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University of Pennsylvania

PARC supports highly interdisciplinary research on aging by funding pilot projects, hosting a weekly seminar series and a working paper series, and maintaining a secure data enclave for access to sensitive aging-related data. Research associates conduct research on population and individual processes in the areas of aging, including the determinants and effects of population composition and processes. They are also involved in large data collection projects in the U.S. and abroad.

Research Themes
Health disparities in aging; Early life conditions and older adult health; Behavior and well-being; global aging and health; Health care and long-term care in older adults; Cognition and Alzheimer’s Disease and Related Dementia (ADRD); COVID-19 & Aging.

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Pilot Projects

  • 2023. A. Hamedani. Identifying visual impairment in older adults using administrative claims data.

    Visual impairment is common in older adults and is associated with negative outcomes such as falls,
    depression, anxiety, and cognitive impairment. Because half of all vision loss in the U.S. is
    preventable or treatable, identifying the burden and consequences of age-related visual impairment
    can lead to interventions to promote access to eye care and improve population health.
    Administrative claims data (e.g. Medicare) are an important tool in public health research and have
    been used to study disease prevalence, healthcare utilization, costs, effectiveness, and outcomes
    across many areas of medicine. However, their application to the study of visual impairment and eye
    disease has been limited by the fact that the most important clinical outcomes in ophthalmology
    (namely, visual acuity and vision-related quality of life) are not captured in administrative claims data.
    In this study, we will link Medicare claims data with questionnaire and examination data from the
    National Health and Nutrition Examination Survey (NHANES) to develop and validate a novel visual
    impairment comorbidity index to predict age-related visual impairment using Medicare diagnosis and
    procedure codes. This tool will facilitate a new generation of population-based research on the
    prevalence and health effects of age-related visual impairment using administrative claims datasets.

    Priority Research Areas: Health Trends and Disparities

  • 2023. C. Ma. Understanding the Dynamic Process of Older Adult Behavior Changes for Disaster Preparedness: An Application of the Integrated Transtheoretical Model with Social Cognitive Theory and Protection Motivation Theory.

    Conceptualized as a dynamic process of individual health protective mechanism, disaster
    preparedness is defined as individual behavior changes in this study, from “not prepared” (NP) stage
    to “having an intention to prepare” (IP) stage, and ultimately to “already prepared” (AP) stage.
    Although older adults are much more vulnerable to the health effects of disasters than their middle
    age and young adult counterparts, the extent to which behavioral transitions from one stage to
    another differ across the two groups has not been explored. Integrating the Transtheoretical Model
    (TTM) with Social Cognitive Theory (SCT) and Protection Motivation Theory (PMT), we propose a
    new model to examine a series of specific reasons behind behavior changes for disaster
    preparedness. Using 2022 National Household Survey data (FEMA, 2022), this U.S. population study
    will address the following questions.
    1. Are there disparities in behavior changes for disaster preparedness between older adults and
    non-older adults?
    2. If so, to what extent are these disparities accounted for by income differences between the two
    3. To what extent does personal disaster experience, preparedness awareness, self-efficacy,
    and risk perception each contribute to behavior changes for disaster preparedness, especially when
    people are at different income levels?
    The study also seeks to provide a new statistical method to estimate individual behavior changes in
    departure from the NP stage and in arrival to the AP stage, respectively. To fill the research gap with
    respect to disaster preparedness for older adults (as recently discussed by NIH/NIA [2002]), the
    proposed study aims to identify the specific reasons behind older adults’ decision-making process for
    all-hazards disaster preparedness. We aim to publish our findings from this study in peer-reviewed
    academic journals. Using these results, we will then employ the present process-oriented approach
    and subsequent measurement to study how to support older adults’ preparedness when they are
    exposed in specific hazards (e.g., floodings, wildfires, heatwaves, earthquakes), through extramural
    funding from NIH and/or NSF.

