Endocrine therapy initiation among women diagnosed with ductal carcinoma in situ from 2001 to 2018.

PURPOSE: Trials demonstrating benefits of tamoxifen for women with ductal carcinoma in situ (DCIS) were published > 20 years ago; yet subsequent uptake of endocrine therapy was low. We estimated endocrine therapy initiation in women with DCIS between 2001 and 2018 in a community setting, reflecting more recent years of diagnosis than previous studies. METHODS: This retrospective cohort included adult females ≥ 20 years diagnosed with first primary DCIS between 2001 and 2018, followed through 2019, and enrolled in one of three U.S. integrated healthcare systems. We collected data on endocrine therapy dispensings (tamoxifen, aromatase inhibitors [AIs]) from electronic pharmacy records within 12 months after DCIS diagnosis. Using generalized linear models with a log link and Poisson distribution, we estimated endocrine therapy initiation rates over time and by patient, tumor (including estrogen receptor [ER] status), and treatment characteristics. RESULTS: Among 2020 women with DCIS, 587 (29%) initiated endocrine therapy within 12 months after diagnosis (36% among 1208 women with ER-positive DCIS). Among women who used endocrine therapy, 506 (86%) initiated tamoxifen and 81 (14%) initiated AIs. Age-adjusted endocrine therapy initiation declined from 34 to 21% between 2001 and 2017; between 2015 and 2018, AI use increased from 8 to 35%. Women less likely to initiate endocrine therapy were ER-negative or had borderline/unknown or no ER test results, ≥ 65 years at diagnosis, Black, and received no radiotherapy. CONCLUSION: One-third of women diagnosed with DCIS initiated endocrine therapy, and use decreased over time. Understanding why women eligible for endocrine therapy do not initiate is important to maximizing disease-free survival following DCIS diagnosis.

Sex/Gender Disparities in Preemptive Referrals for Kidney Transplantation.

Introduction: Sex/gender inequities persist in access to kidney transplantation. Whether differences in preemptive referral (i.e., referral before dialysis start) explain this inequity remains unknown. Methods: All adults (aged 18-79 years; N = 44,204) initiating kidney replacement therapy (KRT; dialysis or transplant) in Georgia (GA), North Carolina (NC), or South Carolina (SC) between 2015 and 2019 were identified from the United States Renal Data System (USRDS). Individuals were linked to the Early Steps to Kidney Transplant Access Registry (E-STAR) to obtain data on preemptive referral and followed-up with through November 13, 2020, for outcomes of waitlisting and living donor transplant. Logistic regression assessed the association between sex/gender and likelihood of preemptive referral among all KRT patients. Cox-proportional hazards assessed the association between sex/gender and waitlisting or living donor among preemptively referred patients. Results: Overall, men and women were similarly likely to be preemptively referred (odds ratio [OR]: 0.99 [0.95-1.04]). Preemptively referred women (vs. men) were, on average, younger and with fewer comorbidities. There were no sex/gender differences in waitlisting once patients were preemptively referred (hazard ratio [HR]: 0.97 [0.91-1.03]); however, women (vs. men) who were preemptively referred remained 25% (HR: 0.75 [0.66-0.86]) less likely to receive a living donor transplant. Conclusion: In the Southeast US, men and women initiating KRT are similarly likely to be preemptively referred for a kidney transplant, and this appears, at least in part, to mitigate known sex/gender inequities in access to waitlisting, but not living donor transplant. Despite this, preemptively referred women, on average, had a more favorable medical profile relative to preemptively referred men.

Access to telehealth and changes in diabetes care patterns during the pandemic: evidence from a large integrated health system in the Southeast USA.

