<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">ketendo</journal-id><journal-title-group><journal-title xml:lang="ru">Клиническая и экспериментальная тиреоидология</journal-title><trans-title-group xml:lang="en"><trans-title>Clinical and experimental thyroidology</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1995-5472</issn><issn pub-type="epub">2310-3787</issn><publisher><publisher-name>Endocrinology Research Centre</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.14341/ket12377</article-id><article-id custom-type="elpub" pub-id-type="custom">ketendo-12377</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Обзоры литературы</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Review of literature</subject></subj-group></article-categories><title-group><article-title>Эффективность систем поддержки принятия врачебных решений: способы и результаты оценки</article-title><trans-title-group xml:lang="en"><trans-title>Efficacy of clinical decision support systems: methods and estimates</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6733-0958</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Реброва</surname><given-names>Ольга Юрьевна</given-names></name><name name-style="western" xml:lang="en"><surname>Rebrova</surname><given-names>Olga Yu.</given-names></name></name-alternatives><bio xml:lang="ru"><p>д.м.н.</p></bio><bio xml:lang="en"><p>MD, PhD</p></bio><email xlink:type="simple">o.yu.rebrova@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Национальный медицинский исследовательский центр эндокринологии; Российский национальный исследовательский медицинский университет им. Н.И. Пирогова</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Endocrinology Research Centre; The Russian National Research Medical University named after N.I. Pirogov</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2019</year></pub-date><pub-date pub-type="epub"><day>03</day><month>07</month><year>2020</year></pub-date><volume>15</volume><issue>4</issue><fpage>148</fpage><lpage>155</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Реброва О.Ю., 2019</copyright-statement><copyright-year>2019</copyright-year><copyright-holder xml:lang="ru">Реброва О.Ю.</copyright-holder><copyright-holder xml:lang="en">Rebrova O.Y.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.cet-endojournals.ru/jour/article/view/12377">https://www.cet-endojournals.ru/jour/article/view/12377</self-uri><abstract><p>Система поддержки принятия врачебных решений (СППВР) – это информационная медицинская технология, проходящая свой жизненный цикл. Оценка ее эффективности и безопасности должна осуществляться на разных его этапах – разработки, клинических исследований, государственной регистрации, клинико-экономического анализа, оценки медицинских технологий. К настоящему времени эффективность и безопасность СППВР варьирует и является неоднозначной – есть как успехи, так и неудачи. Выполнены сотни клинических исследований, более сотни их систематических обзоров. При оценке эффективности и безопасности СППВР обычно оценивают два типа исходов: показатели медицинской помощи (объем, время, затраты и т.д.), исходы пациентов (суррогатные и истинные). Наблюдаемое некоторое увеличение приверженности врачей к клиническим рекомендациям в результате их включения в СППВР приводило к незначительному влиянию на суррогатные исходы, а влияние на клинически значимые исходы пациентов полностью отсутствует. При этом слабое повышение риска в отношении исходов пациентов обнаружено только в единичных исследованиях. Методологическое качество доказательной базы пока является весьма низким. В связи с этим к этапу лицензирования пока подошли немногочисленные продукты на основе искусственного интеллекта. Область СППВР является развивающейся, но пока недостаточно изученной, и впереди длинный путь до настоящих успехов. Существует большой разрыв между постулируемыми и эмпирически продемонстрированными преимуществами СППВР.</p></abstract><trans-abstract xml:lang="en"><p>Clinical decision support (CDS) systems are the medical technologies that go through their life cycle. Evaluation of effectiveness and safety should be carried out at its various stages – at the development, in clinical trials, licensing, clinical and economic analysis, health technologies assessment. To date, the effectiveness and safety of CDS systems vary and are ambiguous – there are both successes and failures. Hundreds of clinical trials are carried out, and more than a hundred of systematic reviews are published. When evaluating the efficacy and safety of CDS systems, two types of outcomes are usually estimated: indicators of medical care (volume, time, costs, etc.), and patient outcomes (clinical and surrogate). A slight increase in physicians’ adherence to clinical guidelines has been observed, but it had very small influence on surrogate outcomes, and there is no effect on clinical patient outcomes. A slight increase in risk with respect to patient outcomes was found in only a few studies. However, the methodological quality of the evidence is very low. In this regard, a few products based on artificial intelligence have so far approached the licensing phase. The field of CDS systems is developing, but not yet sufficiently studied, and there is a long way to real successes ahead. Meanwhile, there is a wide gap between the postulated and empirically demonstrated benefits of CDS systems.