Publications by authors named "Mary D Naylor"

94 Publications

Demographic Characteristics Driving Disparities in Receipt of Long-Term Services and Supports in the Community Setting.

Med Care 2021 Apr 6. Epub 2021 Apr 6.

New York University Rory Meyers College of Nursing, New York City, NY NewCourtland Center for Transitions and Health, University of Pennsylvania School of Nursing University of Pennsylvania Perelman School of Medicine, Philadelphia, PA Yale Center for Analytical Sciences, Department of Biostatistics, Yale School of Public Health, New Haven, CT.

Background: Research suggests that growth in Black and Hispanic (minority) older adults' nursing home (NH) use may be the result of disparities in access to community-based and alternative long-term services and supports (LTSS).

Objective: We aimed to determine whether minority groups receiving care in NHs versus the community had fewer differences in their functional needs compared with the differences in nonminority older adults, suggesting a disparity.

Methods: We identified respondents aged 65 years or above with a diagnosis of Alzheimer disease or dementia in the 2016 Health and Retirement Study who reported requiring LTSS help. We performed unadjusted analyses to assess the difference in functional need between community and NH care. Functional need was operationalized using a functional limitations score and 6 individual activities of daily living. We compared the LTSS setting for minority older adults to White older adults using difference-in-differences.

Results: There were 186 minority older adults (community=75%, NH=25%) and 357 White older adults (community=50%, NH=50%). Between settings, minority older adults did not differ in education or marital status, but were younger and had greater income in the NH versus the community. The functional limitations score was higher in NHs than in the community for both groups. Functional needs for all 6 activities of daily living for the minority group were greater in NHs compared with the community.

Conclusion: Functional need for minority older adults differed by setting while demographics varied in unexpected ways. Factors such as familial and financial support are important to consider when implementing programs to keep older adults out of NHs.
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http://dx.doi.org/10.1097/MLR.0000000000001544DOI Listing
April 2021

Opportunities and challenges presented by recent pedagogical innovations in doctoral nursing education.

J Prof Nurs 2021 Jan-Feb;37(1):228-234. Epub 2020 Sep 2.

NewCourtland Center for Transitions and Health, University of Pennsylvania School of Nursing, 418 Curie Boulevard, Philadelphia, PA 19104, United States of America.

The demand to expand the nurse scientist pipeline over the past decade has generated numerous pedagogical innovations in nursing doctoral education. A PhD nursing education summit was held at the University of Pennsylvania in October 2019 to discuss pedagogical innovations. The main pedagogical innovations discussed by Summit attendees included: 1) the expansion of both 3-year PhD programs and BSN to PhD programs; 2) changes in learning opportunities and curricula content; and 3) the role of postdoctoral fellowships. This overview examines the numerous opportunities and challenges generated by these innovations. Opportunities include producing scholars with research careers that are potentially longer than historically seen in the nursing profession, as well as the emergence of unique educational and mentoring opportunities both during and after doctoral studies. Challenges involve the impact condensed program timelines have had on both the content and delivery of curricula, as well as the research expertise and skillsets of nursing PhD program graduates. There is a need to conduct a national coordinated evaluation of PhD program using shared metrics in order to better evaluate the effect of these pedagogical innovations on the development of nurse scientists, and ultimately, the discipline.
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http://dx.doi.org/10.1016/j.profnurs.2020.09.003DOI Listing
September 2020

Patient Factors Linked with Return Acute Healthcare Use in Older Adults by Discharge Disposition.

J Am Geriatr Soc 2020 10 16;68(10):2279-2287. Epub 2020 Jul 16.

School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Objectives: Compare patient characteristics by hospital discharge disposition (home without services, home with home healthcare (HHC) services, or post-acute care (PAC) facilities). Examine timing and rates of 30-day healthcare utilization (rehospitalization, emergency department (ED) visit, or observation (OBS) visit) and patient characteristics associated with rehospitalization by discharge location.

Design: Retrospective analysis of hospital administrative and clinical data.

Setting And Participants: A total of 3,294 older adult inpatients discharged home with or without HHC services or to a PAC facility.

Measurements: Patient-level sociodemographic and clinical characteristics. Number of and time to occurrences of rehospitalization or ED/OBS visit within 30 days of hospital discharge.

Results: Most rehospitalizations and ED/OBS visits occurred within 14 days from hospital discharge. Patients who returned within 24 hours came mostly from inpatient rehabilitation facilities (IRFs). More intense levels of PAC services were linked with higher rehospitalization risk. However, specific predictors differed by discharge location. Being unemployed, being single, and having more comorbidities were most associated with rehospitalization in those who went home with or without services, whereas patients rehospitalized from IRFs were younger, with less chronic illness burden, but greater and recent functional decline. Those discharged with HHC services had more return ED/OBS visits.

Conclusions: Although sicker patients were referred for more intense levels of PAC services, patients with greater chronic illness burden were still most often rehospitalized. In addition to unique patient differences, rehospitalizations from IRF within 24 hours suggest systems factors are contributory. Most return acute healthcare utilization occurred within 14 days; therefore, interventions should focus on smoothing transitions to all discharge locations. Because predictors of rehospitalization risk differed by discharge disposition, future research is necessary to study approaches aimed at matching patients' care needs with the most suitable PAC services at the right time. J Am Geriatr Soc 68:2279-2287, 2020.
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http://dx.doi.org/10.1111/jgs.16645DOI Listing
October 2020

Self-efficacy of family caregivers of older adults with cognitive impairment: A concept analysis.

