Assessing the Effect of Electronic Health Record Data Quality on Identifying Patients with Type 2 Diabetes

BACKGROUND

Increasing and substantial reliance on Electronic health records (EHR) and data types (i.e., diagnosis (Dx), medication (Rx), laboratory (Lx)) demands assessment of its data quality (DQ) as a fundamental approach; especially since there is need to identify appropriate denominator population with chronic conditions, such as Type-2 Diabetes (T2D), using commonly available computable phenotype definitions (phenotype).

OBJECTIVE

To bridge this gap, our study aims to assess how issues of EHR DQ, and variations and robustness (or lack thereof) in phenotypes may have potential impact in identifying denominator population.

METHODS

Approximately 208k patients with T2D were included in our study using retrospective EHR data of Johns Hopkins Medical Institution (JHMI) during 2017-2019. Our assessment included 4 published phenotypes, and 1 definition from a panel of experts at Hopkins. We conducted descriptive analyses of demographics (i.e., age, sex, race, ethnicity), healthcare utilization (inpatient and emergency room visits), and average Charlson Comorbidity score of each phenotype. We then used different methods to induce/simulate DQ issues of completeness, accuracy and timeliness separately across each phenotype. For induced data incompleteness, our model randomly dropped Dx, Rx, and Lx codes independently at increments of 10%; for induced data inaccuracy, our model randomly replaced a Dx or Rx code with another code of the same data type and induced 2% incremental change from -100% to +10% in Lx result values; and lastly, for timeliness, data was modeled for induced incremental shift of date records by 30 days up to a year.

RESULTS

Less than a quarter (23%) of population overlapped across all phenotypes using EHR. The population identified by each phenotype varied across all combination of data types. Induced incompleteness identified fewer patients with each increment, for e.g., at 100% diagnostic incompleteness, Chronic Conditions Data Warehouse (CCW) phenotype identified zero patients as its phenotypic characteristics included only Dx codes. Induced inaccuracy and timeliness similarly demonstrated variations in performance of each phenotype and therefore, resulting in fewer patients being identified with each incremental change.

CONCLUSIONS

We utilized EHR data with Dx, Rx, and Lx data types from a large tertiary hospital system to understand the T2D phenotypic differences and performance. We learned how issues of DQ, using induced DQ methods, may impact identification of the denominator populations upon which clinical (e.g., clinical research and trials, population health evaluations) and financial/operational decisions are made. The novel results from our study may inform in shaping a common T2D computable phenotype definition that can be applicable to clinical informatics, managing chronic conditions, and additional healthcare industry-wide efforts.

CLINICALTRIAL

Computable phenotype for diagnostic error: developing the data schema for application of symptom-disease pair analysis of diagnostic error (SPADE)

OBJECTIVES

Diagnostic errors are the leading cause of preventable harm in clinical practice. Implementable tools to quantify and target this problem are needed. To address this gap, we aimed to generalize the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework by developing its computable phenotype and then demonstrated how that schema could be applied in multiple clinical contexts.

METHODS

We created an information model for the SPADE processes, then mapped data fields from electronic health records (EHR) and claims data in use to that model to create the SPADE information model (intention) and the SPADE computable phenotype (extension). Later we validated the computable phenotype and tested it in four case studies in three different health systems to demonstrate its utility.

RESULTS

We mapped and tested the SPADE computable phenotype in three different sites using four different case studies. We showed that data fields to compute an SPADE base measure are fully available in the EHR Data Warehouse for extraction and can operationalize the SPADE framework from provider and/or insurer perspective, and they could be implemented on numerous health systems for future work in monitor misdiagnosis-related harms.

CONCLUSIONS

Data for the SPADE base measure is readily available in EHR and administrative claims. The method of data extraction is potentially universally applicable, and the data extracted is conveniently available within a network system. Further study is needed to validate the computable phenotype across different settings with different data infrastructures.

Racial Disparities in Diabetes Care and Outcomes for Patients with Visual Impairment: A Descriptive Analysis of the TriNetX Research Network

Background: This research delves into the confluence of racial disparities and health inequities among individuals with disabilities, with a focus on those contending with both diabetes and visual impairment. Methods: Utilizing data from the TriNetX Research Network, which includes electronic medical records of roughly 115 million patients from 83 anonymous healthcare organizations, this study employs a directed acyclic graph (DAG) to pinpoint confounders and augment interpretation. We identified patients with visual impairments using ICD-10 codes, deliberately excluding diabetes-related ophthalmology complications. Our approach involved multiple race-stratified analyses, comparing co-morbidities like chronic pulmonary disease in visually impaired patients against their counterparts. We assessed healthcare access disparities by examining the frequency of annual visits, instances of two or more A1c measurements, and glomerular filtration rate (GFR) measurements. Additionally, we evaluated diabetes outcomes by comparing the risk ratio of uncontrolled diabetes (A1c > 9.0) and chronic kidney disease in patients with and without visual impairments. Results: The incidence of diabetes was substantially higher (nearly double) in individuals with visual impairments across White, Asian, and African American populations. Higher rates of chronic kidney disease were observed in visually impaired individuals, with a risk ratio of 1.79 for African American, 2.27 for White, and non-significant for the Asian group. A statistically significant difference in the risk ratio for uncontrolled diabetes was found only in the White cohort (0.843). White individuals without visual impairments were more likely to receive two A1c tests, a trend not significant in other racial groups. African Americans with visual impairments had a higher rate of glomerular filtration rate testing. However, White individuals with visual impairments were less likely to undergo GFR testing, indicating a disparity in kidney health monitoring. This pattern of disparity was not observed in the Asian cohort. Conclusions: This study uncovers pronounced disparities in diabetes incidence and management among individuals with visual impairments, particularly among White, Asian, and African American groups. Our DAG analysis illuminates the intricate interplay between SDoH, healthcare access, and frequency of crucial diabetes monitoring practices, highlighting visual impairment as both a medical and social issue.

Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study

BACKGROUND

The use of large-scale data and artificial intelligence (AI) to support complex transplantation decisions is in its infancy. Transplant candidate decision-making, which relies heavily on subjective assessment (ie, high variability), provides a ripe opportunity for AI-based clinical decision support (CDS). However, AI-CDS for transplant applications must consider important concerns regarding fairness (ie, health equity). The objective of this study was to use human-centered design methods to elicit providers' perceptions of AI-CDS for liver transplant listing decisions.

METHODS

In this multicenter qualitative study conducted from December 2020 to July 2021, we performed semistructured interviews with 53 multidisciplinary liver transplant providers from 2 transplant centers. We used inductive coding and constant comparison analysis of interview data.

RESULTS

Analysis yielded 6 themes important for the design of fair AI-CDS for liver transplant listing decisions: (1) transparency in the creators behind the AI-CDS and their motivations; (2) understanding how the AI-CDS uses data to support recommendations (ie, interpretability); (3) acknowledgment that AI-CDS could mitigate emotions and biases; (4) AI-CDS as a member of the transplant team, not a replacement; (5) identifying patient resource needs; and (6) including the patient's role in the AI-CDS.

CONCLUSIONS

Overall, providers interviewed were cautiously optimistic about the potential for AI-CDS to improve clinical and equitable outcomes for patients. These findings can guide multidisciplinary developers in the design and implementation of AI-CDS that deliberately considers health equity.

Enhancing the nation's public health information infrastructure: a report from the ACMI symposium

The COVID-19 pandemic exposed multiple weaknesses in the nation's public health system. Therefore, the American College of Medical Informatics selected "Rebuilding the Nation's Public Health Informatics Infrastructure" as the theme for its annual symposium. Experts in biomedical informatics and public health discussed strategies to strengthen the US public health information infrastructure through policy, education, research, and development. This article summarizes policy recommendations for the biomedical informatics community postpandemic. First, the nation must perceive the health data infrastructure to be a matter of national security. The nation must further invest significantly more in its health data infrastructure. Investments should include the education and training of the public health workforce as informaticians in this domain are currently limited. Finally, investments should strengthen and expand health data utilities that increasingly play a critical role in exchanging information across public health and healthcare organizations.

Trends and opportunities in computable clinical phenotyping: A scoping review

Identifying patient cohorts meeting the criteria of specific phenotypes is essential in biomedicine and particularly timely in precision medicine. Many research groups deliver pipelines that automatically retrieve and analyze data elements from one or more sources to automate this task and deliver high-performing computable phenotypes. We applied a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to conduct a thorough scoping review on computable clinical phenotyping. Five databases were searched using a query that combined the concepts of automation, clinical context, and phenotyping. Subsequently, four reviewers screened 7960 records (after removing over 4000 duplicates) and selected 139 that satisfied the inclusion criteria. This dataset was analyzed to extract information on target use cases, data-related topics, phenotyping methodologies, evaluation strategies, and portability of developed solutions. Most studies supported patient cohort selection without discussing the application to specific use cases, such as precision medicine. Electronic Health Records were the primary source in 87.1 % (N = 121) of all studies, and International Classification of Diseases codes were heavily used in 55.4 % (N = 77) of all studies, however, only 25.9 % (N = 36) of the records described compliance with a common data model. In terms of the presented methods, traditional Machine Learning (ML) was the dominant method, often combined with natural language processing and other approaches, while external validation and portability of computable phenotypes were pursued in many cases. These findings revealed that defining target use cases precisely, moving away from sole ML strategies, and evaluating the proposed solutions in the real setting are essential opportunities for future work. There is also momentum and an emerging need for computable phenotyping to support clinical and epidemiological research and precision medicine.

Abstract P401: Circadian Dietary Patterns and Weight Trajectories in Adults Using the Daily24 Mobile Application

Introduction: It is unclear whether the timing of meals relative to sleep impacts cardiometabolic risk factors (e.g., weight gain). This cohort study aimed to detect and describe the association of the timing of caloric intake and dietary patterns (e.g., skipping breakfast) with weight trajectory over 2 years among participants who used the Daily24 mobile application to record their timing of eating and sleeping.

Hypothesis: We hypothesized that skipping breakfast or consuming 50% or more of daily calories in the latter half of the day is associated with greater weight gain over 2 years.

