Using digital tools in clinical, health and social care research: a mixed-methods study of UK stakeholders.

OBJECTIVE: The COVID-19 pandemic accelerated changes to clinical research methodology, with clinical studies being carried out via online/remote means. This mixed-methods study aimed to identify which digital tools are currently used across all stages of clinical research by stakeholders in clinical, health and social care research and investigate their experience using digital tools. DESIGN: Two online surveys followed by semistructured interviews were conducted. Interviews were audiorecorded, transcribed and analysed thematically. SETTING, PARTICIPANTS: To explore the digital tools used since the pandemic, survey participants (researchers and related staff (n=41), research and development staff (n=25)), needed to have worked on clinical, health or social care research studies over the past 2 years (2020-2022) in an employing organisation based in the West Midlands region of England (due to funding from a regional clinical research network (CRN)). Survey participants had the opportunity to participate in an online qualitative interview to explore their experiences of digital tools in greater depth (n=8). RESULTS: Six themes were identified in the qualitative interviews: 'definition of a digital tool in clinical research'; 'impact of the COVID-19 pandemic'; 'perceived benefits/drawbacks of digital tools'; 'selection of a digital tool'; 'barriers and overcoming barriers' and 'future digital tool use'. The context of each theme is discussed, based on the interview results. CONCLUSIONS: Findings demonstrate how digital tools are becoming embedded in clinical research, as well as the breadth of tools used across different research stages. The majority of participants viewed the tools positively, noting their ability to enhance research efficiency. Several considerations were highlighted; concerns about digital exclusion; need for collaboration with digital expertise/clinical staff, research on tool effectiveness and recommendations to aid future tool selection. There is a need for the development of resources to help optimise the selection and use of appropriate digital tools for clinical research staff and participants.

Replicability and reproducibility of predictive models for diagnosis of depression among young adults using Electronic Health Records.

BACKGROUND: Recent advances in machine learning combined with the growing availability of digitized health records offer new opportunities for improving early diagnosis of depression. An emerging body of research shows that Electronic Health Records can be used to accurately predict cases of depression on the basis of individual's primary care records. The successes of these studies are undeniable, but there is a growing concern that their results may not be replicable, which could cast doubt on their clinical usefulness. METHODS: To address this issue in the present paper, we set out to reproduce and replicate the work by Nichols et al. (2018), who trained predictive models of depression among young adults using Electronic Healthcare Records. Our contribution consists of three parts. First, we attempt to replicate the methodology used by the original authors, acquiring a more up-to-date set of primary health care records to the same specification and reproducing their data processing and analysis. Second, we test models presented in the original paper on our own data, thus providing out-of-sample prediction of the predictive models. Third, we extend past work by considering several novel machine-learning approaches in an attempt to improve the predictive accuracy achieved in the original work. RESULTS: In summary, our results demonstrate that the work of Nichols et al. is largely reproducible and replicable. This was the case both for the replication of the original model and the out-of-sample replication applying NRCBM coefficients to our new EHRs data. Although alternative predictive models did not improve model performance over standard logistic regression, our results indicate that stepwise variable selection is not stable even in the case of large data sets. CONCLUSION: We discuss the challenges associated with the research on mental health and Electronic Health Records, including the need to produce interpretable and robust models. We demonstrated some potential issues associated with the reliance on EHRs, including changes in the regulations and guidelines (such as the QOF guidelines in the UK) and reliance on visits to GP as a predictor of specific disorders.

Prediction and diagnosis of depression using machine learning with electronic health records data: a systematic review.

