Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses' Graph Literacy: National, Web-Based Randomized Controlled Trial.

BACKGROUND: The proliferation of health care data in electronic health records (EHRs) is fueling the need for clinical decision support (CDS) that ensures accuracy and reduces cognitive processing and documentation burden. The CDS format can play a key role in achieving the desired outcomes. Building on our laboratory-based pilot study with 60 registered nurses (RNs) from 1 Midwest US metropolitan area indicating the importance of graph literacy (GL), we conducted a fully powered, innovative, national, and web-based randomized controlled trial with 203 RNs. OBJECTIVE: This study aimed to compare care planning time (CPT) and the adoption of evidence-based CDS recommendations by RNs randomly assigned to 1 of 4 CDS format groups: text only (TO), text+table (TT), text+graph (TG), and tailored (based on the RN's GL score). We hypothesized that the tailored CDS group will have faster CPT (primary) and higher adoption rates (secondary) than the 3 nontailored CDS groups. METHODS: Eligible RNs employed in an adult hospital unit within the past 2 years were recruited randomly from 10 State Board of Nursing lists representing the 5 regions of the United States (Northeast, Southeast, Midwest, Southwest, and West) to participate in a randomized controlled trial. RNs were randomly assigned to 1 of 4 CDS format groups-TO, TT, TG, and tailored (based on the RN's GL score)-and interacted with the intervention on their PCs. Regression analysis was performed to estimate the effect of tailoring and the association between CPT and RN characteristics. RESULTS: The differences between the tailored (n=46) and nontailored (TO, n=55; TT, n=54; and TG, n=48) CDS groups were not significant for either the CPT or the CDS adoption rate. RNs with low GL had longer CPT interacting with the TG CDS format than the TO CDS format (P=.01). The CPT in the TG CDS format was associated with age (P=.02), GL (P=.02), and comfort with EHRs (P=.047). Comfort with EHRs was also associated with CPT in the TT CDS format (P<.001). CONCLUSIONS: Although tailoring based on GL did not improve CPT or adoption, the study reinforced previous pilot findings that low GL is associated with longer CPT when graphs were included in care planning CDS. Higher GL, younger age, and comfort with EHRs were associated with shorter CPT. These findings are robust based on our new innovative testing strategy in which a diverse national sample of RN participants (randomly derived from 10 State Board of Nursing lists) interacted on the web with the intervention on their PCs. Future studies applying our innovative methodology are recommended to cost-effectively enhance the understanding of how the RN's GL, combined with additional factors, can inform the development of efficient CDS for care planning and other EHR components before use in practice.

Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium.

BACKGROUND: Prognostic models of hospital-induced delirium, that include potential predisposing and precipitating factors, may be used to identify vulnerable patients and inform the implementation of tailored preventive interventions. It is recommended that, in prediction model development studies, candidate predictors are selected on the basis of existing knowledge, including knowledge from clinical practice. The purpose of this article is to describe the process of identifying and operationalizing candidate predictors of hospital-induced delirium for application in a prediction model development study using a practice-based approach. METHODS: This study is part of a larger, retrospective cohort study that is developing prognostic models of hospital-induced delirium for medical-surgical older adult patients using structured data from administrative and electronic health records. First, we conducted a review of the literature to identify clinical concepts that had been used as candidate predictors in prognostic model development-and-validation studies of hospital-induced delirium. Then, we consulted a multidisciplinary task force of nine members who independently judged whether each clinical concept was associated with hospital-induced delirium. Finally, we mapped the clinical concepts to the administrative and electronic health records and operationalized our candidate predictors. RESULTS: In the review of 34 studies, we identified 504 unique clinical concepts. Two-thirds of the clinical concepts (337/504) were used as candidate predictors only once. The most common clinical concepts included age (31/34), sex (29/34), and alcohol use (22/34). 96% of the clinical concepts (484/504) were judged to be associated with the development of hospital-induced delirium by at least two members of the task force. All of the task force members agreed that 47 or 9% of the 504 clinical concepts were associated with hospital-induced delirium. CONCLUSIONS: Heterogeneity among candidate predictors of hospital-induced delirium in the literature suggests a still evolving list of factors that contribute to the development of this complex phenomenon. We demonstrated a practice-based approach to variable selection for our model development study of hospital-induced delirium. Expert judgement of variables enabled us to categorize the variables based on the amount of agreement among the experts and plan for the development of different models, including an expert-model and data-driven model.

