{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T14:57:23Z","timestamp":1790521043310,"version":"4.1.0"},"reference-count":38,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Am J Hosp Palliat Care"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>As the patterns of chronic complex disease and death continue to evolve, the demand for palliative care continues to increase. Understanding key patterns in the population using machine learning allows for new insights.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>Using a large prospectively collected dataset on function and symptom burden to explore clinically distinct sub-groups of palliative care. These sub-groups were used to explore patterns of healthcare utilisation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>The Australian national Palliative Care Outcomes Collaboration data were used for K-means clustering and multivariable regression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting\/participants<\/jats:title>\n                    <jats:p>Adults aged \u226518 years who received palliative care and died between 1 January 2014 and 31 December 2023 (261\u00a0290 patients; 350\u00a0512 episodes of care).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Three stable episode-level clinical sub-groups were identified: \u2022\n                      <jats:bold>Sub-group 1<\/jats:bold>\n                      (119\u00a0901 episodes; 42.7%):\n                      <jats:bold>\n                        <jats:italic toggle=\"yes\">dependency-led<\/jats:italic>\n                      <\/jats:bold>\n                      ; very poor function; predominantly inpatient; shortest episode duration. \u2022\n                      <jats:bold>Sub-group 2<\/jats:bold>\n                      (57\u00a0453 episodes; 20.5%):\n                      <jats:bold>\n                        <jats:italic toggle=\"yes\">symptom-led<\/jats:italic>\n                      <\/jats:bold>\n                      ; intermediate function; community and inpatient care; mid-length duration. \u2022\n                      <jats:bold>Sub-group 3<\/jats:bold>\n                      (103\u00a0179 episodes; 36.8%):\n                      <jats:bold>\n                        <jats:italic toggle=\"yes\">function-preserved<\/jats:italic>\n                      <\/jats:bold>\n                      ; mild symptoms; community-based care; longest episode duration. In regression, Sub-group 1 and Sub-group 2 had exponentiated coefficients of 0.49 (95% CI 0.49-0.50) and 0.71 (0.70-0.72), respectively, relative to Sub-group 3. Between-cluster differences were greater among non-cancer episodes and varied according to proximity to death; these associations were attenuated after excluding episodes ending in death. Held-out R\n                      <jats:sup>2<\/jats:sup>\n                      was 0.261 for the cluster-based model and 0.316 for the individual-clinical-variable model.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>K-means clustering provided a concise, clinically interpretable representation of heterogeneity in specialist palliative care. Episode-level clinical sub-groups captured meaningful variation in service use while retaining much of the information contained in clinical measures, supporting prospective evaluation for service planning and care delivery.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/10499091261491646","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T18:45:30Z","timestamp":1790189130000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Identifying Clinical Sub-Groups Using Machine Learning: Functional Status, Symptom Burden, and Healthcare Utilisation From National Palliative Care Data"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8187-6025","authenticated-orcid":false,"given":"Battushig","family":"Migiddorj","sequence":"first","affiliation":[{"name":"University of Wollongong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Currow","sequence":"additional","affiliation":[{"name":"Flinders University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marijka","family":"Batterham","sequence":"additional","affiliation":[{"name":"University of New South Wales"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khin Than","family":"Win","sequence":"additional","affiliation":[{"name":"University of Wollongong"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"e_1_3_6_2_2","doi-asserted-by":"publisher","DOI":"10.1200\/jco.2014.58.6362"},{"key":"e_1_3_6_3_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.16840"},{"key":"e_1_3_6_4_2","doi-asserted-by":"publisher","DOI":"10.1200\/jco.2016.70.5046"},{"key":"e_1_3_6_5_2","doi-asserted-by":"publisher","DOI":"10.3205\/psm000089"},{"key":"e_1_3_6_6_2","doi-asserted-by":"publisher","DOI":"10.1177\/00469580231176855"},{"key":"e_1_3_6_7_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2702.2008.02580.x"},{"key":"e_1_3_6_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpainsymman.2020.06.037"},{"key":"e_1_3_6_9_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph20196871"},{"key":"e_1_3_6_10_2","doi-asserted-by":"publisher","DOI":"10.1080\/0284186X.2020.1736335"},{"key":"e_1_3_6_11_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-022-02513-y"},{"key":"e_1_3_6_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpainsymman.2025.08.009"},{"key":"e_1_3_6_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2025.105914"},{"key":"e_1_3_6_14_2","doi-asserted-by":"publisher","DOI":"10.3390\/cancers15051596"},{"key":"e_1_3_6_15_2","doi-asserted-by":"publisher","DOI":"10.1071\/ah08718"},{"key":"e_1_3_6_16_2","volume-title":"About PCOC","author":"Palliative Care Outcomes Collaboration","year":"2026","unstructured":"Palliative Care Outcomes Collaboration. 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