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.

Scalable Incident Detection via Natural Language Processing and Probabilistic Language Models.

Post marketing safety surveillance depends in part on the ability to detect concerning clinical events at scale. Spontaneous reporting might be an effective component of safety surveillance, but it requires awareness and understanding among healthcare professionals to achieve its potential. Reliance on readily available structured data such as diagnostic codes risk under-coding and imprecision. Clinical textual data might bridge these gaps, and natural language processing (NLP) has been shown to aid in scalable phenotyping across healthcare records in multiple clinical domains. In this study, we developed and validated a novel incident phenotyping approach using unstructured clinical textual data agnostic to Electronic Health Record (EHR) and note type. It's based on a published, validated approach (PheRe) used to ascertain social determinants of health and suicidality across entire healthcare records. To demonstrate generalizability, we validated this approach on two separate phenotypes that share common challenges with respect to accurate ascertainment: 1) suicide attempt; 2) sleep-related behaviors. With samples of 89,428 records and 35,863 records for suicide attempt and sleep-related behaviors, respectively, we conducted silver standard (diagnostic coding) and gold standard (manual chart review) validation. We showed Area Under the Precision-Recall Curve of ∼ 0.77 (95% CI 0.75-0.78) for suicide attempt and AUPR ∼ 0.31 (95% CI 0.28-0.34) for sleep-related behaviors. We also evaluated performance by coded race and demonstrated differences in performance by race were dissimilar across phenotypes and require algorithmovigilance and debiasing prior to implementation.

Trends in Imaging Utilization Among United States Medicare Beneficiaries and the Impact of the COVID-19 Pandemic.

This study characterizes trends in ophthalmic imaging volume and utilization in the United States among and assesses the potential impact of the COVID-19 pandemic using data from the Centers for Medicare and Medicaid Services. Utilization of macular optical coherence tomography (OCT), optic nerve OCT, and fundus photography steadily increased from 2013 to 2020 and was not impacted by the COVID-19 pandemic. At the same time, there was minimal adoption of anterior segment OCT and a decline in the utilization of dye-based angiography. Utilization patterns may be impacted by the advent of new technologies, role of the clinician, and alignment with treatment paradigms. [Ophthalmic Surg Lasers Imaging Retina 2023;54:661-665.].

Surgical Stone Treatment: Patterns May Predict Performance on Episode-based Cost Measure in the Quality Payment Program.

INTRODUCTION: The Renal or Ureteral Stone Surgical Treatment Episode-based Measure in the Quality Payment Program evaluates clinicians' cost to Medicare for beneficiaries who receive surgical treatment for stones. The measure score is calculated from Medicare claims according to a complex methodology. This paper seeks to describe the stone treatment patterns of urologists and establish benchmarks for 2 surrogate measures-preoperative stenting and postoperative infection-which may predict clinician performance on the episode cost-based measure. METHODS: The study data were drawn from the adjudicated claims of 960 providers who performed at least 30 surgical stone treatments between January 1, 2020, and June 30, 2022. To allow for the correlation of procedures performed by the same providers, generalized estimating equations logistic regression models were used to evaluate the rate of preoperative stenting and postoperative infection. RESULTS: A total of 185,076 surgical episodes (113,799 [61.5%] ureteroscopy, 63,931 [34.5%] extracorporeal shock wave lithotripsy, and 7,346 [4.0%] percutaneous nephrolithotripsy) were identified over the study period. Preoperative stenting was performed in 35,550 episodes (19.2%) and postoperative infection was documented in 13,114 episodes (7.1%). Preoperative stenting and postoperative infection were significantly more common in patients who were female (adjusted OR 1.42, 1.38), in those undergoing ureteroscopy vs extracorporeal shock wave lithotripsy (adjusted OR 3.24, 1.66), and in patients on Medicare vs commercial insurance (adjusted OR 1.19, 1.17). CONCLUSIONS: This large study of surgical stone treatments documents rates of events and associated attributes of patients that may increase episode cost and be relevant to urologists participating in the Quality Payment Program.

Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics.

OBJECTIVE: High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach. METHODS: This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank. RESULTS: Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux. CONCLUSIONS: This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

Assessment of a Naloxone Coprescribing Alert for Patients at Risk of Opioid Overdose: A Quality Improvement Project.

