References
Bernal JL, Cummins S, Gasparrini A (2017) Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol 46:348–355. https://doi.org/10.1093/ije/dyw098
Biglan A, Ary D, Wagenaar AC (2000) The value of interrupted time-series experiments for community intervention research. Prev Sci 1:31–49
Dayer MJ, Jones S, Prendergast B, Baddour LM, Lockhart PB, Thornhill MH (2015) Incidence of infective endocarditis in England, 2000–13: a secular trend, interrupted time-series analysis. Lancet 385:1219–1228. https://doi.org/10.1016/s0140-6736(14)62007-9
Dennis J, Ramsay T, Turgeon AF, Zarychanski R (2013) Helmet legislation and admissions to hospital for cycling related head injuries in Canadian provinces and territories: interrupted time series analysis. BMJ (Clin Res ed) 346:f2674. https://doi.org/10.1136/bmj.f2674
Fell D, Sprague AE, Grimshaw JM, Yasseen AS, Coyle C, Dunn SI, Perkins SL, Peterson WE, Johnson M, Bunting PS, Walker MC (2014) Evaluation of the impact of fetal fibronectin test implementation on hospital admissions for preterm labour in Ontario: a multiple baseline time-series design. BJOG 121:438–446. https://doi.org/10.1111/1471-0528.12511
French B, Heagerty PJ (2008) Analysis of longitudinal data to evaluate a policy change. Stat Med 27:5005–5025. https://doi.org/10.1002/sim.3340
Jandoc R, Burden AM, Mamdani M, Levesque LE, Cadarette SM (2015) Interrupted time series analysis in drug utilization research is increasing: systematic review and recommendations. J Clin Epidemiol 68:950–956. https://doi.org/10.1016/j.jclinepi.2014.12.018
Kittel PA (2018) The impact of the recommendation of routine rotavirus vaccination in Germany: an interrupted time-series analysis. Vaccine 36:243–247. https://doi.org/10.1016/j.vaccine.2017.11.041
Klein MB, Saeed S, Yang H, Cohen J, Conway B, Cooper C, Cote P, Cox J, Gill J, Hasse D, Haider S, Montaner J, Pick N, Rachlis AR, Rouleau D, Sandre R, Tyndall M, Walmsley SL (2010) Cohort profile: the Canadian HIV-hepatitis C co-infection cohort study. Int. J Epidemiol 39:1162–1169. https://doi.org/10.1093/ije/dyp297
Laird NM, Ware JH (1982) Random-effects models for longitudinal data. Biometrics 38(4):963–974
Lau WC, Murray M, El-Turki A, Saxena S, Ladhani S, Long P, Sharland M, Wong IC, Hsia Y (2015) Impact of pneumococcal conjugate vaccines on childhood otitis media in the United Kingdom. Vaccine 33:5072–5079. https://doi.org/10.1016/j.vaccine.2015.08.022
Lavergne MR, Law MR, Peterson S, Garrison S, Hurley J, Cheng L, McGrail K (2018) Effect of incentive payments on chronic disease management and health services use in British Columbia, Canada: interrupted time series analysis. Health Policy (Amsterdam, Netherlands) 122:157–164. https://doi.org/10.1016/j.healthpol.2017.11.001
Naumova EN, Must A, Laird NM (2001) Tutorial in biostatistics: evaluating the impact of ‘critical periods’ in longitudinal studies of growth using piecewise mixed effects models. Int J Epidemiol 30:1332–1341
Penfold RB, Zhang F (2013) Use of interrupted time series analysis in evaluating health care quality improvements. Acad Pediatrics 13:S38–44. https://doi.org/10.1016/j.acap.2013.08.002
Rubin DB (2005) Causal inference using potential outcomes: design, modeling, decisions. J Am Stat Assoc 100:322–331
Strumpf EC, Harper S, Kaufman JS (2017) Fixed effects and difference-in-differences. In: Methods in social epidemiology, 2nd edn. Jossey-Bass, San Francisco, pp 341–368
Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D (2002) Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 27:299–309