BACKGROUND: Depression is one of the most significant health conditions in personal, social, and economic impact. The aim of this review is to summarize existing literature in which machine learning methods have been used in combination with Electronic Health Records for prediction of depression. METHODS: Systematic literature searches were conducted within arXiv, PubMed, PsycINFO, Science Direct, SCOPUS and Web of Science electronic databases. Searches were restricted to information published after 2010 (from 1st January 2011 onwards) and were updated prior to the final synthesis of data (27th January 2022). RESULTS: Following the PRISMA process, the initial 744 studies were reduced to 19 eligible for detailed evaluation. Data extraction identified machine learning methods used, types of predictors used, the definition of depression, classification performance achieved, sample size, and benchmarks used. Area Under the Curve (AUC) values more than 0.9 were claimed, though the average was around 0.8. Regression methods proved as effective as more developed machine learning techniques. LIMITATIONS: The categorization, definition, and identification of the numbers of predictors used within models was sometimes difficult to establish, Studies were largely Western Educated Industrialised, Rich, Democratic (WEIRD) in demography. CONCLUSION: This review supports the potential use of machine learning techniques with Electronic Health Records for the prediction of depression. All the selected studies used clinically based, though sometimes broad, definitions of depression as their classification criteria. The reported performance of the studies was comparable to or even better than that found in primary care. There are concerns with generalizability and interpretability.

Evidence for feasibility of implementing online brief cognitive-behavioral therapy for eating disorder pathology in the workplace.

OBJECTIVE: CBT-T is a brief (10-week) cognitive-behavioral therapy for non-underweight eating disorders. This report describes the findings from a single center, single group, feasibility trial of online CBT-T in the workplace as an alternative to health service settings. METHOD: This trial was approved by the Biomedical and Scientific Research Ethics committee, University of Warwick, UK (reference 125/20-21) and was registered with ISRCTN (reference number: ISRCTN45943700). Recruitment was based on self-reported eating and weight concerns rather than diagnosis, potentially enabling access to treatment for employees who have not previously sought help and for those with sub-threshold eating disorder symptoms. Assessments took place at baseline, mid-treatment (week 4), post-treatment (week 10), and follow-up (1 and 3 months post-treatment). Participant experiences following treatment were assessed using quantitative and qualitative approaches. RESULTS: For the primary outcomes, pre-determined benchmarks of high feasibility and acceptability were met, based on recruiting >40 participants (N = 47), low attrition (38%), and a high attendance rate (98%) over the course of the therapy. Participant experiences revealed low previous help-seeking for eating disorder concerns (21%). Qualitative findings indicated a wide range of positive impacts of the therapy and the workplace as the therapeutic setting. Analysis of secondary outcomes for participants with clinical and sub-threshold eating disorder symptoms showed strong effect sizes for eating pathology, anxiety and depression, and moderate effect sizes for work outcomes. DISCUSSION: These pilot findings provide a strong rationale for a fully powered randomized controlled trial to determine the effectiveness of CBT-T in the workplace. PUBLIC SIGNIFICANCE: This study demonstrates the feasibility of implementing an eating disorders intervention (online CBT-T) in the workplace as an alternative to traditional healthcare settings. Recruitment was based on self-reported eating and weight concerns rather than diagnosis, potentially enabling access to treatment for employees who had not previously sought help. The data also provide insights into recruitment, acceptability, effectiveness, and future viability of CBT-T in the workplace.

Machine learning models to detect anxiety and depression through social media: A scoping review.

Despite improvement in detection rates, the prevalence of mental health disorders such as anxiety and depression are on the rise especially since the outbreak of the COVID-19 pandemic. Symptoms of mental health disorders have been noted and observed on social media forums such Facebook. We explored machine learning models used to detect anxiety and depression through social media. Six bibliographic databases were searched for conducting the review following PRISMA-ScR protocol. We included 54 of 2219 retrieved studies. Users suffering from anxiety or depression were identified in the reviewed studies by screening their online presence and their sharing of diagnosis by patterns in their language and online activity. Majority of the studies (70%, 38/54) were conducted at the peak of the COVID-19 pandemic (2019-2020). The studies made use of social media data from a variety of different platforms to develop predictive models for the detection of depression or anxiety. These included Twitter, Facebook, Instagram, Reddit, Sina Weibo, and a combination of different social sites posts. We report the most common Machine Learning models identified. Identification of those suffering from anxiety and depression disorders may be achieved using prediction models to detect user's language on social media and has the potential to complimenting traditional screening. Such analysis could also provide insights into the mental health of the public especially so when access to health professionals can be restricted due to lockdowns and temporary closure of services such as we saw during the peak of the COVID-19 pandemic.