Nurs Forum 2021 Jan 4;56(1):112-126. Epub 2020 Sep 4.

School of Nursing, New Courtland Center for Transitions and Health, University of Pennsylvania, Philadelphia, Pennsylvania.

Background: Research demonstrates that increased self-efficacy can help family caregivers of older adults with Alzheimer's and other types of cognitive impairment experience lower burden and depressive symptom severity.

Aims: The purpose of this concept analysis is to address fundamental gaps in the understanding of self-efficacy in family caregivers of older adults with cognitive impairment, including updating the 26-year-old concept analysis with a contemporary definition.

Methods: This study utilizes Walker and Avant's (2019) concept analysis method, an eight-step iterative process that helps to clarify ambiguous concepts. A literature review was conducted from July 1993 through March 2019 using PubMed/MEDLINE, Scopus, CINAHL, and Embase. Inclusion criteria encompassed peer-reviewed research articles and review articles that included family caregivers of older adults with cognitive impairment.

Results: Eight defining attributes of this concept are identified. The revised definition of self-efficacy in this population is a family caregiver's confidence in their ability to: manage behaviors and other caregiving stresses, control upsetting thoughts, acquire medical information, manage medical issues, obtain self-care, access community supports, assist with activities of daily living and other care, and maintain a good relationship with a relative, friend, or neighbor of an older adult with cognitive impairment.

Conclusion: This paper utilizes over a quarter-century of research to build on the original analysis by Mowat and Spence Laschinger (1994) and update the concept's definition. This analysis should provide researchers with a clearer understanding of this concept and a renewed emphasis on the importance of targeting interventions to improve self-efficacy in this vulnerable caregiving population.
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http://dx.doi.org/10.1111/nuf.12499DOI Listing
January 2021

Reported Needs and Depressive Symptoms Among Older Adults Entering Long-Term Services and Supports.

Innov Aging 2020 9;4(3):igaa021. Epub 2020 Jun 9.

NewCourtland Center for Transitions and Health, University of Pennsylvania School of Nursing, Philadelphia.

Background And Objectives: Long-term services and supports (LTSS) are vital for older adults with physical and cognitive disabilities. LTSS can be provided in settings such as nursing homes, assisted living, or via community-based services. During the transition to LTSS, older adults are at risk of increased depressive symptoms. In addition, older adults may identify unmet needs despite having access to new LTSS resources. The goal of this study was to examine the factors associated with increased depressive symptoms among a pool of older adults, with a focus on change in reported needs after starting LTSS.

Research Design And Methods: This cross-sectional analysis of a cohort study included 352 older adults new to LTSS (R01AG025524). The outcome of depressive symptoms was measured using the Geriatric Depression Scale-Short Form. Reported needs included supportive equipment, devices, transportation, and social activities. Bivariate and linear regression modeling using change in needs 3 months later were performed.

Results: Depressive symptoms were present among 40% of the LTSS recipients at enrollment and 3 months. At baseline, 29% of LTSS recipients reported a need for supportive equipment, 30% for transportation, and 23% for social activities. After 3 months, an average of 12% of LTSS recipients' needs were met, 13% of LTSS recipients' needs persisted, and 11% of LTSS recipients reported new needs. Depressive symptoms 3 months later were higher for those who reported persistent unmet needs compared with those who reported no needs at all, controlling for functional status and LTSS type.

Discussion And Implications: The transition to LTSS is a vulnerable time for older adults. Assessing the need for equipment, transportation, and social activities during this period may identify opportunities to improve the lives and emotional status of this population.
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http://dx.doi.org/10.1093/geroni/igaa021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334621PMC
June 2020

Satisfaction With Outdoor Activities Among Northeastern U.S. Newly Enrolled Long-Term Services and Supports Recipients.

J Appl Gerontol 2020 Jul 1:733464820933774. Epub 2020 Jul 1.

University of Pennsylvania School of Nursing, Philadelphia, PA, USA.

Older adults receiving long-term services and supports (LTSS) experience barriers to outdoor activities and satisfaction ratings with such experiences are not well understood. Our study used cross-sectional data ( = 329) to (a) examine whether those new to LTSS were satisfied with their outdoor activities and (b) describe the characteristics and factors associated with satisfaction levels. Self-report of satisfaction with outdoor activities was the outcome variable. Multivariable linear regression modeling of the outcome was conducted. Fifty-nine percent were satisfied with their outdoor activities. More depressive symptoms ( < .001) and higher cognitive functioning ( = .011) were associated with lower ratings. Higher self-rated physical health ( = .009) and more independence with activities of daily living ( = .022) were associated with greater satisfaction. Findings suggest an unmet need among four in 10 new recipients of LTSS (41%) related to their outdoor activities. LTSS interdisciplinary teams can use these findings to inform their assessments, develop person-centered care plans, and address barriers.
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http://dx.doi.org/10.1177/0733464820933774DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775289PMC
July 2020

Predictors of change over time in subjective daytime sleepiness among older adult recipients of long-term services and supports.

Int Psychogeriatr 2020 Jul;32(7):849-861

Biobehavioral Health Sciences Department, University of Pennsylvania School of Nursing, Philadelphia, PA, USA.

Objectives: Daytime sleepiness is associated with multiple negative outcomes in older adults receiving long-term services and supports (LTSS) including reduced cognitive performance, need for greater assistance with activities of daily living and decreased social engagement. The purpose of this study was to identify predictors of change in subjective daytime sleepiness among older adults during their first 2 years of receiving LTSS.