    Priority Research Areas: Consequences of U.S. and Global Aging

  • 2023. I. Elo. Predictors of Cognitive Health in Sub-Saharan Africa: Comparative Perspective from Ghana and Malawi.

    The overall aim of this pilot project is to conduct comparative analyses and generate findings on the
    predictors of cognitive health among older individuals in Ghana and Malawi, two Sub-Saharan African
    countries at different levels of development, Ghana being low-middle-income country and Malawi a
    low-income country. Importantly, these findings will inform planned pilot data collection activities to
    test the Harmonized Cognitive Assessment Protocol (HCAP) in both countries and the integration of
    HCAP in the nationally representative WHO SAGE survey in Ghana. The proposed analyses will
    examine similarities and differences in the association between demographic, socioeconomic, and
    health-related predictors of cognition in Ghana and Malawi. The project activities will also provide an
    opportunity to engage and train a post-doctoral fellow in aging-related research.

    Priority Research Areas: Cognitive Aging and the Demography of Dementia

  • 2023. K. Britt. Spirituality and Brain Health in Older Adults.

    Historically underrepresented populations experience a disproportionate burden of age-related
    cognitive disorders compared to non-White populations. As a salient resource for coping in Black
    communities, spirituality may be associated with better brain health, yet research is limited, especially
    in this population. This study aims to examine: 1) associations between spirituality and cognition, 2)
    identify possible differences across racial groups and, 3) explore the role of spirituality as a
    moderator between AD blood biomarkers and cognition. I hypothesize a relationship exists between
    (a) spirituality and specific cognitive domains including executive function and memory, (b) the
    protective effect of spirituality on cognition will be stronger in Black individuals, and (c) higher
    spirituality will attenuate the association between AD blood biomarkers and cognition. Using
    secondary data from the Penn AD Research Center and Memory Centers, we will use multivariate
    regression with moderation analyses to elucidate spirituality as a potential resilience factor in minority
    brain health.

    Priority Research Areas: Cognitive Aging and the Demography of Dementia

  • 2023. P. Ho. Alcohol Use, Genetics, and Cognitive Decline.

    Alcohol use disorder (AUD) is one of the most pronounced public health concerns in the U.S. and
    cause an enormous burden to the society. In 2019, 14.5 million people of age 12 and older have AUD
    but only 7.2% of them had received treatment in the past year. Moreover, AUD may be correlated with
    cognitive decline and dementia could be a onerous burden to Individuals, family members, and the
    society. Both alcohol consumption and cognitive decline are often correlated to many unoberved
    factors such as genetics, personality traits, and risk perception therefore resulting in endogneity
    concerns. To tackle the endogeneity concerns, this project proposes to study the alcohol consumption
    of individuals of age 50 and older from the genetic perspective, which is pre-determined, and its
    association with cognitive decline. The development in genome-wide association studies (GWAS) in
    past decades provide a straightforward method to summarize the genetic tendency of a certain trait
    (e.g., alcohol consumption) by calculating a Polygenic score (PGS). A higher PGS refers to a higher
    genetic tendency of a trait. We first aim to establish the association between alcohol consumption
    PGS and the rate of cognitive decline to alleviate the endogeneity of drinking behaviors. To further
    characterize the effects of alcohol consumption on cognitive decline, we identify stressful events (e.g.,
    unemployment, divorce) and investigate how individuals respond to stressful events by changing their
    alcohol consumption. The frequencies and spacingof stressful events can facilitate dose response
    analyses. We then explore the genetic correlations between alcohol consumption and other traits
    (e.g., depression, bipolar, smoking behaviors, and personality traits) that often co-exist with AUD to
    obtain a clear picture of AUD, common comorbidities of AUD, and cognitive decline. Alcohol
    consumption, as a risk factor of many diseases, is modifiable via behavior modifications. Thus, we
    next investigate how education and social interactions may interact with alcohol consumption, which
    may shed light on behavior modification targets.