INTRODUCTION: To examine the role of telehealth in diabetes care and management during versus pre-COVID-19 pandemic. RESEARCH DESIGN AND METHODS: We included adults (≥18 years) with prevalent diabetes as of January 1, 2018, and continuously enrolled at Kaiser Permanente Georgia through December 31, 2021 (n=22,854). We defined pre (2018-2019) and during COVID-19 (2020-2021) periods. Logistic generalized estimating equations (GEEs) assessed the within-subject change in adherence to seven annual routine care processes (blood pressure (BP), hemoglobin A1C (HbA1c), cholesterol, creatinine, urine-albumin-creatinine ratio (UACR), eye and foot examinations) pre versus during COVID-19 among telehealth users (ie, more than one telehealth visit per year per period) and non-telehealth users. Linear GEE compared mean laboratory measurements pre versus during COVID-19 by telehealth use. RESULTS: The proportion of telehealth users increased from 38.7% (2018-2019) to 91.5% (2020-2021). During (vs pre) the pandemic, adherence to all care processes declined in telehealth (range: 1.6% for foot examinations to 12.4% for BP) and non-telehealth users (range: 1.9% for foot examinations to 40.7% for BP). In telehealth users, average HbA1c (mean difference: 0.4% (95% CI 0.2% to 0.6%), systolic BP (1.62 mm Hg (1.44 to 1.81)), and creatinine (0.03 mg/dL (0.02 to 0.04)), worsened during (vs pre) COVID-19, while low density lipoprotein (LDL) cholesterol improved (-9.08 mg/dL (-9.77 to -8.39)). For UACR, odds of elevated risk of kidney disease increased by 48% (OR 1.48 (1.36-1.62)). Patterns were similar in non-telehealth users. CONCLUSIONS: Telehealth use increased during the pandemic and alleviated some of the observed declines in routine diabetes care and management.

Racial Disparities in COVID-19 Severity Are Partially Mediated by Chronic Stress-Evidence from a Large Integrated Healthcare System.

BACKGROUND: Racial and ethnic minorities have experienced a disproportionate burden of severe COVID-19. Whether chronic stress, also disproportionately experienced by racial and ethnic minorities, explains this excess risk is unknown. METHODS: We identified 9577 adults (≥ 18 years) diagnosed with COVID-19 from January 1, 2020, through September 30, 2021, enrolled in Kaiser Permanente Georgia (KPGA) with complete biomarker data. Self-reported race (Black or White) was defined from electronic medical records. Chronic stress, defined as allostatic load (AL), a composite score (scale 0-7) based on seven cardio-metabolic biomarkers, was categorized as below (low AL) or above (high AL) the median. Severe COVID-19 was defined as hospitalization or mortality within 30 days of COVID-19 diagnosis. The association between race, AL, and severe COVID-19 was assessed using multivariable Poisson regression. The mediating effect of AL was assessed using the Valeri and VanderWeele method. All results were expressed as risk ratios (RRs) with 95% confidence intervals. RESULTS: Overall, Black (vs. White) KPGA members had an 18% excess risk of AL (RR: 1.18, 95%CI: 1.14-1.23) and a 24% excess risk of severe COVID-19 (RR: 1.24, 95%CI: 1.12, 1.37). AL explained 23% of the Black-White disparities in severe COVID-19. CONCLUSIONS: In our study, chronic stress, characterized by AL, partially mediated Black-White disparities in severe COVID-19 outcomes.

Dexamethasone Suppression Testing in a Contemporary Cohort with Adrenal Incidentalomas in Two U.S. Integrated Healthcare Systems.

Autonomous cortisol secretion (ACS) from an adrenal adenoma can increase the risk for comorbidities and mortality. The dexamethasone suppression test (DST) is the standard method to diagnose ACS. A multi-site, retrospective cohort of adults with diagnosed adrenal tumors was used to understand patient characteristics associated with DST completion and ACS. Time to DST completion was defined using the lab value and result date; follow-up time was from the adrenal adenoma diagnosis to the time of completion or censoring. ACS was defined by a DST > 1.8 µg/dL (50 nmol/L). The Cox proportional hazards regression model assessed associations between DST completion and patient characteristics. In patients completing a DST, a logistic regression model evaluated relationships between elevated ACS and covariates. We included 24,259 adults, with a mean age of 63.1 years, 48.1% obese, and 28.7% with a Charlson comorbidity index ≥ 4. Approximately 7% (n = 1768) completed a DST with a completion rate of 2.36 (95% CI 2.35, 2.37) per 100 person-years. Fully adjusted models reported that male sex and an increased Charlson comorbidity index were associated with a lower likelihood of DST completion. Current or former smoking status and an increased Charlson comorbidity index had higher odds of a DST > 1.8 µg/dL. In conclusion, clinical policies are needed to improve DST completion and the management of adrenal adenomas.

The Association Between Black vs. White Race and 30-Day Hospitalization Among People Diagnosed with COVID-19 Within an Integrated Care Setting: a Cohort Study.

