A reanalysis of cluster randomized trials showed interrupted time-series studies were valuable in health system evaluation

Journal of Clinical Epidemiology

Volumn 68, Issue 3, 2015, Pages 324-333

  Fretheim, Atle ^a,b,c   Zhang, Fang ^a   Ross Degnan, Dennis ^a   Oxman, Andrew D ^b   Cheyne, Helen ^d   Foy, Robbie ^e   Goodacre, Steve ^f   Herrin, Jeph ^g,h   Kerse, Ngaire ⁱ   McKinlay, R James ^j   Wright, Adam ^k   Soumerai, Stephen B ^a  

^a HARVARD MEDICAL SCHOOL   (United States)

^b NORWEGIAN KNOWLEDGE CENTRE FOR THE HEALTH SERVICES   (Norway)

^c UNIVERSITY OF OSLO   (Norway)

^d UNIVERSITY OF STIRLING   (United Kingdom)

^e UNIVERSITY OF LEEDS   (United Kingdom)

^f UNIVERSITY OF SHEFFIELD   (United Kingdom)

^g YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^h Health Research and Educational Trust   (United States)

ⁱ UNIVERSITY OF AUCKLAND   (New Zealand)

^j MCMASTER UNIVERSITY   (Canada)

^k BRIGHAM AND WOMEN S HOSPITAL   (United States)

more..

Author keywords

Evaluation methods; Health services research; Impact evaluations; Interrupted time series; Quasi experimental design; Randomized trials

Indexed keywords

ANALYTIC METHOD; ARTICLE; CLUSTER ANALYSIS; CLUSTER RANDOMIZED CONTROLLED TRIAL (TOPIC); CONFIDENCE INTERVAL; CONTROL GROUP; DEPENDENT VARIABLE; EMERGENCY WARD; EVALUATION STUDY; FOLLOW UP; HEALTH CARE SYSTEM; HEALTH SERVICE; HUMAN; MEDICAL RECORD; OUTCOME VARIABLE; PHYSICIAN; PRIORITY JOURNAL; RANDOMIZED CONTROLLED TRIAL (TOPIC); SECONDARY ANALYSIS; TIME SERIES ANALYSIS; TOTAL QUALITY MANAGEMENT; EPIDEMIOLOGY; HEALTH SERVICES RESEARCH; METHODOLOGY; STANDARDS; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA;

CLUSTER ANALYSIS; DATA INTERPRETATION, STATISTICAL; HEALTH SERVICES RESEARCH; HUMANS; INTERRUPTED TIME SERIES ANALYSIS; QUALITY IMPROVEMENT; RANDOMIZED CONTROLLED TRIALS AS TOPIC; RESEARCH DESIGN;

EID: 84923629026     PISSN: 08954356     EISSN: 18785921     Source Type: Journal    
DOI: 10.1016/j.jclinepi.2014.10.003     Document Type: Article

References (28)

