Estimating the Burden of Alcohol on Ambulance Callouts through Development and Validation of an Algorithm Using Electronic Patient Records

Background: Alcohol consumption places a significant burden on emergency services, including ambulance services, which often represent patients’ first, and sometimes only, contact with health services. We aimed to (1) improve the assessment of this burden on ambulance services in Scotland using a low-cost and easy to implement algorithm to screen free-text in electronic patient record forms (ePRFs), and (2) present estimates on the burden of alcohol on ambulance callouts in Scotland. Methods: Two paramedics manually reviewed 5416 ePRFs to make a professional judgement of whether they were alcohol-related, establishing a gold standard for assessing our algorithm performance. They also extracted all words or phrases relating to alcohol. An automatic algorithm to identify alcohol-related callouts using free-text in EPRs was developed using these extracts. Results: Our algorithm had a specificity of 0.941 and a sensitivity of 0.996 in detecting alcohol-related callouts. Applying the algorithm to all callout records in Scotland in 2019, we identified 86,780 (16.2%) as alcohol-related. At weekends, this percentage was 18.5%. Conclusions: Alcohol-related callouts constitute a significant burden on the Scottish Ambulance Service. Our algorithm is significantly more sensitive than previous methods used to identify alcohol-related ambulance callouts. This approach and the resulting data have potential for the evaluation of alcohol policy interventions as well as for conducting wider epidemiological research.

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Development and Validation of an Eco-Friendly and Low-Cost Method for the Quantification of Cefepime Hydrochloride in Powder for Injectable Solution Using Infrared (IR) Spectroscopy

Current Analytical Chemistry ◽

10.2174/1573411014666180704122816 ◽

2020 ◽

Vol 16 (4) ◽

pp. 456-464

Author(s):

Danilo F. Rodrigues ◽

Hérida R.N. Salgado

Keyword(s):

Ir Spectroscopy ◽

Low Cost ◽

Pharmaceutical Preparations ◽

Potassium Bromide ◽

Pharmaceutical Products ◽

Injectable Formulation ◽

Ich Guidelines ◽

Lactam Ring ◽

Development And Validation

Background: A simple, eco-friendly and low-cost Infrared (IR) method was developed and validated for the analysis of Cefepime Hydrochloride (CEF) in injectable formulation. Different from some other methods, which employ organic solvents in the analyses, this technique does not use these types of solvents, removing large impacts on the environment and risks to operators. Objective: This study aimed at developing and validating a green analytical method using IR spectroscopy for the determination of CEF in pharmaceutical preparations. Methods: The method was validated according to ICH guidelines and the quantification of CEF was performed in the spectral region absorbed at 1815-1745 cm-1 (stretching of the carbonyl group of β- lactam ring). Results: The validated method showed to be linear (r = 0.9999) in the range of 0.2 to 0.6 mg/pellet of potassium bromide, as well as for the parameters of selectivity, precision, accuracy, robustness and Limits of Detection (LOD) and Quantification (LOQ), being able to quantify the CEF in pharmaceutical preparations. The CEF content obtained by the IR method was 103.86%. Conclusion: Thus, the method developed may be an alternative in the quality control of CEF sample in lyophilized powder for injectable solution, as it presented important characteristics in the determination of the pharmaceutical products, with low analysis time and a decrease in the generation of toxic wastes to the environment.

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IMPROVEMENT OF DOSE ESTIMATION PROCESS USING ARTIFICIAL NEURAL NETWORKS

Radiation Protection Dosimetry ◽

10.1093/rpd/ncy185 ◽

2018 ◽

Vol 184 (1) ◽

pp. 36-43 ◽

Cited By ~ 3

Author(s):

Gal Amit ◽

Hanan Datz

Keyword(s):

Neural Networks ◽

Support Vector Machine ◽

Artificial Neural Networks ◽

Support Vector ◽

Physical Parameters ◽

Machine Method ◽

Algorithm Performance ◽

Artificial Neural ◽

First Time ◽

Automatic Algorithm

Abstract We present here for the first time a fast and reliable automatic algorithm based on artificial neural networks for the anomaly detection of a thermoluminescence dosemeter (TLD) glow curves (GCs), and compare its performance with formerly developed support vector machine method. The GC shape of TLD depends on numerous physical parameters, which may significantly affect it. When integrated into a dosimetry laboratory, this automatic algorithm can classify ‘anomalous’ (having any kind of anomaly) GCs for manual review, and ‘regular’ (acceptable) GCs for automatic analysis. The new algorithm performance is then compared with two kinds of formerly developed support vector machine classifiers—regular and weighted ones—using three different metrics. Results show an impressive accuracy rate of 97% for TLD GCs that are correctly classified to either of the classes.

