This Web site is a component of the SAMHSA Health Information Network
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This Web site is a component of the SAMHSA Health Information Network. |
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1999 Annual Report to Congress on the Evaluation
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CHAPTER SUMMARY In summary, service and cost data from the Phase I national evaluation indicate that:
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| One of the goals of systems of care is to provide a broad array of services to meet the individual needs of children and their families (see text box). How each system of care chooses to address the needs of its population of children varies and is dependent upon the structure and goals of the system, the population targeted for services, and the developmental stage of implementation of the system of care. For example, some systems may supplement outpatient mental health services with in-home or school-based services that reside within the administrative structure of the system. Other systems may rely more heavily on intensive case management to "broker" services from a menu of community-based providers. The approach used depends on current service needs, linkages to the community, and treatment philosophy, all of which may vary across time as systems of care develop with the support of Federal funding. |
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Information regarding the services children receive and the cost or charge for those services can provide valuable data to program staff, managers, and decisionmakers, both locally and at the State and Federal levels. On a local system level, service and cost data provide program directors and other staff information to assist them in effectively implementing, monitoring, and evaluating service delivery to individual children and families and examining overall service patterns. Information regarding
can illustrate how service arrays expand or contract and how time is allocated across services and among different providers (e.g., paraprofessionals, licenced therapists, PhDs, MDs), and can describe costs. This information can be used to make programmatic decisions regarding financing and sustainability, staffing, and services development.
Data regarding service utilization can also be used to describe and interpret changes in outcomes among individual children. Children who enter mental health services with more challenges (e.g., severe functional impairment, higher levels of emotional and behavioral problems, more frequent contacts with the law) use more services for longer periods of time than children without these challenges (Doucette-Gates, Hodges, & Liao, 1999; Lambert et al., 1998). Identifying patterns of service use for different subgroups yields valuable information for determining the relationships between observed patterns of care and a system's model for optimal service delivery. For example, systems of care seek to treat children in the least restrictive setting possible. Holding all other influences constant, inpatient psychiatric hospitalization rates should decrease among children over time. Alternatively, a recent analysis suggested that after adjusting for various individual characteristics and mental health status, added doses of outpatient therapy may improve children's functioning over time (Foster, in press). Information regarding service use or "service mix" such as service duration, services received, and service intensity (Center for Mental Health Services [CMHS], 1997) may also contribute to an understanding of changes in functional outcomes across time. Service use data can contribute to quality assurance efforts and outcomes accountability, two key processes providing feedback to systems as they develop across time.
A well-maintained, accurate, and complete computerized management information system (MIS) is critical to understanding the use of individual services, combinations of services, and their costs. Without an adequate MIS, it is difficult to understand which services are utilized by which children and families and how individual children with serious emotional disturbance participate in the system of care.
Unfortunately, the technology for the development of comprehensive MIS's has lagged behind the development of systems of care in individual communities, resulting in a situation in which it is difficult to capture the available service mix comprehensively. Currently, documentation of the services children and families receive is most often available through mental health MIS's. These MIS's function primarily to track the service a child receives and generate a billing record for that particular service. Although the types of services tracked in public mental health MIS's vary, they are usually limited to outpatient services such as therapy, case management, medication monitoring, and crisis services or intensive in-home services.
Because children and families receive services from different agencies in systems of care, it is important to follow or monitor what services children are receiving, not only to describe the full service array and determine cost accurately, but also to assess what service factors may be supporting changes in child and family outcomes over time. For example, do children who receive therapeutic foster care remain in stable home settings longer and have improved functional outcomes over time? Most therapeutic foster care is funded by child welfare and thus is not typically included in mental health service databases, necessitating the inclusion of MIS's from child welfare agencies. Gaining access to other agency databases is dependent on personnel time, technical expertise, and existing interagency relationships regarding data sharing. It is often difficult to combine MIS's across agencies because information may not be clearly linked to individual children and families and therefore may be difficult to interpret.
Although mental health MIS's are not standardized, there are several pieces of information that the majority of systems monitor to bill third-party payors for services rendered. The information that is typically tracked is shown below.
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Information Typically Tracked in Management Information Systems
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This small, yet important set of information provides data to describe different patterns of service utilization for children and families who are using mental health services.