Methods: We conducted a secondary data analysis from a multi-site, electronic health record-based cohort study of adults from 3 healthcare systems in PCORnet’s PaTH Clinical Research Network. Of the 1017 participants enrolled in the study, N=407 patients downloaded and used the Daily24 mobile application for at least 2 weekdays and 1 weekend day over 6 months. We calculated the median of each participant’s daily eating and sleeping intervals. Participants’ weights were extracted from electronic health records available for up to 10 years prior to until 10 months after baseline. Weight trajectories were calculated over 2 years of this data. Participants completed online surveys about demographics and behavioral characteristics at baseline and after 4 months. We constructed multivariate linear regression models with weight trajectory as the dependent variable and breakfast skipping (i.e., not eating anything within 3 hours of waking), having a medium or large meal within 3 hours of sleep, ≥50% caloric consumption in the latter half of the day (after 12 pm), and ≥90% caloric consumption after 7 pm as independent variables. Additional independent variables included age, sex, race, days of application use, and body mass index (BMI) category.

Results: Mean (SD) baseline age was 50.8 (15.0) years, 75.7% had a BMI≥25 kg/m 2 , 78.1% were women, and 84.0% were white. The average number of recorded Daily24 application days was 55.9 (53.5), significantly greater than the 3-day minimum inclusion criterion. The mean of participants’ median intervals from first to last meal was 11.2 (2.0) hours. Although not statistically significant, consuming 50% of daily calories in the latter half of the day and skipping breakfast were associated with an increasing weight trajectory (0.03 and 0.25 kg/year; 95% CI -0.39 to 0.45 and -0.32 to 0.82, respectively).

Conclusions: Timing of eating (e.g., skipping breakfast or eating most calories later in the day) may be associated with very small weight increases over time. Our app-based approach may not have had enough observations to establish this association. Further research is needed to understand the clinical importance of circadian dietary patterns related to cardiometabolic health.

Development of a Digital Assistant to Support Teleconsultations Between Remote Physicians and Frontline Health Workers in India: User-Centered Design Approach

BACKGROUND

Many low- and middle-income countries have adopted telemedicine programs that connect frontline health workers (FHWs) such as nurses, midwives, or community health workers in rural and remote areas with physicians in urban areas to deliver care to patients. By leveraging technology to reduce temporal, financial, and geographical barriers, these health worker-to-physician telemedicine programs have the potential to increase health care quality, expand the specialties available to patients, and reduce the time and cost required to deliver care.

OBJECTIVE

We aimed to identify, validate, and prioritize unmet needs in the health care space of health worker-to-physician telemedicine programs and develop and refine a solution that addresses those needs.

METHODS

We collected information regarding user needs through ethnographic research, direct observation, and semistructured interviews with 37 stakeholders (n=5, 14% physicians; n=1, 3% public health program manager; n=12, 32% community health workers; and n=19, 51% patients) at 2 telemedicine clinics in rural West Bengal, India. We used the Spiral-Iterative Innovation Model to design and develop a prototype solution to meet these needs.

RESULTS

We identified 74 unmet needs through our immersion in health worker-to-physician telemedicine programs. We identified a critical unmet need that achieving optimal teleconsultations in low- and middle-income countries often requires shifting tasks such as history taking and physical examination from high-skilled remote physicians to FHWs. To meet this need, we developed a prototype digital assistant that would allow FHWs to assume some of the tasks carried out by remote clinicians. The user needs of multiple stakeholder groups (patients, FHWs, physicians, and health organizations) were incorporated into the design and features of the task-shifting tool. The final prototype was shared with the health workers, physicians, and public health program managers who expressed that the tool would be useful and valuable.

CONCLUSIONS

The final prototype that was developed was released as an open-source digital public good and may improve the quality and efficiency of care delivery in health worker-to-physician telemedicine programs.

Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort

Background We aim to evaluate the association between meal intervals and weight trajectory among adults from a clinical cohort. Methods and Results This is a multisite prospective cohort study of adults recruited from 3 health systems. Over the 6-month study period, 547 participants downloaded and used a mobile application to record the timing of meals and sleep for at least 1 day. We obtained information on weight and comorbidities at each outpatient visit from electronic health records for up to 10  years before until 10 months after baseline. We used mixed linear regression to model weight trajectories. Mean age was 51.1 (SD 15.0) years, and body mass index was 30.8 (SD 7.8) kg/m²; 77.9% were women, and 77.5% reported White race. Mean interval from first to last meal was 11.5 (2.3) hours and was not associated with weight change. The number of meals per day was positively associated with weight change. The average difference in annual weight change (95% CI) associated with an increase of 1 daily meal was 0.28 kg (0.02-0.53). Conclusions Number of daily meals was positively associated with weight change over 6 years. Our findings did not support the use of time-restricted eating as a strategy for long-term weight loss in a general medical population.

A scoping review of knowledge authoring tools used for developing computerized clinical decision support systems

Objective

Clinical Knowledge Authoring Tools (CKATs) are integral to the computerized Clinical Decision Support (CDS) development life cycle. CKATs enable authors to generate accurate, complete, and reliable digital knowledge artifacts in a relatively efficient and affordable manner. This scoping review aims to compare knowledge authoring tools and derive the common features of CKATs.

