ÐÏࡱá>þÿ þÿÿÿ  ýÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿÿì¥Á7 ø¿¯bjbjUU ò‹7|7|¦YÿÿÿÿÿÿlFFF"ht’z’z’zÈZ{¼|4ÏèDV~l~"Ž~Ž~È~‹„–!…4U…*è,è,è,è,è,è,è$ë 3ítPèq…[ƒ0‹„q…q…PèÓ•„„Ž~È~“eè.Ó•Ó•Ó•q…f„lŽ~:È~*èÓ•q…*èÓ•„Ó•WÉ€ð,îÊÈ~J~ Ð[›³FÂk’z×†à –Ê,îÊ<“è<ÏèÂÊ,§í·’§íîÊÓ•„„„„Ù INCLUDEPICTURE "http://aesop.rutgers.edu/~biodiversity/RULOGO2.GIF" \* MERGEFORMATINET  Draft – For discussion only  EVALUATION DESIGN OF THE EARLY INTERVENTION PILOT Part II: DATA ASSESSMENT PAPER Prepared by: Sophie Mitra, Rutgers, the State University of New Jersey 23 October 2002  INTRODUCTION The purpose of this paper is to prepare a list of data needed for the evaluation of the Early Intervention (EI) pilot and to review available sources of data. The evaluation design paper for the EI pilot (Mitra and Dean, 2002) requires the collection of a broad range of data at different levels. First, Table 1 shows that a large amount of data is needed at the individual level: outcome data, baseline characteristics, intervention data, and linking data (i.e., identifiers to link across data sets). The important outcomes are individuals’ reliance on SSDI after enrollment in EI and earnings. The evaluation requires data about the baseline characteristics of individuals (education, work experience, and pre-EI earnings) that influence the post-EI outcomes. Data is also needed to characterize the interventions experienced by participants individually. Ideally, comparable information about the services received from treatments and controls should be collected so that the net intervention can be assessed, i.e. the extent to which the services received by treatments differ from the service mix used by controls. Finally, the evaluation requires information to identify applicants so that data about them can be linked from several sources. Second, information is required at the field office and EI Program Manager (EIPM) level regarding the implementation of the pilot. The data is mainly expected to show whether and how EI procedures are being implemented. Third, information needs to be collected at the service provider level whether it is the state VR department or an employment service provider (ESP). This information includes for each organization some general characteristics, the types of services provided, clients’ profiles and a description of relationships with other providers. Fourth, the evaluation requires economic and demographic data about the environments in which EI will be implemented that may influence the employment of persons with disabilities. Data will be collected through administrative records, visits, telephone calls, desk research and a survey. Each data element that needs to be collected and its source is described below under three categories, baseline, outcome and process data in sections 2, 3 and 4 respectively. In section 5, we discuss the organization of the data collection and outline the next steps to be taken for the completion of the data assessment. 2. BASELINE DATA We review below the information that is available at EI point of entry and, out of this data, we recommend a selection of baseline data that will be tracked for the evaluation of the pilot. Prior to applying any of the screening instruments, a claims representative (CR) must determine if the individual is eligible for DI. For the most part, the technical requirements for eligibility are earnings below SGA, an impairment with a duration of at least 12 months, and insured status. To meet the insured status requirement, a person must have worked long enough and recently enough under Social Security. The CR has access to SSA administrative records in order to determine if the insured-status requirement is met. Once these requirements are met, the eligibles are asked to fill out Form 3368 and Form SSA-16, and are subject to the two screens to determine whether they have “impairments that may be reasonably presumed to be disabling” (PL 106-70) and whether they are good candidates for a return to work program. It is important to note that this information is self-reported information and will not go through a rigorous verification process. We list below the information collected in each form and each screen. 2.a Form 3368 Information about the person (section 1) Section 1 includes name, contact details, social security number, weight, height, medical assistance card, level of fluency in English. Medical conditions (section 2) Section 2 gives a description of the illnesses, injuries or conditions and how they have affected the person’s ability to work. Subsection E asks “When did you become unable to work because of your illnesses, injuries or conditions?” We propose to use the answer to this question as an EI alleged data of disability onset that will be used as part of the dynamic analysis of earnings. Work History (section 3) This section presents the kinds of jobs held for the past 15 years, and their requirements in terms of physical activities (walk, stand, sit, climb, etc), lifting and carrying, and supervising other people. However, this section is often left blank or is filled in with data that is not comparable across eligibles. Medical records, medications, tests (sections 4,5 and 6) Under sections 4, 5 and 6, the applicant is asked detailed information on who may have medical records or other information about the illnesses, about hospital or clinic visits, medications taken and medical tests done. Education and training (section 7) The applicant is asked: the highest grade of school completed at grade school and college; whether the applicant received special education; and whether the applicant has completed any type of special job training, trade or vocational school. Vocational rehabilitation, employment, or other support services information (section 8) The applicant is asked if he or she is participating in the Ticket Program or another program of vocational rehabilitation services, employment services or other support services to help him or her go to work. If the applicant answers with a yes, information is required on the name of the organization, the name of counselor, the address and phone number, the dates seen and the types of services or tests performed. Section 9 includes remarks that the applicant would like to add. 2.b. Form SSA 16 Form SSA-16 includes general information about a DI applicant (e.g., name, SSN, date of birth) and is also a form of consent and understanding of the rules of disability insurance benefits. The only piece of information in SSA-16 that is not already included in form 3368 is the marital status of the applicant. 