PROJECT SUMMARY / ABSTRACT
Close to two-thirds of the over 1.7 million U.S nursing home (NH) residents have a cognitive impairment such
as Alzheimer’s disease or a related dementia (ADRD), and are at high risk of hospital transfer. Reducing
avoidable hospitalizations for NH residents is a national priority due to the negative effects on resident health
and high Medicare and Medicaid costs. NH-to-hospital transfers result in > $2.6 billion in expenditures
annually, harm to residents from physical and emotional relocation stress, and is avoidable in as many as 60%
of cases. Avoidable NH-to-hospital transfers include transfers for conditions that can be safely and effectively
managed in the NH. Early illness recognition and treatment could prevent the need for hospital transfer
altogether, ultimately reducing morbidity and mortality in residents with ADRD while controlling costs. NH-to-
hospital transfer decision-making is complex and relies on timely transmission of information among the
interdisciplinary team. Unfortunately, many NHs rely on antiquated communication methods (e.g., phone, fax)
rather than leveraging modern, convenient, and low-cost options, like text messaging (TM), which could
improve health information sharing. Complicating the decision-making process about residents with ADRD is
the progressive loss of language impacting the individual’s ability to communicate. We expect that
communication among health care team members differs for NH residents with and without ADRD. Our dataset
provides an ideal and novel opportunity to apply natural language processing and social network analysis to
TMs shared among an interdisciplinary team about NH resident transfer. We propose to examine the content
of TM using the age-friendly health system 4M framework, which includes four evidence-based elements of
high-quality care (what Matters, Medications, Mentation, and Mobility). The 4M framework addresses the core
issues that should drive all decision making in the care of older adults and is a way of systematically rethinking
care in ways that improve patient health and satisfaction. A critical need exists to examine how convenient,
low-cost communication options like TM can reduce avoidable NH-to-hospital transfers of residents with
ADRD. Our aims are to: 1) Identify documentation of the 4Ms in health information shared by the
interdisciplinary team through electronic TM two weeks prior to NH-to-hospital transfer of residents with ADRD;
2) Estimate the effects of the 4Ms found in TMs on avoidable NH-to-hospital transfers; and 3) Compare
communication patterns of interdisciplinary teams making transfer decisions about residents with and without
ADRD. A potential impact of this work is to decrease avoidable hospitalizations, and ultimately, morbidity and
mortality in NH residents with ADRD by identifying evidence-based elements of high-quality care for older
adults (4Ms). Another potential impact is the development of a structured language allowing for timely and
seamless portability of information across the complete spectrum of care, optimizing the health of individuals
and populations.