Nurses' Perceptions of Recommended Fall Prevention Strategies: A Rapid Review.

BACKGROUND: Limited studies have synthesized evidence on nurses' perceptions of recommended fall prevention strategies and potential differences between those and the practiced strategies. PURPOSE: To synthesize evidence about nurses' perceptions of recommended fall prevention strategies for hospitalized adults. METHODS: Using PubMed, 50 records underwent abstract and full-text screening, and 10 studies were retained. Narrative synthesis was conducted to identify common themes across studies. Quality assessment was not performed. RESULTS: Nurses are aware of effective fall prevention strategies but identified unit-level barriers and facilitators to implementing these in their practice. Unit culture and policies, educational offerings, nursing interventions, and style of communication and collaboration were seen to influence fall prevention. CONCLUSIONS: Nurses recognize falls as a multifactorial issue suggesting that prevention efforts be tailored to the unit and involve all employees. We recommend that future research emphasize identifying and understanding the combination of factors that produce successful unit-level fall prevention strategies.

Twenty-first Century Bedside Manner: Exploring Patient-Centered Communication in Secure Messaging with Cancer Patients.

Patient-centered communication (PCC) is integral to providing high-quality health care and is recommended to be incorporated during face-to-face consultations. Electronic communication, such as the use of secure messaging (SM) within patient portals, is a popular form of patient-provider communication, but preliminary studies have shown that PCC is rarely utilized by providers in SM. As a consequence, the patient-provider relationship can be negatively affected, especially for cancer patients who have greater electronic health information needs than the general population. Therefore, our objective was to determine the importance of SM to cancer patients and to identify which attributes of PCC are preferred to be incorporated into secure messages. Five focus groups were conducted, comprised of patients with a current or previous cancer diagnosis (three all-female; two all-male). Participants recalled their own experiences and reviewed simulated messages. Three main topics emerged from the thematic analysis: (1) the normalization of SM, (2) SM quality can affect perceptions of care, and (3) patients need guidance. Overall, participants valued the ability to communicate with their care team using SM and indicated that electronic communication may have the potential to have just as big of an impact on a patient's care than in-person communication.

Fall Prevention Decision Making of Acute Care Registered Nurses.

OBJECTIVE: The aim of this study was to examine acute care registered nurses' (RNs') fall prevention decision-making. BACKGROUND: The RN decision-making process related to fall prevention needs to be investigated to ensure that hospital policies align with nursing workflow and support nursing judgment. METHODS: Qualitative semistructured interviews based on the Critical Decision Method were conducted with RNs about their planning and decision making during their last 12-hour shift worked. RESULTS: Data saturation was achieved with 12 RNs. Nine themes emerged related to the RN decision-making process and included hospital-level (eg, fear of discipline), unit-level (eg, value of bed alarm technology), and nurse-level (eg, professional judgment) factors that could influence fall prevention. CONCLUSIONS: Nursing administrators should consider a multilevel approach to fall prevention policies that includes promoting a practice environment that embraces self-reporting adverse events without fear of shame or being reprimanded, evaluating unit-level practice and technology acceptance and usability, and supporting autonomous nursing practice.

The Role of Nurse Managers in the Adoption of Health Information Technology: Findings From a Qualitative Study.

OBJECTIVE: This study aims to investigate the role of nurse managers in supporting point-of-care nurses' health information technology (IT) use and identify strategies employed by nurse managers to improve adoption, while also gathering point-of-care nurses' perceptions of these strategies. BACKGROUND: Nurse managers are essential in facilitating point-of-care nurses' use of health IT; however, the underlying phenomenon for this facilitation remains unreported. METHODS: A qualitative descriptive study was conducted with 10 nurse managers and 14 point-of-care nurses recruited from a mental health hospital environment in Ontario, Canada. Inductive and deductive content analyses were used to analyze the semistructured interviews. RESULTS: Nurse managers adopt the role of advocate, educator, and connector, using the following strategies: communicating system updates, demonstrating use of health IT, linking staff to resources, facilitating education, and providing IT oversight. CONCLUSIONS: Nurse managers use a variety of strategies to support nurses' use of health IT. Future research should focus on the effectiveness of these strategies.