1. S. Barber Health system strengthening interventions: making the case for impact evaluation 2007 The Alliance for Health Policy and Systems Research Geneva
2. A. Fretheim, A.D. Oxman, J.N. Lavis, and S. Lewin SUPPORT tools for evidence-informed policymaking in health 18: planning monitoring and evaluation of policies Health Res Policy Syst 7 Suppl 1 2009 S18
3. C.R. Ramsay, L. Matowe, R. Grilli, J.M. Grimshaw, and R.E. Thomas Interrupted time series designs in health technology assessment: lessons from two systematic reviews of behavior change strategies Int J Technol Assess Health Care 19 4 2003 613 623
4. D.T.R. Campbell, and H.L. Ross The Connecticut Crackdown on Speeding: time-series data in quasi-experimental analysis Law Soc Rev 3 1 1968 33 54
5. D.K. Simonton Cross-sectional time-series experiments: some suggested statistical analyses Psychol Bull 84 3 1977 489 502
6. W. Shadish, T. Cook, and D. Campbell Quasi-experiments: interrupted time-series designs. Experimental and quasi-experimental designs for generalized causal inference 2002 Houghton Mifflin Company Boston 171 206
7. D. Atkins, M. Eccles, S. Flottorp, G.H. Guyatt, D. Henry, and S. Hill Systems for grading the quality of evidence and the strength of recommendations I: critical appraisal of existing approaches the GRADE Working Group BMC Health Serv Res 4 1 2004 38
8. Effective Practice and Organisation of Care (EPOC) What study designs should be included in an EPOC review and what should they be called? EPOC resources for review authors 2013 Norwegian Knowledge Centre for the Health Services Oslo
9. B. Reeves, J. Deeks, J. Higgins, and G. Wells Including non-randomized studies J. Higgins, S. Green, Cochrane handbook for systematic reviews of interventions 2008 John Wiley & Sons Chichester
10. R. Kunz, and A.D. Oxman The unpredictability paradox: review of empirical comparisons of randomised and non-randomised clinical trials BMJ 317 1998 1185 1190
11. J. Odgaard-Jensen, G. Vist, A. Timmer, R. Kunz, E. Akl, and H. Schünemann Randomisation to protect against selection bias in healthcare trials Cochrane Database Syst Rev 2011 Issue 4. Art. No.: MR000012. http://dx.doi.org/10.1002/14651858.MR000012.pub3
12. S. Oliver, A.M. Bagnall, J. Thomas, J. Shepherd, A. Sowden, and I. White Randomised controlled trials for policy interventions: a review of reviews and meta-regression Health Technol Assess 14 2010 1 165, iii
13. A. Fretheim, S.B. Soumerai, F. Zhang, A.D. Oxman, and D. Ross-Degnan Interrupted time-series analysis yielded an effect estimate concordant with the cluster-randomized controlled trial result J Clin Epidemiol 66 2013 883 887
14. A.D. Oxman, and I. Chalmers Fair tests of health-care policies and treatments: a request for help from readers Bull World Health Organ 87 6 2009 407
15. A.K. Wagner, S.B. Soumerai, F. Zhang, and D. Ross-Degnan Segmented regression analysis of interrupted time series studies in medication use research J Clin Pharm Ther 27 4 2002 299 309
16. D. Gillings, D. Makuc, and E. Siegel Analysis of interrupted time series mortality trends: an example to evaluate regionalized perinatal care Am J Public Health 71 1981 38 46
17. B. Huitema Simple interrupted time-series designs. The analysis of covariance and alternative: statistical methods for experiments, quasi-experiments, and single-case studies 2nd ed. 2011 John Wiley & Sons, Inc Hoboken, New Jersey 367 402
18. O. Ukoumunne, and S. Thompson Analysis of cluster randomized trials with repeated cross-sectional binary measurements Stat Med 20 2001 417 443
19. R. Willlliams Using the margins command to estimate and interpret adjusted predictions and marginal effects STATA J 12 2 2012 308 331
20. J.M. Wooldridge Econometric analysis of cross section and panel data 2nd ed. 2010 MIT Press Cambridge, MA
21. H. Cheyne, V. Hundley, D. Dowding, J.M. Bland, P. McNamee, and I. Greer Effects of algorithm for diagnosis of active labour: cluster randomised trial BMJ 337 2008 a2396
22. S. Flottorp, A.D. Oxman, K. Havelsrud, S. Treweek, and J. Herrin Cluster randomised controlled trial of tailored interventions to improve the management of urinary tract infections in women and sore throat BMJ 325 2002 367
23. R. Foy, M.P. Eccles, S. Hrisos, G. Hawthorne, N. Steen, and I. Gibb A cluster randomised trial of educational messages to improve the primary care of diabetes Implement Sci 6 2011 129
24. S. Goodacre, E. Cross, C. Lewis, J. Nicholl, and S. Capewell Effectiveness and safety of chest pain assessment to prevent emergency admissions: ESCAPE cluster randomised trial BMJ 335 2007 659
25. R.B. Haynes, J. Holland, C. Cotoi, R.J. McKinlay, N.L. Wilczynski, and L.A. Walters McMaster PLUS: a cluster randomized clinical trial of an intervention to accelerate clinical use of evidence-based information from digital libraries J Am Med Inform Assoc 13 2006 593 600
26. N. Kerse, M. Butler, E. Robinson, and M. Todd Fall prevention in residential care: a cluster, randomized, controlled trial J Am Geriatr Soc 52 4 2004 524 531
27. A. Wright, J. Pang, J.C. Feblowitz, F.L. Maloney, A.R. Wilcox, and K.S. McLoughlin Improving completeness of electronic problem lists through clinical decision support: a randomized, controlled trial J Am Med Inform Assoc 19 2012 555 561
28. A. Fretheim, A.D. Oxman, K. Havelsrud, S. Treweek, D.T. Kristoffersen, and A. Bjorndal Rational prescribing in primary care (RaPP): a cluster randomized trial of a tailored intervention PLoS Med 3 6 2006 e134