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Academic literature on the topic 'Routinely Collected Health Data'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Routinely Collected Health Data"

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Roberts, Christine L., Carolyn A. Cameron, Jane C. Bell, Charles S. Algert, and Jonathan M. Morris. "Measuring Maternal Morbidity in Routinely Collected Health Data." Medical Care 46, no. 8 (August 2008): 786–94. http://dx.doi.org/10.1097/mlr.0b013e318178eae4.

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Koo, Malcolm. "Reporting of secondary data analysis using routinely collected health data." European Journal of Internal Medicine 34 (October 2016): e34. http://dx.doi.org/10.1016/j.ejim.2016.05.018.

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Rosella, Laura, and Vinyas Harish. "Machine Learning Applied to Routinely Collected Health Administrative Data." Healthcare Quarterly 25, no. 1 (April 27, 2022): 12–16. http://dx.doi.org/10.12927/hcq.2022.26813.

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Prytherch, D. R., J. S. Briggs, P. C. Weaver, P. Schmidt, and G. B. Smith. "Measuring clinical performance using routinely collected clinical data." Medical Informatics and the Internet in Medicine 30, no. 2 (January 2005): 151–56. http://dx.doi.org/10.1080/14639230500298966.

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Zeng, X. "Modeling the Effects of Epidemics on Routinely Collected Data." Journal of the American Medical Informatics Association 9, no. 90061 (November 1, 2002): 17S—22. http://dx.doi.org/10.1197/jamia.m1219.

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Fleming, D. M., N. J. Andrews, J. S. Ellis, A. Bermingham, P. Sebastianpillai, A. J. Elliot, E. Miller, and M. Zambon. "Estimating influenza vaccine effectiveness using routinely collected laboratory data." Journal of Epidemiology & Community Health 64, no. 12 (November 12, 2009): 1062–67. http://dx.doi.org/10.1136/jech.2009.093450.

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Glover, Gyles. "Use of routinely collected data on psychiatric in-patient care." Advances in Psychiatric Treatment 9, no. 4 (July 2003): 300–307. http://dx.doi.org/10.1192/apt.9.4.300.

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Since the start of the National Health Service, data have been collected on admissions to psychiatric in-patient units, first as the Mental Health Enquiry, then as part of Hospital Episode Statistics. Some details have changed but many have stayed remarkably consistent. Published literature on the wide range of research and policy work undertaken using this data source is reviewed. Early work was central to the government's deinstitutionalisation policy in the early 1960s. Subsequent studies cover a wide range of epidemiological and health services research issues. A new statistical base, the Mental Health Minimum Data Set, covering individuals receiving all types of health care is currently being set up. This will supplement (but not replace) admission statistics.
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van Ginneken, A. M., T. Timmers’, H. Stam, R. F. A. Weber, and F. H. Pierik. "Restructuring Routinely Collected Patient Data: ORCA Applied to Andrology." Methods of Information in Medicine 36, no. 03 (July 1997): 184–90. http://dx.doi.org/10.1055/s-0038-1636842.

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Hospital information systems do not always cover all required detail per specialty. This may lead to scattering of data over disparate systems and the paper record. The ORCA (Open Record for CAre) CPR offers a generic structure for record sharing, and record keeping tailored to specific needs. We studied whether a semantic integration of existing and new data was possible, using the ORCA structure. Existing andrology data, originating from separate sources, were utilized for this purpose. During normalization, validation and explication steps, latent problems in the source data were exposed and removed, followed by a merge with new data items. By conversion of source data to ORCA, a unique representation of medical concepts in the database was attained, facilitating retrieval of univocal data for multiple purposes. We conclude that the expansion to the andrology domain, including transparent integration of existing data, provides support for the generality of ORCA.
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Fry, Richard J., Sarah E. Rodgers, Jennifer Morgan, Scott Orford, and David L. Fone. "Using Routinely Collected Administrative Data in Public Health Research: Geocoding Alcohol Outlet Data." Applied Spatial Analysis and Policy 10, no. 2 (March 18, 2016): 301–15. http://dx.doi.org/10.1007/s12061-016-9184-4.

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Carpenter, Lucy M., Noreen E. S. Maconochie, Eve Roman, and D. R. Cox. "Examining Associations between Occupation and Health by using Routinely Collected Data." Journal of the Royal Statistical Society: Series A (Statistics in Society) 160, no. 3 (September 1997): 507–21. http://dx.doi.org/10.1111/j.1467-985x.1997.00077.x.

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Dissertations / Theses on the topic "Routinely Collected Health Data"

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Hockin, James Charles. "A case-control study of risk factors for ectopic pregnancy using routinely collected administrative data." Thesis, University of Ottawa (Canada), 1990. http://hdl.handle.net/10393/5628.

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The potential for using the case-control design with only hospital separation records was explored in a study of ectopic pregnancy. The Saskatchewan Hospital Services Commission hospital morbidity database was used. Cases were women hospitalized for ectopic pregnancy in the years 1984 through 1986. Controls were women hospitalized for any other pregnancy condition. In a case-control study using pregnant controls, the odds ratio is an appropriate estimator of relative risk, conditional on conception. Among the potential risk factors (exposures) represented in the data were tubal surgery, prior ectopic pregnancy, pelvic inflammatory disease, and infertility. Of these, the first two are completely ascertained during the time a woman was resident in Saskatchewan. Under representation of exposures should be non-differential, leading to odds ratios which are biased towards the null. Multiple logistic regression analysis yielded estimates of the odds ratios for acute PID, chronic PID or pelvic adhesions, prior ectopic pregnancy, tubal sterilization, and tubal repair. Of particular interest was the association between ectopic pregnancy and tubal surgery performed in the hope of maintaining or restoring normal tubal function. The attributable risk proportion of ectopic pregnancy due to such surgery was 8.1%. This study design can be used to follow trends in surgical causes of ectopic pregnancy in Canada. (Abstract shortened by UMI.)
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Xu, Yan. "Using data to answer questions of public health importance for ACT Health, with an emphasis on routinely-collected linked data." Master's thesis, Canberra, ACT : The Australian National University, 2017. http://hdl.handle.net/1885/144601.

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My field placement was with the Epidemiology Section in the Population Health Protection and Prevention Division at ACT Health. Within this placement, I have completed four projects for this thesis: an analysis of Emergency Department (ED) data; a gastroenteritis outbreak investigation; an evaluation of a population health survey and, for my main project, a study of unplanned hospital readmissions. One of the motivations for undertaking these projects was to promote better use of the routinely-collected linked data to answer questions of public health importance for ACT Health. My data analysis project was an analysis of frequent ED use in the Australian Capital Territory (ACT). This is the first study to quantify and characterise ED frequent users in the ACT. The results support existing evidence that frequent users tend to be older, female, and/or single, and commonly present with pain-related conditions. The data also showed that compared to non-frequent ED users, frequent users were more likely to be referred by police, corrective or community services; arrive by ambulance, not wait to be assessed, or leave at their own risk. In addition, we investigated visit intervals, rarely reported on in other studies. This study found around one third of frequent users returned within 7 days, with 41% of their visits having the same diagnosis as the last visit. Early identification and follow-up in the community for frequent users will assist in the development of targeted strategies to improve health service delivery to this vulnerable group. Unexpected return to hospital has negative impacts on families and healthcare systems. We examined which conditions have the highest rates of readmission and contribute most to 30-day unplanned readmissions in the ACT, and which patient characteristics are associated with readmissions. The study identified a 30-day unplanned readmission rate of 6.2%, with admission rates highest for alcohol-related liver disease (19.2%), and heart valve disorders (17.4%). Older age and comorbidities are strong predictors for 30-day unplanned readmissions. For some conditions the rates were relatively high, suggesting areas to target for reducing readmissions. Therefore, when developing preventative strategies and post-discharge plans, particular consideration should be given to patients at older age or with underlying comorbidities. As part of the ACT Health Survey Program (HSP), the ACT General Health Survey (GHS) is a computer-assisted telephone interviewing survey conducted every year among ACT residents. My evaluation of the GHS found that it is a useful tool to monitor trends of overweight, obesity, nutrition and physical activity for adults and children in the ACT. The data collected are used to provide evidence to understand and analyse overweight and obesity patterns in the ACT and create awareness of unhealthy lifestyles. However, improvements could be made in a few areas, including: developing a proper evaluation plan and a data quality statement, increasing the sample size and the proportion of young people in the sample population. I also carried out an outbreak investigation of foodborne gastroenteritis that occurred among staff and public members at a large national institution in Canberra. I conducted two studies for this outbreak – a retrospective cohort study and a case control study. The epidemiological, environmental and laboratory evidence suggested the outbreak was caused by C. perfringens toxin Type A, with the likely vehicles of transmission being butter chicken and rice. The findings of this investigation suggest that a breakdown in temperature control and good food handling practices may have resulted in C. perfringens bacterium growing rapidly and producing a toxin which caused the illness. This project also indicated that the value of a second epidemiological study was questionable given the limited time and resources available.
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King, Carina. "Can routinely collected electronic health data be used to develop novel healthcare associated infection surveillance tools?" Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/17759.