Mental health MIS data were solicited from all 22 grant communities in Phase I of the national evaluation; however, not all systems of care had a functioning MIS. Fifteen systems of care provided some type of service and/or cost data, 10 of them using an existing computerized MIS. Service and cost data were not available for the remaining seven grant communities for the following reasons. Four of the seven grant communities had no existing MIS system. These grant communities did not develop a system to track services linked to individual children, although one grant community was developing an extensive MIS that eventually will integrate demographic, clinical, outcome, and service information. One grant community did have local service information, but could not access and compile the data. The final two grant communities did not have a local MIS system but tried to use State Medicaid databases to provide information regarding system-of-care services.
Data from existing mental health management information systems were used to assess the types of services children received. For this analysis, grant communities provided MIS data regarding services received by families from 1996 through 1998 (the last year data were currently available). Criteria for inclusion in the service and cost analysis included the following:
Five of the 15 system-of-care grant communities that provided information regarding services did not access information by using an existing MIS. Some of these grant communities compiled case records and counted the number of services documented. Other grant communities "estimated" the services children and families may have received by assessing individualized service plans. Yet other grant communities gathered cost data using simple spreadsheets and counted aggregate grant dollars spent by service category. These five grant communities were not included in the analysis. The majority of data from the remaining 10 grant communities came from mental health billing systems. Four of the 10 grant communities were profiled in the 1998 Congressional Report (Charleston, South Carolina; Vermont; Stark County, Ohio; and Baltimore, Maryland). Of the six remaining grant communities, five met the previously stated criteria.
The following sections describe service use in these five CMHS-funded grant communities: Santa Barbara, California; Wai‘anae Coast, Hawai‘i; Edgecombe/Nash and Pitt Counties, North Carolina; Philadelphia, Pennsylvania; and Milwaukee, Wisconsin. Analyses were conducted on several service utilization variables, including the length of time in services, breaks or gaps in services, the number of hours of services received, and the cost of mental health services within systems of care.
Nearly all grant communities were unable to access information from other agency MIS's. For example, accessing a child welfare database for service information was denied because information regarding family history of custody, negligence, or abuse was also contained in the system. In addition, several grant communities found that after accessing the child welfare or juvenile justice information system, they were unable to find data on individual children but rather found monthly aggregated data that did not allow them to link services to individual children in the system of care.
A number of issues should be considered when interpreting these data on services and costs for several reasons. First, it is not reasonable to compare service and cost data from MIS's across systems of care. Second, because of the different foci of systems of care (i.e., target population, service interventions, level of system development), the types of services vary from grant community to grant community. Third, there are virtually no residential services reported in the MIS's in Santa Barbara, Hawai‘i, North Carolina, or Philadelphia. Furthermore, the manner in which services were recorded and the content of the MIS's used to track services varied. Information reported below should be interpreted on a grant community level using additional knowledge, documentation, and analysis from each grant community.
In this section, data from MIS's have been used to describe how long children stay in systems of care. Information on time spent in services can be used to plan for staffing systems of care and to project future resources needed to
| maintain or expand services. For example, a grant community determined from its MIS that 60 percent of the children in its system of care stayed in services for more than18 months. Using this information, the grant community evaluated the current ratio of case managers to clients and hired two additional case managers |
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For the current analysis, the length of time in mental health services was defined as the time between the first service a child received and the last service received as documented in the MIS. Because these MIS data sets only spanned 3 years, a "window" was designated so that children who were just finishing services in 1996 or beginning services in 1998 were removed from analysis. This provided a more accurate assessment of time spent in services.
Information from the systems of care indicated that average stay in services was over a year (see Figure 47). Multiple factors at each grant community determined the time spent in mental health services. For example, the treatment approach in Milwaukee shifted from diverting adolescents from residential placement to removing adolescents currently in facilities and integrating them back into their community. In order to expand service capacity while working with these youth, Milwaukee designed treatment plans and services to support youth and their families so that they could transition out of the system of care after a year. Conversely, in Philadelphia treatment focused on providing support, day treatment services, and intensive case management services for young children referred from elementary schools. The intensive case managers in this system of care were the main conduit for all child-serving agencies. Although children in Philadelphia received a high proportion of care coordination services, their direct mental health services may have ended. Extended lengths of stay were likely due to the continuing intensive case management services provided to children over time.
