{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T08:29:00Z","timestamp":1751617740825},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T00:00:00Z","timestamp":1713830400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T00:00:00Z","timestamp":1713830400000},"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><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>This study aims to propose a semi-automatic method for monitoring the waiting times of follow-up examinations within the National Health System (NHS) in Italy, which is currently not possible to due the absence of the necessary structured information in the official databases.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>A Natural Language Processing (NLP) based pipeline has been developed to extract the waiting time information from the text of referrals for follow-up examinations in the Lombardy Region. A manually annotated dataset of 10\u00a0000 referrals has been used to develop the pipeline and another manually annotated dataset of 10\u00a0000 referrals has been used to test its performance. Subsequently, the pipeline has been used to analyze all 12 million referrals prescribed in 2021 and performed by May 2022 in the Lombardy Region.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The NLP-based pipeline exhibited high precision (0.999) and recall (0.973) in identifying waiting time information from referrals\u2019 texts, with high accuracy in normalization (0.948-0.998). The overall reporting of timing indications in referrals\u2019 texts for follow-up examinations was low (2%), showing notable variations across medical disciplines and types of prescribing physicians. Among the referrals reporting waiting times, 16% experienced delays (average delay = 19 days, standard deviation = 34 days), with significant differences observed across medical disciplines and geographical areas.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The use of NLP proved to be a valuable tool for assessing waiting times in follow-up examinations, which are particularly critical for the NHS due to the significant impact of chronic diseases, where follow-up exams are pivotal. Health authorities can exploit this tool to monitor the quality of NHS services and optimize resource allocation.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12911-024-02506-2","type":"journal-article","created":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T13:01:52Z","timestamp":1713877312000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A NLP-based semi-automatic identification system for delays in follow-up examinations: an Italian case study on clinical referrals"],"prefix":"10.1186","volume":"24","author":[{"given":"Vittorio","family":"Torri","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michele","family":"Ercolanoni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Bortolan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olivia","family":"Leoni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesca","family":"Ieva","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,23]]},"reference":[{"key":"2506_CR1","unstructured":"OECD. Health spending. 2021. https:\/\/www.oecd-ilibrary.org\/content\/data\/8643de7e-en. Accessed 18 Apr 2024."},{"issue":"1","key":"2506_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12911-016-0387-z","volume":"16","author":"C Kersting","year":"2016","unstructured":"Kersting C, Weltermann B. Electronic reminders to facilitate longitudinal care: a mixed-methods study in general practices. BMC Med Inform Decis Mak. 2016;16(1):1\u20139.","journal-title":"BMC Med Inform Decis Mak."},{"issue":"1","key":"2506_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1472-6947-13-76","volume":"13","author":"R Haq","year":"2013","unstructured":"Haq R, Heus L, Baker NA, Dastur D, Leung FH, Leung E, et al. Designing a multifaceted survivorship care plan to meet the information and communication needs of breast cancer patients and their family physicians: results of a qualitative pilot study. BMC Med Inform Decis Making. 2013;13(1):1\u201313.","journal-title":"BMC Med Inform Decis Making."