Pandemic and student mental health: mental health symptoms among university students and young adults after the first cycle of lockdown in the UK.

BACKGROUND: Early COVID-19 research suggests a detrimental impact of the initial lockdown on young people's mental health. AIMS: We investigated mental health among university students and young adults after the first UK lockdown and changes in symptoms over 6 months. METHOD: In total, 895 university students and 547 young adults not in higher education completed an online survey at T1 (July-September 2020). A subset of 201 university students also completed a 6 month follow-up survey at T2 (January-March 2021). Anxiety, depression, insomnia, substance misuse and suicide risk were assessed. RESULTS: At T1, approximately 40%, 25% and 33% of the participants reported moderate to severe anxiety and depression and substance misuse risk, clinically significant insomnia and suicidal risk. In participants reassessed at T2, reductions were observed in anxiety and depression but not in insomnia, substance misuse or suicidality. Student and non-student participants reported similar levels of mental health symptoms. Student status was not a significant marker of mental health symptoms, except for lower substance misuse risk.Cross-sectionally, greater symptoms across measures were consistently associated with younger age, pre-existing mental health conditions, being a carer, worse financial status, increased sleep irregularity and difficulty since lockdown. Longitudinally, T2 symptoms were consistently associated with worse financial status and increased difficulty sleeping at T1. However, these associations were attenuated when baseline mental health symptoms were adjusted for in the models. CONCLUSIONS: Mental health symptoms were prevalent in a large proportion of young people after the first UK lockdown. Risk factors identified may help characterise high-risk groups for enhanced support and inform interventions.

The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review.

Artificial intelligence (AI) has been successfully exploited in diagnosing many mental disorders. Numerous systematic reviews summarize the evidence on the accuracy of AI models in diagnosing different mental disorders. This umbrella review aims to synthesize results of previous systematic reviews on the performance of AI models in diagnosing mental disorders. To identify relevant systematic reviews, we searched 11 electronic databases, checked the reference list of the included reviews, and checked the reviews that cited the included reviews. Two reviewers independently selected the relevant reviews, extracted the data from them, and appraised their quality. We synthesized the extracted data using the narrative approach. We included 15 systematic reviews of 852 citations identified. The included reviews assessed the performance of AI models in diagnosing Alzheimer's disease (n = 7), mild cognitive impairment (n = 6), schizophrenia (n = 3), bipolar disease (n = 2), autism spectrum disorder (n = 1), obsessive-compulsive disorder (n = 1), post-traumatic stress disorder (n = 1), and psychotic disorders (n = 1). The performance of the AI models in diagnosing these mental disorders ranged between 21% and 100%. AI technologies offer great promise in diagnosing mental health disorders. The reported performance metrics paint a vivid picture of a bright future for AI in this field. Healthcare professionals in the field should cautiously and consciously begin to explore the opportunities of AI-based tools for their daily routine. It would also be encouraging to see a greater number of meta-analyses and further systematic reviews on performance of AI models in diagnosing other common mental disorders such as depression and anxiety.

Effects of a hybrid digital cognitive-behavioural therapy for insomnia and emotion regulation in the workplace (SLEEP): study protocol for a randomised waitlist control trial.

INTRODUCTION: This trial tests the efficacy of implementing a hybrid digital cognitive-behavioural therapy for insomnia (dCBT-I) and emotion regulation (ER) in the workplace. The study protocol follows the SPIRIT (Standard Protocol Items: Recommendations for Intervention Trials) 2013 recommendations. METHODS AND ANALYSIS: This is a mixed methods evaluation with a two-arm randomised waitlist control design of a 6-week dCBT-I+ER intervention through self-guided online platform and four videoconferencing therapy sessions. A process evaluation will examine the fidelity of delivery and experiences of the intervention. The primary outcomes are the Insomnia Severity Index, the Patient Health Questionnaire-9 and the Generalised Anxiety Disorder-7. The secondary outcomes are job productivity, job satisfaction, well-being, quality of life, self-reported (sleep diary data) and objective (actigraphy) sleep parameters, and usage of online intervention platform. Assessments take place at baseline (T0), week 8 post-treatment (T1) and week 12 postrandomisation (T2). We will recruit 156 workers with sleep and ER problems ranging from subclinical to clinical levels not engaged in treatment at the time of the trial. ETHICS AND DISSEMINATION: Full approval was given by the University of Warwick Biomedical and Research Ethics Committee (BSREC 45/20-21). The current protocol version is 2.9_Dec21. Publication of results will inform the scientific, clinical and business communities through peer-reviewed articles, webinars, conferences and newsletters. TRIAL REGISTRATION NUMBER: ISRCTN13596153.

