Case-mix payment models now have a long history in health care.9–12 Medicaid long-term home care programs for children and youth, however, often lack an appropriate case-mix model. Case-mix adjustment for payment is not, however, completely absent in this area. State Medicaid programs, when seeking a case-mix model for children’s services, often apply some variant of models developed for older adults.

For example, Texas’s Medically Dependent Children Program provides services to those younger than 21 years of age who meet the medical necessity requirement for care in a nursing home.13 To determine the payment rates for this program, the state agency uses a modified version of the Resource Utilization Groups (RUG) model developed for case-mix classification of adult nursing home residents, who are almost exclusively frail older persons.14 Other states, such as Washington State, have developed somewhat more complex strategies for determining the need for home care on an “age-appropriate” basis.15,16 The Washington model is very elaborate, but it is also based on a model developed primarily to pay for services rendered to older adults.


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A new home care case-mix model for children and youth

Regrettably, problems arise when programs for children and youth use models based on the analyses of conditions and impairments afflicting frail older persons. Serious health challenges faced by children that might complicate care provision (eg, cystic fibrosis, hydrocephaly or microcephaly, incontinence, or being bed bound or chair bound) are not included in these “transplanted” models. Yet, such conditions have important implications for providers attempting to properly care for a child and for the health and welfare of the child.

One element of this problem comes in the lack of a uniform assessment system across home care programs for children facing special health care challenges. A variety of other settings where vulnerable populations receive care mandate standard assessments or outcome measurement.17,18 However, no standard assessment tool is now used to assess the home care needs of children. Some states have developed specific assessment tools for specific programs for children. Others simply fall back on assessment tools used with adults.

For example, Texas used the same assessment tool for determining the needs of adults and children for home care services, until a lawsuit filed by parents and advocates resulted in reform. The settlement agreement in Alberto N. vs. Hawkins demanded that the Texas Health and Human Services Commission develop an assessment tool specifically designed to assess the needs of children.19 The settlement led to the development of the Personal Care Assessment Form (PCAF) instruments, the precursors of the interRAI Pediatric Home Care Assessment (PEDS HC). The PEDS HC is a more comprehensive revision of the PCAF that was revised and finalized by the members of interRAI, an organization of >90 health professionals working in 35 countries.20

The publication of the PEDS HC instrument and users’ manual involved expanding the focus of the original PCAF instrument and modifying some items to assure consistency with common items in interRAI’s suite of instruments.21 The interRAI PEDS HC is described in greater detail in a recent commentary in Health Services Insights.22 A review copy of the PEDS HC instrument can be obtained through a query to [email protected].

The purpose of this research was to develop and present a case-mix classification model, the Pediatric Home Care/Expenditure Classification Model (P/ECM), specifically developed for use with children receiving long-term home care. The model was developed using data collected with an early version of the PEDS HC that was used in the Texas EPSDT program (PCAF 4-20). The model was then tested to determine:

  • How well the model explained variance in home care expenditures for the entire sample of home care clients.
  • How well the model explained variance in home care expenditures when tested with important sub-populations.
  • How a variety of additional variables affected the model’s explanatory power.
  • Whether the model performed consistently well when tested with a series of random 50% sub-samples.
  • How well the model predicted which clients had the lowest or highest home care expenditures.

METHODS

Data collection

In September 2008, case managers in Texas’ EPSDT program began using an early version of the interRAI PEDS HC assessment form, the PCAF 4-20. State case managers used the PCAF 4-20 to assess all children older than three years of age and younger than 21 years of age who received personal care services through Texas’s EPSDT program. Children below the age of four years were assessed with a different instrument (PCAF 0-3). Ninety-three percent of all EPSDT home care program participants during that period were children or youth older than three years of age.

All data used in this research were collected using the PCAF 4-20. The PEDS HC includes all the PCAF 4-20 items used in these analyses. All project activities reported in this research were reviewed and approved by the institutional review board at Texas A&M University.

The PCAF assessment was completed in the client’s residence, with both the client and their primary caregiver present. For six months, assessors submitted all completed assessments to a research team at Texas A&M University. The data included assessments for all new applicants for program services and all service recipients who were reassessed.

This research used the assessment data on the 2,578 children and youth from 4 to 20 years of age assessed during that six-month study period and for whom Medicaid expenditure data were available (93.4% of all PCAF 4-20 assessments). The population below four years of age was not included in these analyses because of the differences in the two assessment instruments used for these populations (PCAF 0-3 vs. PCAF 4-20). Although collected as part of an administrative reform process, these data have proven their research-grade quality in peer-reviewed publications in a number of professional journals.3,22–28