BACKGROUND: Patients taking high doses of opioids, or taking opioids in combination with other central nervous system depressants, are at increased risk of opioid overdose. Coprescribing the opioid-reversal agent naloxone is an essential safety measure, recommended by the surgeon general, but the rate of naloxone coprescribing is low. Therefore, we set out to determine whether a targeted clinical decision support alert could increase the rate of naloxone coprescribing. METHODS: We conducted a before-after study from January 2019 to April 2021 at a large academic health system in the Southeast. We developed a targeted point of care decision support notification in the electronic health record to suggest ordering naloxone for patients who have a high risk of opioid overdose based on a high morphine equivalent daily dose (MEDD) ≥90 mg, concomitant benzodiazepine prescription, or a history of opioid use disorder or opioid overdose. We measured the rate of outpatient naloxone prescribing as our primary measure. A multivariable logistic regression model with robust variance to adjust for prescriptions within the same prescriber was implemented to estimate the association between alerts and naloxone coprescribing. RESULTS: The baseline naloxone coprescribing rate in 2019 was 0.28 (95% confidence interval [CI], 0.24-0.31) naloxone prescriptions per 100 opioid prescriptions. After alert implementation, the naloxone coprescribing rate increased to 4.51 (95% CI, 4.33-4.68) naloxone prescriptions per 100 opioid prescriptions (P < .001). The adjusted odds of naloxone coprescribing after alert implementation were approximately 28 times those during the baseline period (95% CI, 15-52). CONCLUSIONS: A targeted decision support alert for patients at risk for opioid overdose significantly increased the rate of naloxone coprescribing and was relatively easy to build.

Correlation Between Ophthalmology Market Saturation and Medicare Utilization Rates.

PURPOSE: To characterize usage of ophthalmologic services by Medicare Fee-For-Service (FFS) beneficiaries relative to geography-specific market saturation, demographics, and contextual factors DESIGN: Cross-sectional study METHODS: Data sets from Centers for Medicare & Medicaid Services, US Census Bureau, US Department of Agriculture, and Housing and Urban Development, were used to calculate county- and state-level ophthalmologic service usage, market saturation, and demographic characteristics. Negative binomial regression models were used to evaluate the association between results and demographic or population-specific variables. RESULTS: Ophthalmologic service usage ranged from 58.2% to 15.2%, whereas saturation ranged from 21,763 to 91.4 FFS beneficiaries per registered ophthalmologist. Usage was significantly associated with demographic characteristics in each geography: lower proportion of African American (P = .009), Hispanic (P < .001), and other race beneficiaries (P < .001), relative to white beneficiaries; a higher proportion of female (P < .001) relative to male; a higher proportion of adults having completed an associate degree or some college (P = .001), or holding a bachelor's degree or higher (P < .001), relative to a high school diploma; a lower proportion of adults in each geography experiencing poverty (P = .009), geographies with lower Multidimensional Deprivation Index (P < .001); a higher urban-influence code (P < .001). There was no significant correlation between the usage of ophthalmologic services and the geographic market saturation of ophthalmologists (Spearman rho, -0.030, P = .227). CONCLUSIONS AND RELEVANCE: Ophthalmologic service usage is significantly influenced by population demographics; however, increased provider density alone appears insufficient to promote the usage of eye care services.

Cost-aware active learning for named entity recognition in clinical text.

OBJECTIVE: Active Learning (AL) attempts to reduce annotation cost (ie, time) by selecting the most informative examples for annotation. Most approaches tacitly (and unrealistically) assume that the cost for annotating each sample is identical. This study introduces a cost-aware AL method, which simultaneously models both the annotation cost and the informativeness of the samples and evaluates both via simulation and user studies. MATERIALS AND METHODS: We designed a novel, cost-aware AL algorithm (Cost-CAUSE) for annotating clinical named entities; we first utilized lexical and syntactic features to estimate annotation cost, then we incorporated this cost measure into an existing AL algorithm. Using the 2010 i2b2/VA data set, we then conducted a simulation study comparing Cost-CAUSE with noncost-aware AL methods, and a user study comparing Cost-CAUSE with passive learning. RESULTS: Our cost model fit empirical annotation data well, and Cost-CAUSE increased the simulation area under the learning curve (ALC) scores by up to 5.6% and 4.9%, compared with random sampling and alternate AL methods. Moreover, in a user annotation task, Cost-CAUSE outperformed passive learning on the ALC score and reduced annotation time by 20.5%-30.2%. DISCUSSION: Although AL has proven effective in simulations, our user study shows that a real-world environment is far more complex. Other factors have a noticeable effect on the AL method, such as the annotation accuracy of users, the tiredness of users, and even the physical and mental condition of users. CONCLUSION: Cost-CAUSE saves significant annotation cost compared to random sampling.

An assessment of pharmacists' readiness for paperless labeling: a national survey.