BACKGROUND: Black Americans are more likely to experience hospitalization from COVID-19 compared with White Americans. Whether this excess risk differs by age, sex, obesity, or diabetes, key risk factors for COVID hospitalization, among an integrated population with uniform healthcare access, are less clear. METHODS: We identified all adult members (≥ 18 years) of Kaiser Permanente Georgia (KPGA) diagnosed with COVID-19 between January 1, 2020, and September 30, 2021 (N = 24,564). We restricted the analysis to members of Black or White race identified from electronic medical records. Our primary outcome was first hospitalization within 30 days of COVID-19 diagnosis. To assess the association between race and 30-day hospitalization, we performed multivariable logistic regression adjusting for several member and neighborhood-level characteristics, and tested for interactions of race with age, sex, diabetes, and obesity. A regression-based decomposition method was then used to estimate how much of the observed race disparity in 30-day hospitalization could be explained by member and neighborhood-level factors. RESULTS: Overall, 11.27% of Black KPGA members were hospitalized within 30 days of a COVID diagnosis, as compared with 9.44% of White KPGA members. Black (vs. White) KPGA members had a 34% (aOR: 1.32 [95% CI: 1.19-1.47]) higher odds of 30-day hospitalization following COVID-19 after accounting for clinical differences. The odds of 30-day hospitalization in Black vs. White KPGA members did not differ significantly by sex (men: 1.46 [1.25-1.70]; women: 1.24 [1.07-1.43]), by age (18-29 years: 1.33 [0. 841-2.10]; 30-49 years: 1.26 [1.02-1.56]; ≥ 50 years: 1.24 [1.10-1.41]); by diabetes status (with diabetes: 1.38 [1.16-1.66]; without diabetes: 1.26 [1.11-1.44]), or by obesity (with obesity: 1.31 [1.15-1.50]; without obesity: 1.28 [1.06-1.53]). Factors that, if Black and White KPGA members had the same level of exposure, would be most likely to reduce the Black-White disparity in 30-day hospitalization from COVID-19 were obesity, history of flu vaccine, and neighborhood-level income and social vulnerability. CONCLUSIONS: Early in the pandemic, Black (vs. White) members of an integrated health system had higher odds of being hospitalized within 30 days of COVID-19 diagnosis and this excess risk was similar by sex, age, and comorbidities. Factors that explained the largest proportions of race-based disparities were obesity, receipt of flu vaccine, and neighborhood-level social determinants of health. These findings suggest that social determinants of health, or other unmeasured factors, may be drivers of racial disparities in COVID-19 outcomes.

Disruption to routine diabetes care processes during the pandemic: evidence from a large integrated health system in the Southeast United States.

INTRODUCTION: We investigated the impact of the COVID-19 pandemic on annual adherence to seven diabetes care guidelines and risk factor management among people with diabetes. RESEARCH DESIGN AND METHODS: We included all adults (aged ≥18 years) with prevalent diabetes as of 1 January 2018, who were continuously enrolled at Kaiser Permanente Georgia (KPGA) through 31 December 2021 (n=22 854). Prevalent diabetes was defined as a history of at least one of a diagnosis code for diabetes, use of antihyperglycemic medication, or at least one laboratory value of HbA1c, fasting plasma glucose or random glucose in the diabetic range. We defined pre-COVID (2018-2019) and during COVID (2020-2021) cohorts. Cohort-specific laboratory measurements (ie, blood pressure (BP), HbA1c, cholesterol, creatinine, urine-albumin-creatinine ratio (UACR)) and procedures (ie, eye and foot examinations) were determined from KPGA's electronic medical record data. We used logistic generalized estimating equations (GEE), adjusted for baseline age, to assess the within-subject change in guideline adherence (ie, at least one measurement per year per period) from pre-COVID to during COVID era overall, and by age, sex, and race. Linear GEE compared mean laboratory measurements pre and during COVID. RESULTS: The proportion of adults meeting each of the seven diabetes care guidelines decreased significantly during (vs pre) COVID (range in absolute reductions: -0.8% to -11.2%) with greatest reductions seen for BP (-11.2%) and cholesterol (-8.8%). Declines were similar across age, sex, and race subgroups. Average HbA1c and systolic BP increased 0.11% and 1.6 mmHg, respectively, while low-density lipoprotein cholesterol declined 8.9 mg/dL. The proportion of adults at high risk of kidney disease (ie, UACR ≥300 mg/g) increased from 6.5% to 9.4%. CONCLUSIONS: In an integrated healthcare system, the proportion of people with diabetes meeting guideline-recommended screenings decreased during the pandemic, coinciding with worsening glucose, kidney, and (some) cardiovascular risk profiles. Follow-up is needed to assess the long-term implications of these care gaps.