A feasibility study of the delivery of online brief cognitive-behavioral therapy (CBT-T) for eating disorder pathology in the workplace.

OBJECTIVE: CBT-T is a brief (10 sessions) version of cognitive behavioral therapy for non-underweight eating disorders. This report describes the protocol for a single center, single group, feasibility trial of online CBT-T in the workplace as an alternative to the health-service setting. By offering mental health services for eating disorders in the workplace, greater accessibility and increased help-seeking behaviors could be achieved. METHOD: Treatment will be delivered online over 10 weeks and offered to employees based on self-referral rather than meeting diagnostic criteria, making treatment available to employees with sub-threshold eating disorder symptoms. RESULTS: Assessments will be conducted at baseline, mid-treatment (week 4), posttreatment (week 10) and at follow-up (1 month and 3 months posttreatment). For the primary outcome, measures will include recruitment, attrition and attendance data using pre-set benchmarks to determine high, medium or low feasibility and acceptability. Qualitative participant experiences data will be analyzed using thematic analysis. Impact on work engagement and effect sizes will be determined from secondary outcome measures; the latter enabling sample size calculations for future study. DISCUSSION: These pilot data will provide insights to recruitment, acceptability, effectiveness and viability of a future fully powered clinical trial of online CBT-T in the workplace. PUBLIC SIGNIFICANCE STATEMENT: This study will present feasibility data from an eating disorders intervention (online CBT-T) using the workplace as an alternative to the healthcare setting to recruit and treat workers. Recruitment will be based on self-reported eating and weight concerns rather than diagnosis potentially enabling treatment to employees who have not previously sought help. The data will also provide insights to recruitment, acceptability, effectiveness, and future viability of CBT-T in the workplace.

The Effectiveness and Safety of Serious Games for Improving Cognitive Abilities Among Elderly People With Cognitive Impairment: Systematic Review and Meta-Analysis.

BACKGROUND: Cognitive impairment is a mental disorder that commonly affects elderly people. Serious games, which are games that have a purpose other than entertainment, have been used as a nonpharmacological intervention for improving cognitive abilities. The effectiveness and safety of serious games for improving cognitive abilities have been investigated by several systematic reviews; however, they are limited by design and methodological weaknesses. OBJECTIVE: This study aims to assess the effectiveness and safety of serious games for improving cognitive abilities among elderly people with cognitive impairment. METHODS: A systematic review of randomized controlled trials (RCTs) was conducted. The following 8 electronic databases were searched: MEDLINE, Embase, CINAHL, PsycINFO, ACM Digital Library, IEEE Xplore, Scopus, and Google Scholar. We also screened reference lists of the included studies and relevant reviews, as well as checked studies citing our included studies. Two reviewers independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence appraisal. We used a narrative and statistical approach, as appropriate, to synthesize the results of the included studies. RESULTS: Fifteen studies met the eligibility criteria among 466 citations retrieved. Of those, 14 RCTs were eventually included in the meta-analysis. We found that, regardless of their type, serious games were more effective than no intervention (P=.04) and conventional exercises (P=.002) for improving global cognition among elderly people with cognitive impairment. Further, a subgroup analysis showed that cognitive training games were more effective than no intervention (P=.05) and conventional exercises (P<.001) for improving global cognition among elderly people with cognitive impairment. Another subgroup analysis demonstrated that exergames (a category of serious games that includes physical exercises) are as effective as no intervention and conventional exercises (P=.38) for improving global cognition among elderly people with cognitive impairment. Although some studies found adverse events from using serious games, the number of adverse events (ie, falls and exacerbations of pre-existing arthritis symptoms) was comparable between the serious game and control groups. CONCLUSIONS: Serious games and specifically cognitive training games have the potential to improve global cognition among elderly people with cognitive impairment. However, our findings remain inconclusive because the quality of evidence in all meta-analyses was very low, mainly due to the risk of bias raised in the majority of the included studies, high heterogeneity of the evidence, and imprecision of total effect sizes. Therefore, psychologists, psychiatrists, and patients should consider offering serious games as a complement and not a substitute to existing interventions until further more robust evidence is available. Further studies are needed to assess the effect of exergames, the safety of serious games, and their long-term effects.

