A Survey of Technology Abandonment in US Nursing Homes.

OBJECTIVE: Adoption of health information technology (HIT) in nursing homes (NHs) improves quality of care. Although there is a robust body of research on HIT adoption, the closely related process of technology abandonment is not well understood. As NHs grow more reliant on HIT, problems of technology abandonment, defined as failure to scale up, spread, and sustain HIT need to be studied. Our objective is to describe HIT abandonment and its associations with organizational characteristics among a national sample of US NHs. DESIGN: Longitudinal, retrospective analysis of data from 2 sources: HIT Maturity Survey and Staging model and public data from the Care Compare database. SETTING AND PARTICIPANTS: Random sample of NHs (n = 299) representing each US state that completed the HIT maturity survey in 2 consecutive years: year 1 (Y1) was June 2019-August 2020 and year 2 (Y2) was June 2020-August 2021. METHODS: The primary dependent variable was technology abandonment, operationalized by using total HIT maturity score, HIT maturity stage, and subscale scores within each dimension/domain. Independent variables were NH organizational characteristics including bed size, type of ownership, urbanicity, Centers for Medicare & Medicaid Services Five-Star Overall Rating and Staffing Rating. RESULTS: Over the 2-year period, HIT abandonment occurred in 28% (n = 85) of NHs compared with 44% (n = 133) that experienced growth in HIT systems. HIT capabilities in resident care were abandoned most frequently. Using multivariable multinomial logistic regression, we found that large NHs (bed size greater than 120) were more likely to experience technology abandonment in administrative activities. CONCLUSIONS AND IMPLICATIONS: Technology abandonment can increase strain on scarce resources and may impact administrators' ability to oversee clinical operations, especially in large NHs. This study contributes to the limited understanding of technology abandonment and can serve as a building block for others working to ensure limited resources are used effectively to improve care for NH residents.

Examining the Use of Text Messages Among Multidisciplinary Care Teams to Reduce Avoidable Hospitalization of Nursing Home Residents with Dementia: Protocol for a Secondary Analysis.

BACKGROUND: Reducing avoidable nursing home (NH)-to-hospital transfers of residents with Alzheimer disease or a related dementia (ADRD) has become a national priority due to the physical and emotional toll it places on residents and the high costs to Medicare and Medicaid. Technologies supporting the use of clinical text messages (TMs) could improve communication among health care team members and have considerable impact on reducing avoidable NH-to-hospital transfers. Although text messaging is a widely accepted mechanism of communication, clinical models of care using TMs are sparsely reported in the literature, especially in NHs. Protocols for assessing technologies that integrate TMs into care delivery models would be beneficial for end users of these systems. Without evidence to support clinical models of care using TMs, users are left to design their own methods and protocols for their use, which can create wide variability and potentially increase disparities in resident outcomes. OBJECTIVE: Our aim is to describe the protocol of a study designed to understand how members of the multidisciplinary team communicate using TMs and how salient and timely communication can be used to avert poor outcomes for NH residents with ADRD, including hospitalization. METHODS: This project is a secondary analysis of data collected from a Centers for Medicare & Medicaid Services (CMS)-funded demonstration project designed to reduce avoidable hospitalizations for long-stay NH residents. We will use two data sources: (1) TMs exchanged among the multidisciplinary team across the 7-year CMS study period (August 2013-September 2020) and (2) an adapted acute care transfer tool completed by advanced practice registered nurses to document retrospective details about NH-to-hospital transfers. The study is guided by an age-friendly model of care called the 4Ms (What Matters, Medications, Mentation, and Mobility) framework. We will use natural language processing, statistical methods, and social network analysis to generate a new ontology and to compare communication patterns found in TMs occurring around the time NH-to-hospital transfer decisions were made about residents with and without ADRD. RESULTS: After accounting for inclusion and exclusion criteria, we will analyze over 30,000 TMs pertaining to over 3600 NH-to-hospital transfers. Development of the 4M ontology is in progress, and the 3-year project is expected to run until mid-2025. CONCLUSIONS: To our knowledge, this project will be the first to explore the content of TMs exchanged among a multidisciplinary team of care providers as they make decisions about NH-to-hospital resident transfers. Understanding how the presence of evidence-based elements of high-quality care relate to avoidable hospitalizations among NH residents with ADRD will generate knowledge regarding the future scalability of behavioral interventions. Without this knowledge, NHs will continue to rely on ineffective and outdated communication methods that fail to account for evidence-based elements of age-friendly care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50231.

Examining Structural Disparities in US Nursing Homes: National Survey of Health Information Technology Maturity.

BACKGROUND: There are 15,632 nursing homes (NHs) in the United States. NHs continue to receive significant policy attention due to high costs and poor outcomes of care. One strategy for improving NH care is use of health information technology (HIT). A central concept of this study is HIT maturity, which is used to identify adoption trends in HIT capabilities, use and integration within resident care, clinical support, and administrative activities. This concept is guided by the Nolan stage theory, which postulates that a system such as HIT moves through a series of measurable stages. HIT maturity is an important component of the rapidly changing NH landscape, which is being affected by policies generated to protect residents, in part because of the pandemic. OBJECTIVE: The aim of this study is to identify structural disparities in NH HIT maturity and see if it is moderated by commonly used organizational characteristics. METHODS: NHs (n=6123, >20%) were randomly recruited from each state using Nursing Home Compare data. Investigators used a validated HIT maturity survey with 9 subscales including HIT capabilities, extent of HIT use, and degree of HIT integration in resident care, clinical support, and administrative activities. Each subscale had a possible HIT maturity score of 0-100. Total HIT maturity, with a possible score of 0-900, was calculated using the 9 subscales (3 x 3 matrix). Total HIT maturity scores equate 1 of 7 HIT maturity stages (stages 0-6) for each facility. Dependent variables included HIT maturity scores. We included 5 independent variables (ie, ownership, chain status, location, number of beds, and occupancy rates). Unadjusted and adjusted cumulative odds ratios were calculated using regression models. RESULTS: Our sample (n=719) had a larger proportion of smaller facilities and a smaller proportion of larger facilities than the national nursing home population. Integrated clinical support technology had the lowest HIT maturity score compared to resident care HIT capabilities. The majority (n=486, 60.7%) of NHs report stage 3 or lower with limited capabilities to communicate about care delivery outside their facility. Larger NHs in metropolitan areas had higher odds of HIT maturity. The number of certified beds and NH location were significantly associated with HIT maturity stage while ownership, chain status, and occupancy rate were not. CONCLUSIONS: NH structural disparities were recognized through differences in HIT maturity stage. Structural disparities in this sample appear most evident in HIT maturity, measuring integration of clinical support technologies for laboratory, pharmacy, and radiology services. Ongoing assessments of NH structural disparities is crucial given 1.35 million Americans receive care in these facilities annually. Leaders must be willing to promote equal opportunities across the spectrum of health care services to incentivize and enhance HIT adoption to balance structural disparities and improve resident outcomes.