Materials and Methods

We performed a keyword-based literature search, followed by a snowball search, to identify peer-reviewed publications describing the development or use of CKATs. We used PubMed and Embase search engines to perform the initial search (n = 1579). After removing duplicate articles, nonrelevant manuscripts, and not peer-reviewed publication, we identified 47 eligible studies describing 33 unique CKATs. The reviewed CKATs were further assessed, and salient characteristics were extracted and grouped as common CKAT features.

Results

Among the identified CKATs, 55% use an open source platform, 70% provide an application programming interface for CDS system integration, and 79% provide features to validate/test the knowledge. The majority of the reviewed CKATs describe the flow of information, offer a graphical user interface for knowledge authors, and provide intellisense coding features (94%, 97%, and 97%, respectively). The composed list of criteria for CKAT included topics such as simulating the clinical setting, validating the knowledge, standardized clinical models and vocabulary, and domain independence. None of the reviewed CKATs met all common criteria.

Conclusion

Our scoping review highlights the key specifications for a CKAT. The CKAT specification proposed in this review can guide CDS authors in developing more targeted CKATs.

Development of a Mobile App for Ecological Momentary Assessment of Circadian Data: Design Considerations and Usability Testing

BACKGROUND

Collecting data on daily habits across a population of individuals is challenging. Mobile-based circadian ecological momentary assessment (cEMA) is a powerful frame for observing the impact of daily living on long-term health.

OBJECTIVE

In this paper, we (1) describe the design, testing, and rationale for specifications of a mobile-based cEMA app to collect timing of eating and sleeping data and (2) compare cEMA and survey data collected as part of a 6-month observational cohort study. The ultimate goal of this paper is to summarize our experience and lessons learned with the Daily24 mobile app and to highlight the pros and cons of this data collection modality.

METHODS

Design specifications for the Daily24 app were drafted by the study team based on the research questions and target audience for the cohort study. The associated backend was optimized to provide real-time data to the study team for participant monitoring and engagement. An external 8-member advisory board was consulted throughout the development process, and additional test users recruited as part of a qualitative study provided feedback through in-depth interviews.

RESULTS

After ≥4 days of at-home use, 37 qualitative study participants provided feedback on the app. The app generally received positive feedback from test users for being fast and easy to use. Test users identified several bugs and areas where modifications were necessary to in-app text and instructions and also provided feedback on the engagement strategy. Data collected through the mobile app captured more variability in eating windows than data collected through a one-time survey, though at a significant cost.

CONCLUSIONS

Researchers should consider the potential uses of a mobile app beyond the initial data collection when deciding whether the time and monetary expenditure are advisable for their situation and goals.

Patient Recruitment Into a Multicenter Clinical Cohort Linking Electronic Health Records From 5 Health Systems: Cross-sectional Analysis

Background

There is growing interest in identifying and recruiting research participants from health systems using electronic health records (EHRs). However, few studies have described the practical aspects of the recruitment process or compared electronic recruitment methods to in-person recruitment, particularly across health systems.

Objective

The objective of this study was to describe the steps and efficiency of the recruitment process and participant characteristics by recruitment strategy.

Methods

EHR-based eligibility criteria included being an adult patient engaged in outpatient primary or bariatric surgery care at one of 5 health systems in the PaTH Clinical Research Network and having ≥2 weight measurements and 1 height measurement recorded in their EHR within the last 5 years. Recruitment strategies varied by site and included one or more of the following methods: (1) in-person recruitment by study staff from clinical sites, (2) US postal mail recruitment letters, (3) secure email, and (4) direct EHR recruitment through secure patient web portals. We used descriptive statistics to evaluate participant characteristics and proportion of patients recruited (ie, efficiency) by modality.

Results

The total number of eligible patients from the 5 health systems was 5,051,187. Of these, 40,048 (0.8%) were invited to enter an EHR-based cohort study and 1085 were enrolled. Recruitment efficiency was highest for in-person recruitment (33.5%), followed by electronic messaging (2.9%), including email (2.9%) and EHR patient portal messages (2.9%). Overall, 779 (65.7%) patients were enrolled through electronic messaging, which also showed greater rates of recruitment of Black patients compared with the other strategies.

Conclusions

We recruited a total of 1085 patients from primary care and bariatric surgery settings using 4 recruitment strategies. The recruitment efficiency was 2.9% for email and EHR patient portals, with the majority of participants recruited electronically. This study can inform the design of future research studies using EHR-based recruitment.

Abstract 017: Meal Intervals And Weight Trajectories In Adults Using The Daily24 Mobile Application: A Prospective Cohort Study

Background: Small pilot and randomized controlled studies suggest that time-restricted feeding may decrease body weight. However, the role of meal timing and intervals, measured using mobile applications, has not been examined in larger population-based studies. The objective of this study is to evaluate the association between meal intervals and weight trajectories among adults from a population-based clinical cohort.

Methods: Multi-site prospective cohort study of adults recruited from three health systems. Over the 6-month study period, 547 participants downloaded and used the Daily24 mobile application to record the timing of meals and sleep for at least one day. Intervals were calculated as the average of all available daily entries for each participant. We obtained information on weight and comorbidities at each outpatient visit from electronic health records available for up to 10 years prior to until 10 months after baseline. We used mixed linear regression to model weight trajectories.