Design And Setting: Secondary analysis of data from a prospective longitudinal study of older adults who received LTSS in their homes, assisted living communities or nursing homes interviewed at baseline and every 3 months for 24 months.

Participants: 470 older adults (60 years and older) newly enrolled in LTSS (mean = 81, SD = 8.7; range 60-98; 71% women).

Measurements: Subjective daytime sleepiness was assessed every 3 months through 2 years using the Epworth Sleepiness Scale. Multiple validated measures were used to capture health-related quality of life characteristics of enrollees and their environment, including symptom status (Symptom Bother Scale), cognition (Mini Mental Status Exam), physical function (Basic Activities of Daily Living), physical and mental general health, quality of life (Dementia Quality of Life, D-QoL), depressive symptoms (Geriatric Depression Scale) and social support (Medical Outcomes Survey-Social Support).

Results: Longitudinal mixed effects modeling was used to examine the relationship between independent variables and continuous measure of daytime sleepiness. Increased feelings of belonging, subscale of the D-QoL (effect size = -0.006, 95% CI: -0.013 to -0.0001, p = 0.045) and higher number of depressive symptoms (effect size = -0.002, 95% CI: -0.004 to -0.001, p = 0.001) at baseline were associated with slower rates of increase in daytime sleepiness over time.

Conclusions: Comprehensive baseline and longitudinal screening for changes in daytime sleepiness along with depression and perceived quality of life should be used to inform interventions aimed at reducing daytime sleepiness among older adults receiving LTSS.
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http://dx.doi.org/10.1017/S1041610220000782DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455051PMC
July 2020

"We are Alone in This Battle": A Framework for a Coordinated Response to COVID-19 in Nursing Homes.

J Aging Soc Policy 2020 Jul-Oct;32(4-5):316-322. Epub 2020 Jun 4.

Marian S. Ware Professor in Gerontology, Director of the NewCourtland Center for Transitions and Health, University of Pennsylvania , Philadelphia, Pennsylvania, USA.

As of May 2020, nursing home residents account for a staggering one-third of the more than 80,000 deaths due to COVID-19 in the U.S. This pandemic has resulted in unprecedented threats to achieving and sustaining care quality even in the best nursing homes, requiring active engagement of nursing home leaders in developing solutions responsive to the unprecedented threats to quality standards of care delivery during the pandemic. This perspective offers a framework, designed with the input of nursing home leaders, to facilitate internal and external decision-making and collective action to address these threats. Policy options focus on assuring a shared understanding among nursing home leaders and government agencies of changes in the operational status of nursing homes throughout the crisis, improving access to additional essential resources needed to mitigate the crisis' impact, and promoting shared accountability for consistently achieving accepted standards in core quality domains.
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http://dx.doi.org/10.1080/08959420.2020.1773190DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495491PMC
July 2020

Meeting the Transitional Care Needs of Older Adults with COVID-19.

J Aging Soc Policy 2020 Jul-Oct;32(4-5):387-395. Epub 2020 May 31.

Professor of Cardiovascular Nursing, NewCourtland Center for Transitions and Health, University of Pennsylvania School of Nursing , Philadelphia, Pennsylvania, USA.

Older adults with COVID-19 who survive hospitalizations and return to their homes confront substantial health challenges and an unpredictable future. While understanding of the unique needs of COVID-19 survivors is developing, components of the evidence-based Transitional Care Model provide a framework for taking a more immediate, holistic response to caring for these individuals as they moved back into the community. These components include: increasing screening, building trusting relationships, improving patient engagement, promoting collaboration across care teams, undertaking symptom management, increasing family caregiver care/education, coordinating health and social services, and improving care continuity. Evidence generated from rigorous testing of these components reveal the need for federal and state policy solutions to support the following: employment/redeployment of nurses, social workers, and community health workers; training and reimbursement of family caregivers; widespread access to research-based transitional care tools; and coordinated local efforts to address structural barriers to effective transitions. Immediate action on these policy options is necessary to more effectively address the complex issues facing these older adults and their family caregivers who are counting on our care system for essential support.
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http://dx.doi.org/10.1080/08959420.2020.1773189DOI Listing
July 2020

Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety.

J Am Med Inform Assoc 2020 06;27(6):929-933

School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Objective: The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning algorithms can be used to train a classifier for anxiety.

Materials And Methods: We used a secondary data set generated by a clinical trial examining problem-solving therapy for hospice caregivers consisting of 140 transcripts of multiple, sequential conversations between an interviewer and a family caregiver along with standardized assessments of anxiety prior to each session; 98 of these transcripts (70%) served as the training set, holding the remaining 30% of the data for evaluation.

Results: A classifier for anxiety was developed relying on language-based features. An 86% precision, 78% recall, 81% accuracy, and 84% specificity were achieved with the use of the trained classifiers. High anxiety inflections were found among recently bereaved caregivers and were usually connected to issues related to transitioning out of the caregiving role. This analysis highlighted the impact of lowering anxiety by increasing reciprocity between interviewers and caregivers.

Conclusion: Verbal communication can provide a platform for machine learning tools to highlight and predict behavioral health indicators and trends.
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http://dx.doi.org/10.1093/jamia/ocaa049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309232PMC
June 2020

Adapting Andersen's expanded behavioral model of health services use to include older adults receiving long-term services and supports.