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Background: Healthcare associated infections (HCAI) pose a significant burden to health systems both within the UK and internationally. Surveillance is an essential component to any infection control programme, however traditional surveillance systems are time consuming and costly. Large amounts of electronic routine data are collected within the English NHS, yet these are not currently exploited for HCAI surveillance. Aim: To investigate whether routinely collected electronic hospital data can be exploited for HCAI surveillance within the NHS. Methods: This thesis made use of local linked electronic health data from Imperial College Healthcare NHS Trust, including information on patient admissions, discharges, diagnoses, procedures, laboratory tests, diagnostic imaging requests and traditional infection surveillance data. To establish the evidence base on surveillance and risks of HCAI, two literature reviews were carried out. Based on these, three types of innovative surveillance tools were generated and assessed for their utility and applicability. Results: The key findings were firstly the emerging importance of automated and syndromic surveillance in infection surveillance, but the lack of investigation and application of these tools within the NHS. Syndromic surveillance of surgical site infections was successful in coronary artery bypass graft patients; however it was an inappropriate methodology for caesarean section patients. Automated case detection of healthcare associated urinary tract infections, based on electronic microbiology data, demonstrated similar rates of infection to those recorded during a point prevalence survey. Routine administrative data demonstrated mixed utility in the creation of simplified risk scores or infection, with poorly performing risk models of surgical site infections but reasonable model fit for HCA UTI. Conclusion: Whilst in principle routine administrative data can be used to generate novel surveillance tools for healthcare associated infections; in reality it is not yet practical within the IT infrastructure of the NHS.
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Rouamba, Toussaint. "Optimal use of routinely collected data among pregnant women to improve malaria surveillance in Burkina Faso: Contribution of Bayesian spatiotemporal modelling." Doctoral thesis, Universite Libre de Bruxelles, 2020. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/314119.

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Background: The control of malaria in pregnancy remains a large challenge in Burkina Faso, despite the adoption of control measures known to be effective. Known effective programs include individual measures, such as intermittent preventive treatment during pregnancy, and the use of long lasting insecticide nets and daily supplementation of ferrous sulphate (200 mg) along with folic acid. Besides these measures, health programs that aim at enhancing the well-being of the population and improve maternal and child health have emerged, including results-based financing (in 2014), a project promoting health in 130 communities (implemented in 2015), and free health care (implemented in 2016). This thesis attempts to assess the effects of health programs on the space–time patterns of malaria (morbidity and mortality) through routinely collected data in pregnancy and explore the various prediction approaches to address challenges in routine health data reporting. Methods: We utilized a substantial range of data and applied advanced quantitative approaches while considering the specific distribution of the data. Our thesis is based on the valorization (analyses) of malaria surveillance data (aggregated by space and time units) recorded in the health information system of Burkina Faso between 2011 and 2019. These analyses also integrate environmental remote sensing data, data from periodic surveys, and data from other sources. These data were coupled into a database. After performing appropriate descriptive analyses considering the complexity of the data design, we performed spatio-temporal Bayesian modeling to determine areas with high risk and assess the effect of health programs on the space–time patterns of malaria incidence among pregnant women at the community-level; to explore an approach to estimate health facility readiness from survey data designed to be regionally representative (and then quantify the effect of this readiness on severe-malaria cases and case fatality); and to explore the prediction approaches used to address challenges in routine health data reporting, thereby supporting a malaria early warning system. Results: Our results show spatial and temporal heterogeneity and indicate that the annual incidence of malaria increased between 2013 and 2018, while the mortality rate decreased significantly. Some communities with a high malaria burden experienced a reduction in their risk through the deployment of the health programs mentioned above. The risk of a pregnant woman dying from severe malaria was 2.5 times higher in districts with low operational capacity. Finally, our thesis proposed an approach to respond to crisis situations that would affect data collection and could be used to set the target or provide early warnings for epidemics or other notifications. Conclusion: Our thesis provides useful tools for disease surveillance in developing countries to help optimize the scarce resources in malaria high burden areas. The results of our thesis could be used by the Ministry of Health to strengthen the capacity of existing surveillance tools and to develop rational strategies and/or new tools for monitoring malaria cases and associated deaths in communities.
Contexte :La lutte contre le paludisme pendant la grossesse reste un grand défi au Burkina Faso, malgré l'adoption de mesures de contrôle dont l'efficacité est reconnue. Les programmes dont l'efficacité est reconnue comprennent des mesures individuelles, telles que le traitement préventif intermittent pendant la grossesse, l'utilisation de moustiquaires imprégnées d'insecticide de longue durée et la supplémentation quotidienne en sulfate ferreux (200 mg) ainsi qu'en acide folique. Outre ces mesures, des programmes de santé visant à accroître le bien-être de la population et à améliorer la santé maternelle et infantile ont vu le jour, notamment le financement basé sur les résultats (en 2014), le projet de promotion de la santé dans 130 communes (mis en œuvre en 2015) et la gratuité des soins de santé (mise en œuvre en 2016). Cette thèse tente d'évaluer les effets des programmes de santé sur les caractéristiques spatio-temporelles du paludisme (morbidité et mortalité) par le biais de données de routine collectées pendant la grossesse et d'explorer les différentes approches de prévision pour relever les défis de la rapportage systématique des données de santé. Méthodes :Nous avons utilisé un large éventail de données et appliqué des approches quantitatives avancées tout en tenant compte de la distribution spécifique des données. Notre thèse est basée sur la valorisation (analyses) des données de surveillance du paludisme (agrégées par unités spatiales et temporelles) enregistrées dans le système d'information sanitaire du Burkina Faso entre 2011 et 2019. Ces analyses intègrent également des données de télédétection environnementale, des données issues d'enquêtes périodiques et des données provenant d'autres sources. Ces données ont été couplées pour constituer une base de données. Après avoir effectué des analyses descriptives appropriées en tenant compte de la complexité de la conception des données, nous avons procédé à une modélisation bayésienne spatio-temporelle pour déterminer les zones à haut risque et évaluer l'effet des programmes de santé sur les tendances spatio-temporelles de l'incidence du paludisme chez les femmes enceintes au niveau communautaire ;pour explorer une approche permettant d'estimer la capacité opérationnelle des établissements de santé à partir de données d'enquête conçues pour être représentatives au niveau régional (et ensuite quantifier l'effet de cette capacité opérationnelle sur les cas de paludisme grave et la mortalité) ;et pour explorer les approches de prévision utilisées pour relever les défis relatifs au rapportaga systématique des données de santé, pouvant aussi servir à un système d'alerte précoce du paludisme. Résultats :Nos résultats montrent une hétérogénéité spatiale et temporelle et indiquent que l'incidence annuelle du paludisme a augmenté entre 2013 et 2018, tandis que le taux de mortalité a diminué de manière significative. Certaines communes où la charge du paludisme est élevée ont connu une réduction de leur risque grâce au déploiement des programmes de santé mentionnés ci-dessus. Le risque qu'une femme enceinte meure d'un paludisme grave était 2,5 fois plus élevé dans les districts ayant une faible capacité opérationnelle. Enfin, notre thèse a proposé une approche pour répondre aux situations de crise qui affecterait la collecte de données et pourrait être utilisée pour fixer l'objectif ou fournir des alertes précoces pour les épidémies ou autres notifications. Conclusion :Notre thèse fournit des outils utiles pour la surveillance des maladies dans les pays en développement afin de contribuer à optimiser les ressources limitées dans les zones à forte incidence de paludisme. Les résultats de notre thèse pourraient être utilisés par le ministère de la santé pour renforcer la capacité des outils de surveillance existants et pour développer des stratégies rationnelles et/ou de nouveaux outils de surveillance des cas de paludisme et des décès associés dans les communautés.
Doctorat en Sciences de la santé Publique
info:eu-repo/semantics/nonPublished
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Vallance, Abigail Ella. "Using routinely collected national data to describe the surgical management and outcomes of patients with colorectal cancer liver metastases in the English National Health Service." Thesis, University of Leeds, 2017. http://etheses.whiterose.ac.uk/20576/.

