UnitedHealth Group Research Articles

A Financial Analysis and Valuation of Pfizer

Abstract: The rational valuation of the healthcare industry and the analysis and research of the financial risks faced by enterprises can not only provide a basis for rational investment and transaction pricing decisions, but also help enterprises to find out the shortcomings of the production and operation, so as to improve the management mode of the enterprise, and help enterprises to achieve the maximisation of management. Firstly, this paper analyse the risks faced by Pfizer from a financial point of view by quantitatively comparing the data of Pfizer and its two competitors, Amgen and Unitedhealth Group, and then qualitatively analysing their characteristics in terms of liquidity, solvency and profitability and the reasons for this. Next, Pfizer is valued by looking at its leverage, business risk, earnings per share, etc. to measure the financial risk of the business and the reasons for the capital structure. It then gives investors an objective investment recommendation by forecasting Pfizer's future share price. The study concludes that Pfizer Inc. is illiquid, has poor corporate solvency, is at risk of debt servicing, and has suffered a significant decline in profitability. Valuing Pfizer, the forecast suggests that Pfizer's stock is currently undervalued.

355-OR: Glycemic Outcomes with CGM Use in Patients with Type 2 Diabetes—Real-World Analysis

Introduction & Objectives: While the benefits of CGM use in T1D are well documented, its efficacy across the spectrum of T2D patients in real-world settings has not been evaluated. We assessed the effects of CGM use in a large T2D adult population across the treatment spectrum, considering non-insulin therapies (NIT), basal insulin (BIT), and prandial insulin (PIT) with/without non-insulin medications. Methods: This retrospective,12-month analysis used data from a large claims database that included >7.1 million patients with T2D in the electronic medical records. The two observation periods were: pre-index period -- 360 days prior to patients' first CGM claim; and post-index period -- 360 days after to the first CGM claim. The index date (baseline) was the date of the first CGM claim between December 27, 2019, and January 5, 2022. The primary outcome was change in HbA1c closest to 12 months after CGM acquisition. Results: The analysis included 16,410 adults with T2D (NIT, n=4,659; (BIT, n=6,182, and PIT, n=5,569) with mean baseline HbA1c 8.8% and mean age 59 years. At 12 months, the mean change in HbA1c was significant in all three subgroups compared with HbA1c levels in the pre-index period. (Figure) Conclusions: In this 12-month, real-world study, CGM use was associated with significant improvements in glucose control in both non-insulin and insulin-treated patients with T2D. Disclosure S.K. Garg: Research Support; Eli Lilly and Company. Advisory Panel; Medtronic. Research Support; Medtronic. Advisory Panel; Novo Nordisk. Research Support; DarioHealth Corp., Dexcom, Inc., Diasome. Advisory Panel; Roche Diabetes Care. I.B. Hirsch: Advisory Panel; Abbott. Research Support; Dexcom, Inc. Advisory Panel; Roche Diabetes Care. Research Support; MannKind Corporation, Tandem Diabetes Care, Inc. Advisory Panel; embecta. Research Support; Tandem Diabetes Care, Inc. Advisory Panel; Vertex Pharmaceuticals Incorporated. E. Repetto: Employee; Roche Diabetes Care. B. Ulmer: Employee; Roche Diabetes Care. C. Perkins: Employee; Roche Diabetes Care. J.K. Snell-Bergeon: None. R.M. Bergenstal: Other Relationship; Abbott. Research Support; Arkray Marketing. Consultant; Ascensia Diabetes Care, Bigfoot Biomedical, Inc., CeQur. Other Relationship; Dexcom, Inc., Eli Lilly and Company. Consultant; embecta, Hygieia. Research Support; Insulet Corporation. Consultant; MannKind Corporation. Other Relationship; Medtronic, Novo Nordisk. Consultant; Onduo LLC, Roche Diabetes Care. Other Relationship; Sanofi. Research Support; Tandem Diabetes Care, Inc. Other Relationship; UnitedHealth Group. Consultant; Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S. Funding Roche Diabetes Care

Partnership to tackle MH crisis for people with disabilities launched

The United Health Foundation, the philanthropic foundation of the UnitedHealth Group has awarded the nonprofit disability rights advocacy organization, The Arc of the United States, a three‐year, $2.5 million grant to improve mental health care for people with intellectual and developmental disabilities (IDD), a news release by The Arc stated. Up to 40% of people with IDD have co‐occurring mental health conditions, and this critical funding will help address their unmet mental health needs. Currently, only 1 in 10 children and adolescents with IDD and mental health disorders receive specialized services. These statistics highlight the need for training and awareness to ensure providers and caregivers are equipped to support the mental health needs of people with disabilities. This includes expanding access to quality mental health care services, improving coordination between disability and health systems, training over 2,000 providers and caregivers to recognize mental health needs in people with IDD, and launching public awareness campaigns to counteract stigma and misconceptions. A key component of the grant is partnering with the National Council for Mental Wellbeing to adapt its evidence‐based Mental Health First Aid program with information on IDD. Over three years, the United Health Foundation grant will help train caregivers, health care professionals, first responders, educators and family members to recognize the mental health needs of people with IDD and decrease the number of mental health crisis incidents experienced by this population.