BMC Geriatr 2020 02 14;20(1):58. Epub 2020 Feb 14.

NewCourtland Center for Transitions and Health, University of Pennsylvania School of Nursing, 418 Curie Blvd, Philadelphia, PA, 19104, USA.

Background: Andersen's Expanded Behavioral Model of Health Services Use describes factors associated with the use of long-term services and supports (LTSS). This model, however, has only been tested on the intent to use such services among African-American and White older adults and not the actual use. Given the increasing diversity of older adults in the U.S., the ability to conceptualize factors associated with actual use of LTSS across racial/ethnic groups is critical.

Methods: We applied Andersen's Expanded model in the analysis of 2006-2010 qualitative data using multiple methods to understand both the relevancy of factors for older adults who currently use LTSS vs. those who intend to use LTSS (as described in Andersen's original exploration). We additionally explored differences in these factors across racial/ethnic groups and included Hispanic older adults in our analyses.

Results: Four additional constructs linked with actual LTSS use emerged: losses and changes, tangible support, capability to provide informal support, and accessibility of informal support. Racial differences were seen in level of participation in decisions to use nursing home services (Not involved: 45% African-Americans vs. 24% Whites). Reports of LTSS use to avoid burdening one's family were greater among White older adults compared to African-American older adults.

Conclusions: Findings around decision-making and burden along with other constructs enhance our understanding of determinants that influence actual LTSS use and require targeted interventions.
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http://dx.doi.org/10.1186/s12877-019-1405-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7023712PMC
February 2020

Factors Associated With Perceived Worsened Physical Health Among Older Adults Who Are Newly Enrolled Long-term Services and Supports Recipients.

Inquiry 2020 Jan-Dec;57:46958019900835

University of Pennsylvania School of Nursing, Philadelphia, PA, USA.

Limited information exists on the perceived health of older adults new to receiving long-term services and supports (LTSS) compared with the year prior, posing challenges to the anticipation of health care need and optimization of wellness efforts for this growing population. In response, we sought to identify differences in perceived worsened physical health across three LTSS types (nursing home, assisted living, and home and community-based services) along with health-related quality of life (HRQoL) characteristics associated with older adults' ratings of perceived worsened physical health at the start of receiving LTSS. Enrolled LTSS recipients completed a single interview assessing their HRQoL. Bivariate and multivariable logistic regression analyses were performed to determine associations in LTSS types and HRQoL characteristics with perceived worsened physical health among older adults (≥60 years old) since 1 year prior to study enrollment. Among the 467 LTSS recipients, perceived physical health was rated as worse than the previous year by 36%. Bivariate analyses revealed no differences in perceived worsened physical health across LTSS types. In adjusted analyses, religiousness/spirituality and better mental and general health perception had a decreased odds of being associated with perceived worsened physical health ( < .05). Participants with major changes in their health in the past 6 months were more likely to report perceived worsened physical health ( < .001). Findings provide information that may be used to target efforts to enhance perceived physical health and improve quality of life among LTSS enrollees.
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http://dx.doi.org/10.1177/0046958019900835DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6990604PMC
November 2020

Factors Affecting Patient Prioritization Decisions at Admission to Home Healthcare: A Predictive Study to Develop a Risk Screening Tool.

Comput Inform Nurs 2020 Feb;38(2):88-98

Author Affiliations: School of Nursing and Data Science Institute, Columbia University (Dr Topaz); and Visiting Nurse Service of New York (Drs Topaz and Bowles); and School of Nursing (Drs Naylor and Bowles), and Department of Biostatistics and Epidemiology, Institute for Biomedical Informatics, Perelman School of Medicine (Dr Holmes), University of Pennsylvania, Philadelphia.

There is a lack of evidence on how to identify high-risk patients admitted to home healthcare. This study aimed (1) to identify which disease characteristics, medications, patient needs, social support characteristics, and other factors are associated with patient priority for the first home health nursing visit; and (2) to construct and validate a predictive model of patient priority for the first home health nursing visit. This was a predictive study of home health visit priority decisions made by 20 nurses for 519 older adults. The study found that nurses were more likely to prioritize patients who had wounds (odds ratio = 1.88), comorbid condition of depression (odds ratio = 1.73), limitation in current toileting status (odds ratio = 2.02), higher number of medications (increase in odds ratio for each medication = 1.04), and comorbid conditions (increase in odds ratio for each condition = 1.04). This study developed one of the first clinical decision support tools for home healthcare called "PREVENT". (PRiority home health Visit Tool). Further work is needed to increase the specificity and generalizability of the tool and to test its effects on patient outcomes.
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http://dx.doi.org/10.1097/CIN.0000000000000576DOI Listing
February 2020

High-value care for older adults with complex care needs: Leveraging nurses as innovators.

Nurs Outlook 2020 Jan - Feb;68(1):26-32. Epub 2019 Jun 27.

University of Pennsylvania School of Nursing, Philadelphia, PA.

Background: Our health care system is facing unprecedented and complex challenges in caring for older adults and their families. A paradigm shift is needed that recognizes new roles and competencies for nurses to play a leadership role in the design and implementation of high value care models.

Purpose: The purpose of this paper is to introduce a series of recommendations for leveraging nurses to generate innovative tools and solutions for the delivery of value-based care for older adults living with complex health and social needs and their families.

Methods: These recommendations were generated by a Think-Tank of national experts based on review of current evidence and focus groups with older adults.