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>системы поддержки принятия врачебных решений</kwd><kwd>клинические исследования</kwd><kwd>эффективность</kwd><kwd>безопасность</kwd><kwd>качество доказательств</kwd><kwd>истинные исходы</kwd><kwd>суррогатные исходы</kwd></kwd-group><kwd-group xml:lang="en"><kwd>clinical decision support system</kwd><kwd>clinical trials</kwd><kwd>efficacy</kwd><kwd>safety</kwd><kwd>effectiveness</kwd><kwd>evidence quality</kwd><kwd>clinical endpoint</kwd><kwd>surrogate endpoint</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Гусев А.В., Зарубина Т.В. Поддержка принятия врачебных решений в медицинских информационных системах медицинской организации // Врач и информационные технологии. 2017. №2. С. 60-72. [Gusev A.V., Zarubina T.V. Clinical Decisions Support in medical information systems of a medical organization // Vrach i informacionnye tehnologii. 2017;(2):60-72. (In Russ.)]</mixed-citation><mixed-citation xml:lang="en">Гусев А.В., Зарубина Т.В. Поддержка принятия врачебных решений в медицинских информационных системах медицинской организации // Врач и информационные технологии. 2017. №2. С. 60-72. [Gusev A.V., Zarubina T.V. Clinical Decisions Support in medical information systems of a medical organization // Vrach i informacionnye tehnologii. 2017;(2):60-72. (In Russ.)]</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Реброва О.Ю. Жизненный цикл систем поддержки принятия врачебных решений как медицинских технологий // Врач и информационные технологии. 2020. №1. С. 27-37. [Rebrova O.Yu. Life cycle of decision support systems as medical technologies // Vrach i informacionnye tehnologii. 2020;(1): 27-37. (In Russ.)]</mixed-citation><mixed-citation xml:lang="en">Реброва О.Ю. Жизненный цикл систем поддержки принятия врачебных решений как медицинских технологий // Врач и информационные технологии. 2020. №1. С. 27-37. [Rebrova O.Yu. Life cycle of decision support systems as medical technologies // Vrach i informacionnye tehnologii. 2020;(1): 27-37. (In Russ.)]</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Письмо Росздравнадзора “О программном обеспечении” от 13.02.2020. [Pis’mo Roszdravnadzora “O programmnom obespechenii” ot 13.02.2020. (In Russ.)] https://www.roszdravnadzor.ru/i/upload/images/ 2020/2/14/1581670651.93473-1-10822.pdf</mixed-citation><mixed-citation xml:lang="en">Письмо Росздравнадзора “О программном обеспечении” от 13.02.2020. [Pis’mo Roszdravnadzora “O programmnom obespechenii” ot 13.02.2020. (In Russ.)] https://www.roszdravnadzor.ru/i/upload/images/ 2020/2/14/1581670651.93473-1-10822.pdf</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Black AD, Car J, Pagliari C, et al. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med. 2011;8(1):e1000387. https://doi.org/10.1371/journal.pmed.1000387.</mixed-citation><mixed-citation xml:lang="en">Black AD, Car J, Pagliari C, et al. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med. 2011;8(1):e1000387. https://doi.org/10.1371/journal.pmed.1000387.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Bright TJ, Wong A, Dhurjati R, et al. Effect of clinical decision-support systems. A systematic review. Ann Intern Med. 2012;157:29-43. doi: 10.7326/0003-4819-157-1-201207030-00450.</mixed-citation><mixed-citation xml:lang="en">Bright TJ, Wong A, Dhurjati R, et al. Effect of clinical decision-support systems. A systematic review. Ann Intern Med. 2012;157:29-43. doi: 10.7326/0003-4819-157-1-201207030-00450.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Moja L, Kwag KH, Lytras T, et al. Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. Am J Public Health. 2014; 104(12):e12–e22. https://doi.org/10.2105/AJPH.2014.302164.</mixed-citation><mixed-citation xml:lang="en">Moja L, Kwag KH, Lytras T, et al. Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. Am J Public Health. 2014; 104(12):e12–e22. https://doi.org/10.2105/AJPH.2014.302164.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Varghese J, Kleine M, Gessner SDI, et al. Effects of computerized decision support system implementations on patient outcomes in inpatient care: a systematic review. J Am Med Inform Assoc. 2018;25(5):593-602. https://doi.org/10.1093/jamia/ocx100.</mixed-citation><mixed-citation xml:lang="en">Varghese J, Kleine M, Gessner SDI, et al. Effects of computerized decision support system implementations on patient outcomes in inpatient care: a systematic review. J Am Med Inform Assoc. 2018;25(5):593-602. https://doi.org/10.1093/jamia/ocx100.