Effect of BCG vaccination against Mycobacterium tuberculosis infection in adult Brazilian health-care workers: a nested clinical trial

The effectiveness of BCG vaccine for adult pulmonary tuberculosis remains uncertain. In this study, we aimed to evaluate the effect of vaccination with BCG-Denmark to prevent initial and sustained interferon-γ release assay conversion in Brazilian health-care workers. This substudy is a nested randomised controlled trial embedded within the BRACE trial (NCT04327206). Specifically, this substudy enrolled Brazilian health-care workers (aged ≥18 years) from three sites in Brazil (Manaus, Campo Grande, and Rio de Janeiro) irrespective of previously receiving BCG vaccination. Participants were excluded if they had contraindications to BCG vaccination, more than 1 month of treatment with specific tuberculosis treatment drugs, previous adverse reactions to BCG, recent BCG vaccination, or non-compliance with assigned interventions. Those eligible were randomly assigned (1:1) to either the BCG group (0·1 mL intradermal injection of BCG-Denmark [Danish strain 1331; AJ Vaccines, Copenhagen]) or the placebo group (intradermal injection of 0·9% saline) using a web-based randomisation process in variable-length blocks (2, 4, or 6), and were stratified based on the study site, age (<40, ≥40 to <60, ≥60 years), and comorbidity presence (diabetes, chronic respiratory disease, cardiac condition, hypertension). Sealed syringes were used to prevent inadvertent disclosure of group assignments. The QuantiFERON-TB Gold (QFT) Plus test (Qiagen; Hilden, Germany) was used for baseline and 12-month tuberculosis infection assessments. The primary efficacy outcome was QFT Plus conversion (≥0·35 IU/mL) by 12 months following vaccination in participants who had a negative baseline result (<0·35 IU/mL). Between Oct 7, 2020, and April 12, 2021, 1985 (77·3%) of 2568 participants were eligible for QFT Plus assessment at 12 months and were included in this substudy; 996 (50·2%) of 1985 were in the BCG group and 989 (49·8%) were in the placebo group. Overall, 1475 (74·3%) of 1985 participants were women and 510 (25·7%) were men, and the median age was 39 years (IQR 32-47). During the first 12 months, QFT Plus conversion occurred in 66 (3·3%) of 1985 participants, with no significant differences by study site (p=0·897). Specifically, 34 (3·4%) of 996 participants had initial QFT conversion in the BCG group compared with 32 (3·2%) of 989 in the placebo group (risk ratio 1·09 [95% CI 0·67-1·77]; p=0·791). BCG-Denmark vaccination did not reduce initial QFT Plus conversion risk in Brazilian health-care workers. This finding underscores the need to better understand tuberculosis prevention in populations at high risk. Bill & Melinda Gates Foundation, the Minderoo Foundation, Sarah and Lachlan Murdoch, the Royal Children's Hospital Foundation, Health Services Union NSW, the Peter Sowerby Foundation, SA Health, the Insurance Advisernet Foundation, the NAB Foundation, the Calvert-Jones Foundation, the Modara Pines Charitable Foundation, the United Health Group Foundation, Epworth Healthcare, and individual donors. For the Portuguese translation of the abstract see Supplementary Materials section.

Research on Capital Structure and Investment Value of the Healthcare Industry

This paper makes an in-depth study of the US healthcare industry from both empirical and theoretical aspects of capital structure and investment value. By calculating the WACC (weighted average cost of capital) for three of the most representative public companies in the US healthcare industry (Johnson &amp; Johnson, Pfizer, and UnitedHealth Group) and reviewing the literature, it is concluded that the company's business and capital flows have been affected due to the impact of the COVID-19 pandemic. At the same time, due to some differences in the main business and nature of the three companies, United Health Group found that it has the highest investment risk. Based on the analysis of the investment value and investment risk of Johnson &amp; Johnson, Pfizer, and UnitedHealth Group, this paper provides more appropriate investment recommendations for investors with different preferences, to further understand the future development trend of the American medical industry.

SAT116 Utilizing User-centered Design And Usability And Skills Testing For Remote Diabetes Survival Skills Training

Abstract Disclosure: S.J. Freeman: None. B. Radonski: None. L. Lecka: Employee; Self; Doximity. Stock Owner; Self; Doximity. K. Davis: None. G. Prince: None. K. Carthy: None. J.J. Seley: Speaker; Self; Lifescan Diabetes Institute. J. Song: None. J. Lee: None. S.C. Bailey: Consulting Fee; Self; Merck, Lundbeck, Sanofi-Aventis, Pfizer, Inc., Luto, University of Westminster, Gilead. Grant Recipient; Self; Merck, Eli Lilly &amp; Company, Pfizer, Inc., Lundbeck, Gordon and Betty Moore Foundation, National Institutes of Health, Gilead. R. Khorzad: None. D. Gatchell: None. B. Ankenman: None. D.R. Lewis: Grant Recipient; Self; Pfizer, Inc., Spencer Foundation, National Institutes of Health. J. Holl: None. A. Wallia: Consulting Fee; Self; Eli Lilly &amp; Company. Grant Recipient; Self; Novo Nordisk. Research Investigator; Self; UnitedHealth Group, Eli Lilly &amp; Company. Patient-centered approaches for teaching diabetes mellitus (DM) survival skills are essential. Furthermore, in the peri-COVID era, interventions also need to be amenable to remote care delivery. User-Centered design (UCD) including usability testing is a key strategy to optimize adoption and engagement of interventions. We developed a Diabetes Survival Skills Toolkit (website, paper guide, and a physical Kit with simulation supplies) using UCD (&amp;gt; 50 sessions), followed by administration of system usability surveys (SUS) (scored as unacceptable, acceptable, or excellent) and, in a subset, additional skills testing. Skills testing included simulated blood glucose checks and insulin administration, conducted by 2 trained observers. Forty-three participants with no prior history of DM were recruited between 01/2021-07/2022 to independently learn survival skills using different Toolkit components [website only (N=11), Kit + paper guide (N=28), and Kit + website (N=4)]. Purposive sampling for age and highest education level resulted in 33% being ≥ 65 years and 35% having &amp;lt; 4-year degree. Overall, SUS scores were deemed excellent (N=15/43 [35%]) or acceptable (N=20/43 [47%]). Unacceptable scores were noted in 8/43 (19%) [4 website only (all &amp;gt; 4-year degree) and 4 Kit + paper guide (3 of 4 &amp;gt; 65 years, all &amp;lt; 4-year degree)]. Use of the website alone resulted in a higher rate of unacceptable SUS scores (37%) compared to use of the Kit with either the paper guide or website (13%). SUS-score category was not associated with age (82% acceptable/excellent among &amp;lt;45 years, 86% among 45-64 years, and 79% among &amp;gt;=65 years; Fishers’ p=1.00) nor highest education level (80% acceptable/excellent among &amp;lt;4-year degree and 82% among &amp;gt;=4-year degree; Fisher’s p=0.69). Participants who completed skills testing (N= 28 Kit + paper guide, 4 Kit + website), regardless of their SUS score, all correctly demonstrated the ability to inject insulin with simulation supplies. However, 4/32 (13%) (all SUS scores acceptable/excellent) were unable to navigate all steps independently and 9/32 (28%) (2 SUS unacceptable) did not use the recommended instructional pathway. All 4 participants (3 with &amp;gt; age 65 and &amp;lt; 4-year degree) who completed skills testing but had unacceptable SUS scores still correctly demonstrated the ability to measure blood glucose and inject insulin. In conclusion, a Survival Skills Toolkit, resulted in excellent rates of successful survival skills performance when tested with laypersons of diverse ages and education levels. Subjective usability (SUS scores) did differ among users of different Toolkit components; however, they did not align with actual skill performance. Design preferences and usability tests as well as subsequent skills testing are critical to optimally design tools for diabetes survival skills training. Presentation: Saturday, June 17, 2023

