Publications by authors named "Claudia Nau"

Article Synopsis
  • Firearm injuries are a significant public health issue, though they are infrequent occurrences in healthcare settings.
  • The study created a predictive model using electronic health records from Kaiser Permanente Southern California to identify adults at high risk for firearm injury, analyzing over 170 factors related to demographics and socioeconomic status.
  • The model demonstrated a sensitivity of 0.83 but a lower specificity of 0.56, allowing for more focused screening efforts by identifying a high-risk group that could streamline prevention initiatives.
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Background: Food insecurity is associated with poor glycemic control and increased risk for diabetes-related complications. The clinical benefit of addressing these challenges through a medically supportive grocery prescription (GRx) program in patients with type 2 diabetes mellitus (T2D) remains unclear. We report the aims and design of a randomized clinical trial to evaluate the effectiveness of a 6-month GRx intervention on hemoglobin A1c (HbA1c) levels among low-income adults with T2D.

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Purpose: The purpose of this study is to evaluate the associations between neighborhood income, education, and neighborhood racial composition (measured as a low percentage of white residents) and risk of developing cardiovascular diseases (CVD), diabetes (DM), and severe depression among survivors of AYA cancer and matched non-cancer peers.

Methods: Two-year survivors of AYA cancers diagnosed at age 15-39 yrs at Kaiser Permanente Southern California (diagnosed 2000-2012) and individually matched (1:13) non-cancer subjects were included. The development of CVD, DM, and severe depression was ascertained via electronic health records.

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Objectives: Collaborative care (CC) has demonstrated effectiveness for improving late-life depression in primary care, but clinics offering this service can find it challenging to address unmet social needs that may be contributing to their patients' depression. Clinics may benefit from better coordination and communication with community-based organizations (CBO) to strengthen depression treatment and to address unmet social needs. We evaluated the feasibility of adding a CBO to enhance standard collaborative care and the impact of such partnered care on older adults.

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Article Synopsis
  • Researchers developed the COVID Hospitalized Patient Deterioration Index (COVID-HDI) to better predict serious health declines in hospitalized COVID-19 patients, improving on an existing model not tailored for respiratory issues related to the virus.
  • The study involved analyzing data from COVID patients at Kaiser Permanente Southern California, applying machine learning techniques and various predictors to create an effective model for identifying high-risk patients.
  • With a high accuracy rate (0.83) and the ability to classify 74% of patients as low-risk during hospitalization, COVID-HDI aids in clinical decisions regarding patient discharge and care escalation.
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Background: Firearm injury is a significant public health concern in the United States.

Methods: Data on fatal and nonfatal firearm injuries were obtained from a cohort of N = 7,473,650 members of Kaiser Permanente Southern California, a large integrated healthcare system between 2010 and 2020. Age-adjusted rates of combined fatal and nonfatal firearm injury per 100,000 members were calculated by year, with the 2010 US census as the reference population.

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Objective: To understand how race and serious mental illness (SMI) interact for disruptive life events defined as financial (bankruptcy and judgement filings), and non-financial (arrests).

Methods: Patients were adults with schizophrenia (SCZ; N = 16,159) or bipolar I disorder (BPI; N = 30,008) matched 1:1 to patients without SMI (non-SMI) from health systems in Michigan and Southern California during 1/1/2007 through 12/31/2018. The main exposure was self-reported race, and the outcome was disruptive life events aggregated by Transunion.

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Article Synopsis
  • Efficient identification of social risks in seriously ill patients is vital for delivering patient-centered care, particularly for those who may be homeless or at risk of homelessness.* -
  • A natural language processing (NLP) algorithm was refined and applied to electronic health records, successfully identifying 1,737 out of 206,993 patients with serious illnesses as homeless or at risk.* -
  • The updated algorithm demonstrated high accuracy, with a sensitivity of 100% and a positive predictive value of 93.8%, indicating its potential for targeting interventions for these vulnerable patients.*
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Objective: To examine whether gentrification exposure is associated with future hypertension and diabetes control.

Methods: Linking records from an integrated health care system to census-tract characteristics, we identified adults with hypertension and/or diabetes residing in stably low-SES census tracts in 2014 (n = 69,524). We tested associations of census tract gentrification occurring between 2015 and 2019 with participants' disease control in 2019.

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Importance: Recent evidence links air pollution to the severity COVID-19 symptoms and to death from the disease. To date, however, few studies have assessed whether air pollution affects the sequelae to more severe states or recovery from COVID-19 in a cohort with individual data.

Objective: To assess how air pollution affects the transition to more severe COVID-19 states or to recovery from COVID-19 infection in a cohort with detailed patient information.

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Importance: There is a dearth of population-level data on major disruptive life events (defined here as arrests by a legal authority, address changes, bankruptcy, lien, and judgment filings) for patients with bipolar I disorder (BPI) or schizophrenia, which has limited studies on mental health and treatment outcomes.

Objective: To conduct a population-level study on disruptive life events by using publicly available data on disruptive life events, aggregated by a consumer credit reporting agency in conjunction with electronic health record (EHR) data.

Design, Setting, And Participants: This study used EHR data from 2 large, integrated health care systems, Kaiser Permanente Southern California and Henry Ford Health.