},{"key":"2506_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1472-6947-9-49","volume":"9","author":"H Singh","year":"2009","unstructured":"Singh H, Wilson L, Petersen LA, Sawhney MK, Reis B, Espadas D, et al. Improving follow-up of abnormal cancer screens using electronic health records: trust but verify test result communication. BMC Med Inform Decis Mak. 2009;9:1\u20137.","journal-title":"BMC Med Inform Decis Mak."},{"issue":"3","key":"2506_CR5","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.phr.2004.04.005","volume":"119","author":"G Anderson","year":"2004","unstructured":"Anderson G, Horvath J. The growing burden of chronic disease in America. Public Health Rep. 2004;119(3):263\u201370.","journal-title":"Public Health Rep."},{"issue":"4","key":"2506_CR6","doi-asserted-by":"publisher","first-page":"262","DOI":"10.3802\/jgo.2015.26.4.262","volume":"26","author":"K Nanthamongkolkul","year":"2015","unstructured":"Nanthamongkolkul K, Hanprasertpong J. Longer waiting times for early stage cervical cancer patients undergoing radical hysterectomy are associated with diminished long-term overall survival. J Gynecol Oncol. 2015;26(4):262\u20139.","journal-title":"J Gynecol Oncol."},{"issue":"4","key":"2506_CR7","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.oraloncology.2013.12.018","volume":"50","author":"MC van Harten","year":"2014","unstructured":"van Harten MC, de Ridder M, Hamming-Vrieze O, Smeele LE, Balm AJ, van den Brekel MW. The association of treatment delay and prognosis in head and neck squamous cell carcinoma (HNSCC) patients in a Dutch comprehensive cancer center. Oral Oncol. 2014;50(4):282\u201390.","journal-title":"Oral Oncol."},{"issue":"4","key":"2506_CR8","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.1016\/j.juro.2009.06.041","volume":"182","author":"GS Kulkarni","year":"2009","unstructured":"Kulkarni GS, Urbach DR, Austin PC, Fleshner NE, Laupacis A. Longer wait times increase overall mortality in patients with bladder cancer. J Urol. 2009;182(4):1318\u201324.","journal-title":"J Urol."},{"issue":"6","key":"2506_CR9","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1097\/HCR.0b013e318228a32f","volume":"31","author":"KL Russell","year":"2011","unstructured":"Russell KL, Holloway TM, Brum M, Caruso V, Chessex C, Grace SL. Cardiac rehabilitation wait times: effect on enrollment. J Cardpulm Rehabil Prev. 2011;31(6):373\u20137.","journal-title":"J Cardpulm Rehabil Prev."},{"issue":"9","key":"2506_CR10","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1016\/S0828-282X(06)70290-2","volume":"22","author":"H Ross","year":"2006","unstructured":"Ross H, Howlett J, Arnold JMO, Liu P, O\u2019Neill B, Brophy J, et al. Treating the right patient at the right time: access to heart failure care. Can J Cardiol. 2006;22(9):749\u201354.","journal-title":"Can J Cardiol."},{"issue":"26","key":"2506_CR11","doi-asserted-by":"publisher","first-page":"2648","DOI":"10.1080\/09638288.2016.1238967","volume":"39","author":"S Deslauriers","year":"2017","unstructured":"Deslauriers S, Raymond MH, Lalibert\u00e9 M, Lavoie A, Desmeules F, Feldman DE, et al. Access to publicly funded outpatient physiotherapy services in Quebec: waiting lists and management strategies. Disabil Rehabil. 2017;39(26):2648\u201356.","journal-title":"Disabil Rehabil."},{"issue":"4","key":"2506_CR12","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1161\/CIRCULATIONAHA.112.125435","volume":"126","author":"AS Desai","year":"2012","unstructured":"Desai AS, Stevenson LW. Rehospitalization for heart failure: predict or prevent? Circulation. 2012;126(4):501\u20136.","journal-title":"Circulation."},{"issue":"4","key":"2506_CR13","first-page":"255","volume":"2","author":"M Adib-Hajbaghery","year":"2013","unstructured":"Adib-Hajbaghery M, Maghaminejad F, Abbasi A. The role of continuous care in reducing readmission for patients with heart failure. J Caring Sci. 2013;2(4):255.","journal-title":"J Caring Sci."},{"issue":"12","key":"2506_CR14","doi-asserted-by":"publisher","first-page":"1993","DOI":"10.1097\/JTO.0b013e31822b01a1","volume":"6","author":"L Calman","year":"2011","unstructured":"Calman L, Beaver K, Hind D, Lorigan P, Roberts C, Lloyd-Jones M. Survival benefits from follow-up of patients with lung cancer: a systematic review and meta-analysis. J Thorac Oncol. 