{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T21:26:29Z","timestamp":1757453189005,"version":"3.37.3"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,3,26]],"date-time":"2022-03-26T00:00:00Z","timestamp":1648252800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,3,26]],"date-time":"2022-03-26T00:00:00Z","timestamp":1648252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["GNT1131932"],"award-info":[{"award-number":["GNT1131932"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Acute Rheumatic Fever (ARF) is a critically important condition for which there is no diagnostic test. Diagnosis requires the use of a set of criteria comprising clinical, laboratory, electrocardiographic and echocardiographic findings. The complexity of the algorithm and the fact that clinicians lack familiarity with ARF, make ARF diagnosis ideally suited to an electronic decision support tool. The <jats:italic>ARF Diagnosis Calculator<\/jats:italic> was developed to assist clinicians in diagnosing ARF and correctly assign categories of \u2018possible, \u2018probable\u2019 or \u2018definite\u2019 ARF. This research aimed to evaluate the acceptability, accuracy, and test performance of the <jats:italic>ARF Diagnosis Calculator.<\/jats:italic><\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>Three strategies were used to provide triangulation of data. Users of the calculator employed at Top End Health Service, Northern Territory, Australia were invited to participate in an online survey<jats:italic>,<\/jats:italic> and clinicians with ARF expertise were invited to participate in semi-structured interviews. Qualitative data were analysed using inductive analysis. Performance of the calculator in correctly diagnosing ARF was assessed using clinical data from 35 patients presenting with suspected ARF. Diagnoses obtained from the calculator were compared using the Kappa statistic with those obtained from a panel of expert clinicians.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Survey responses were available from 23 Top End Health Service medical practitioners, and interview data were available from five expert clinicians. Using a 6-point Likert scale, participants highly recommended the <jats:italic>ARF Diagnosis Calculator<\/jats:italic> (median 6, IQR 1), found it easy to use (median 5, IQR 1) and believed the calculator helped them diagnose ARF (median 5, IQR 1). Clinicians with ARF expertise noted that electronic decision making is not a substitute for clinical experience. There was high agreement between the <jats:italic>ARF Diagnosis Calculator<\/jats:italic> and the \u2018gold standard\u2019 ARF diagnostic process (\u03ba\u2009=\u20090.767, 95% CI: 0.568\u20130.967). Incorrect assignment of diagnosis occurred in 4\/35 (11%) patients highlighting the greater accuracy of expert clinical input for ambiguous presentations. Sixteen changes were incorporated into a revised version of the calculator.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The <jats:italic>ARF Diagnosis Calculator<\/jats:italic> is an easy-to-use, accessible tool, but it does not replace clinical expertise. The calculator performed well amongst clinicians and is an acceptable tool for use within the clinical setting with a high level of accuracy in comparison to the gold standard diagnostic process. Effective resources to support clinicians are critically important for improving the quality of care of ARF.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12911-022-01816-7","type":"journal-article","created":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T01:03:50Z","timestamp":1648515830000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Evaluation of an ARF diagnosis calculator: a survey and content analysis"],"prefix":"10.1186","volume":"22","author":[{"given":"Elizabeth","family":"Fisher","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"James","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Diana","family":"Mosca","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bart J.","family":"Currie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna P.","family":"Ralph","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,3,26]]},"reference":[{"unstructured":"Australian Institute of Health and Welfare. Acute rheumatic fever and rheumatic hart disease in Australia, 2015\u20132019. Cat.no. CVD 90. Canberra: AIHW; 2021. Available from: https:\/\/www.aihw.gov.au\/getmedia\/ed8003f2-f2d6-41fc-ac7e-7ab5189f56ac\/Acute-rheumatic-fever-and-rheumatic-heart-disease-in-Australia-2015-2019.pdf.aspx?inline=true.","key":"1816_CR1"},{"key":"1816_CR2","first-page":"1","volume":"368","author":"AP Ralph","year":"2013","unstructured":"Ralph AP, Carapetis JR. Group A streptococcal diseases and their global burden. Current topics in microbiology and immunology. 2013;368:1-27.","journal-title":"Curr Top Microbiol Immunol"},{"issue":"5","key":"1816_CR3","doi-asserted-by":"publisher","first-page":"220","DOI":"10.5694\/mja2.50851","volume":"214","author":"AP Ralph","year":"2021","unstructured":"Ralph AP, Noonan S, Wade V, Currie BJ. The 2020 Australian guideline for prevention, diagnosis and management of acute rheumatic fever and rheumatic heart disease. Med J Aust. 2021;214(5):220-7","journal-title":"Med J Aust"},{"issue":"20","key":"1816_CR4","doi-asserted-by":"publisher","first-page":"1806","DOI":"10.1161\/CIR.0000000000000205","volume":"131","author":"MH Gewitz","year":"2015","unstructured":"Gewitz MH, Baltimore RS, Tani LY, Sable CA, Shulman ST, Carapetis J, et al. Revision of the Jones Criteria for the diagnosis of acute rheumatic fever in the era of Doppler echocardiography: a scientific statement from the American Heart Association. Circulation. 2015;131(20):1806-18.","journal-title":"Circulation"},{"key":"1816_CR5","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1001\/jama.1944.02850430015005","volume":"126","author":"T Jones","year":"1944","unstructured":"Jones T. The diagnosis of rheumatic fever. J Am Med Assoc. 1944;126:481-4.","journal-title":"J Am Med Assoc"},{"unstructured":"Remond M. Informing the prevention, diagnosis and management of acute rheumatic fever and rheumatic heart disease in Aboriginal Australian and Torres Strait Islander populations. [Dissertation]. Townsville: James Cook University; 2014.","key":"1816_CR6"},{"unstructured":"RHDAustralia (ARF\/RHD writing group). The 2020 Australian guideline for prevention, diagnosis and management of acute rheumatic fever and rheumatic heart disease (3rd edition) Darwin: Menzies School of Health Research; 2020. Available from: https:\/\/www.rhdaustralia.org.au\/arf-rhd-guideline","key":"1816_CR7"},{"doi-asserted-by":"crossref","unstructured":"Wakerman J, Humphreys J, Bourke L, Dunbar T, Jones M, Carey TA, et al. Assessing the Impact and Cost of Short-Term Health Workforce in Remote Indigenous Communities in Australia: A Mixed Methods Study Protocol. JMIR Res Protoc. 2016;5(4):e135.","key":"1816_CR8","DOI":"10.2196\/resprot.5831"},{"issue":"5","key":"1816_CR9","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1111\/1753-6405.13002","volume":"44","author":"K Hardie","year":"2020","unstructured":"Hardie K, Ralph AP, de Dassel JL. RHD elimination: action needed beyond secondary prophylaxis. Aust N Z J Public Health. 2020;44(5):427","journal-title":"Aust N Z J Public Health"},{"doi-asserted-by":"crossref","unstructured":"Paradis M, Stiell I, Atkinson KM, Guerinet J, Sequeira Y, Salter L, et al. Acceptability of a mobile clinical decision tool among emergency department clinicians: development and evaluation of the Ottawa rules app. JMIR mHealth and uHealth. 2018;6(6):e10263.","key":"1816_CR10","DOI":"10.2196\/10263"},{"issue":"1","key":"1816_CR11","doi-asserted-by":"publisher","first-page":"e15503","DOI":"10.2196\/15503","volume":"8","author":"AML Quan","year":"2020","unstructured":"Quan AML, Stiell I, Perry JJ, Paradis M, Brown E, Gignac J, et al. Mobile Clinical Decision Tools Among Emergency Department Clinicians: Web-Based Survey and Analytic Data for Evaluation of The Ottawa Rules App. JMIR mHealth and uHealth. 2020;8(1):e15503.","journal-title":"JMIR Mhealth Uhealth"},{"doi-asserted-by":"publisher","unstructured":"Waldemar V, Ademir Luiz Do P, Yusra A-L, Adriana T, Fabiana Santos P, Dayane A, et al. d-GDM: a mobile diagnostic decision support system for gestational diabetes. Arch Endocrinol Metab. 