scholarly journals Harm minimisation for the management of self-harm: a mixed-methods analysis of electronic health records in secondary mental healthcare

BJPsych Open ◽  
2021 ◽  
Vol 7 (4) ◽  
Author(s):  
Charlotte Cliffe ◽  
Alexandra Pitman ◽  
Rosemary Sedgwick ◽  
Megan Pritchard ◽  
Rina Dutta ◽  
...  

Background Prevalence of self-harm in the UK was reported as 6.4% in 2014. Despite sparse evidence for effectiveness, guidelines recommend harm minimisation; a strategy in which people who self-harm are supported to do so safely. Aims To determine the prevalence, sociodemographic and clinical characteristics of those who self-harm and practise harm minimisation within a London mental health trust. Method We included electronic health records for patients treated by South London and Maudsley NHS Trust. Using an iterative search strategy, we identified patients who practise harm minimisation, then classified the approaches using a content analysis. We compared the sociodemographic characteristics with that of a control group of patients who self-harm and do not use harm minimisation. Results In total 22 736 patients reported self-harm, of these 693 (3%) had records reporting the use of harm-minimisation techniques. We coded the approaches into categories: (a) ‘substitution’ (>50% of those using harm minimisation), such as using rubber bands or using ice; (b) ‘simulation’ (9%) such as using red pens; (c) ‘defer or avoid’ (7%) such as an alternative self-injury location; (d) ‘damage limitation’ (9%) such as using antiseptic techniques; the remainder were unclassifiable (24%). The majority of people using harm minimisation described it as helpful (>90%). Those practising harm minimisation were younger, female, of White ethnicity, had previous admissions and were less likely to have self-harmed with suicidal intent. Conclusions A small minority of patients who self-harm report using harm minimisation, primarily substitution techniques, and the large majority find harm minimisation helpful. More research is required to determine the acceptability and effectiveness of harm-minimisation techniques and update national clinical guidelines.

Author(s):  
Jiao Song ◽  
Elizabeth Elliot ◽  
Andrew D Morris ◽  
Joannes J Kerssens ◽  
Ashley Akbari ◽  
...  

IntroductionDue to various regulatory barriers, it is increasingly difficult to move pseudonymised routine health data across platforms and among jurisdictions. To tackle this challenge, we summarized five approaches considered to support a scientific research project focused on the risk of the new non-vitamin K Target Specific Oral Anticoagulants (TSOACs) and collaborated between the Farr institute in Wales and Scotland. ApproachIn Wales, routinely collected health records held in the Secure Anonymous Information Linkage (SAIL) Databank were used to identify the study cohort. In Scotland, data was extracted from national dataset resources administered by the eData Research & Innovation Service (eDRIS) and stored in the Scottish National Data Safe Haven. We adopted a federated data and multiple analysts approach, but arranged simultaneous accesses for Welsh and Scottish analysts to generate study cohorts separately by implementing the same algorithm. Our study cohort across two countries was boosted to 6,829 patients towards risk analysis. Source datasets and data types applied to generate cohorts were reviewed and compared by analysts based on both sites to ensure the consistency and harmonised output.  DiscussionThis project used a fusion of two approaches among five considered. The approach we adopted is a simple, yet efficient and cost-effective method to ensure consistency in analysis and coherence with multiple governance systems. It has limitations and potentials of extending and scaling. It can also be considered as an initialisation of a developing infrastructure to support a distributed team science approach to research using Electronic Health Records (EHRs) across the UK and more widely. KeywordsTeam science, cross-jurisdictional data linkage, electronic health records


PLoS ONE ◽  
2018 ◽  
Vol 13 (12) ◽  
pp. e0210040
Author(s):  
Hamad Bastaki ◽  
Louise Marston ◽  
Jackie Cassell ◽  
Greta Rait

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Jennifer F. Summers ◽  
Dan G. O’Neill ◽  
David Church ◽  
Lisa Collins ◽  
David Sargan ◽  
...  

2019 ◽  
Vol 18 ◽  
pp. S77
Author(s):  
R. Griffiths ◽  
D.K. Schlüter ◽  
A. Akbari ◽  
R. Cosgriff ◽  
D.F. Tucker ◽  
...  

2016 ◽  
Vol 26 (8) ◽  
pp. 1900-1905 ◽  
Author(s):  
Helen P. Booth ◽  
◽  
Omar Khan ◽  
Alison Fildes ◽  
A. Toby Prevost ◽  
...  

