{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T14:17:00Z","timestamp":1790086620617,"version":"4.0.1"},"reference-count":41,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T00:00:00Z","timestamp":1659484800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000133","name":"Agency for Healthcare Research and Quality","doi-asserted-by":"publisher","award":["HS026257\u201001"],"award-info":[{"award-number":["HS026257\u201001"]}],"id":[{"id":"10.13039\/100000133","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Learning Health Systems"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Introduction<\/jats:title><jats:p>Learning health systems are challenged to combine computable biomedical knowledge (CBK) models. Using common technical capabilities of the World Wide Web (WWW), digital objects called Knowledge Objects, and a new pattern of activating CBK models brought forth here, we aim to show that it is possible to compose CBK models in more highly standardized and potentially easier, more useful ways.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Using previously specified compound digital objects called Knowledge Objects, CBK models are packaged with metadata, API descriptions, and runtime requirements. Using open\u2010source runtimes and a tool we developed called the KGrid Activator, CBK models can be instantiated inside runtimes and made accessible via RESTful APIs by the KGrid Activator. The KGrid Activator then serves as a gateway and provides a means to interconnect CBK model outputs and inputs, thereby establishing a CBK model composition method.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>To demonstrate our model composition method, we developed a complex composite CBK model from 42 CBK submodels. The resulting model called CM\u2010IPP is used to compute life\u2010gain estimates for individuals based their personal characteristics. Our result is an externalized, highly modularized CM\u2010IPP implementation that can be distributed and made runnable in any common server environment.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>CBK model composition using compound digital objects and the distributed computing technologies is feasible. Our method of model composition might be usefully extended to bring about large ecosystems of distinct CBK models that can be fitted and re\u2010fitted in various ways to form new composites. Remaining challenges related to the design of composite models include identifying appropriate model boundaries and organizing submodels to separate computational concerns while optimizing reuse potential.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Learning health systems need methods for combining CBK models from a variety of sources to create more complex and useful composite models. It is feasible to leverage Knowledge Objects and common API methods in combination to compose CBK models into complex composite models.<\/jats:p><\/jats:sec>","DOI":"10.1002\/lrh2.10325","type":"journal-article","created":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T08:45:19Z","timestamp":1659516319000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["<scp>CBK<\/scp>model composition using paired web services and executable functions: A demonstration for individualizing preventive services"],"prefix":"10.1002","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3471-3063","authenticated-orcid":false,"given":"Allen","family":"Flynn","sequence":"first","affiliation":[{"name":"Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Glen","family":"Taksler","sequence":"additional","affiliation":[{"name":"Cleveland Clinic, Internal Medicine and Geriatrics Cleveland Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tanner","family":"Caverly","sequence":"additional","affiliation":[{"name":"Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adam","family":"Beck","sequence":"additional","affiliation":[{"name":"Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Boisvert","sequence":"additional","affiliation":[{"name":"Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philip","family":"Boonstra","sequence":"additional","affiliation":[{"name":"School of Public Health University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nate","family":"Gittlen","sequence":"additional","affiliation":[{"name":"Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George","family":"Meng","sequence":"additional","affiliation":[{"name":"Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brooke","family":"Raths","sequence":"additional","affiliation":[{"name":"Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charles P.","family":"Friedman","sequence":"additional","affiliation":[{"name":"Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,8,3]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1197\/jamia.M3023"},{"key":"e_1_2_9_3_1","unstructured":"BlaomAD KiralyF LienartT SimillidesY ArenasD VollmerSJ.MLJ: a Julia package for composable machine learning. arXiv Preprint arXiv:2007.12285.2020."},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/258077.258078"},{"key":"e_1_2_9_5_1","doi-asserted-by":"crossref","unstructured":"B\u00e9zivinJ BouzitounaS Del FabroMD et al.A canonical scheme for model composition. 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