OBJECTIVE: To assess the state of readiness for the adoption of paperless labeling among a nationally representative sample of pharmacies, including chain pharmacies, independent retail pharmacies, hospitals, and other rural or urban dispensing sites. METHODS: Both quantitative and qualitative analyses were used to analyze responses to a cross-sectional survey disseminated to American Pharmacists Association pharmacists nationwide. The survey assessed factors related to pharmacists' attitudinal readiness (ie, perceptions of impact) and pharmacies' structural readiness (eg, availability of electronic resources, internet access) for the paperless labeling initiative. RESULTS: We received a total of 436 survey responses (6% response rate) from pharmacists representing 44 US states and territories. Across the spectrum of settings we studied, pharmacists had work access to computers, printers, fax machines and access to the internet or intranet. Approximately 79% of respondents believed that the initiative would improve the adequacy of drug information available in their work site and 95% believed it would either not change (33%) or would improve (62%) communication to patients. Overall, respondents' comments supported advancing the initiative; however, some comments revealed reservations regarding corporate or pharmacy buy-in, success of implementation, and ease of adoption. CONCLUSIONS: This is the first nationwide study to report about pharmacists' perspectives on paperless labeling. In general, pharmacists believe they are ready and that their pharmacies are well equipped for the transition to paperless labeling. Further exploration of perspectives from product label manufacturers and corporate pharmacy offices is needed to understand fully what will be necessary to complete this transition.

Bayesian modeling and inference for clinical trials with partial retrieved data following dropout.

In randomized clinical trials, it is common that patients may stop taking their assigned treatments and then switch to a standard treatment (standard of care available to the patient) but not the treatments under investigation. Although the availability of limited retrieved data on patients who switch to standard treatment, called off-protocol data, could be highly valuable in assessing the associated treatment effect with the experimental therapy, it leads to a complex data structure requiring the development of models that link the information of per-protocol data with the off-protocol data. In this paper, we develop a novel Bayesian method to jointly model longitudinal treatment measurements under various dropout scenarios. Specifically, we propose a multivariate normal mixed-effects model for repeated measurements from the assigned treatments and the standard treatment, a multivariate logistic regression model for those stopping the assigned treatments, logistic regression models for those starting a standard treatment off protocol, and a conditional multivariate logistic regression model for completely withdrawing from the study. We assume that withdrawing from the study is non-ignorable, but intermittent missingness is assumed to be at random. We examine various properties of the proposed model. We develop an efficient Markov chain Monte Carlo sampling algorithm. We analyze in detail via the proposed method a real dataset from a clinical trial.

The financial impact of health information exchange on emergency department care.

OBJECTIVE: To examine the financial impact health information exchange (HIE) in emergency departments (EDs). MATERIALS AND METHODS: We studied all ED encounters over a 13-month period in which HIE data were accessed in all major emergency departments Memphis, Tennessee. HIE access encounter records were matched with similar encounter records without HIE access. Outcomes studied were ED-originated hospital admissions, admissions for observation, laboratory testing, head CT, body CT, ankle radiographs, chest radiographs, and echocardiograms. Our estimates employed generalized estimating equations for logistic regression models adjusted for admission type, length of stay, and Charlson co-morbidity index. Marginal probabilities were used to calculate changes in outcome variables and their financial consequences. RESULTS: HIE data were accessed in approximately 6.8% of ED visits across 12 EDs studied. In 11 EDs directly accessing HIE data only through a secure Web browser, access was associated with a decrease in hospital admissions (adjusted odds ratio (OR)=0.27; p<0001). In a 12th ED relying more on print summaries, HIE access was associated with a decrease in hospital admissions (OR=0.48; p<0001) and statistically significant decreases in head CT use, body CT use, and laboratory test ordering. DISCUSSION: Applied only to the study population, HIE access was associated with an annual cost savings of $1.9 million. Net of annual operating costs, HIE access reduced overall costs by $1.07 million. Hospital admission reductions accounted for 97.6% of total cost reductions. CONCLUSION: Access to additional clinical data through HIE in emergency department settings is associated with net societal saving.

Assessment of parental acceptance of a potential cytomegalovirus vaccine for adolescent females.

The development of a vaccine against cytomegalovirus (CMV) has been designated as a high priority and adolescent females are a likely target population for CMV vaccination. A self-administered, internet-based survey was developed using constructs from the Health Belief Model to identify factors that may be associated with parental acceptance of a CMV vaccine for their adolescent daughters. Data from 516 parents were analyzed, the majority of whom were female, white, and college educated. Parental acceptance of a CMV vaccine was generally high. Perceived benefits of vaccine were independently associated with vaccine acceptance while history of previous vaccine refusal, concerns about safety and cost of the vaccine were negatively associated. These findings provide initial data on factors that are likely to influence parental acceptance of a CMV vaccine for adolescent girls.

