Does Diabetes Disease Management Save Money and Improve Outcomes?

Jaan Sidorov, MD, FACP, CMCE, Robert Shull, PHD, Janet Tomcavage, RN, MSN, CDE, Sabrina Girolami, RN, BSN, Ronald Harris, MD, FACE, Nadine Lawton, RN


Diabetes Care. 2002;25(4) 

In This Article


These retrospective data demonstrate that participants in a managed care-sponsored diabetes disease management program experienced lower overall paid insurance claims for health care compared with those not in disease management. This difference was not only statistically significant but substantial, amounting to $104.86 per member per month or $ 1,294.32 per year. For the 3,118 continuously enrolled patients included in this analysis, this amounts to a total of $4,035,689.70 per year in fewer claims paid compared with nonprogram patients. Lower claims for program patients were present in both commercial and Medicare risk insurance. As noted above, the total budget, including capital for all disease management programs in this HMO, was ~$4.2 million per year. Because ~43% of all patients seen in disease management had diabetes, we believe the estimated allocated cost of ~$1.81 million for diabetes disease management contrasts favorably with the $4,035,689.70 in fewer claims for the patients included in this analysis. We found that much of the observed savings were accompanied by comparatively lower measures of inpatient use, with fewer admissions and fewer inpatient days. These findings persisted after we statistically controlled for factors that could alter health care use, such as age, sex, duration of enrollment in the HMO, presence of a pharmacy benefit, and type of insurance. Because all insurance claims for each year of the study were recorded among the HMO enrollees we examined, it is unlikely that the savings were underestimated [31].

Our findings also add to the weight of evidence linking diabetes disease management to health care use and glycemic control. We found that patients in disease management not only experienced lower charges but also had significantly higher measures in the key diabetes HEDIS measures. Although our data do not support the assertion that increased quality causes lower health care costs, we did find it is possible to achieve both at the same time. This association between cost and glycemic control has been previously described. Davies et al. [32] examined the effectiveness of nurse-based diabetes education and found less inpatient use was associated with better glycemic control. Menzin et al. [33] also linked insurance claims and mean HbA1c levels among 2,394 patients with diabetes in the Fallon Clinic Health Plan. As in this study, the economic impact of blood glucose control was apparent within a relatively short period of time and was also manifested by less inpatient use. Gilmer et al. [34] and Wagner et al. [35] also found hospitalizations and overall health care costs in a managed care setting to be positively associated with elevated HbA1c levels. Others outside of managed care have shown that in randomized clinical trials, achieving a lower HbA1c is associated with fewer complications and lower health care costs [36,37].

These data also support the findings of other researchers who have shown that nurses can champion clinical guidelines and provide diabetes education to achieve significant improvements in blood glucose control [38–45]. This approach compares favorably with usual primary care, in which up to 40% of patients with diabetes do not have a measurement of their HbA1c[46]. Aubert et al. [47] found that in a randomized clinical trial, nurse managers can achieve significant improvements in blood glucose among primary care patients. As in this program, these nurses relied on staged diabetes management guidelines, which also have been shown to result in better glycemic control [48].

To our knowledge, this is the first report linking HEDIS and use. HEDIS theoretically enables purchasers to compare quality among competing MCOs. Purchasers also use other considerations when choosing an MCO, such as premium amount, network size, and financial stability. Despite widespread use of HEDIS, managed care has been criticized for failing to convince purchasers to rate quality of care over other factors in purchasing decisions [49]. Our data suggest that patient education, clinical guidelines with provider teaming, and financial performance need not be mutually exclusive.

The growth of independent disease management companies, financed through a percentage of the insurance premium, is further evidence of a widespread belief that this strategy can achieve bottom-line savings. Reports of their success across a variety of managed care settings, in lowering use or improving outcome measures, also stress the effectiveness of clinical guidelines and team-based care, which promotes self-management [50–54].

Our findings may be biased. For example, greater willingness to cooperate with treatment recommendations, better health practices, or more interest in use of a glucose meter among patients who also agreed to opt in could explain the differences in use rather than disease management per se. In addition, because physicians had referred an unmeasured fraction of program patients, some of the differences in use could have been the result of differences in physician behavior outside of the disease management program. However, this program recruited just under one-half of all patients fulfilling HEDIS criteria for diabetes from the same network of primary care sites that cared for patients not in disease management. We also statistically controlled for known patient variables that could have accounted for the observed outcome differences. Because this disease management program was available to all HMO members with diabetes, close to one-half of eligible patients used it. We statistically controlled for known confounding patient variables, and we believe the impact of other unmeasured patient factors could have caused nonrandom selection and fewer claims, reducing better outcomes in the disease management group. Regardless of potential patient selection bias, our simultaneous demonstration of improved clinical outcomes and lower use has important implications for health care organizations struggling to reconcile cost and quality.

Our data were also limited by restricting the claims analysis to overall paid charges. Although we found evidence of decreased inpatient use (manifested by fewer admissions and fewer inpatient days in program patients) and increased primary care office visits, we were unable to more fully characterize the savings. Although insurance claims are linked to diagnoses by ICD-9 code, we have anecdotally found that practice patterns and reimbursement issues significantly influence code selection, thus limiting our analysis. We were also unable to determine whether the HMO education nurses influenced health care use by redirecting their patients away from more costly services. We also caution that fewer insurance claims for health care do not necessarily mean lower health care costs, especially for patients who may experience significant out-of-pocket expenses. Our data are also limited by the lack of information concerning the use or cost of pharmaceuticals, which could also be responsible for changes in use. Our population resides in a largely rural setting, which may also limit the generalizability of our findings. Finally, this disease management program consisted of several interventions that in turn were adapted to accommodate local physician practice styles. Determining the source of short-term savings in disease management using methodologies that can prospectively and precisely define the relative contribution of each of the interventions typically used in multifaceted disease management programs is an area ripe for further research.

These issues can only be addressed through random selection and assignment of patients in a clinical trial using predefined clinical and financial criteria. Pending more research in this area, however, our data may demonstrate that disease management can simultaneously benefit participants and MCOs, with lower health care use, significant savings, and higher health care quality.

Abbreviations: GHP, Geisinger Health Plan • HEDIS, health employer data and information set • HMO, health maintenance organization • MCO, managed care organization • TPA, third-party administration