Nurse Documentation of Sexual Orientation and Gender Identity in Home Healthcare: A Text Mining Study.

Health disparities have been documented in the lesbian, gay, bisexual, and transgender population, but more research is needed to better understand how to address them. To that end, this observational study examined what is documented about sexual orientation and gender identity in narrative home care nurses' notes in an electronic health record. Lexical text mining approaches were used to examine a total of 862 715 clinical notes from 20 447 unique patients who received services from a large home care agency in Manhattan, New York, and extracted notes were qualitatively reviewed to build a lexicon of terms for use in future research. Forty-two notes, representing 35 unique patients, were identified as containing documentation of the patient's sexual orientation or gender identity. Documentation of sexual orientation or gender identity was relatively infrequent, compared to the estimated frequency of lesbian, gay, bisexual, and transgender people in the US population. Issues related to fragmentary language emerged, and variety in phrasing and word frequency was identified between different types of notes and between providers. This study provides insight into what nurses in home healthcare document about sexual orientation and gender identity and their clinical priorities related to such documentation, and provides a lexicon for use in further research in the home care setting.

Benefits of Implementing and Improving Collection of Sexual Orientation and Gender Identity Data in Electronic Health Records.

Individuals in lesbian, gay, bisexual, and transgender communities experience several disparities in physical and mental health (eg, cardiovascular disease and depression), as well as difficulty accessing care that is compassionate and relevant to their unique needs. Access to care is compromised in part due to inadequate information systems that fail to capture identity data. Beginning in January 2018, meaningful use criteria dictate that electronic health records have the capability to collect data related to sexual orientation and gender identity of patients. Nurse informaticists play a vital role in the process of developing new electronic health records that are sensitive to the needs and identities of the lesbian, gay, bisexual, and transgender communities. Improved collection of sexual orientation and gender identity data will advance the identification of health disparities experienced by lesbian, gay, bisexual, and transgender populations. More inclusive electronic health records will allow providers to monitor risk behavior, assess progress toward the reduction of disparities, and provide healthcare that is patient and family centered. Concrete suggestions for the modification of electronic health record systems are presented, as well as how nurse informaticists may be able to bridge gaps in provider knowledge and discomfort through interprofessional collaboration when implementing changes in electronic health records.

Patient perspectives on answering questions about sexual orientation and gender identity: an integrative review.

AIMS AND OBJECTIVES: To examine patients' perceptions of being asked about their sexual orientation and gender identity in the healthcare setting. BACKGROUND: Health disparities exist in the lesbian, gay, bisexual and transgender population, but further research is needed to better understand these disparities. To address this issue, experts recommend the routine collection of sexual orientation and gender identity data in health care. Nurses on the front line of patient care play a key role in the collection of these data. However, to enable nurses to conduct such assessments it is important to understand the perspective of the patients on being asked about their sexual orientation and gender identity in a healthcare setting. DESIGN: An integrative review was conducted using the methodology proposed by Whittemore and Knafl (Journal of Advanced Nursing, 2005, 52, 546). METHODS: Six electronic databases were searched, and two reviewers independently reviewed papers for inclusion. Papers were included if they were empirical studies, peer-reviewed papers or reports, assessing patient perspectives on discussing sexual orientation and gender identity in the healthcare setting. RESULTS: Twenty-one relevant studies that met the inclusion criteria were identified. A majority of the studies indicated patients' willingness to respond to, and a perceived importance of, questions about sexual orientation and gender identity. However, fears of homophobia and negative consequences hindered willingness to disclose this information. CONCLUSIONS: This review indicates that in most cases patients are willing to answer routine questions about their sexual orientation in the healthcare setting and perceive them as important questions to ask. RELEVANCE TO CLINICAL PRACTICE: The findings of this review have implications for nurses looking to incorporate questions about sexual orientation into their routine patient assessment. The findings indicate that care providers need to be mindful of heteronormative assumptions and take steps to ensure they are knowledgeable about lesbian, gay, bisexual and transgender health.

Implementation of Electronic Health Records in US Nursing Homes.