2.c First screen Claims representatives will collect the information listed below. This data will yield the probability of the applicant becoming a beneficiary. Age: Enter the applicant’s age. Mental: Determine the illnesses, injuries, or conditions that limit the applicant's ability to work. Enter a 1 if the applicant states that they have either a mental illness or mental retardation. Earnings: The data of interest are annual earnings over the last six years. Disregard current year and last year income. Average the preceding 5 years’ income. Enter 1 if average annual earnings were less than or equal to $10,712. Enter 2 if average earnings were between $10,713-$20,606. Enter 3 if average annual earnings were between $20,607-$34,344. Enter 4 if average annual earnings were between $34,345 and $54,951. Enter 5 if average annual earnings were greater than $54,951. Did onset of illness coincide with stopping work? If the onset of the illness was the same date as the date applicant stopped working, enter 1; enter 0 if the dates are different. Functional limitations: Assess whether the applicant has any of the following difficulties. Reading ___ Writing ___ Answering ___ Hearing ___ Sitting ___ Understanding ___ Using hands ___ Breathing ___ Seeing ___ Walking ___ Enter the number of functional limitations. 2.d Second screen Each of the variables of the second screen are collected on a three-point scale as follows.  Although the motivation questions are not yet finalized, there will be five questions worth five points each. The range of the cumulative motivation score will be between 5-25 points with 25 points reprenting a person highly motivated to work. 2.e List of Proposed Baseline Data Baseline data will be collected during the enrollment period of the pilot, as shown in Table 2. We have prepared in Table 3 a list of baseline data to be collected. Out of form 3368, we will use the education information (the number of grade school or college years completed), and out of form SSA-16, we will use the marital status information and the contact details (mail address and phone number). It should be noted that Form 3368 comes only in paper format while SSA-16 is entered into SSA’s administrative records in an electronic form. SSA is in the process of converting the form 3368 to an electronic format. If the electronic form is unavailable for the pilot, SSA staff will enter the information manually. Out of the first EI screen, we propose to track three items for all applicants: one demographic variable (age) and two disability related variables (presence of mental illness, number of functional limitations). Out of the second EI screen, we propose to track for those applicants who have already passed the first screen the disability type, the family support status, education and the work experience over the past two years. We also propose to collect, as part of baseline data, the health insurance coverage of persons who meet the return to work specialist (RTWS). Because every applicant who passes the two screens meets with the RTW, the majority of the population of interest is asked about their health insurance status. It is an important variable since during the national demonstration we will need to evaluate the magnitude of induced entry for the project. The RTWS will ask a few specific questions to determine the health care coverage of the individuals: 1) are you currently covered under Medicaid? If yes, do you pay for this coverage; 2) Are you currently covered by a private health insurance plan, for example that you get through an employer, a family member or that you purchase on your own; 3) Are you currently covered by any public assistance program; and 4) During the past 12 months, have you been covered by any other types of health insurance? All the above information will be available for all eligibles, except for the data collected as part of the second screen which will only be available for those eligibles who pass the first screen, and the health insurance coverage which will only be available for persons who pass the two screens and meet the RTWS. It is important to note that we plan to collect the education data from both form 3368 and the second screen. We realize that some of the data in the forms are limited in important ways, partly because they are collected for administrative purposes as opposed to research. In particular, it seems that the education and marital status information seem to be missing for an important share of DI beneficiaries in SSA administrative data system (The Lewin Group, 2001; p. 73). It may well be that these data are not consistently collected as part of the forms. In the pilot, we will have the education scale from the second screen if we do not consistently have the education information from form 3368. It is also important to keep in mind that SSA’s Numident file may be used for the collection of some baseline data. The evaluator can use it to determine mortality, to fill in missing information on age and to have gender or race data. The Numident file is the master file of assigned social security numbers and it includes the official death master file of the U.S. government. Given the small size of samples in the pilot, and hence the limited use that can be made of demographic characteristics, we do not feel that the Numident file should be used as part of the pilot evaluation. The completeness of the data collected in the pilot as part of the screens and the forms will be assessed so as to determine if the Numident file and other sources should be used for the national demonstration’s evaluation. 