Identifying erroneous height and weight values from adult electronic health records in the All of Us research program.

INTRODUCTION: Electronic Health Records (EHR) are a useful data source for research, but their usability is hindered by measurement errors. This study investigated an automatic error detection algorithm for adult height and weight measurements in EHR for the All of Us Research Program (All of Us). METHODS: We developed reference charts for adult heights and weights that were stratified on participant sex. Our analysis included 4,076,534 height and 5,207,328 wt measurements from âˆ¼ 150,000 participants. Errors were identified using modified standard deviation scores, differences from their expected values, and significant changes between consecutive measurements. We evaluated our method with chart-reviewed heights (8,092) and weights (9,039) from 250 randomly selected participants and compared it with the current cleaning algorithm in All of Us. RESULTS: The proposed algorithm classified 1.4 % of height and 1.5 % of weight errors in the full cohort. Sensitivity was 90.4 % (95 % CI: 79.0-96.8 %) for heights and 65.9 % (95 % CI: 56.9-74.1 %) for weights. Precision was 73.4 % (95 % CI: 60.9-83.7 %) for heights and 62.9 (95 % CI: 54.0-71.1 %) for weights. In comparison, the current cleaning algorithm has inferior performance in sensitivity (55.8 %) and precision (16.5 %) for height errors while having higher precision (94.0 %) and lower sensitivity (61.9 %) for weight errors. DISCUSSION: Our proposed algorithm outperformed in detecting height errors compared to weights. It can serve as a valuable addition to the current All of Us cleaning algorithm for identifying erroneous height values.

Measuring social determinants of health in the All of Us Research Program.

To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbach's alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

Burden of employment loss and absenteeism in adults and caregivers of children with sickle cell disease.

ABSTRACT: Sickle cell disease (SCD) is a genetic disorder affecting 100 000 people with an estimated annual medical cost of $3 billion in the United States; however, the economic impact on patients is not well described. We aimed to examine the indirect economic burden and test the hypothesis that socioeconomic status and greater social vulnerability risks are associated with increased absenteeism and employment loss. We surveyed adults and caregivers of children with SCD at 5 US centers from 2014 to 2021. Logistic regression models were used to examine the associations of employment loss and missed days of work with demographics and social determinants. Indirect costs were estimated by multiplying the self-reported missed days of work and job loss by 2022 average wages by the state of the participating institution. Of the 244 participants, 10.3% reported employment loss in the last 5 years, and 17.5% reported missing 10 or more days of work. Adults had 3 times more employment loss compared with caregivers of children with SCD (OR, 3.18; 95% CI, 1.12-9.01) but fewer missed days of work (OR, 0.24; 95% CI, 0.11-0.0.51). Participants who did not live with a partner reported increased employment loss (OR, 4.70; 95% CI, 1.04-21.17) and more missed days of work (OR, 4.58; 95% CI, 1.04-20.15). The estimated annual indirect economic burden was $2 266 873 ($9290 per participant). Adults with SCD and caregivers of children with SCD commonly report employment loss and missed days of work as important risk factors. The high indirect economic burden suggests that future economic evaluations of SCD should include SCD-related indirect economic burden.

Comparing super-utilizers and lower-utilizers among commercial- and Medicare-insured adults with sickle cell disease.

ABSTRACT: Sickle cell disease (SCD) is a rare but costly condition in the United States. Super-utilizers have been defined as a subset of the population with high health care encounters or expenditures. Although super-utilizers have been described in other disease states, little is known about super-utilizers among adults with SCD. This study aimed to characterize the differences in expenditures, overall health care encounters, and pain episode encounters between super-utilizers (top 10% expenditures) and lower-utilizers with SCD (high, top 10%-24.9%; moderate, 25%-49.9%; and low, bottom 50% expenditures). A retrospective longitudinal cohort of adults with SCD were identified using validated algorithms in MarketScan and Medicare claim databases from 2016 to 2020. Encounters and expenditures were analyzed from inpatient, outpatient, and emergency department settings. Differences in encounters and expenditures between lower-utilizers and super-utilizers were compared using logistic regression. Among super-utilizers, differences in encounters and expenditures were compared according to incidences of pain episode encounters. The study population included 5666 patients with commercial insurance and 8600 with Medicare. Adjusted total annual health care expenditure was 43.46 times higher for super-utilizers than for low-utilizers among commercial-insured and 13.37 times higher in Medicare-insured patients. Among super-utilizers, there were patients with few pain episode encounters who had higher outpatient expenditures than patients with a high number of pain episode encounters. Our findings demonstrate the contribution of expensive outpatient care among SCD super-utilizers, in which analyses of high expenditure have largely focused on short-term care. Future studies are needed to better understand super-utilizers in the SCD population to inform the effective use of preventive interventions and/or curative therapies.