2011;6(12):1993\u20132004.","journal-title":"J Thorac Oncol."},{"issue":"2","key":"2506_CR15","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1111\/j.1524-4733.2004.72329.x","volume":"7","author":"B Detournay","year":"2004","unstructured":"Detournay B, Pribil C, Fournier MT, Housset B, Huchon G, Huas D, et al. The SCOPE study: health-care consumption related to patients with chronic obstructive pulmonary disease in France. Value Health. 2004;7(2):168\u201374.","journal-title":"Value Health."},{"issue":"3","key":"2506_CR16","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1046\/j.1524-4733.2001.43022.x","volume":"4","author":"L Garattini","year":"2001","unstructured":"Garattini L, Tediosi F, Chiaffarino F, Roggeri D, Parazzini F, Coscelli C, et al. The outpatient cost of diabetes care in Italian diabetes centers. Value Health. 2001;4(3):251\u20137.","journal-title":"Value Health."},{"issue":"2","key":"2506_CR17","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.jval.2021.07.015","volume":"25","author":"F Rea","year":"2022","unstructured":"Rea F, Ronco R, Martini N, Maggioni AP, Corrao G. Cost-effectiveness of posthospital management of acute coronary syndrome: A real-world investigation from Italy. Value Health. 2022;25(2):185\u201393.","journal-title":"Value Health."},{"key":"2506_CR18","unstructured":"Italian Ministry of Health. National Plan for the Management of Waiting Lists 2019-2021. 2019. https:\/\/www.salute.gov.it\/imgs\/C_17_pubblicazioni_2824_allegato.pdf. Accessed 18 Apr 2024."},{"issue":"1","key":"2506_CR19","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.healthpol.2014.01.018","volume":"117","author":"G Mariotti","year":"2014","unstructured":"Mariotti G, Siciliani L, Rebba V, Fellini R, Gentilini M, Benea G, et al. Waiting time prioritisation for specialist services in Italy: the homogeneous waiting time groups approach. Health Policy. 2014;117(1):54\u201363.","journal-title":"Health Policy."},{"key":"2506_CR20","doi-asserted-by":"crossref","unstructured":"Sharma AR, Kaushik P. Literature survey of statistical, deep and reinforcement learning in natural language processing. In: 2017 International Conference on Computing, Communication and Automation (ICCCA). Greater Noida: IEEE; 2017. p. 350\u20134.","DOI":"10.1109\/CCAA.2017.8229841"},{"issue":"12","key":"2506_CR21","doi-asserted-by":"publisher","first-page":"583","DOI":"10.3390\/buildings11120583","volume":"11","author":"M Locatelli","year":"2021","unstructured":"Locatelli M, Seghezzi E, Pellegrini L, Tagliabue LC, Di Giuda GM. Exploring Natural Language Processing in Construction and Integration with Building Information Modeling: A Scientometric Analysis. Buildings. 2021;11(12):583.","journal-title":"Buildings."},{"key":"2506_CR22","doi-asserted-by":"crossref","unstructured":"Friedman C, Elhadad N. Natural language processing in health care and biomedicine. In: Biomedical informatics. London: Springer; 2014. p. 255\u201384.","DOI":"10.1007\/978-1-4471-4474-8_8"},{"key":"2506_CR23","first-page":"44","volume":"8","author":"OG Iroju","year":"2015","unstructured":"Iroju OG, Olaleke JO. A systematic review of natural language processing in healthcare. Int J Inform Technol Comput Sci. 2015;8:44\u201350.","journal-title":"Int J Inform Technol Comput Sci."},{"issue":"1","key":"2506_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13326-018-0179-8","volume":"9","author":"A N\u00e9v\u00e9ol","year":"2018","unstructured":"N\u00e9v\u00e9ol A, Dalianis H, Velupillai S, Savova G, Zweigenbaum P. Clinical natural language processing in languages other than english: opportunities and challenges. J Biomed Semant. 2018;9(1):1\u201313.","journal-title":"J Biomed Semant."},{"issue":"4","key":"2506_CR25","first-page":"1","volume":"16","author":"F Ferr\u00e9","year":"2014","unstructured":"Ferr\u00e9 F, de Belvis AG, Valerio L, Longhi S, Lazzari A, Fattore G, et al. Italy: health system review. Health Syst Transition. 2014;16(4):1\u2013168.","journal-title":"Health Syst Transition."