3. OUTCOME DATA To the extent possible, outcome data will be collected through administrative records because of the lower cost and greater accuracy of these records compared to self-reported information. 3.1 Benefits data As shown in Table 1, benefits data are required in the pilot for all participants as well as nonparticipants in order the test the effectiveness of the first screen. Benefits data will be collected from the Disabled Beneficiaries and Dependents Master Beneficiary Records (DBADMBR) which is an extract of the MBR that only includes information of disabled beneficiaries and their dependents. The DBADMBR contains the data needed to generate Social Security benefit checks under the OASDI. For all SSDI recipients, this file contains variables indicating beneficiary characteristics and information on SSDI program participation. From the DBADMBR, we want to know for each individual if he or she has received DI benefits, over what period(s), in what amounts, and the reason why benefits may have been changed or terminated. Benefits data are available on a monthly basis and provides a complete benefit history during the post random assignment period up to the time of data extraction. A benefit history file will need to be created to summarize DI benefit information including benefit status codes and the dollar value of monthly benefit. The file also covers the first month of eligibility for DI benefits, the total number of months on DI, the date of conversion to SSA’s Old Age program and the date of death (if applicable). Table 4 shows the data elements from DBADMBR that might be required for the evaluation. We have prepared this list on the basis of the data required in the evaluation of other RTW experiments. Descriptions of data elements in Table 4 are from Panis et. al (2000). The ledger account file (LAF), the beneficiary identification code (BIC) and the type of claim (TOC) give the benefit receipt status of the individual. The monthly benefit credited (MBC) shows the amount received as benefit. The date of initial entitlement (DOEI), the date of current entitlement (DOEC), the date of entitlement to disability insurance benefits (DOED_n) and the date of suspension/termination (DOST) are useful for beneficiaries who have different periods of disability. In the State Partnership Initiatives (SPI) project, these variables were used to construct a variable summarizing this information to report the “length of time on SSDI”. In cases where DOEI and DOEC are the same, the period of entitlement is current, and denotes an individual’s first instance of benefits receipt. DOST denotes the end of benefits receipt for the current spell, resulting from suspension or termination. Four variables (HI-START, HI-END, SMI-START and SMI-END) give the period of coverage under Medicare. It is important to keep in mind that the MBR is scheduled for a major re-write some time in 2003 (Panis et. al 2000). New variables will be added, some will be deleted, and some will be expanded to include historical transaction information. Our data collection plan will need to be adjusted accordingly. 3.2 Earnings data Determining the impact of the pilot on earnings presents the challenge of collecting accurate and meaningful earnings data. Earnings data will be collected from two administrative sources: SSA’s Master Earnings File (MEF) and state employment commission records. The MEF is SSA’s primary repository of earnings data for the US population. The Summary Earnings Record (SER) contains an annual summary of all FICA earnings received by an individual and detailed information on all FICA earnings processed since 1977. The source of the SER earnings data is W-2 forms that are received continuously. The file is updated on a bi-weekly basis. Annual earnings for a calendar year are available approximately 11 months after the end of the tax year. Non-SSA staff (contractor staff) are not allowed direct access to the SER. Special files including earnings data would need to be generated by SSA staff. Contractor staff can develop programs that SSA staff will run on these files, and transmit the results to the contractor staff. Alternatively, the earnings data in these files must be at a sufficient level of aggregation for the contractor to be allowed access. In the EI pilot evaluation, earnings data could be generated at the treatment and control group levels. SER data correspond to FICA earnings covered by SSA in a given calendar year. The earnings measure for that year may represent a mingling of different streams of earnings. In particular, for the year the individual applies for DI, the earnings measure may reflect a mix of predisability earnings, and much lower earnings or no earnings until EI cash stipend or DI benefits are received. We do not know how much earning of the total for that year accrues during each of these phases. Such mix is reduced if we use the quarterly earnings data from the state employment commissions. State employment commissions record earnings only from occupations covered by unemployment insurance (UI). For a record to be generated, the employer must contribute a portion of the employee’s wages to the relevant state UI trust fund. State employment commission earnings data have the advantage of being available on a quarterly basis rather than on an annual basis in the MEF, and of being released 6 months after the end of the quarter, while MEF earnings are available approximately 11 months after the end of the tax year. It should be noted that state employment commission data do not capture individuals’ earnings out of the jurisdiction of the commission (i.e. out of the state). Pilot sites in Vermont and Wisconsin are close to state