Results: The mean (SD) baseline (at consent) age was 51.1 (15.0) years and body mass index (BMI) 30.8 (7.8) kg/m 2 ; 77.9% were women and 77.5% were White. Average time in the cohort was 5.9 years prior to and 0.3 years after baseline. The mean interval from first to last meal was 11.5 (2.3) hours. The associations between meal intervals and weight trajectories are shown in the Table . The number of meals per day was positively associated with weight change before baseline, and number of snacks and drinks per day was inversely associated with weight change after baseline. Each additional occasion of snacks and drinks was associated with a 3.20 kg weight decrease (95% CI 1.41 to 4.99). None of the other associations were statistically significant.

Conclusions: Number of daily meals was positively associated with weight change in previous periods, while the number of daily snacks and drinks was inversely associated with weight trajectory. The intervals from first to last meal was not associated with weight change.

Preferences for Updates on General Research Results: A Survey of Participants in Genomic Research from Two Institutions

There is a need for multimodal strategies to keep research participants informed about study results. Our aim was to characterize preferences of genomic research participants from two institutions along four dimensions of general research result updates: content, timing, mechanism, and frequency.

METHODS

We conducted a web-based cross-sectional survey that was administered from 25 June 2018 to 5 December 2018.

RESULTS

397 participants completed the survey, most of whom (96%) expressed a desire to receive research updates. Preferences with high endorsement included: update content (brief descriptions of major findings, descriptions of purpose and goals, and educational material); update timing (when the research is completed, when findings are reviewed, when findings are published, and when the study status changes); update mechanism (email with updates, and email newsletter); and update frequency (every three months). Hierarchical cluster analyses based on the four update preferences identified four profiles of participants with similar preference patterns. Very few participants in the largest profile were comfortable with budgeting less money for research activities so that researchers have money to set up services to send research result updates to study participants.

CONCLUSION

Future studies may benefit from exploring preferences for research result updates, as we have in our study. In addition, this work provides evidence of a need for funders to incentivize researchers to communicate results to participants.

Scalable Production of Equine Platelet Lysate for Multipotent Mesenchymal Stromal Cell Culture

Translation of multipotent mesenchymal stromal cell (MSC)-based therapies is advancing in human and veterinary medicine. One critical issue is the in vitro culture of MSC before clinical use. Using fetal bovine serum (FBS) as supplement to the basal medium is still the gold standard for cultivation of many cell types including equine MSC. Alternatives are being explored, with substantial success using platelet lysate-supplemented media for human MSC. However, progress lags behind in the veterinary field. The aim of this study was to establish a scalable protocol for equine platelet lysate (ePL) production and to test the ePL in equine MSC culture. Whole blood was harvested into blood collection bags from 20 healthy horses. After checking sample materials for pathogen contamination, samples from 19 animals were included. Platelet concentrates were prepared using a buffy coat method. Platelets, platelet-derived growth factor BB, and transforming growth factor β1 concentrations were increased in the concentrates compared with whole blood or serum (p < 0.05), while white blood cells were reduced (p < 0.05). The concentrates were lysed using freeze/thaw cycles, which eliminated the cells while growth factor concentrations were maintained. Donor age negatively correlated with platelet and growth factor concentrations after processing (p < 0.05). Finally, all lysates were pooled and the ePL was evaluated as culture medium supplement in comparison with FBS, using adipose-derived MSC from four unrelated donor horses. MSC proliferated well in 10% FBS as well as in 10% ePL. However, using 5 or 2.5% ePL entailed highly inconsistent proliferation or loss of proliferation, with significant differences in generation times and confluencies (p < 0.05). MSC expressed the surface antigens CD90, CD44, and CD29, but CD73 and CD105 detection was low in all culture media. Adipogenic and osteogenic differentiation led to similar results in MSC from different culture media. The buffy coat method is useful to produce equine platelet concentrate with increased platelet and reduced white blood cell content in large scales. The ePL obtained supports MSC expansion similar as FBS when used at the same concentration (10%). Further investigations into equine MSC functionality in culture with ePL should follow.

A method for measuring the effect of certified electronic health record technology on childhood immunization status scores among Medicaid managed care network providers

OBJECTIVE

To provide a methodology for estimating the effect of U.S.-based Certified Electronic Health Records Technology (CEHRT) implemented by primary care physicians (PCPs) on a Healthcare Effectiveness Data and Information Set (HEDIS) measure for childhood immunization delivery.

MATERIALS AND METHODS

This study integrates multiple health care administrative data sources from 2010 through 2014, analyzed through an interrupted time series design and a hierarchical Bayesian model. We compared managed care physicians using CEHRT to propensity-score matched comparisons from network physicians who did not adopt CEHRT. Inclusion criteria for physicians using CEHRT included attesting to the Childhood Immunization Status clinical quality measure in addition to meeting "Meaningful Use" (MU) during calendar year 2013. We used a first-presence patient attribution approach to develop provider-specific immunization scores.

RESULTS

We evaluated 147 providers using CEHRT, with 147 propensity-score matched providers selected from a pool of 1253 PCPs practicing in Maryland. The estimate for change in odds of increasing immunization rates due to CEHRT was 1.2 (95% credible set, 0.88-1.73).

