Study participants' average age was 74 years at the end of the study period or during the last month they were enrolled in the MCO and 58 percent were female (). The most prevalent comorbid conditions were coronary artery disease (75.6 percent), chronic obstructive pulmonary disease (36.6 percent), and congestive heart failure (27.6 percent). The morbidity burden (Dx Rx PM) of the intervention group was higher (p<.0001) than the comparison group (56.2 percent).
Characteristics of Members in the Intervention and Comparison Samples
Our primary hypothesis was that medical care, as measured by P4P-incentivized quality indicators, would be of higher quality for patients with diabetes exposed to the intervention compared with their nonexposed diabetic counterparts. – illustrate the observed data and estimated changes in trends over time for each of the outcomes assessed. The 12-month linear spline models appear to fit the data adequately for all outcomes except the influenza vaccination quality measure, for which we report the 6-month spline model results. provides a summary of the analysis results, with OR and RR representing the changes in trends over time for binary outcomes and costs, respectively.
Monthly Trend for Incentivized Quality Indicators: Low-Density Lipoprotein Screening, Influenza Vaccine, and Hemoglobin A1c Testing
Monthly Trend for Emergency Department Visits and Per Member Per Month Costs
Results Comparing Baseline to Follow-Up for Each Study Group and the Relative Change between Study Groups across Study Periods
As an illustrative example for interpretations on and , consider the LDL screening quality measure. shows that both the intervention and comparison groups were improving in the initial preintervention period (months −25 to −12). In the 12-month period just before implementation (months −12 to 0), the intervention group LDL screening rates plateaued and rates in the comparison group actually decreased. During the intervention period (months 0–14) both groups again saw improvements in LDL screening rates. The improvement over the observed −12 to 0 month plateau for the intervention group was a doubling in the odds of LDL screening (OR=1.99, 95 percent CI [1.44, 2.75]) while the intervention period improvement over the observed −12 to 0 month decrease for the comparison group was a threefold increase in the odds of screening (OR=3.23 [2.94, 3.55]). Thus, the improvement in LDL screening for the intervention group was 40 percent smaller (p=.005) than the improvement for the comparison group (1.99/3.23); treatment effect OR=0.62 (0.44, 0.86).
If one compares trends in influenza vaccination from the 6-month period just before the intervention period (months −6 to 0) with trends in the latter half of the intervention period (months 7–14), the estimated improvement in the intervention group is approximately 80 percent greater; OR=1.79 (1.37, 2.35), as shown in . However, as illustrates, both intervention and comparison groups appear to follow similar influenza vaccination trajectories across the entire study period and the potential intervention effect appears to be attributed to a slight slowing of the improvement in the comparison group, rather than a substantive increase in the improvement of the intervention group. This 6-month comparison for influenza vaccination was the only component of the five incentivized quality measures where any positive intervention effect was observed.
For the remaining four incentivized measures (HbA1c testing, nephropathy screening, eye examination, and LDL screening), both groups had absolute increases in the probability of meeting the quality measures in the follow-up period (see and , and ). When comparing the differences between the intervention and the comparison groups in the change from baseline to follow-up, there was either no significant difference between the intervention and comparison groups (nephropathy screening and eye exam), or the improvement was significantly lower for the intervention sites (HbA1c testing, p<.0001; LDL screening, p<.01).
Monthly Trend for Incentivized Quality Indicators: Nephropathy Screening and Eye Exam
The second research question asked, “Does the intervention provide higher quality of care for nonincentivized quality indicators for diabetic patients than that received in comparison practices with standard call center–based DM?” Using filled prescriptions as a marker for written prescriptions, two prescription measures were used to examine the question (see ). There was no evidence of an intervention main effect between the patients of the intervention and comparison practices in either avoiding short-acting antihypertensive medication (OR=1.11 [0.58, 2.13]) or prescribing an ACE for those with renal insufficiency (OR=0.76 [0.54, 1.06]).
Monthly Trend for Nonincentivized Quality Indicators: ACE Script for Those with Renal Insufficiency and No Short-Acting Medications
The third and final research question asked whether the intervention affected resource use as measured by (1) ED utilization and (2) total medical costs (see ). For ED utilization, both groups' trends demonstrated a decreasing likelihood of a visit during each of the study periods. The change in odds from baseline to follow-up was not significantly different between the groups (OR=0.17 [0.02, 1.25]), although the comparison group's 105 percent increase (from OR=0.08 at baseline to 0.84 at follow-up) was statistically significant (OR=10.46 [4.62, 23.66]).
The analysis of the average total medical cost trends per member per month indicated that there was no significant difference (p=.42) between intervention and comparison members with diabetes on the change in cost trend from baseline to follow-up. The expected cost trend for members in the intervention group demonstrated a slightly (15 percent) higher yearly increase from baseline to follow-up than found for the comparison group, although this difference was not statistically significant (RR=1.15 [0.82, 1.61]).