borders, so participants are likely to engage in out of state work. It is possible though to do a cross-state data request. We could submit a batch file with the participants’ SSNs to the pilot state and the neighboring states employment commissions, which might be a lengthy process. In addition, according to Abt (2000), sometimes states keep only a limited amount of historical data in readily accessible form. For instance, some keep only five quarters of earnings, which is the amount needed to adjudicate unemployment claims. Prior quarters of data are archived and may be difficult to retrieve. Therefore, it will be important to begin soon to investigate the availability and utility of UI earnings data in each pilot state. Despite these limitations, it will be critical to test the process of collecting quarterly earnings data from state employment commissions in the pilot. The Office of Child Support Enforcement (OCSE) compiles this data at a national level. SSA does not have access to this data, but may have access in the future. 3.3 Employment data The pilot evaluation’s focus is more on the assessment of processes than impacts. Benefit receipt and earnings are the two outcomes that the pilot evaluation will cover. Employment data will be needed to test the effectiveness of the return to work screen. Employment data will therefore need to be collected from the treatment and control groups as well as from second screenouts (i.e., applicants who passed the first screen but failed the second one). This will allow the evaluator to find out how accurate the return to work screen is in selecting applicants who have a successful return to work. The exact timing and contents of the survey need to be determined. It seems that the survey would need to be administered at least once and that it should cover the following four employment related outcomes: total number of hours worked, hourly wage rates, fringe benefits, and occupations. The contact information collected as part of Form SSA-16 will need to be entered into the MIS for the purpose of administering the survey. 4. PROCESS DATA 4.1 Site Profiles The pilot will be implemented in selected sites located in four states. Each site refers to an SSA field office (FO) that may serve one or more counties. Among the pilot evaluation sites, there is a broad diversity in the geographic location, the urban/suburban/rural mix, the racial and ethnic compositions, the role of the state vocational rehabilitation (VR) department and of employment service providers (ESPs). The evaluator will prepare descriptive profiles for each of the pilot sites to account for this diversity. The site profile will include tables of relevant data and a write up. Quantitative data will be collected through desk research, using the Census Bureau as a major source. Qualitative information on site specific conditions will be obtained through telephone calls or visits to key site individuals and organizations (e.g., ESPs, disability advocates, researchers). The site profile will be prepared in year one of the project but will need to be updated in year two to account for any contextual change that may have an effect on the pilot’s operations. Table 5 presents data about the economic and demographic environment of each site. Table 6 gives a list of data that is aimed at presenting an overall picture of employment service provision at the county level. Table 7 shows data to be collected at the service provider level for participating ESPs. The list of data to be collected at the ESP level varies depending on whether the services are provided by VR or by private providers. The ability to collect certain types of data (e.g., clients’ profiles) is expected to vary among ESPs. Data at the service provider level (Table 7) will be collected through standard sets of questionnaires that are to be prepared by the Rutgers team. If the pilot states have the necessary resources and are willing to participate in the evaluation, they can collect part or all of the data required for the preparation of these site profiles in agreement with the Rutgers team. 4.2 Implementation Analysis Data The implementation analysis will serve different purposes. The first is to confirm and update basic information about the status of the pilot, including the number of random assignments. The second is to track the implementation of procedures, and attempt to identify some procedures that need to be modified in the context of site or model specific conditions. This monitoring plan will start at the beginning of the enrollment period and will continue during the three years of the pilot post enrollment. It will cover the activities of all the organizations involved in the pilot implementation, mainly the EIPM and the SSA field offices (FO). Table 8 gives a list of information that will need to be collected for the implementation analysis. Data will be collected through structured phone calls, site visits and reports. Information might also be collected from copies of all forms used by local pilot staff and client case folders if need be. The EIPM will need to have twice-per-month meetings with SSA and the Rutgers team by teleconference and will submit monthly reports to SSA regarding progress and issues on the project implementation. FO managers will participate in a monthly teleconference call with SSA and the Rutgers team. The Rutgers team will visit each site three times during the pilot period: two month after the beginning of enrollment, two months after the end of enrollment and one year after the end of enrollment. During site visits, the Rutgers team will conduct structured interviews of a sample of key site representatives (FO and EIPM staff). If the pilot states have the necessary resources and are willing to participate in the evaluation, they can conduct part or all of these meetings in agreement with the Rutgers team. Participation of local evaluation staff will enhance the accessibility and continuity of data collection. 