Evidence-based medicine as Bayesian decision-making
We review two recent trends: the emergence of evidence‐based medicine and the growing use of Bayesian statistics in medical applications. Evidence‐based medicine requires an integrated assessment of the available evidence, and associated uncertainty, but there is also an emphasis on decision‐making,...
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Veröffentlicht in: | Statistics in medicine 2000-12, Vol.19 (23), p.3291-3305 |
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description | We review two recent trends: the emergence of evidence‐based medicine and the growing use of Bayesian statistics in medical applications. Evidence‐based medicine requires an integrated assessment of the available evidence, and associated uncertainty, but there is also an emphasis on decision‐making, for individual patients, or at other points in the health‐care system. This demands consideration of the values and costs associated with potential outcomes. We argue that the natural statistical framework for evidence‐based medicine is a Bayesian approach to decision‐making that incorporates an integrated summary of the available evidence and associated uncertainty with assessment of utilities. We outline a practical agenda for further development. Copyright © 2000 John Wiley & Sons, Ltd. |
doi_str_mv | 10.1002/1097-0258(20001215)19:23<3291::AID-SIM627>3.0.CO;2-T |
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M.</creatorcontrib><title>Evidence-based medicine as Bayesian decision-making</title><title>Statistics in medicine</title><addtitle>Statist. Med</addtitle><description>We review two recent trends: the emergence of evidence‐based medicine and the growing use of Bayesian statistics in medical applications. Evidence‐based medicine requires an integrated assessment of the available evidence, and associated uncertainty, but there is also an emphasis on decision‐making, for individual patients, or at other points in the health‐care system. This demands consideration of the values and costs associated with potential outcomes. We argue that the natural statistical framework for evidence‐based medicine is a Bayesian approach to decision‐making that incorporates an integrated summary of the available evidence and associated uncertainty with assessment of utilities. We outline a practical agenda for further development. Copyright © 2000 John Wiley & Sons, Ltd.</description><subject>Bayes Theorem</subject><subject>Biological and medical sciences</subject><subject>Computerized, statistical medical data processing and models in biomedicine</subject><subject>Decision Making</subject><subject>Evidence-Based Medicine - methods</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Medical statistics</subject><issn>0277-6715</issn><issn>1097-0258</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqVkNFu0zAUQC0EYmXwC6gSEoIHF_u6jpMyIW1ljEqDVhA0iZcrx75B3tJ0xCvQv8dVQnnhBb_Yso6Prw5jJ1JMpBDwSorCcAE6fwFCCAlSv5TFDNSJgkLOZqeLt_zz4kMG5o2aiMl8-Rp4eY-NDs_us5EAY3hmpD5ij2K8ThapwTxkRzItVWRixNT5j-CpdcQrG8mP1-SDCy2NbRyf2R3FYNuxJxdi2LR8bW9C--0xe1DbJtKTYT9mX96dl_P3_HJ5sZifXnI3VcJw7asMVDoWDjT4vALy0jsyIre1ojzPja89yAqKQjrK6qlQWVVZDXmlrFPqmD3vvbfd5vuW4h2uQ3TUNLalzTaiAa1E6pLAsgddt4mxoxpvu7C23Q6lwH1M3FfBfRX8ExNlgaBwHxMxxcQ-JioUOF8iYJm0T4f_t1Xq8lc61EvAswGw0dmm7mybQh243BgD00Rd9dTP0NDuP0f752TDTTLz3hziHf06mG13g5lRRuPVxwvMVivz9axc4Sf1GxBMqEc</recordid><startdate>20001215</startdate><enddate>20001215</enddate><creator>Ashby, Deborah</creator><creator>Smith, Adrian F. 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M.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Statistics in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ashby, Deborah</au><au>Smith, Adrian F. M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evidence-based medicine as Bayesian decision-making</atitle><jtitle>Statistics in medicine</jtitle><addtitle>Statist. Med</addtitle><date>2000-12-15</date><risdate>2000</risdate><volume>19</volume><issue>23</issue><spage>3291</spage><epage>3305</epage><pages>3291-3305</pages><issn>0277-6715</issn><eissn>1097-0258</eissn><abstract>We review two recent trends: the emergence of evidence‐based medicine and the growing use of Bayesian statistics in medical applications. Evidence‐based medicine requires an integrated assessment of the available evidence, and associated uncertainty, but there is also an emphasis on decision‐making, for individual patients, or at other points in the health‐care system. This demands consideration of the values and costs associated with potential outcomes. We argue that the natural statistical framework for evidence‐based medicine is a Bayesian approach to decision‐making that incorporates an integrated summary of the available evidence and associated uncertainty with assessment of utilities. We outline a practical agenda for further development. 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subjects | Bayes Theorem Biological and medical sciences Computerized, statistical medical data processing and models in biomedicine Decision Making Evidence-Based Medicine - methods Female Humans Male Medical sciences Medical statistics |
title | Evidence-based medicine as Bayesian decision-making |
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