Benefits and pitfalls of pooling datasets from comparable observational studies: combining US and Dutch nursing home studies
Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individ...
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| Published in | Palliative medicine Vol. 22; no. 6; pp. 750 - 759 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London, England
SAGE Publications
01.09.2008
Sage Publications Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0269-2163 1477-030X 1477-030X |
| DOI | 10.1177/0269216308094102 |
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| Abstract | Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individual subject data from observational studies that addresses differences in research design, illustrating the approach with two prospective observational studies on treatment and outcomes of lower respiratory tract infection in US and Dutch nursing home residents. Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures. In our pooled dataset, we were able to evaluate treatments and end-of-life decisions for comparable patients across settings, which suggested opportunities to improve care. In addition, greater variation in participants and treatments in the combined dataset allowed for subgroup analyses and interaction hypotheses, but required more complex analytic methods. Pitfalls included the large amount of time required for equating study procedures and variables and the need for additional funding. |
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| AbstractList | Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individual subject data from observational studies that addresses differences in research design, illustrating the approach with two prospective observational studies on treatment and outcomes of lower respiratory tract infection in US and Dutch nursing home residents. Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures. In our pooled dataset, we were able to evaluate treatments and end-of-life decisions for comparable patients across settings, which suggested opportunities to improve care. In addition, greater variation in participants and treatments in the combined dataset allowed for subgroup analyses and interaction hypotheses, but required more complex analytic methods. Pitfalls included the large amount of time required for equating study procedures and variables and the need for additional funding. Adapted from the source document. Research using pooled data concerning lower respiratory infection in nursing home patients from the Netherlands and the USA. Comparability of study design, measurements and population and the benefits and pitfalls of pooling data are described, with examples. [(BNI unique abstract)] 48 references Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individual subject data from observational studies that addresses differences in research design, illustrating the approach with two prospective observational studies on treatment and outcomes of lower respiratory tract infection in US and Dutch nursing home residents. Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures. In our pooled dataset, we were able to evaluate treatments and end-of-life decisions for comparable patients across settings, which suggested opportunities to improve care. In addition, greater variation in participants and treatments in the combined dataset allowed for subgroup analyses and interaction hypotheses, but required more complex analytic methods. Pitfalls included the large amount of time required for equating study procedures and variables and the need for additional funding.Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individual subject data from observational studies that addresses differences in research design, illustrating the approach with two prospective observational studies on treatment and outcomes of lower respiratory tract infection in US and Dutch nursing home residents. Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures. In our pooled dataset, we were able to evaluate treatments and end-of-life decisions for comparable patients across settings, which suggested opportunities to improve care. In addition, greater variation in participants and treatments in the combined dataset allowed for subgroup analyses and interaction hypotheses, but required more complex analytic methods. Pitfalls included the large amount of time required for equating study procedures and variables and the need for additional funding. Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individual subject data from observational studies that addresses differences in research design, illustrating the approach with two prospective observational studies on treatment and outcomes of lower respiratory tract infection in US and Dutch nursing home residents. Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures. In our pooled dataset, we were able to evaluate treatments and end-of-life decisions for comparable patients across settings, which suggested opportunities to improve care. In addition, greater variation in participants and treatments in the combined dataset allowed for subgroup analyses and interaction hypotheses, but required more complex analytic methods. Pitfalls included the large amount of time required for equating study procedures and variables and the need for additional funding. Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individual subject data from observational studies that addresses differences in research design, illustrating the approach with two prospective observational studies on treatment and outcomes of lower respiratory tract infection in US and Dutch nursing home residents. Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures. In our pooled dataset, we were able to evaluate treatments and end-of-life decisions for comparable patients across settings, which suggested opportunities to improve care. In addition, greater variation in participants and treatments in the combined dataset allowed for subgroup analyses and interaction hypotheses, but required more complex analytic methods. Pitfalls included the large amount of time required for equating study procedures and variables and the need for additional funding. [PUBLICATION ABSTRACT] |
| Author | Kruse, RL Ribbe, MW Szafara, KL Mehr, DR D'Agostino, RB van der Steen, JT van der Wal, G |
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| References | van der Steen JT, Kruse RL, Ooms ME, Ribbe MW, van der Wal G, Heintz LL 2004; 52 Higginson IJ 2005; 8 Ioannidis JPA, Lau J 1999; 25 van der Steen JT, Ooms ME, van der Wal G, Ribbe MW 2005; 25 Glance LG, Osler TM, Papadakos P 2000; 28 van der Steen JT, Ooms ME, van der Wal G, Ribbe MW 2002; 50 Simmonds MC, Higgins JP, Stewart LA, Tierney JF, Clarke MJ, Thompson SG 2005; 2 Fabiszewski KJ, Volicer B, Volicer L 1990; 263 Folstein MF, Folstein SE, McHugh PR 1975; 12 Mehr DR, Binder EF, Kruse RL, Zweig SC, Madsen R, D’Agostino RB 2001; 50 Morris JN, Fries BE, Mehr DR, Hawes C, Phillips C, Mor V 1994; 49 van der Steen JT, Mehr DR, Kruse RL, Ribbe MW, van der Wal G 2007; 8 Kaasa S, Hjermstad MJ, Loge JH 2006; 20 Rothwell PM, Eliasziw M, Gutnikov SA, Fox AJ, Taylor DW, Mayberg MR 2003; 361 Charlson ME, Ales KL, Simon R, MacKenzie CR 1987; 147 Helmes E, Caapo KG, Short JA 1987; 42 Kruse RL, Mehr DR, Boles KE, Lave JR, Binder EF, Madsen R 2004; 42 van der Steen JT, Mehr DR, Kruse RL, Ribbe MW, van der Wal G 2007; 22 Smith-Warner SA, Spiegelman D, Ritz J, Albanes D, Beeson WL, Bernstein L 2006; 163 Binder EF, Kruse RL, Sherman AK, Madsen R, Zweig SC, D’Agostino R 2003; 58 Stewart LA, Clarke MJ 1995; 14 Volicer L, Hurley AC, Lathi DC, Kowall NW 1994; 49 Kruse RL, Mehr DR, van der Steen JT, Ooms ME, Madsen RW, Sherman AK 2005; 3 Mehr DR, van der Steen JT, Kruse RL, Ooms ME, Rantz M, Ribbe MW 2003; 43 van der Steen JT, Ooms ME, Adèr HJ, Ribbe MW, van der Wal G 2002; 162 van der Steen JT, van der Wal G, Mehr DR, Ooms ME, Ribbe MW 2005; 19 van der Steen JT, Mehr DR, Kruse RL, Sherman AK, Madsen RW, D’Agostino RB 2006; 59 Justice AC, Covinsky KE, Berlin JA 1999; 130 Stewart LA, Tierney JF 2002; 25 van der Steen JT, Ooms ME, Mehr DR, van der Wal G 2002; 50 Mehr DR, Binder EF, Kruse RL, Zweig SC, Madsen R, Popejoy L 2001; 286 van der Steen JT, Kruse RL, van der Wal G, Mehr DR, Ribbe MW 2007; 151 Mulrow C, Langhorne P, Grimshaw J 1997; 127 Zeegers MPA, Heisterkamp SH, Kostense PJ, van der Windt DAWM, Scholten RJPM 2000; 144 Fery-Lemonnier E, Landais P, Loirat P, Kleinknecht D, Brivet F 1995; 21 Lambert PC, Sutton AJ, Abrams KR, Jones DR 2002; 55 van der Steen JT, Kruse RL, Mehr DR, Ribbe MW, van der Wal G 2007; 11 Morrison RS, Siu AL 2000; 284 Stukel TA, Fisher ES, Wennberg DE 2007; 297 Vickers AJ 2006; 7 Blettner M, Sauerbrei W, Schlehofer B, Scheuchenpflug T, Friedenreich C 1999; 28 Christakis NA 2006; 20 van der Steen JT, Volicer L, Gerritsen DL, Kruse RL, Ribbe MW, Mehr DR 2006; 21 Murphy-Filkins R, Teres D, Lemeshow S, Hosmer DW 1996; 24 atypb19 atypb26 atypb48 atypb27 atypb29 atypb22 atypb44 atypb23 atypb45 atypb24 atypb46 atypb25 atypb47 atypb40 atypb41 NHS Centre for Reviews and Dissemination (atypb9) 2001 atypb20 van der Steen JT (atypb33) 2007; 151 atypb42 atypb43 Zeegers MPA (atypb10) 2000; 144 Folstein MF (atypb28) 1975; 12 atypb15 atypb37 atypb16 atypb17 atypb39 atypb18 atypb11 atypb12 Mehr DR (atypb21) 2001; 50 atypb34 atypb13 atypb35 atypb14 atypb36 atypb1 van der Steen JT (atypb38) 2007; 11 atypb30 atypb3 atypb31 atypb2 atypb32 atypb5 atypb4 atypb7 Ioannidis JPA (atypb8) 1999; 25 atypb6 |
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| SubjectTerms | Cost-Benefit Analysis - economics Homes for the Aged Humans Meta-analysis Meta-Analysis as Topic Multicenter Studies as Topic - economics Netherlands North America Nursing Homes Observational research Palliative Care Research Design Respiratory Tract Infections - mortality |
| Title | Benefits and pitfalls of pooling datasets from comparable observational studies: combining US and Dutch nursing home studies |
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