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.

Albuminuria Screening in People With Type 2 Diabetes in a Managed Care Organization.

Introduction: Albuminuria-an increased amount of urine albumin, in milligrams, adjusted for grams of urine creatinine-is an early marker of diabetic kidney disease. Several new classes of medications are now available that effectively lower albuminuria levels with the potential to delay or prevent the progression of diabetic kidney disease. However, screening for albuminuria in the U.S. is low in population-based studies (<10% to ∼50% at most). In this study, we examine whether screening for albuminuria was improved in an integrated model of healthcare delivery following the recommendations of the National Committee for Quality Assurance mandate (an umbrella group for the managed healthcare industry) to screen for albuminuria. Methods: We examined screening for albuminuria over a 2-year period among people with Type 2 diabetes in a U.S. HMO with an electronic medical record, onto which automated laboratory ordering for albuminuria could be added when a patient appeared at the laboratory (for any reason) if albuminuria testing had not been obtained within the previous 365 days. Participants under this plan received diabetes education at no cost and panel managers to guide their diabetes care. Logistic regression using data from 2020 and 2021, separately, evaluated the relationship between patient characteristics and the likelihood of albuminuria screening. Results: There were 20,688 and 22,487 participants with Type 2 diabetes mellitus in 2020 and 2021, respectively, who were analyzed. Approximately 80% were screened for albuminuria in both years. African American participants and those aged >64 years were more likely to have completed albuminuria screening. Screened individuals had lower HbA1c, blood pressure, and low-density lipoprotein cholesterol levels than those who were not screened. Conclusions: In an integrated healthcare model, it is possible to achieve consistently high rates of albuminuria screening in people with Type 2 diabetes, especially in groups at high risk for kidney disease.

Incidence and Survival for Patients Diagnosed With Breast, Colorectal, and Lung Cancer in an Integrated System.

INTRODUCTION: Documenting trends in cancer incidence and survival is a national priority. This study estimated age- and sex-adjusted incidence and 5-year relative survival among patients with cancer diagnosed within Kaiser Permanente compared to Surveillance, Epidemiology, and End Results (SEER) estimates. METHODS: The cohort included Kaiser Permanente health plan members diagnosed with breast (BC), colorectal (CRC), or lung cancer (LC) between January 1, 1999 and December 31, 2018. Incidence was computed as age-adjusted rates per 100,000 member-years. SEER*Stat was used to compute 5-year relative survival. RESULTS: Kaiser Permanente BC incidence rates were persistently higher than SEER from 2004 (126.5 [95% confidence interval (CI) = 123.2-129.9] vs 122.6 [95% CI = 121.3-123.2]) through 2013 (132.06 [95% CI = 129.5-135.7] vs 126.7 [95% CI = 125.9-127.5]). Kaiser Permanente CRC and LC incidence rates were lower than SEER for all years except 2008, showing a spike in CRC incidence (51.5 [95% CI = 49.9-53.0] vs 46.1 [95% CI = 45.7-46.4]). Kaiser Permanente BC, CRC, and LC survival estimates for all stages were higher than SEER. CONCLUSIONS: Incidence rates for all-stage and localized-stage BC were consistently higher for Kaiser Permanente than for SEER. CRC and LC rates were lower. Kaiser Permanente survival rates were consistently higher than for SEER. The strengths of these findings are associated with the ability to capture "gold-standard" cancer registry data on defined Kaiser Permanente populations. However, findings should be interpreted cautiously given differences in the underlying populations and secular and regional differences between Kaiser Permanente and SEER. The Kaiser Permanente population is younger and more racially diverse than SEER aggregate populations, and Kaiser Permanente members are insured with access to preventive care (eg, smoking cessation programs, cancer screening).

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.

Understanding Racial Disparities in COVID-19-Related Complications: Protocol for a Mixed Methods Study.

BACKGROUND: In the United States, the COVID-19 pandemic has magnified the disproportionate and long-standing health disparities experienced by Black communities. Although it is acknowledged that social determinants of health (SDOH) rather than biological factors likely contribute to this disparity, few studies using rigorous analytic approaches in large, information-rich community-based data sets are dedicated to understanding the underlying drivers of these racial disparities. OBJECTIVE: The overall aim of our study is to elucidate the mechanisms by which racial disparities in severe COVID-19 outcomes arise, using both quantitative and qualitative methods. METHODS: In this protocol, we outline a convergent parallel mixed methods approach to identifying, quantifying, and contextualizing factors that contribute to the dramatic disparity in COVID-19 severity (ie, hospitalization, mortality) in Black versus white COVID-19 patients within the integrated health care system of Kaiser Permanente Georgia (KPGA). Toward this end, we will generate two quantitative cohorts of KPGA members with a confirmed COVID-19 diagnosis between January 1, 2020, and September 30, 2021: (1) an electronic medical record (EMR) cohort including routinely captured data on diagnoses, medications, and laboratory values, and a subset of patients hospitalized at Emory Healthcare to capture additional in-hospital data; and (2) a survey cohort, where participants will answer a range of questions related to demographics (eg, race, education), usual health behaviors (eg, physical activity, smoking), impact of COVID-19 (eg, job loss, caregiving responsibilities), and medical mistrust. Key outcomes of interest for these two cohorts include hospitalization, mortality, intensive care unit admission, hospital readmission, and long COVID-19. Finally, we will conduct qualitative semistructured interviews to capture perceptions of and experiences of being hospitalized with COVID-19 as well as related interactions with KPGA health care providers. We will analyze and interpret the quantitative and qualitative data separately, and then integrate the qualitative and quantitative findings using a triangulation design approach. RESULTS: This study has been funded by a Woodruff Health Sciences grant from December 2020 to December 2022. As of August 31, 2022, 31,500 KPGA members diagnosed with COVID-19 have been included in the EMR cohort, including 3028 who were hospitalized at Emory Healthcare, and 482 KPGA members completed the survey. In addition, 20 KPGA members (10 Black and 10 white) have been interviewed about their experiences navigating care with COVID-19. Quantitative and qualitative data cleaning and coding have been completed. Data analysis is underway with results anticipated to be published in December 2022. CONCLUSIONS: Results from this mixed methods pilot study in a diverse integrated care setting in the southeastern United States will provide insights into the mechanisms underpinning racial disparities in COVID-19 complications. The quantitative and qualitative data will provide important context to generate hypotheses around the mechanisms for racial disparities in COVID-19, and may help to inform the development of multilevel strategies to reduce the burden of racial disparities in COVID-19 and its ongoing sequelae. Incorporating contextual information, elucidated from qualitative interviews, will increase the efficacy, adoption, and sustainability of such strategies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/38914.

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.