},{"issue":"3","key":"2506_CR26","first-page":"97","volume":"14","author":"D Timotfe","year":"2018","unstructured":"Timotfe D, Stoian AP, Hainarosie R, Diaconu C, Iliescu B, Balan G, et al. A review on the advantages and disadvantages of using administrative data in surgery outcome studies. J Surg. 2018;14(3):97\u20139.","journal-title":"J Surg."},{"issue":"3","key":"2506_CR27","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1111\/rssa.12315","volume":"181","author":"DJ Hand","year":"2018","unstructured":"Hand DJ. Statistical challenges of administrative and transaction data. J R Stat Soc Ser A (Stat Soc). 2018;181(3):555\u2013605.","journal-title":"J R Stat Soc Ser A (Stat Soc)."},{"issue":"1","key":"2506_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12913-016-1489-0","volume":"16","author":"C Mazzali","year":"2016","unstructured":"Mazzali C, Paganoni AM, Ieva F, Masella C, Maistrello M, Agostoni O, et al. Methodological issues on the use of administrative data in healthcare research: the case of heart failure hospitalizations in Lombardy region, 2000 to 2012. BMC Health Serv Res. 2016;16(1):1\u201310.","journal-title":"BMC Health Serv Res."},{"issue":"3","key":"2506_CR29","doi-asserted-by":"publisher","first-page":"1350","DOI":"10.1177\/0962280215578777","volume":"26","author":"F Ieva","year":"2017","unstructured":"Ieva F, Jackson CH, Sharples LD. Multi-State modelling of repeated hospitalisation and death in patients with Heart Failure: the use of large administrative databases in clinical epidemiology. Stat Methods Med Res. 2017;26(3):1350\u201372.","journal-title":"Stat Methods Med Res."},{"key":"2506_CR30","doi-asserted-by":"crossref","unstructured":"Ieva F, Paganoni AM, Secchi P. Mining administrative health databases for epidemiological purposes: a case study on acute myocardial infarctions diagnoses. In: Advances in Theoretical and Applied Statistics. Heidelberg: Springer; 2013. p. 417\u201326.","DOI":"10.1007\/978-3-642-35588-2_38"},{"issue":"12","key":"2506_CR31","doi-asserted-by":"publisher","first-page":"e019503","DOI":"10.1136\/bmjopen-2017-019503","volume":"7","author":"G Corrao","year":"2017","unstructured":"Corrao G, Rea F, Di Martino M, De Palma R, Scondotto S, Fusco D, et al. Developing and validating a novel multisource comorbidity score from administrative data: a large population-based cohort study from Italy. BMJ Open. 2017;7(12):e019503.","journal-title":"BMJ Open."},{"issue":"3","key":"2506_CR32","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1161\/HYPERTENSIONAHA.114.04858","volume":"65","author":"G Corrao","year":"2015","unstructured":"Corrao G, Mancia G. Generating evidence from computerized healthcare utilization databases. Hypertension. 2015;65(3):490\u20138.","journal-title":"Hypertension."},{"issue":"1","key":"2506_CR33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12913-020-05996-8","volume":"21","author":"F Venturelli","year":"2021","unstructured":"Venturelli F, Ottone M, Pignatti F, Bellocchio E, Pinotti M, Besutti G, et al. Using text analysis software to identify determinants of inappropriate clinical question reporting and diagnostic procedure referrals in Reggio Emilia. Italy BMC Health Serv Res. 2021;21(1):1\u201313.","journal-title":"Italy. BMC Health Serv Res."},{"key":"2506_CR34","unstructured":"Foundation PS. Python Language Reference, version 3.7. http:\/\/www.python.org. Accessed 18 Apr 2024."},{"key":"2506_CR35","unstructured":"Lombardy Region. DGR XI \/ 6002 - Determinations regarding the 2022 waiting list plan. 2022. https:\/\/areadocumentale.servizirl.it\/atti\/download\/AAAAWOWkQM9\/PrCeYPCLXUJpI0ksRK0WkbCi0vQJyuZ6OQ3AwaydPHTZjqwEJQCqduNbQppW5ZxjQD5oppBnrsdA8AMxlsNxjB0lRAVa5vTSHu0XpmwLIWit\/ioAAACAQpuf6d4a4TuH9BvJxFayYj9DAEvGHN2iz5HeuzeGH+HuH0qKVix6ktJPMulHpfT4pvOa2DZmanGFFEp6xdWROjFywLK\/u3kbajD5Stm+9lZ5PXmfvvhrJCuk4+ePSS1ojpTjAidsmIQlhvYg4AlL3+8jQh2Q4GbPk4zoIGDCobYAAAAIhHxEx2uaIvk=. Accessed 18 Apr 2024."},{"issue":"4","key":"2506_CR36","first-page":"931","volume":"15","author":"CG Lim","year":"2019","unstructured":"Lim CG, Jeong YS, Choi HJ. Survey of temporal information extraction. J Inf Process Syst. 2019;15(4):931\u201356.","journal-title":"J Inf Process Syst."