Rm 705, VGH Research Pavilion
Vancouver, BC
phone: 6048754558

Professor Boris Sobolev is a Senior Scientist and Leader of Health Services and Outcomes Research Program at the Center for Clinical Epidemiology and Evaluation.

Prof. Sobolev held the Canada Research Chair in Statistics and Modeling of the Health Care System from 2003-2013. Since 2011 he has served as Editor-in-Chief, Handbook of Health Services Research, a major reference work commissioned by Springer, http://refworks.springer.com/mrw/index.php?id=4082

In a recent interview with International Innovation, Prof. Sobolev described the field of health services and outcomes research.

Could you begin by summarizing the importance of your research?

Health services and outcomes research has experienced explosive growth in the past three decades. The field was formed at the interface of a number of disciplines including medicine, statistics, economics, management science and the social and behavioral sciences. The rich, multidisciplinary research developed from this fusion is producing a growing body of clinical evidence and methodology. Its methods continue to benefit from developments in diverse disciplines, while formulating and addressing unique scientific questions.

What are the implications of knowledge on the causal connection between the processes and outcomes of care?

The fundamental discovery was variation in healthcare delivery that cannot be explained by illness level, known benefit or patient preference. The study of medical practice variation gave birth to important themes of inquiry: effectiveness, quality, efficiency, access and disparities. Although a prevailing hypothesis relates this variation to differences in treatment results, the causal connection between the processes and outcomes of care has rarely been shown. As a result, current knowledge offers only limited insights into how changes in delivery of care may affect its outcomes.

Were further findings uncovered from an improved understanding of this causal connection?

Another important discovery was that the results of clinical trials cannot always be generalised to clinical practice, as patient groups enrolled in trials can be narrow. Researchers have been able to identify patients who will definitely benefit from one treatment method, and those who will benefit from another, but there is a third group – the patients for whom optimal treatment is not well defined. Learning what works in real life gave rise to comparative effectiveness research.

Can you explain how you are advancing health services research when experimentation is not feasible?

The causal connection between organisation and outcomes in medical care can be established by comparing patient groups assigned randomly to one of several care alternatives. This balances the groups in terms of known and unknown factors that might affect the outcome. In other words, the researcher forces the study groups to be as similar as possible in all respects except care delivery. As a result, the differences in outcomes observed between the groups can more confidently be ascribed to the intervention rather than to other factors.

In our research, we advance existing knowledge by estimating the causal effects of healthcare interventions when experimentation is not feasible. We use the framework of causal inference from observational data to examine causal effects in the connection between standards of care and patient outcomes. As a practical application, we are estimating the health effects of delays in providing coronary artery bypass grafting, which are common in Canada when demand exceeds capacity. Concerned with the adverse effects of delays, federal and provincial governments have called for standards on access to this type of surgery. In response, experts developed guidelines for the timing of surgery, yet there is little empirical evidence to support these recommendations. Indeed, the current literature offers no estimates of the causal effect of providing needed surgery to all patients within the recommended time.

Using data from routine medical care, we make causal inferences about: the reduction in post-operative mortality expected from providing timely cardiac surgical care; the health effects of receiving hip fracture surgery within the government benchmark; the proportion of hospital readmissions that could be avoided had patients had medication review in emergency department rather than in hospital ward or; the expected reduction of mortality had all coronary obstructive pulmonary disease patients had their second exacerbation prevented.

Most significant contributions:

  1. Sobolev B, Guy P, Sheehan KJ, Bohm E, Beaupre L, Morin SN. Hospital mortality after hip fracture surgery in relation to length of stay by care delivery factors: A database study. Medicine 2017; 96 (16): 1-8
  2. Sobolev B, Harel D, Vasilakis C, Levy A. Using the Statecharts paradigm for simulation of patient flow in surgical care. Health Care Management Science 2008; 11(1): 79-86.
  3. Sobolev BG, Levy AR, Kuramoto L, Hayden R, FitzGerald JM. Do longer delays for coronary artery bypass surgery contribute to preoperative mortality in less urgent patients? Medical Care 2006; 44(7): 680-6.
  4. Brown PM, Sobolev B, Zelt D. Selective management of abdominal aortic aneurysm smaller than 5.0 cm in a prospective sizing program with gender-specific analysis. Journal of Vascular Surgery 2003; 38(4):762-5.
  5. Sobolev B, Mercer D, Brown P, FitzGerald M, Jalink D, Shaw R. Risk of emergency admission while awaiting for elective cholecystectomy. Canadian Medical Association Journal 2003; 169(7): 662-5.