Finding: The generated recommendations focus on positioning nurses to assume leadership roles in implementing evidence-based care models, preparing nurses to serve as health innovators and catalysts of system transformation, and fostering system-level infrastructure that leverages the contributions of nurses for current and emerging roles.

Discussion: Nurses as innovators can address the challenges in providing high quality care for older adults with complex needs and their families. System-level infrastructure, including resources for training and implementation of well-established programs, is necessary to leverage the contributions of nurses and facilitate innovative approaches to care.
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http://dx.doi.org/10.1016/j.outlook.2019.06.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6933093PMC
May 2020

Policy Flight Simulators: Accelerating Decisions to Adopt Evidence-Based Health Interventions.

J Healthc Manag 2019 Jul-Aug;64(4):231-241

professor, Center for Complex Systems and Enterprises, Stevens Institute of Technology, Hoboken, New Jersey professor, University of Pennsylvania School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania research assistant professor, Center for Complex Systems and Enterprises, Stevens Institute of Technology assistant professor, Center for Complex Systems and Enterprises, Stevens Institute of Technology research associate professor, University of Pennsylvania School of Nursing; professor, Wharton School, University of Pennsylvania director of industry and government relations, Center for Complex Systems and Enterprises, Stevens Institute of Technology.

Executive Summary: In this study, the authors used simulation to explore factors that might influence hospitals' decisions to adopt evidence-based interventions. Specifically, they developed a simulation model to examine the extent to which hospitals would benefit economically from the transitional care model (TCM). The TCM is designed to transition high-risk older adults from hospitals back to communities using interventions focused on preventing readmissions.The authors used qualitative methods to identify and validate simulation facets. Four simulation experiments explored the economic impact of the TCM on more than 3,000 U.S. hospitals: (1) magnitude of readmission penalty, (2) application to specific diagnosis-related groups, (3) level of cost sharing between payer and provider, and (4) capitated versus fee-for-service payments. The simulator projected hospital-specific economic effects. The authors used Monte Carlo methods for the simulations, which were parameterized with public data sets from the Centers for Medicare & Medicaid Services (CMS) and TCM data from randomized controlled trials and comparative effectiveness studies.Under current conditions, the simulation indicated that only 10 of more than 3,000 Medicare-certified hospitals would benefit financially from the TCM. If current readmission penalties were doubled, the number of hospitals projected to benefit would increase to 300. Targeting selected diagnosis cohorts would also increase the number of hospitals to 300. If payers reimbursed providers for 100% of the TCM costs, 2,000 hospitals would benefit financially. Under a capitated payment model, 1,500 hospitals would benefit from the TCM.Current CMS penalties-or reasonable increases-have little economic effect on the TCM. In the current environment, two strategies are likely to facilitate adoption: (1) persuading payers to reimburse TCM costs and (2) focusing on hospitals with higher bed occupancies and higher revenue patients.
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http://dx.doi.org/10.1097/JHM-D-18-00114DOI Listing
August 2020

Association of health related quality of life domains with daytime sleepiness among elderly recipients of long-term services and supports.

Geriatr Nurs 2019 Jul - Aug;40(4):417-423. Epub 2019 Mar 7.

University of Pennsylvania, School of Nursing, United States. Electronic address:

Excessive daytime sleepiness (EDS) is prevalent in older adults; however, data are lacking that examine EDS across living environments. The aims of this secondary data analysis were to identify the prevalence and predictors of EDS among older adults receiving long-term services and supports (LTSS) in assisted living communities (ALCs), nursing homes (NHs), and the community. Participants (n = 470) completed multiple measures including daytime sleepiness. Logistic regression modeling was used to identify EDS predictors. Participants were primarily female and white with a mean age of 81 ± 9 years. The overall prevalence of EDS was 19.4%; the prevalence differed across living environment. Older adults in ALCs and NHs had higher odds of EDS than those living in the community. Also, depressive symptoms and number of bothersome symptoms predicted EDS. Upon admission for LTSS, evaluating older adults, especially those in ALCs and NHs, for depression and bothersome symptoms may reveal modifiable factors of EDS.
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http://dx.doi.org/10.1016/j.gerinurse.2019.01.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708490PMC
December 2019

What Predicts Health Care Transitions for Older Adults Following Introduction of LTSS?

J Appl Gerontol 2020 07 28;39(7):702-711. Epub 2019 Feb 28.

University of Pennsylvania School of Nursing, Philadelphia, USA.

To determine predictors of health care transitions (i.e., acute care service use, transfers from lower to higher intensity services) among older adults new to long-term services and supports [LTSS]. 470 new LTSS recipients followed for 24 months. Multivariable Poisson regression modeling within a generalized estimating equation framework. Being male, having multiple chronic conditions, lower self-reported physical health ratings and lower quality of life ratings at baseline were associated with increased risk of health care transitions. Older adults in assisted living communities and nursing homes experienced decreases in health care transitions over time, while LTSS recipients at home had no change in risk. LTSS recipients who had orders to receive therapy, compared with those who did not, had a lower relative risk of transitions over time. Predictors of future health care transitions support the need for LTSS providers to anticipate and monitor this risk for LTSS recipients.
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http://dx.doi.org/10.1177/0733464819833565DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713625PMC
July 2020

Using a Decision Support Algorithm for Referrals to Post-Acute Care.

J Am Med Dir Assoc 2019 04 8;20(4):408-413. Epub 2018 Nov 8.

University of Pennsylvania School of Nursing, New Courtland Center for Transitions and Health, Philadelphia, PA.