DISCUSSION

We created a method for estimating immunization quality scores using Bayesian modeling. Our approach required linking separate administrative data sets, constructing a propensity-score matched cohort, and using first-presence, claims-based childhood visit information for patient attribution. In the absence of integrated data sets and precise and accurate patient attribution, this is a reusable method for researchers and health system administrators to estimate the impact of health information technology on individual, provider-level, process-based, though outcomes-focused, quality measures.

CONCLUSION

This research has provided evidence for using Bayesian analysis of propensity-score matched provider populations to estimate the impact of CEHRT on outcomes-based quality measures such as childhood immunization delivery.

What influences the "when" of eating and sleeping?A qualitative interview study

Timing of eating relative to sleep and endogenous circadian rhythm impacts weight and cardiometabolic health. We used qualitative methods to explore what influences the "when" of eating and sleeping. We conducted 37 one-on-one semi-structured interviews among participants with a body mass index (BMI) ≥ 25 kg/m² recruited from three internal medicine clinics affiliated with an urban academic hospital. Participants (70.3% Female; 51.4% White; Age range: 21-83 years old) completed measures of social jetlag, physical activity, eating habits, and mobile application use and participated in interviews following a guide developed by the study team. Responses were recorded, transcribed and coded sequentially by two trained researchers using editing-style analysis to identify themes. We identified two main themes, each with subthemes: 1) influences on the "when" of eating and sleeping, with subthemes including social jetlag and being overscheduled, and 2) contextualizing beliefs and perceptions about the "when" of eating and sleeping, with subthemes including perceived recommendations for timing of eating and sleeping, and alignment of behaviors with perceived recommendations. Many participants noted being more flexible in their eating and sleeping times on work-free vs work days. The themes this study identified should be considered when designing interventions that influence the timing of eating and sleeping for weight management.

Are maternal hemodynamic indices markers of fetal growth restriction in pregnancies with a small-for-gestational-age fetus?

OBJECTIVE

Pregnancies complicated by fetal growth restriction (FGR) have a worse outcome than those with a small-for-gestational-age (SGA) fetus. There is increasing evidence of a maternal cardiovascular role in the pathophysiology of FGR. We aimed to compare maternal hemodynamic indices between pregnancies complicated by FGR and those delivering a SGA neonate, using a non-invasive device.

METHODS

This was a prospective study of normotensive pregnancies complicated by FGR (defined as estimated fetal weight (EFW) < 3^rd centile or Doppler evidence of impaired placental-fetal blood flow), those with a SGA fetus (defined as EFW < 10^th centile) and control pregnancies with an appropriately grown fetus. Assessment of maternal hemodynamics (heart rate (HR), cardiac output (CO), mean arterial pressure (MAP), systemic vascular resistance (SVR) and stroke volume) was performed using a non-invasive device (USCOM-1A®). Uterine artery (UtA) pulsatility index (PI) was measured using transabdominal ultrasound. Hemodynamic variables that are affected by gestational age and maternal characteristics were corrected for using device-specific reference ranges. Comparison between groups was performed using the chi-square test or the Mann-Whitney U-test, as appropriate.

RESULTS

A total of 102 FGR, 64 SGA and 401 control pregnancies, with a median gestational age of 36 weeks, were included in the analysis. Women with a pregnancy complicated by FGR and those with a SGA fetus were shorter and weighed less than did controls. Compared with controls, the FGR group had significantly lower median maternal HR (80 beats per min (bpm) vs 85 bpm; P = 0.001) and CO multiples of the median (MoM; 0.91 vs 0.98; P = 0.003), and higher median maternal MAP (90 mmHg vs 87 mmHg; P = 0.040), SVR MoM (1.2 vs 1.0; P < 0.001) and UtA-PI MoM (1.1 vs 0.96; P < 0.001), but there was no significant difference in stroke volume MoM (1.0 vs 0.98; P = 0.647). Compared with the SGA group, the FGR group had a significantly lower median HR (80 bpm vs 87 bpm; P = 0.022), and higher median maternal MAP (90 mmHg vs 85 mmHg; P = 0.025), SVR MoM (1.2 vs 1.0; P = 0.002) and UtA-PI MoM (1.1 vs 0.98; P = 0.005), but there was no significant difference in CO MoM (0.91 vs 0.96; P = 0.092) or stroke volume MoM (1.0 vs 1.0; P = 0.806). There were no significant differences in adjusted maternal hemodynamic indices between the SGA group and controls.

CONCLUSION

Pregnancies complicated by FGR presented with impaired maternal hemodynamic function, as evidenced by lower HR and CO, as well as higher MAP, SVR and UtA resistance. Pregnancies delivering a SGA neonate, without evidence of FGR, had normal maternal hemodynamic function. Maternal hemodynamic indices may therefore be of value in distinguishing FGR from SGA pregnancies. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Evaluation of a Training Program to Improve Organizational Capacity for Health Systems Analytics

OBJECTIVE

The Leadership in Analytics and Data Science (LEADS) course was evaluated for effectiveness. LEADS was a 6-month program for working biomedical and health informatics (BMHI) professionals designed to improve analytics skills, knowledge of enterprise applications, data stewardship, and to foster an analytics community of practice through lectures, hands-on skill building workshops, networking events, and small group projects.