  1. Sobolev B, Kuramoto L. Analysis of Waiting-Time Data in Health Services Research. First edition. Springer 2008; 214 pages (ISBN: 0387764216) — over 5500 electronic copies downloaded.
  2. Sobolev B, Sanchez V, Kuramoto L. Health Care Evaluation Using Computer Simulation: Concepts, Methods and Applications. Springer 2012; 406 pages — over 9500 electronic copies downloaded

Health Services Research series:

The series provides a comprehensive reference to all aspects of the field that welcomes various disciplines: medicine, public health, statistics, economics and management. Boris Sobolev serves as Editor-in-Chief for this multi-volume series commissioned by Springer. The series contains a collection of tertiary literature that overviews established knowledge and provides access to accepted information in the field of health services research.

The first two volumes of the series, Medical Practice Variations  (over 6800 copies downloaded) and Comparative Effectiveness Research  (over 6900 copies), have been published in 2016.

Other contributions in 2010-2017:

  1. Sheehan K, Sobolev B, Guy P, Kuramoto L. Feasibility of administrative data for studying complications after hip fracture surgery. BMJ Open 2017; 7 (4): e015368
  2. Guy P, Sobolev B, Sheehan K, Kuramoto L, LeFaivre K. The burden of second hip fractures: provincial surgical hospitalizations over 15 years. Canadian Journal of Surgery 2017; 60(2):101-108
  3. Hohl CM, Partovi N, Ghement I, Wickham ME, McGrail K, Reddekopp LN, Sobolev B. Impact of early in-hospital medication review by clinical pharmacists on health services utilization. PloS One 2017; 12 (2): e0170495
  4. Edwards JD, Koehoorn M, Boyd LA, Sobolev B, Levy AR. Diagnostic Accuracy of Transient Ischemic Attack from Physician Claims. Canadian Journal of Neurological Sciences 2017; 1:1-7
  5. Sheehan KJ, Sobolev B, Guy P, Kuramoto L, Morin SN, Sutherland JM, Beaupre L, Griesdale D, Dunbar M, Bohm E, Harvey E and the Canadian Collaborative on Hip Fractures. In-hospital mortality after hip fracture by treatment setting. Canadian Medical Association Journal 2016;188 (17-18): 1219-1225. doi:10.1503/cmaj.160522
  6. Sobolev B, Guy P, Sheehan KJ, Kuramoto L, Bohm E, Beaupre L, Sutherland JM, Dunbar M, Griesdale D, Morin SN, Harvey E and the Canadian Collaborative on Hip Fractures. Time trends in hospital stay after hip fracture in Canada, 2004-2012: Database study. Archives of Osteoporosis. 2016; 11: 1-13
  7. Sheehan KJ, Sobolev B, Chudyk A, Stephens T, Guy P. Patient and system factors associated with mortality after hip fracture: a scoping review. BMC Musculoskeletal Disorders. 2016; 17: 166
  8. Sheehan KJ, Sobolev B, Guy P, Bohm E, Hellsten E, Sutherland J, Kuramoto L, Jaglal S and the Canadian Collaborative on Hip Fractures. Constructing an episode of care from acute hospitalization records for studying effects of timing of hip fracture. Journal of Orthopaedic Research 2016; 34(2): 197-204
  9. Levy AR, Sobolev B. Challenges of measuring performance of health systems. In: Comparative Effectiveness Research in Health Services. Springer: New York, 2016.
  10. Sobolev B, Sheehan K, Kuramoto L, Guy P. Risk of second hip fracture persists for years after initial trauma. Bone 2015; 75: 72-76. Audio slides
  11. Hohl CM, Wickham ME, Sobolev B, Perry JJ, Sivilotti ML, Garrison S, Lang E, Brasher P, Doyle-Waters MM, Brar B, Rowe BH, Lexchin J, Holland R. The effect of early in-hospital medication review on health outcomes: a systematic review. British Journal of Clinical Pharmacology 2015; 80(1): 51-61
  12. Sobolev B, Sheehan KJ, Kuramoto L, Guy P. Excess mortality associated with second hip fracture. Osteoporosis International 2015; 26(7): 1903-1910
  13. Hohl C, McGrail K, Sobolev B. The effect of pharmacist-led medication review in high-risk emergency department patients: evaluation protocol of a quality improvement program. Canadian Medical Association Journal 2014; 3(1): E103-E110.
  14. Bell N, Sobolev B, Townson A, Evans DC, Anton H, Simons RK. Classifying outcomes of care for injured patients. Canadian Journal of Surgery 2014; 57(6): 368-370.
