In two separate datasets in which we evaluated long term glucocorticoid users and nursing home patients with a prior fracture, we observed wide variability in osteoporosis management across outpatient physician practices and nursing homes, respectively. We observed that most of the clustering effects within these two types of practice settings was due to the treatment proclivities of individual physicians rather than shared practice patterns related to the practice setting that might influence the physicians.
Our findings have implications for osteoporosis implementation research efforts in which interventions need to consider whether to target physicians, the healthcare environment including group practice setting, and/or patients. Although ideally an intervention would target all of these, we showed that the effect of osteoporosis management at the individual physician level outweighs the effect of the setting in which physicians practice together. Largely because of fear for contamination between intervention and control group physicians, the two trials represented in this analysis randomized at the practice setting rather than individual physicians (8
). This had the effect of reducing power because fewer units were randomized. The effects on study power as a function of the number of units randomized shown in the demonstrates that in the range of cluster sizes relevant for the SPOF study, the decision regarding which level to randomize was of high importance. Moreover, at least prior to intervention, our results indicate that the groups in which physicians practice appear to have only a small effect on other physicians' osteoporosis treatment patterns. Indeed, the adjusted odds ratios of the effect of the practice setting ranged from 1.04 to 1.14, which might be argued to be clinically irrelevant. However, although these data are suggestive that the effect of clustering at the practice setting level is small, contamination still might occur in the context of a potent evidence implementation intervention. This observational study cannot fully discount this possibility, and cluster randomization by facility should still be conducted until the potential for contamination has been further evaluated. Ideally, this could take place in the context of a study that randomized in one arm at the facility level, and in the other arm, at the provider level. However, this approach may or not be feasible.
Our results are consistent with a prior report that evaluated treatment patterns among 1973 predominantly postmenopausal women patients treated by 435 primary care physicians practicing in the northeastern U.S. (14
). In that study, the magnitude of the clustering observed among physicians (ICC = 0.03 – 0.04) was similar to our results where we observed ICCs ranging from 0.04 – 0.12 (depending on the practice setting and the outcome of BMD testing or receipt of prescription osteoporosis therapy). Our work extends those observations by focusing on two populations at high risk for fractures, long term glucocorticoid users and nursing home residents with prior fracture. Additionally, we considered the effect of both clustering at the physician level and also the common practice setting (i.e. the outpatient clinic and the nursing home). We also were able to evaluate and control for the specialty of the physicians and a number of other physician, physician group, and facility covariates.
The strengths of our work include demonstrating consistent results in two separate datasets with unique patient populations that both considered the same osteoporosis endpoint. These two populations, long term glucocorticoid users and older patients with prior fracture, represent individuals for which the strongest evidence and most robust osteoporosis management guidance exists. Additionally, this work should help guide future osteoporosis and other chronic disease quality improvement that use a group randomized trial design with multiple levels of clustering. As a potential limitation, we did not have information about whether the outpatient physician practices had DXA scanners in their office, which might account for some physician group clustering for the BMD testing outcome. We also recognize that these long term glucocorticoid users were enrolled in a large commercial U.S. healthcare organization and the nursing homes studied were from only two U.S. states, and the generalizability of our findings may not extend to other populations.
In conclusion, we observed that patients receiving care in the same outpatient physician practices and nursing homes were significantly more likely to receive similar care than patients in different physician practices and nursing homes. Most of this effect was a result of individual physicians' treatment patterns rather than the shared practice setting. Although osteoporosis implementation research interventions are most likely to be successful if they can target all facets of the healthcare environment, the treatment patterns of individual physicians appear to outweigh the effects of the common settings in which they practice. The number of units randomized also was important in determining the study power, suggesting that if there is no effect of clustering at the physician group level, randomizing at the physician level would be preferable to maximize study power. This decision would require the assumption that these observational results apply in the context of a randomized evidence implementation intervention. In future studies, and depending on the number of physicians and physician groups available to randomize, baseline data on these hierarchical relationships is likely to be useful in the design phase to maximize study power.