EGEMS

Objective: To implement a quality improvement based system to measure and improve data quality in an observational clinical registry to support a Learning Healthcare System. Data Source: ImproveCareNow Network registry, which as of September 2019 contained data from 314,250 visits of 43,305 pediatric Inflammatory Bowel Disease (IBD) patients at 109 participating care centers. Study Design: The impact of data quality improvement support to care centers was evaluated using statistical process control methodology...

Background: Antibiotic resistant bacteria like community-onset methicillin resistant Staphylococcus aureus (CO-MRSA) have continued to cause infections in children at alarming rates and are associated with health disparities. Geospatial analyses of individual and area level data can enhance disease surveillance and identify socio-demographic and geographic indicators to explain CO-MRSA disease transmission patterns and risks. Methods: A case control epidemiology approach was undertaken to compare children with CO-MRSA to a noninfectious condition (unintentional traumatic brain injury (uTBI))...

Background: Reducing hospital-acquired pressure ulcers (PUs) in intensive care units (ICUs) has emerged as an important quality metric for health systems internationally. Limited work has been done to characterize the profile of PUs in the ICU using observational data from the electronic health record (EHR). Consequently, there are limited EHR-based prognostic tools for determining a patient's risk of PU development, with most institutions relying on nurse-calculated risk scores such as the Braden score to identify high-risk patients...

Context: Sustaining electronic health data networks and maximizing return on federal investment in their development is essential for achieving national data insight goals for transforming health care. However, crossing the business model chasm from grant funding to self-sustaining viability is challenging. Case description: This paper presents lessons learned in seeking the sustainability of the Scalable Architecture for Federated Translational Inquiries Network (SAFTINet), and electronic health data network involving over 50 primary care practices in three states...

This issue of eGEMS focuses on application of data science as a driver of health care transformation. Importantly, quantitative or qualitative analysis with a particular method is only one downstream step in the process of leveraging data. Effective analytics occurs on a continuum with multiple complementary phases, categorized here as data acquisition, ensuring or enhancing data access and usability, data analysis, and dissemination. Each of these activities is encompassed in the series of papers presented...

Objective: To assess whether implementation of age-dependent therapeutic targets for high hemoglobin A1c (HbA1c) changed clinicians' ordering of diabetes medications for older adults. Background: In 2016, Kaiser Permanente Southern California (KPSC) changed the therapeutic targets for alerting clinicians about high HbA1c results in the electronic health record, KP HealthConnect (KPHC). Previously, all HbA1c results ≥7.0 percent were flagged as high in adult patients with diabetes...

Research Objective: Non-profit hospitals are required to work with community organizations to prepare Community Health Needs Assessment (CHNA) and implementation strategy (IS). In concert with the health care delivery system's transformation from volume to value and efforts to enhance multi-sector collaboration, such community health improvement (CHI) processes have the potential to bridge efforts of the health care delivery sector, public health agencies, and community organizations to improve population health...

Research Objective: Non-profit hospitals are required to work with community organizations to prepare a Community Health Needs Assessment (CHNA) and implementation strategy (IS). In concert with the health care delivery system's transformation from volume to value and efforts to enhance multi-sector collaboration, such community health improvement (CHI) processes have the potential to bridge efforts of the health care delivery sector, public health agencies, and community organizations to improve population health...

Objective: To assess documentation of urinary incontinence (UI) in prostatectomy patients using unstructured clinical notes from Electronic Health Records (EHRs). Methods: We developed a weakly-supervised natural language processing tool to extract assessments, as recorded in unstructured text notes, of UI before and after radical prostatectomy in a single academic practice across multiple clinicians. Validation was carried out using a subset of patients who completed EPIC-26 surveys before and after surgery...

Background: Stable angina patients have difficulty understanding the tradeoffs between treatment alternatives. In this analysis, we assessed treatment planning conversations for stable angina to determine whether inadequate health literacy acts as a barrier to communication that may partially explain this difficulty. Methods: We conducted a descriptive analysis of patient questionnaire data from the PCI Choice Trial. The main outcomes were the responses to the Decisional Conflict Scale and the proportion of correct responses to knowledge questions about stable angina...