Impact of COVID-19 on Trends in Outpatient Clinic Utilization: A Tale of 2 Departments.

BACKGROUND: The COVID-19 pandemic forced many US health care organizations to shift from mostly in-person care to a hybrid of virtual visits (VV) and in-person visits (IPV). While there was an expected and immediate shift to virtual care (VC) early in the pandemic, little is known about trends in VC use after restrictions eased. METHODS: This is a retrospective study using data from 3 health care systems. All completed visits from adult primary care (APC) and behavioral health (BH) were extracted from the electronic health record of adults aged 19 years and older from January 1, 2019 to June 30, 2021. Standardized weekly visit rates were calculated by department and site and analyzed using time series analysis. RESULTS: There was an immediate decrease in APC visits following the onset of the pandemic. IPV were quickly replaced by VV such that VV accounted for most APC visits early in the pandemic. By 2021, VV rates declined, and VC visits accounted for <50% of all APC visits. By Spring 2021, all 3 health care systems saw a resumption of APC visits as rates neared or returned to prepandemic levels. In contrast, BH visit rates remained constant or slightly increased. By April 2020, almost all BH visits were being delivered virtually at each of the 3 sites and continue to do so without changes to utilization. CONCLUSIONS: VC use peaked during the early pandemic period. While rates of VC are higher than prepandemic levels, IPV are the predominant visit type in APC. In contrast, VC use has sustained in BH, even after restrictions eased.

Patient Factors Associated With Use of Adult Primary Care and Virtual Visits During the COVID-19 Pandemic.

BACKGROUND: The delivery of adult primary care (APC) shifted from predominately in-person to modes of virtual care during the COVID-19 pandemic. It is unclear how these shifts impacted the likelihood of APC use during the pandemic, or how patient characteristics may be associated with the use of virtual care. METHODS: A retrospective cohort study using person-month level datasets from 3 geographically disparate integrated health care systems was conducted for the observation period of January 1, 2020, through June 30, 2021. We estimated a 2-stage model, first adjusting for patient-level sociodemographic, clinical, and cost-sharing factors, using generalized estimating equations with a logit distribution, along with a second-stage multinomial generalized estimating equations model that included an inverse propensity score treatment weight to adjust for the likelihood of APC use. Factors associated with APC use and virtual care use were separately assessed for the 3 sites. RESULTS: Included in the first-stage models were datasets with total person-months of 7,055,549, 11,014,430, and 4,176,934, respectively. Older age, female sex, greater comorbidity, and Black race and Hispanic ethnicity were associated with higher likelihood of any APC use in any month; measures of greater patient cost-sharing were associated with a lower likelihood. Conditional on APC use, older age, and adults identifying as Black, Asian, or Hispanic were less likely to use virtual care. CONCLUSIONS: As the transition in health care continues to evolve, our findings suggest that to ensure vulnerable patient groups receive high quality health care, outreach interventions to reduce barriers to virtual care use may be warranted.

Virtual Care and Urinary Tract Infection Management: Comparing Ancillary Service Orders and Patient Order Fulfillments Between Virtual and In-person Encounters During the COVID-19 Pandemic in the United States.