    Priority Research Areas: Biology, Genetics and Demography of Aging

  • 2022. C. Leonard. Effect of outdoor temperature and air pollution on the comparative safety of antihyperglycemic therapies.

    Diabetes exacts a profound societal cost in terms of morbidity, disability, and mortality. As climate
    change progresses and further magnifies the negative impacts of extreme outdoor temperatures and air
    pollution on health, there is urgency in the need for adaptable and personalized diabetes care. Natural
    environmental factors like extreme temperatures and pollution are known to be associated with serious adverse
    health outcomes in persons with type 2 diabetes; these include hypoglycemia (very low blood sugar), diabetic
    ketoacidosis (very high blood ketones), and cardiovascular events (like heart arrhythmias). The most vulnerable
    and disadvantaged populations tend to be hardest hit by climate change and are least equipped to combat its
    effects, and there is substantial overlap between these populations and Medicaid recipients. Furthermore,
    Medicaid recipients are diagnosed with diabetes and hospitalized for diabetes-related adverse health outcomes
    at higher rates than the general US population.
    Personalized diabetes care involves selecting the best therapy based on patient characteristics.
    Unfortunately, clinical trials comparing diabetes drugs have not examined interactions with outdoor temperature
    or air pollution, and are underpowered to do so. This presents a major knowledge gap for efforts to incorporate
    natural environmental factors into personalized diabetes care. While innovative, the inclusion of environmental
    factors in clinical decision-making has precedent, and is even anticipated in the treatment of diabetes.
    To address this knowledge gap, we recently submitted an R01 application to examine the roles of outdoor
    temperature and air pollution on the comparative safety of diabetes drugs in persons with type 2 diabetes. We
    proposed to conduct pharmacoepidemiologic studies by linking federal environmental datasets to Department
    of Health and Human Services healthcare data for the entire US Medicaid (and Medicare) populations residing
    in the conterminous US. We proposed to examine the effects of outdoor temperature and air pollution on rates
    of serious hypoglycemia, diabetic ketoacidosis, and serious arrhythmia, within and among incident users of
    different diabetes drug classes. Our Quartet application proposes to generate pilot data to bolster an R01
    resubmission, recommended by our NIDDK Program Official, by demonstrating proof-of-concept by linking
    environmental to healthcare data for Medicaid beneficiaries with type 2 diabetes, then using this dataset to: a)
    examine temperature and pollution variability by beneficiary ZIP code of residence; b) examine rates of the
    above-named health outcomes by temperature and pollution; and c) demonstrate variability in outcome rates
    among users of different diabetes drug regimens. These pilot data will enable us to directly respond to
    summary statement feedback and improve the fundability of our proposed, innovative R01 that would
    incorporate natural environmental factors to improve health in persons with diabetes.

    Priority Research Areas: Health Trends and Disparities

  • 2022. G. Nave. Biological age and its value for behavioral and decision science.

    The proposed project draws on recent advances in bio-informational research, with an aim to
    investigate how a new type of measurement—called “epigenetic clocks”, which quantifies biological
    processes related to aging (i.e., biological age)—can better our understanding of individuals’
    judgments and decisions. At this time, epigenetic clocks have been previously used in medical
    research to understand the aging process and human lifespan, and such measures have been shown
    to be better at capturing variability in biological aging processes than chronological age. In this
    project, we will partner with one of the largest firms in the US selling epigenetic testing kits,
    TruDiagnostic, and, leveraging their existing customer base (~15,000 individuals with epigenetic
    data), survey participants on a variety of psychological tasks relevant to the aging process, such as
    temporal discounting, risk taking, cognitive reflection, and personality change over the lifespan. Using
    survey measures combined with epigenetic data, we seek to differentiate the contribution of biological
    aging from other non-biological aging-related measures (such as chronological age), and empirically
    disentangle their effects on psychological well-being as well as other meaninful outcomes. Funding
    from this grant will be used for participant incentives.

