Untangling the complex web of avoidable nursing home-to-hospital transfers of residents with dementia.

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.

Feasibility of Fall-Risk Detection in Older Adults: Real-World Use of Sensor Data With Machine Learning.

PURPOSE: To use machine learning techniques with sensor data to predict fall risk in older adults aging in place. METHOD: We tested the feasibility of using anomaly detection on a dataset comprising 315 days of continuous unobtrusive sensor data obtained from a single participant to predict fall risk within a 10-day window. Predictions were validated with performance metrics, including accuracy, F1 score, and receiver operating characteristic-area under curve (ROC-AUC), using actual falls documented in the electronic health record. RESULTS: The model resulted with accuracy = 0.96 (95% confidence interval [CI] [0.94, 0.99]), F1 = 0.78 (95% CI [0.73, 0.83]), and ROC-AUC = 0.89 (95% CI [0.85, 0.93]). CONCLUSION: The application of anomaly detection on sensor data may provide a timely and valid indication of fall risk in older adults within a 10-day window. Further research and validation are warranted to confirm these findings and expand the scope of application in the domain of older adult care and health care support. [Journal of Gerontological Nursing, 50(10), 7-10.].

Examining Social Networks in Text Messages About Nursing Home Resident Health Status.

Social network analysis (SNA) uses quantitative methods to analyze relationships between people. In the current study, SNA was applied in two nursing homes (NHs) to describe how health care teams interact via text messages. Two data sources were used: (a) a Qualtrics® survey completed by advanced practice RNs containing resident transfer data, and (b) text messages from a secure platform called Mediprocity™. SNA software was used to generate a visual representation of the social networks and calculate quantitative measures of network structure, including density, clustering coefficient, hierarchy, and centralization. Differences were found in the low and high transfer rate NHs for all SNA measures. Staff in the NH with low transfer rate had greater decision-making interactions, higher information exchange rates, and more individuals communicating with each other compared to the high transfer rate NH. SNA can be applied to examine communication patterns found in text messages occurring around the time of NH resident transfers. [Journal of Gerontological Nursing, 47(7), 16-22.].

Qualitative Validation of the Nursing Home IT Maturity Staging Model.

The goal of the current study was to qualitatively explore issues of validity, specificity, and sensitivity regarding the nursing home (NH) information technology (IT) maturity survey and staging model. Participants who completed the NH IT maturity survey were recruited during pilot testing of the survey and staging model. Cognitive interviewing was used to collect qualitative data. Findings indicate the NH IT maturity survey and staging model is a straightforward and acceptable instrument. Every participant in our study agreed with the IT maturity stage assigned to their facility, based on their total score on the IT maturity survey. However, some participants were not sure how to answer some questions on the survey because they did not have in-depth knowledge of IT processes that took place outside of their NH facility and others experienced difficulty interpreting items because their NH facility was in a time of transition. The next step in development is quantitative psychometric testing and use of the instrument in a 3-year national study. [Journal of Gerontological Nursing, 46(7), 47-54].

Exploring Resident Care Information Technology Use and Nursing Home Quality.

A wide array of sophisticated information technology (IT) systems are being used in nursing home (NH) resident care to improve quality. The purpose of the current study was to explore differences in NH IT sophistication, a comprehensive measure of adoption, used in resident care processes based on facility characteristics over 4 consecutive years and to examine the impact on select long-stay NH quality measures. Results indicate IT systems used in resident care are becoming increasingly sophisticated. NH bed size, type of ownership, and location were significant predictors of IT score in areas related to resident care. Results also suggest that as electronic clinical processes and documents increase (e.g., incident reporting, nursing flowsheets, care planning) in resident care, more falls with injury are detected. Continued assessments of NH IT sophistication are important as the impact of technology on quality continues to be evaluated. [Journal of Gerontological Nursing, 46(4), 15-20.].

Patient-Perceived Facilitators of and Barriers to Electronic Portal Use: A Systematic Review.