The Effectiveness of Serious Games for Alleviating Depression: Systematic Review and Meta-analysis.

BACKGROUND: Depression is a common mental disorder characterized by disturbances in mood, thoughts, or behaviors. Serious games, which are games that have a purpose other than entertainment, have been used as a nonpharmacological therapeutic intervention for depression. Previous systematic reviews have summarized evidence of effectiveness of serious games in reducing depression symptoms; however, they are limited by design and methodological shortcomings. OBJECTIVE: This study aimed to assess the effectiveness of serious games in alleviating depression by summarizing and pooling the results of previous studies. METHODS: A systematic review of randomized controlled trials (RCTs) was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. The search sources included 6 bibliographic databases (eg, MEDLINE, PsycINFO, IEEE Xplore), the search engine "Google Scholar," and backward and forward reference list checking of the included studies and relevant reviews. Two reviewers independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence appraisal. Results of the included studies were synthesized narratively and statistically, as appropriate, according to the type of serious games (ie, exergames or computerized cognitive behavioral therapy [CBT] games). RESULTS: From an initial 966 citations retrieved, 27 studies met the eligibility criteria, and 16 studies were eventually included in meta-analyses. Very low-quality evidence from 7 RCTs showed no statistically significant effect of exergames on the severity of depressive symptoms as compared with conventional exercises (P=.12). Very low-quality evidence from 5 RCTs showed a statistically and clinically significant difference in the severity of depressive symptoms (P=.004) between exergame and control groups, favoring exergames over no intervention. Very low-quality evidence from 7 RCTs showed a statistically and clinically significant effect of computerized CBT games on the severity of depressive symptoms in comparison with no intervention (P=.003). CONCLUSIONS: Serious games have the potential to alleviate depression as other active interventions do. However, we could not draw definitive conclusions regarding the effectiveness of serious games due to the high risk of bias in the individual studies examined and the low quality of meta-analyzed evidence. Therefore, we recommend that health care providers consider offering serious games as an adjunct to existing interventions until further, more robust evidence is available. Future studies should assess the effectiveness of serious games that are designed specifically to alleviate depression and deliver other therapeutic modalities, recruit participants with depression, and avoid biases by following recommended guidelines for conducting and reporting RCTs. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42021232969; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=232969.

Digital cognitive behavioural therapy intervention in the workplace: study protocol for a feasibility randomised waitlist-controlled trial to improve employee mental well-being, engagement and productivity.