As states have embraced additional flexibility to change coverage of and payment for Medicaid services, they have also faced heightened expectations for delivering high-value care. Efforts to meet these new expectations have increased the need for rigorous, evidence-based policy, but states may face challenges finding the resources, capacity, and expertise to meet this need. By describing state-university partnerships in more than 20 states, this commentary describes innovative solutions for states that want to leverage their own data, build their analytic capacity, and create evidence-based policy...

The results of many large-scale federal or multi-site evaluations are typically compiled into long reports which end up sitting on policymaker's shelves. Moreover, the information policymakers need from these reports is often buried in the report, may not be remembered, understood, or readily accessible to the policymaker when it is needed. This is not a new challenge for evaluators, and advances in statistical methodology, while they have created greater opportunities for insight, may compound the challenge by creating multiple lenses through which evidence can be viewed...

Introduction: As hospitals and physician organizations increasingly vertically integrate, there is an important opportunity to use health systems to improve performance. Prior research has largely relied on secondary data sources, but little is known about how health systems are organized "on the ground" and what mechanisms are available to influence physician practice at the front line of care. Methods: We collected in-depth information on eight health systems through key informant interviews, descriptive surveys, and document review...

Background: Data quality frameworks within information technology and recently within health care have evolved considerably since their inception. When assessing data quality for secondary uses, an area not yet addressed adequately in these frameworks is the context of the intended use of the data. Methods: After review of literature to identify relevant research, an existing data quality framework was refined and expanded to encompass the contextual requirements not present...

Background: Despite the importance of characterizing colonoscopy indication for quality monitoring and cancer screening program evaluation, there is no standard approach to documenting colonoscopy indication in medical records. Methods: We applied two algorithms in three health care systems to assign colonoscopy indication to persons 50-89 years old who received a colonoscopy during 2010-2013. Both algorithms used standard procedure, diagnostic, and laboratory codes...

Background: Clinical data research networks (CDRNs) aggregate electronic health record data from multiple hospitals to enable large-scale research. A critical operation toward building a CDRN is conducting continual evaluations to optimize data quality. The key challenges include determining the assessment coverage on big datasets, handling data variability over time, and facilitating communication with data teams. This study presents the evolution of a systematic workflow for data quality assessment in CDRNs...

Introduction: The use of electronic health records (EHR) data in research to inform recruitment and outcomes is considered a critical element for pragmatic studies. However, there is a lack of research on the availability of substance use disorder (SUD) treatment data in the EHR to inform research. Methods: This study recruited providers who used an EHR for patient care and whose facilities were affiliated with the National Institute on Drug Abuse's National Drug Abuse Treatment Clinical Trials Network (NIDA CTN)...

Context: Enhanced recovery after surgery (ERAS) aims to improve surgical outcomes by integrating evidence-based practices across preoperative, intraoperative, and postoperative care. Data in electronic medical records (EMRs) provide insight on how ERAS is implemented and its impact on surgical outcomes. Because ERAS is a multimodal pathway provided by multiple physicians and health care providers over time, identifying ERAS cases in EMRs is not a trivial task. To better understand how EMRs can be used to study ERAS, we describe our experience with using current methodologies and the development and rationale of a new method for retrospectively identifying ERAS cases in EMRs...

Introduction: Health information generated by health care encounters, research enterprises, and public health is increasingly interoperable and shareable across uses and users. This paper examines the US public's willingness to be a part of multi-user health information networks and identifies factors associated with that willingness. Methods: Using a probability-based sample (n = 890), we examined the univariable and multivariable relationships between willingness to participate in health information networks and demographic factors, trust, altruism, beliefs about the public's ethical obligation to participate in research, privacy, medical deception, and policy and governance using linear regression modeling...

The well-known hazards of repurposing data make Data Quality (DQ) assessment a vital step towards ensuring valid results regardless of analytical methods. However, there is no systematic process to implement DQ assessments for secondary uses of clinical data. This paper presents DataGauge, a systematic process for designing and implementing DQ assessments to evaluate repurposed data for a specific secondary use. DataGauge is composed of five steps: (1) Define information needs, (2) Develop a formal Data Needs Model (DNM), (3) Use the DNM and DQ theory to develop goal-specific DQ assessment requirements, (4) Extract DNM-specified data, and (5) Evaluate according to DQ requirements...