polymerase chain reaction (PCR) assay, used for confirmation of COVID-19 patients around the globe. New cheaper and faster monitoring tools are being developed to detect Covid-19 in wastewater by biosensors, ELISA, or paper-based indicator methods. This will allow to reveal true scale of Covid-19 outbreak associated with population link to a specific wastewater treatment plant.

Benefits and Disadvantages of Electronic Patient-reported Outcome Measures: Systematic Review.

BackgroundPatient-reported outcome measures (PROMs) are important in clinical practice and research. The growth of electronic health technologies provides unprecedented opportunities to systematically collect information via PROMs.ObjectiveThe aim of this study was to provide an objective and comprehensive overview of the benefits, barriers, and disadvantages of the digital collection of qualitative electronic patient-reported outcome measures (ePROMs).MethodsWe performed a systematic review of articles retrieved from PubMED and Web of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed during all stages. The search strategy yielded a total of 2333 records, from which 32 met the predefined inclusion and exclusion criteria. The relevant ePROM-related information was extracted from each study.ResultsResults were clustered as benefits and disadvantages. Reported benefits of ePROMs were greater patient preference and acceptability, lower costs, similar or faster completion time, higher data quality and response rates, and facilitated symptom management and patient-clinician communication. Tablets were the most used ePROM modality (14/32, 44%), and, as a platform, Web-based systems were used the most (26/32, 81%). Potential disadvantages of ePROMs include privacy protection, a possible large initial financial investment, and exclusion of certain populations or the “digital divide.”ConclusionsIn conclusion, ePROMs offer many advantages over paper-based collection of patient-reported outcomes. Overall, ePROMs are preferred over paper-based methods, improve data quality, result in similar or faster completion time, decrease costs, and facilitate clinical decision making and symptom management. Disadvantages regarding ePROMs have been outlined, and suggestions are provided to overcome the barriers. We provide a path forward for researchers and clinicians interested in implementing ePROMs.Trial RegistrationPROSPERO CRD42018094795; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=94795