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INTRODUCTION: Nursing home (NH) residents with Alzheimer's disease or related dementias (ADRD) are at high risk for hospital transfer. We aimed to (1) describe characteristics and predictors of avoidable transfer of residents with ADRD and (2) explore how "what matters" influences the decision to transfer. METHODS: We applied an exploratory, mixed methods design using data collected as part of a Centers for Medicare and Medicaid Services demonstration project. Advanced practice registered nurses documented retrospective details about nursing home (NH)‐to‐hospital transfers (n = 3687) from 16 NHs. RESULTS: NH residents with ADRD had 1.22 times higher odds of having an avoidable NH‐to‐hospital transfer (odds ratio = 1.22; 95% confidence interval = 1.03, 1.45). Factors contributing to avoidable transfers were age, stage of ADRD, what matters to the resident and their family, changes in condition, and resources available in the NH. DISCUSSION: These findings highlight the need for enhanced specificity in the discussion and documentation of resident and family preferences and continued investments in the NH workforce. Highlights: This article reports on factors contributing to avoidable nursing home (NH)‐to‐hospital transfer of residents with Alzheimer's disease and related dementias (ADRD). The mixed methods design used in this study offers insight beyond what is possible using a single‐method design.Using data collected from a Centers for Medicare and Medicaid Services demonstration project, advanced practice registered nurses documented retrospective details about NH‐to‐hospital transfers (n = 3687) of residents.NH residents with ADRD were more likely to have an avoidable NH‐to‐hospital transfer. Factors contributing to avoidable transfers were age, stage of ADRD, what matters to the resident and their family, changes in condition, and resources available in the NH.These findings highlight the need for enhanced specificity in discussion and documentation of resident and family preferences and continued investments in the NH workforce. [ABSTRACT FROM AUTHOR]

Older adults are a heterogeneous group, and their care experience preferences are likely to be diverse and individualized. Thus, the aim of this study was to identify categories of older adults’ care experience preferences and to examine similarities and differences across different age groups.The initial categories of older adults’ care experience preferences were identified through a qualitative review of narrative text (n = 3134) in the ADVault data set. A natural language processing (NLP) algorithm was used to automatically and accurately define older adults’ care experience preference categories. Descriptive statistics were used to examine similarities and differences in care experience preference categories across different age groups.The overall average performance of NLP algorithms was relatively high (average F-score = 0.88; range: 0.77-0.96). Through a qualitative review of 350 randomly selected texts, a total of 11 categories were identified. The most frequent category was music, followed by photographs, entertainment, family/friends, religion-related, atmosphere, flower/plants, pet, bed/bedding, hobby, and other. After applying the best performing NLP algorithm to each category, older adults’ care experience preference categories were music (41.32%), followed by photographs (28.47%), entertainment (13.46%), religion-related (n = 12.69%), pet (12.22%), flower/plants (11.51%), family/friends (8.45%), atmosphere (7.75%), bed/bedding (6.12%), and hobby (5.45%). Young-old and old-old adults had similar care experience preferences with music being the most frequent category while old-old adults had photographs as the most frequent category for their care experience preference.Clinicians must understand the distinct categories of care experience preferences and incorporate them into personalized care planning. [ABSTRACT FROM AUTHOR]

Introduction: Nursing home (NH) residents with Alzheimer's disease or related dementias (ADRD) are at high risk for hospital transfer. We aimed to (1) describe characteristics and predictors of avoidable transfer of residents with ADRD and (2) explore how "what matters" influences the decision to transfer., Methods: We applied an exploratory, mixed methods design using data collected as part of a Centers for Medicare and Medicaid Services demonstration project. Advanced practice registered nurses documented retrospective details about nursing home (NH)-to-hospital transfers (n = 3687) from 16 NHs., Results: NH residents with ADRD had 1.22 times higher odds of having an avoidable NH-to-hospital transfer (odds ratio = 1.22; 95% confidence