Primary care use and depression screening among young adults with sickle cell disease during their final year of pediatric hematology care.

Depression may contribute to transition risk among young adults with sickle cell disease (SCD). It is unclear if they receive depression screening because primary care providers (PCPs) routinely perform this screening, but PCP use declines with age. This retrospective study of young adults with SCD during their final year of pediatric hematology care identified 51 (91%) had PCPs. Among those with hospital system PCPs, 20% saw their PCP and 50% of those were screened for depression by the PCP. This suggests young adults with SCD may not receive depression screening or see PCPs, leading to potential missed opportunities for intervention.

A feasibility randomized controlled trial of an mHealth app vs booklets for patient-facing guidelines in adults with SCD.

Despite the increased number of evidence-based guidelines for sickle cell disease (SCD), dissemination of evidence-based guidelines in lay language for individuals or families with SCD has not been evaluated. We conducted a feasibility randomized controlled trial to determine the acceptability of a mobile health (mHealth) app with patient-facing guidelines to improve the knowledge of individuals with SCD about SCD-specific knowledge and reduce hospitalizations. Primary outcome measures include recruitment, retention, and adherence rates. Adults with SCD were enrolled at 2 sickle cell centers between 2018 and 2022. Participants were randomized to receive either an mHealth app + booklet with patient-facing guidelines or a booklet with the guidelines alone. Participants completed surveys at baseline and a final 6-month visit. Approximately 67 of 74 (91%) agreed to participate and were randomized, with 50 of 67 (75%) completing all the study components. All participants who completed the study in the treatment arm used the app. Our results demonstrated high recruitment, retention, and adherence rate for the first randomized trial for an mHealth app with patient-facing guidelines in adults with SCD. This clinical trial was registered at https://www.clinicaltrials.gov/ as #NCT03629678.

Comparison of thromboembolism outcomes in patients with sickle cell disease prescribed hormonal contraception.

Patients with sickle cell disease (SCD) are at a risk of thromboembolism (TE), and use of hormonal contraception can further increase that risk. This study aims to assess patterns of hormonal contraceptive use and compare risk of contraception-related TE between combined hormonal contraceptives (CHCs) and progestin-only contraceptives (POCs). Patients with SCD aged between 12 and 44 years with a new prescription of a hormonal contraceptive in the Centers for Medicare and Medicaid Services Medicaid Analytic eXtract database (2006-2018) were followed up to 1 year. We identified 7173 new users: 44.6% initiated CHC and 55.4% initiated POC. Combined oral contraceptive pills (OCPs; 36.5%) and progestin-only depot medroxyprogesterone acetate (33.9%) were the most frequently prescribed agents. A total of 1.8% of contraception users had a new diagnosis of TE within 1 year of the first identified contraception prescription. There were no significant differences in TE event rates between CHC and POC users (17.2 and 24.7 events per 1000 person-years, respectively). In patients prescribed OCP, there were no differences in TE event rates based on estrogen dose or progestin generation. Transdermal patch had a 2.4-fold increased risk of TE as compared with that of OCP. Although limited by the retrospective study design and use of administrative claims data, this study found no significant differences in TE rates between new users of CHC and POC in patients with SCD. Careful evaluation of underlying TE risk factors should be considered for each patient with SCD before initiation of hormonal contraception.

Pregnancy-related thromboembolism in women with sickle cell disease: An analysis of National Medicaid Data.