  15. Bell N, Sobolev B, Anderson S, Hewko R, Simons RK. Routine versus ad hoc screening for acute stress following injury: who would benefit and what are the opportunities for prevention. Journal of Trauma Management & Outcomes 2014; 8(5): 1-7.
  16. Quon J, Sobolev B, Levy A, Fisher C, Bishop PB, Kopec J, Dvorak MF, Schechter M. Effect of waiting time on outcome of surgical lumbar discectomy. Spine Journal 2013; 13(12): 1736-48.
  17. Andersson G, Sobolev B. Small effects of selective migration and selective survival in retrospective studies of fertility. European Journal of Population 2013; 29(3): 345-354.
  18. Hohl CM, Kuramoto L, Yu E, Rogula B, Stausberg J, Sobolev B. Evaluating adverse drug event reports in administrative data of emergency department patients: a validation study. BMC Health Services Research 2013; 13: 473.
  19. Sobolev B, Fradet G , Kuramoto L , Rogula B. The occurrence of adverse events in relation to time after registration for coronary artery bypass surgery: a population-based observational study. Journal of Cardiothoracic Surgery 2013; 8: 74.
  20. Levy A, Sobolev B. The challenges of measuring the performance of health systems in Canada. In: Health Care Federalism in Canada: Critical Junctures and Critical Perspectives. Eds. K. Fierlbeck and W. Lahey. Queen’s–McGill Press 2013: 139-159.
  21. Evans DC, Andrusiek DL, Sobolev B. Process mapping of a regional trauma system. In: Patient Flow: Reducing Delay in Healthcare Delivery, Second Edition. Ed. R. Hall. Springer, International Series in Operations Research and Management Science 2013: 311-332.
  22.  Sobolev B, Levy A, Kuramoto L. Access to surgery and medical consequences of delays. In: Patient Flow: Reducing Delay in Healthcare Delivery, Second Edition. Ed. R. Hall. Springer, International Series in Operations Research and Management Science 2013: 129-149.
  23. Sobolev B, Fradet G, Kuramoto L , Sobolyeva R , Rogula B , Levy AR. Evaluation of supply-side initiatives to improve access to coronary bypass surgery. BMC Health Services Research 2012; 12(1): 311.
  24. Sobolev BG , Fradet G , Kuramoto L , Rogula B. An observational study to evaluate 2 target times for elective coronary bypass surgery. Medical Care 2012; 50(7): 611-9.
  25. Lepik KJ, Sobolev BG, Levy AR, Purssell RA, DeWitt CR, Erhardt GD, Baker JL, Kennedy JR, Daws DE. Medication errors associated with the use of ethanol and fomepizole as antidotes for methanol and ethylene glycol poisoning. Clinical Toxicology 2011; 49(5):391-401.
  26. Cheng SY, Levy AR, Lefaivre KA, Guy P, Kuramoto L, Sobolev B. Geographic trends in incidence of hip fractures: a comprehensive literature review. Osteoporosis International 2011; 22(10): 2575-2586.
  27. Lefaivre KA, Levy A, Sobolev B, Cheng S, Kuramoto L, Guy P. Changes in first hip fracture rates in British Columbia Canada, 1990-2004. Osteoporosis International 2011; 22(11): 2817-2827.
  28. Hohl CM, Nosyk B, Kuramoto L, Zed PJ, Brubacher JR, Abu-Laban RB, Sheps SB, Sobolev B. Outcomes of emergency department patients presenting with adverse drug events. Annals of Emergency Medicine 2011; 58(3):270-9.
  29. Sobolev B, Kuramoto L. Cluster-randomized design for simulation-based evaluation of complex healthcare interventions. Journal of Simulation 2010; 4(1): 24-33.
  30. Sobolev B, Sanchez V, Vasilakis C. Systematic review of the use of computer simulation modeling of patient flow in surgical care. Journal of Medical Systems 2011; 35(1): 1-16.
  31. Kopec JA, Sayre EC, Flanagan WM, Fines P, Cibere J, Rahman M, Bansback N, Anis AH, Jordan JM, Sobolev B, Aghajanian J, Kang W, Greidanus NV, Garbuz DS, Hawker GA, Badley EM. Development of a population-based microsimulation model of osteoarthritis in Canada. Osteoarthritis and Cartilage 2010; 18(3):303-311.
  32. Sobolev B, Sanchez V, Kuramoto L. Evaluation of methods for scheduling clinic appointments using simulation experiments. In: Discrete Event Simulation. Ed. Aitor Goti. Rijeka SCIYO Publishers 2010: 167-186.