BACKGROUND: During the COVID-19 pandemic, more health care issues were being managed remotely. Urinary tract infections (UTIs) are being managed more often using telehealth although few reports compare the rate of UTI ancillary service orders placed and fulfilled during these visits. OBJECTIVES: We aimed to evaluate and compare the rate of ancillary service orders and order fulfillments in incident UTI diagnoses between virtual and in-person encounters. RESEARCH DESIGN: The retrospective cohort study involved 3 integrated health care systems: Kaiser Permanente (KP) Colorado, KP Georgia, and KP Mid-Atlantic States. SUBJECTS: We included incident UTI encounters from adult primary care data from January 2019 to June 2021. MEASURES: Data were categorized as: prepandemic (January 2019-March 2020), COVID-19 Era 1 (April 2020-June 2020), and COVID-19 Era 2 (July 2020-June 2021). UTI-specific ancillary services included medication, laboratory, and imaging. Orders and order fulfillments were dichotomized for analyses. Weighted percentages for orders and fulfillments were calculated using inverse probability treatment weighting from logistic regression and compared between virtual and in-person encounters using χ2 tests. RESULTS: We identified 123,907 incident encounters. Virtual encounters increased from 13.4% prepandemic to 39.1% in COVID-19 Era 2. Ancillary service orders from virtual encounters were not placed as often as in-person encounters. However, the weighted percentage for ancillary service order fulfillment across all services remained above 65.3% across sites and eras, with many fulfillment percentages above 90%. CONCLUSIONS: Our study reported a high rate of order fulfillment for both virtual and in-person encounters. Health care systems should encourage providers to place ancillary service orders for uncomplicated diagnoses, such as UTI, to provide enhanced access to patient-centered care.

Management of Neck or Back Pain in Ambulatory Care: Did Visit Mode or the COVID-19 Pandemic Affect Provider Practice or Patient Adherence?

BACKGROUND/OBJECTIVE: In recent years, 2 circumstances have changed provider-patient interactions in ambulatory care: (1) the replacement of virtual for in-person visits and (2) the COVID-19 pandemic. We studied the potential impact of each event on provider practice and patient adherence by comparing the frequency of the association of provider orders, and patient fulfillment of those orders, by visit mode and pandemic period, for incident neck or back pain (NBP) visits in ambulatory care. METHODS: Data were extracted from the electronic health records of 3 Kaiser Permanente regions (Colorado, Georgia, and Mid-Atlantic States) from January 2017 to June 2021. Incident NBP visits were defined from ICD-10 coded as primary or first listed diagnoses on adult, family medicine, or urgent care visits separated by at least 180 days. Visit modes were classified as virtual or in-person. Periods were classified as prepandemic (before April 2020 or the beginning of the national emergency) or recovery (after June 2020). Percentages of provider orders for, and patient fulfillment of orders, were measured for 5 service classes and compared on: virtual versus in-person visits, and prepandemic versus recovery periods. Comparisons were balanced on patient case-mix using inverse probability of treatment weighting. RESULTS: Ancillary services in all 5 categories at each of the 3 Kaiser Permanente regions were substantially ordered less frequently on virtual compared with in-person visits in both the prepandemic and recovery periods (both P ≤ 0.001). Conditional on an order, patient fulfillment within 30 days was high (typically ≥70%) and not likely meaningfully different between visit modes or pandemic periods. CONCLUSIONS: Ancillary services for incident NBP visits were ordered less frequently during virtual than in-person visits in both prepandemic and recovery periods. Patient fulfillment of orders was high, and not significantly different by mode or period.

Did Access to Ambulatory Care Moderate the Associations Between Visit Mode and Ancillary Services Utilization Across the COVID-19 Pandemic Period?

BACKGROUND/OBJECTIVE: In recent years, 2 circumstances changed provider-patient interactions in primary care: the substitution of virtual (eg, video) for in-person visits and the COVID-19 pandemic. We studied whether access to care might affect patient fulfillment of ancillary services orders for ambulatory diagnosis and management of incident neck or back pain (NBP) and incident urinary tract infection (UTI) for virtual versus in-person visits. METHODS: Data were extracted from the electronic health records of 3 Kaiser Permanente Regions to identify incident NBP and UTI visits from January 2016 through June 2021. Visit modes were classified as virtual (Internet-mediated synchronous chats, telephone visits, or video visits) or in-person. Periods were classified as prepandemic [before the beginning of the national emergency (April 2020)] or recovery (after June 2020). Percentages of patient fulfillment of ancillary services orders were measured for 5 service classes each for NBP and UTI. Differences in percentages of fulfillments were compared between modes within periods and between periods within the mode to assess the possible impact of 3 moderators: distance from residence to primary care clinic, high deductible health plan (HDHP) enrollment, and prior use of a mail-order pharmacy program. RESULTS: For diagnostic radiology, laboratory, and pharmacy services, percentages of fulfilled orders were generally >70-80%. Given an incident NBP or UTI visit, longer distance to the clinic and higher cost-sharing due to HDHP enrollment did not significantly suppress patients' fulfillment of ancillary services orders. Prior use of mail-order prescriptions significantly promoted medication order fulfillments on virtual NBP visits compared with in-person NBP visits in the prepandemic period (5.9% vs. 2.0%, P=0.01) and in the recovery period (5.2% vs. 1.6%, P=0.02). CONCLUSIONS: Distance to the clinic or HDHP enrollment had minimal impact on the fulfillment of diagnostic or prescribed medication services associated with incident NBP or UTI visits delivered virtually or in-person; however, prior use of mail-order pharmacy option promoted fulfillment of prescribed medication orders associated with NBP visits.