METHODS

The effectiveness of the LEADS course was evaluated using the Kirkpatrick Model by assessing pre- and postcourse knowledge, analytics capabilities, goals, practice, class lecture reaction, and change in the size of participant professional networks. Differences in pre- and postcourse responses were analyzed with a Wilcoxon signed rank test to determine significance, and effect sizes were computed using a z-statistic.

RESULTS

Twenty-nine students completed the course with 96% of respondents reporting that they were "very" or "extremely" likely to recommend the course. Participants reported improvement in several analytics capabilities including Epic data warehousing (p = 0.017), institutional review board policy (p = 0.005), and data stewardship (p = 0.007). Changes in practice patterns mirrored those in self-reported capability. On average, the participant professional network doubled.

CONCLUSION

LEADS was the first course targeted to working BMHI professional at a large academic medical center to have a formal effectiveness evaluation be published in the literature. The course achieved the goals of expansion of BMHI knowledge, skills, and professional networks. The LEADS course provides a template for continuing education of working BMHI professionals.

Please Be Careful with Me: Discrepancies between Adolescent Expectations and Clinician Perspectives on the Management of Pelvic Inflammatory Disease

STUDY OBJECTIVE

To compare clinician perspectives for the treatment of pelvic inflammatory disease (PID) with those of adolescent patients and parents.

DESIGN

Cross-sectional study.

SETTING

Urban academic pediatric and adolescent medicine practices and school-based health clinics in a large urban community with a high prevalence of sexually transmitted infections and a national sample of adolescent-serving clinicians.

PARTICIPANTS

Female patients aged 12-19 years, parents raising an adolescent older than the age of 12 years in the urban community, and clinicians who serve adolescents recruited from regional and national listservs.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Visual analogue scale scores on a scale of 0-10 corresponding to preferences on patient disposition in 17 clinical scenarios for a hypothetical patient with PID.

RESULTS

Compared with adolescents, clinicians were significantly more likely to endorse hospitalizations when patients presented with severe or complicated illness (β = 0.9; standard error [SE], 0.22; P < .001), possible surgical emergency (β = 0.83; SE, 0.2; P < .001), concurrent pregnancy (β = 0.59; SE, 0.3; P = .046), or failure of outpatient treatment (β = 0.58; SE, 0.29; P = .045). Compared with clinicians, adolescents were significantly more likely to endorse hospitalizations when patients presented at a young age (β = 1.36; SE, 0.38; P < .001), were homeless (β = 0.88; SE, 0.32; P = .007), were afraid to inform a partner (β = 1.66; SE, 0.40; P < .001), or had unaware parents (β = 2.86; SE, 0.39; P < .001).

CONCLUSION

Clinicians were more likely to recommend hospitalization when doing so adhered to national guidelines on PID treatment. Adolescents opted for hospitalization more often than clinicians in scenarios in which patients exhibited social vulnerability. Clinicians should engage with adolescents in shared disposition planning and use a more nuanced approach to PID management for adolescents who might not be able to tolerate an outpatient regimen.

Correlation between central and uterine hemodynamics in hypertensive disorders of pregnancy

OBJECTIVE

Pregnancies affected by a hypertensive disorder (HDP) have increased uterine artery pulsatility index (UtA-PI) compared with that in healthy pregnancies. Women with HDP are also known to have lower cardiac output and increased systemic vascular resistance. The aim of this study was to investigate the relationship between central and uterine hemodynamics in HDP and uncomplicated pregnancy.

METHODS

This was a prospective study of HDP and normotensive control singleton pregnancies presenting at a tertiary referral hospital between January 2012 and December 2017. Paired measurements of maternal hemodynamics, using a non-invasive device (USCOM-1A®), and UtA-PI were performed in the third trimester. HDP pregnancies were divided into preterm (onset < 37 weeks' gestation) and term (onset ≥ 37 weeks). Spearman's rank coefficient was used to assess the correlation between the central and uteroplacental hemodynamics. Regression analysis was performed to assess the association of UtA-PI with independent variables.

RESULTS

We included 231 women with HDP (152 with preterm and 79 with term HDP) and 378 controls with normotensive pregnancy. Compared with controls, women with preterm HDP had significantly lower cardiac output (median (interquartile range (IQR)), 6.0 (5.1-7.2) vs 6.6 (5.8-7.5) L/min; P < 0.001) and significantly higher systemic vascular resistance (median (IQR), 1394 (1189-1670) vs 1063 (915-1222) dynes × s/cm⁵ ; P < 0.001) and UtA-PI (median (IQR), 1.0 (0.75-1.4) vs 0.67 (0.58-0.83); P < 0.001). Conversely, in women with term HDP, there were no significant differences in heart rate, cardiac output or UtA-PI compared with controls (all P > 0.05), while systemic vascular resistance was significantly higher (median (IQR), 1315 (1099-1527) vs 1063 (915-1222) dynes × s/cm⁵ ; P < 0.001). On multiple regression analysis, heart rate, mean arterial pressure and stroke volume were associated significantly with mean UtA-PI (all P < 0.001).