4.3 Individual Service data Intervention data is an essential part of the process evaluation. The data required include the types of services received, their duration and their costs. The experience of service providers and the services provided is a major focus of the process evaluation since it has an impact of the program’s outcomes. Ideally, data on services provided should be collected in a similar manner across different types of service providers, participants’ subgroups and models. A survey of members of the treatment and control groups is one way to collect information on services provided by VR and ESPs. However, surveys are expensive and they may be an unreliable source of service data since the quality of the data is likely to be compromised by recall bias and to be correlated with participants’ impairments. We assess below other ways to collect service information for VR and ESPs. 4.3.a VR service information Individual VR service data would be useful for the process evaluation and the cost benefit analysis as part of the assessment of the levels and costs of services provided to the controls who go on DI and use VR, and for the treatments who receive VR services under the Intensive Service Barrier Removal Model and the Integrated Community Support Model. SSA’s administrative data contain information on beneficiaries’ use of VR services. However, this information is limited to payments to the VR system for services rendered if a beneficiary returns to work. While RSA data contain substantial information on the use of state VR services, it may not be feasible to link RSA and SSA data for the purpose of the pilot evaluation. The RSA 911 file, which has detailed service and cost information, is available only for participants who have formally exited the VR system. VR consumers spend on average two years in the system before being closed, so it seems that only a small number of EI participants may be covered under RSA 911 by the time the two year long pilot ends. An alternative would be to use in each pilot state the state VR agency data. For each pilot site VR agency, the evaluators would submit a batch file of SSNs for the treatment and control group members in order to obtain for each individual a purchase service file. Before the large scale demonstration is implemented, SSA hopes to have an interagency agreement with the Department of Education to obtain national level access to the state’s VR data. 4.3.b Employment Service Providers (ESPs) While SSA intends to limit the administrative burden placed on the ESPs, the exact data that they will be expected to report is yet to be determined, and will vary by model. Under the Intensive Service Barrier Removal Model, ESPs will be paid on a cost basis, they will therefore report every service to the EIPM for reimbursement. The type and cost of the services provided will therefore be available as part of the management information system set up by the EIPM for each individual. Under the Employment Service Market System Model, ESPs are paid on an outcome basis, ESPs will not have any incentive to report every service they provide to each individual. If the IWP (Individual Work Plan) is reported, the services listed in the IWP could be used as a proxy of the actual services received. It is unlikely, however, that the services actually provided will correspond to those initially included in the IWP. The ESP is expected to be in contact with the EIPM on a monthly basis so that if there is a change in the type of services provided to each individual, the EIPM should be informed. ORGANIZATION OF DATA COLLECTION AND NEXT STEPS Table 2 gives a summary of the different types of data to be collected, the sources and the timing of collection. Data collection will start the day DI applicants start going through the EI screens (the beginning of the enrollment period), and will end three years after the enrollment of the last participant. 5.1 Management Information System Part of the data required in the evaluation will be collected and stored through a standardized Management Information System (MIS) that will be set up by the EIPM. The MIS will be used to record all individual data about pilot participants (and non-participants) and to track the various stages in the service provision and employment development process. Table 9 shows the types of data stored in the MIS for each model and the persons who will input the data into the MIS. The MIS will include baseline data from SSA forms and the web-based entry screens, SSA administrative records (benefits), records maintained by the RTWS for the provision of the cash stipend and the health insurance and the EIPM regarding service provision. SSA staff may need to manually enter form 3368 and SSA-16 information into the MIS until both forms are available electronically. 5.2 Data Collection Responsibilities While the Rutgers team has the responsibility for conducting the evaluation of the EI pilot, several persons and organizations will participate in data collection for the evaluation. Table 10 and Figure 1 show an allocation of data collection responsibilities. The Claims Representative will enter the data for the EI entry screens and the electronic SSA-16 form. The RTWS will be responsible for collecting inducement related data while the EIPM will be in charge of gathering individual service data. The Rutgers team will be responsible for the collection of administrative data (VR data, earnings and benefits data), on the one hand, and for the site profile and the implementation analysis, on the other. Central SSA staff will assist the Rutgers team in gaining access to SSA administrative data (MBR, SER). If states have the necessary resources and are willing to participate in data collection for the evaluation, they will work with the Rutgers team to collect information for the site profiles and the implementation analysis. The team responsible for administering the survey (survey staff) will collect employment related data. 5.3 Next Steps 5.3.a Evaluation procedures The evaluation must have procedures in place to document the implementation of the pilot in the different sites. These procedures include routine procedures to be performed by implementation staff (i.e., the CR, the EIPM) and periodic procedures to be performed by evaluation staff (the Rutgers team, state teams when applicable). The Rutgers team is currently preparing the former as part of the states’ protocols, and the latter were broadly described under the implementation analysis data above (section 4.2) and will need to be refined before the beginning of the pilot in 2003. 