Health-care-Related Practices in Virtual Behavioral Health Treatment for Major Depression Before and During the COVID-19 Pandemic.

BACKGROUND: The abrupt shift to virtual care at the onset of the COVID-19 pandemic had the potential to disrupt care practices in virtual behavioral health encounters. We examined changes over time in virtual behavioral health-care-related practices for patient encounters with diagnoses of major depression. METHODS: This retrospective cohort study utilized electronic health record data from 3 integrated health care systems. Inverse probability of treatment weighting was used to adjust for covariates across 3 time periods, prepandemic (January 2019-March 2020), peak-pandemic shift to virtual care (April 2020-June 2020), and recovery of health care operations (July 2020-June 2021). First virtual follow-up behavioral health department encounters after an incident diagnostic encounter were examined for differences across the time periods in rates of antidepressant medication orders and fulfillments, and completion of patient-reported symptoms screeners in service of measurement-based care. RESULTS: Antidepressant medication orders declined modestly but significantly in 2 of the 3 systems during the peak-pandemic period but rebounded during the recovery period. There were no significant changes in patient fulfillment of ordered antidepressant medications. Completion of symptom screeners increased significantly in all 3 systems during the peak-pandemic period and continued to increase significantly in the subsequent period. CONCLUSIONS: A rapid shift to virtual behavioral health care was possible without compromising health-care-related practices. The transition and subsequent adjustment period have instead been marked by improved adherence to measurement-based care practices in virtual visits, signaling a potential new capacity for virtual health care delivery.

Development of a Common Data Model for a Multisite and Multiyear Study of Virtual Visit Implementation: A Case Study.

BACKGROUND/OBJECTIVE: In multisite studies, a common data model (CDM) standardizes dataset organization, variable definitions, and variable code structures and can support distributed data processing. We describe the development of a CDM for a study of virtual visit implementation in 3 Kaiser Permanente (KP) regions. METHODS: We conducted several scoping reviews to inform our study's CDM design: (1) virtual visit mode, implementation timing, and scope (targeted clinical conditions and departments); and (2) extant sources of electronic health record data to specify study measures. Our study covered the period from 2017 through June 2021. Integrity of the CDM was assessed by a chart review of random samples of virtual and in-person visits, overall and by specific conditions of interest (neck or back pain, urinary tract infection, major depression). RESULTS: The scoping reviews identified a need to address differences in virtual visit programs across the 3 KP regionsto harmonize measurement specifications for our research analyses. The final CDM contained patient-level, provider-level, and system-level measures on 7,476,604 person-years for KP members aged 19 years and above. Utilization included 2,966,112 virtual visits (synchronous chats, telephone visits, video visits) and 10,004,195 in-person visits. Chart review indicated the CDM correctly identified visit mode on>96% (n=444) of visits, and presenting diagnosis on >91% (n=482) of visits. CONCLUSIONS: Upfront design and implementation of CDMs may be resource intensive. Once implemented, CDMs, like the one we developed for our study, provide downstream programming and analytic efficiencies by harmonizing, in a consistent framework, otherwise idiosyncratic temporal and study site differences in source data.

Factor Analysis in Distinguishing Coronavirus Disease 2019 From Other Influenza-like Illness Using a Validated Patient-Reported Outcome Instrument FLU-PRO Plus: A Prospective Real-world Cohort Study.