2019;63(5):524\u201330. doi:https:\/\/doi.org\/10.20945\/2359-3997000000171.","key":"1816_CR12","DOI":"10.20945\/2359-3997000000171"},{"unstructured":"World Health Organisation (WHO). mHealth: New horizons for health through mobile technologies: second global survey on eHealth. Geneva, Switzerland: WHO; 2011.","key":"1816_CR13"},{"unstructured":"RHDAustralia. ARF & RHD Guideline app - with ARF diagnosis calculator: iPhone. 2014. Available from: https:\/\/www.rhdaustralia.org.au\/apps.","key":"1816_CR14"},{"unstructured":"Creswell JW, Poth CN. Qualitative inquiry & research design. Choosing among five approaches (4th Edition). California: SAGE Publications; 2018.","key":"1816_CR15"},{"unstructured":"Telethon Kids Institute. START Study (Searching for a technology-driven acute rheumatic fever test). Available from: www.telethonkids.org.au\/projects\/working-towards-a-better-understanding-of-arf.","key":"1816_CR16"},{"doi-asserted-by":"crossref","unstructured":"Nemerimana M, Karambizi AC, Umutoniwase S, Barnhart DA, Beck K, Bihibindi VK, et al. Evaluation of an mHealth tool to improve nutritional assessment among infants under 6 months in paediatric development clinics in rural Rwanda: Quasi\u2010experimental study. Matern Child Nutr. 2021;17(4):e13201","key":"1816_CR17","DOI":"10.1111\/mcn.13201"},{"issue":"1","key":"1816_CR18","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1186\/s12887-020-02378-1","volume":"20","author":"HB Amoakoh","year":"2020","unstructured":"Amoakoh HB, Klipstein-Grobusch K, Agyepong IA, Amoakoh-Coleman M, Kayode GA, Reitsma JB, et al. Can an mhealth clinical decision-making support system improve adherence to neonatal healthcare protocols in a low-resource setting? BMC Pediatr. 2020;20(1):534","journal-title":"BMC Pediatr"},{"doi-asserted-by":"crossref","unstructured":"Charanthimath U, Katageri G, Kinshella M-LW, Mallapur A, Goudar S, Ramadurg U, et al. Community health worker evaluation of implementing an mHealth application to support maternal health care in Rural India. Front Glob Women's Health. 2021;2:645690.","key":"1816_CR19","DOI":"10.3389\/fgwh.2021.645690"},{"issue":"Suppl 10","key":"1816_CR20","first-page":"S3","volume":"213","author":"R Wyber","year":"2020","unstructured":"Wyber R, Noonan K, Halkon C, Enkel S, Cannon J, Haynes E, et al. Ending rheumatic heart disease in Australia: the evidence for a new approach. Med J Aust. 2020;213 Suppl 10:S3\u2013S31.","journal-title":"Med J Aust"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-022-01816-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-022-01816-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-022-01816-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T01:06:42Z","timestamp":1648516002000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-022-01816-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,26]]},"references-count":20,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["1816"],"URL":"https:\/\/doi.org\/10.1186\/s12911-022-01816-7","relation":{},"ISSN":["1472-6947"],"issn-type":[{"type":"electronic","value":"1472-6947"}],"subject":[],"published":{"date-parts":[[2022,3,26]]},"assertion":[{"value":"10 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 March 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Approval for the study was granted from the Human Research Ethics Committee of the Northern Territory Department of Health and Menzies School of Health Research (HREC-19-3505 and HREC-18-3126). Informed consent to participate was taken from each participant. For survey participants, the invitation email provided for entry into the survey, detailed that participation in the survey was an indication of informed consent for answers to be used for research and quality improvement purposes. Lastly, deidentified data collected from the START study (HREC-18-3126) for comparison of clinical panel vs ARF Diagnosis Calculator was from participants who had written informed consent for data to be used in future related research.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"77"}}