{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T18:59:01Z","timestamp":1787165941807,"version":"build-2736575974"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,2,27]],"date-time":"2025-02-27T00:00:00Z","timestamp":1740614400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"Valneva and Pfizer as part of their co-development of a Lyme disease vaccine"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Lyme disease (LD) is the most common vector-borne disease in the United States, though traditional LD surveillance underestimates the burden of disease. We validated algorithms for early localized and disseminated LD, with and without LD-specific diagnosis codes, in states with high incidence and their neighboring states with low LD incidence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We identified cohorts of potential incident LD cases in administrative insurance claims data, October 2015\u2014October 2023, in 1 national and 1 regional insurer. Three algorithms were studied: a primary algorithm of an LD-specific diagnosis code and indicated antibiotic and 2 secondary algorithms for disseminated LD requiring a non\u2013LD-specific musculoskeletal or neurologic diagnosis code, an antibiotic, and an LD diagnostic test. We included individuals from high LD-incidence states and neighboring low LD-incidence states. We validated the algorithms using medical records for a sample of potential cases, classifying them according to modified surveillance case definitions. We calculated positive predictive values (PPVs) for each algorithm.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Overall, we identified 9483 potential LD cases in claims data and reviewed 841 medical records. The PPVs for the primary algorithm were 90.7% and 81.3% in high-incidence and neighboring states, respectively, when suspect, probable, and confirmed cases were included; they were 76.6% and 28.0% when only confirmed and probable were included. For confirmed and possible cases, the secondary musculoskeletal algorithm PPVs were 12.9% and 4.1%, and the secondary neurologic algorithm PPVs were 6.2% and 1.8% in high-incidence and neighboring states, respectively.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study found that claims-based algorithms requiring diagnosis codes for LD or for related symptoms, in addition to other criteria, can identify cohorts of true LD cases. These algorithms, adjusted for PPV, can be used to estimate LD incidence in the United States.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ofid\/ofaf109","type":"journal-article","created":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T23:20:14Z","timestamp":1740525614000},"source":"Crossref","is-referenced-by-count":5,"title":["Validation of Algorithms to Detect Acute and Disseminated Lyme Disease in U.S. Administrative Claims Data"],"prefix":"10.1093","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2846-7879","authenticated-orcid":false,"given":"Sheryl A","family":"Kluberg","sequence":"first","affiliation":[{"name":"Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute , Boston, Massachusetts ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noelle M","family":"Cocoros","sequence":"additional","affiliation":[{"name":"Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute , Boston, Massachusetts ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3982-6515","authenticated-orcid":false,"given":"June","family":"O\u2019Neill","sequence":"additional","affiliation":[{"name":"Department of Population Medicine, Harvard Pilgrim Health Care Institute , Boston, Massachusetts ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9579-6982","authenticated-orcid":false,"given":"Thomas G","family":"Boyce","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Marshfield Clinic Research Institute, Marshfield Clinic Health System , Marshfield, Wisconsin ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8056-3302","authenticated-orcid":false,"given":"Maria E","family":"Sundaram","sequence":"additional","affiliation":[{"name":"Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute , Marshfield, Wisconsin ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Schotthoefer","sequence":"additional","affiliation":[{"name":"Integrated Research and Development Laboratory, Marshfield Clinic Research Institute , Marshfield, Wisconsin ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0618-7895","authenticated-orcid":false,"given":"Robert