{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T17:55:14Z","timestamp":1791309314804,"version":"4.3.1"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:00:00Z","timestamp":1788912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Astute observers of health systems are aware that worldwide there is a clinical trend toward integrative and personalized models. Ayurveda, inherently by its theory and practice, a personalized system of healthcare. Evidence from Ayurvedic clinical settings shows its effectiveness in managing chronic diseases; however, a lack of comprehensive multi-centric and retrospective clinical data hampers the credibility of Ayurveda within research circles. Traditional research, particularly Randomized Controlled Trials (RCTs), is deemed unsuitable for evaluating Ayurveda because these trials focus on standardized interventions and do not account for the personalized and multifaceted nature of Ayurvedic practices. This study intends to demonstrate that routine electronic medical record (EMR) data can effectively be transformed into actionable real-world evidence to support Ayurvedic management of chronic conditions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Analysis was done using digitized Electronic Medical Records (EMR) Practo Insta, from the Institute of Ayurveda and Integrative Medicine, Bengaluru (and IIHNO Indore). Five clinical areas were assessed: Cancer (\n                      <jats:italic>n<\/jats:italic>\n                      = 36), Oral Mucositis (\n                      <jats:italic>n<\/jats:italic>\n                      = 89), Psoriasis (\n                      <jats:italic>n<\/jats:italic>\n                      = 38), Diabetes Mellitus (\n                      <jats:italic>n<\/jats:italic>\n                      = 65), and Infertility (\n                      <jats:italic>n<\/jats:italic>\n                      = 65). We used standardized metrics, including EORTC QLQ-C30, WHO Oral Mucositis grades, PASI, DLQI, and HbA1C, to measure outcomes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Improvements were observed across all clinical areas. In oncology, global QoL increased by 17%, functional scores rose by 10%, and symptomatic burden dropped by 48%. In Oral Mucositis, at the primary 3-week endpoint 57.3% (51\/89) of AGR patients achieved complete Grade 0 resolution versus 0% in PBMT. In Psoriasis, 76.3% of patients showed PASI improvement, and 92.1% reported better QoL. Diabetic participants exhibited noticeable reductions in blood glucose levels, with 85% reporting improved QoL. In infertility management, 58% of female participants successfully conceived within an average of 6 months, alongside improvements in secondary fertility and follicular parameters.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Integrating Ayurveda into mainstream healthcare requires a decisive shift toward robust, data-driven evidence. Evaluating personalized, multi-component interventions solely through conventional RCTs is limited, making the systematic use of Real-World Data (RWD) both necessary and appropriate. Standardizing routine EMR data translates nuanced Ayurvedic assessments into quantifiable metrics, bridging the epistemological gap between ancient clinical wisdom and modern scientific rigor to build the long-term evidence base.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1895750","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T04:44:18Z","timestamp":1788929058000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["From clinical records to community care: using real-world evidence in Ayurveda"],"prefix":"10.3389","volume":"13","author":[{"given":"Amritha Sindhu","family":"D","sequence":"first","affiliation":[{"name":"The University of Trans Disciplinary Health Sciences and Technology","place":["Bengaluru, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bhargavi","family":"N","sequence":"additional","affiliation":[{"name":"Institute 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