SAT114 Global Social Determinants Of Health Needs And Response For Those New To Insulin At Discharge

Abstract Disclosure: C.A. Bullock: None. K. Davis: None. K. Carthy: None. P. Wax: None. C. Smyrniotis: None. T. Pollack: None. C. Barnard: None. J. Holl: None. A. Wallia: Grant Recipient; Self; Novo Nordisk. Research Investigator; Self; UnitedHealth Group. Unmet social determinant of health (SDoH) needs of patients with diabetes who are discharged with newly prescribed insulin place these patients at high risk of poor outcomes. Yet, few system level initiatives exist to identify patients with these needs and address them. An SDoH screening and referral initiative, consisting of an integrated screening tool administered by nursing upon hospital admission, was launched at a Chicago academic health system that cares for a diverse patient population. The electronic health record (EHR) screener assesses six specific domains including medication affordability, transportation barriers, food insecurity, housing stability, usual source of care, and mental health needs and a follow-up question if the patient would like assistance (leading to social work consultation). Our goal was to review the identified SDOH needs of patients newly prescribed insulin at discharge, and for whom a certified diabetes care and education specialist consultation (CDCES) was placed. From 05/01/22- 09/30/22, 279 patients had a CDCES consultation at Northwestern Memorial Hospital (NMH) of which 3 expired during admission. Of the 131 patients (47%) discharged with a new prescription for insulin, 18 (14%) were non-English, of which 17 (95%) had a complete SDOH screener, and 113 were English-speaking (86%), of which 74% (N=84) had a complete SDoH screener. The 113 English speaking patients had an age range from 20-84 (mean 56, SD + 14), 37 (33%) identified as black, 58 (51%) were female, and a majority (N= 55 [49%]) had Medicaid, Medicare coverage or were uninsured. Of those who had a screener completed (N=84), 28 (33%) reported at least 1 need, while 8% (N=7) identified &amp;gt;=3 needs, and 11% (N=9) requested assistance. The most reported need was a usual source of care (N=14, 17%). Other identified SDoH needs included medication affordability (N=8), transportation need (N=8), food insecurity (N=7), and housing stability issue (N=6), but few (N=2) identified any mental health needs. Sixty-five patients in total had a Social Work consultation and of those patients who identified needs 58% had their SDoH needs addressed by a Social Worker. Of the 14 patients without a usual source of care, 5 (43%) were readmitted or seen in the emergency department within 90 days of discharge and 1 had &amp;gt; 8 visit, despite enrollment in a hospital transitional care program. Only one patient established a usual source of care. Overall, 2 patients (2%), both with no identified needs, died within 90 days. Our findings reveal that many hospitalized patients who had a CDCES consultation before discharge and were newly prescribed insulin, identified global (&amp;gt; 3 SDoH or requiring assistance) needs. The findings also suggest that CDCES, nurses, pharmacists, and/or social workers may need to facilitate and/or create new pathways to address the needs of hospitalized patients newly prescribed insulin. Presentation: Saturday, June 17, 2023

Portfolio Optimization Based on 10 US Stocks

Focusing on the U.S. market, this research selects ten high-capitalization U.S. stocks in different industries and uses stock price forecasting in machine learning as well as Monte Carlo simulation to explore the efficient frontier of assets. Besides, this paper builds a portfolio with equal weight, maximum Sharpe ratio, and minimum volatility criteria, respectively. The results show that the Exxon Mobil Corporation possesses the largest proportion of the maximum Sharpe ratio portfolio, and the UnitedHealth Group Inc. accounts largest weights for the portfolio with the minimum volatility. In addition, this paper also compares the cumulative returns of the three investment portfolios with the important index NASDAQ of the US stock market. The results indicate that that the above mentioned three portfolios are all better than the benchmark index and can obtain a higher return. The results may shed light on some investors' approach to portfolio management during this extraordinary time.

Accessibility to Obstetric Care in South Florida Based on Insurance: A Cross-Sectional Study.