Pregnancy and sickle cell disease (SCD) both individually carry a risk of thromboembolism (TE). Pregnancy in people with SCD may further enhance the prothrombotic effect of the underlying disease. The objectives of this study were to determine the rate and risk factors for arterial and venous thrombosis in pregnant people with SCD. Administrative claims data from the United States Centers for Medicare and Medicaid Service Analytic eXtract from 2006 to 2018 were used. The study population included people with SCD from the start of their first identified pregnancy until 1 year postpartum and a control cohort of pregnant people without SCD of similar age and race. Outcomes of interest were identified with ICD-9 or 10 codes. Logistic regression analyses were used to analyze risk factors. We identified infant deliveries in 6388 unique people with SCD and 17 110 controls. A total of 720 venous thromboembolism (11.3%) and 335 arterial TE (5.2%) were observed in people with SCD compared to 202 (1.2%) and 95 (0.6%) in controls. People with SCD had an 8-11 times higher odds of TE compared to controls (p < .001). Within the SCD cohort, age, hemoglobin SS (HbSS) genotype, hypertension, and history of thrombosis were identified as independent risk factors for pregnancy-related TE. Pregnancy-specific factors (pre-eclampsia, eclampsia, multigestational pregnancy) were not associated with TE. In conclusion, the risk of pregnancy-related TE is considerably higher in people with SCD compared with controls without SCD. Hence, people with SCD, particularly those with multiple risk factors may be candidates for thromboprophylaxis during pregnancy and the postpartum period.

The All of Us Data and Research Center: Creating a Secure, Scalable, and Sustainable Ecosystem for Biomedical Research.

The All of Us Research Program's Data and Research Center (DRC) was established to help acquire, curate, and provide access to one of the world's largest and most diverse datasets for precision medicine research. Already, over 500,000 participants are enrolled in All of Us, 80% of whom are underrepresented in biomedical research, and data are being analyzed by a community of over 2,300 researchers. The DRC created this thriving data ecosystem by collaborating with engaged participants, innovative program partners, and empowered researchers. In this review, we first describe how the DRC is organized to meet the needs of this broad group of stakeholders. We then outline guiding principles, common challenges, and innovative approaches used to build the All of Us data ecosystem. Finally, we share lessons learned to help others navigate important decisions and trade-offs in building a modern biomedical data platform.

Importance of missingness in baseline variables: A case study of the All of Us Research Program.

OBJECTIVE: The All of Us Research Program collects data from multiple information sources, including health surveys, to build a national longitudinal research repository that researchers can use to advance precision medicine. Missing survey responses pose challenges to study conclusions. We describe missingness in All of Us baseline surveys. STUDY DESIGN AND SETTING: We extracted survey responses between May 31, 2017, to September 30, 2020. Missing percentages for groups historically underrepresented in biomedical research were compared to represented groups. Associations of missing percentages with age, health literacy score, and survey completion date were evaluated. We used negative binomial regression to evaluate participant characteristics on the number of missed questions out of the total eligible questions for each participant. RESULTS: The dataset analyzed contained data for 334,183 participants who submitted at least one baseline survey. Almost all (97.0%) of the participants completed all baseline surveys, and only 541 (0.2%) participants skipped all questions in at least one of the baseline surveys. The median skip rate was 5.0% of the questions, with an interquartile range (IQR) of 2.5% to 7.9%. Historically underrepresented groups were associated with higher missingness (incidence rate ratio (IRR) [95% CI]: 1.26 [1.25, 1.27] for Black/African American compared to White). Missing percentages were similar by survey completion date, participant age, and health literacy score. Skipping specific questions were associated with higher missingness (IRRs [95% CI]: 1.39 [1.38, 1.40] for skipping income, 1.92 [1.89, 1.95] for skipping education, 2.19 [2.09-2.30] for skipping sexual and gender questions). CONCLUSION: Surveys in the All of Us Research Program will form an essential component of the data researchers can use to perform their analyses. Missingness was low in All of Us baseline surveys, but group differences exist. Additional statistical methods and careful analysis of surveys could help mitigate challenges to the validity of conclusions.