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Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom. Up to half of patients with CRC will develop liver metastases. For selected patients with liver metastases, liver resection can offer a chance of long-term cure. The aim of this thesis was to investigate the management and outcomes associated with the surgical treatment of patients with CRC liver metastases in England in an attempt to identify areas where care may be improved. Four separate studies were performed describing i) the impact of centralisation of hepatobiliary surgical services on liver resections rates for patients with CRC liver metastases and patient survival, ii) the effect of socioeconomic deprivation on rates of liver resection in patients with CRC liver metastases ,and the impact on survival, iii) the timing of liver resection in relation to CRC resection in patients with synchronous CRC liver metastases and iv) the impact of advancing age on outcomes following liver resection. These studies were conducted by linking three national databases: the National Bowel Cancer Audit, Hospital Episode Statistics data and Office for National Statistics mortality data. The results of these studies highlight that firstly, amongst patients with synchronous CRC liver metastases, those diagnosed at hospital sites with no on-site hepatobiliary services and those of higher socioeconomic deprivation have poorer survival than would be expected. This appears to relate to inequalities in provision of liver resection. Secondly, there is wide inter-hospital variation in the timing of liver resection in relation to CRC resection in England. Thirdly, although elderly patients are at increased risk of post-operative mortality following liver resection, cancer-specific and overall survival in patients between 65 and 74 years are comparable to younger patients. This thesis also discusses methodological issues associated with using national routine data for the analyses in this patient cohort.
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Holm, Hansen Christian. "Analysis of routinely collected repeated patient outcomes." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9556.

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Clinical practice should be based on the best available evidence. Ideally such evidence is obtained through rigorously conducted, purpose-designed clinical studies such as randomised controlled trials and prospective cohort studies. However gathering information in this way requires a massive effort, can be prohibitively expensive, is time consuming, and may not always be ethical or practicable. When answers are needed urgently and purpose-designed prospective studies are not feasible, retrospective healthcare data may offer the best evidence there is. But can we rely on analysis with such data to give us meaningful answers? The current thesis studies this question through analysis with repeated psychological symptom screening data that were routinely collected from over 20,000 outpatients who attended selected oncology clinics in Scotland. Linked to patients’ oncology records these data offer a unique opportunity to study the progress of distress symptoms on an unprecedented scale in this population. However, the limitations to such routinely collected observational healthcare data are many. We approach the analysis within a missing data context and develop a Bayesian model in WinBUGS to estimate the posterior predictive distribution for the incomplete longitudinal response and covariate data under both Missing At Random and Missing Not At Random mechanisms and use this model to generate multiply imputed datasets for further frequentist analysis. Additional to the routinely collected screening data we also present a purpose-designed, prospective cohort study of distress symptoms in the same cancer outpatient population. This study collected distress outcome scores from enrolled patients at regular intervals and with very little missing data. Consequently it contained many of the features that were lacking in the routinely collected screening data and provided a useful contrast, offering an insight into how the screening data might have been were it not for the limitations. We evaluate the extent to which it was possible to reproduce the clinical study results with the analysis of the observational screening data. Lastly, using the modelling strategy previously developed we analyse the abundant screening data to estimate the prevalence of depression in a cancer outpatient population and the associations with demographic and clinical characteristics, thereby addressing important clinical research questions that have not been adequately studied elsewhere. The thesis concludes that analysis with observational healthcare data can potentially be advanced considerably with the use of flexible and innovative modelling techniques now made practicable with modern computing power.
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Almashrafi, Ahmed. "Optimising cardiac services using routinely collected data and discrete event simulation." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/43388.

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Background: The current practice of managing hospital resources, including beds, is very much driven by measuring past or expected utilisation of resources. This practice, however, doesn't reflect variability among patients. Consequently, managers and clinicians cannot make fully informed decisions based upon these measures which are considered inadequate in planning and managing complex systems. Aim: to analyse how variation related to patient conditions and adverse events affect resource utilisation and operational performance. Methods: Data pertaining to cardiac patients (cardiothoracic and cardiology, n=2241) were collected from two major hospitals in Oman. Factors influential to resource utilisation were assessed using logistic regressions. Other analysis related to classifying patients based on their resource utilisation was carried out using decision tree to assist in predicting hospital stay. Finally, discrete event simulation modelling was used to evaluate how patient factors and postoperative complications are affecting operational performance. Results: 26.5% of the patients experienced prolonged Length of Stay (LOS) in intensive care units and 30% in the ward. Patients with prolonged postoperative LOS had 60% of the total patient days. Some of the factors that explained the largest amount of variance in resource use following cardiac procedure included body mass index, type of surgery, Cardiopulmonary Bypass (CPB) use, non-elective surgery, number of complications, blood transfusion, chronic heart failure, and previous angioplasty. Allocating resources based on patient expected LOS has resulted in a reduction of surgery cancellations and waiting times while overall throughput has increased. Complications had a significant effect on perioperative operational performance such as surgery cancellations. The effect was profound when complications occurred in the intensive care unit where a limited capacity was observed. Based on the simulation model, eliminating some complications can enlarge patient population. Conclusion: Integrating influential factors into resource planning through simulation modelling is an effective way to estimate and manage hospital capacity.
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Badriyah, Tessy. "Developing risk of mortality and early warning score models using routinely collected data." Thesis, University of Portsmouth, 2013. https://researchportal.port.ac.uk/portal/en/theses/developing-risk-of-mortality-and-early-warning-score-models-using-routinely-collected-data(88353bb6-9b5d-4bca-ba60-78e33bd8e085).html.

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Aim. The aim of this study was to contribute to the building of effective and efficient methods to predict adverse clinical outcome. It has been done by developing risk of mortality and early warning score models using routinely collected data that are available from hospital computer systems. Methods. To predict risk of mortality, firstly we used logistic regression using (Biochemistry and Haematology Outcome Model - BHOM dataset) to generate a model, and the performance of each model was then compared using discrimination (AUROC or c-index) and calibration (the Hosmer- Lemeshow test). Secondly, we focused on decision trees (DT) to be compared with logistic regression (LR). In addition, we used cross validation to compare LR with other various machine learning methods. We developed early warning score algorithmically using decision trees (DTEWS) using vital sign dataset and compared the performance of DTEWS with other EWSs based on clinical expertise using c index, early warning score efficiency curve and distribution score. We also compared DTEWS with another EWS based on statistics and applied DTEWS to BHOM dataset. Results. In BHOM dataset, there were 9497 adult hospital discharges, and it was divided into four subsets. A model was built using one training set and then applied to three other testing data sets. The model in logistic regression satisfied both discrimination and calibration value when the c-index in the range 0.700-0.800 is reasonable discrimination and the p-value > 0.05 indicates there is no evidence of significant lack of fit. We also found that decision trees gave a satisfactory result followed by some other machine learning methods.Using a large vital signs dataset (n = 198,755 observation sets) from acute medical admissions, DTEWS can provide a discrimination (c-index) as good as other EWSs, has a better c-index, and also is better in other measurements including EWS efficiency curve, and distribution of score. We found DTEWS can also be applied to BHOM dataset with satisfactory results. Conclusion. The results of this study support the idea that decision trees can be applied to medical problems. When we produced a model for risk of mortality, we have shown that the decision trees model has reasonable discrimination and could be considered as an alternative technique to logistic regression. We have shown that a structured methodology using decision trees to develop early warning score has satisfactory result and contributes additional evidence that suggests an algorithmical method can be employed to quickly produce EWSs for employment in particular types of medical purpose.
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Fear, Nicola Townsend. "Paternal occupation and childhood cancer : an analysis of routinely collected death certification data." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390489.