Introduction Obstetrical research confirms that earlier onset prenatal care significantly improves pregnancy and birth outcomes. Initiating care in the second trimester or having less than 50% of recommended visits has been associated with an increased risk of prematurity, stillbirth, neonatal, and infant death. Studies have shown that women on public health insurance plans initiate prenatal care substantially later into pregnancy than those on private plans. The purpose of this study is to assess whether public health insurance limits Florida patients' access to obstetric care. Methods A cross-sectional study was conducted by collecting data on the four most populated zip codes for Medicaid in South Florida using HealthGrades.com. The following search parameters were used: "obstetric care", "four stars and up" and "10-mile distance". Each obstetrician was called three times to assess appointment availability for fictional nulliparous women at eight weeks of gestation requesting prenatal care. Accepted insurance types (Medicaid, Cigna, and United Health Group (UHG)), time to an appointment in business days, and self-pay rates were recorded. Practices with invalid contact information and retired obstetricians were excluded. Summary statistics, chi-squared analysis, and a two-way t-test were conducted for the primary outcome. Results Seventy-one out of 178 obstetricians were successfully contacted, of which 31 physicians accepted all three insurances, and 40 physicians did not accept at least one insurance. Of those, 97.2% acceptedUnitedHealthcare, 98.6% accepted Cigna, and 45.1% accepted Medicaid. There was a statistically significant difference when comparing acceptance rates between UHC and Medicaid as well as Cigna and Medicaid (p<0.001). There was no statistically significant difference in acceptance rates in the direct comparison of the two private insurances, Cigna and UnitedHealthcare (p=0.559). The average number of days until the next available appointment was 12.7 (SD= 7.2) for UnitedHealthcare, 20.0 (SD=6.7) for Cigna, and 17.0 (SD=8.6) for Medicaid. There was a statistically significant trend between the type of insurance and the time to the earliest appointment (p=0.002). Conclusion This study demonstrated patients enrolled in Medicaid in South Florida have significantly less access to prenatal care than those with private insurance. This evidence shows that decreased access to care from Medicaid plans can possibly increase the risk of adverse outcomes associated with inadequate prenatal care. This information should be considered by policymakers when considering future Medicaid expansion.

Development and electronic health record validation of an algorithm for identifying patients with Duchenne muscular dystrophy in US administrative claims.

BACKGROUND: Muscular dystrophies (MDs) comprise a heterogenous group of genetically inherited conditions characterized by progressive muscle weakness and increasing disability. The lack of separate diagnosis codes for Duchenne MD (DMD) and Becker MD, 2 of the most common forms of MD, has limited the conduct of DMD-specific real-world studies. OBJECTIVE: To develop and validate administrative claims-based algorithms for identifying patients with DMD and capturing their nonambulatory and ventilation-dependent status. METHODS: This was a retrospective cohort study using the statistically deidentified Optum Market Clarity Database (including patient claims linked with electronic health records [EHRs] data) to develop and validate the following algorithms: DMD diagnosis, nonambulatory status, and ventilation-dependent status. The initial study sample consisted of US patients in the database who had a diagnosis code for Duchenne/Becker MD (DBMD) between October 1, 2018, and September 30, 2020, who were male, aged 40 years or younger on their first DBMD diagnosis, and met continuous enrollment and 1-day minimal clinical activities requirement in a 12-month measurement period between October 1, 2017, and September 30, 2020. The algorithms, developed by a cross-functional team of DMD specialists (including patient advocates), were based on administrative claims data with International Classification of Diseases, Tenth Revision, Clinical Modifications coding, using information of diagnosis codes for DBMD, sex, age, treatment, and disease severity (eg, evidence of ambulation assistance/support and/or evidence of ventilation support or dependence). Patients who met each algorithm and had EHR notes available were then validated against structured fields and unstructured provider notes from their own linked EHR to confirm patients' DMD diagnoses, nonambulatory status, and ventilation-dependent status. Algorithm performance was assessed by positive predictive value with 95% CIs. RESULTS: A total of 1,300 patients were included in the initial study sample. Of these, EHR were available and reviewed for 303 patients. The mean age of the 303 patients was 14.8 years, with 61.7% being non-Hispanic White. A majority had a Charlson comorbidity index score of 0 (59.4%) or 1-2 (27.7%). Positive predictive value (95% CI) was 91.6% (85.8%-95.6%) for the DMD diagnosis algorithm, 88.4% (80.2%-94.1%) for the nonambulatory status algorithm, and 77.8% (62.9%-88.8%) for the ventilation-dependent status algorithm. CONCLUSIONS: This work provides the means to more accurately identify patients with DMD from administrative claims data without a specific diagnosis code. The algorithms validated in this study can be applied to assess treatment effectiveness and other outcomes among patients with DMD treated in clinical practice. DISCLOSURES: This study was funded by Pfizer, which contracted with Optum to perform the study and provide medical writing assistance. Ms Schrader reports being an employee of Parent Project Muscular Dystrophy. Mr Posner reports being an employee and stockholder of Pfizer and receiving support from Pfizer for attending conferences not related to this manuscript. Dr Dorling reports being an employee and stockholder of Pfizer at the time the study was conducted and is a current employee of Chiesi USA, Inc. Ms Senerchia reports being an employee of Optum and owning stock in Pfizer and UnitedHealth Group, the parent company of Optum. Dr Chen reports being an employee and stockholder of Pfizer. Ms Beaverson reports being an employee of Pfizer and owning stock in Pfizer and Amicus Therapeutics. Dr Seare reports being an employee of Optum at the time the study was conducted. Dr Garnier and Ms Merla report being employees of Pfizer. Ms Walker reports being an employee of Optum. Dr Alvir reports being an employee and stockholder of Pfizer. Dr Mahn reports being an employee and stockholder of Pfizer. Dr Zhang reports being an employee of Optum. Ms Landis reports being an employee of Optum. Ms Buikema reports being an employee of Optum and holding stock in UnitedHealth Group, the parent company of Optum.