},{"key":"2506_CR37","doi-asserted-by":"crossref","unstructured":"Yu S. Regular languages. In: Handbook of formal languages. Heidelberg: Springer; 1997. p. 41\u2013110.","DOI":"10.1007\/978-3-642-59136-5_2"},{"issue":"4","key":"2506_CR38","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1109\/MSP.2022.3155906","volume":"39","author":"TK Ho","year":"2022","unstructured":"Ho TK, Luo YF, Guido RC. Explainability of Methods for Critical Information Extraction From Clinical Documents: A survey of representative works. IEEE Signal Process Mag. 2022;39(4):96\u2013106.","journal-title":"IEEE Signal Process Mag."},{"key":"2506_CR39","unstructured":"Str\u00f6tgen J, Gertz M. Heideltime: High quality rule-based extraction and normalization of temporal expressions. In: Proceedings of the 5th international workshop on semantic evaluation. Uppsala: Association for Computational Linguistics; 2010. p. 321\u20134."},{"key":"2506_CR40","unstructured":"Manfredi G, Str\u00f6tgen J, Zell J, Gertz M. HeidelTime at EVENTI: Tuning Italian resources and addressing TimeML\u2019s empty tags. In: Proceedings of the Fourth International Workshop EVALITA. Pisa: Pisa University Press; 2014. p. 39\u201343."},{"issue":"5","key":"2506_CR41","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1136\/amiajnl-2013-001628","volume":"20","author":"W Sun","year":"2013","unstructured":"Sun W, Rumshisky A, Uzuner O. Evaluating temporal relations in clinical text: 2012 i2b2 challenge. J Am Med Inf Assoc. 2013;20(5):806\u201313.","journal-title":"J Am Med Inf Assoc."},{"key":"2506_CR42","doi-asserted-by":"crossref","unstructured":"Hamon T, Grabar N. Tuning HeidelTime for identifying time expressions in clinical texts in English and French. In: Proceedings of the 5th International Workshop on Health Text Mining and Information Analysis (Louhi). 2014. pp. 101\u20135.","DOI":"10.3115\/v1\/W14-1116"},{"key":"2506_CR43","unstructured":"Chase A. Reparse Python library. 2015. https:\/\/github.com\/andychase\/reparse. Accessed 18 Apr 2024."},{"issue":"1","key":"2506_CR44","first-page":"7","volume":"5","author":"S Kannan","year":"2014","unstructured":"Kannan S, Gurusamy V, Vijayarani S, Ilamathi J, Nithya M, Kannan S, et al. Preprocessing techniques for text mining. Int J Comput Sci Commun Netw. 2014;5(1):7\u201316.","journal-title":"Int J Comput Sci Commun Netw."},{"issue":"3","key":"2506_CR45","doi-asserted-by":"publisher","first-page":"262","DOI":"10.7763\/LNSE.2014.V2.134","volume":"2","author":"V Balakrishnan","year":"2014","unstructured":"Balakrishnan V, Lloyd-Yemoh E. Stemming and lemmatization: A comparison of retrieval performances. Lect Notes Softw Eng. 2014;2(3):262\u20137.","journal-title":"Lect Notes Softw Eng."}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-024-02506-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-024-02506-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-024-02506-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T13:08:59Z","timestamp":1713877739000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-024-02506-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,23]]},"references-count":45,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["2506"],"URL":"https:\/\/doi.org\/10.1186\/s12911-024-02506-2","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,23]]},"assertion":[{"value":"4 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 April 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 April 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":"The need for ethics approval is deemed unnecessary according to national regulations. In particular, according to the rules from the Italian Medicines Agency (available at: ExternalRef removed), retrospective studies using administrative databases do not require Ethics Committee protocol approval.The need for consent to participate is deemed unnecessary according to national regulations. In particular, see the rules of the Italian Privacy Authority available at ExternalRef removed and the European Union regulation n. 2016\/679 (GDPR) Art. 1 c. 1 (ExternalRef removed), Art. 4 c.1 (ExternalRef removed) and Recital 26 (ExternalRef removed).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","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":"107"}}