Objectives: Although hospital clinicians strive to effectively refer patients who require post-acute care (PAC), their discharge planning processes often vary greatly, and typically are not evidence-based.

Design: Quasi-experimental study employing pre-/postdesign. Aimed at improving patient-centered discharge processes, we examined the effects of the Discharge Referral Expert System for Care Transitions (DIRECT) algorithm that provides clinical decision support (CDS) regarding which patients to refer to PAC and to what level of care (home care or facility).

Setting And Participants: Conducted in 2 hospitals, DIRECT data elements were collected in the pre-period (control) but discharging clinicians were blinded to the advice and provided usual discharge care. During the postperiod (intervention), referral advice was provided within 24 hours of admission to clinicians, and updated twice daily. Propensity modeling was used to account for differences between the pre-/post patient cohorts.

Measures: Outcomes compared between the control and the intervention periods included PAC referral rates, patient characteristics, and same-, 7-, 14-, and 30-day readmissions or emergency department visits.

Results: Although 24%-25% more patients were recommended for PAC referral by DIRECT algorithm advice, the proportion of patients receiving referrals for PAC did not significantly differ between the control (3302) and intervention (5006) periods. However, the characteristics of patients referred for PAC services differed significantly and inpatient readmission rates decreased significantly across all time intervals when clinicians had DIRECT CDS compared with without. There were no differences observed in return emergency department visits. Largest effects were observed when clinicians agreed with the algorithm to refer (yes/yes).

Conclusions/implications: Our findings suggest the value of timely, automated, discharge CDS for clinicians to optimize PAC referral for those most likely to benefit. Although overall referral rates did not change with CDS, the algorithm may have identified those patients most in need, resulting in significantly lower inpatient readmission rates.
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http://dx.doi.org/10.1016/j.jamda.2018.08.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6541013PMC
April 2019

Changing the Care System Long Before the "End Game".

J Am Geriatr Soc 2018 11 9;66(11):2050-2051. Epub 2018 Oct 9.

School of Nursing, University of Pennsylvania, Philadelphia, PA.

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http://dx.doi.org/10.1111/jgs.15618DOI Listing
November 2018

Cost impact of the transitional care model for hospitalized cognitively impaired older adults.

J Comp Eff Res 2018 09 11;7(9):913-922. Epub 2018 Sep 11.

NewCourtland Center for Transitions & Health at the University of Pennsylvania School of Nursing, Philadelphia, PA, 19104, USA.

Aim: The goal of this study was to compare postacute care costs of three care management interventions.

Materials & Methods: A total of 202 hospitalized older adults with cognitive impairment received either Augmented Standard Care, Resource Nurse Care or the Transitional Care Model. The Lin method was used to estimate costs at 30 and 180 days postindex hospital discharge.

Results: The Transitional Care Model had significantly lower costs than the Augmented Standard Care group at both 30 (p < 0.001) and 180 days (p = 0.03) and significantly lower costs than Resource Nurse Care at 30 days (p = 0.02).

Conclusion: These findings suggest that the Transitional Care Model can reduce both the amount of other postacute care and the total cost of care compared with alternative services for cognitively impaired older adults. Clinicaltrials.gov : NCT00294307.
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http://dx.doi.org/10.2217/cer-2018-0040DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219439PMC
September 2018

Adaptations of the evidence-based Transitional Care Model in the U.S.

Soc Sci Med 2018 09 17;213:28-36. Epub 2018 Jul 17.

Wharton School at the University of Pennsylvania, Philadelphia, PA, United States.

Despite a growing body of evidence that adaptations of evidence-based interventions (EBI) are ubiquitous, few studies have examined the nature and rationale for modifications to the components of these interventions. The primary aim of this study was to describe and classify common local adaptations of the Transitional Care Model (TCM), an EBI comprised of 10 components that has been proven in multiple clinical trials to improve the care and outcomes of chronically ill older adults transitioning from hospitals to home. Guided by Stirman's System of Classifying Adaptations, 582 transitional care clinicians in health systems and community-based organizations throughout the U.S. completed a survey between September 2014 and January 2015; interviews were then conducted with a subset of survey respondents (N = 24) between April and December 2015. A total of 342 survey respondents (59%) reported implementation of the TCM in distinct organizations. Of this group, 96% reported a mean of 4.4 adaptations to the 10 TCM components (40%, one to three; 43%, four to six; and 17%, seven to nine). Nine of ten respondents (94%) reported contextual adaptations while content adaptations were less frequently reported (58%). The top three reported adaptations all related to context (i.e., delivering services from hospital to home, relying on advance practice nurses, and fostering care continuity); interviews clarified a diverse set of reasons for such modifications. Findings reinforce the need for investment in adaptation science and suggest hypotheses to guide rigorous examination of the association between adaptations of TCM components and desired outcomes.
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http://dx.doi.org/10.1016/j.socscimed.2018.07.023DOI Listing
September 2018

Nurse Generated EHR Data Supports Post-Acute Care Referral Decision Making: Development and Validation of a Two-step Algorithm.

AMIA Annu Symp Proc 2017 16;2017:465-474. Epub 2018 Apr 16.

University of Pennsylvania, Philadelphia, PA.

