{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T13:42:49Z","timestamp":1783172569378,"version":"3.54.6"},"reference-count":23,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2025,4,30]],"date-time":"2025-04-30T00:00:00Z","timestamp":1745971200000},"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":["Telemedicine and e-Health"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>: Interprofessional electronic consultations (eConsults) can reduce health care utilization and improve access to specialty care. However, health care utilization and access impacts of eConsults for headache disorders remain incompletely characterized.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>: We conducted a retrospective, 1:3-matched cohort study comparing patients referred for in-person headache evaluations to patients who had a headache-related eConsult. The cohorts were propensity score-matched by age, sex, race, preferred language, provider specialty, insurance status, and medical comorbidities. Our primary outcome was the presence of one or more headache-related ambulatory encounters in the 12 months following the index referral date. We used univariable and conditional logistic regression models to ascertain the associations between referral type and outcome.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      : We identified 74 and 222 patients with eConsult and in-person referrals, respectively. Over the follow-up period, the proportion of patients with the primary outcome was significantly greater in the eConsult cohort than the in-person cohort (46.0% vs. 43.2%,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      &lt; 0.0001). A greater proportion of the in-person cohort had one or more ambulatory headache encounters in the 12 months preceding their referral than the eConsult cohort (10.8% vs. 5.4%,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      &lt; 0.0001). In the adjusted analysis, eConsult usage was not associated with significantly increased odds of the primary outcome (adjusted odds ratio [aOR] 1.1, 95% confidence interval [CI] 0.6\u20132.0,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      = 0.71), although patients with one or more ambulatory neurology encounters in the preceding 12 months had significantly increased odds of the primary outcome (aOR 3.1, 95% CI 1.2\u20137.9,\n                      <jats:italic toggle=\"yes\">p<\/jats:italic>\n                      = 0.015).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>: Compared to in-person referrals, eConsult use for headache was not associated with significantly increased odds of having subsequent ambulatory headache-related encounters.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1089\/tmj.2024.0483","type":"journal-article","created":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T19:58:29Z","timestamp":1736366309000},"page":"614-623","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Health Care Utilization Patterns Associated with eConsults for Headache: Insights from an Urban Academic Medical Center"],"prefix":"10.1177","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6240-106X","authenticated-orcid":false,"given":"Soonmyung","family":"Hwang","sequence":"first","affiliation":[{"name":"Icahn School of Medicine at Mount Sinai, New York, New York, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Parul","family":"Agarwal","sequence":"additional","affiliation":[{"name":"Department of Population Science and Health Policy, Icahn School of Medicine at Mount Sinai, New York, New York, USA."},{"name":"Institute for Health Care Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Dakov","sequence":"additional","affiliation":[{"name":"Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret H.","family":"Downes","sequence":"additional","affiliation":[{"name":"Icahn School of Medicine at Mount Sinai, New York, New York, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin R.","family":"Kummer","sequence":"additional","affiliation":[{"name":"Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA."},{"name":"Clinical Neuro-Informatics Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA."},{"name":"Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,4,30]]},"reference":[{"key":"e_1_3_7_2_2","doi-asserted-by":"publisher","DOI":"10.1377\/hlthaff.2016.1283"},{"issue":"1","key":"e_1_3_7_3_2","first-page":"E9","article-title":"A cost-effectiveness analysis of cardiology eConsults for medicaid patients","volume":"24","author":"Anderson D","year":"2018","unstructured":"Anderson D, , Villagra V, , Coman EN, et al. 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