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Pombo N, Araújo P, Viana J. Knowledge discovery in clinical decision support systems for pain management: a systematic review. Artif Intell Med. 2014;60(1):1-11. https://doi.org/10.1016/j.artmed.2013.11.005.</mixed-citation><mixed-citation xml:lang="en">Pombo N, Araújo P, Viana J. Knowledge discovery in clinical decision support systems for pain management: a systematic review. Artif Intell Med. 2014;60(1):1-11. https://doi.org/10.1016/j.artmed.2013.11.005.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Tomaselli Muensterman E, Tisdale JE. Predictive analytics for identification of patients at risk for QT interval prolongation: a systematic review. Pharmacotherapy. 2018;38(8):813-821. https://doi.org/10.1002/phar.2146.</mixed-citation><mixed-citation xml:lang="en">Tomaselli Muensterman E, Tisdale JE. Predictive analytics for identification of patients at risk for QT interval prolongation: a systematic review. Pharmacotherapy. 2018;38(8):813-821. https://doi.org/10.1002/phar.2146.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Arani LA, Hosseini A, Asadi F, et al. Intelligent computer systems for multiple sclerosis diagnosis: a systematic review of reasoning techniques and methods. Acta Inform Med. 2018;26(4):258-264. https://doi.org/10.5455/aim.2018.26.258-264.</mixed-citation><mixed-citation xml:lang="en">Arani LA, Hosseini A, Asadi F, et al. Intelligent computer systems for multiple sclerosis diagnosis: a systematic review of reasoning techniques and methods. Acta Inform Med. 2018;26(4):258-264. https://doi.org/10.5455/aim.2018.26.258-264.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Cresswell K, Callaghan M, Khan S, et al. Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: a systematic review. Health Informatics J. 1460458219900452, 2020 Jan 22 [Online ahead of print]</mixed-citation><mixed-citation xml:lang="en">Cresswell K, Callaghan M, Khan S, et al. Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: a systematic review. Health Informatics J. 1460458219900452, 2020 Jan 22 [Online ahead of print]</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Dissanayake PI, Colicchio TK, Cimino JJ. Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis. J Am Med Inform Assoc. 2020;27(1):159-174. https://doi.org/10.1093/jamia/ocz169.</mixed-citation><mixed-citation xml:lang="en">Dissanayake PI, Colicchio TK, Cimino JJ. Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis. J Am Med Inform Assoc. 2020;27(1):159-174. https://doi.org/10.1093/jamia/ocz169.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Liu X, Faes L, Kale AU, et al. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. The Lancet Digital Health. 2019;1(6):e271-e297. https://doi.org/10.1016/S2589-7500(19)30123-2.</mixed-citation><mixed-citation xml:lang="en">Liu X, Faes L, Kale AU, et al. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. The Lancet Digital Health. 2019;1(6):e271-e297. https://doi.org/10.1016/S2589-7500(19)30123-2.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Electronic health records vendor to pay largest criminal fine in Vermont history and a total of $145 million to resolve criminal and civil investigations. Department of Justice, U.S. Attorney’s Office, District of Vermont // https://www.justice.gov/usao-vt/pr/electronic-health-records-vendor-pay-largest-criminal-fine-vermont-history-and-total-145.</mixed-citation><mixed-citation xml:lang="en">Electronic health records vendor to pay largest criminal fine in Vermont history and a total of $145 million to resolve criminal and civil investigations. Department of Justice, U.S. Attorney’s Office, District of Vermont // https://www.justice.gov/usao-vt/pr/electronic-health-records-vendor-pay-largest-criminal-fine-vermont-history-and-total-145.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Roshanov PS, Fernandes N, Wilczynski JM, et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ. 346, f657, 2013 Feb 14. https://doi.org/10.1136/bmj.f657.</mixed-citation><mixed-citation xml:lang="en">Roshanov PS, Fernandes N, Wilczynski JM, et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ. 346, f657, 2013 Feb 14. https://doi.org/10.1136/bmj.f657.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Государственный реестр медицинских изделий и организаций (индивидуальных предпринимателей), осуществляющих производство и изготовление медицинских изделий. [Gosudarstvennyj reestr medicinskih izdelij i organizacij (individual’nyh predprinimatelej), osushhestvljajushhih proizvodstvo i izgotovlenie medicinskih izdelij. (In Russ.)] https://www.roszdravnadzor.ru/services/misearch</mixed-citation><mixed-citation xml:lang="en">Государственный реестр медицинских изделий и организаций (индивидуальных предпринимателей), осуществляющих производство и изготовление медицинских изделий. [Gosudarstvennyj reestr medicinskih izdelij i organizacij (individual’nyh predprinimatelej), osushhestvljajushhih proizvodstvo i izgotovlenie medicinskih izdelij. (In Russ.)] https://www.roszdravnadzor.ru/services/misearch</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
