Objectives: The National Academies of Sciences, Engineering, and Medicine (NASEM) Nursing Home Quality report recommends that states “develop and operate state-based…technical assistance programs…to help nursing homes…improve care and…operations.” The Quality Improvement Program for Missouri (QIPMO) is one such program. This longitudinal evaluation examined and compared differences in quality measures (QMs) and nursing home (NH) characteristics based on intensity of QIPMO services used.

Design: A descriptive study compared key QMs of clinical care, facility-level characteristics, and differing QIPMO service intensity use. QIPMO services include on-site clinical consultation by expert nurses; evidence-based practice information; teaching NHs use of quality improvement (QI) methods; and guiding their use of Centers for Medicare and Medicaid Services (CMS)-prepared QM comparative feedback reports to improve care.

Setting and Participants: All Missouri NHs (n = 510) have access to QIPMO services at no charge. All used some level of service during the study, 2020–2022.
Methods QM data were drawn from CMS’s publicly available website (Refresh April 2023) and NH characteristics data from other public websites. Service intensity was calculated using data from facility contacts (on-site visits, phone calls, texts, emails, webinars). NHs were divided into quartiles based on service intensity.

Results:All groups had different beginning QM scores and improved ending scores. Group 2, moderate resource intensity use, started with “worse” overall score and improved to best performing by the end. Group 4, most resource intensity use, improved least but required highest service intensity.

Conclusions and Implications: This longitudinal evaluation of QIPMO, a statewide QI technical assistance and support program, provides evidence of programmatic stimulation of statewide NH quality improvements. It provides insight into intensity of services needed to help facilities improve. Other states should consider QIPMO success and develop their own programs, as recommended by the NASEM report so their NHs can embrace QI and “initiate fundamental change” for better care for our nation’s older adults.

Rantz, M.J., Martin, C., Zaniletti, I., Mueller, J., Galambos, C., Vogelsmeier, A., Popejoy, L., Thompson, R.A., & Crecelius, C. (2024). Longitudinal evaluation of a statewide Quality Improvement Program for Nursing Homes. Journal of the American Medical Directors Association. Published online January 31, 2024.

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Objectives: A comprehensive multilevel intervention was tested to build organizational capacity to create and sustain improvement in quality of care and subsequently improve resident outcomes in nursing homes in need of improvement.

Design/Setting/Participants: Intervention facilities (N ¼ 29) received a 2-year multilevel intervention with monthly on-site consultation from expert nurses with graduate education in gerontological nursing. Attention control facilities (N ¼ 29) that also needed to improve resident outcomes received monthly information about aging and physical assessment of elders.

Intervention: The authors conducted a randomized clinical trial of nursing homes in need of improving resident outcomes of bladder and bowel incontinence, weight loss, pressure ulcers, and decline in activities of daily living. It was hypothesized that following the intervention, experimental facilities would have higher quality of care, better resident outcomes, more organizational attributes of improved working conditions than control facilities, higher staff retention, similar staffing and staff mix, and lower total and direct care costs.

Rantz, M.J., Zwygart-Stauffacher, M., Hicks, L., Mehr, D., Flesner, M., Petroski, G.F., Madsen, R.W., & Scott-Cawiezell, J. (2012). Randomized multilevel intervention to improve outcomes of residents in nursing homes in need of improvementJournal of the American Medical Directors Association, 13(1), 60-68.

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There is growing political pressure for nursing homes to implement the electronic medical record (EMR) but there is little evidence of its impact on resident care. The purpose of this study was to test the unique and combined contributions of EMR at the bedside and on-site clinical consultation by gerontological expert nurses on cost, staffing, and quality of care in nursing homes. Eighteen nursing facilities in 3 states participated in a 4-group 24-month comparison: Group 1 implemented bedside EMR, used nurse consultation; Group 2 implemented bedside EMR only; Group 3 used nurse consultation only; Group 4 neither. Intervention sites (Groups 1 and 2) received substantial, partial financial support from CMS to implement EMR. Costs and staffing were measured from Medicaid cost reports, and staff retention from primary data collection; resident outcomes were measured by MDS-based quality indicators and quality measures.

Rantz, M.J., Hicks, L., Petroski, G.F., Madsen, R.W., Alexander, G., Galambos, C., Conn, V., Scott-Cawiezell, J., Zwygart-Stauffacher, M., & Greenwald, L. (2010). Cost, staffing, and quality impact of bedside electronic medical record (EMR) in nursing homes. Journal of the American Medical Directors Association, 11(7), 485-493.

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There is growing political pressure for nursing homes to implement the electronic medical record (EMR) but there is little evidence of its impact on resident care. The purpose of this study was to test the unique and combined contributions of EMR at the bedside and on-site clinical consultation by gerontological expert nurses on cost, staffing, and quality of care in nursing homes. Eighteen nursing facilities in 3 states participated in a 4-group 24-month comparison: Group 1 implemented bedside EMR, used nurse consultation; Group 2 implemented bedside EMR only; Group 3 used nurse consultation only; Group 4 neither. Intervention sites (Groups 1 and 2) received substantial, partial financial support from CMS to implement EMR. Costs and staffing were measured from Medicaid cost reports, and staff retention from primary data collection; resident outcomes were measured by MDS-based quality indicators and quality measures.

Rantz, M.J., Hicks, L., Petroski, G.F., Madsen, R.W., Alexander, G., Galambos, C., Conn, V., Scott-Cawiezell, J., Zwygart-Stauffacher, M., & Greenwald, L. (2010). Cost, staffing, and quality impact of bedside electronic medical record (EMR) in nursing homesJournal of the American Medical Directors Association, 11(7), 485-493.