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Development and Validation of an UHPLC Method for Ostarine Determination in Dietary Supplements

Acta Medica Marisiensis ◽

10.2478/amma-2019-0008 ◽

2019 ◽

Vol 65 (2) ◽

pp. 49-54

Author(s):

Amalia Miklos ◽

Amelia Tero-Vescan ◽

Lénárd Farczádi ◽

Daniela-Lucia Muntean

Keyword(s):

Quantitative Determination ◽

Dietary Supplements ◽

Low Cost ◽

Reversed Phase ◽

European Pharmacopoeia ◽

Average Mass ◽

7Th Edition ◽

Development And Validation ◽

Mg Content

AbstractObjective: The purpose of this study was to develop a low-cost, yet sensitive and precise UHPLC method for the quantitative determination of ostarine from dietary supplements (DS) for athletes. The analytical performance of the method was verified on a DS legally acquired from a specialized website for athletes. The uniformity of mass and content of the ostarine DS was also verified.Methods: For the quantitative determination of ostarine a UHPLC method was developed and validated. The separation was performed using a reversed-phase C18 column, using a mixture of 75% methanol: 25% formic acid 0.1% in isocratic elution, at a flow rate of 0.5 ml/min. The uniformity of mass and content of DS was performed following the methodology described in the European Pharmacopoeia 7th Edition.Results: The validated method was specific and linear on the concentration range of 1-25 µg/ml and was precise and accurate at all concentration levels, according to the official guidelines for validating analytical methods. An average mass of 510 mg content was obtained for the ostarine capsules, with an RSD of 2.41%. Regarding the uniformity of the content, an average of 4.65 mg ostarine/capsule was obtained with an RSD of 1.05%.Conclusions: The developed UHPLC method was suitable, rapid, sensitive and allowed quantitative determination of active substance content in a DS with ostarine (92.91% ostarine/capsule from 5 mg ostarine/capsule declared by the manufacturer).

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Development and Validation of a Low-Cost Eye-Tracking Device

Korean Journal of Cognitive and Biological Psychology ◽

10.22172/cogbio.2010.22.1.007 ◽

2010 ◽

Vol 22 (1) ◽

pp. 95-107

Author(s):

Sohn, Yeung-Jun ◽

Ho-Wan Kwak ◽

Sangil, Lee

Keyword(s):

Eye Tracking ◽

Low Cost ◽

Tracking Device ◽

Development And Validation

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P21 Feasibility of the Learning and Exercise to Avert Pain (LEAP) programme: an evaluation of a group therapy intervention for young people with chronic musculoskeletal pain

Rheumatology ◽

10.1093/rheumatology/kez415.017 ◽

2019 ◽

Vol 58 (Supplement_4) ◽

Author(s):

Hannah Wong ◽

Margaret Wheeler ◽

Jennifer Nisbet ◽

Janet McDonagh ◽

Verna Cuthbert

Keyword(s):