Burden of respiratory syncytial virus in hospitalized infants and young children in Amman, Jordan.

Acute respiratory infections (ARI) play a major role in hospitalizations in the Middle East, but the specific viral causes are unknown. We conducted prospective viral surveillance in children <5 y of age admitted with ARI and/or fever at 2 dissimilar hospitals in Amman, Jordan during peak respiratory syncytial virus (RSV) season. We collected prospective clinical and demographic data and obtained nose/throat swabs for testing for RSV by real-time polymerase chain reaction (RT-PCR). We obtained clinical and laboratory data for 728/743 (98%) subjects enrolled. The children's median age was 4.3 months, 58.4% were males, 87% were breastfed, 4% attended day care, 67% were exposed to smokers, 7% were admitted to the intensive care unit, and 0.7% died (n = 5). Out of 728 subjects, 467 (64%) tested positive by RT-PCR for RSV. Comparing RSV-positive with RSV-negative subjects, the RSV-positive subjects had lower median age (3.6 vs 6.4 months, p < 0.001) and fewer males (55% vs 64%, p = 0.02). RSV-positive children had higher rates of oxygen use (72% vs 42%, p < 0.001), a longer hospital stay (5 vs 4 days, p = 0.001), and higher hospital charges (US$538 vs US$431, p < 0.001) than RSV-negative children. In young hospitalized Jordanian infants, the medical and financial burden of RSV was found to be high. Effective preventive measures, such as an RSV vaccine, would have a significant beneficial impact.

Performing without a net: transitioning away from a health information technology-rich training environment.

PURPOSE: In many academic medical centers (AMCs), health information technology (HIT) has become a foundational component of patient care. Medical training in these environments generates dependence on HIT. The authors conducted this study to determine how transitioning from an HIT-rich environment affects practitioners' self-perceptions of competence, practice efficiency, and patient safety. METHOD: In 2004 and 2005, the authors performed a cross-sectional survey study involving medical students and residents who had graduated from Vanderbilt University Medical Center (VUMC), an HIT-rich AMC. The authors distributed surveys to 679 graduates from 2001 to 2003 who transferred to other institutions. RESULTS: Although 128 surveys were returned undelivered because of wrong addresses, 328 (60%) were returned complete and analyzed. Among respondents, 255 (78%) reported transitioning to environments with less HIT than VUMC. The authors compared responses from this group with those of peers who transitioned to environments with the same or greater HIT penetration. After controlling for confounding effects, the authors found that graduates who transitioned to lower-HIT institutions reported feeling less able to practice safe patient care (P = .02), to utilize evidence at the point of care (P = .05), to work efficiently (P < .001), to share and communicate information (P = .03), and to work effectively within the local system (P = .007). CONCLUSIONS: Providers who transition away from HIT-rich environments may perceive their care as less safe and less efficient. These results support greater adoption of HIT and underscore the need for formal education for new trainees, faculty, and staff transitioning to a new system of care.

Providers' beliefs, attitudes, and behaviors before implementing a computerized pneumococcal vaccination reminder.

BACKGROUND: The emergency department (ED) has been recommended as a suitable setting for offering pneumococcal vaccination; however, implementations of ED vaccination programs remain scarce. OBJECTIVES: To understand beliefs, attitudes, and behaviors of ED providers before implementing a computerized reminder system. METHODS: An anonymous, five-point Likert-scale, 46-item survey was administered to emergency physicians and nurses at an academic medical center. The survey included aspects of ordering patterns, implementation strategies, barriers, and factors considered important for an ED-based vaccination initiative as well as aspects of implementing a computerized vaccine-reminder system. RESULTS: Among 160 eligible ED providers, the survey was returned by 64 of 67 physicians (96%), and all 93 nurses (100%). The vaccine was considered to be cost effective by 71% of physicians, but only 2% recommended it to their patients. Although 98% of physicians accessed the computerized problem list before examining the patient, only 28% reviewed the patient's health-maintenance section. Physicians and nurses preferred a computerized vaccination-reminder system in 93% and 82%, respectively. Physicians' preferred implementation approach included a nurse standing order, combined with physician notification; nurses, however, favored a physician order. Factors for improving vaccination rates included improved computerized documentation, whereas increasing the number of ED staff was less important. Relevant implementation barriers for physicians were not remembering to offer vaccination, time constraints, and insufficient time to counsel patients. The ED was believed to be an appropriate setting in which to offer vaccination. CONCLUSIONS: Emergency department staff had favorable attitudes toward an ED-based pneumococcal vaccination program; however, considerable barriers inherent to the ED setting may challenge such a program. Applying information technology may overcome some barriers and facilitate an ED-based vaccination initiative.