942-P: A1C-Glucose Management Indicator (GMI) Discordance among Continuous Glucose Monitor (CGM)–Wearing Adults with T2D

ADA Standards of Medical Care considers 14-day CGM-based GMI an A1c surrogate for clinical management. To date, supporting evidence is from T1D or insulin-treated T2D populations. As CGM demand and access grows, quantifying A1c-GMI discordance in diverse T2D populations can inform practice. We evaluated this discordance, stratified by T2D drugs and A1c. CGM-wearing adults with T2D, an overlapping A1c and GMI date (10/2019 to 3/2022), and CGM data sufficiency (DS) ≥ 70% were included. Prior 3 month pharmacy claims defined drug histories. We calculated the Pearson correlation coefficient (r) and A1c-GMI differences by subgroup. A1c-GMI pairs existed for 2,760 people (mean [SD] age 55 [9]; 46% F; 58% had A1c &amp;lt;7%). Overall, pairs highly correlated (56% differed by &amp;lt;0.5%; r=0.80). Non-insulin T2D drug users (N=1,674) had slightly higher concordance than basal insulin (N=437) and basal-bolus insulin users (N=317), with 58%, 50%, and 56% discordance &amp;lt;0.5% (r=0.79, 0.77, 0.77). On average, A1c underestimated GMI for non-insulin users and overestimated GMI for basal and basal-bolus insulin users. Concordance decreased at A1c extremes, with 61-76% concordance for A1cs from 5.7% to 8%. Sensitivity analyes with lower DS had similar results. A1c-GMI discordance varied by T2D drug class and A1c, highlighting how CGM-derived measures can provide personalized insights for diverse T2D populations. Disclosure A.Jhuang: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group. S.Bacon: Employee; Optum Labs, Research Support; Level2. S.Kamrudin: Employee; UnitedHealth Group. N.Thompson: Employee; Level2, Stock/Shareholder; UnitedHealth Group. C.Clark: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group.

987-P: Digital Signals from Continuous Glucose Monitors Predict 90-Day Median Glucose in Type 2 Diabetes

The use of continuous glucose monitors (CGMs) among people with type 2 diabetes continues to expand beyond those treated with insulin or at high-risk for hypoglycemia. Defining precision CGM utilization strategies and augmenting A1c monitoring approaches is increasingly important to inform the application of episodic or continuous wearable data in clinical, payer, and digital health settings. We offer a method to predict 90-day glucose from 30 days of CGM data, offering an accelerated intervention window for people with T2D at low risk of hypoglycemia and no insulin treatment. We used linear regression to predict 90-day glucose from initial median glucose and glycemic variability (Fig1A - eq 2). Of 5516 people with T2D in a digital diabetes program with rtCGM and no insulin use (2019 - 2022), 497 had sufficient data for inclusion (age 56.5 +/- 8.9; 49.5% F, 75% with &amp;gt; 81 days CGM wear in the first 90 days). The data was 80/20 train/test split. The model predicted median glucose at 77 - 90 days with MAE +/- 14.7 mg/dL, RMSE 21.9 mg/dL and adj R2 =0.424 for training; and MAE +/- 16.7 mg/dL, RMSE +/- 26.0 mg/dL for testing. Fig 1B shows the distribution of the MAE of full dataset across different initial median glucose levels. Hence, based on the plot, error IQR and outlier boundary increase beyond 177.6 mg/dL, the model may be best used with initial glucose level &amp;lt; 177.6 mg/dL. Disclosure Z.Li: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group. C.Clark: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group. S.Saha: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group.

638-P: Social Media as a Source of Personalized Weight-Loss Information

People with obesity may seek clinical, nutritional, activity, and psychosocial guidance, but recommendations they receive in clinical settings may be inadequate or lack sufficient personalization to be implemented into their lives. Understanding unmet information needs may enable more tailored weight guidance. We used health narratives posted in a weight loss forum to research topics of information being sought. Public posts (N=52,576) from 1/2020-1/2022 were extracted from r/LoseIt, a Reddit weight loss forum of 3.8M members. From these, 63,006 questions were extracted using a research-purpose BERT language model tested and fine-tuned on 500 hand-annotated questions. Extracted questions were clustered into distinct topics by Top2Vec and hierarchical clustering. Excluding 2 uninterpretable topics, 27 of 28 (96%) topics represented requests for personalized recommendations. Topics focused on diet (7%), exercise (7%), sensemaking (11%), how to implement a behavior change or solve a weight-loss problem (11%), tips for specific stages of weight loss (beginning, plateau) (7%), and comparing weight loss experiences (11%). Weight-loss forum users requested personalized recommendations to support sensemaking of frustrating weight loss problems and ask for help choosing and deploying behavior change. Results call for interventions customized to individuals’ weight loss stage, process, experiences, and motivations. Disclosure C.Clark: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group. J.Stremmel: None. R.G.Mccoy: Consultant; Emmi. M.Jarvis: Employee; Optum Labs, UnitedHealth Group, Stock/Shareholder; Oramed Pharmaceuticals, UnitedHealth Group, Dexcom, Inc., Apple, Hologic Inc., Intuitive Surgical. J.D.Ard: Advisory Panel; Novo Nordisk, Consultant; Eli Lilly and Company, Intuitive Surgical, Regeneron, Other Relationship; Optum Labs, Weight Watchers International, Research Support; Nestlé Health Science, Boehringer Ingelheim Inc., Epitomee, KVK Tech. N.Lambert: Employee; Optum Labs.