T","family":"Greenlee","sequence":"additional","affiliation":[{"name":"Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute , Marshfield, Wisconsin ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Djeneba Audrey","family":"Djibo","sequence":"additional","affiliation":[{"name":"CVS Healthspire Life Sciences Solutions, CVS Health , Blue Bell, Pennsylvania ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheryl N","family":"McMahill-Walraven","sequence":"additional","affiliation":[{"name":"CVS Healthspire Life Sciences Solutions, CVS Health , Blue Bell, Pennsylvania ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Aucott","sequence":"additional","affiliation":[{"name":"Lyme Disease Research Center, Division of Rheumatology, Department of Medicine, Johns Hopkins University School of Medicine , Baltimore, Maryland ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer C","family":"Mo\u00efsi","sequence":"additional","affiliation":[{"name":"Vaccine Medical Affairs, Pfizer Inc. , Paris ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1246-530X","authenticated-orcid":false,"given":"Luis","family":"Jodar","sequence":"additional","affiliation":[{"name":"Vaccine Medical Affairs, Pfizer Inc. , New York, New York ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4254-3705","authenticated-orcid":false,"given":"Sarah J","family":"Willis","sequence":"additional","affiliation":[{"name":"Vaccine Medical Affairs, Pfizer, Inc. , Cambridge, Massachusetts ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James H","family":"Stark","sequence":"additional","affiliation":[{"name":"Vaccine Medical Affairs, Pfizer, Inc. , Cambridge, Massachusetts ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,2,27]]},"reference":[{"key":"2025052712075095900_ofaf109-B1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.15585\/mmwr.ss6622a1","article-title":"Surveillance for Lyme disease\u2014United States, 2008\u20132015","volume":"66","author":"Schwartz","year":"2017","journal-title":"MMWR Surveill Summ"},{"key":"2025052712075095900_ofaf109-B2","author":"United States Environmental Protection Agency"},{"key":"2025052712075095900_ofaf109-B3","doi-asserted-by":"crossref","first-page":"e200319","DOI":"10.1001\/jamanetworkopen.2020.0319","article-title":"Current and future spatiotemporal patterns of Lyme disease reporting in the northeastern United States","volume":"3","author":"Bisanzio","year":"2020","journal-title":"JAMA Netw Open"},{"key":"2025052712075095900_ofaf109-B4","author":"U.S. Centers for Disease Control and 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Maryland","volume":"65","author":"Rutz","year":"2018","journal-title":"Zoonoses Public Health"},{"key":"2025052712075095900_ofaf109-B15","doi-asserted-by":"crossref","DOI":"10.3399\/bjgpopen20X101050","article-title":"GP coding behaviour for non-specific clinical presentations: a pilot study","volume":"4","author":"Tulloch","year":"2020","journal-title":"BJGP Open"},{"key":"2025052712075095900_ofaf109-B16","author":"Kluberg","year":"2024"},{"key":"2025052712075095900_ofaf109-B17","author":"National Notifiable Diseases Surveillance System, U.S. CDC"},{"key":"2025052712075095900_ofaf109-B18","doi-asserted-by":"crossref","first-page":"118","DOI":"10.15585\/mmwr.mm7306a1","article-title":"Surveillance for Lyme disease after implementation of a revised case definition\u2014United States, 2022","volume":"73","author":"Kugeler","year":"2024","journal-title":"MMWR Morb Mortal Wkly Rep"},{"key":"2025052712075095900_ofaf109-B19","doi-asserted-by":"crossref","first-page":"e137","DOI":"10.1097\/MLR.0000000000000524","article-title":"Validity of using inpatient and outpatient administrative codes to identify acute venous thromboembolism: the CVRN VTE study","volume":"55","author":"Fang","year":"2017","journal-title":"Med Care"},{"key":"2025052712075095900_ofaf109-B20","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.2147\/CLEP.S335621","article-title":"Positive predictive value of COVID-19 ICD-10 diagnosis codes across calendar time and clinical setting","volume":"13","author":"Lynch","year":"2021","journal-title":"Clin Epidemiol"},{"key":"2025052712075095900_ofaf109-B21","doi-asserted-by":"crossref","first-page":"1290","DOI":"10.1002\/pds.5662","article-title":"Validation of an algorithm to identify fractures among patients within the Veterans Health Administration","volume":"32","author":"Horton","year":"2023","journal-title":"Pharmacoepidemiol Drug 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