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Kingkeow, Chamnong. "The use of routinely collected epidemiological data to improve malaria control in northwestern Thailand." Thesis, London School of Hygiene and Tropical Medicine (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263726.

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Books on the topic "Routinely Collected Health Data"

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Wilson, Richard Connor. Utilisation of routinely collected data in health services research: A study of their application across the West Midlands region of the national health service. Birmingham: University of Birmingham, 1998.

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Grayson, Narelle. Use of routinely collected national data sets for reporting on induced abortion in Australia. Sydney: Australian Institute of Health and Welfare, National Perinatal Statistics Unit, 2005.

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Yates, J. M. The use of routinely collected information in the monitoring of performance in the health service. Birmingham: University of Birmingham, 1986.

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Abrahamsen, Thomas A. Ecological data collected in the Santee River basin and coastal drainages, North and South Carolina, 1996-98. Columbia, S.C: U.S. Dept. of the Interior, U.S. Geological Survey, 2001.

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Abrahamsen, Thomas A. Ecological data collected in the Santee River basin and coastal drainages, North and South Carolina, 1996-98. Columbia, S.C: U.S. Dept. of the Interior, U.S. Geological Survey, 2001.

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Abrahamsen, Thomas A. Ecological data collected in the Santee River basin and coastal drainages, North and South Carolina, 1996-98. Columbia, S.C: U.S. Dept. of the Interior, U.S. Geological Survey, 2001.

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Shuaib, Muhammad. A review of the primary data on child survival and development indicators being collected by selected agencies in Bangladesh. [Dhaka: Unicef Dhaka, Programme Planning Unit, 1993.

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Balding, John. Young people and illegal drugs into 2000: Did illegal drug levels peak in the mid-1990's : a report based on data collected using the Health Related Behaviour Questionnaire from more than 300,000 young people since 1987, and in particular from 40,229 between the ages of 9 and 15 in 1999. Exeter: Schools Health Education Unit, 2000.

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Wacks, Raymond. 5. Data protection. Oxford University Press, 2015. http://dx.doi.org/10.1093/actrade/9780198725947.003.0005.

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The routine functions of government and private institutions require a continual supply of data about us in order to administer effectively the many services that are an integral part of modern life. The provision of health services, social security, credit, insurance, and the prevention and detection of crime assume the availability of a considerable quantity of personal data and, hence, a willingness by individuals to supply it. The ubiquity of computers and computer networks facilitates almost instant storage, retrieval, and transfer of data, a far cry from the world of manual filing systems. At the core of all data protection legislation is the proposition that data relating to an identifiable individual should not be collected in the absence of a genuine purpose or the consent of the individual concerned. Adherence to, and enforcement of, this idea (and the associated rights of access and correction) has been mixed in the nearly 100 jurisdictions that have enacted data protection legislation. This chapter assesses the extent to which these statutes have succeeded in protecting personal data.
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Evaluation of the Adherence Guidelines for Chronic Diseases in South Africa Using Routinely Collected Data. World Bank, Washington, DC, 2018. http://dx.doi.org/10.1596/31480.

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Book chapters on the topic "Routinely Collected Health Data"

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Ostler, Richard, Nathalie Castells, Margaret Glendining, and Sarah Perryman. "Linking Legacies: Realising the Potential of the Rothamsted Long-Term Agricultural Experiments." In Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development, 125–47. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13276-6_7.

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AbstractLong-term agricultural experiments are used to test the effects of different farm management practices on agricultural systems over time. The time-series data from these experiments is well suited to understanding factors affecting soil health and sustainable crop production and can play an important role for addressing the food security and environmental challenges facing society from climate change. The data from these experiments is unique and irreplaceable. We know from the Rothamsted experience that the datasets available are valued assets that can be used to address multiple scientific questions, and the reuse and impact of the data can be increased by making the data accessible to the wider community. However, to do this requires active data stewardship. Long-term experiments are also available as research infrastructures, meaning external researchers can generate new datasets, additional to the routine data collected for an experiment. The publication of the FAIR data principles has provided an opportunity for us to re-evaluate what active data stewardship means for realising the potential of the data from our long-term experiments. In this paper we discuss our approach to FAIR data adoption, and the challenges for refactoring and describing existing legacy data and defining meaningful linkages between datasets.
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León-Sandoval, Edgar, Mahdi Zareei, Liliana Ibeth Barbosa-Santillán, and Luis Eduardo Falcón Morales. "Using Big Data and Serverless Architecture to Follow the Emotional Response to the COVID-19 Pandemic in Mexico." In Communications in Computer and Information Science, 145–59. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-23821-5_11.

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AbstractThe emergence of the COVID-19 pandemic has led to an unprecedented change in the lifestyle routines of millions of people. Beyond the multiple repercussions of the pandemic, we are also facing significant challenges in the population’s mental health and health programs. Typical techniques to measure the population’s mental health are semiautomatic. Social media allow us to know habits and daily life, making this data a rich silo for understanding emotional and mental well-being. This study aims to build a resilient and flexible system that allows us to track and measure the sentiment changes of a given population, in our case, the Mexican people, in response to the COVID-19 pandemic. We built an extensive data system utilizing modern cloud-based serverless architectures to analyze 760,064,879 public domain tweets collected from a public access repository to examine the collective shifts in the general mood about the pandemic evolution, news cycles, and governmental policies using open sentiment analysis tools. We provide metrics, advantages, and challenges of developing serverless cloud-based architectures for a natural language processing project of a large magnitude.
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Bergsjø, P. "Use of routinely collected data for perinatal surveillance." In Perinatal Medicine, 237–41. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4918-8_45.

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Trifirò, Gianluca, and Preciosa Coloma. "Leveraging Routinely Collected Healthcare Data to Scale Up Drug Safety Surveillance: The EU-ADR Experience." In Mann's Pharmacovigilance, 439–51. Oxford, UK: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118820186.ch28.

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Veeman, Dhinakaran, M. Varsha Shree, M. Swapna Sai, Akshita Kancharla, and Chaudhery Mustansar Hussain. "AI in Acquisition, Analysis and Processing of Medical Signal Data Collected By Wearable Devices." In Connected e-Health, 125–45. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97929-4_6.

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Watson, Meg, Emily Michels, Andrew Spieldenner, Leonard W. Ortmann, and Drue H. Barrett. "Stories, Stigma and Sequences: HIV Cluster Detection and Response Activities Through a Narrative Ethics Lens." In Public Health Ethics Analysis, 95–109. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92080-7_7.

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AbstractViral genetic sequences are generated as part of clinical care to treat people with HIV. Public health practitioners analyze these sequences, reported routinely through surveillance systems as part of disease reporting, to identify and respond to clusters of rapid HIV transmission. The ethical, social, and legal implications of this work have arisen against the backdrop of HIV stigma and amidst efforts to build trust with the HIV community. HIV disproportionately affects persons marginalized because of racism, homophobia, transphobia, or other socially stigmatized behaviors. The compounded effects of HIV and other stigmas result in barriers to care. This narrative explores several issues related to HIV cluster detection and response, including lack of individual consent for HIV surveillance, the collection of HIV genotype data, and the use of these data for public health purposes. Moreover, the potential use of these data for non-public health purposes which are likely to disproportionately impact marginalized populations also underscores the need for transparency. The characters in the narrative – public health agency staff and people with HIV – portray these issues from various perspectives. The narrative also illustrates ethical considerations related to public health activities, including a focus on population-level interventions, partnering with communities, and establishing trusting relationships.
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Lukeš, Petr. "Monitoring of Bark Beetle Forest Damages." In Big Data in Bioeconomy, 351–61. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_26.