  • 2022. K. Auriemma. Using hospital-free days to understand the impact of lung allocation policy changes on older lung transplant recipients.

    Background: Changes in US lung allocation policies in 2005 and 2017 increased transplants among
    the sickest and oldest candidates on the waitlist. The impacts of these policy changes on health care
    utilization and quality of life are not known. Assessing hospital-free days (HFDs) among transplant
    recipients will provide a better assessment of the post-transplant survivorship experience than simple
    measures of mortality.
    Objectives: To better understand the consequences of changes in lung allocation policy and inform
    future decision making.
    Specific Aims: (1) To quantify temporal changes in HFDs among lung transplant recipients. (2) To
    determine the impact of May 2005 and November 2017 lung allocation score policy changes on HFDs
    in older relative to younger lung transplant recipients.
    Design: We will create a retrospective cohort of Penn lung transplant recipients from 2000 to 2020 by
    merging Penn data with regional utilization data and data from the Lung Transplant Outcomes Group.
    Methods: Median HFDs, defined as all days alive spent outside of an acute-care hospital, long-term
    acute-care hospital, or emergency department, will be calculated at 365 days post-transplant for each
    year of the study. We will identify patient characteristics associated with greater attainment of HFDs.
    We will use an interrupted time-series design to compare HFDs before and after major lung allocation
    policy changes and determine how these changes differed among older relative to younger patients.
    Impact: This study will generate key preliminary data for a planned NIH R01 proposal to assess the
    impact of previous and future LAS policy changes on HFDs nationally and to assess changes in
    patient function and quality of life. Future work will integrate those measures into quality-weighted

    Priority Research Areas: Disability, Health Care and Long-Term Care

  • 2022. K. Miller. Impacts of the COVID-19 Pandemic on Youth and Young Adult Caregivers.

    A growing proportion of individuals provide unpaid care to family members and friends (i.e., are family
    caregivers). Among younger individuals, an estimated 12.7 million young adults (ages 18-34) and 5.4
    million youth (aged <18) are family caregivers. As the ongoing COVID-19 pandemic has increased
    disability and comorbidities, it follows an increasing number of young adults and youths may
    undertake the role of family caregiver. Potential increases in young adult/youth caregiving
    responsibilities are of major concern because caregiving is associated with adverse mental, physical,
    and financial outcomes. Additionally, because the pandemic has disproportionately impacted
    historically marginalized communities, younger adults/youth of historically marginalized populations
    may disproportionately become family caregivers; thus, existing mental, physical, and financial
    disparities may be exacerbated. Little evidence exists quantifying the impact of the COVID-19
    pandemic on the proportion of young adults/youths acting as caregivers and the intensity of their
    caregiving. The overall objectives of this pilot study are to estimate the prevalence of and describe
    the impact of the COVID-19 pandemic on young adult/youth caregivers. This research will advance
    our understanding of young adult/youths acting as family caregivers.

    Priority Research Areas: Health Trends and Disparities

  • 2022. M. Dougherty. Improving the Outcomes of Older Adult Surgical Patients with Prolonged Surgical Time: Evaluating Modifiable Hospital Nursing Resources.

