CHIPRA Mandated Evaluation of Express Lane Eligibility: First Year Findings. b. Data Analysis

12/01/2012

Combining data from all discussions with staff in a given state, we calculated three types of ELE-related costs and savings: (1) the initial costs of implementation, (2) the savings or costs per marginal ELE application, and (3) the total savings or costs on an annual basis. Because states vary in the way they have chosen to divide ELE tasks between the state Medicaid or CHIP agency and ELE partner agency, we calculated all three of these measures as the costs or savings to the public sector, regardless of the original funding source. If certain costs or savings were absorbed by private contractors, they are not included in our analysis because they did not affect public sector finances in the short run.19 Below we provide additional details on these measures.

Initial costs of implementation.

The initial costs of implementation primarily reflect eligibility and policy staff training and information systems modifications needed to implement data-sharing arrangements with ELE partner agencies. Because they were often working on multiple initiatives and did not contemporaneously document time dedicated specifically to ELE, policy staff struggled to estimate their efforts on ELE design and implementation; however, they were able to characterize the opportunity costs states incurred by prioritizing ELE over other policy development initiatives. Staff training costs are presented in person-hours spent, noting the range of the duration of training sessions and the number of staff who attended them. In some states, such as Louisiana and Iowa, ELE was covered during a regularly scheduled staff training session that would still have focused on another topic in the absence of ELE. In other states, new training sessions were created specifically for ELE. Estimates of information systems modifications and computer programming were obtained from public health insurance and/or partner agency staff. Because programming costs were often documented on a “per job” basis, states were generally able to supply reliable estimates.

Savings and costs for the marginal application.

Our calculation of savings or costs per marginal application assumes that applications being processed via ELE that resulted in an ELE enrollment would otherwise have been processed the traditional way. This calculation fulfills the Children’s Health Insurance Program Reauthorization Act (CHIPRA) mandate that the evaluation compare costs through ELE versus costs of the traditional application process, and it is a useful way to examine how ELE costs differ from those of traditional enrollment methods. However, this method of calculating and comparing marginal administrative costs does not capture additional administrative costs that states may incur (such as hiring additional case managers or recruiting additional providers) if ELE significantly increases enrollment. To the extent that ELE significantly increases enrollment, generating these types of additional administrative costs, our analysis may overstate this component of marginal cost savings to a state.20

For Oregon and Iowa Medicaid, we also assume that staff time spent on ELE applications that do not result in ELE enrollments represents new costs to these states (costs they would not have incurred in the absence of ELE). This assumption does not affect costs estimates for the other ELE programs examined. For example, in Louisiana, the automated ELE data matching process means essentially no staff time is spent on ELE applications that do not result in enrollment. In Alabama and Maryland, the ELE process costs no additional staff time; and in New Jersey, extra time spent on ELE is absorbed by the third-party contractor, whose contracts were not adjusted to account for changes introduced by ELE.

Given these assumptions, we began by subtracting the minutes taken by each type of staff member to process a typical application via ELE from the minutes taken by each type of staff member to process a typical application via the traditional route. Some states provided a range of times for the ELE process, the traditional process, or both, since time per application depends on factors such as the number of individuals per application and the complexity of household relationships. If the state provided a range, we took the midpoint as our estimate. We multiplied the time saved for a typical ELE application by the proportional salary and benefits for the relevant members of the application processing staff. If the state provided a range of salaries, we again used the midpoint. The calculation does not include possible overhead costs (including any managerial staff time or non-payroll costs such as rent or utility costs), nor does it include other possible savings, such as avoided outreach costs or the avoided costs of individuals seeking application assistance.21

The calculation described above yields an estimate of the amount of staff time saved by processing successful applications via ELE rather than the traditional route. From this estimate, we subtracted the cost of processing unsuccessful ELE applications (where applicable) and the cost of other new ongoing expenses associated with ELE—primarily mailing costs per successful ELE enrollment. The difference between staff time saved and new costs reflects the change in administrative expenses associated with the marginal ELE application.

Net annual savings or costs.

We multiplied the average number of successful applications per year by our estimate of the savings and costs for the marginal application. The average number of successful applications per year is based on data from program start through December 2011. This assumption evens out month-to-month fluctuations in enrollment; however, we note that some states enrolled many more people in the first months of ELE than in later months (see Section B later in this chapter).


19 New Jersey and Iowa CHIP both use private contractors for eligibility determinations. Both programs confirmed that contracts were not amended to account for any increase in the volume of applications or any time savings per application, resulting from ELE.

20 On the other hand, some children who enrolled in public health insurance via ELE when they were healthy might have signed up later, in a worse state of health, if ELE were not in place. Enrolling when sick might entail greater administrative costs associated with expedited eligibility determination (versus the traditional enrollment method) and retroactive payment of Medicaid claims. The potential savings of enrolling children when they are healthy, rather than in response to a health crisis, are not taken into account in this analysis.

21 Managerial staff time was excluded from calculations because comparable data were not available across states. The amount of managerial time spent per application is also typically small, since direct managerial oversight is not required in most cases.

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