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AbstractIn this chapter, we present a multi-source remote sensing approach for country-wise monitoring of bark beetle calamity to support government decision making processes. In the first part, we describe the forest health monitoring system, which is based on the analysis of satellite big data–Sentinel-2 observations collected every five days. We propose an automated processing chain for high-quality cloud-free image synthesis for user-defined acquisition periods. Such a processing chain is applied to yield yearly cloud-free images of the entire Czech Republic from 2015 onwards. Based on this data, we assess forest health trends using Sentinel-2 derived vegetation indices and in situ data of forest status. Finally, we demonstrate the benefits of multi-source remote sensing for timely and objective mapping of bark beetle spread by combining several data sources, including planet high-resolution satellite data, Sentinel-2 forest health maps and other maps of forest conditions. Detected bark beetle sanitary logging and dead standing wood polygons are used by the Ministry of Agriculture of Czech Republic in their decision processes regarding the management of affected forest areas.
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Brazeau, Stéphanie, Cécile Vignolles, Ramesha S. Krishnamurthy, Juli Trtanj, John Haynes, Steven Ramage, Thibault Catry, et al. "Needs, challenges, and opportunities: a review by experts." In Earth observation, public health and one health: activities, challenges and opportunities, 93–103. Wallingford: CABI, 2022. http://dx.doi.org/10.1079/9781800621183.0003.

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Abstract This book chapter discusses all the information collected has been grouped together into eight categories: (i) aligning with and supporting UN Sustainable Development Goals; (ii) focusing on public health needs and key theme areas for further research; (iii) accessing and developing Earth Observation (EO) and geospatial evidence-based data and products leveraging public health capacities; (iv) developing a sustainable community of practice; (v) developing knowledge and know-how; (vi) developing solutions: methods, tools, and systems; (vii) implementing technical infrastructures and technologies; and (viii) participating in EO satellite mission development for monitoring disease risks. One such advancement attributable to Landsat data is the ability to monitor changing patterns in forest cover loss and human encroachment on previously wild areas that allows for better prediction of zoonotic disease emergence. For example, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the US Aqua and Terra satellites offer atmosphere, land, cryosphere, and ocean products that are used in several user communities. MODIS indicator data sets have been so successful that they do not require additional remote sensing analysis; they can be used directly in predictive models. Some EO satellite systems offer ARD (i.e. pre-processed images) and related information products derived from the raw data stream generated by the satellite instruments and the use of algorithms.
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Moriarty, Frank, Wade Thompson, and Fiona Boland. "Evaluating benefits and harms of deprescribing using routinely collected data." In Contemporary Research Methods in Pharmacy and Health Services, 249–60. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-91888-6.00036-3.

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Zucker, Kieran, Millie Wagstaff, Cathy Tomson, Roger Beecham, and Geoff Hall. "AuguR: A Scalable Open-Source Interactive Web Application for Routinely Collected Data." In MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation. IOS Press, 2022. http://dx.doi.org/10.3233/shti220177.

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Most data collected by hospitals as a consequence of the delivery of routine care is not utilised for analytics or organisational intelligence. This project aims to develop tools to enhance the utilisation of routinely collected cancer data within hospitals across England. This was achieved by developing a web application using open source tools to provide health care professionals and hospital managers with easy to use, interactive analytics for cancer data. The application uses data items hospitals in England are mandated to collect as part of the Cancer Outcomes and Services Dataset (COSD), to provide clinical insight into survival outcomes, population distributions, service demands, waiting times, geographical case distributions and treatment information in real-time or near real-time. Development was guided by end user needs through the use of panels of clinical and non-clinical end users.
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Conference papers on the topic "Routinely Collected Health Data"

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Khalid, Sara, Andrew Judge, and Rafael Pinedo-Villanueva. "An Unsupervised Learning Model for Pattern Recognition in Routinely Collected Healthcare Data." In 11th International Conference on Health Informatics. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006535602660273.

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Ayorinde, AA, EA Raja, A. Shetty, PJ Danielian, and S. Bhattacharya. "OP51 Outcomes of twin pregnancies receiving antenatal corticosteroids: analysis of routinely collected obstetric data." In Society for Social Medicine 62nd Annual Scientific Meeting, Hosted by the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, 5–7 September 2018. BMJ Publishing Group Ltd, 2018. http://dx.doi.org/10.1136/jech-2018-ssmabstracts.51.

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Shearer, Jessica, David Chizhande, Rebecca Jones, and Ian A. Rowe. "PWE-089 Routinely collected health data to study the surveillance for complications of advanced chronic liver disease." In British Society of Gastroenterology, Annual General Meeting, 4–7 June 2018, Abstracts. BMJ Publishing Group Ltd and British Society of Gastroenterology, 2018. http://dx.doi.org/10.1136/gutjnl-2018-bsgabstracts.231.

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Fleetwood, KJ, SH Wild, DJ Smith, K. Licence, SW Mercer, C. Sudlow, and C. Jackson. "OP47 The impact of major mental illness on quality of care in people with type 2 diabetes in scotland: an analysis of routinely collected health data." In Society for Social Medicine and Population Health and International Epidemiology Association European Congress Annual Scientific Meeting 2019, Hosted by the Society for Social Medicine & Population Health and International Epidemiology Association (IEA), School of Public Health, University College Cork, Cork, Ireland, 4–6 September 2019. BMJ Publishing Group Ltd, 2019. http://dx.doi.org/10.1136/jech-2019-ssmabstracts.48.

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Bury, Fran, and Paula Baraitser. "P20 Patterns of oral and emergency contraception use through an online sexual health service in the UK: a quantitative study of routinely collected data." In BASHH 2022 Abstracts. BMJ Publishing Group Ltd, 2022. http://dx.doi.org/10.1136/sextrans-bashh-2022.67.

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WU, YUNING, CHI-LUEN HUANG, SANGMIN LEE, KEPING ZHANG, JOHN POPOVICS, MARCUS DERSCH, and XUAN ZHU. "RAIL NEUTRAL TEMPERATURE ESTIMATION USING ZERO GROUP VELOCITY MODES AND MACHINE LEARNING." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36296.

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With increasingly frequent extreme heat events over the past half century, thermal stress measurement and management of continuous welded rail (CWR) have become more important for railroad maintenance. Methods, including visual inspections and rail lifting, are routinely performed in railroad networks of the U.S. to prevent rail thermal buckling. When intervention becomes necessary, a rail distressing process, involving rail cutting and welding, will be performed to re-establish the zero-stress state at a desirable temperature. And the temperature at which the rail is stress-free is defined as rail neutral temperature (RNT). In this work, an RNT predictive tool that exploits zero group velocity (ZGV) modes and machine learning is proposed. First, the existence of ZGV modes in CWR is investigated through numerical simulation, using both semianalytical finite element analysis (SAFE) and finite element (FE) models. Further, parametric studies are performed to quantify the effect of axial loads and rail temperature on ZGV modes. Additionally, the team established an instrumented field test site at a revenue-service line and performed multi-day data collection to cover a wide range of temperature and thermal stress levels. FE models were calibrated based on the field-collected vibrational data via a linear program optimization approach and an excellent agreement between model and experimental results was obtained. Finally, a supervised learning framework was developed to estimate the RNT using rail temperature and resonance frequencies as the inputs. The results show that the proposed framework can provide RNT estimation with reasonable accuracy (±5 ºF) when measurement noise is low.
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Fleetwood, K., S. Wild, D. Smith, K. Licence, S. Mercer, C. Sudlow, and C. Jackson. "OP73 The impact of major mental illness on risk of stroke and myocardial infarction in people with type 2 diabetes in scotland: an analysis of routinely collected health data." In Society for Social Medicine 62nd Annual Scientific Meeting, Hosted by the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, 5–7 September 2018. BMJ Publishing Group Ltd, 2018. http://dx.doi.org/10.1136/jech-2018-ssmabstracts.72.

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Miele, Eric Stefan, Fabrizio Bonacina, Alessandro Corsini, Arianna Peruch, Marco Cannarozzo, Daniele Baldan, and Francesco Pennisi. "Unsupervised Feature Selection of Multi-Sensor SCADA Data in Horizontal Axis Wind Turbine Condition Monitoring." In ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/gt2022-82462.