BACKGROUND/OBJECTIVE: InFLUenza Patient-reported Outcome (FLU-PRO Plus) is a 34-item patient-reported outcome instrument designed to capture the intensity and frequency of viral respiratory symptoms. This study evaluates whether FLU-PRO Plus responses could discriminate between symptoms of coronavirus disease 2019 (COVID-19) and influenza-like illness (ILI) with no COVID diagnosis, as well as forecast disease progression. METHODS: FLU-PRO Plus was administered daily for 14 days. Exploratory factor analysis was used to reduce the FLU-PRO Plus responses on the first day to 3 factors interpreted as "symptom clusters." The 3 clusters were used to predict COVID-19 versus ILI diagnosis in logistic regression. Correlation between the clusters and quality of life (QoL) measures was used to assess concurrent validity. The timing of self-reported return to usual health in the 14-day period was estimated as a function of the clusters within COVID-19 and ILI groups. RESULTS: Three hundred fourteen patients completed day 1 FLU-PRO Plus, of which 65% had a COVID-19 diagnosis. Exploratory factor analysis identified 3 symptom clusters: (1)general Body, (2) tracheal/bronchial, and (3) nasopharyngeal. Higher nasopharyngeal scores were associated with higher odds of COVID-19 compared with ILI diagnosis [adjusted odds ratio = 1.61 (1.21, 2.12)]. Higher tracheal/bronchial scores were associated with lower odds of COVID-19 [0.58 (0.44, 0.77)]. The 3 symptom clusters were correlated with multiple QoL measures ( r = 0.14-0.56). Higher scores on the general body and tracheal/bronchial symptom clusters were associated with prolonged time to return to usual health [adjusted hazard ratios: 0.76 (0.64, 0.91), 0.80 (0.67, 0.96)]. CONCLUSION: Three symptom clusters identified from FLU-PRO Plus responses successfully discriminated patients with COVID-19 from non-COVID ILI and were associated with QoL and predicted symptom duration.

The bidirectional association between diabetes and long-COVID-19 - A systematic review.

Some evidence suggests that diabetes may be a risk factor for the development of post-acute sequelae of COVID-19 (PASC). Recent data also indicate that new-onset diabetes may be a complication of COVID-19. Here, we review the existing evidence. Following PRISMA guidelines, we conducted a systematic review through August 8, 2022. We included longitudinal studies reporting on the risk of PASC (i.e., sequelae that extend beyond four weeks after initial infection) in people with and without diabetes, and studies reporting on the risk of new-onset diabetes in people with vs without COVID-19 with a minimum of 4-weeks of follow-up. All studies were published in English. Among 5,532 studies screened, 39 were included in the final review. Among 25 studies reporting on diabetes and PASC, 44 % (n = 11) identified diabetes as a significant risk factor for PASC (increased relative risk ranging from 7 % to 342 %) while 56 % (n = 14) did not. Among 14 studies reporting on new-onset diabetes, 12 (86 %) reported that COVID-19 (vs no COVID) was significantly associated with new-onset diabetes with increased risks ranging from 11 % to 276 %. COVID-19 survivors may be at increased risk for new-onset diabetes, but whether pre-existing diabetes is also a risk factor for PASC remains unclear.

Systematic surveillance of patient-reported symptoms of viral respiratory tract infectious Syndromes in diverse populations.

BACKGROUND: Patient reported outcome measures (PROM) can improve patient care and be crucial for symptom tracking especially during disease outbreaks. FLU-PRO Plus is a validated PROM used to track viral respiratory symptoms. Our study aimed to evaluate the feasibility of using FLU-PRO© Plus, to track symptoms across three healthcare systems. METHODS: The prospective, longitudinal study recruited adults between February-May 2021 from HealthPartners Institute (HP), Kaiser Permanente Georgia (KPGA), and Kaiser Permanente Mid-Atlantic States (KPMAS). Adult members were eligible if they had a positive lab or diagnosis for either COVID-19 or influenza-like illness (ILI) or exhibited 2 + viral respiratory symptoms. Descriptive statistics were calculated to describe the patient characteristics for participants that were eligible for FLU-PRO Plus, successfully contacted, attempted to log in to the FLU-PRO Plus website, and participants who completed FLU-PRO Plus Day 1. Bivariable and multivariable logistic regression using PROC GLIMMIXX investigated the patient characteristics associated with (1) successful contact and (2) FLU-PRO Plus Day 1 completion. RESULTS: We identified a total of 15,650 eligible participants during the enrollment period: 9,582 from HP, 1,740 from KPGA, and 4,328 from KPMAS. Among the total of 409 eligible adults who attempted to participate in FLU-PRO Plus, 317 completed FLU-PRO Plus Day 1. Among the 317 individuals that completed FLU-PRO Plus Day 1, 205 (67.5%) were diagnosed with COVID-19; 112 adults diagnosed with COVID-19 completed FLU-PRO Plus Day 14. Among adults successfully contacted, adults aged 35-64 (OR = 1.40, 95% CI 1.05, 1.87), females (OR = 1.77, 95% CI 1.38, 2.27), and adults diagnosed with COVID-19 (OR = 1.66, 95% CI 1.27, 2.17) had higher odds of completing FLU-PRO Plus Day 1; Asian adults (OR = 0.38, 95% CI 0.19, 0.76) and Black and African American adults (OR = 0.33, 95% CI 0.19, 0.76) had lower odds compared to White adults. CONCLUSION: Our study reports on the feasibility of patients across three integrated healthcare systems utilizing FLU-PRO Plus to monitor their respiratory symptoms. Patient reported outcome measures (PROM) can improve patient care, quality of life, and reduce the strain of limited resources on healthcare systems. Future FLU-PRO Plus studies should develop an implementation strategy to fully integrate FLU-PRO Plus within clinical care and patient management.