Design and Implementation of the All of Us Research Program COVID-19 Participant Experience (COPE) Survey.

In response to the rapidly evolving coronavirus disease 2019 (COVID-19) pandemic, the All of Us Research Program longitudinal cohort study developed the COVID-19 Participant Experience (COPE) survey to better understand the pandemic experiences and health impacts of COVID-19 on diverse populations within the United States. Six survey versions were deployed between May 2020 and March 2021, covering mental health, loneliness, activity, substance use, and discrimination, as well as COVID-19 symptoms, testing, treatment, and vaccination. A total of 104,910 All of Us Research Program participants, of whom over 73% were from communities traditionally underrepresented in biomedical research, completed 275,201 surveys; 9,693 completed all 6 surveys. Response rates varied widely among demographic groups and were lower among participants from certain racial and ethnic minority populations, participants with low income or educational attainment, and participants with a Spanish language preference. Survey modifications improved participant response rates between the first and last surveys (13.9% to 16.1%, P < 0.001). This paper describes a data set with longitudinal COVID-19 survey data in a large, diverse population that will enable researchers to address important questions related to the pandemic, a data set that is of additional scientific value when combined with the program's other data sources.

Creating an automated contemporaneous cohort in sickle cell anemia to predict survival after disease-modifying therapy.

The Food and Drug Administration requires contemporaneous controls to compare clinical outcomes for participants receiving experimental gene therapy or gene editing clinical trials. However, developing a contemporaneous cohort of rare diseases requires multiple person-hours. In a single referral center for sickle cell disease, we tested the hypothesis that we could create an automated contemporaneous cohort of children and adults with sickle cell anemia (SCA) to predict mortality. Data were obtained between 1 January 2004 and 30 April 2021. We identified 419 individuals with SCA with consistent medical care defined as followed continuously for >0.5 years with no visit gaps >3.0 years. The median age was 10.2 years (IQR, 1-24 years), with a median follow-up of 7.4 years (IQR, 3.6-13.5 years) and 47 deaths. A total of 98% (274 of 277) of the children remained alive at 18 years of age, and 34.3% (94 of 274) of those children were followed into adulthood. For adults, the median age of survival was 49.3 years. Treatment groups were mutually exclusive and in a hierarchical order: hematopoietic stem cell transplant (n = 22)>regular blood transfusion for at least 2 years (n = 56)>hydroxyurea for at least 1 year (n = 243)>no disease-modifying therapy (n = 98). Compared to those receiving no disease-modifying treatment, those treated with hydroxyurea therapy had a significantly lower hazard of mortality (hazard ratio = 0.38; P = 0.016), but no statistical difference for those receiving regular blood transfusions compared to no disease-modifying therapy (hazard ratio = 0.71; P = 0.440). An automated contemporaneous SCA cohort can be generated to estimate mortality in children and adults with SCA.

Patient-Centered Digital Health Records and Their Effects on Health Outcomes: Systematic Review.