Time in services was coded into four categories based on 6-month intervals to examine factors that may have contributed to the length of time children spent in the system of care. For each of the five grant communities, cases were coded into the following categories: (a) children who received mental health services for less than 6 months, (b) children who received services for 6 months to 1 year, (c) children who received services for 12 to 18 months, and (d) children who received services for more than 18 months (see Figure 48).
Approximately two-thirds of the children in four of the CMHS-funded grant communities received mental health services for 12 months or longer. Across four of the five grant communities, the highest percentage of children received system-of-care services for more than 18 months. In Milwaukee, only 45 percent of the children spent more than a year in services. The lower percentage of children in Milwaukee was due to the system's goal to serve children and return them to providers in their communities within a year.
Different factors may have influenced the length of time children spend in services, including demographic variables, functioning status at intake, and history of service utilization. Previous studies indicate that functional impairment and caregiver strain can predict the restrictiveness of care, the total number of services, and the total cost of services among children using continuum-of-care services (Hodges & Wong, 1997; Angold et al., 1998). In each of the five grant communities, gender, race, age, previous history of residential treatment, total CAFAS score, and total problem scale of the CBCL were assessed to examine their relationship with time in services.
In Milwaukee, children who had been in residential treatment before they entered the system of care were more likely to have stayed in services longer than children who did not have a history of residential treatment (χ2 = 30.945, df = 3, p < .001). Children in the three-county region of North Carolina (χ2 = 22.551, df = 9, p < .007); Santa Barbara, California (χ2 = 35.885, df = 9, p < .000); and Milwaukee, Wisconsin (χ2 = 22.669, df = 9, p < .01), who were between the ages of 6 and 15 years old when they entered the system of care spent significantly more time in services than children 16 years or older. For example, in Santa Barbara, only 25 percent of youth 16 years or older received mental health services for more than 18 months. This percentage doubled for children between the ages of 6 and15 years (see Figure 49). This may be due to youth transitioning to the adult mental health system. Other demographic variables, family factors, previous service utilization history, and functional impairment were not found to be related to time in services.
Dividing mental health services into categories yields data on the patterns
of service utilization and the types and amounts of services children
receive. Classifying services into categories is also useful to assess
costs. From an evaluation perspective, information on type of service
may contribute to understanding changes in service arrays over time as
well as how service type may influence functional outcomes. Programmatically,
information on the types of services delivered provides estimates for
decisionmakers to secure resources to sustain or expand services. Analyzing
services by type may also point to gaps in the service array.
Because the definition of services varied from grant community to grant community, services were divided into two types or categories: direct and indirect services. Direct services specifically include direct contact with the child, such as individual, family, or group therapy; crisis services; medication; assessment or evaluation; home- and school-based services; residential services; and hospitalization. Indirect services are services that do not specifically include direct contact with the child, such as case management or care coordination. Grouping mental health services into direct and indirect provides more detailed information regarding the gaps or breaks in services, the dose or number of hours of services received, and the costs. In the following sections, service use indicators are reported in the aggregate and also are divided into direct and indirect services to describe more fully the service array and utilization patterns. Finally, services are broken into more detailed categories in a single grant community to assess changes in the service array over time.
Although children on average may stay in systems of care for a year or longer, there are usually " breaks" or "gaps" in services over time. A service break is defined as 30 days or longer without a direct or indirect service received
| by the child or family. Service breaks may indicate lack of continuity in care, for example, when children are transitioning from residential settings back to their community. Alternatively, service breaks may be due to family circumstances such as changes in schools, the birth of a sibling, or even a |
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Not all children had breaks in mental health services, as indicated in Table 16. The percentage of children who had a break in services varied from 12 percent in Milwaukee to 79 percent in North Carolina. As expected, in grant communities in which children stayed in the system of care longer, there were more breaks between services. For example, children in North Carolina who stayed in services an average of nearly 2 years had an average of four breaks in services, while children in Milwaukee only averaged slightly over one 30-day break. Service breaks were not calculated for Philadelphia due to overlapping services and services that were aggregated across months within their MIS system.
Breaks were categorized as direct breaks (30 days or more without a direct service) and indirect breaks (30 days without an indirect service). As expected, the frequency of direct and indirect breaks and the percentage of children with direct and indirect breaks increased across all grant communities. This was due to the removal of services when calculating breaks. For example, when all indirect services were removed from the MIS to assess direct service breaks, more gaps or time between services were created between service records. The same phenomena occurred when direct services were removed to examine indirect services.
