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A state-sponsored evaluation of aging in place (AIP) as an alternative to assisted living and nursing home has been underway in Missouri. Cost, physical, and mental health assessment data reveal the cost-effectiveness and positive health measures of AIP. Findings of the first four years of the AIP evaluation of two long-term care settings in Missouri with registered nurse care coordination are compared with national data for traditional long-term care. The combined care and housing cost for any resident who received care services beyond base services of AIP and who qualified for nursing home care has never approached or exceeded the cost of nursing home care at either location. Both mental health and physical health measures indicate the health restoration and independence effectiveness of the AIP model for long-term care., (Copyright © 2011. Published by Mosby, Inc.)

The relationship between cost and quality of care in nursing homes was examined using quality indicator measures of resident outcomes. While each individual quality measure makes only small contributions to costs, when considered across the facility, quality could have a substantial financial impact on the operations of the home.

Purpose: The purpose of the study was to determine if simply providing nursing facilities with comparative quality performance information and education about quality improvement would improve clinical practices and subsequently improve resident outcomes, or if a stronger intervention, expert clinical consultation with nursing facility staff, is needed., Design and Methods: Nursing facilities (n = 113) were randomly assigned to one of three groups: workshop and feedback reports only, workshop and feedback reports with clinical consultation, and control. Minimum Data Set (MDS) Quality Indicator (QI) feedback reports were prepared and sent quarterly to each facility in intervention groups for a year. Clinical consultation by a gerontological clinical nurse specialist (GCNS) was offered to those in the second group., Results: With the exception of MDS QI 27 (little or no activity), no significant differences in resident assessment measures were detected between the groups of facilities. However, outcomes of residents in nursing homes that actually took advantage of the clinical consultation of the GCNS demonstrated trends in improvements in QIs measuring falls, behavioral symptoms, little or no activity, and pressure ulcers (overall and for low-risk residents)., Implications: Simply providing comparative performance feedback is not enough to improve resident outcomes. It appears that only those nursing homes that sought the additional intensive support of the GCNS were able to effect enough change in clinical practice to improve resident outcomes significantly.

The "Observable Indicators of Nursing Home Care Quality" instrument was developed as a new measure of nursing home care quality. The instrument is based on a theoretical model of quality nursing home care grounded in data from provider and consumer focus groups. The instrument was piloted in 10 Missouri nursing homes. Subsequent versions were tested in 109 Missouri and 11 Icelandic nursing homes. Content validity was established using experts. Concurrent and known groups validity was evaluated using Minimum Data Set quality indicators, survey citations, and a process of care measure. Interrater and test-retest reliabilities were calculated as well as coefficient alpha. The "Observable Indicators of Nursing Home Care Quality" instrument is a new measure that can be used by researchers, and potentially by regulators, consumers, or providers, to observe and score specific indicators of quality care following a 20- to 30-minute inspection of a nursing home.

Background: Determining meaningful thresholds to reinforce excellent performance and flag potential problem areas in nursing home care is critical for preparing reports for nursing homes to use in their quality improvement programs. This article builds on the work of an earlier panel of experts that set thresholds for quality indicators (QIs) derived from Minimum Data Set (MDS) assessment data. Thresholds were now set for the revised MDS 2.0 two-page quarterly form and Resource Utilization Groups III (RUGS III) quarterly instrument., Setting Thresholds: In a day-long session in October 1998, panel members individually determined lower (good) and upper (poor) threshold scores for each QI, reviewed statewide distributions of MDS QIs, and completed a follow-up Delphi of the final results., Reporting Mds Qis for Quality Improvement: The QI reports compiled longitudinal data for all residents in the nursing home during each quarter and cumulatively displayed data for five quarters for each QI. A resident roster was provided to the nursing home so that the quality improvement team could identify the specific residents who developed the problems defined by each QI during the last quarter. Quality improvement teams found the reports helpful and easy to interpret., Summary and Conclusions: As promised in an earlier report, to ensure that thresholds reflect current practice, research using experts in a panel to set thresholds was repeated as needed. As the MDS instrument or recommended calculations for the MDS QIs change, thresholds will be reestablished to ensure a fit with the instrument and data.

This exploratory study was undertaken to discover the defining dimensions of nursing home care quality from the viewpoint of consumers of nursing home care. Eleven focus groups were conducted in five Missouri communities. The seven dimensions of the consumer multidimensional model of nursing home care quality are: staff, care, family involvement, communication, environment, home, and cost. The views of consumers and families are compared with the results of a previous study of providers of nursing home services. An integrated, multidimensional theoretical model is presented for testing and evaluation. An instrument based on the model is being tested to observe and score the dimensions of nursing home care quality.

