In this study of rural primary care practices, we found that physician-level performance was significantly related to patients’ age and insulin use as well as difficulties with self-testing and keeping appointments. Difficulties with self-testing and keeping appointments have not been included in other studies of practice-level performance on quality of care but likely play a prominent role in barriers to achieving control for rural patients with diabetes and were strong predictors of practice-level glycemic control. We acknowledge that current quality assessment frequently include other performance measures than A1c and may measure quality of care delivered based on composite measures. In our analyses, accounting for patient factors resulted in a marked impact on ranked performance, suggesting the need for caution in making quality comparisons. If pay-for-performance programs or other reimbursement plans are based on observed A1c values, the risk of unanticipated consequences is real. What does a practice with a wide geographic catchment area of low-income patients do to boost their performance ratings? Doctors practicing in these critical at-risk areas are at significant risk of disproportionately low rankings based on factors over which they have less than total control.
We do not mean to imply that rural (or any) physicians should not play a strong role in assisting patients with self-care and visit attendance. However, these private offices were not part of larger health systems that could provide special outreach programs, such as telemedicine, home visits, or financial assistance. Although our study was not designed to examine the barriers rural patients with diabetes face nor to compare rural to urban practices, it is likely that the quality of care being provided by the physician had less influence than low income, transportation difficulties, and lack of social support systems. Indeed, difficulties with self-testing and keeping appointments are mulifactorial problems. It is important to acknowledge the significant role physicians play in recognizing and assisting patients who have barriers, but it is equally important to recognize how far removed their influence may be from the considerably more distal outcome of glycemic control.
Although there is conflicting evidence regarding positive health outcomes associated with self-testing for patients with diabetes who are not on insulin, lack of self-testing may reflect suboptimal patient activation.15
Self-testing of blood glucose requires time and therefore an economic cost that lower-income patients may not be able to afford,16
yet a recent study demonstrated that extra time spent on self-care activities was greater in traditionally disadvantaged patients.17
If patients are vigilant about ambulatory glucose monitoring and note worsening glycemic control, medication intensification may be initiated sooner with better health outcomes long-term. Similarly, faithful adherence to appointments may prompt health care providers to attend to problems sooner, before complications arise. Poor adherence with appointments has been associated with worse glycemic control in a similar population from rural Virginia.18
Our study underscores an important limitation of current diabetes quality measurement. Simply reporting the proportion of patients controlled in a physician’s practice does little to point the way toward improvement. The proportion in control does not permit assessment of how much of the result can be attributed to patient characteristics vs direct quality of care delivered by the practice. “Smarter” performance measures less influenced by patient factors are needed, especially for vulnerable or complex patients. For example, a measure that provides information on specific clinical actions, such as how many patients with uncontrolled A1c
had their medications adjusted, would be much more helpful for physicians wishing to improve their practices.19–21
Our study also demonstrates the difficulty of physician-level performance assessment in the private practice rural setting, which used predominately handwritten records. The labor-intensive and costly approach we needed to take in this study is unlikely to be feasible in an ongoing, sustained manner. Electronic health records open the door to more refined performance assessment; more reliable data; and ongoing, automated reporting. Continued efforts to provide electronic health records to remote practices are badly needed.22,23
Our findings are consistent with other studies reported in the scientific literature. Other studies have found patient clinical and sociodemographic factors to be associated with glycemic control.3–5
However, we are not aware of other studies that directly examine the association of patient’s difficulties with self-testing and keeping appointments on practice-level performance on diabetes control. Several other studies have linked insulin use with worse diabetes control at the population level, and our study again demonstrated the association of older age with better control.3–5,24
These findings confirm that this population of patients was similar to others in these aspects.
Our study has several limitations. A convenience sample of physicians agreed to participate in the study, and they may not be representative of rural primary care practices in the southeast. We relied on the physician or his/her office staff to select consecutive patients with diabetes. Consecutive sampling of patient charts mitigates against “cherry-picking” those patients with well-controlled diabetes but may not be as good as random sampling for physician performance feedback.25
The small sample size of patient charts submitted in our study is similar to the minimum amount requested by the American Board of Internal Medicine for self-evaluation of practice performance to maintain certification.26
Though Hofer et al proposed that reliable assessment of physician performance on quality measures would require a panel of 100 patients with diabetes,27
the median panel sizes in studies involving large health maintenance organizations (HMOs) and the VA were fewer than 30 patients with diabetes.28
However, for feedback purposes, highly reliable estimates are not needed.29
The main purpose of the intervention portion of our study was to provide feedback to physicians so that quality improvement efforts could be focused in their offices. Therefore, the baseline analyses in the current study were constrained by small clusters of patients within physicians. As pointed out by Greenfield et al, to adequately power comparisons of physicians or practices, one would need to increase the number of physicians or practices.30
Likewise, our sample size of practices was limited to those recruited in the trial.
We relied on medical records to ascertain patient difficulties with self-testing and appointment keeping. We acknowledge that it is likely that physicians recognize only a subset of patients struggling with these barriers and note them in extreme cases, suggesting that our report may be an underestimate of their true effect. Finally, future studies are needed to examine structural and process features of the practices associated with variations in glycemic control rates.
In conclusion, few studies have focused on the quality of care of physicians caring for patients with diabetes living in rural areas. In this setting, we found important predictors of physicians’s practice ranking on glycemic control that were beyond immediate and direct physician control. Clearly, rural patients confront barriers in self-testing and appointment keeping, and fair and informative quality assessment should account for these factors. Basing public reporting and resource allocation on quality assessment that does not account for patient characteristics may further harm this vulnerable group of patients and physicians.