The percentage of children who had a direct service break increased with average time spent in mental health services. In Santa Barbara, 73 percent of the children had a direct service break. This increased to 76 percent in Hawai‘i and 90 percent in North Carolina, where children spend, on average, 21 months in mental health services. Time did not appear to affect the percentage of children who had indirect service breaks, which remained at approximately 80 percent across grant communities.
Again, significantly fewer children in Milwaukee experienced overall service breaks than children in the other four grant communities (F = 140.385, df = 3/1096, p < .000). This was a function of Milwaukee's lower average time spent in services. In Milwaukee, the more time children spent in services, the more likely they were to have a service break (r = 0.301, p < .000). Because Milwaukee's MIS recorded more than outpatient mental health services, fewer gaps or breaks in services may have been the result of broader documentation of services.
Service utilization literature regarding children's mental health services suggests that there is usually a group of children who are atypically heavy service users. Using cluster analysis, Lambert et al. (1998) found that approximately 7 percent of children used services extensively and accounted for 44 percent of the system costs. This is consistent with studies of adult mental health service utilization which found that the largest proportion of services were used by a small percentage of clients (Smith & Loftus-Rueckheim, 1993). When the service
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utilization patterns of these children are included in analysis, the mean or average hours of service increase substantially. Therefore, in order to describe more "typical" service users, we report the median rather than the mean, as the median is not as sensitive to extreme values. The number of hours of service a family received may vary |
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In four of the grant communities, results indicate that children in systems of care use proportionally more indirect services such as case management. Although the definition of case management varies by locale, the principal components of case management include brokering and coordinating services; preparing, monitoring, and revising service plans; and advocating on behalf of the child and family. The results in Table 17 indicate that, in most grant communities, more hours are spent in these activities than in direct services.
It is important to track hours of service for two reasons. Program planners can clearly use the hours of services rendered to estimate future caseloads and plan resources accordingly. If services are disaggregated to provide more detail, decisionmakers can assess which services are under- or over-utilized by children and families within the system of care. Documenting hours of service can also contribute to understanding changes, or lack of change, in functional outcomes, for example, whether there is a relationship between the hours of outpatient therapy received by children and adolescents and changes in functional impairment scores.
The median cost of mental health services ranged from approximately $4,700 in North Carolina to nearly $35,000 in Milwaukee (see Table 18). Cost of mental health services is a function of the population served, time in services and the type of services children received. Children who were in services for longer times had a higher average or median cost than children who were in the system of care for a short period of time. Additionally, children who received more residential treatment services had higher costs. By dividing the median total cost by the number of months in services, the median cost per month can be calculated. Median cost per month varied from $918 in North Carolina to more than three times that amount, $3,275, in Milwaukee. As previously noted, Milwaukee's costs were higher because more system-of-care services were documented in the MIS and more hours of
| residential services were reported. Children who use many more hours have far higher costs than other children involved in the system of care. The cost of indirect services compared to direct services reflected the same pattern found in the analysis of hours |
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Tracking costs is an essential component of any system of care. The costs of specific services or programs, cost per child, and aggregate costs can be used by program planners to estimate future resource needs. For example, estimating the average cost per child per month can help project directors assess current financial capacity of the system of care and estimate needed resources to expand services. As systems of care move toward managed behavioral health care, estimates of costs will be essential for creating accurate capitated rates for different populations. Finally, data on costs and revenues can be used for sustainability. Using information from MIS's, grant communities can use cost information to leverage funds from other child-serving agencies that support the system of care. By documenting the services and the costs of services provided to children and youth in other agencies, systems of care can illustrate the need for financial support from these agencies.
To interpret service and cost data appropriately, all available information should be used. Unfortunately, providing an in-depth profile of each grant community with service and cost data is beyond the scope of this report. For illustrative purposes, a single system of care was profiled to interpret changes in the services received and costs rendered over various years of the grant cycle.
Service information from Milwaukee, Wisconsin, was chosen for several reasons:
Data from Milwaukee offered a unique understanding of how the service array and costs may change over time. The analysis of Milwaukee is illustrative of the need to interpret service and cost data with additional information to create a complete assessment of service delivery within systems of care.