This systematic review describes characteristics of portal users and their perceptions of this emerging technology. Recent empirical evidence (2010-2016) was reviewed to answer three questions: (1) What are the characteristics of electronic patient portal users? (2) What are patient-perceived facilitators of electronic patient portal use? (3) What are patient-perceived barriers to electronic patient portal use? Characteristics of portal users are described according to three broad categories: demographic characteristics, patterns of use, and complexity and duration of disease. Three themes were found related to patient-perceived facilitators of use: provider encouragement, access/control over health information, and enhanced communication; two themes were found related to patient-perceived barriers to use: lack of awareness/training and privacy and security concerns. Understanding a patient's perception of technology is paramount in optimizing use. These insights will allow for development of better products and clinical processes that facilitate broad goals of improved use of information technology. Policy and practice implications are discussed, as well as suggestions for future research.

Coverage and quality: A comparison of Web of Science and Scopus databases for reporting faculty nursing publication metrics.

BACKGROUND: Web of Science and Scopus are the leading databases of scholarly impact. Recent studies outside the field of nursing report differences in journal coverage and quality. PURPOSE: A comparative analysis of nursing publications reported impact. METHOD: Journal coverage by each database for the field of nursing was compared. Additionally, publications by 2014 nursing faculty were collected in both databases and compared for overall coverage and reported quality, as modeled by Scimajo Journal Rank, peer review status, and MEDLINE inclusion. Individual author impact, modeled by the h-index, was calculated by each database for comparison. DISCUSSION: Scopus offered significantly higher journal coverage. For 2014 faculty publications, 100% of journals were found in Scopus, Web of Science offered 82%. No significant difference was found in the quality of reported journals. Author h-index was found to be higher in Scopus. CONCLUSION: When reporting faculty publications and scholarly impact, academic nursing programs may be better represented by Scopus, without compromising journal quality. Programs with strong interdisciplinary work should examine all areas of strength to ensure appropriate coverage.

Emotional Intelligence: A Critical Evaluation of the Literature with Implications for Mental Health Nursing Leadership.

Emotional intelligence (EI) is necessary for the development of interpersonal and professional competence in nurses. We argue that the concept of emotional intelligence has particular relevance for mental health nursing leadership. In this critique, we examine the recent empirical evidence (2010-2014) related to emotional intelligence, in general, and nursing, specifically. Correlations between emotional intelligence and better overall health, increased work satisfaction, higher spiritual well-being, and decreased risk of job burnout are noted. We offer suggestions for mental health nurse leaders in developing successful project management teams and improving retention of current leaders. We also provide suggestions for future research.

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.

A mixed-methods analysis of telehealth implementation in nursing homes amidst the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has forced nursing homes to adapt new models of care in response to the evolving crisis including rapid implementation of telehealth services. The purpose of our study was to investigate implementation of telehealth in nursing homes amidst the COVID-19 pandemic using a human factors model. METHODS: Using a mixed methods design, we conducted a secondary analysis of data from a national survey of nursing home administrative leaders (n = 204). Using six survey questions, we calculated a total telehealth score (range 0-42). Descriptive statistics and paired sample t-test were used to explore the change in telehealth in two consecutive years (2019-2021). Next, we conducted semi-structured interviews with (n = 21) administrators and clinicians to assess differences in implementation according to extent of telehealth use. RESULTS: The mean telehealth score in year 1 was 12.11 (SD = 9.85) and year 2 was 19.25 (SD = 11.25). There was a significant difference in telehealth scores from year 1 to year 2 (t = 6.83, p < 0.000). While 64% of nursing homes reported higher telehealth scores in year 2 compared to year 1, over 32% reported a decline. Qualitative analysis revealed facilitators of telehealth including training, use of integrated equipment, having staff present for the visit, and using telehealth for different types of visits. Barriers included using smart phones to conduct the visit, billing, interoperability and staffing. CONCLUSION: Training, adaptation of work processes to support communication, and restructuring teams and tasks are the result of interactions between system components that could improve usability and sustainability of telehealth in nursing homes.

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.

Authorship trends in infectious diseases society of America affiliated journal articles conducted in low-income countries, 1998-2018.

