A Case-Mix System for Children and Youth With Developmental Disabilities.

Limited funding across health and social service programs presents a challenge regarding how to best match resources to the needs of the population. There is increasing consensus that differences in individual characteristics and care needs should be reflected in variations in service costs, which has led to the development of case-mix systems. The present study sought to develop a new approach to allocate resources among children and youth with intellectual and developmental disabilities (IDD) as part of a system-wide Medicaid payment reform initiative in Arkansas. To develop the system, assessment data collected using the interRAI Child and Youth Mental Health-Developmental Disability instrument was matched to paid service claims. The sample consisted of 346 children and youth with developmental disabilities in the home setting. Using automatic interactions detection, individuals were sorted into unique, clinically relevant groups (ie, based on similar resource use) and a standardized relative measure of the cost of services provided to each group was calculated. The resulting case-mix system has 8 distinct, final groups and explains 30% of the variance in per diem costs. Our analyses indicate that this case-mix classification system could provide the foundation for a future prospective payment system that is centered around stability and equitability in the allocation of limited resources within this vulnerable population.

A Case-Mix System for Adults with Developmental Disabilities.

Effective management of publicly funded services matches the provision of needed services with cost-efficient payment methods. Payment systems that recognize differences in care needs (eg, case-mix systems) allow for greater proportions of available funds to be directed to providers supporting individuals with more needs. We describe a new way to allocate funds spent on adults with intellectual disabilities (ID) as part of a system-wide Medicaid payment reform initiative in Arkansas. Analyses were based on population-level data for persons living at home, collected using the interRAI ID assessment system, which were linked to paid service claims. We used automatic interactions detection to sort individuals into unique groups and provide a standardized relative measure of the cost of the services provided to each group. The final case-mix system has 33 distinct final groups and explains 26% of the variance in costs, which is similar to other systems in health and social services sectors. The results indicate that this system could be the foundation for a future case-mix approach to reimbursement and stand the test of "fairness" when examined by stakeholders, including parents, advocates, providers, and political entities.

The interRAI Suite of Mental Health Assessment Instruments: An Integrated System for the Continuum of Care.

The lives of persons living with mental illness are affected by psychological, biological, social, economic, and environmental factors over the life course. It is therefore unlikely that simple preventive strategies, clinical treatments, therapeutic interventions, or policy options will succeed as singular solutions for the challenges of mental illness. Persons living with mental illness receive services and supports in multiple settings across the health care continuum that are often fragmented, uncoordinated, and inadequately responsive. Appropriate assessment is an important tool that health systems must deploy to respond to the strengths, preferences, and needs of persons with mental illness. However, standard approaches are often focused on measurement of psychiatric symptoms without taking a broader perspective to address issues like growth, development, and aging; physical health and disability; social relationships; economic resources; housing; substance use; involvement with criminal justice; stigma; and recovery. Using conglomerations of instruments to cover more domains is impractical, inconsistent, and incomplete while posing considerable assessment burden. interRAI mental health instruments were developed by a network of over 100 researchers, clinicians, and policy experts from over 35 nations. This includes assessment systems for adults in inpatient psychiatry, community mental health, emergency departments, mobile crisis teams, and long-term care settings, as well as a screening system for police officers. A similar set of instruments is available for child/youth mental health. The instruments form an integrated mental health information system because they share a common assessment language, conceptual basis, clinical emphasis, data collection approach, data elements, and care planning protocols. The key applications of these instruments include care planning, outcome measurement, quality improvement, and resource allocation. The composition of these instruments and psychometric properties are reviewed, and examples related to homeless are used to illustrate the various applications of these assessment systems.

Hearing the Voice of the Resident in Long-Term Care Facilities-An Internationally Based Approach to Assessing Quality of Life.