One of the goals of the CMHS grant is to modify and refine the existing service array. Thus, influences of the CMHS grant should be related to changes in services over time. This section will discuss changes in service provision over 3 years of the CMHS grant cycle, 1996–98. To assess changes in the service array, the percentage of children who received each service was calculated for each year of the grant. Services rendered were divided into case management, wraparound, attendant care, residential treatment, in-school and in-home services, therapy, diagnosis and assessment, day treatment, therapeutic foster care, and medication monitoring. Figure 50 illustrates changes in the percentage of each service received by children. The percentage of children receiving in-home and in-school, therapy, day treatment, therapeutic foster care, and medication grew, while the percentage of children receiving case management and attendant care remained constant. The percentage of children receiving diagnostic evaluation services declined slightly. Wraparound services were moved into other billing categories and thus declined between 1996 and 1997.
The percentage of children who received residential treatment tripled from 1996 to 1998. This appeared, at first glance, counter-intuitive to the system-of-care approach. Further examination of cost data showed that residential treatment services were indeed absorbing a greater percentage of annual costs. Data also revealed that the target population of children served nearly tripled, from 301 in 1996 to 896 in 1998.
While greatly expanding the number of children and youth served, the focus of the system of care changed from serving children at risk of out-of-home placement to court-referred youth currently residing in residential treatment centers. In 1996, 32 percent of children were referred from courts and corrections. Referrals from corrections increased to 58 percent in 1997 and to 74 percent in 1998. The system of care in Milwaukee was financially responsible for residential treatment costs while adolescents were being extracted from residential services and brought back to the community. This resulted in an increase in the proportion of children receiving residential treatment services and the increased proportion of dollars spent on residential services. Estimates for 1999 revealed that residential services consumed a much smaller percentage of services in 1999 (see Figure 51). Information from budget reports indicated that Milwaukee was successful in leveraging funds from juvenile justice and child welfare to offset residential treatment costs while increasing the total number of youth served.
Fiscal or financial sustainability was defined as the ability of the system of care to maintain the level of funding after the expiration of the Federal grant. Using annual budget data (not found in the MIS) fiscal sustainability was evaluated by examining CMHS Federal grant dollars' contribution to system-of-care resources. Figure 52 indicates that in 1996, 88 percent of the system-of-care budget was provided by the Federal grant. This decreased dramatically to 16 percent in 1997 and only 8 percent in 1998.
During these years, dollars spent on children's mental health services increased substantially. Figure 53 reveals that as CMHS grant dollars declined, annual total dollars increased from $4.3 million in 1996 to $31 million in 1998. As stated previously, blended funding mechanisms developed with juvenile justice and child welfare have significantly increased resources, which has ensured the fiscal sustainability of the system of care. Using only MIS information to interpret changes in the service array and costs does not adequately describe the development of systems of care. Without additional information on referrals collected through the national evaluation and supplemental data from budgets, interpreting the results of MIS data would have led to inaccurate conclusions.
A key feature of the system-of-care philosophy is that services should be individualized by being matched to the specific characteristics and needs of service users. In this section, analyses were conducted to assess the link between individual characteristics and service use. In particular, the link between level of service use or restrictiveness, a key feature of service use, and measures of client demographics, symptomatology, functioning, past service use, and other family characteristics was examined.
In order to gauge between-site variation, analyses were conducted for three of the five grant communities: Santa Barbara, Hawai‘i, and Milwaukee. These three grant communities' MIS's provided enough differentiation among service types to create restrictiveness criteria. Analyses focused on service "restrictiveness" as a key measure of service use. Using MIS data, individuals were classified into one of four service categories:
Individuals were classified according to the highest level of services received. For example, a substantial proportion of individuals receiving inpatient therapy also received crisis services. This group was classified in the inpatient or residential treatment category.
As noted, the measure of service restrictiveness is based on MIS data. As a result, it is incomplete for two reasons. First, individuals in the outcome data sets who lacked MIS data were not included in the analyses. These individuals comprised roughly 15 percent of the sample, ranging from a low of 11 percent in Santa Barbara to a high of 20 percent in Milwaukee.
A second problem with an MIS-based measure of service restrictiveness is that in two grant communities (Hawai‘i and Santa Barbara) these data do not include inpatient care. As a result, information from the national evaluation's 6-month data collection was used to classify individuals into the highest restrictiveness category. That information came from the Restrictiveness of Living Environment Scale (ROLES). Thus, data used for these two grant communities combine information from two sources: respondent reports and MIS data. A key question is how closely the two sources correspond. Since Milwaukee had both sources of information, the correspondence between the two was assessed using data for that grant community. Data from the ROLES were found to underestimate substantially the proportion of individuals who have received care in inpatient or residential treatment facilities. As a result, the combined data used for Santa Barbara and Hawai‘i likely underestimated overall service restrictiveness.