1430-P: Early Real-World Experiences with Tirzepatide

Online communities offer real-world data about interactions with new treatments prior to visibility in clinical or administrative data assets. We evaluated early tirzepatide initiation experiences reported in online health narratives after its May 2022 FDA approval for type 2 diabetes. At data extraction, &amp;lt; 10 tirzepatide claims were in OptumLabs’ deidentified administrative data. We extracted all publicly available posts (N=786) from r/Mounjaro (5/22 to 9/22), a Reddit community of 16,200 members. Categorical coding (agreement = .99) assessed the demographics, clinical history, treatment effects, and side effects from SURPASS trials and captured open-ended details of experiences. Most posts (67.3%) posed a question and included the r/Mounjaro users’ tirzepatide status (78.1%). Of narratives describing active tirzepatide use (N=465; 59.2%), common SURPASS side effects were decreased appetite (21.9%), nausea (11.2%), abdominal discomfort (5.8%), and diarrhea (5.2%). Common poster-defined side effects were fatigue (6.5%), body aches/stiffness (4.1%), and burping (4.1%). Posters reported tirzepatide use for weight (8.4%) more than glucose (0.4%) and obtained prescriptions from virtual clinics (7.1%) more than primary care (4.1%) or obesity specialists (0.4%). While missing some clinical details, online health narratives offer accelerated insights and can inform practice prior to traditional observational data availability. Disclosure N.Lambert: Employee; Optum Labs. M.Jarvis: Employee; Optum Labs, UnitedHealth Group, Stock/Shareholder; Oramed Pharmaceuticals, UnitedHealth Group, Dexcom, Inc., Apple, Hologic Inc., Intuitive Surgical. J.Fester: None. R.G.Mccoy: Consultant; Emmi. J.D.Ard: Advisory Panel; Novo Nordisk, Consultant; Eli Lilly and Company, Intuitive Surgical, Regeneron, Other Relationship; Optum Labs, Weight Watchers International, Research Support; Nestlé Health Science, Boehringer Ingelheim Inc., Epitomee, KVK Tech. C.Clark: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group.

1428-P: Type 2 Diabetes Drug Utilization by Claims-Based and Self-Reported Weight Status

Background: Weight is an increasingly important component of care goals and treatment selection for people with type 2 diabetes (T2D). Over 80% of people with T2D have obesity, yet population-level assessments can be challenging as weight is often underreported in administrative data. Methods: We conducted a cross-sectional descriptive analysis of 8,680 commercially insured adults enrolled in a virtual specialty clinic (Level2) for at least one year using de-identified administrative claims and patient-reported BMI in a research database. Diabetes drug prevalence was measured using fill rates and stratified by claims-based and self-reported weight, to describe differences. Claims and diabetes drug fills from 9/15/2021 to 9/15/2022 were included. Results: Overall, 25.1% (n = 2183) had an obesity-related claim. Of the subset with a self-reported BMI, 76.3% (n = 366) had obesity and 50.1% (n = 187) had at least one obesity-related claim. Diabetes drug fills (Table 1) varied by class, BMI strata, and BMI source. After biguanides, GLP-1 RAs were the most filled class, with utilization varying from 21% (self-reported BMI 25 to 30 kg/m2) to 34% (claims-based BMI &amp;gt; 40 kg/m2). Conclusion: Despite the importance of weight in T2D care, it remains underreported in administrative data assets. Using administrative data together with accurate measures of weight, including from self-report, can inform T2D practice and program design. Disclosure P.Wollersheim: Employee; Level2. S.Bacon: Employee; Optum Labs, Research Support; Level2. N.Thompson: Employee; Level2, Stock/Shareholder; UnitedHealth Group. C.Clark: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group.

1174-P: Characterization of Glucose Levels in Pregnancy Measured by Blood Glucose Testing or CGM Monitoring after a 50-g Screening or a 75-g or 100-g OGTT

Glucose challenge testing (GCT) is standard diagnostic approach for gestational diabetes (GDM). Using CGM glucose values to characterize glycemia during GCT is not well described. CGM and blood glucose (BG) values were matched with closest CGM value ±5 min of each reported BG time. GDM diagnosed by standard glucose thresholds for 50g GCT, 75g and 100g OGTTs. GCT (n=543, mean gestation 28 wks) showed mean±SD 1 hr BG of 117±28 mg/dL, while matched CGM mean BG was 126±36 mg/dL. The 1 hr BG was ≥135 mg/dL in 24% of GCT vs. 38% by CGM. OGTT (75g) (n=44, mean gestational age 28 wks) showed mean±SD fasting, 1 hr and 2 hr BG of 84±9 mg/dL, 156±33 mg/dL, and 119±26 mg/dL. OGTT (100g) (n=77, mean gestational age 29 wks) showed mean±SD fasting, 1 hr, 2 hr, and 3 hr BG of 82±9 mg/dL, 166±31 mg/dL, 137±27, and 101±27 mg/dL. CGM levels during GCT and both OGTT were similar but slightly higher for each time point; maximum glucose and glucose excursions were also similar between each test vs CGM. Those diagnosed with GDM had consistently higher CGM glucoses than those without GDM (Figure 1). CGM during GCT/OGTT demonstrates CGM correlates to BG, although consistently slightly higher for all 3 glucose tests, regardless of glucose load or timing of measurement. Correlating CGM values to obstetric outcomes would help further describe the role of CGM for diagnosing GDM and improving glucose metabolism in pregnancy. Disclosure A.L.Carlson: Advisory Panel; MannKind Corporation, Novo Nordisk, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk, Insulet Corporation, UnitedHealth Group, Sanofi. J.Sibayan: None. P.Calhoun: None. C.Durnwald: None. R.Beck: Consultant; Eli Lilly and Company, Novo Nordisk, Diasome, Insulet Corporation, Research Support; Tandem Diabetes Care, Inc., Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc., Medtronic, Ascensia Diabetes Care, Roche Diabetes Care, Eli Lilly and Company, Novo Nordisk. Z.Li: None. E.Norton: None. R.M.Bergenstal: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Zealand Pharma A/S, Consultant; Ascensia Diabetes Care, Bigfoot Biomedical, Inc., CeQur SA, Dexcom, Inc., Hygieia, Onduo LLC, Sanofi, Vertex Pharmaceuticals Incorporated, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk, Sanofi, UnitedHealth Group. M.L.Johnson: Research Support; Abbott, Lilly, Insulet Corporation, NIH - National Institutes of Health, Patient-Centered Outcomes Research Institute, Novo Nordisk, Tandem Diabetes Care, Inc., Medtronic, Hemsley Charitable Trust, Jaeb Center for Health Research. S.Dunnigan: None. M.Banfield: None. K.J.Krumwiede: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust; United Health Group

