{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T06:13:24Z","timestamp":1774332804497,"version":"3.50.1"},"reference-count":13,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T00:00:00Z","timestamp":1726444800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T00:00:00Z","timestamp":1726444800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The aim is to develop and deploy an automated clinical alert system to enhance patient care and streamline healthcare operations. Structured and unstructured data from multiple sources are used to generate near real-time alerts for specific clinical scenarios, with an additional goal to improve clinical decision-making through accuracy and reliability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The automated clinical alert system, named Smart Watchers, was developed using Apache NiFi and Python scripts to create flexible data processing pipelines and customisable clinical alerts. A comparative analysis between Smart Watchers and the legacy Elastic Watchers was conducted to evaluate performance metrics such as accuracy, reliability, and scalability. The evaluation involved measuring the time taken for manual data extraction through the electronic patient record (EPR) front-end and comparing it with the automated data extraction process using Smart Watchers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Deployment of Smart Watchers showcased a consistent time savings between 90% to 98.67% compared to manual data extraction through the EPR front-end. The results demonstrate the efficiency of Smart Watchers in automating data extraction and alert generation, significantly reducing the time required for these tasks when compared to manual methods in a scalable manner.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The research underscores the utility of employing an automated clinical alert system, and its portability facilitated its use across multiple clinical settings. The successful implementation and positive impact of the system lay a foundation for future technological innovations in this rapidly evolving field.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12911-024-02633-w","type":"journal-article","created":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T03:02:27Z","timestamp":1726455747000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Enhancing clinical data retrieval with Smart Watchers: a NiFi-based ETL pipeline for Elasticsearch queries"],"prefix":"10.1186","volume":"24","author":[{"given":"Mohammad","family":"Al-Agil","sequence":"first","affiliation":[]},{"given":"Stephen J.","family":"Obee","sequence":"additional","affiliation":[]},{"given":"Vlad","family":"Dinu","sequence":"additional","affiliation":[]},{"given":"James","family":"Teo","sequence":"additional","affiliation":[]},{"given":"David","family":"Brawand","sequence":"additional","affiliation":[]},{"given":"Piers E. M.","family":"Patten","sequence":"additional","affiliation":[]},{"given":"Anwar","family":"Alhaq","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,16]]},"reference":[{"issue":"1","key":"2633_CR1","doi-asserted-by":"publisher","DOI":"10.1136\/bmjhci-2020-100253","volume":"28","author":"V Sharma","year":"2021","unstructured":"Sharma V, Ali I, van der Veer S, Martin G, Ainsworth J, Augustine T. Adoption of clinical risk prediction tools is limited by a lack of integration with electronic health records. BMJ Health Care Inform. 2021;28(1): e100253.","journal-title":"BMJ Health Care Inform"},{"issue":"1","key":"2633_CR2","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1186\/s12911-018-0623-9","volume":"18","author":"R Jackson","year":"2018","unstructured":"Jackson R, Kartoglu I, Stringer C, Gorrell G, Roberts A, Song X, et al. CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital. BMC Med Inform Decis Making. 2018;18(1):47 (Accessed 15 Sept 2023).","journal-title":"BMC Med Inform Decis Making."},{"key":"2633_CR3","unstructured":"Elastic. What is Elasticsearch?. [cited 2024 Jun 18]. Available from: https:\/\/www.elastic.co\/guide\/en\/elasticsearch\/reference\/current\/elasticsearch-intro.html."},{"key":"2633_CR4","unstructured":"Elastic. kibana. Elastic; 2024 [cited 2024 Jun 18]. Available from: https:\/\/github.com\/elastic\/kibana."},{"key":"2633_CR5","unstructured":"Apache NiFi Team. Apache NiFi. [cited 2024 Jun 18]. Apache NiFi Overview. Available from: https:\/\/nifi.apache.org\/documentation\/v2\/."},{"key":"2633_CR6","unstructured":"Watcher. [cited 2023 May 1]. Watcher. https:\/\/www.elastic.co\/guide\/en\/kibana\/current\/watcher-ui.html. 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BMJ Qual Saf. 2022;31(10):725\u201334.\u00a0https:\/\/qualitysafety.bmj.com\/content\/31\/10\/725.\u00a0Accessed 15 Sept 2023.","journal-title":"BMJ Qual Saf."},{"key":"2633_CR9","unstructured":"Bashkirova V, Vijayanathan A, Vidler J, Marrinan E, Peacock V, Roberts L, et al. A Single Centre 7-year Experience of Bleeding Events In CLL\/SLL Patients taking Ibrutinib and Anticoagulation. Poster session presented at: 63rd Annual Scientific Meeting of the British Society for Haematology; 23-25 April 2023; Birmingham. https:\/\/www.postersessiononline.eu\/173580348_eu\/congresos\/BSH2023\/aula\/-EP_149_BSH2023.pdf. Accessed 15 Sept 2023."},{"key":"2633_CR10","doi-asserted-by":"crossref","unstructured":"Cannata A, Bhatti P, Roy R, Al-Agil M, Daniel A, Ferone E, et al. Prognostic relevance of demographic factors in cardiac magnetic resonance-proven acute myocarditis: A cohort study. Front Cardiovasc Med. 2022;9. 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[cited 2023 Aug 7]. Poster session presented at: 31st Congress of the International Society on Thrombosis and Haemostasis. 2023; Montreal. https:\/\/isth2023.eventscribe.net\/agenda.asp?BCFO=P&pfp=Poster&fa=&fb=&fc=&fd=&all=1&mode=. Accessed 15 Sept 2023.","DOI":"10.1016\/j.rpth.2023.101864"},{"key":"2633_CR13","unstructured":"Kraljevic Z, Searle T, Shek A, Roguski L, Noor K, Bean D, et al. Multi-domain clinical natural language processing with MedCAT: the Medical Concept Annotation Toolkit. arXiv; 2021 [cited 2023 Aug 7]. http:\/\/arxiv.org\/abs\/2010.01165. Accessed 15 Sept 2023."}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-024-02633-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-024-02633-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-024-02633-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T15:05:34Z","timestamp":1726499134000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-024-02633-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,16]]},"references-count":13,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["2633"],"URL":"https:\/\/doi.org\/10.1186\/s12911-024-02633-w","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-3481327\/v1","asserted-by":"object"}]},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,16]]},"assertion":[{"value":"23 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 August 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ethical approval and informed consent were not sought for this project because the manuscript exclusively details projects that utilised the Smart Watcher platform and does not involve the use, presentation, or sharing of any individual-level patient data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable: No informed consent was sought from individual persons, as no individual persons\u2019 data is presented in this manuscript.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"255"}}