Build and validate a clinical decision support (CDS) algorithm for discharge decisions regarding referral for post-acute care (PAC) and to what site of care. Case studies derived from EHR data were judged by 171 interdisciplinary experts and prediction models were generated. A two-step algorithm emerged with area under the curve (AUC) in validation of 91.5% (yes/no refer) and AUC 89.7% (where to refer). CDS for discharge planning (DP) decisions may remove subjectivity, and variation in decision-making. CDS could automate the assessment process and alert clinicians of high need patients earlier in the hospital stay. Our team successfully built and validated a two-step algorithm to support discharge referral decision-making from EHR data. Getting patients the care and support they need may decrease readmissions and other adverse events. Further work is underway to test the effects of the CDS on patient outcomes in two hospitals.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977719PMC
March 2019

Developing a Policy Flight Simulator to Facilitate the Adoption of an Evidence-Based Intervention.

IEEE J Transl Eng Health Med 2018 7;6:4800112. Epub 2018 May 7.

School of Systems and EnterprisesStevens Institute of TechnologyHobokenNJ07030USA.

While the use of evidence-based interventions (EBIs) has been advocated by the medical research community for quite some time, uptake of these interventions by healthcare providers has been slow. One possible explanation is that it is challenging for providers to estimate impacts of a specific EBI on their particular organization. To address that concern, we developed and evaluated a type of simulation called a policy flight simulator to determine if it could improve the adoption decision about a specific EBI, the transitional care model (TCM). The TCM uses an advanced practice nurse-led model of care to transition older adults with multiple chronic conditions from a hospitalization to home. An evaluation by a National Advisory Committee, made up of senior representatives from various stakeholders in the U.S. healthcare system, found the policy flight simulator to be a useful tool that has the potential to better inform adoption decisions. This paper describes the simulation development effort and documents lessons learned that may be useful to the healthcare modeling community and those interested in using simulation to support decisions based on EBIs.
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http://dx.doi.org/10.1109/JTEHM.2018.2833847DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5957263PMC
May 2018

Strategic partnerships to address adverse social determinants of health: Redefining health care.

Nurs Outlook 2018 May - Jun;66(3):233-236. Epub 2018 Mar 8.

School of Nursing, University of Pennsylvania, Philadelphia, PA.

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http://dx.doi.org/10.1016/j.outlook.2018.03.002DOI Listing
February 2019

Connect-Home: Transitional Care of Skilled Nursing Facility Patients and their Caregivers.

J Am Geriatr Soc 2017 Oct 16;65(10):2322-2328. Epub 2017 Aug 16.

University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.

Background: Older adults that transfer from skilled nursing facilities (SNF) to home have significant risk for poor outcomes. Transitional care of SNF patients (i.e., time-limited services to ensure coordination and continuity of care) is poorly understood.

Objective: To determine the feasibility and relevance of the Connect-Home transitional care intervention, and to compare preparedness for discharge between comparison and intervention dyads.

Design: A non-randomized, historically controlled design-enrolling dyads of SNF patients and their family caregivers.

Setting: Three SNFs in the Southeastern United States.

Participants: Intervention dyads received Connect-Home; comparison dyads received usual discharge planning. Of 173 recruited dyads, 145 transferred to home, and 133 completed surveys within 3 days of discharge.

Intervention: The Connect-Home intervention consisted of tools and training for existing SNF staff to deliver transitional care of patient and caregiver dyads.

Measurements: Feasibility was assessed with a chart review. Relevance was assessed with a survey of staff experiences using the intervention. Preparedness for discharge, the primary outcome, was assessed with Care-Transitions Measure-15 (CTM-15).

Results: The intervention was feasible and relevant to SNF staff (i.e., 96.9% of staff recommended intervention use in the future). Intervention dyads, compared to comparison dyads, were more prepared for discharge (CTM-15 score 74.7 vs 65.3, mean ratio 1.16, 95% CI: 1.08, 1.24).

Conclusion: Connect-Home is a promising transitional care intervention for older patients discharged from SNF care. The next step will be to test the intervention using a cluster randomized trial, with patient outcomes including re-hospitalization.
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http://dx.doi.org/10.1111/jgs.15015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5666578PMC
October 2017

Policy Research Challenges in Comparing Care Models for Dual-Eligible Beneficiaries.

Policy Polit Nurs Pract 2017 May 24;18(2):72-83. Epub 2017 Jul 24.

4 NewCourtland Center for Transitions and Health, University of Pennsylvania School of Nursing, Philadelphia, PA, USA.

Providing affordable, high-quality care for the 10 million persons who are dual-eligible beneficiaries of Medicare and Medicaid is an ongoing health-care policy challenge in the United States. However, the workforce and the care provided to dual-eligible beneficiaries are understudied. The purpose of this article is to provide a narrative of the challenges and lessons learned from an exploratory study in the use of clinical and administrative data to compare the workforce of two care models that deliver home- and community-based services to dual-eligible beneficiaries. The research challenges that the study team encountered were as follows: (a) comparing different care models, (b) standardizing data across care models, and (c) comparing patterns of health-care utilization. The methods used to meet these challenges included expert opinion to classify data and summative content analysis to compare and count data. Using descriptive statistics, a summary comparison of the two care models suggested that the coordinated care model workforce provided significantly greater hours of care per recipient than the integrated care model workforce. This likely represented the coordinated care model's focus on providing in-home services for one recipient, whereas the integrated care model focused on providing services in a day center with group activities. The lesson learned from this exploratory study is the need for standardized quality measures across home- and community-based services agencies to determine the workforce that best meets the needs of dual-eligible beneficiaries.
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http://dx.doi.org/10.1177/1527154417721909DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7133145PMC
May 2017

Research Priorities to Advance the Health and Health Care of Older Adults with Multiple Chronic Conditions.