While electronic health records have emerged as promising tools to help improve quality of care, nursing homes have lagged behind in implementation. This study assessed electronic health records implementation, associated facility characteristics, and potential impact on quality indicators in nursing homes. Using national Centers for Medicare & Medicaid Services and survey data for nursing homes, a cross-sectional analysis was conducted to identify variations between nursing homes that had and had not implemented electronic health records. A difference-in-differences analysis was used to estimate the longitudinal effect of electronic health records on commonly used quality indicators. Data from 927 nursing homes were examined, 49.1% of which had implemented electronic health records. Nursing homes with electronic health records were more likely to be nonprofit/government owned (P = .04) and had a lower percentage of Medicaid residents (P = .02) and higher certified nursing assistant and registered nurse staffing levels (P = .002 and .02, respectively). Difference-in-differences analysis showed greater quality improvements after implementation for five long-stay and two short-stay quality measures (P = .001 and .01, respectively) compared with those who did not implement electronic health records. Implementation rates in nursing homes are low compared with other settings, and better-resourced facilities are more likely to have implemented electronic health records. Consistent with other settings, electronic health records implementation improves quality in nursing homes, but further research is needed to better understand the mechanism for improvement and how it can best be supported.

"Striving for Excellence": Minimum Data Set Coordinators' Perceptions of Their Role in the Nursing Home.

The purpose of the current study was to explore how Minimum Data Set (MDS) coordinators perceive their role and the assessment process. Eleven MDS coordinators from 10 geographically dispersed nursing homes (NHs) were interviewed between May and September 2013. Four broad themes emerged from content analysis: (a) information gathering, (b) interdisciplinary coordination, (c) role challenges, and (d) resources. The first two themes referred to key components and competencies in the MDS coordinators' role, the third theme dealt with certain challenges inherent in the role, and the fourth theme highlighted resources that helped address these challenges. The current study provides insight into how MDS coordinators perceive their role, as well as some of the challenges they face to successfully enact that role. The current findings can help inform NH management staff, such as directors of nursing and NH administrators, and policy makers, on how best to support MDS coordinators' work to enable efficient and accurate resident assessment processes.

Perceived barriers to infection prevention and control for nursing home certified nursing assistants: a qualitative study.

Healthcare-associated infections, while preventable, result in increased morbidity and mortality in nursing home (NH) residents. Frontline personnel, such as certified nursing assistants (CNAs), are crucial to successful implementation of infection prevention and control (IPC) practices. The purpose of this study was to explore barriers to implementing and maintaining IPC practices for NH CNAs as well as to describe strategies used to overcome these barriers. We conducted a multi-site qualitative study of NH personnel important to infection control. Audio-recorded interviews were transcribed verbatim and transcripts were analyzed using conventional content analysis. Five key themes emerged as perceived barriers to effective IPC for CNAs: 1) language/culture; 2) knowledge/training; 3) per-diem/part-time staff; 4) workload; and 5) accountability. Strategies used to overcome these barriers included: translating in-services, hands on training, on-the-spot training for per-diem/part-time staff, increased staffing ratios, and inclusion/empowerment of CNAs. Understanding IPC barriers and strategies to overcome these barriers may better enable NHs to achieve infection reduction goals.

Understanding infection prevention and control in nursing homes: A qualitative study.

Infections have been identified as a priority issue in nursing homes (NHs). We conducted a qualitative study purposively sampling 10 NHs across the country where 6-8 employees were recruited (N = 73). Semi-structured, open-ended guides were used to conduct in-depth interviews. Data were audiotaped, transcribed and a content analysis was performed. Five themes emerged: 'Residents' Needs', 'Roles and Training' 'Using Infection Data,' 'External Resources' and 'Focus on Hand Hygiene.' Infection prevention was a priority in the NHs visited. While all sites had hand hygiene programs, other recommended areas were not a focus and many sites were not aware of available resources. Developing ways to ensure effective, efficient and standardized infection prevention and control in NHs continues to be a national priority.

The use of artificial intelligence for graduate nursing education: An educational evaluation.