173-OR: CGM-Measured Differences in Pregnancies With vs. Without Gestational Diabetes (GDM) and Adverse Perinatal Outcomes (APO)

An objective of the study was to characterize if continuous glucose monitor (CGM) glycemic patterns throughout pregnancy are indicative of gestational diabetes (GDM) and adverse pregnancy outcomes (APOs). A prospective observational cohort of 760 pregnant patients enrolled &amp;lt;17 weeks with A1c &amp;lt;6.5% wore a blinded CGM sequentially during pregnancy. Patients with ≥14 days of CGM data overall with ≥10 days in the 2nd trimester, oral glucose tolerance test (OGTT), and an APO assessment were included. The primary outcome was GDM diagnosis by abnormal OGTT. Large gestational age (LGA) birthweight &amp;gt;90% and hypertensive disorder of pregnancy (HDP) were analyzed. Glycemic metrics using CGM between those with and without GDM and each APO were compared. Participants had a mean±SD of 112±42 days of CGM data. Prevalence of GDM, LGA, and HDP were 7%, 16%, and 27%. Mean glucose, glucose standard deviation, time &amp;gt; 120 mg/dL and &amp;gt; 140 mg/dL were significantly higher during the entire gestational period prior to OGTT (mean 27 ± 2 weeks) in those who developed GDM. TIR 63-120 mg/dL and 63-140 mg/dL were significantly lower in those who developed GDM (Table 1). Similar findings were noted for the diagnosis of LGA and HDP. CGM use during pregnancy revealed glycemic differences between those with vs without GDM, LGA, and HDP throughout gestation. Higher glucose levels during pregnancy are associated with these APOs. Disclosure C.Durnwald: None. P.Calhoun: None. A.L.Carlson: Advisory Panel; MannKind Corporation, Novo Nordisk, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk, Insulet Corporation, UnitedHealth Group, Sanofi. R.Beck: Consultant; Eli Lilly and Company, Novo Nordisk, Diasome, Insulet Corporation, Research Support; Tandem Diabetes Care, Inc., Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc., Medtronic, Ascensia Diabetes Care, Roche Diabetes Care, Eli Lilly and Company, Novo Nordisk. Z.Li: None. E.Norton: None. R.M.Bergenstal: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Zealand Pharma A/S, Consultant; Ascensia Diabetes Care, Bigfoot Biomedical, Inc., CeQur SA, Dexcom, Inc., Hygieia, Onduo LLC, Sanofi, Vertex Pharmaceuticals Incorporated, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk, Sanofi, UnitedHealth Group. M.Banfield: None. M.L.Johnson: Research Support; Abbott, Lilly, Insulet Corporation, NIH - National Institutes of Health, Patient-Centered Outcomes Research Institute, Novo Nordisk, Tandem Diabetes Care, Inc., Medtronic, Hemsley Charitable Trust, Jaeb Center for Health Research. S.Dunnigan: None. J.Sibayan: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust; United Health Group

172-OR: Normative CGM Glucose Levels throughout Gestation in Patients with Uncomplicated Pregnancies

Glycemic patterns throughout pregnancy are not well described, particularly early pregnancy. CGM used throughout the gestational period in uncomplicated pregnancies may help describe glycemic patterns in more detail. Blinded CGM data were collected throughout pregnancy from 760 pregnant patients ≥18 years old, with HbA1c &amp;lt;6.5%, no known diabetes, and gestational age &amp;lt;17 weeks. CGM data from uncomplicated pregnancies (pregnancy without gestational diabetes, large for gestational age birth, or hypertensive disorder of pregnancy) established the normative data set. Uncomplicated pregnancies (n=427, mean±SD age 32±4 years, 73% White non-Hispanic, mean HbA1c 5.1±0.3%) showed mean glucose during the entire gestational period was 99±7 mg/dL. Trimester specific mean glucose was: 103±7, 98±7 and 98±8 mg/dL for 1st, 2nd, 3rd trimesters. Figure 1 shows mean glucose by hour/trimester. Median (quartiles) percent time in range (TIR) 63-120 mg/dL was 86% (82-89%) for gestational period, and 84% (79-89%), 87% (82-90%), and 85% (80-90%) for 1st, 2nd, 3rd trimesters. Figure 2 shows TIR 63-120 mg/dL by 4-week periods. In uncomplicated pregnancies, mean glucose and TIR 63-120 mg/dL remained consistent throughout the gestational period. These normative CGM data will help set pregnancy-specific glycemic targets and will be important to compare to those 333 women in this study with complicated pregnancies. Disclosure A.L.Carlson: Advisory Panel; MannKind Corporation, Novo Nordisk, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk, Insulet Corporation, UnitedHealth Group, Sanofi. J.Sibayan: None. P.Calhoun: None. C.Durnwald: None. R.Beck: Consultant; Eli Lilly and Company, Novo Nordisk, Diasome, Insulet Corporation, Research Support; Tandem Diabetes Care, Inc., Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc., Medtronic, Ascensia Diabetes Care, Roche Diabetes Care, Eli Lilly and Company, Novo Nordisk. Z.Li: None. E.Norton: None. R.M.Bergenstal: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Zealand Pharma A/S, Consultant; Ascensia Diabetes Care, Bigfoot Biomedical, Inc., CeQur SA, Dexcom, Inc., Hygieia, Onduo LLC, Sanofi, Vertex Pharmaceuticals Incorporated, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk, Sanofi, UnitedHealth Group. M.L.Johnson: Research Support; Abbott, Lilly, Insulet Corporation, NIH - National Institutes of Health, Patient-Centered Outcomes Research Institute, Novo Nordisk, Tandem Diabetes Care, Inc., Medtronic, Hemsley Charitable Trust, Jaeb Center for Health Research. S.Dunnigan: None. M.Banfield: None. K.J.Krumwiede: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust; United Health Group