An increasing amount of infectious diseases research is conducted in low-income countries (LIC) given their high burden of disease; however, the contribution of LIC investigators as measured by authorship metrics, specifically to infectious diseases research, has not been thoroughly studied. We performed a literature search for primary research conducted either within LICs or using samples from LIC participants published between 1998-2017 in the Infectious Disease Society of America-affiliated journals Clinical Infectious Diseases, Journal of Infectious Diseases, and Open Forum Infectious Diseases. Primary outcomes included proportion of LIC-affiliated first and last authors (i.e. lead authors) per year and authorship trends over time. Secondary outcomes included proportion of LIC-affiliated authorship by geographic distribution and disease focus. Among 1308 publications identified, 50% had either a first or last LIC-affiliated author. Among these authors, 48% of LIC-affiliated first authors and 52% of LIC-affiliated last authors also reported a non-LIC institutional affiliation. While the absolute number of articles by LIC-affiliated lead authors increased over the 20-year period, the proportion of articles with LIC-affiliated lead authors decreased. There is a growing literature for infectious disease research conducted in LICs yet authorship trends in a small subset of these publications demonstrate a pronounced and worsening exclusion of LIC-affiliated investigators from publishing as lead authors.

Development and Pilot Analysis of the Nursing Home Health Information Technology Maturity Survey and Staging Model.

The current research includes a psychometric test of a nursing home (NH) health information technology (HIT) maturity survey and staging model. NHs were assembled based on HIT survey scores from a prior study representing NHs with low (20%), medium (60%), and high (20%) HIT scores. Inclusion criteria were NHs that completed at least two annual surveys over 4 years. NH administrators were excluded who participated in the Delphi panel responsible for instrument recommendations. Recruitment occurred from January to May 2019. Administrators from 121 of 429 facilities completed surveys. NHs were characteristically for-profit, medium bed size, and metropolitan. A covariance matrix demonstrated that all dimensions and domains were significantly correlated, except HIT capabilities and integration in administrative activities. Cronbach's alpha was very good (0.86). Principal component analysis revealed all items loaded intuitively onto four components, explaining 80% variance. The HIT maturity survey and staging model can be used to assess nine dimensions and domains, total HIT maturity, and stage, leading to reliable assumptions about NH HIT. [Research in Gerontological Nursing, 15(2), 93-99.].

Consequences of Rapid Telehealth Expansion in Nursing Homes: Promise and Pitfalls.

BACKGROUND: Expectations regarding use and potential benefits of telehealth (TH) in nursing homes (NHs) are high; however, unplanned and unexpected consequences can occur as a result of major policy and technological changes. OBJECTIVES: The goal of this study was to elicit stakeholder perspectives of consequences of rapid TH expansion in NHs. METHODS: Using a qualitative descriptive design, we drew a sample based on findings from a national study examining trends in NH information and technology (IT) maturity, including TH use. We used maximum variation sampling to purposively select participants who (1) participated in our IT maturity survey for two consecutive years, (2) completed year 1 of the IT maturity survey prior to TH expansion (before March 6, 2020) and year 2 after TH expansion (after March 6, 2020), (3) represented a broad range of facility characteristics, and (4) were identified as an end user of TH or responsible for TH implementation. Using six questions from the IT maturity survey, we created a total TH score for each facility and selected participants representing a range of scores. RESULTS: Interviews were conducted with (n = 21) NH administrators and clinicians from 16 facilities. We found similarities and differences in perceptions of TH expansion according to facility TH score, NH location, and participant role. Desirable consequences included four subthemes as follows: (1) benefits of avoiding travel for the NH resident, (2) TH saving organizational resources, (3) improved access to care, and (4) enhanced communication. Undesirable consequences include the following five subthemes: (1) preference for in-person encounters, (2) worsening social isolation, (3) difficulty for residents with cognitive impairment, (4) workflow and tech usability challenges, and (5) increased burden on NH staff/infrastructure. Participants from rural NHs perceived lack of training, poor video/sound quality, and internet/connectivity issues to be potential pitfalls. CONCLUSION: Clinicians and NH administrators should consider leveraging the desirable consequences of rapid TH expansion and implement mitigation strategies to address the undesirable/unanticipated consequences.

Health Data Sharing in US Nursing Homes: A Mixed Methods Study.