INTRODUCTION: One in six workers experience some form of mental health problems at work costing the UK economy an estimated £70 billion/year. Digital interventions provide low cost and easily scalable delivery methods to implement psychological interventions in the workplace. This trial tests the feasibility of implementing a self-guided 8-week digital cognitive behavioural therapy intervention for subthreshold to clinical depression and/or anxiety versus waitlist control (ie, life as usual) in the workplace. METHODS AND ANALYSIS: Feasibility of implementation will be tested using a mixed-methods evaluation of the two-arm randomised waitlist-control trial. Evaluation will include examination of organisational buy-in, and the engagement of employees through the trial indicated by the completion of outcome measures. In addition, we also explore how participants use the platform, the appropriateness of the analysis both with reference to the outcome measures and linear modelling. Finally, we examine the acceptability of the intervention based on participants experiences using qualitative interviews. Assessments take place at baseline (T0), at 8 weeks post-treatment (T1), at short-term follow-up 4 weeks post-treatment (T2) and long-term follow-ups (6 and 12 months after-end of treatment). We will recruit from 1 July 2021 to 31 December 2021 for employees and self-employed workers with depression and anxiety symptoms (subclinical and clinical levels) who are not seeking or engaged in treatment at the time of the trial. ETHICS AND DISSEMINATION: Full approval was given by the University of Warwick Biomedical and Research Ethics Committee (BSREC 45/20-21). The current protocol version is 2.8 (August 2021). Publication of results in peer-reviewed journals will inform the scientific, clinical and business communities. We will disseminate results through webinars, conferences, newsletter as well as a lay summary of results on the study website (mhpp.me). TRIAL REGISTRATION NUMBER: ISRCTN31161020.

Abnormal expression of post-synaptic proteins in prefrontal cortex of patients with schizophrenia.

There is converging evidence of dendritic spine dysfunction in schizophrenia. In the present study we hypothesized that the expression of key proteins involved in dendritic spine development and stability may be affected in schizophrenia. Postmortem frontal cortex (BA6) from patients with schizophrenia, major depressive disorder, bipolar disorder and healthy controls was processed for glutamate post-synaptic fraction extraction and post-synaptic density purification. Protein expression of the post-synaptic fraction and the post-synaptic density was assessed using immunoprecipitation and Western blotting respectively. The expression of the N-methyl-d-aspartate glutamate receptor (NMDAR) subunit NR2A, post-synaptic density 95 (PSD-95), Ca2+/calmodulin-dependent protein kinase II subunits α and ß (CaMKIIα and ß) were significantly reduced in schizophrenia. A significant decrease in the expression of NR2A was also observed in patients with major depressive disorder relative to controls, but not in patients with bipolar disorder. These results add to existing evidence for disturbed post-synaptic glutamate function and synaptic plasticity in schizophrenia. There may also be subtle disturbances in the post-synaptic glutamatergic function in major depressive disorder.

Active HHV-6 Infection of Cerebellar Purkinje Cells in Mood Disorders.

Early-life infections and associated neuroinflammation is incriminated in the pathogenesis of various mood disorders. Infection with human roseoloviruses, HHV-6A and HHV-6B, allows viral latency in the central nervous system and other tissues, which can later be activated causing cognitive and behavioral disturbances. Hence, this study was designed to evaluate possible association of HHV-6A and HHV-6B activation with three different groups of psychiatric patients. DNA qPCR, immunofluorescence and FISH studies were carried out in post-mortem posterior cerebellum from 50 cases each of bipolar disorder (BPD), schizophrenia, 15 major depressive disorder (MDD) and 50 appropriate control samples obtained from two well-known brain collections (Stanley Medical Research Institute). HHV-6A and HHV-6B late proteins (indicating active infection) and viral DNA were detected more frequently (p < 0.001 for each virus) in human cerebellum in MDD and BPD relative to controls. These roseolovirus proteins and DNA were found less frequently in schizophrenia cases. Active HHV-6A and HHV-6B infection in cerebellar Purkinje cells were detected frequently in BPD and MDD cases. Furthermore, we found a significant association of HHV-6A infection with reduced Purkinje cell size, suggesting virus-mediated abnormal Purkinje cell function in these disorders. Finally, gene expression analysis of cerebellar tissue revealed changes in pathways reflecting an inflammatory response possibly to HHV-6A infection. Our results provide molecular evidence to support a role for active HHV-6A and HHV-6B infection in BPD and MDD.

A flexible and low-cost polypropylene pouch for naked-eye detection of herpes simplex viruses.