    More older adults in the United States are undergoing inpatient surgery than ever before. Older age is a risk factor for greater morbidity and mortality following surgery; therefore, improving the surgical care and outcomes of older adults warrants attention. In this proposal, we focus on one concerning adverse surgical event which is particularly threatening to the postoperative recovery of older adults—prolonged surgical time. Prolonged surgical time is associated with complications including a greater risk of death, longer stays in the hospital, and other poor outcomes including venous thromboembolism, anemia, and sepsis. The current literature on outcomes of older adults with prolonged surgical time is limited to descriptive research and offers no evidence about prevention or early intervention of complications should they occur. The proposed study seeks to examine the outcomes of older adult surgical patients that experience prolonged surgical time and modifiable nursing resources within hospitals. Decades of research has shown that when nurses at the bedside are adequately staffed and practice in environments that allow for nurse autonomy and teamwork with physician colleagues, patients are more likely to have favorable postoperative outcomes. The benefits of these good nursing resources are most pronounced among patients with the highest clinical risk, which lends credence to our hypothesis that favorable staffing ratios and supportive work environments will be especially beneficial to older adults with prolonged surgical time. The proposed study addresses the following aims: 1) to evaluate whether and to what extent differences in hospital nursing resources (i.e., patient-to-nurse staffing ratios, work environment) are associated with outcomes of older adult surgical patients with and without prolonged surgical time and 2) to determine whether the effects of hospital nursing resources on older adult surgical patient outcomes are conditional on surgical time. This study will use multiple linked secondary data sources including patient data from the Centers from Medicare and Medicaid Services (CMS), hospital data about nursing resources from the RN4CAST survey of nurses, and data of hospital structural characteristics from the American Hospital Association Annual Survey. Datasets will be linked by hospital identifiers common to all datasets. We anticipate the patient sample will include 800,000 older adult surgical patients, 65 years old or older, which will be representative of approximately 160 surgical procedures and approximately 500 hospitals. Findings obtained from this study will support a burgeoning program of research to inform targeted interventions for improving the care and outcomes of high-risk older adult surgical patients.

    Priority Research Areas: Disability, Health Care and Long-Term Care

  • 2021. C. Boen. Uneven Spillover Effects of Police Violence: Police Shootings and Disparities in Emotional Well-Being.

    In 2018, 992 people were shot and killed by the police in the United States. Black men are at particularly high risk of deadly police violence relative to other groups. In addition to direct consequences of this violence, studies document a host of spill-over effects of police violence, including decreased trust in the police and increased legal cynicism. Given racial disparities in risk of police violence and a broader context of structural racism in the U.S., the collateral consequences of this violence are magnified for Black communities. Now, with the rise of portable video recorders and social media, police violence that was only observed in situ is recorded and broadcast to a global audience, made viral, and viewed repeatedly, broadening the potential reach of these spillover effects. At the same time, forms of social connectivity like Twitter offer individuals platforms for expressing their emotions in real time, offering researchers valuable insight into the effects of widely publicized events, including police violence. A growing body of research aims to identify the spillover effects of police violence, but critical gaps in scientific understanding of the role of police violence in shaping emotional and psychological outcomes—as well as population disparities in well-being—remain. The proposed project improves scientific understanding of the population impacts of police violence by using a corpus of text data from Twitter and computational text analysis to evaluate the emotional spillover effects of police violence and assess racial-ethnic, gender, age, and geographic variation in the associations between police violence and emotional well-being. The project uses longitudinal data, a quasi-natural experiment design, and two cases—the shootings of Michael Brown and Tamir Rice—to assess whether and how police violence affects the emotional well-being of individuals, paying particular attention to the stress-related psychological processes undergirding these links as well as differential vulnerability to these events. This project will expand and shift scholarship on police violence and population disparities in well-being in three key ways. First, this study leverages big data and cutting-edge computational methods to examine the impacts of police violence on population well-being. While most research in this area relies on survey data, our use of Twitter data will allow for improved understanding of how these events shape individual and population well-being in real time. Second, we use a quasi-experimental design and difference-in-difference models to assess the links between police violence and emotional well-being, thereby improving our ability to make causal inferences. Finally, we use a variety of techniques to code sociodemographic characteristics and test for differential vulnerability of exposure to police violence by race, gender, age, and geography, providing new evidence of the role of police violence in shaping inequities in emotional and psychological well-being. Findings from this study will generate new understandings of the spillover effects of police violence, particularly as these events shape individual emotions in ways that relate to individual health and contribute to population health disparities. Results from this project will be inform applications for subsequent extramural funding focused on the links between police violence, emotions, and population disparities in psychological well-being.

