When and how to use instrumental variables in palliative care research.

Most palliative care researchers want to demonstrate the effect of a treatment or intervention X on outcome Y. For example, we want to say that patients treated by the hospital-based palliative care team will have fewer intensive care unit (ICU) admissions than those not treated by the team (usual care patients). Randomized controlled trials (RCT) are the strongest design for making causal inferences about the effect of treatment X on outcome Y. Random assignment of patients to the treatment or control groups ensures there are no systematic differences between the groups in characteristics, observed and unobserved, that may affect outcome. Consequently differences between the groups on the outcome of interest can be attributed to the treatment. RCTs of palliative care treatments and interventions are difficult but not impossible to do. The difficulties arise from several sources, including enrollment bias, protocol adherence, and problems with external validity.1–3 Some physicians believe that palliative care is superior to usual care. Consequently, they believe it's unethical to encourage their patients to be in randomized trials of palliative care interventions.4 At the same, there are physicians who do not believe palliative care will benefit their patients and so, do not want them enrolled in a palliative care study. In addition, it may be unethical for researchers to take part in an RCT of palliative care. If palliative care was an additional service and researchers did not know if it provided benefit or harm then randomization might be an option. However, for palliative care researchers who believe the specialized care is beneficial, an RCT becomes an ethical issue. Adherence to the protocol can be challenging in an RCT of palliative care. Once patients are enrolled in an RCT, the crossover between treatment and usual care can be considerable.4 Physicians who gain direct or indirect positive experience with palliative care at the study hospital are likely to request palliative care consultation for their patients randomized to usual care. Similarly, family members and patients themselves may also request palliative care consultation. If these patients received palliative care as crossovers, “intent to treat,” or “as treated” analysis would produce biased estimates of the treatment effect.3,5 Finally, most RCTs sacrifice wide external validity for strong internal validity.6 That is to say, the trials are methodologically rigorous, but the results may not generalize to other more clinically relevant populations. For some program and policy research in palliative care, this trade-off may be inappropriate. For these reasons, many questions about the effects of palliative care on such outcomes as pain and other symptom management, family satisfaction with care, use of ICU care and costs will have to be answered using observational data. The analyses will have to use sophisticated methods that many of us in clinical research and practice may be less familiar with compared to the RCT. In this article we first explain what instrument variable estimation is and we show its use in a classic study of treatment of acute myocardial infarction (AMI).7 We then discuss how instrumental variable estimation is used in a recent study from geriatrics literature. Finally, we suggest possible instrumental variables for a recent palliative care study. Readers will find a thorough and modern introduction to instrumental variables models and their applications in Stock and Watson.8