5.3.b Participant Agreement An important implication of the evaluation design is that individuals’ consent must be obtained in order to collect data from administrative records. The scope of the required consent varies depending on their status in the project (e.g., first screenout, second screenout, participant in Table 1). This agreement is currently being prepared by SSA. 5.3.c Survey As a final step of the data assessment, the Rutgers team is to prepare the employment survey. The contents and the timing of the survey will be the subject of part III of the evaluation design of the Early Intervention project. REFERENCES Abt Associates (2000), Evaluation of the Welfare to Work Voucher Demonstration: Evaluation Design, Final Report. Abt Associates (1999), Impacts of the Project Network Demonstration: Final Report. Agodini et al (2001), Initial Assessment of SSA Administrative Data for Use in the Net-Outcomes Evaluation of the State Partnership Initiatives. The Lewin Group (2001a), Evaluation Design for the Ticket To Work Program, Part II: Data Assessment Report, December. The Lewin Group (2002), Evaluation Design for the Ticket To Work Program, Attachment B: Beneficiary Survey Instrument, March. Mitra S., and D. Dean (2002), Evaluation Design of the Early Intervention Pilot, Rutgers University. Panis, C., R. Euller, C. Grant, M. Bradley, C. E. Peterson, R. Hirscher and P. Steinberg (2000), SSA Program Data User’s Manual, Rand.  Table 2: Overview of Data Collection Data ElementComponent of    Data Sources     Date   Evaluation           ProcessImpactScreensFormsAdmin. data setsVisitsPhoneDesk researchInterv. RTWSSurveyOtherEnroll. periodYear 1Year 2Year 31. Participants' level data              1.1 Baseline Dataxxxx    x  x   1.2 Individual Service Data               - VR data in 3 modelsx   x      xxx  - ESP data in Barrier Rem. Modelx         xxxx  - ESP data in Market System Modelx         xxxx 1.3 Outcome Data               - Benefits x  x      xxx - Earnings x  x      xxxx - Employment x      xx xx                2. Site Profilesx    xxx   xx                 3. Implementation Analysisx    xx    xxxx                 Table 3: Proposed Baseline Data From form 3368 Social Security Number Education EI alleged data of disability onset From form SSA 16 Marital status Contact details From the first screen Age Mental illness Earnings Number of functional limitations From the second screen Disability type Family support Education Work experience in past two years From interview with the RTWS Health insurance coverage Table 4: List of Relevant MBR Data Data elementDescriptionBaseline dataClaim Account Number (CAN)This data element is the social security number of the person whose earnings are the basis of the benefit record.Indexed Monthly Earnings (IME)Represent pre-disability earnings (AIME). It is a measure of past earnings capacity. PIA is a function of IME, and MBA is a function of PIA.Benefits outcomeType of claim (TOC) Indicates the type of claim made by the beneficiary (e.g., retired, survivor, disability).Beneficiary Identification Code (BIC)Reflects the category of benefit for which the claimant has applied. It may not have been approved or may not be active for other reasons. Categories include disabled worker, spouse, child, widow(er). Together, TOC and BIC define the benefit type. For instance, disabled workers are BIC A and TOCs 5 and 6Ledger account file (LAF)Reflects MBR payment status: current, deferred (the reason why) and death.Reason for deduction (RFD)Indicates the reason a payment is reduced or withheld.Benefit paid designation (BPD)Indicates that a benefit was paid or credited in the current month. It is used for studying how benefit status changes over time.Reason for suspension or termination (RSF)Represents the specific reason for the suspension or termination of benefits.Monthly Benefit Credited (MBC)MBC is the MBA rounded to the next lowest dollar, but prior to the collection of any obligation of the beneficiary (including SMI premium). For statistical purposes, this is the basic benefit amount.Date of Current Entitlement (DOEC) Reflects the start date (month and year) for a beneficiary’s current period of eligibility or entitlement. Entitlement means that all the requirements for eligibility have been met and a claim has been filed. For the disabled, the date may be retroactive for up to 12 months.Date of Initial Entitlement (DOEI)Reflects the initial date of entitlement to a social security benefit. It denotes an individual’s first spell of benefits receipt.Date of entitlement to disability insurance benefits (DOED_n)Reflects the date (month and year) on which the beneficiary became entitled or deemed entitled to disability benefits. Multiple spells of disability are recorded depending on an individual’s applications, benefits and terminations. The variable DOED_n parametizes the different periods of disability by storing the date values for the beginning point of entitlement of each period. Date of suspension/termination (DOST)This date is the effective month in which benefits are suspended or terminated. If a beneficiary has been suspended or terminated, the beneficiary has a DOST. If benefits are reinstated, DOST is cleared and no date exists. However, the actual posting may be delayed, the date the credit