    Priority Research Areas: Determinants of Health, Well-Being and Longevity

  • 2021. C. Low. Reproductive Disability: The Link Between Infertility and Economic Well-Being for Women in Zambia.

    It is widely acknowledged that disability results in a permanent downward shift in worker’s incomes, and thus consumption. In other words, workers are not fully insured against these negative shocks in labor market productivity. There is much less attention to another form of disability, that of secondary infertility, which may affect women economically if they are partly dependent on male partners for economic support. In this project, I will test whether infertility materially impacts women’s economic well-being similarly to how worker disability affects their earnings. The long-term plan for this project is to collect longitudinal data over a two-year period on 1,000 women in Zambia to measure how consumption, health, and economic wellbeing co-move with fecundity and spousal expectations of fecundity. The longitudinal data will allow an event study analysis with individual fixed effects to show that the onset of infertility, or “reproductive disability” is associated with a loss of consumption and economic wellbeing. In the initial pilot phase, I will begin enrolling the first 400 women in the survey, as well as analyze existing DHS data in Zambia to demonstrate the connection between infertility and loss of consumption.

    Priority Research Areas: Disability, Health Care and Long-Term Care

  • 2021. R. Greysen. Gamification to Improve Physical Activity in Seniors at Risk for Alzheimer's.

    Increased physical activity by walking further or more vigorously may delay the development of Alzheimer’s Disease and Related Dementias (ADRD) and associated cognitive decline but reaching higher levels of activity and maintaining it as a long-term habit is difficult to do. This project will use concepts from behavioral science to create a mobility game that people at risk for developing ADRD can play in order to increase their levels of activity while having fun doing it. The game is played with a support partner who is a spouse, family member, or close friend who provides feedback and encouragement to help the game-player reach activity goals and maintain them as habits over time. Participants in the game will use their own smartphone and a wristwatch that tracks activity (such as a FitBit, provided by this study) to set goals, get feedback, and play the game for 12 weeks. Participants will be asked to continue wearing the wristwatch for another 6 weeks to track activity after the game is over. To determine the effectiveness of this game, we will randomly assign 50 people to the game and 50 people to only get the wristwatch but no game component. All participants in this study will be recruited from the GeneMatch registry which offers genetic testing on risk for ADRD to all participants. We will recruit participants to our study who have elevated genetic risk as well as those without specific genetic risks to see if either group responds differently to the game. The short-term goal of this study is to determine the feasibility of remotely recruiting and engaging older adults at high risk for developing ADRD from an existing Alzheimer’s cohort study. We hypothesize that we will be able demonstrate the efficacy of gamification to increase physical activity in this pilot population as well as explore differential effects of high-risk genotypes and demonstrate the ability to collect functional and cognitive measures remotely. These results will enable competitive applications for larger studies (NIA R01) immediately after the completion of this pilot. The long-term goal for this project is to launch a successful new line of inquiry into physical activity in patients with ADRD by adapting and applying behavioral economics approaches such as gamification which have been successfully developed for other populations.

    Priority Research Areas: Effects of Interventions on Population Health

  • 2021. W. Roth. How Does Genetic Ancestry Testing Affect Perceptions of Race?.