Recently submitted articles:

  1. Sheehan KJ, Sobolev B, Guy P, Tang M, Kuramoto L, Belmont P, Blair J, Sirrett S, Morin SN, Griesdale D, Jaglal S, Bohm E, Sutherland JM, Beaupre L for the Canadian Collaborative Study on Hip Fractures. Feasibility of administrative data for studying complications after hip fracture surgery. Archives of Osteoporosis 2016.
  2. Sobolev B, Sheehan K, Kuramoto L, Guy P. A tutorial on risk measures for analysis in the competing-risk settings. Statistics in Medicine 2016.
  3. Sheehan KL. Sobolev B, Guy P for the Canadian Collaborative Study on Hip Fractures. Phenomenology of mortality worsening after delayed surgery. JBJS 2016
  4. Sheehan KL. Sobolev B, Guy P. System and patient factors influencing timing of surgery. BMJ Open 2016
  5. Sobolev B, Dodek P, Griesdale D, Fradet G, Kuramoto L, Huang R, Rogula B. Adverse safety events in relation to timing of coronary bypass surgery. Journal of Thoracic Surgery 2015.
SPPH 681A Causal Inferences in Public Health Sciences
SPPH 500 Analytical Methods in Epidemiologic Research
SPPH 580 Pharmacoepidemiology (sections)
VCHRI Applied Research Design and Data Analysis

Dr. Sobolev’s multidisciplinary expertise is well suited for training highly qualified personnel in health services research. Training opportunities at the graduate and post-doctoral levels are available through the School of Population and Public Health and the Centre for Clinical Epidemiology & Evaluation. His trainees, which include 8 MSc students, 8 PhD students and 4 Postdoctoral fellows, have subsequently found employment in the academia, regional health authorities, the hospital sector, the pharmaceutical industry, and the provincial ministry of health. The unique benefits of the training environment include exposure to a multidisciplinary approach, participation in collaborative on-the-job training in both academic and non-academic settings, and acquisition of skills to communicate research results to practitioners and policy makers.

Dr. Sobolev recently introduced a new course to the SPPH curriculum: “Causal Inference in Public Health Sciences”. Words from students.

The purpose of the course is to develop competency in applying causal inference methodology to observational data. This fall, the School will continue offering the course.

The offering addresses a recognized need for a graduate-level course that links concepts and practical skills for making causal inference in epidemiology, health services research, and studies in occupational and environmental health. First, the course formally defines concepts of causality and causal effect, and explicates conditions for attributing observed associations to causal relationship. Then, the course offers learning of causal methodology through practical applications to real data.

Learning from the course, students will be able to produce causal diagrams for thesis projects, to refine research questions, to identify variables for adjustment, to detail the plan of analysis, and to attempt to estimate causal effects with data from their own projects.

This 600-level course builds on the knowledge and skills acquired from SPPH500, SPPH503, and SPPH548.


Student evaluations

“The delivery of this course was absolutely first-rate. The content was very specialized but incredibly relevant to the type of work I am doing. I would not change a thing for course content. It is thorough, comprehensive, with technical aspects rooted firmly in theory.”

“I think the course is very solid as it is. I would be interested in a continuation of the course in a graduate seminar of some sort. Not sure if that’s practical, but I have found myself wanting to know more.”

“The reading materials, data sets for practicing stata, in-between class discussions with Dr. Sobolev, in-class assessment, and in-class slide presentation prepared by Dr. Sobolev.”

“This should be, if not a required course, a strongly recommended course, for all PhD students in health services and policy research.”

“This is a fantastic course for anyone in population and public health, but especially for anyone in the biostatistics or health services research divisions. We don’t talk about the theoretical underpinnings of our analyses in many of the other courses, at least not in depth. SPPH 548 is mostly about methods (it has a new number now), but 681A provides the foundation from which to do analysis about exposures and effects. The DAG development section alone is incredibly valuable. Highly recommended course for all PhD students in either HSPR or biostatistics.”