131-LB: Diabetes and Disparities in Continuous Glucose Monitoring in Community Health Care Settings

Federally qualified health centers (FQHCs) serve vulnerable DM patients in primary care in underserved settings. The state of DM (glycemic control, complications) may differ and utilization of technologies (e.g. continuous glucose monitoring [CGM]) may be essential. But the current state of DM and CGM is poorly characterized. Using EHR data from a national FQHC network (2015-2021) we examined baseline demographic characteristics, CGM prescriptions, and their association. We included 47,579 with DM: n=1630 with T1D [3%], n= 45,949 T2D [97%], 38% Hispanic, 34% Black (Table 1). Notably, T1D pts [mean age 43 SD 16], had poor glycemic control (HbA1c 9.4 SD 2.4) with elevated DM complications severity index scores [mean DSCI 2.3 SD 4.7]. Overall CGM prescriptions were extremely low; 9% in T1D and only 1% in T2D. Among T1D, those who were Hispanic [OR 0.39, (CI 0.23, 0.66), p &amp;lt; 0.001] or Black [OR 0.52, (CI 0.33, 0.81), p = 0.003] were less likely to have CGM prescribed than White adults, after adjustment. Among T2D, those who were Hispanic [OR 0.42, CI 0.33, 0.55, p &amp;lt; 0.001] or Black [OR 0.68, CI 0.54, 0.85, p = 0.001] were similarly less likely to have CGM. Non-private insurance was also a significant factor. DM severity (poor control, complications) is notable in FQHCs, yet CGM is exceptionally low. These findings underscore the major translation gap in standard of care for FQHCs and the critical need to understand inequities. Disclosure A. Wallia: Research Support; UnitedHealth Group, Novo Nordisk, Eli Lilly and Company. D. Bright: None. A. Eggleston: None. M. J. O'brien: None. S. Agarwal: Advisory Panel; Medtronic, Consultant; Beta Bionics, Inc., Research Support; Abbott Diabetes, Dexcom, Inc. A. L. Owen: None. E. L. Lam: None. K. Davis: None. S. Bailey: Advisory Panel; Gilead Sciences, Inc., Consultant; Lundbeck, Pfizer Inc., Research Support; Eli Lilly and Company, Merck Sharp &amp; Dohme Corp., Gilead Sciences, Inc., Lundbeck, Pfizer Inc. S. E. Delacey: None. A. Pack: Consultant; Gilead Sciences, Inc., Research Support; Merck &amp; Co., Inc., Pfizer Inc., Gordon and Betty Moore Foundation, RRF Foundation for Aging, Lundbeck, Eli Lilly and Company, Gilead Sciences, Inc. J. Espinoza: Consultant; Sanofi, Research Support; NIH - National Institutes of Health, FDA, Speaker's Bureau; Glooko, Inc. Funding Centers for Diabetes Translation Research (5P30DK020541, 472P30DK092949-11A); National Pilot and Feasibility Grant for Diabetes Research Centers; Center for Diabetes Translation Research

764-P: Time in Range and Time in Tight Range in Tirzepatide-Treated Patients Achieving Normoglycemia in the SURPASS-3 CGM Substudy

Tirzepatide (TZP), a novel once-weekly GIP/GLP-1 receptor agonist, demonstrated superior glycemic control vs insulin degludec (IDeg) in SURPASS-3 CGM. This post-hoc analysis evaluated changes from baseline to Week (Wk) 52 in Time in Range (TIR) (71-180 mg/dL), Time in Tight Range (TITR) (71-140 mg/dL), and glycemic variation (within-day coefficient of variation (CV) and Mean Amplitude of Glycemic Excursions (MAGE)) in TZP-treated patients achieving or not achieving HbA1c &amp;lt;5.7% at Wk 52. Interstitial glucose values were collected by CGM at 5-minute intervals for 7 days at baseline, Wk 24, and Wk 52 in a subset of patients in the SURPASS-3 trial. Analyses used pooled data from all TZP arms (5, 10, 15 mg) only due to limited sample size for IDeg patients achieving HbA1c &amp;lt;5.7% at Wk 52. Patients achieving HbA1c &amp;lt;5.7% were slightly younger, had lower HbA1c and FSG, and higher TITR and TIR vs those not achieving HbA1c &amp;lt;5.7% at baseline (Table). Increases in daily TITR and TIR from baseline (61.02% and 41.12% respectively) were seen in patients achieving HbA1c &amp;lt;5.7% while those not achieving HbA1c &amp;lt;5.7% had increased daily TITR and TIR of 36.62% and 32.40% (Table). Within-day CV and MAGE were reduced in both patient groups but more apparent in those achieving HbA1c &amp;lt;5.7%. In TZP-treated patients, improvements in TIR, TITR, and glycemic variability were more pronounced in those achieving HbA1c &amp;lt;5.7%. Disclosure R.M.Bergenstal: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Zealand Pharma A/S, Consultant; Ascensia Diabetes Care, Bigfoot Biomedical, Inc., CeQur SA, Dexcom, Inc., Hygieia, Onduo LLC, Sanofi, Vertex Pharmaceuticals Incorporated, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk, Sanofi, UnitedHealth Group. Á.Rodríguez: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. B.D.Benneyworth: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. C.Nicolay: Employee; Eli Lilly and Company. K.Brown: Employee; Eli Lilly and Company. Funding Eli Lilly and Company