West SG, Duan N, Pequegnant W, Gaist P, Des Jarlais DC, Holtgrave D, Szapocznik J, Fishbein M, Rapkin B, Clatts M, Mullen PD (2008) Alternatives to the randomized controlled trial. Am J Public Health 98:1359–1366. https://doi.org/10.2105/ajph.2007.124446
Acknowledgements
The Canadian Co-infection cohort investigators (CTN222) are: Drs. Lisa Barrett, QEII Health Science Center for Clinical Research, Halifax, NS; Jeff Cohen, Windsor Regional Hospital Metropolitan Campus, Windsor, ON; Brian Conway, Vancouver Infectious Diseases Research and Care Centre, Vancouver, BC; Curtis Cooper, The Ottawa Hospital Research Institute, Ottawa ON; Pierre Côté, Clinique du Quartier Latin, Montréal, QC; Joseph Cox, MUHC IDTC-Montréal General Hospital, Montréal, QC; John Gill, Southern Alberta HIV Clinic, Calgary, AB; Shariq Haider, McMaster University, Hamilton, ON; Mark Hull, BC Centre for Excellence in HIV/AIDS, Vancouver, BC; Marina Klein, McGill University Health Centre, Division of Infectious Diseases and Chronic Viral Illness Service, Montreal, QC; Erica Moodie, McGill University, Montreal, QC; Neora Pick, Oak Tree Clinic, Children’s and Women’s Health Centre of British Columbia, University of British Columbia, Vancouver, BC; Anita Rachlis, Sunnybrook & Women’s College Health Sciences Centre, Toronto, ON; Danielle Rouleau, Centre Hospitalier de l’Université de Montréal, Montréal, QC; Aida Sadr, St. Paul’s Hospital, Vancouver, BC; Roger Sandre, HAVEN Program, Sudbury, ON; Mark Tyndall, Department of Medicine, Infectious Diseases Division, University of Ottawa, Ottawa ON; Steve Sanche, SHARE University of Saskatchewan, Saskatoon, SK; Marie-Louise Vachon, Centre Hospitalier Universitaire de Québec, Québec, QC; Sharon Walmsley, University Health Network, Toronto, ON; and Alex Wong, Regina Qu’Appelle Health Region, Regina General Hospital, Regina, SK. We thank all study coordinators and nurses for their assistance with study coordination, participant recruitment and care.
Funding
This study was funded through support by doctoral awards funded to SS by the Canadian Institutes of Health Research and the Canadian Hepatitis C Network. ECS and EEMM are supported by a Chercheur boursier Junior 2 from the Fonds de Recherche Santé (FRQ-S). The Canadian HIV–HCV Coinfection Cohort Study was supported by the Fonds de recherche du Québec-Santé (FRQ-S); Réseau SIDA/maladies infectieuses, the Canadian Institutes of Health Research (CIHR FDN 143270); and the CIHR Canadian HIV Trials Network (CTN222).
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Authors SS, EEMM and ECS declare that they have no conflicts of interest. None of the authors have any conflict of interest with regard to this study and there was no pharmaceutical industry support to conduct this study although MBK has received research grants for investigator-initiated trials from Merck and ViiV Healthcare, and consulting fees from ViiV Healthcare, Bristol-Meyers Squibb, Merck, Gilead and AbbVie.
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The data used to illustrate the study design come from the Canadian HIV–HCV Coinfection Study (CCC) which has been approved by the community advisory committee of the Canadian Institutes of Health Research (CIHR) Canadian HIV Trials Network and by all institutional ethics boards of the participating centers.
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Saeed, S., Moodie, E.E.M., Strumpf, E.C. et al. Segmented generalized mixed effect models to evaluate health outcomes. Int J Public Health 63, 547–551 (2018). https://doi.org/10.1007/s00038-018-1091-9
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DOI: https://doi.org/10.1007/s00038-018-1091-9