“Grading was fair. There certainly were a lot of opportunities for evaluation, but it felt like the whole scheme truly supported learning. It’s one of the best courses I’ve seen in this regard, in my experience as a student, ever.”

“Katie did a fantastic job in leading the tutorials. She was very accessible and great about answering questions that came up in the learning process.”

“There was considerable preparation for each session, and it showed in how the sessions were assembled. I appreciated the logical ‘demo-guided exercise-homework’ progression. It created ample time to really understand not only the technical aspects of what we were doing, but the theoretical aspects as well.”

“I thought the choice of Stata was a good one – I was worried about needing to seriously dust off my R and SAS skills, and was relieved that I didn’t have to learn another language to do the work in the course.”

“I liked the rigor of the materials; it’s given me a lot of useful tools that I can go back and dust off when I need them.”

Health Services And Outcomes Research

Health services and outcomes research examines how people get access to health care, what health services they use, and what happens to patients as a result of this care, Pan-Canadian Vision and Strategy.

There are several reasons why health services should be a subject of research:

• health services is a part of maintaining and improving of people’s health
• there is uncertainty about the effectiveness of many interventions
• conflicting perspectives of providers, patients, system managers, the industry

The societal value of health services and outcomes studies lies in identifying the ways in which health care can best be organized, financed, and delivered. The main reason for public support of health services research is the common understanding that new knowledge will lead to more effective health care.

International Innovations Issue 16 profiled SIMCARE, a recent study conducted by Prof. Sobolev and his colleagues.

The Canadian Collaborative Study Of Hip Fractures

Each year, Canadian hospitals admit over 25,000 older men and women with fracture of the hip. Overall, two-thirds of these patients receive surgical treatment on the day of admission or the next day, but the timing of surgery varies widely across the country. Canada’s health ministers have adopted 48 hours after admission as a benchmark for provision of hip fracture surgery. However, current evidence is insufficient to justify the changes in hospital care that would be required to prioritize access to this procedure. This knowledge gap is important, because of the pressing need to identify patients who will benefit from accelerating their surgery through the 48-hour commitment.

What We Are Doing

The pan-Canadian collaborative led by Prof. Boris Sobolev and Dr. Pierre Guy is conducting a population-based study of hip fracture surgery wait times and associated outcomes. We use the Canadian Institute for Health Information Discharge Abstract Database to identify patients admitted for hip fracture surgery to any acute care hospital in Canada between 2003 and 2012. Comparisons will be made in health outcomes among patients exposed to various wait times before surgery and across subgroups of patients stratified by various patient and system related reasons for delay. We will test whether preoperative deaths were more frequent among Canadian hip fracture patients 65 years of age or older who remained untreated at 48 hours after admission. We will also determine whether postoperative complications and ensuing in-hospital deaths were more frequent when surgery was performed beyond 48 hours after admission.

Why This Work Is Important

The significance of this research arises from the opportunity to supplement existing knowledge about the benefits of expeditious hip fracture surgery with evidence from real-life care delivered to a large number of patients across the entire country. Our study will improve understanding of the pathways linking waits and health outcomes through a comparison of two types of in-hospital deaths, those occurring before surgery and those occurring after surgical complications. Finally the study will identify groups of patients who would benefit from accelerated access to the procedure in terms of fewer complications and deaths.

For the latest updates visit our C2E2 webpage, CHHM webpage, or follow us on Twitter @HFstudy.

Recent media covearge

CBCNews: http://www.cbc.ca/news/health/broken-hip-death-1.3809311

Toronto Star: www.thestar.com/news/canada/2016/10/17/hip-fracture-deaths-more-likely-at-smaller-hospitals-canadian-study-finds.html

Global Science News: https://www.eurekalert.org/pub_releases/2016-10/cmaj-hfd101316.php

CTVNews: http://www.ctvnews.ca/health/deaths-from-hip-fractures-more-common-in-smaller-hospitals-study-1.3119518


Prospective UBC MSc and PhD students are invited to work on the Canadian Collaborative Study of Hip Fractures! The primary location for this study is the Vancouver Coastal Health Research Institute. As part of its long-term commitment, the Institute provides some salary support, space, and hosts the data management facility for this project. The facility was originally established through a grant from the Canada Foundation for Innovation.