2015 ◽  
Vol 84 (4) ◽  
pp. 237-247 ◽  
Author(s):  
Fiona Riordan ◽  
Chrysanthi Papoutsi ◽  
Julie E. Reed ◽  
Cicely Marston ◽  
Derek Bell ◽  
...  

2016 ◽  
Vol 19 (6) ◽  
pp. 687-692 ◽  
Author(s):  
Sara Burke ◽  
Vicki Black ◽  
Fernando Sánchez-Vizcaíno ◽  
Alan Radford ◽  
Angie Hibbert ◽  
...  

Objectives The objective was to use electronic health records to describe the use of cefovecin (Convenia; Zoetis UK), a third-generation long-acting injectable antimicrobial, in a UK population of cats attending first-opinion practices, and to compare the use of Convenia with the licensed uses described on the UK Convenia datasheet. Methods Data were obtained as an Excel database from the Small Animal Veterinary Surveillance Network for all feline consultations containing the word Convenia and/or cefovecin from 1 September 2012 to 23 September 2013 inclusive. Entries were classified according to body system treated, confirmation or suspicion of an abscess, evidence of microbiological evaluation being performed, any concurrent therapies given and whether any reason was given for use of Convenia over alternative antimicrobials. Data were exported to IBM SPSS Statistics and descriptive analysis performed. Results In total, 1148 entries were analysed. The most common body system treated was skin in 553 (48.2%) entries, then urinary (n = 157; 13.7%) and respiratory (n = 112; 9.8%). Microbiological evaluation was recorded in 193 (16.8%) entries, with visible purulent material most commonly cited (in 147 [12.8%] entries). A reason for prescribing Convenia over alternative antimicrobials was given in 138 (12.0%) entries; the most cited was an inability to orally medicate the cat in 77 (55.8%) of these entries. Excluding 131 entries where no body system or multiple body systems were described, the use of Convenia complied with a licensed use in the UK datasheet in 710 (69.8%) of 1017 entries. Conclusions and relevance Most administrations were licensed uses; however, most entries did not describe any microbiological evaluation, or a reason for prescribing Convenia over alternative antimicrobials. Further education of the public and the veterinary profession is needed to promote antimicrobial stewardship in the UK. Health records provide a valuable tool with which to monitor, both locally and at scale, the use of important therapeutics like antimicrobials. Information relevant to decision-making should be recorded in individual animal health records.


2020 ◽  
Author(s):  
Zeineb Safi ◽  
Neethu Venugopal ◽  
Haytham Ali ◽  
Michel Makhlouf ◽  
Sabri Boughorbel

Abstract Background: Preterm deliveries have many negative health implications on both mother and child. Identifying the population level factors that increase the risk of preterm deliveries is an important step in the direction of mitigating the impact and reducing the frequency of occurrence of preterm deliveries. The purpose of this work is to identify preterm delivery risk factors and their progression throughout the pregnancy from a large collection of Electronic Health Records (EHR). Results: The study cohort includes more than 60,000 deliveries in the USA with the complete medical history from EHR for diagnoses, medications, procedures and demographics. We propose a temporal analysis of risk factors by estimating and comparing risk ratios at different time points prior to the delivery event. We selected the following time points before delivery: 9, 6, 3 and 1 month(s). We did so by conducting a retrospective cohort study of patient history for a selected set of mothers who delivered preterm and a control group of mothers that delivered full-term. We analyzed the extracted data using a logistic regression model. The results of our analyses showed that the highest risk ratio corresponds to history of previous preterm delivery. Other risk factors were identified, some of which are consistent with those that are reported in the literature, others need further investigation. Conclusions: The comparative analysis of the risk factors at different time points showed that risk factors in the early pregnancy related to patient history and chronic condition, while the risk factors in late pregnancy are specific to the current pregnancy. Our analysis unifies several previously reported studies on preterm risk factors. It also gives important insights on the changes of risk factors in the course of pregnancy.


2020 ◽  
Author(s):  
Jemma L Walker ◽  
Daniel J Grint ◽  
Helen Strongman ◽  
Rosalind M Eggo ◽  
Maria Peppa ◽  
...  

Background This study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom in 2019. Methods We used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to describe the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status. Findings On 5 March 2019, 24.4% of the UK population were at risk due to a record of at least one underlying health condition, including 8.3% of school-aged children, 19.6% of working-aged adults, and 66.2% of individuals aged 70 years or more. 7.1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1.6% of the population had a new diagnosis of cancer in the past five years. Interpretation The population at risk of severe COVID-19 (aged ≥70 years, or with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals.


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