ABSTRACT: With artificial intelligence (AI) rapidly advancing, advanced practice nurses must understand and use it responsibly. Here, we describe an assignment in which Doctor of Nursing Practice (DNP) students learned to use generative text AI. Using our program and course outcomes, developed from the 2021 American Association of Colleges of Nursing (AACN) Essentials competency for DNP students to learn and use AI, we reviewed the literature seeking examples using ChatGPT for the DNP informatics course. No published examples existed to guide us toward infusing a ChatGPT assignment into the course. We developed a novel assignment that included a guide for students on how to use ChatGPT. Students were given time before the assignment to learn the AI/chatbot technology. They were then given the assignment and grading rubric. The assignment was to develop a tool for their current or future practice using ChatGPT. During the course faculty debrief, we learned that few students had questions and the assignment was clear. We also learned that students who sought to develop straightforward, uncomplicated patient tools succeeded with the technology. Those who sought to create something for complex patients had more challenges. Nursing education and practice will be influenced by the increasing prevalence of AI. This manuscript outlines an AI-based assignment for graduate nursing education intended for the students to become familiar with current AI and best practices for patient care. The assignment was well received by students. We plan to use it again in the next course offering.

Unveiling Fall Risk Factors: Nurse-Driven Corpus Development for Natural Language Processing.

Hospital-acquired falls are a continuing clinical concern. The emergence of advanced analytical methods, including NLP, has created opportunities to leverage nurse-generated data, such as clinical notes, to better address the problem of falls. In this nurse-driven study, we employed an iterative process for expert manual annotation of RNs clinical notes to enable the training and testing of an NLP pipeline to extract factors related to falls. The resulting annotated data corpus had moderately high interrater reliability (F-score=0.74) and captured a breadth of clinical concepts for extraction with potential utility beyond patient falls. Further research is needed to determine which annotation tasks most benefit from nursing expert annotators, to optimize efficiency when tapping into the invaluable resource represented by the nursing workforce.

Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review.

PURPOSE: The purpose of this systematic review was to assess risk of bias in existing prognostic models of hospital-induced delirium for medical-surgical units. METHODS: APA PsycInfo, CINAHL, MEDLINE, and Web of Science Core Collection were searched on July 8, 2022, to identify original studies which developed and validated prognostic models of hospital-induced delirium for adult patients who were hospitalized in medical-surgical units. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was used for data extraction. The Prediction Model Risk of Bias Assessment Tool was used to assess risk of bias. Risk of bias was assessed across four domains: participants, predictors, outcome, and analysis. RESULTS: Thirteen studies were included in the qualitative synthesis, including ten model development and validation studies and three model validation only studies. The methods in all of the studies were rated to be at high overall risk of bias. The methods of statistical analysis were the greatest source of bias. External validity of models in the included studies was tested at low levels of transportability. CONCLUSIONS: Our findings highlight the ongoing scientific challenge of developing a valid prognostic model of hospital-induced delirium for medical-surgical units to tailor preventive interventions to patients who are at high risk of this iatrogenic condition. With limited knowledge about generalizable prognosis of hospital-induced delirium in medical-surgical units, existing prognostic models should be used with caution when creating clinical practice policies. Future research protocols must include robust study designs which take into account the perspectives of clinicians to identify and validate risk factors of hospital-induced delirium for accurate and generalizable prognosis in medical-surgical units.

Usability Testing of an Interoperable Computerized Clinical Decision Support Tool for Fall Risk Management in Primary Care.

BACKGROUND: Falls are a widespread and persistent problem for community-dwelling older adults. Use of fall prevention guidelines in the primary care setting has been suboptimal. Interoperable computerized clinical decision support systems have the potential to increase engagement with fall risk management at scale. To support fall risk management across organizations, our team developed the ASPIRE tool for use in differing primary care clinics using interoperable standards. OBJECTIVES: Usability testing of ASPIRE was conducted to measure ease of access, overall usability, learnability, and acceptability prior to pilot . METHODS: Participants were recruited using purposive sampling from two sites with different electronic health records and different clinical organizations. Formative testing rooted in user-centered design was followed by summative testing using a simulation approach. During summative testing participants used ASPIRE across two clinical scenarios and were randomized to determine which scenario they saw first. Single Ease Question and System Usability Scale were used in addition to analysis of recorded sessions in NVivo. RESULTS: All 14 participants rated the usability of ASPIRE as above average based on usability benchmarks for the System Usability Scale metric. Time on task decreased significantly between the first and second scenarios indicating good learnability. However, acceptability data were more mixed with some recommendations being consistently accepted while others were adopted less frequently. CONCLUSION: This study described the usability testing of the ASPIRE system within two different organizations using different electronic health records. Overall, the system was rated well, and further pilot testing should be done to validate that these positive results translate into clinical practice. Due to its interoperable design, ASPIRE could be integrated into diverse organizations allowing a tailored implementation without the need to build a new system for each organization. This distinction makes ASPIRE well positioned to impact the challenge of falls at scale.