    The proposed research will evaluate the relative influence of genomic, phenotypic, social attributes, and social context in shaping how individuals perceive other people’s race, to determine how genomic information is influencing societal norms of racial classification. The larger project will conduct a conjoint survey experiment that includes unique morphed photographs, information about genetic ancestry test (GAT) results, and social attributes like racial self-identification before and after testing, to influence the racial classification of others by White, Black, Hispanic, and Asian respondents. The pilot project will develop and test the morphed photographs to be used as the visual stimuli in the experiment. GATs are one of the most common ways that genomic awareness has increased in the public sphere. Many scholars believe GATs will shape individuals’ beliefs about race, including beliefs in essential racial differences and that races are genetically determined. Recent research shows that GATs lead some people to change their racial identity based on the reported genetic information. However, we know little about whether those genetically-influenced identity claims are accepted by others or whether information about an individual’s genetic ancestry influences how their race is perceived. Increased genomic knowledge may be shifting norms of racial classification. This could have significant social implications ranging from demographic shifts and identity-based political mobilization to changing patientprovider interactions and assessments in healthcare settings. In everyday life, people typically rely on phenotype to racially classify others, often using it as a proxy for ancestry. However, we know little about how the perception of phenotype interacts with information about ancestry, which we will test using photographs of human faces and hypothetical GAT results. In addition, an abundant scholarship has shown that race is shaped by social context. Nevertheless, most studies have been observational and may be afflicted by endogeneity. We will provide rigorous experimental evidence for how the social context influences racial classifications: some respondents will be asked to categorize individuals seeking membership in a cultural affinity group; others will be told the individual is applying to college, priming a context of competition for scarce resources; the remainder will be given a neutral context. Last, our nationally representative survey will sample Black, White, Asian, and Hispanic respondents, which will allow us to test how racial perceptions vary across the U.S. and among the nation’s largest ethnoracial groups. This project will develop a research protocol and preliminary data for a larger future study focusing on how genomic information shapes healthcare providers’ racial perceptions and clinical assessments of patients.

    Priority Research Areas: Biology, Genetics and Demography of Aging

  • 2020. I. Kohler. Comparative Cognitive Health Changes in Low-Income Settings.

    This projects overall aim is to lay foundations for a program application to examine for the first time individual variation and age-related changes in cognitive health in mature adults across non-WEIRD (Western, Educated, Industrialized, Rich, Democratic), low-income populations with the ultimate goal to understand if cognitive aging follows universal trajectories and/or is determined by environmentally dependent mechanisms. The project focuses on comparative analysis of longitudinal data on cognition among mature adults using data sets covering substantial segments (at least two decades) of the life-cycle in three very distinct relatively low-income populations in Bolivia, Guatemala, and Malawi.

    Priority Research Areas: Cognitive Aging and the Demography of Dementia

  • 2020. M. Candon. Understanding Nursing Turnover: The Case of Home Health.

    High levels of turnover in professions that rely heavily on skill acquisition is a major source of inefficiency due to productivity loss, termination costs, vacancy, orientation and training, and other spillovers. Turnover among nurses, a bedrock in health care, is a particular concern given the amount of direct care they provide patients – indeed, compromised nursing care has been associated with longer lengths of stay and higher rates of adverse outcomes, including mortality. To date, most studies of nursing turnover have focused on inpatient nurses in hospitals using self-reported survey data and are therefore limited in scope. No projects have been able to cleanly connect nurses to patients, making it impossible to understand the full impact of nursing turnover. This project will leverage a collaborative agreement between the University of Pennsylvania and Encompass Home Health, which is one of the largest home health agencies in the country, currently operating in 30 states. We will acquire a host of different datasets from Encompass to answer two main questions: first, which factors drive nursing turnover in home health; and second, how does nursing turnover in home health affect patient outcomes such as hospitalizations and mortality? Using variables constructed from human resources, payroll, visit logs, and other secondary data sources, we will include a host of potential factors that may drive turnover, e.g., driving time, patient acuity, and outside labor market opportunities, in order to construct an algorithm that can flag nurses at high risk of turnover. This will allow for more tailored personnel interventions to improve retention among home health nurses at Encompass. Next, we will use these unique data to explore the confounded relationship between nursing turnover and patient outcomes. Because home health nurses work alone or in tandem with other provider types, we are able to connect individual nurses to individual patients. That, along with more rigorous statistical approaches, gives us an unprecedented opportunity to pin down the causal pathway between nursing turnover and patient care.

    Priority Research Areas: Disability, Health Care and Long-Term Care

Center-Supported Publications

Center Administrator: Abby Dolinger