J Am Geriatr Soc 2017 Jul 26;65(7):1549-1553. Epub 2017 May 26.

Meyers Primary Care Institute, A Joint Endeavor of University of Massachusetts Medical School, Reliant Medical Group, and Fallon Health, Worcester, Massachusetts.

Objectives: To prioritize research topics relevant to the care of the growing population of older adults with multiple chronic conditions (MCCs).

Design: Survey of experts in MCC practice, research, and policy. Topics were derived from white papers, funding announcements, or funded research projects relating to older adults with MCCs.

Setting: Survey conducted through the Health Care Systems Research Network (HCSRN) and Claude D. Pepper Older Americans Independence Centers (OAICs) Advancing Geriatrics Infrastructure and Network Growth Initiative, a joint endeavor of the HCSRN and OAICs.

Participants: Individuals affiliated with the HCSRN or OAICs and national MCC experts, including individuals affiliated with funding agencies having MCC-related grant portfolios.

Measurements: A "top box" methodology was used, counting the number of respondents selecting the top response on a 5-point Likert scale and dividing by the total number of responses to calculate a top box percentage for each of 37 topics.

Results: The highest-ranked research topics relevant to the health and healthcare of older adults with MCCs were health-related quality of life in older adults with MCCs; development of assessment tools (to assess, e.g., symptom burden, quality of life, function); interactions between medications, disease processes, and health outcomes; disability; implementation of novel (and scalable) models of care; association between clusters of chronic conditions and clinical, financial, and social outcomes; role of caregivers; symptom burden; shared decision-making to enhance care planning; and tools to improve clinical decision-making.

Conclusion: Study findings serve to inform the development of a comprehensive research agenda to address the challenges relating to the care of this "high-need, high-cost" population and the healthcare delivery systems responsible for serving it.
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http://dx.doi.org/10.1111/jgs.14943DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5507733PMC
July 2017

Physical Functioning Among Older Adults New to Long-Term Services and Supports.

Gerontologist 2018 11;58(6):1147-1155

NewCourtland Center for Transitions and Health, School of Nursing, University of Pennsylvania, Philadelphia.

Background And Objectives: To identify determinants of self-reported physical functioning (PF) among older adults new to long-term services and supports (LTSS).

Research Design And Method: Using the International Classification of Function, Disability, and Health (ICF) framework, we conducted a secondary analysis of self-reported data on symptoms, basic/instrumental activities of daily living, quality of life, assistive devices, physical therapy needs, prior healthcare utilization, health status, and demographics from 470 older adults new to LTSS (Home/Community-Based n = 156; Assisted Living n = 156; Nursing Home n = 158). Multiple linear regression was used to identify associations between ICF constructs and self-reported PF (SF-12 Physical Composite Summary score [SF12PCS], lower scores indicate worse PF).

Results: LTSS recipients were mostly female (71%) and over age 80 (Mean: 80.9 years, SD: 8.7). LTSS recipients' mean SF12PCS score was 37.3 (SD 11.0), indicating overall low self-reported PF. LTSS recipients living in their homes (b = -3.35, p = .003) or assisted living facilities (b = -2.93, p = .012) had significantly lower mean scores compared to recipients in nursing homes. Higher SF12PCS scores were associated with fewer activities of daily living deficits (p < .001), and better quality of life (p < .001). Lower scores were associated with more symptoms (p < .001), poorer nutrition (p = .013), ambulation aid use (p < .001), and physical therapy (p < .026).

Discussion And Implications: Diverse health, activity, and environmental factors may facilitate early identification of new LTSS recipients most in need of interventions to optimize self-reported PF. Several health conditions may be targets for such interventions. Additional research is needed to evaluate and compare PF trajectories among older adults receiving LTSS in diverse settings.
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http://dx.doi.org/10.1093/geront/gnx082DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6215465PMC
November 2018

Components of Comprehensive and Effective Transitional Care.

J Am Geriatr Soc 2017 Jun 3;65(6):1119-1125. Epub 2017 Apr 3.

Center for Health Services Research, University of Kentucky, Lexington, Kentucky.

Transitional care (TC) has received widespread attention from researchers, health system leaders, clinicians, and policy makers as they attempt to improve health outcomes and reduce preventable hospital readmissions, yet little is known about the critical elements of effective TC and how they relate to patients' and caregivers' needs and experiences. To address this gap, the Patient-Centered Outcomes Research Institute (PCORI) funded a national study, Achieving patient-centered Care and optimized Health In care transitions by Evaluating the Value of Evidence (Project ACHIEVE). A primary aim of the study is the identification of TC components that yield desired patient and caregiver outcomes. Project ACHIEVE established a multistakeholder workgroup to recommend essential TC components for vulnerable Medicare beneficiaries. Guided by a review of published evidence, the workgroup identified and defined a preliminary set of components and then analyzed how well the set aligned with real-world patients' and caregivers' experiences. Through this process, the workgroup identified eight TC components: patient engagement, caregiver engagement, complexity and medication management, patient education, caregiver education, patients' and caregivers' well-being, care continuity, and accountability. Although the degree of attention given to each component will vary based on the specific needs of patients and caregivers, workgroup members agree that health systems need to address all components to ensure optimal TC for all Medicare beneficiaries.
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http://dx.doi.org/10.1111/jgs.14782DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5497308PMC
June 2017