Management of Fall Risk Among Older Adults in Diverse Primary Care Settings.

OBJECTIVES: Falls are persistent among community-dwelling older adults despite existing prevention guidelines. We described how urban and rural primary care staff and older adults manage fall risk and factors important to integration of computerized clinical decision support (CCDS). METHODS: Interviews, contextual inquiries, and workflow observations were analyzed using content analysis and synthesized into a journey map. Sociotechnical and PRISM domains were applied to identify workflow factors important to sustainable CCDS integration. RESULTS: Participants valued fall prevention and described similar approaches. Available resources differed between rural and urban locations. Participants wanted evidence-based guidance integrated into workflows to bridge skills gaps. DISCUSSION: Sites described similar clinical approaches with differences in resource availability. This implies that a single intervention would need to be flexible to environments with differing resources. Electronic Health Record's inherent ability to provide tailored CCDS is limited. However, CCDS middleware could integrate into different settings and increase evidence use.

Clinical Prediction Models for Hospital-Induced Delirium Using Structured and Unstructured Electronic Health Record Data: Protocol for a Development and Validation Study.

BACKGROUND: Hospital-induced delirium is one of the most common and costly iatrogenic conditions, and its incidence is predicted to increase as the population of the United States ages. An academic and clinical interdisciplinary systems approach is needed to reduce the frequency and impact of hospital-induced delirium. OBJECTIVE: The long-term goal of our research is to enhance the safety of hospitalized older adults by reducing iatrogenic conditions through an effective learning health system. In this study, we will develop models for predicting hospital-induced delirium. In order to accomplish this objective, we will create a computable phenotype for our outcome (hospital-induced delirium), design an expert-based traditional logistic regression model, leverage machine learning techniques to generate a model using structured data, and use machine learning and natural language processing to produce an integrated model with components from both structured data and text data. METHODS: This study will explore text-based data, such as nursing notes, to improve the predictive capability of prognostic models for hospital-induced delirium. By using supervised and unsupervised text mining in addition to structured data, we will examine multiple types of information in electronic health record data to predict medical-surgical patient risk of developing delirium. Development and validation will be compliant to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. RESULTS: Work on this project will take place through March 2024. For this study, we will use data from approximately 332,230 encounters that occurred between January 2012 to May 2021. Findings from this project will be disseminated at scientific conferences and in peer-reviewed journals. CONCLUSIONS: Success in this study will yield a durable, high-performing research-data infrastructure that will process, extract, and analyze clinical text data in near real time. This model has the potential to be integrated into the electronic health record and provide point-of-care decision support to prevent harm and improve quality of care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48521.

The relationship between electronic health records user interface features and data quality of patient clinical information: an integrative review.

OBJECTIVES: Electronic health records (EHRs) user interfaces (UI) designed for data entry can potentially impact the quality of patient information captured in the EHRs. This review identified and synthesized the literature evidence about the relationship of UI features in EHRs on data quality (DQ). MATERIALS AND METHODS: We performed an integrative review of research studies by conducting a structured search in 5 databases completed on October 10, 2022. We applied Whittemore & Knafl's methodology to identify literature, extract, and synthesize information, iteratively. We adapted Kmet et al appraisal tool for the quality assessment of the evidence. The research protocol was registered with PROSPERO (CRD42020203998). RESULTS: Eleven studies met the inclusion criteria. The relationship between 1 or more UI features and 1 or more DQ indicators was examined. UI features were classified into 4 categories: 3 types of data capture aids, and other methods of DQ assessment at the UI. The Weiskopf et al measures were used to assess DQ: completeness (n = 10), correctness (n = 10), and currency (n = 3). UI features such as mandatory fields, templates, and contextual autocomplete improved completeness or correctness or both. Measures of currency were scarce. DISCUSSION: The paucity of studies on UI features and DQ underscored the limited knowledge in this important area. The UI features examined had both positive and negative effects on DQ. Standardization of data entry and further development of automated algorithmic aids, including adaptive UIs, have great promise for improving DQ. Further research is essential to ensure data captured in our electronic systems are high quality and valid for use in clinical decision-making and other secondary analyses.