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The article focuses on nursing homes costs and quality of care outcomes. Consumers are demanding mechanisms that will allow them to evaluate the quality of care provided in nursing homes. Policymakers, who are responsible for oversight of the public funding of more than 70% of patient days in nursing home care and approximately two-thirds of expenditures on nursing home care, want assurance that monies are contributing to better quality care. A number of studies attempted to assess the factors contributing to variations in the costs of care in nursing homes. An underlying assumption in these studies was the existence of a direct relationship between costs and the efficient provision of services appropriate to patient needs.

Hicks, L.L., Rantz, M.J., Petroski, G.F., & Mukamel, D.B. (2004). Nursing home costs and quality of care outcomesNursing Economics, 224, 178-192.

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The purpose of this study was to describe the processes of care, organizational attributes, cost of care, staffing level, and staff mix in a sample of Missouri homes with good, average, and poor resident outcomes. In facilities with good resident outcomes, there are basics of care and processes surrounding each that staff consistently do: helping residents with ambulation, nutrition and hydration, and toileting and bowel regularity; preventing skin breakdown; and managing pain. For nursing homes to achieve good resident outcomes, they must have leadership that is willing to embrace quality improvement and group process and see that the basics of care delivery are done for residents. Good quality care may not cost more than poor quality care; there is some evidence that good quality care may cost less. Small facilities of 60 beds were more likely to have good resident outcomes. Strategies have to be considered so larger facilities can be organized into smaller clusters of units that could function as small nursing homes within the larger whole.

Rantz, M.J., Hicks, L., Grando, V.T., Petroski, G.F., Madsen, R.W., Mehr, D.R., Conn, V., Zwygart-Stauffacher, M., Scott, J., Flesner, M., Bostick, J., Porter, R., & Maas, M. (2004). Nursing home quality, cost, staffing, and staff-mixThe Gerontologist, 44(1), 24-38.

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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.

Rantz, M.J., Popejoy, L, Petroski, G.F., Madsen, R.W., Mehr, D.R., Zwygart-Stauffacher, M., Hicks, L.L., Grando, V., Wipke-Tevis, D.D., Bostick, J., Porter, R., Conn, V.S., & Maas, M. (2001). Randomized clinical trial of a quality improvement intervention in nursing homesThe Gerontologist, 41(4), 525-538.

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It is becoming increasingly common for nursing facilities to use Quality Indicators (Ql) derived from Minimum Data Set (MDS) data for quality improvement initiatives within their facilities. It is not known how much support facilities need to effectively review Ql reports, investigate problems areas, and implement practice changes to improve care. In Missouri, the University of Missouri-Columbia MDS and Nursing Home Quality Research Team has undertaken a Quality Improvement Intervention Study using a gerontological clinical nurse specialist (GCNS) to support quality improvement activities in nursing homes. Nursing facilities have responded positively to the availability of a GCNS to assist them in improving nursing facility care quality.

Popejoy, L.L., Rantz, M.J., Conn, V., Wipke-Tevis, D., Grando, V., & Porter, R. (2000). Improving quality of care in nursing facilities: The gerontological clinical nurse specialist as research nurse consultant. Journal of Gerontological Nursing, 26(4), 6-13.

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An important area of inquiry in quality measurement when using quality indicators (QIs) lies in determining what thresholds indicate good and poor resident outcomes. In July 1996, a cross-section of 13 clinical care personnel from nursing homes participated on an expert panel for threshold setting of Qls derived from Minimum Data Set (MDS) assessment data. Panel members met as a group for a day, individually determined good and poor threshold scores for each QI, reviewed statewide distributions of MDS Qls, and completed a follow-up Delphi round of the final results. Reports of MDS scores that are sent to a group of nursing homes in Missouri now include thresholds established for good and poor scores so the facilities can easily see where they are performing well and where they need to concentrate quality improvement efforts. This article describes the efforts made to develop and disseminate the thresholds for MDS scores.

Rantz, M. J., Petroski, G.F., Madsen, R.W., Scott, J., Mehr, D., Popejoy, L., Hicks, L., Porter, R., Zwygart-Stauffacher, M., & Grando, V. (1997). Setting thresholds for MDS quality indicators for nursing home quality improvement reportsJoint Commission Journal on Quality Improvement, 23(11), 602-611.

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An important area of inquiry in quality measurement when using quality indicators (QIs) lies in determining what thresholds indicate good and poor resident outcomes. In July 1996, a cross-section of 13 clinical care personnel from nursing homes participated on an expert panel for threshold setting of Qls derived from Minimum Data Set (MDS) assessment data. Panel members met as a group for a day, individually determined good and poor threshold scores for each QI, reviewed statewide distributions of MDS Qls, and completed a follow-up Delphi round of the final results. Reports of MDS scores that are sent to a group of nursing homes in Missouri now include thresholds established for good and poor scores so the facilities can easily see where they are performing well and where they need to concentrate quality improvement efforts. This article describes the efforts made to develop and disseminate the thresholds for MDS scores.

Rantz, M. J., Petroski, G.F., Madsen, R.W., Scott, J., Mehr, D., Popejoy, L., Hicks, L., Porter, R., Zwygart-Stauffacher, M., & Grando, V. (1997). Setting thresholds for MDS quality indicators for nursing home quality improvement reportsJoint Commission Journal on Quality Improvement, 23(11), 602-611.

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