Effective viral detection is a key goal in the development of point of care (POC) diagnostic devices. Loop-mediated isothermal amplification (LAMP) could potentially be a valuable tool for rapid viral detection and diagnosis in commercial and hospital laboratories and resource limited settings. Here, we present a novel polypropylene pouch (PP) for detection of HSV-1 and HSV-2. With this plastic pouch we could detect up to 6.08 × 10(1) copies per µL of HSV-1 DNA and 0.598 copies per µL of HSV-2 DNA within 45 minutes. Since LAMP itself is less sensitive to inhibitory substances present in the real sample, we could also detect viral DNA without the need for viral DNA extraction and purification. The result from LAMP could be evaluated by naked eye due to the addition of hydroxy naphthol blue (HNB) dye in the reaction mixture. Since this proposed device is easy to handle, portable, user friendly and low cost, it offers a tremendous potential to be a perfect candidate for POC diagnostic device for use in resource limited settings.

[Blood supply during disasters: the experience of Chile in 2010]. / Abastecimiento de sangre durante desastres: la experiencia de Chile en 2010.

A review of the management of blood supply and its administration during disasters was conducted based on the experience of several events that occurred primarily from 2000-2010, particularly the earthquake that measured 8.8 on the Richter scale that struck central and southern Chile on 27 February 2010. The objective was to provide information that could be useful in improving response plans and strategies during potential future disasters. The descriptive information on response procedures was obtained from interviews, internal reports, and the computer database from the Maule regional blood production center. The results lead to the conclusion that to respond efficiently and effectively to the need for blood in the immediate wake of a disaster it is essential to have both a centralized management system that facilitates the supply and administration of blood and volunteers with competence in health that are willing to swiftly arrive during these events. A change in the profile of blood donors during such emergencies was also observed. In Chile, for example, during the two weeks after the earthquake, the ratio of male/female donors was reversed. There was 61.1% participation by women, whereas in the week before the event women accounted for only 37%.

Abastecimiento de sangre durante desastres: la experiencia de Chile en 2010 / Blood supply during disasters: the experience of Chile in 2010

Se realizó una revisión de la gestión del abastecimiento y suministro de sangre durante desastres a partir de las experiencias de diversos eventos ocurridos principalmente en la primera década de este siglo, y en particular el terremoto grado 8,8 en la escala de Richter que afectó la zona centro sur de Chile el 27 de febrero de 2010. El objetivo fue proporcionar información que pueda ser útil para mejorar las estrategias y planes de respuesta durante potenciales desastres futuros. La información descriptiva sobre los procedimientos de respuesta se obtuvo mediante entre-vistas, reportes internos y la base de datos del sistema informático del Centro Productivo Regional de Sangre del Maule. Los resultados permiten concluir que para responder de manera eficiente y efectiva a las necesidades de sangre inmediatamente después de un desastre es de importancia clave tener un sistema centralizado de gestión que facilite el abastecimiento y el suministro de sangre y con-tar con personal voluntario competente en salud que esté dispuesto a acudir con celeridad durante estos eventos. Asimismo, se ha observado que durante dichas emergencias se produce un cambio en el perfil de quienes donan sangre. En Chile, por ejemplo, durante las dos semanas siguientes al terremoto la razón hombre/mujer en los donantes se invirtió, con 61,1 por ciento de participación por parte de las mujeres, quienes en la semana previa al evento representaban a solo 37 por ciento.

A review of the management of blood supply and its administration during disasters was conducted based on the experience of several events that occurred primarily from 2000-2010, particularly the earthquake that measured 8.8 on the Richter scale that struck central and southern Chile on 27 February 2010. The objective was to provide information that could be useful in improving response plans and strategies during potential future disasters. The descriptive information on response procedures was obtained from interviews, internal reports, and the computer database from the Maule regional blood production center. The results lead to the conclusion that to respond efficiently and effectively to the need for blood in the immediate wake of a disaster it is essential to have both a centralized management system that facilitates the supply and administration of blood and volunteers with competence in health that are willing to swiftly arrive during these events. A change in the profile of blood donors during such emergencies was also observed. In Chile, for example, during the two weeks after the earthquake, the ratio of male/female donors was reversed. There was 61.1 percent participation by women, whereas in the week before the event women accounted for only 37 percent.