action is processed is reflected in another variable , the DOCA (date of credit action).Medicare coverageHI-STARTShows the beginning of Hospital Insurance enrollmentHI-ENDShows the end of Hospital Insurance enrollmentSMI-STARTStart date for SMI coverageSMI-STARTEnd date for SMI coverage Table 5: Demographic and Economic Data for Site Profiles Characteristic Reason for InclusionNational StateSite  AverageAverageAverage   Demographic attributes  Population growthRelative measure of change in population  Percent of population of Hispanic or Latino OriginRelative measure of ethnic breakdown of population  Percent of population not White or Hispanic/LatinoRelative measure of ethnic breakdown of population  Percent of population in Metro AreasRelative measure of client concentration for service providers and jobs     Labor market conditions  Per capita incomeRelative measure of average income level  Poverty rateRelative measure of other disadvantaged populations competing for jobs  Unemployment rateRelative measure of work opportunities  Unemployment volatility 1990-2000Relative measure of fluctuations in work opportunities  Employment growth 1990-2000Relative measure of employment growth   Percent of manufacturing employmentConcentration of the labor market in occupations which have traditionally    provided fewer opportunities for persons with disabilities  Percent change in share in manufacturing employment Relative measure of labor market change away from occupations which have  1992-2002 traditionally provided fewer opportunities for persons with disabilities   Percent of workers who commute on public transportationRelative measure of access to EI services and work opportunities  DI and SSI recipients as a percentage of the populationReflects underlying state characteristics that define disability (state DDS    practices, overall education levels, and other labor market factors/barriers)  Median Monthly benefit for DI recipients relative to Relative measure of the generosity of benefits and related work disincentives  median household income  Employment rate among SSI disabled beneficiariesRelative measure of the SSI beneficiaries access to work    Table 6: County Level Employment Service Provision Profile Number of ESPs and locationsMain characteristics of providers - providers' clients' profiles - service focus - public/private - caseloadRelationships between VR and other providersOther employment program(s) in the county Table 7: Service Provider Level Data for Each Participating ESP VREmployment Services Provider   1. Characteristics    - annual caseloadXX - number of staffXX - date incorporated X - profit/non-profit status X - public/private X   2. Type of services   - trainingXX - placementXX - post-placementXX - otherXX - service delivery areaXX   3. Clients' profiles   - by disability typeXX - by ageXX - by genderXX - by nb of ADLsXX - by marital statusXX   4. Number of cases in status past 5 years   - status 02 (applicant for VR services)X  - status 08 (not eligible for VR services)X  - status 10 (eligible for VR services, receiving services)X  - status 30 (eligible for VR services, no services received)X  - status 28 (not rehabilitated after receipt of services)X  - status 26 (successfully rehabilitated)X    5. Relationship with VR X   6. Relationship with other providersXX    Table 8: Scope of the Implementation Analysis SSA Field Office (FO)Orientation of FO ManagersTraining of CRsCR Caseload size (numbers of persons who took screens 1 and 2, who dropped out right after passing the screens) Tracking of EI procedures to be followed by the CRTime spent by CRs on EI proceduresEI costs to the field office EIPMHiring and training of the RTWSManagement of the RTWSRTWS Caseload size (numbers of persons allocated to treatment and control, and who dropped out after meeting RTWS) Tracking of EI procedures to be followed by the RTWS  - Random assignment - counseling - number of days between encounter with the CR and the first meeting with the RTWS - efficiency of the referral back to the CR for controls and nonparticipantsEffectiveness of the MIS in collecting and storing data for the project's implementation and evaluationAdministration of the cash stipendAdministration of payments to ESPsFacilitation of health insurance coverageCoordination with other organizations VR and ESPsStaff orientation  Table 9: Data Collection through the MIS Data Element Model  Input into MIS by ICSESMSISBRCRRTWSEIPMOther        1. Baseline Data        - Screensxxxx    - Form SSA-16xxx   x - Form 3368xxx   x - Health insurance coveragexxx x       2. SSA Administrative records    Monthly Benefit Amountxxxx      3. Inducement Related Data        - Monthly Earningsxxx x   - Medicare coverage (e.g., start date)xxx xx  - Medicaid coverage (e.g., eligibility, start date)xxx x          4. Individual Service Data        - Detailed service and cost data  x  x  - Type of service provided x   x          Notes: ICS stands for Integrated Community Support model, ESMS stands for Employment Service Market System model, ISBR stands for the Intensive Service Barrier Removal model. Table 10: Allocation of Data Collection Responsibilities  Figure 1: Allocation of responsibility and method for data collection   CR ( RTWS, EIPM ( M.I.S. Other ( Rutgers Team ( Admin. Central SSA staff ( Data sets Rutgers Team ( Visits and State Team (when applicable) Phone calls Rutgers Team ( Desk research State Team (when applicable)  Survey staff ( Survey  The work presented here was performed pursuant to a grant from the U.S. Social Security Administration (SSA) funded as part of the Disability Research Institute.  The opinions and conclusions expressed are solely those of the author(s) and should not be construed as representing the opinions or policy of SSA or any agency of the Federal Government.  The project is going to induce some individuals who have no real intention to attempt to go back to work to apply for EI so as to benefit from the immediate cash stipend and health insurance.  