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Abstract Wind power is one of the fastest-growing renewable energy sectors and is considered instrumental in the ongoing decarbonization process. However, wind turbines (WTs) present high operation and maintenance costs caused by inefficiencies and failures, leading to ever-increasing attention to effective Condition Monitoring (CM) strategies. Nowadays, modern WTs are integrated with sensor networks as part of the Supervisory Control and Data Acquisition (SCADA) system for supervision purposes. CM of wind farms through predictive models based on routinely collected SCADA data is envisaged as a viable mean of improving producibility by spotting operational inefficiencies. However, given the large number of variables monitored by SCADA systems, selecting those that contribute the most to the modelling of wind turbine health conditions is an open challenge. In this paper, we propose an unsupervised feature selection algorithm based on a novel multivariate Predictive Power Score (PPS). Unlike other approaches in literature that only consider relationships between pairs of variables, here we propose a Combined PPS (CPPS), where the information content of combinations of variables is considered for the prediction of one or more key parameters. The algorithm has been tested on 9 turbines belonging to the same wind farm located in the Italian territory. The results show that the proposed approach is more flexible and outperforms standard PPS.
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Sari, Dewi Indah, Afni Yulianti, and Ninik Wahyuni. "Effectiveness of Cookies Produced From Moringa Oleifera Leaves on Haemoglobin Level in Students at Islamic Junior High School Miftahul Hayat, Serang, Banten." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.05.28.

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ABSTRACT Background: Anemia is very common in developing countries and is one of the most common complications of serious diseases. Based on the results of screening the Hb levels student at islamic junior high school Miftahul Hayat in 2018, it was found that 37 students had anemia. This study aimed to determine the effectiveness of cookies produced from moringa oleifera leaves on haemoglobin level in students at Islamic Junior High school Miftahul Hayat, Serang, Banten. Subjects and Method: This was a quasi-experimental. A sample of 37 students of MTS Miftahul Hayat, Serang, Banten and randomly allocated into two groups: intervention and control groups. The dependent variable was an increase in hemoglobin value. The independent variable was anemic student. The data were collected from checklist and analyzed using paired t- test. Results: The results of this study were obtained by respondents as many as 33 people because during the research process 4 people did not consume cookies produced from Moringa Oleifera leaves routinely for 14 days because they were sick so they were excluded from the study sample. Hb level before consume consume cookies produced from Moringa Oleifera leaves (Mean = 10.5 gr/ dl; SD= 0.56; p< 0.001). Hb level after consume cookies produced from Moringa Oleifera leaves (Mean= 13 gr/ dl; SD= 0.85). The difference in Hb levels (Mean = 2.5; SD = 0.88; p <0.001), and it was statically significant (p< 0.001) Conclusion: Consume cookies produced from Moringa Oleifera leaves is effective to improve haemoglobin levels in adolescent. Keywords: anemia, teenager, moringa oleifera leaves cookies Correspondence: Dewi Indah Sari. School of Health Polytechnics, Banten. Jl.Dr.Sitanala Kec.Neglasari Kota Tangerang. Email: dewi.indah@poltekkesbanten.ac.id Mobile:+6281906061400 DOI: https://doi.org/10.26911/the7thicph.05.28
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Khalid, Sara, M. Sanni Ali, and Daniel Prieto-Alhambra. "Cluster Analysis to Detect Patterns of Drug Use from Routinely Collected Medical Data." In 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2018. http://dx.doi.org/10.1109/cbms.2018.00041.

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Reports on the topic "Routinely Collected Health Data"

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Kingston, A. W., A. Mort, C. Deblonde, and O H Ardakani. Hydrogen sulfide (H2S) distribution in the Triassic Montney Formation of the Western Canadian Sedimentary Basin. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329797.

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The Montney Formation is a highly productive hydrocarbon reservoir with significant reserves of hydrocarbon gases and liquids making it of great economic importance to Canada. However, high concentrations of hydrogen sulfide (H2S) have been encountered during exploration and development that have detrimental effects on environmental, health, and economics of production. H2S is a highly toxic and corrosive gas and therefore it is essential to understand the distribution of H2S within the basin in order to enhance identification of areas with a high risk of encountering elevated H2S concentrations in order to mitigate against potential negative impacts. Gas composition data from Montney wells is routinely collected by operators for submission to provincial regulators and is publicly available. We have combined data from Alberta (AB) and British Columbia (BC) to create a basin-wide database of Montney H2S concentrations. We then used an iterative quality control and quality assurance process to produce a dataset that best represents gas composition in reservoir fluids. This included: 1) designating gas source formation based on directional surveys using a newly developed basin-wide 3D model incorporating AGS's Montney model of Alberta with a model in BC, which removes errors associated with reported formations; 2) removed injection and disposal wells; 3) assessed wells with the 50 highest H2S concentrations to determine if gas composition data is accurate and reflective of reservoir fluid chemistry; and 4) evaluated spatially isolated extreme values to ensure data accuracy and prevent isolated highs from negatively impacting data interpolation. The resulting dataset was then used to calculate statistics for each x, y location to input into the interpolation process. Three interpolations were constructed based on the associated phase classification: H2S in gas, H2S in liquid (C7+), and aqueous H2S. We used Empirical Bayesian Kriging interpolation to generate H2S distribution maps along with a series of model uncertainty maps. These interpolations illustrate that H2S is heterogeneously distributed across the Montney basin. In general, higher concentrations are found in AB compared with BC with the highest concentrations in the Grande Prairie region along with several other isolated region in the southeastern portion of the basin. The interpolations of H2S associated with different phases show broad similarities. Future mapping research will focus on subdividing intra-Montney sub-members plus under- and overlying strata to further our understanding of the role migration plays in H2S distribution within the Montney basin.
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Chaparadza, Diana. An Analysis of Patient-Generated Health Data in Assisting Nurses and Physicians to Better Treat Patients with Hypertension. University of Tennessee Health Science Center, November 2020. http://dx.doi.org/10.21007/chp.hiim.0080.

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Patient Generated Health Data (PGHD is not new but it has gained more attention these past years due to the advent of smart devices, remote monitoring devices and many applications on various smart devices. PGHD reflects medications and treatment, lifestyle choices, and health history. Unlike traditional medical visits, where clinicians collect and manage data within their offices, PGHD is collected by patients throughout the course of their day and provides an insight of how they are responding to treatments or lifestyle choices. Examples include blood glucose monitoring or blood pressure readings using home health equipment, exercise and diet tracking using mobile applications or wearable devices such as the Fitbit or other smart watches.
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Tronstad, Lusha. Aquatic invertebrate monitoring at Agate Fossil Beds National Monument: 2019 data report. National Park Service, April 2022. http://dx.doi.org/10.36967/nrds-2293128.

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Monitoring ecosystems is vital to understanding trends over time and key to detecting change so that managers can address perturbations. Freshwater streams are the lifeblood of the surrounding landscape, and their health is a measure of the overall watershed integrity. Streams are the culmination of upland processes and inputs. Degradation on the landscape as well as changes to the stream itself can be detected using biota living in these ecosystems. Aquatic invertebrates are excellent indicators of ecosystem quality because they are relatively long-lived, sessile, diverse, abundant and their tolerance to perturbation differs. Aquatic invertebrates were monitored at three sites along the Niobrara River at Agate Fossil Beds National Monument in 2019 completing 23 years of data using Hester-Dendy and Hess samplers. Hess samplers are artificial multi-plate samplers suspended in the water column to allow invertebrates to colonize and Hess samples collect invertebrates in a known area on natural substrate and vegetation. We identified 45 invertebrate taxa from four phyla (Annelida, Arthropoda, Mollusca, Nematoda) using both samplers in the Niobrara River (Appendix A and B). Hester-Dendy samplers collected 4 taxa not found in Hess samples and Hess samples collected 17 taxa not collected with Hester-Dendy samplers. Hess samples captured more (91%) than Hester-Dendy samples (62%). Crustacea, Diptera and Ephemeroptera were the most abundant groups of invertebrates collected in the Niobrara River. The proportion of Insecta, Annelida, Trichoptera and Diptera differed between Hester-Dendy and Hess samples (p < 0.05). EPT richness, proportion EPT taxa and Hilsenhoff’s Biotic Index (HBI) (p < 0.0001) differed between sampler types, but taxa richness, taxa diversity and evenness (p > 0.29) did not. We collected the highest density of invertebrates at the Agate Middle site. Agate Spring Ranch had the lowest taxa richness and HBI, and the highest proportion of EPT taxa. HBI at the sites ranged from 4.0 to 6.3 (very good to fair from Hilsenhoff 1987) using the Hester-Dendy and 5.2 to 6.9 (good to fairly poor from Hilsenhoff 1987) using the Hess sampler.
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Rohwerder, Brigitte. Sexual Exploitation, Abuse and Harassment in the Food Security Sector. Institute of Development Studies, February 2022. http://dx.doi.org/10.19088/k4d.2022.062.