OBJECTIVES: interRAI launched this study to introduce a set of standardized self-report measures through which residents of long-term care facilities (LTCFs) could describe their quality of life and services. This article reports on the international development effort, describing measures relative to privacy, food, security, comfort, autonomy, respect, staff responsiveness, relationships with staff, friendships, and activities. First, we evaluated these items individually and then combined them in summary scales. Second, we examined how the summary scales related to whether the residents did or did not say that the LTCFs in which they lived felt like home. DESIGN: Cross-sectional self-report surveys by residents of LTCFs regarding their quality of life and services. SETTING/PARTICIPANTS: Resident self-report data came from 16,017 individuals who resided in 355 LTCFs. Of this total, 7113 were from the Flanders region of Belgium, 5143 residents were from Canada, and 3358 residents were from the eastern and mid-western United States. Smaller data sets were collected from facilities in Australia (20), the Czech Republic (72), Estonia (103), Poland (118), and South Africa (87). MEASUREMENTS: The interRAI Self-Report Quality of Life Survey for LTCFs was used to assess residents' quality of life and services. It includes 49 items. Each area of inquiry (eg, autonomy) is represented by multiple items; the item sets have been designed to elicit resident responses that could range from highly positive to highly negative. Each item has a 5-item response set that ranges from "never" to "always." RESULTS: Typically, we scored individual items scored based on the 2 most positive categories: "sometimes" and "always." When these 2 categories were aggregated, among the more positive items were: being alone when wished (83%); decide what clothes to wear (85%); get needed services (87%); and treated with dignity by staff (88%). Areas with a less positive response included: staff knows resident's life story (30%); resident has enjoyable things to do on weekends (32%); resident has people to do things with (33%); and resident has friendly conversation with staff (45%). We identified 5 reliable scales; these scales were positively associated with the resident statement that the LTCF felt like home. Finally, international score standards were established for the items and scales. CONCLUSIONS: This study establishes a set of standardized, self-report items and scales with which to assess the quality of life and services for residents in LTCFs. The study also demonstrates that these scales are significantly related to resident perception of the home-like quality of the facilities.

Beyond Section Q: prioritizing nursing home residents for transition to the community.

BACKGROUND: Nursing Facility Transition (NFT) programs often rely on self-reported preference for discharge to the community, as indicated in the Minimum Data Set (MDS) Section Q, to identify program participants. We examined other characteristics of long-stay residents discharged from nursing facilities by NFT programs, to "flag" similar individuals for outreach in the Money Follows the Person (MFP) initiative. METHODS: Three states identified persons who transitioned between 2001 and 2009 with the assistance of a NFT or MFP program. These were used to locate each participant's MDS 2.0 assessment just prior to discharge and to create a control sample of non-transitioned residents. Logistic regression and Automatic Interactions Detection were used to compare the two groups. RESULTS: Although there was considerable variation across states in transitionees' characteristics, a derived "Q + Index" was highly effective in identifying persons similar to those that states had previously transitioned. The Index displays high sensitivity (86.5%) and specificity (78.7%) and identifies 28.3% of all long-stayers for follow-up. The Index can be cross-walked to MDS 3.0 items. CONCLUSIONS: The Q + Index, applied to MDS 3.0 assessments, can identify a population closely resembling persons who have transitioned in the past. Given the US Government's mandate that states consider all transition requests and the limited staffing available at local contact agencies to address such referrals, this algorithm can also be used to prioritize among persons seeking assistance from local contact agencies and MFP providers.

Hard times: the effects of financial strain on home care services use and participant outcomes in Michigan.

PURPOSE: When government funding for long-term care is reduced, participant outcomes may be adversely affected. We investigated the effect of program resources on individuals enrolled in the Michigan Home- and Community-Based Services (HCBS) waiver program for elderly and disabled adults. DESIGN AND METHODS: Using dates of major policy and budget changes, we defined 4 distinct time periods between October 2001 and December 2005. Minimum Data Set for Home Care assessment records for HCBS participants (n = 112,182) were used to examine temporal trends in formal care hours and 6 outcomes: emergency room (ER) use, hospitalization, caregiver burden, death, nursing facility (NF) use, and permanent NF placement. Controlling for demographics, functional status, and cognitive status, adjusted odds of outcomes were obtained using discrete-time survival analysis. RESULTS: As resources diminished, mean formal care hours decreased, declining most for persons with moderate functional or cognitive impairment, for up to an approximately 30% decrease. In the most financially restricted period, 3 adverse outcomes increased relative to baseline: hospitalization (odds ratio [OR] = 1.10; 95% confidence interval [CI] = 1.03-1.18), ER use (OR = 1.13; 95% CI = 1.03-1.24), and permanent NF placement (OR = 1.20; 95% CI = 1.00-1.42). IMPLICATIONS: Reductions in resources for home care were associated with increased probability of adverse outcomes. Cutting funds to home care programs can increase utilization of other more costly services, thus offsetting potential health care savings. Policymakers must consider all ways in which budget reductions and policy changes can affect participants.

Predicting nursing facility transition candidates using AID: a case study.