OBJECTIVES: (1) To understand the extent to which nursing homes have the capability for data sharing and (2) to explore nursing home leaders' perceptions of data sharing with other health care facilities and with residents and family members. DESIGN: Exploratory, mixed-methods. SETTING AND PARTICIPANTS: We conducted a secondary analysis of data from a national survey of nursing home administrative leaders (n = 815) representing every state in the United States. Next, semistructured interviews were used to elicit rich contextual information from (n = 12) administrators from nursing homes with varying data-sharing capabilities. METHODS: We used descriptive statistics along with Rao-Scott chi-square and logistic regression models to examine the relationship between health data-sharing capabilities and nursing home characteristics such as location, bed size, and type of ownership. Qualitative data were analyzed using content analysis. RESULTS: Of the 815 nursing homes completing the survey, 95% had computerized (electronic) medical records, and 46% had some capability for health information exchange. Nursing homes located in metropolitan areas had 2.53 (95% confidence interval = 1.53, 4.18) times greater odds for having health information exchange capability compared with nursing homes in small towns. Perceived challenges to health data sharing with residents and family members and external clinical partners include variance in systems and software, privacy and security concerns, and organizational factors slowing uptake of technology. Perceived benefits of health data sharing included improved communication, improved care planning, and anticipating future demand. CONCLUSIONS AND IMPLICATIONS: As health data sharing becomes more ubiquitous in acute care settings, policy makers, nursing home leaders, and other stakeholders should prepare by working to mitigate barriers and capitalize on potential benefits of implementing this technology in nursing homes.

An evaluation of telehealth expansion in U.S. nursing homes.

OBJECTIVE: This research brief contains results from a national survey about telehealth use reported in a random sample of U.S. nursing homes. METHODS AND MATERIALS: The sample includes nursing homes (N = 664) that completed surveys about information technology maturity, including telehealth use, beginning January 1, 2019, and ending August 4, 2020. A pre/post design was employed to examine differences in nursing home telehealth use for nursing homes completing surveys prior to and after telehealth expansion, on March 6, 2020. We calculated a cumulative telehealth score using survey data from 6 questions about extent of nursing home telehealth use (score range 0-42). We calculated proportions of nursing homes using telehealth and used logistic regression to look for differences in nursing homes based on organizational characteristics and odds ratios. RESULTS: Significant relationships were found between nursing home characteristics and telehealth use, and specifically, larger metropolitan homes reported greater telehealth use. Ownership had little effect on telehealth use. Nursing homes postexpansion used telehealth applications for resident evaluation 11.24 times more (P < .01) than did nursing homes pre-expansion. DISCUSSION: Administrators completing our survey reported a wide range of telehealth use, including approximately 16% having no telehealth use and 5% having the maximum amount of telehealth use. Mean telehealth use scores reported by the majority of these nursing homes is on the lower end of the range. CONCLUSIONS: One solution for the current pandemic is to encourage the proliferation of telehealth with continued relaxed regulations, which can reduce isolation and preserve limited resources (eg, personal protective equipment) while maintaining proper distancing parameters.

Pathogenic bacteria induce colonic PepT1 expression: an implication in host defense response.

BACKGROUND & AIMS: Expression of the di/tripeptide transporter PepT1 has been observed in the colon under inflammatory conditions; however, the inducing factors and underlying mechanisms remain unknown. Here, we address the effects of pathogenic bacteria on colonic PepT1 expression together with its functional consequences. METHODS: Human colonic HT29-Cl.19A cells were infected with the attaching and effacing enteropathogenic Escherichia coli (EPEC). Wild-type and PepT1 transgenic mice or cultured colonic tissues derived from these mice were infected with Citrobacter rodentium, a murine attaching and effacing pathogen related to EPEC. RESULTS: EPEC induced PepT1 expression and activity in HT29-Cl.19A cells by intimately attaching to host cells through lipid rafts. Induction of PepT1 expression by EPEC required the transcription factor Cdx2. PepT1 expression reduced binding of EPEC to lipid rafts, as well as activation of nuclear factor-kappaB and mitogen-activated protein kinase and production of interleukin-8. Accordingly, ex vivo and in vivo experiments revealed that C rodentium induced colonic PepT1 expression and that, compared with their wild-type counterparts, PepT1 transgenic mice infected with C rodentium exhibited decreased bacterial colonization, production of proinflammatory cytokines, and neutrophil infiltration into the colon. CONCLUSIONS: Our findings demonstrate a molecular mechanism underlying the regulation of colonic PepT1 expression under pathologic conditions and reveal a novel role for PepT1 in host defense via its capacity to modulate bacterial-epithelial interactions and intestinal inflammation.