Predictors of service restrictiveness included measures of demographics, symptomatology, functioning, past service use, and other family characteristics. Measures of demographics included gender, age, family income, and race and ethnicity. Because the grant communities differed dramatically in terms of race and ethnicity, the categories used varied across grant communities. For Santa Barbara and Milwaukee, respondents were classified as African-American, White, Hispanic, and "other." For Hawai‘i, individuals were classified as native Hawai‘ian or other. Respondents reported family income as falling into a series of ranges; the mid-points of those ranges were assigned. Levels of symptomatology and functioning were measured using the CBCL and the CAFAS. Other characteristics included indicators of whether the child had been sexually abused and three measures of mental illness and substance abuse among the caretaker or other family members, including (a) a history of substance abuse among family members, (b) a history of mental illness among family members, and (c) whether the caretaker or parent had been admitted to a psychiatric hospital. Finally, using ROLES data collected at the baseline interview, a series of measures of prior use of mental health services during the preceding 6 months was included. These include prior use of (a) foster care, (b) a group home, (c) inpatient or residential treatment facilities, (d) drug treatment, or (e) juvenile justice facilities.
| Results from regression analysis indicated that several individual variables were significantly correlated to the level of restrictiveness. The mean total CAFAS score was positively related to the level of restrictiveness across all three grant communities. On average, the higher a child's CAFAS score at entry into the system of care, the more likely it was that the child received more restrictive services during the first 6 |
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It is essential to continue studying service utilization and costs in the evaluation of the effectiveness of systems of care. Information technology in this area continues to develop at a rapid pace, with the possibility of cross-agency management information systems becoming more widely available in the next several years. As this technology spreads, many of the problems with existing data noted in this chapter will no longer present obstacles to obtaining accurate, real-time information for program planning and evaluation purposes. Continued investment in developing analytic strategies; identifying the most important variables for analysis; and understanding the relationships between service utilization, cost, and outcomes is creating a solid foundation for the rapid progress that can be made in the future as cross-agency management information systems evolve.
Information from management information systems regarding the services children receive and the cost of those services can provide valuable data to program staff, managers, and decisionmakers. Five CMHS grant communities provided data indicating that children, on average, stay in the system of care longer than a year, and most children stay in services for more than 18 months. Children who are 16 years of age or older stay in systems of care for significantly less time than children between the ages of 6 and 15 years. Time in services varied among grant communities and may be influenced by specific treatment strategies and the overall goals of the system of care.
While in services, the majority of children had a break in their services of 30 days or more. In general, the longer children were in services, the more likely they were to have a break in services. In most cases, children received more hours of indirect services such as case management than direct services such as therapy, school services, in-home services, assessment, or medication. The median cost per child per month varied among each grant community, ranging from $918 to $3,275. Systems of care that documented more services within an MIS had higher costs than systems whose MIS's tracked only a subset of mental health services. An analysis of MIS data from Milwaukee indicated that fiscal sustainability is related to leveraging funds from other child-serving agencies and this may alter the focus of the population that is targeted for services. On average, higher CAFAS scores were associated with an increased level of restrictiveness during the first 6 months of services across grant communities. Other factors that were positively correlated to service use were a history of incarceration and higher levels of symptomatology. Information on service use contributes to quality assurance efforts and outcome accountability, two key processes providing feedback to systems as they develop across time.
Future analyses will look at budget data in the later years of the grant to assess fiscal sustainability for more CMHS grant communities. In addition, more analyses will be conducted to evaluate the use of services among different subpopulations of children being served in systems of care. For example, are there differences in service use and cost among children diagnosed with ADHD versus children diagnosed with depression? Does the array of services differ, on average, for these groups? Finally, service and cost information from grant communities in Phase II may provide more comprehensive and developed MIS data that will be used with other information to interpret changes in outcomes for children served in systems of care.
As systems of care and their management information systems develop, program directors, providers, and legislators can more accurately understand and assess families' experiences within the system of care and use that information to provide more effective and efficient services.
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