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Importance: Unaffordable housing is associated with adverse health-related outcomes, but little is known about the associations between moving due to unaffordable housing and health-related outcomes.

Objective: To characterize the association of recent cost-driven residential moves with health-related outcomes.

Design, Setting, And Participants: This cross-sectional study involved a weighted multivariable regression analysis of California Health Interview Survey data from January 1, 2011, to December 31, 2017.

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Background: Recent evidence links ambient air pollution to COVID-19 incidence, severity, and death, but few studies have analyzed individual-level mortality data with high quality exposure models.

Methods: We sought to assess whether higher air pollution exposures led to greater risk of death during or after hospitalization in confirmed COVID-19 cases among patients who were members of the Kaiser Permanente Southern California (KPSC) healthcare system (N=21,415 between 06-01-2020 and 01-31-2022 of whom 99.85 % were unvaccinated during the study period).

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Introduction: Physical activity before COVID-19 infection is associated with less severe outcomes. The study determined whether a dose‒response association was observed and whether the associations were consistent across demographic subgroups and chronic conditions.

Methods: A retrospective cohort study of Kaiser Permanente Southern California adult patients who had a positive COVID-19 diagnosis between January 1, 2020 and May 31, 2021 was created.

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Importance: Health care research on racial disparities among children and youths has historically used the White race as a reference category with which other racial and ethnic groups are compared, which may inadvertently set up Whiteness as a standard for health.

Objective: To compare 2 interpretations of an analysis of racial disparities in speech therapy receipt among children and youths with developmental disabilities: a traditional, White-referenced analysis and a Hispanic majority-referenced analysis.

Design, Setting, And Participants: This cross-sectional study used multiple logistic regression to analyze speech therapy referrals for children, adolescents, and transition age youths in an integrated health care system in Southern California from 2017 to 2020.

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Background And Objectives: Few studies have tested multiple socio-ecological risk factors assocated with firearm injury among pediatric populations and distinguished self-inflicted from non-self-inflicted injury. To address this gap, the current study examined demographic, individual psychosocial, and neighborhood variables as risk factors for firearm injury among a large cohort of children and adolescents.

Methods: Retrospective cohort study.

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Purpose: Because social conditions such as food insecurity and housing instability shape health outcomes, health systems are increasingly screening for and addressing patients' social risks. This study documented the prevalence of social risks and examined the desire for assistance in addressing those risks in a US-based integrated delivery system.

Methods: A survey was administered to Kaiser Permanente members on subsidized exchange health insurance plans (2018-2019).

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Objective: To evaluate whether a natural language processing (NLP) algorithm could be adapted to extract, with acceptable validity, markers of residential instability (ie, homelessness and housing insecurity) from electronic health records (EHRs) of 3 healthcare systems.

Materials And Methods: We included patients 18 years and older who received care at 1 of 3 healthcare systems from 2016 through 2020 and had at least 1 free-text note in the EHR during this period. We conducted the study independently; the NLP algorithm logic and method of validity assessment were identical across sites.

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Background: Serious illness often causes financial hardship for patients and families. Home-based palliative care (HBPC) may partly address this.

Objective: Describe the prevalence and characteristics of patients and family caregivers with high financial distress at HBPC admission and examine the relationship between financial distress and patient and caregiver outcomes.

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Background: Asthma exerts a substantial burden on patients and health care systems. To facilitate preventive care for asthma management and improve patient outcomes, we recently developed two machine learning models, one on Intermountain Healthcare data and the other on Kaiser Permanente Southern California (KPSC) data, to forecast asthma-related hospital visits, including emergency department visits and hospitalizations, in the succeeding 12 months among patients with asthma. As is typical for machine learning approaches, these two models do not explain their forecasting results.

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Background: The American Community Survey (ACS) is the largest household survey conducted by the US Census Bureau. We sought to describe the community-level characteristics derived from the ACS among enrollees of Kaiser Permanente Southern California (KPSC), evaluate the associations between ACS estimates and selective individual-level health outcomes, and explore how using different scales of the census geography and the linearity assumption affect the associations.

Methods: We examined the associations between track-level and block group-level ACS 5-year estimates and 4 individual-level Healthcare Effectiveness Data and Information Set (HEDIS) outcome measures (comprehensive diabetes care, postpartum care, antidepressant medication management, and childhood immunization status) using multilevel generalized linear models.

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Objective: Develop and validate a risk score using variables available during an Emergency Department (ED) encounter to predict adverse events among patients with suspected COVID-19.

Methods: A retrospective cohort study of adult visits for suspected COVID-19 between March 1 - April 30, 2020 at 15 EDs in Southern California. The primary outcomes were death or respiratory decompensation within 7-days.

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Purpose: The purpose of this study was to characterize the differences in myopic progression in children by race/ethnicity and age.

Methods: Patients enrolled in Kaiser Permanente Southern California between 2011 and 2016 and between the ages of 4 and 11 years old with a documented refraction between -6 and -1 diopters (Ds) were included in this retrospective cohort study. Patients with a history of amblyopia, strabismus, retinopathy of prematurity, or prior ocular surgery were excluded from analyses.

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