PURPOSE: Although the nursing facility transition literature is growing, little research has analyzed the characteristics of individuals so assisted or compared participants to those who remain institutionalized. This article describes an analytic method that researchers can apply to address these knowledge gaps, using the Arkansas Passages nursing facility transition program as a case study. DESIGN AND METHODS: This study employed Arkansas Minimum Data Set 2.0 data for 111 transitioned individuals, a derivation sample of 1,000 other residents, and a validation sample of all residents from the transitioned individuals' nursing facilities. Tree classification techniques identified distinct groups of transitioned and nontransitioned residents. RESULTS: Nearly two thirds of transitionees were part of a group comprising only 1.5% of all Arkansas nursing facility residents. Five characteristics identified this group: age, day of stay (i.e., current day of stay at the time of the assessment), having hemiplegia/paraplegia, cognitive impairment level, and classification into one of eight Resource Utilization Groups (RUG-III) case-mix groups associated with the least nursing staff time. Another group containing 92% of the transitionees comprised 22% of all residents. Two characteristics identified this group: being younger than age 65 or being in the eight low-resource RUG-III groups. IMPLICATIONS: Given that the majority of individuals assisted by this pilot represent a small and unusual nursing facility subpopulation, policy makers may wish to exercise caution in utilizing these data to forecast future transition populations, costs, or outcomes. Replicating this analysis using additional states' data could increase understanding about the characteristics of those assisted across transition programs and could help construct a more robust definition of what constitutes a transition success.

Prospects and pitfalls: use of the RAI-HC assessment by the Department of Veterans Affairs for home care clients.

PURPOSE: The U.S. Department of Veterans Affairs has adopted two functional assessment systems that guide care planning: one for nursing home residents (the Resident Assessment Instrument [RAI]) and a compatible one for home care clients (RAI-HC). The purpose of this article is to describe the RAI-HC (often referred to as the Minimum Data Set-Home Care or MDS-HC) and its uses and offer lessons learned from implementation experiences in other settings. DESIGN AND METHODS: We reviewed implementation challenges associated both with the RAI and the RAI-HC in the United States, Canada, and other adopter countries, and drew on these to suggest lessons for the Department of Veterans Affairs as well as other entities implementing the RAI-HC. RESULTS: Beyond its clinical utility, there are a number of evidence-based uses for the assessment system. The resident-level data can be aggregated and analyzed, and scales identify clinical conditions and risk for various types of negative outcomes. In addition, the data can be used for other programmatic and research purposes, such as determining eligibility, setting payment rates for contract care, and evaluating clinical interventions. At the same time, there are a number of implementation challenges the Department of Veterans Affairs and other organizations may face. IMPLICATIONS: Policy makers and program managers in any setting, including state long-term-care programs, who wish to implement an assessment system must anticipate and address a variety of implementation problems with a clear and consistent message from key leadership, adequate training and clinical support for assessors, and appropriate planning and resources for data systems.

Insomnia and hypnotic use, recorded in the minimum data set, as predictors of falls and hip fractures in Michigan nursing homes.

OBJECTIVES: To examine the relationship between insomnia, hypnotic use, falls, and hip fractures in older people. DESIGN: Secondary analysis of a large, longitudinal, assessment database. SETTING: Four hundred thirty-seven nursing homes in Michigan. PARTICIPANTS: Residents aged 65 and older in 2001 with a baseline Minimum Data Set assessment and a follow-up 150 to 210 days later. MEASUREMENTS: Logistic regression modeled any follow-up report of fall or hip fracture. Predictors were baseline reports of insomnia (previous month) and use of hypnotics (previous week). Potential confounds taken into account included standard measures of functional status, cognitive status, intensity of resource utilization, proximity to death, illness burden, number of medications, emergency room visits, nursing home new admission, age, and sex. RESULTS: In 34,163 nursing home residents (76% women, mean age+/-standard deviation 84+/-8), hypnotic use did not predict falls (adjusted odds ratio (AOR)=1.13, 95% confidence interval (CI)=0.98, 1.30). In contrast, insomnia did predict future falls (AOR=1.52, 95% CI=1.38, 1.66). Untreated insomnia (AOR=1.55, 95% CI=1.41, 1.71) and hypnotic-treated (unresponsive) insomnia (AOR=1.32, 95% CI=1.02, 1.70) predicted more falls than did the absence of insomnia. After adjustment for confounding variables, insomnia and hypnotic use were not associated with subsequent hip fracture. CONCLUSION: In elderly nursing home residents, insomnia, but not hypnotic use, is associated with a greater risk of subsequent falls. Future studies will need to confirm these findings and determine whether appropriate hypnotic use can protect against future falls.