Questions were prepared in part on the basis of the health insurance component of the Ticket To Work’s beneficiary survey instrument (The Lewin Group, 2002).  Agodini et. al (2001) for the State Partnership Initiative Project, Abt (1999) for Project Network, The Lewin Group (2001) for the Ticket To Work Program.  Data is broken down into baseline data, outcome data and process data although there is a limited overlap between outcome and process data. For instance, service information pertaining to costs in the process evaluation is also used in the outcome evaluation as part of the benefit cost analysis. 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Screen-outs-! Withdrawals*/! EI Participants¾ -9Failed FailedPassed 2 screens,.:Passed 2 screens9 first screen second screenwithdrew control grouptreatment group¾StayerLeaver,1. Baseline data¾ (dropped out) education  x x x x x xmarital status  x x x x x x age  x x x x x x mental illness  x x x x x x Number of ADLs  x x x x x x disability type   x x x x x family support   x x x x x recent work experience  x x x x x motivation x x x x x#health Insurance¾  #x 8x #x,2. Service Data¾!dates of service receipt¾  x x x6-nature of services received (e.g., placement)¾  x x x completion¾  x x x8/nb of days from random assignment to completion¾  x x x.%nb days from completion to employment¾  x x x service cost¾  x x x,3. Outcome Data¾(DI beneficiary status (monthly) x x x x x x%DI benefit amounts (monthly)¾  x x xNumber of hours worked x x x xhourly wage rates x x x x(earnings (quaterly or annually) x x x x,4. Other¾Contact information x x x x xsocial security number x x x x x x×D&lÊ€’:KkpeppmlsgW2_tQvlS2€cojx+p ,)  Dropout interview (date, reason)¾  x×c>¶@  ï7 ¯ÍÉ@  dü©ñÒMbP?_*+‚€%,Áƒ„'{®GázÄ?M–HP 2200ܸ?€dXXLetter”.HP LaserJet 2200 Series PCL 62z†xœePKKœA¬úzu|Æ=•É FW‘/›E¼æ 9„_gÔ„îeD{A/9(Hù brMþˆ˜³·DóØÌ÷-.ô¡zª¦›©©JåÿŠˆUÞ2´·|·I®)Åæ­}J¹d­fƒ¬FÔV«§¢ý”#éÎDú–£mQ‡¨cÔaÚ(Ãöc„öšmÐEê6_gVg Yý.¡ÛÌÂí%—v©;éÈ83‚C£Oøµô% ÈB®dî›DH+̬ÓSZ¹ ûýòôô íì'ôì!µ‡ÚK=ó´>J'W hYZíPªç¢Rú$ú5’3ù€ð[yÁýs‘Ð]¤ñQÓˆoÑ ™âb$ÓôXJ/ÓìfØ k£¶S;B€&½¡ YÇ=à\\¡"dXXà?à?U} ¶d} ¶}  ¶ ,,,,,,,, , , , , ,,,,,,,,,,,,,,6SSA Field Office (FO)##Orientation of FO ManagersTraining of CRsypCR Caseload size (numbers of persons who took screens 1 and 2, who dropped out right after passing the screens) ;#2Tracking of EI procedures to be followed by the CR+#"Time spent by CRs on EI procedures%#EI costs to the field office ,EIPM( Hiring and training of the RTWS Management of the RTWS| sRTWS Caseload size (numbers of persons allocated to treatment and control, and who dropped out after meeting RTWS) > #5Tracking of EI procedures to be followed by the RTWS !# - Random assignment# - counseling`#W - number of days between encounter with the CR and the first meeting with the RTWSZ#Q - efficiency of the referral back to the CR for controls and nonparticipantspgEffectiveness of the MIS in collecting and storing data for the project's implementation and evaluation+"Administration of the cash stipend+"Administration of payments to ESPs2)Facilitation of health insurance coverage.%Coordination with other organizations, VR and ESPs4Staff orientation1×86ô"'}?/) ,#€B%d^t//62 >¶@ï7 ¯ÍÉ@  dü©ñÒMbP?_*+‚€%,Áƒ„&Ãõ(\ÂÅ?'{®GázÄ?M–HP 2200ܸ?€dXXLetter”.HP LaserJet 2200 Series PCL 62y†xœePKKœA¬úzu¢ñ±_£Cbâù\É5õ xDcî.Ä$t/»"âcAЋ!„ü1¹ê={ÓÄÇ:ß·¸҇꩚n¦¦Êåÿ+"Þñ’¡}äw¸Ï$àRlLЪД#V«öœ•ˆúˆÇÊWѧ”é‚ÎDz ¢­R¨#Ô—´a†íAÆmÍÐ%ê[&l±Æ¬ÆÞfµ»„®1 ·™<\Ü ®§#£Ì>ágÒ“4 9•e¸s‰V˜yÏ>jíz‹Ò_è ´Ÿv»†ÞÁ:©]Ôn꾘§õPZ¹ m£eií´m©ˆ~‘â/Ñ“H¾É„¿Êknµ˜‹ôÝaΓ{S¼@ÀFâÁ°?œ‚œ©Ë?ÿ•êò^]v¿e ù|.çç ¥•BÙÍMÎúWË…RyÅÔû‰8Ç9?UøûDMþƒÈ$—"™  »RœN“›a+¬™ú˜ÚâË0Iè]H28¾ùÜ\i¡"dXXà?à?U} ¶d} ¶1} ¶A} ¶),,,,,,,, , , , , ,,,,,,,,,,,,,,,,,8/Local Environment Analysis (county/state level)¾&Characteristic 'Reason for Inclusion National State Site¾ 20AverageAverageAverage¾,Demographic attributes¾#Population growth1(Relative measure of change in population¾ ;#2Percent of population of Hispanic or Latino Origin;2Relative measure of ethnic breakdown of population¾ ;#2Percent of population not White or Hispanic/Latino;2Relative measure of ethnic breakdown of population¾ - 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Cammisa5C:\WINDOWS\Desktop\NotesonReport,February 24,2002.docMonroe Berkowitz.C:\temp\zips\NotesonReport,February24,2002.docRutgers University9C:\My Documents\Pilots\NotesonReport,February 24,2002.docRutgers UniversityMC:\My Documents\Pilots\Transmitted comprehensive report, February 27,2002.docEconomics DepartmentID:\drepweb\Reports\Transmitted comprehensive report, February 27,2002.docJþÿÿÿÊ‚^:ÿÿÿÿÿÿÿÿÿÿt1 ÿ¯`o”pRëÿÿÿÿÿÿÿÿÿMY°P»´êÿÿÿÿÿÿÿÿÿ²Vg ÿœyö ÿ†kÿŠQä~ÿÿÿÿÿÿÿÿÿYH‡ ÿ‘/`^‚žÿ _PID_GUIDäAN{9649769E-E5C7-11D6-AA78-0002A57AFE8E}Ole ÿÿÿÿÿÿÿÿÿÿÿÿCompObjÿÿÿÿfObjInfoÿÿÿÿÿÿÿÿÿÿÿÿWorkbookÿÿÿÿœ? ¯ÍÉ@B°aÀ=œÞ”=xZ§:T$8X1.ÈÿTimes New Roman1.ÈÿTimes New Roman1.ÈÿTimes New Roman1.ÈÿTimes New Roman1.ÜÿTimes New Roman1.Üÿ¼Times New Roman1.ÈÿTimes New Roman1.ÜÿTimes New Roman1.È Times New Roman1.È$Times New Roman"$"#,##0_);\("$"#,##0\)!"$"#,##0_);[Red]\("$"#,##0\)""$"#,##0.00_);\("$"#,##0.00\)'""$"#,##0.00_);[Red]\("$"#,##0.00\)7*2_("$"* #,##0_);_("$"* \(#,##0\);_("$"* "-"_);_(@_).))_(* #,##0_);_(* \(#,##0\);_(* "-"_);_(@_)?,:_("$"* #,##0.00_);_("$"* \(#,##0.00\);_("$"* "-"??_);_(@_)6+1_(* #,##0.00_);_(* \(#,##0.00\);_(* "-"??_);_(@_)àõÿ À àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ àõÿ ôÀ à À à+õÿ øÀ à)õÿ øÀ à,õÿ øÀ à*õÿ øÀ à ôÿôÀ à ôÿôÀ à õÿ øÀ à(À à 0À à(8@ @ À à(8 @ À à(8@ À à(8 À à 8@ À à (@ À à (@ À à 8@ À à(x@ @ À à À à (@@À à (@À à (@À à ( @À à (@ À à ( À à ( À à(8@ À à"8@ À à"8 À à (@ À à (@ À à (@@ À à À à (@ À à ( @ À à#8@À à"8@ @À à(8@ À à (@ À à  @ À à 8@ À à @À à À à @ À à (@À à (@À à"0@ À à*8@ À à 8 À à ( À à (P @À à (P À à(8Q@ @ À à(8Q@ À à"8Q@ À à (Q@ À à(x@ À à (P À à(8P @ À à(8Q@ @À “€ÿ“€ÿ“€ÿ“€ÿ“€ ÿ“€ÿ“€ÿ“€ÿ…¥Respons.…E Overview… ¾0MISŒ®  ;  ;  ;ÁÁ`iük¼> Claims Rep.RTWSCentral SSA Staff Survey Staffx?Other1. 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