interval = 1.03, 1.45). Factors contributing to avoidable transfers were age, stage of ADRD, what matters to the resident and their family, changes in condition, and resources available in the NH., Discussion: These findings highlight the need for enhanced specificity in the discussion and documentation of resident and family preferences and continued investments in the NH workforce., Highlights: This article reports on factors contributing to avoidable nursing home (NH)-to-hospital transfer of residents with Alzheimer's disease and related dementias (ADRD). The mixed methods design used in this study offers insight beyond what is possible using a single-method design. Using data collected from a Centers for Medicare and Medicaid Services demonstration project, advanced practice registered nurses documented retrospective details about NH-to-hospital transfers (n = 3687) of residents. NH residents with ADRD were more likely to have an avoidable NH-to-hospital transfer. Factors contributing to avoidable transfers were age, stage of ADRD, what matters to the resident and their family, changes in condition, and resources available in the NH. These findings highlight the need for enhanced specificity in discussion and documentation of resident and family preferences and continued investments in the NH workforce., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Survey-driven research is a reliable method for large-scale data collection. Investigators incorporating mixed-mode survey designs report benefits for survey research including greater engagement, improved survey access, and higher response rate. Mix-mode survey designs combine 2 or more modes for data collection including web, phone, face-to-face, and mail. Types of mixed-mode survey designs include simultaneous (ie, concurrent), sequential, delayed concurrent, and adaptive. This paper describes a research protocol using mixed-mode survey designs to explore health IT (HIT) maturity and care environments reported by administrators and nurse practitioners (NPs), respectively, in US nursing homes (NHs)., Objective: The aim of this study is to describe a research protocol using mixed-mode survey designs in research using 2 survey tools to explore HIT maturity and NP care environments in US NHs., Methods: We are conducting a national survey of 1400 NH administrators and NPs. Two data sets (ie, Care Compare and IQVIA) were used to identify eligible facilities at random. The protocol incorporates 2 surveys to explore how HIT maturity (survey 1 collected by administrators) impacts care environments where NPs work (survey 2 collected by NPs). Higher HIT maturity collected by administrators indicates greater IT capabilities, use, and integration in resident care, clinical support, and administrative activities. The NP care environment survey measures relationships, independent practice, resource availability, and visibility. The research team conducted 3 iterative focus groups, including 14 clinicians (NP and NH experts) and recruiters from 2 national survey teams experienced with these populations to achieve consensus on which mixed-mode designs to use. During focus groups we identified the pros and cons of using mixed-mode designs in these settings. We determined that 2 mixed-mode designs with regular follow-up calls (Delayed Concurrent Mode and Sequential Mode) is effective for recruiting NH administrators while a concurrent mixed-mode design is best to recruit NPs., Results: Participant recruitment for the project began in June 2023. As of April 22, 2024, a total of 98 HIT maturity surveys and 81 NP surveys have been returned. Recruitment of NH administrators and NPs is anticipated through July 2025. About 71% of the HIT maturity surveys have been submitted using the electronic link and 23% were submitted after a QR code was sent to the administrator. Approximately 95% of the NP surveys were returned with electronic survey links., Conclusions: Pros of mixed-mode designs for NH research identified by the team were that delayed concurrent, concurrent, and sequential mixed-mode methods of delivering surveys to potential participants save on recruitment time compared to single mode delivery methods. One disadvantage of single-mode strategies is decreased versatility and adaptability to different organizational capabilities (eg, access to email and firewalls), which could reduce response rates., International Registered Report Identifier (irrid): DERR1-10.2196/56170., (©Gregory L Alexander, Lusine Poghosyan, Yihong Zhao, Mollie Hobensack, Sergey Kisselev, Allison A Norful, John McHugh, Keely Wise, M Brooke Schrimpf, Ann Kolanowski, Tamanna Bhatia, Sabrina Tasnova. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 29.08.2024.)