Developing an algorithm across integrated healthcare systems to identify a history of cancer using electronic medical records.

OBJECTIVE: Tumor registries in integrated healthcare systems (IHCS) have high precision for identifying incident cancer but often miss recently diagnosed cancers or those diagnosed outside of the IHCS. We developed an algorithm using the electronic medical record (EMR) to identify people with a history of cancer not captured in the tumor registry to identify adults, aged 40-65 years, with no history of cancer. MATERIALS AND METHODS: The algorithm was developed at Kaiser Permanente Colorado, and then applied to 7 other IHCS. We included tumor registry data, diagnosis and procedure codes, chemotherapy files, oncology encounters, and revenue data to develop the algorithm. Each IHCS adapted the algorithm to their EMR data and calculated sensitivity and specificity to evaluate the algorithm's performance after iterative chart review. RESULTS: We included data from over 1.26 million eligible people across 8 IHCS; 55 601 (4.4%) were in a tumor registry, and 44848 (3.5%) had a reported cancer not captured in a registry. The common attributes of the final algorithm at each site were diagnosis and procedure codes. The sensitivity of the algorithm at each IHCS was 90.65%-100%, and the specificity was 87.91%-100%. DISCUSSION: Relying only on tumor registry data would miss nearly half of the identified cancers. Our algorithm was robust and required only minor modifications to adapt to other EMR systems. CONCLUSION: This algorithm can identify cancer cases regardless of when the diagnosis occurred and may be useful for a variety of research applications or quality improvement projects around cancer care.

Improving Access to Kidney Transplantation: Perspectives From Dialysis and Transplant Staff in the Southeastern United States.

RATIONALE & OBJECTIVE: There are many barriers to meeting the goal of increasing kidney transplants in the United States. It is important to understand dialysis and transplant center providers' existing practices and identified barriers to increasing the number of dialysis patients who are evaluated for and get wait-listed for a transplant. STUDY DESIGN: Cross-sectional survey of dialysis unit and transplant center staff in End Stage Renal Disease Network 6 (Georgia, North Carolina, South Carolina). SETTING & PARTICIPANTS: Ninety-one transplant staff from all 9 transplant centers in the region and 421 dialysis staff from 421 facilities responded to the survey. PREDICTORS: N/A. OUTCOME: Provider perceptions of barriers faced by patients in the kidney transplant evaluation process and suggestions for improving care. ANALYTICAL APPROACH: Mixed methods. Descriptive analyses of responses to multiple-choice questions and qualitative analysis of open-ended survey responses. RESULTS: The top 5 barriers to kidney transplantation as reported by transplant staff were transportation (63.7%), low health literacy (50.5%), lack of understanding about the transplant process (37.4%), distance to transplant center (29.7%), and low socioeconomic status (28.6%). When asked how dialysis units can help patients complete the evaluation process, the most common responses from transplant center staff were educating patients about transplant (54%), helping patients through steps in the process (35%), and better communication with transplant centers (15%). When dialysis unit staff were asked what could be done to help the facility improve its transplant wait-list rate, the most common responses were educational materials for patients and staff (55%), better communication with transplant centers (12%), and transportation and financial assistance (9%). LIMITATIONS: Survey responses are from 1 end stage renal disease network. CONCLUSIONS: Dialysis units, transplant centers, and ESRD networks can work together to help patients address key barriers to transplantation to improve the country's transplantation rate.