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Sökning: WFRF:(Fitzpatrick K) > (2010-2014) > Assessing the cost ...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00005100naa a2200481 4500
001oai:DiVA.org:liu-53837
003SwePub
008100205s2010 | |||||||||||000 ||eng|
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-538372 URI
0247 a https://doi.org/10.1136/bmj.b56062 DOI
040 a (SwePub)liu
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Henriksson, Martinu Linköpings universitet,Utvärdering och hälsoekonomi,Hälsouniversitetet4 aut0 (Swepub:liu)marhe38
2451 0a Assessing the cost effectiveness of using prognostic biomarkers with decision models: case study in prioritising patients waiting for coronary artery surgery
264 c 2010-01-19
264 1b BMJ,c 2010
338 a electronic2 rdacarrier
520 a Objective To determine the effectiveness and cost effectiveness of using information from circulating biomarkers to inform the prioritisation process of patients with stable angina awaiting coronary artery bypass graft surgery. Design Decision analytical model comparing four prioritisation strategies without biomarkers (no formal prioritisation, two urgency scores, and a risk score) and three strategies based on a risk score using biomarkers: a routinely assessed biomarker (estimated glomerular filtration rate), a novel biomarker (C reactive protein), or both. The order in which to perform coronary artery bypass grafting in a cohort of patients was determined by each prioritisation strategy, and mean lifetime costs and quality adjusted life years (QALYs) were compared. Data sources Swedish Coronary Angiography and Angioplasty Registry (9935 patients with stable angina awaiting coronary artery bypass grafting and then followed up for cardiovascular events after the procedure for 3.8 years), and meta-analyses of prognostic effects (relative risks) of biomarkers. Results The observed risk of cardiovascular events while on the waiting list for coronary artery bypass grafting was 3 per 10 000 patients per day within the first 90 days (184 events in 9935 patients). Using a cost effectiveness threshold of 20 pound 000-30 pound 000 ((sic)22 000-(sic)33 000; $32 000-$48 000) per additional QALY, a prioritisation strategy using a risk score with estimated glomerular filtration rate was the most cost effective strategy (cost per additional QALY was andlt;410 pound compared with the Ontario urgency score). The impact on population health of implementing this strategy was 800 QALYs per 100 000 patients at an additional cost of 245 pound 000 to the National Health Service. The prioritisation strategy using a risk score with C reactive protein was associated with lower QALYs and higher costs compared with a risk score using estimated glomerular filtration rate. Conclusion Evaluating the cost effectiveness of prognostic biomarkers is important even when effects at an individual level are small. Formal prioritisation of patients awaiting coronary artery bypass grafting using a routinely assessed biomarker (estimated glomerular filtration rate) along with simple, routinely collected clinical information was cost effective. Prioritisation strategies based on the prognostic information conferred by C reactive protein, which is not currently measured in this context, or a combination of C reactive protein and estimated glomerular filtration rate, is unlikely to be cost effective. The widespread practice of using only implicit or informal means of clinically ordering the waiting list may be harmful and should be replaced with formal prioritisation approaches.
653 a MEDICINE
653 a MEDICIN
7001 a Damant, Jacquelineu UCL4 aut
7001 a K Fitzpatrick, Natalieu UCL4 aut
7001 a Abrams, Keithu University of Leicester4 aut
7001 a Hingorani, Aroon Du UCL4 aut
7001 a Stenestrand, Ulfu Östergötlands Läns Landsting,Linköpings universitet,Kardiologi,Hälsouniversitetet,Kardiologiska kliniken4 aut0 (Swepub:liu)ulfst38
7001 a Janzon, Magnusu Östergötlands Läns Landsting,Linköpings universitet,Kardiologi,Hälsouniversitetet,Kardiologiska kliniken4 aut0 (Swepub:liu)magja75
7001 a Feder, Geneu University of Bristol4 aut
7001 a Keogh, Bruceu UCL4 aut
7001 a Shipley, Martin Ju UCL4 aut
7001 a Kaski, Juan-Carlosu University of London4 aut
7001 a Timmis, Adamu Barts and London Medical School4 aut
7001 a Sculpher, Marku University of York4 aut
7001 a Hemingway, Harryu UCL4 aut
7102 a Linköpings universitetb Utvärdering och hälsoekonomi4 org
7730 t BRITISH MEDICAL JOURNALd : BMJg 340q 340x 0959-535X
7730 t BMJd : BMJg 340q 340x 0959-8138x 1468-5833
8564 u https://liu.diva-portal.org/smash/get/diva2:292197/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print
8564 u https://www.bmj.com/content/340/bmj.b5606.full.pdf
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-53837
8564 8u https://doi.org/10.1136/bmj.b5606

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