{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T22:38:45Z","timestamp":1779403125088,"version":"3.53.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686615","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,21]]},"abstract":"<jats:p>This study integrates agent-based modeling (ABM) and causal machine learning (ML) to assess the impact of clinicians\u2019 adherence to antibiotic guidelines in older adults hospitalized with community-acquired pneumonia (CAP). Using a synthetic population and longitudinal data, we estimate individual treatment effects of vancomycin via the longitudinal modified treatment policy (LMTP) algorithm and simulate clinical decision-making and MRSA transmission dynamics in a NetLogo-based ABM. We evaluate how varying hospital-level propensities toward vancomycin prescribing influence 30-day mortality under different causal and behavioral scenarios. Results show high model repeatability and confirm increased mortality among mechanically ventilated patients treated empirically with vancomycin. Integrating causal inference within ABM supports evidence-based antibiotic stewardship and privacy-preserving simulation of clinical behaviors.<\/jats:p>","DOI":"10.3233\/shti260180","type":"book-chapter","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T21:57:30Z","timestamp":1779400650000},"source":"Crossref","is-referenced-by-count":0,"title":["Integrating Causal Inference and Agent-Based Modelling to Assess the Impact of Clinicians\u2019 Guideline Adherence in Older Adults Hospitalized with Pneumonia"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5718-4240","authenticated-orcid":false,"given":"Fabrizio","family":"Pecoraro","sequence":"first","affiliation":[{"name":"Institute for Research on Population and Social Policies, National Research Council, Via Palestro, 32 \u2013 00185 \u2013 Rome, Italy"},{"name":"Department of Epidemiology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9021-5595","authenticated-orcid":false,"given":"Mattia","family":"Prosperi","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Opening the Personal Gate between Technology and Health Care"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI260180","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T21:57:30Z","timestamp":1779400650000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI260180"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,21]]},"ISBN":["9781643686615"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti260180","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,21]]}}}