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Globally food insecurity is rising, especially for women and girls, potentially placing them at increased risk of sexual exploitation and abuse in their attempts to access food. Most of the existing literature focuses on sexual exploitation and abuse than on sexual harassment, and the literature focusing on sexual harassment tended not to specify the organisations involved making it hard to identify if they are in the food security sector. Most of the literature seems to focus on sexual exploitation and abuse relating to food security in humanitarian rather than other settings Sexual exploitation and abuse and sexual harassment is widely underreported across the aid sector and data is not routinely collected indicating whether or not the case relates to food security programming. This report thus aims to discover what is known about the particular risks and incidence of sexual exploitation and abuse and sexual harassment in the food security sector, and what learning is there on effective risk analysis and management. Several recommendations from the literature for food security actors are provided at the end of the report, including suggestions from beneficiaries for measures that could be taken to make food distribution processes safer.
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Rudd, Ian. Leveraging Artificial Intelligence and Robotics to Improve Mental Health. Intellectual Archive, July 2022. http://dx.doi.org/10.32370/iaj.2710.

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Artificial Intelligence (AI) is one of the oldest fields of computer science used in building structures that look like human beings in terms of thinking, learning, solving problems, and decision making (Jovanovic et al., 2021). AI technologies and techniques have been in application in various aspects to aid in solving problems and performing tasks more reliably, efficiently, and effectively than what would happen without their use. These technologies have also been reshaping the health sector's field, particularly digital tools and medical robotics (Dantas & Nogaroli, 2021). The new reality has been feasible since there has been exponential growth in the patient health data collected globally. The different technological approaches are revolutionizing medical sciences into dataintensive sciences (Dantas & Nogaroli, 2021). Notably, with digitizing medical records supported the increasing cloud storage, the health sector created a vast and potentially immeasurable volume of biomedical data necessary for implementing robotics and AI. Despite the notable use of AI in healthcare sectors such as dermatology and radiology, its use in psychological healthcare has neem models. Considering the increased mortality and morbidity levels among patients with psychiatric illnesses and the debilitating shortage of psychological healthcare workers, there is a vital requirement for AI and robotics to help in identifying high-risk persons and providing measures that avert and treat mental disorders (Lee et al., 2021). This discussion is focused on understanding how AI and robotics could be employed in improving mental health in the human community. The continued success of this technology in other healthcare fields demonstrates that it could also be used in redefining mental sicknesses objectively, identifying them at a prodromal phase, personalizing the treatments, and empowering patients in their care programs.
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Casper, Gary, Stefanie Nadeau, and Thomas Parr. Acoustic amphibian monitoring, 2019 data summary: Sleeping Bear Dunes National Lakeshore. National Park Service, December 2022. http://dx.doi.org/10.36967/2295512.

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Amphibians are a Vital Sign indicator for monitoring long-term ecosystem health in seven national park units that comprise the Great Lakes Network. We present here the results for 2019 amphibian monitoring at Sleeping Bear Dunes National Lakeshore (SLBE). Appendices contain tabular summaries for six years of cumulative results. The National Park Service Great Lakes Inventory and Monitoring Network established 10 permanent acoustic amphibian monitoring sites at SLBE in 2013. Acoustic samples are collected by placing automated recorders with omnidirectional stereo microphones at each of the 10 sampling sites. Temperature loggers co-located with the recorders also collect air temperature during the sampling period. We expanded analyses and reporting in 2018 to address calling phenology and to provide a second metric for tracking changes in abundance across years. Occupancy analyses track whether or not a site was occupied by a species. Abundance is tracked by assessing how the maximum call intensity changes on sites across years, and by how many automated detections are reported from sites across years. Using two independent survey methods, manual and automated, with large sample sizes continues to return reliable results, providing a confident record of site occupancy for most species. The monitoring program detected five of the six species of frog and toad known to occur at SLBE in 2019, with Eastern American Toad, Gray Treefrog, Green Frog and Spring Peeper occurring at almost every site sampled. Wood Frog was found at one new site, and Northern Leopard Frog was not confirmed in 2019 but was detected at five sites in 2018. There were no significant data collection issues in 2019 except for late deployment of SLBE11, which limited data analyses for this site. Remaining sites successfully collected data as programmed. Cumulative data collection result summaries since inception are provided in appendices. Since temperature logs show that the threshold of ≥40°F was often exceeded by 1 April in 2019, making 15 March a start date for data collection may be considered if park personnel feel snow and ice cover would be reduced enough by that date as well.
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Casper, Gary, Stefanie Nadeau, and Thomas Parr. Acoustic amphibian monitoring, 2019 data summary: Pictured Rocks National Lakeshore. National Park Service, December 2022. http://dx.doi.org/10.36967/2295509.

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Amphibians are a Vital Sign indicator for monitoring long-term ecosystem health in seven national park units that comprise the Great Lakes Network. We present here the results for 2019 amphibian monitoring at Pictured Rocks National Lakeshore (PIRO). Appendices contain tabular summaries for six years of cumulative results. The National Park Service Great Lakes Inventory and Monitoring Network established 10 permanent acoustic amphibian monitoring sites at PIRO in 2013. Acoustic samples are collected by placing automated recorders with omnidirectional stereo microphones at each of the 10 sampling sites. Temperature loggers co-located with the recorders also collect air temperature during the sampling period. We expanded analyses and reporting in 2018 to address calling phenology and to provide a second metric for tracking changes in abundance across years. Occupancy analyses track whether or not a site was occupied by a species. Abundance is tracked by assessing how the maximum call intensity changes on sites across years, and by how many automated detections are reported from sites across years. Using two independent survey methods, manual and automated, with large sample sizes continues to return reliable results, providing a confident record of site occupancy for most species. The monitoring program detected five of the six species of frog and toad known to occur at PIRO in 2019, with Eastern American Toad, Gray Treefrog, Green Frog, and Spring Peeper occurring at almost every site sampled. Wood Frog was found at five sites. Mink Frog is known to occur at Sand Point but has never been confirmed at sites monitored by this GLKN program. Additional species of potential occurrence remain hypothetical (i.e., Northern Leopard Frog). The only significant data collection issue in 2019 was at PIRO02, where the equipment recorded only intermittently resulting in only partial data analysis possible. Remaining sites successfully collected data as programmed. Cumulative program result summaries since inception are provided in appendices. Temperature logs in 2019 showed that the threshold of ≥40°F was uniformly exceeded by 1 May, hence we recommend making 10 April the target start date for data collection in future. This could be accomplished by fall deployment of recorders on delayed starts. We also recommend making sure that recorders are mounted 6–10 feet high to better survey the soundscape with less interference from foliage, and that temperature loggers be placed within solar shields.
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Leavy, Michelle B., Danielle Cooke, Sarah Hajjar, Erik Bikelman, Bailey Egan, Diana Clarke, Debbie Gibson, Barbara Casanova, and Richard Gliklich. Outcome Measure Harmonization and Data Infrastructure for Patient-Centered Outcomes Research in Depression: Report on Registry Configuration. Agency for Healthcare Research and Quality (AHRQ), November 2020. http://dx.doi.org/10.23970/ahrqepcregistryoutcome.