CONCLUSIONS

Differences observed between HDP and normotensive pregnancies in third-trimester UtA resistance are mirrored in the central maternal hemodynamic parameters. Late pregnancy differences in the uteroplacental circulation in preterm and term HDP are an index of maternal cardiovascular function rather than being related to inadequate spiral artery remodeling and impaired placentation. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

Association of sex and atrial fibrillation therapies with patient-reported outcomes

OBJECTIVES

Women report higher atrial fibrillation (AF) symptom severity and receive less AF therapies than their male counterparts. It is understudied if differences in AF therapies received explains sex differences in AF symptom severity. We investigate the impact of sex and AF therapies on patient-reported outcomes.

METHODS

Participants were recruited (n=953) across four academic medical centres with an AF diagnosis and age ≥18 years. Patient-reported outcomes (AF symptom severity, AF-related quality of life, functional status and emotional status) were determined by biannual surveys. We performed multiple linear regressions on propensity-matched cohorts to determine the association of AF therapies and sex on patient-reported outcomes.

RESULTS

Our study population (n=953) was 65% male (n=616), 93% white (n=890) and 72 (±10) years old. Individuals receiving rate control therapy reported comparatively lower AF-related quality of life (-7.22, 95% CI -11.51 to -2.92) and poorer functional status (-3.69, 95% CI -5.27 to -2.12). Individuals receiving rhythm control strategies did not report significantly different patient-reported outcomes. Women were more likely to report poorer functional status (-2.63, 95% CI -3.86 to -1.40) and poorer AF-related quality of life, higher anxiety (2.33, 95% CI 1.07 to 3.59), higher symptoms of depression (1.48, 95% CI 0.31 to 2.65) and AF symptom severity (0.29, 95% CI 0.07 to 0.52).

CONCLUSIONS

Female sex was associated with comparatively poorer AF symptom severity and quality of life, and this association remained after accounting for AF therapies received. Receiving rate control medication alone was associated with comparatively poorer AF-related quality of life and functional status.

Association of sex, age and education level with patient reported outcomes in atrial fibrillation

BACKGROUND

In atrial fibrillation (AF), there are known sex and sociodemographic disparities in clinical outcomes such as stroke. We investigate whether disparities also exist with respect to patient-reported outcomes. We explored the association of sex, age, and education level with patient-reported outcomes (AF-related quality of life, symptom severity, and emotional and functional status).

METHODS

The PaTH AF cohort study recruited participants (N = 953) with an AF diagnosis and age ≥ 18 years across 4 academic medical centers. We performed longitudinal multiple regression with random effects to determine if individual characteristics were associated with patient-reported outcomes.

RESULTS

Women reported poorer functional status (β - 2.23, 95% CI: -3.52, - 0.94) and AF-related quality of life (β - 4.12, 95% CI: -8.10, - 0.14), and higher symptoms of anxiety (β 2.08, 95% CI: 0.76, 3.40), depression (β 1.44, 95% CI: 0.25, 2.63), and AF (β 0.29, 95% CI: 0.08, 0.50). Individuals < 60 years were significantly (p < 0.05) more likely to report higher symptoms of depression, anxiety, and AF, and poorer AF-related quality of life. Lack of college education was associated with reporting higher symptoms of AF (β 0.42, 95% CI: 0.17, 0.68), anxiety (β 1.86, 95% CI: 0.26, 3.45), and depression (β 1.11, 95% CI: 0.15, 2.38), and lower AF-related quality of life (β - 4.41, 95% CI: -8.25, - 0.57) and functional status.

CONCLUSION

Women, younger adults, and individuals with lower levels of education reported comparatively poor patient-reported outcomes. These findings highlight the importance of understanding why individuals experience AF differently based on certain characteristics.

Anemia Screening, Prevalence, and Treatment in Pediatric Inflammatory Bowel Disease in the United States, 2010-2014

PURPOSE

We examined the prevalence of anemia, annual screening for anemia, and treatment of anemia with iron among children with inflammatory bowel disease (IBD).

METHODS

A retrospective study of U.S. pediatric patients with IBD was performed in the MarketScan commercial claims database from 2010-2014. Children (ages 1-21) with at least two inpatient or outpatient encounters for IBD who had available lab and pharmacy data were included in the cohort. Anemia was defined using World Health Organization criteria. We used logistic regression to determine differences in screening, incident anemia, and treatment based on age at first IBD encounter and sex.

RESULTS

The cohort (n=2,446) included 1,560 Crohn's disease (CD) and 886 ulcerative colitis (UC). Approximately, 85% of CD and 81% of UC were screened for anemia. Among those screened, 51% with CD and 43% with UC had anemia. Only 24% of anemia patients with CD and 20% with UC were tested for iron deficiency; 85% were iron deficient. Intravenous (IV) iron was used to treat 4% of CD and 4% UC patients overall and 8% of those with anemia.

CONCLUSION

At least 80% of children with IBD were screened for anemia, although most did not receive follow-up tests for iron deficiency. The 43%-50% prevalence of anemia was consistent with prior studies. Under-treatment with IV iron points to a potential target for quality improvement.