Young People ◽

Musculoskeletal Pain ◽

Conflicts Of Interest ◽

Outcome Data ◽

Free Text ◽

Electronic Patient Records ◽

Structured Interviews ◽

Group Setting ◽

Adolescent Anxiety

Abstract Background Chronic idiopathic musculoskeletal pain (CIMSKP) has become increasingly recognised as a major cause of morbidity in adolescents. In view of increasing referrals to a paediatric rheumatology centre, the Learning and Exercise to Avert Pain (LEAP) intervention was designed as an approach to pain management within a group setting, led by an occupational therapist and a physiotherapist. It involves 2 hour weekly sessions for 6 weeks and includes education, gym activities and relaxation sessions with routine collection of Pain VAS, CHAQ, Bath Pain questionnaires (adolescent BAPQ and parent BAPQ-p forms) at baseline, end of LEAP and 3 months follow-up. We aim to assess the feasibility and impact of LEAP for adolescents with CIMSKP. Methods Young people who had been referred for the LEAP programme were identified (n = 46). Basic demographics and questionnaire scores were collected from electronic patient records and therapy notes. Feasibility was assessed by delivery of programme and percentage completion of questionnaires at three time-points. Semi-structured interviews were conducted with healthcare professionals involved in the programme and analysed using thematic analyses as were any free text comments on the BAPQ from adolescents and parents. Statistical analysis of the outcome data was performed using paired t-tests and SPSS software (v22). Results 46 adolescents were identified: 85% female, median age 16 years (range 10 to 19). 34 participated in LEAP, 12 received 1:1 therapy. Feasibility of programme delivery was achieved with completion of all six sessions. Completion rates for all 3 measures for adolescents/parents at baseline, end of programme review and follow up were 78.6/71.4%, 64.3/71.4%, and 45.5/36.4% respectively. Adolescent scores indicated a significant increase in impairment in the development subscale scores on BAPQ from baseline to programme end (p = 0.021) although not at follow up. Parent scores for adolescent anxiety and pain-specific anxiety on BAPQ-p increased significantly from end of programme to follow-up (p = 0.017, p = 0.034 respectively). Parents scored higher than adolescents for most outcomes. The qualitative data (available for 11 adolescents, 12 parents) revealed that parents and adolescents appreciated learning coping techniques and gaining a greater understanding of chronic pain. The intervention was perceived to be socially beneficial in particular but imperfect in terms of data collection by the professionals interviewed (n = 2). Conclusion Baseline demographics of the LEAP participants echoed current literature. Delivery of the programme was feasible and the programme was positively received by young people, their parents and professionals alike. The increase in adolescent development subscale scores following the programme could represent increased self-reflection and/or peer to peer observations as a result of the group setting but needs longer term follow-up data to clarify further. The increase in parental anxiety highlights the need for a concurrent session for parents. Routine collection of objective measures remains challenging in non-research setting. Conflicts of Interest The authors declare no conflicts of interest.

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A dynamic reaction picklist for improving allergy reaction documentation in the electronic health record

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocaa042 ◽

2020 ◽

Vol 27 (6) ◽

pp. 917-923

Author(s):

Liqin Wang ◽

Suzanne V Blackley ◽

Kimberly G Blumenthal ◽

Sharmitha Yerneni ◽

Foster R Goss ◽

...

Keyword(s):

Electronic Health Record ◽

Language Processing ◽

Clinical Decision ◽

Free Text ◽

Health Record ◽

Dynamic Reaction ◽

Value Set ◽

Expert Review ◽

Electronic Health ◽

Development And Validation

Abstract Objective Incomplete and static reaction picklists in the allergy module led to free-text and missing entries that inhibit the clinical decision support intended to prevent adverse drug reactions. We developed a novel, data-driven, “dynamic” reaction picklist to improve allergy documentation in the electronic health record (EHR). Materials and Methods We split 3 decades of allergy entries in the EHR of a large Massachusetts healthcare system into development and validation datasets. We consolidated duplicate allergens and those with the same ingredients or allergen groups. We created a reaction value set via expert review of a previously developed value set and then applied natural language processing to reconcile reactions from structured and free-text entries. Three association rule-mining measures were used to develop a comprehensive reaction picklist dynamically ranked by allergen. The dynamic picklist was assessed using recall at top k suggested reactions, comparing performance to the static picklist. Results The modified reaction value set contained 490 reaction concepts. Among 4 234 327 allergy entries collected, 7463 unique consolidated allergens and 469 unique reactions were identified. Of the 3 dynamic reaction picklists developed, the 1 with the optimal ranking achieved recalls of 0.632, 0.763, and 0.822 at the top 5, 10, and 15, respectively, significantly outperforming the static reaction picklist ranked by reaction frequency. Conclusion The dynamic reaction picklist developed using EHR data and a statistical measure was superior to the static picklist and suggested proper reactions for allergy documentation. Further studies might evaluate the usability and impact on allergy documentation in the EHR.

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