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Background: Major depressive disorder is a common mental disorder. Many pressing questions regarding depression treatment and outcomes exist, and new, efficient research approaches are necessary to address them. The primary objective of this project is to demonstrate the feasibility and value of capturing the harmonized depression outcome measures in the clinical workflow and submitting these data to different registries. Secondary objectives include demonstrating the feasibility of using these data for patient-centered outcomes research and developing a toolkit to support registries interested in sharing data with external researchers. Methods: The harmonized outcome measures for depression were developed through a multi-stakeholder, consensus-based process supported by AHRQ. For this implementation effort, the PRIME Registry, sponsored by the American Board of Family Medicine, and PsychPRO, sponsored by the American Psychiatric Association, each recruited 10 pilot sites from existing registry sites, added the harmonized measures to the registry platform, and submitted the project for institutional review board review Results: The process of preparing each registry to calculate the harmonized measures produced three major findings. First, some clarifications were necessary to make the harmonized definitions operational. Second, some data necessary for the measures are not routinely captured in structured form (e.g., PHQ-9 item 9, adverse events, suicide ideation and behavior, and mortality data). Finally, capture of the PHQ-9 requires operational and technical modifications. The next phase of this project will focus collection of the baseline and follow-up PHQ-9s, as well as other supporting clinical documentation. In parallel to the data collection process, the project team will examine the feasibility of using natural language processing to extract information on PHQ-9 scores, adverse events, and suicidal behaviors from unstructured data. Conclusion: This pilot project represents the first practical implementation of the harmonized outcome measures for depression. Initial results indicate that it is feasible to calculate the measures within the two patient registries, although some challenges were encountered related to the harmonized definition specifications, the availability of the necessary data, and the clinical workflow for collecting the PHQ-9. The ongoing data collection period, combined with an evaluation of the utility of natural language processing for these measures, will produce more information about the practical challenges, value, and burden of using the harmonized measures in the primary care and mental health setting. These findings will be useful to inform future implementations of the harmonized depression outcome measures.
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9

Boyle, Maxwell, and Elizabeth Rico. Terrestrial vegetation monitoring at Fort Pulaski National Monument: 2019 data summary. National Park Service, December 2021. http://dx.doi.org/10.36967/nrds-2288716.

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The Southeast Coast Network (SECN) conducts long-term terrestrial vegetation monitoring as part of the nationwide Inventory and Monitoring Program of the National Park Service (NPS). The vegetation community vital sign is one of the primary-tier resources identified by SECN park managers, and monitoring is currently conducted at 15 network parks (DeVivo et al. 2008). Monitoring plants and their associated communities over time allows for targeted understanding of ecosystems within the SECN geography, which provides managers information about the degree of change within their parks’ natural vegetation. 2019 marks the first year of conducting this monitoring effort on four SECN parks, including Fort Pulaski National Monument (FOPU). Twelve vegetation plots were established at Fort Pulaski National Monument in August. Data collected in each plot included species richness across multiple spatial scales, species-specific cover and constancy, species-specific woody stem seedling/sapling counts and adult tree (greater than 10 centimeters [3.9 inches {in}]) diameter at breast height (DBH), overall tree health, landform, soil, observed disturbance, and woody biomass (i.e., fuel load) estimates. This report summarizes the baseline (year 1) terrestrial vegetation data collected at Fort Pulaski National Monument in 2019. Data were stratified across two dominant broadly defined habitats within the park (Maritime Tidal Wetlands and Maritime Upland Forests and Shrublands). Noteworthy findings include: Sixty-six vascular plant taxa were observed across 12 vegetation plots, including six taxa not previously known from the park. Plots were located on both Cockspur and McQueen’s Island. The most frequently encountered species in each broadly defined habitat included: Maritime Tidal Wetlands: smooth cordgrass (Spartina alterniflora), perennial saltmarsh aster(Symphyotrichum enuifolium), and groundsel tree (Baccharis halimifolia) Maritime Upland Forests and Shrublands: yaupon (Ilex vomitoria), southern/eastern red cedar (Juniperus silicicola + virginiana), and cabbage palmetto (Sabal palmetto). Four non-native species identified as invasive by the Georgia Exotic Pest Plant Council (GA-EPPC 2018) were found during this monitoring effort. These species (and their overall frequency of occurrence within all plots) included: Japanese honeysuckle (Lonicera japonica; 17%), bahiagrass (Paspalum notatum; 8%), Vasey’s grass (Paspalum urvillei; 8%), and European common reed (Phragmites australis; 8%). Two rare plants tracked by the Georgia Department of Natural Resources (GADNR 2013) were found during this monitoring effort. These include Florida wild privet (Forestiera segregata) and Bosc’s bluet (Oldenlandia boscii). Southern/eastern red cedar and cabbage palmetto were the most dominant species within the tree stratum of the maritime Upland Forest and Shrubland habitat type. Species that dominated the sapling and seedling strata of this type included yaupon, cabbage palmetto, groundsel tree, and Carolina laurel cherry (Prunus caroliniana). The health status of sugarberry (Celtis laevigata)—a typical canopy species in maritime forests of the South Atlantic Coastal Plain--observed on park plots appeared to be in decline, with most stems experiencing elevated levels of dieback and low vigor. Over the past decade, this species has been experiencing unexplained high rates of dieback and mortality throughout its range in the Southeastern United States; current research is focusing on what may be causing these alarming die-off patterns. Duff and litter made up the majority of downed woody biomass (fuel loads) across FOPU vegetation plots.
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10

Boyle, Maxwell, and Elizabeth Rico. Terrestrial vegetation monitoring at Cape Hatteras National Seashore: 2019 data summary. National Park Service, January 2022. http://dx.doi.org/10.36967/nrr-2290019.

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The Southeast Coast Network (SECN) conducts long-term terrestrial vegetation monitoring as part of the nationwide Inventory and Monitoring Program of the National Park Service (NPS). The vegetation community vital sign is one of the primary-tier resources identified by SECN park managers, and monitoring is currently conducted at 15 network parks (DeVivo et al. 2008). Monitoring plants and their associated communities over time allows for targeted understanding of ecosystems within the SECN geography, which provides managers information about the degree of change within their parks’ natural vegetation. The first year of conducting this monitoring effort at four SECN parks, including 52 plots on Cape Hatteras National Seashore (CAHA), was 2019. Twelve vegetation plots were established at Cape Hatteras NS in July and August. Data collected in each plot included species richness across multiple spatial scales, species-specific cover and constancy, species-specific woody stem seedling/sapling counts and adult tree (greater than 10 centimeters [3.9 inches {in}]) diameter at breast height (DBH), overall tree health, landform, soil, observed disturbance, and woody biomass (i.e., fuel load) estimates. This report summarizes the baseline (year 1) terrestrial vegetation data collected at Cape Hatteras National Seashore in 2019. Data were stratified across four dominant broadly defined habitats within the park (Maritime Tidal Wetlands, Maritime Nontidal Wetlands, Maritime Open Uplands, and Maritime Upland Forests and Shrublands) and four land parcels (Bodie Island, Buxton, Hatteras Island, and Ocracoke Island). Noteworthy findings include: A total of 265 vascular plant taxa (species or lower) were observed across 52 vegetation plots, including 13 species not previously documented within the park. The most frequently encountered species in each broadly defined habitat included: Maritime Tidal Wetlands: saltmeadow cordgrass Spartina patens), swallow-wort (Pattalias palustre), and marsh fimbry (Fimbristylis castanea) Maritime Nontidal Wetlands: common wax-myrtle (Morella cerifera), saltmeadow cordgrass, eastern poison ivy (Toxicodendron radicans var. radicans), and saw greenbriar (Smilax bona-nox) Maritime Open Uplands: sea oats (Uniola paniculata), dune camphorweed (Heterotheca subaxillaris), and seabeach evening-primrose (Oenothera humifusa) Maritime Upland Forests and Shrublands: : loblolly pine (Pinus taeda), southern/eastern red cedar (Juniperus silicicola + virginiana), common wax-myrtle, and live oak (Quercus virginiana). Five invasive species identified as either a Severe Threat (Rank 1) or Significant Threat (Rank 2) to native plants by the North Carolina Native Plant Society (Buchanan 2010) were found during this monitoring effort. These species (and their overall frequency of occurrence within all plots) included: alligatorweed (Alternanthera philoxeroides; 2%), Japanese honeysuckle (Lonicera japonica; 10%), Japanese stilt-grass (Microstegium vimineum; 2%), European common reed (Phragmites australis; 8%), and common chickweed (Stellaria media; 2%). Eighteen rare species tracked by the North Carolina Natural Heritage Program (Robinson 2018) were found during this monitoring effort, including two species—cypress panicgrass (Dichanthelium caerulescens) and Gulf Coast spikerush (Eleocharis cellulosa)—listed as State Endangered by the Plant Conservation Program of the North Carolina Department of Agriculture and Consumer Services (NCPCP 2010). Southern/eastern red cedar was a dominant species within the tree stratum of both Maritime Nontidal Wetland and Maritime Upland Forest and Shrubland habitat types. Other dominant tree species within CAHA forests included loblolly pine, live oak, and Darlington oak (Quercus hemisphaerica). One hundred percent of the live swamp bay (Persea palustris) trees measured in these plots were experiencing declining vigor and observed with symptoms like those caused by laurel wilt......less
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