This exploratory study was undertaken to discover the defining dimensions of nursing home care quality and to propose a conceptual model to guide nursing home quality research and the development of instruments to measure nursing home care quality. Three focus groups were conducted in three central Missouri communities. A naturalistic inductive analysis of the transcribed content was completed. Two core variables (interaction and odor) and several related concepts emerged from the data. Using the core variables, related concepts, and detailed descriptions from participants, three models of nursing home care quality emerged from the analysis: (1) a model of a nursing home with good quality care; (2) a model of a nursing home with poor quality care; and (3) a multidimensional model of nursing home care quality. The seven dimensions of the multidimensional model of nursing home care quality are: central focus, interaction, milieu, environment, individualized care, staff, and safety. To pursue quality, the many dimensions must be of primary concern to nursing homes. We are testing an instrument based on the model to observe and score the dimensions of nursing home care quality.

Researchers, providers and government agencies have devoted time and resources to the development of a set of Quality Indicators derived from Minimum Data Set (MDS) data. Little effort has been directed toward verifying that Quality Indicators derived from MDS data accurately measure nursing home quality. Researchers at the University of Missouri-Columbia have independently verified the accuracy of QI derived from MDS data using four different methods; 1) structured participative observation, 2) QI Observation Scoring Instrument, 3) Independent Observable Indicators of Quality Instrument, and 4) survey citations. Our team was able to determine that QIs derived from MDS data did differentiate nursing homes of good quality from those of poorer quality.

Background: Determining meaningful thresholds to reinforce excellent performance and flag potential problem areas is critical for quality improvement reports. Without thresholds, an organization may interpret its performance as superior to others because it is "better than average" and falsely assume it does not have care problems in certain areas., Setting Thresholds: The Minimum Data Set (MDS) assessment instrument is mandated for use nationwide in all nursing homes participating in Medicaid or Medicare programs. Since 1993 a research team at the University of Missouri-Columbia has been developing and testing quality indicators (QIs) derived from MDS data as a foundation for quality improvement activities. In July 1996, a cross-section of 13 clinical care personnel from nursing homes participated on an expert panel for threshold setting for QIs derived from MDS assessment data. Panel members individually determined good and poor threshold scores for each QI, reviewed statewide distributions of MDS QIs, and, two weeks later, completed a follow-up Delphi round. Three members of the research team reviewed the results of the expert panel and set the final thresholds. With thresholds established for good and poor scores, MDS QI scores are reported to a sample of Missouri nursing homes using the thresholds., Conclusions: To ensure that thresholds reflect current practice, threshold setting with another panel of experts will be repeated as needed, but at least biannually. The report format will be revised on the basis of user input, and a statewide study testing different educational support methods for quality improvement using MDS QIs is now underway.

In 1994 12.7% of the population was 65 and over, while 10.6% were 85 and over. Expenditures for nursing homes reached $72.3 billion in 1994 (much of which is tax-supported) accounting for 8.7% of all personal health money spent. Data from the 1993 Missouri Medicaid cost reports for 403 nursing homes were reviewed to determine differences in costs per resident day (PRD) and discover which factors most influenced these differences. Mid-sized facilities with 60-120 beds reported the lowest resident-related PRD costs. PRD expenses for aides and orderlies were higher in tax-exempt facilities, which was thought to be related to their "more altruistic" mission. Investor-owned facilities showed significantly greater administrative costs PRD, which may relate to higher administrative salaries and fancier offices. The authors suggest further study that would incorporate location, occupancy rate, quality of care, case mix, and payer mix data.

Efforts to improve the quality of care and outcomes for nursing home residents are constantly of concern to state and federal regulators, nursing home providers, nursing home advocacy groups, and health policy researchers. The article describes a study that analyzed the quality indicators identified by the Health Care Financing Administration-sponsored Case Mix and Quality Demonstration Project using the Missouri nursing home Minimum Data Set database. The range of performance was considerable, and five of the indicators analyzed were risk adjusted to account for variation in resident acuity within facilities. Determining quality of care from assessment information that is routinely collected for nursing home residents has the potential to influence dramatically public policy decisions regarding reimbursement, recertification, and regulation and can play a vital role in improving resident outcomes.