Is Telephone Screening Feasible? Accuracy and Cost-Effectiveness of Identifying People Medically Eligible for Home- and Community-Based Services

Proxy Survey Cost Indicators in Interviewer-Administered Surveys: Are they Actually Correlated with Costs?

Survey design decisions are-by their very nature-tradeoffs between costs and errors. However, measuring costs is often difficult. Furthermore, surveys are growing more complex. Many surveys require that cost information be available to make decisions during data collection. These complexities create new challenges for monitoring and understanding survey costs. Often, survey cost information lags behind reporting of paradata. Furthermore, in some situations, the measurement of costs at the case level is difficult. Given the time lag in reporting cost information and the difficulty of assigning costs directly to cases, survey designers and managers have frequently turned to proxy indicators for cost. These proxy measures are often based upon level-of-effort paradata. An example of such a proxy cost indicator is the number of attempts per interview. Unfortunately, little is known about how accurately these proxy indicators actually mirror the true costs of the survey. In this article, we examine a set of these proxy indicators across several surveys with different designs, including different modes of interview. We examine the strength of correlation between these indicators and two different measures of costs-the total project cost and total interviewer hours. This article provides some initial evidence about the quality of these proxies as surrogates for the true costs using data from several different surveys with interviewer-administered modes (telephone, face to face) across three organizations (University of Michigan's Survey Research Center, Westat, US Census Bureau). We find that some indicators (total attempts, total contacts, total completes, sample size) are correlated (average correlation ∼0.60) with total costs across several surveys. These same indicators are strongly correlated (average correlation ∼0.82) with total interviewer hours. For survey components, three indicators (total attempts, sample size, and total miles) are strongly correlated with both total costs (average correlation ∼0.77) and with total interviewer hours (average correlation ∼0.86).

Assisted living pilot program: background, methods, and facility characteristics

Objectives. The Department of Veterans Affairs (VA) funded assisted living (AL), adult family home (AFH), and residential care for the first time in the Assisted Living Pilot Program (ALPP). This article describes the background and methods of the ALPP evaluation and the characteristics and experiences of the facilities. Method. Facility data were collected from the contracting/inspection process and a survey of ALPP facilities and those contacted but not participating in ALPP. Results. Data on 131 participating facilities are presented: 41 AFHs, 47 assisted living facilities (ALFs), and 43 residential care facilities (RCFs). The average facility had 33 beds (about one quarter Medicaid beds), for-profit ownership, and private rooms for ALPP residents, and about half had private baths. About two thirds of ALPP AFH providers spoke a primary language other than English. Discussion. Findings indicate that a wide range of community facilities were willing to provide care to residents with heterogeneous needs on VA funding.

Characteristics of residents and providers in the assisted living pilot program

PURPOSE

The number of residents in assisted living has rapidly increased, although these facilities still primarily serve people who can pay out of pocket. The U.S. Department of Veterans Affairs was authorized to provide this level of care for the first time in the Assisted Living Pilot Program (ALPP). We describe the residents and providers, comparing them across three facility types and other populations, to assess the characteristics and feasibility of this new approach.

DESIGN AND METHODS

We assessed ALPP residents and providers across seven Veterans Affairs Medical Centers. We obtained information from medical records, assessment tools, and a provider survey.

RESULTS

We report here on 743 residents placed from 2002 to 2004. The Department of Veterans Affairs contracted with 58 adult family homes, 56 assisted living facilities, and 46 residential care facilities. The average ALPP resident was a 70-year-old unmarried White man referred from an inpatient hospital and living in a private residence prior to placement. Adult family homes enrolled residents requiring greater levels of assistance with activities of daily living than other facility types. Assisted living facilities were less likely than adult family homes to admit residents with functional disabilities and less likely than either adult family homes or adult residential care facilities to admit residents with certain care needs.

IMPLICATIONS

ALPP placed residents with a wide range of characteristics in community facilities that varied widely in size and services. This information can help determine the role of this type of care in and outside of the Department of Veterans Affairs.

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.