BACKGROUND: eHealth tools such as patient portals and personal health records, also known as patient-centered digital health records, can engage and empower individuals with chronic health conditions. Patients who are highly engaged in their care have improved disease knowledge, self-management skills, and clinical outcomes. OBJECTIVE: We aimed to systematically review the effects of patient-centered digital health records on clinical and patient-reported outcomes, health care utilization, and satisfaction among patients with chronic conditions and to assess the feasibility and acceptability of their use. METHODS: We searched MEDLINE, Cochrane, CINAHL, Embase, and PsycINFO databases between January 2000 and December 2021. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. Eligible studies were those evaluating digital health records intended for nonhospitalized adult or pediatric patients with a chronic condition. Patients with a high disease burden were a subgroup of interest. Primary outcomes included clinical and patient-reported health outcomes and health care utilization. Secondary outcomes included satisfaction, feasibility, and acceptability. Joanna Briggs Institute critical appraisal tools were used for quality assessment. Two reviewers screened titles, abstracts, and full texts. Associations between health record use and outcomes were categorized as beneficial, neutral or clinically nonrelevant, or undesired. RESULTS: Of the 7716 unique publications examined, 81 (1%) met the eligibility criteria, with a total of 1,639,556 participants across all studies. The most commonly studied diseases included diabetes mellitus (37/81, 46%), cardiopulmonary conditions (21/81, 26%), and hematology-oncology conditions (14/81, 17%). One-third (24/81, 30%) of the studies were randomized controlled trials. Of the 81 studies that met the eligibility criteria, 16 (20%) were of high methodological quality. Reported outcomes varied across studies. The benefits of patient-centered digital health records were most frequently reported in the category health care utilization on the "use of recommended care services" (10/13, 77%), on the patient-reported outcomes "disease knowledge" (7/10, 70%), "patient engagement" (13/28, 56%), "treatment adherence" (10/18, 56%), and "self-management and self-efficacy" (10/19, 53%), and on the clinical outcome "laboratory parameters," including HbA1c and low-density lipoprotein (LDL; 16/33, 48%). Beneficial effects on "health-related quality of life" were seen in only 27% (4/15) of studies. Patient satisfaction (28/30, 93%), feasibility (15/19, 97%), and acceptability (23/26, 88%) were positively evaluated. More beneficial effects were reported for digital health records that predominantly focus on active features. Beneficial effects were less frequently observed among patients with a high disease burden and among high-quality studies. No unfavorable effects were observed. CONCLUSIONS: The use of patient-centered digital health records in nonhospitalized individuals with chronic health conditions is potentially associated with considerable beneficial effects on health care utilization, treatment adherence, and self-management or self-efficacy. However, for firm conclusions, more studies of high methodological quality are required. TRIAL REGISTRATION: PROSPERO (International Prospective Register of Systematic Reviews) CRD42020213285; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=213285.

The All of Us Research Program: Data quality, utility, and diversity.

The All of Us Research Program seeks to engage at least one million diverse participants to advance precision medicine and improve human health. We describe here the cloud-based Researcher Workbench that uses a data passport model to democratize access to analytical tools and participant information including survey, physical measurement, and electronic health record (EHR) data. We also present validation study findings for several common complex diseases to demonstrate use of this novel platform in 315,000 participants, 78% of whom are from groups historically underrepresented in biomedical research, including 49% self-reporting non-White races. Replication findings include medication usage pattern differences by race in depression and type 2 diabetes, validation of known cancer associations with smoking, and calculation of cardiovascular risk scores by reported race effects. The cloud-based Researcher Workbench represents an important advance in enabling secure access for a broad range of researchers to this large resource and analytical tools.

Comparing medical history data derived from electronic health records and survey answers in the All of Us Research Program.

OBJECTIVE: A participant's medical history is important in clinical research and can be captured from electronic health records (EHRs) and self-reported surveys. Both can be incomplete, EHR due to documentation gaps or lack of interoperability and surveys due to recall bias or limited health literacy. This analysis compares medical history collected in the All of Us Research Program through both surveys and EHRs. MATERIALS AND METHODS: The All of Us medical history survey includes self-report questionnaire that asks about diagnoses to over 150 medical conditions organized into 12 disease categories. In each category, we identified the 3 most and least frequent self-reported diagnoses and retrieved their analogues from EHRs. We calculated agreement scores and extracted participant demographic characteristics for each comparison set. RESULTS: The 4th All of Us dataset release includes data from 314 994 participants; 28.3% of whom completed medical history surveys, and 65.5% of whom had EHR data. Hearing and vision category within the survey had the highest number of responses, but the second lowest positive agreement with the EHR (0.21). The Infectious disease category had the lowest positive agreement (0.12). Cancer conditions had the highest positive agreement (0.45) between the 2 data sources. DISCUSSION AND CONCLUSION: Our study quantified the agreement of medical history between 2 sources-EHRs and self-reported surveys. Conditions that are usually undocumented in EHRs had low agreement scores, demonstrating that survey data can supplement EHR data. Disagreement between EHR and survey can help identify possible missing records and guide researchers to adjust for biases.