Health Records Research Articles

Evaluation of an Outpatient Cervical Ripening Program Using Osmotic Dilators and Foley Balloon Catheters.

This study aimed to describe patient characteristics, satisfaction, and outcome measures for patients undergoing outpatient cervical ripening. A retrospective cohort study using electronic health record data from March 2020 to March 2022 from a large health system. The sample included patients with a low-risk singleton pregnancy undergoing outpatient cervical ripening with either an osmotic dilator or Foley balloon catheter. A subset of patients completed satisfaction surveys. Frequencies and means were used to describe the population and conduct comparisons by device type. Inverse probability of treatment weighted estimates were generated to address baseline differences between patients in the two device groups. Outpatient cervical ripening was completed by 120 patients (80 osmotic dilators and 40 Foley balloon catheters). The mean time from insertion to inpatient admission was 16.2 ± 4.8 hours. The mean change in simplified Bishop score (SBS) was 1.8 ± 1.4 and the mean change in dilation was 1.8 ± 1.1 cm. There were no differences in the amount of cervical change by device type. Patients returned earlier than planned 16.7% of the time, primarily for contractions or rupture of membranes. Following outpatient cervical ripening, the time from admission to delivery was 19.9 ± 10.3 hours, with no difference by device type. Vaginal delivery occurred for 74.8% of patients. Patients reported overall satisfaction with the outpatient cervical ripening experience, with the highest satisfaction among those with osmotic dilators. Patients with both device types stated they would recommend outpatient cervical ripening to others, and experienced low levels of stress and discomfort at home prior to hospital admission. Patients participating in outpatient cervical ripening with osmotic dilators or Foley balloon catheters experienced clinically meaningful changes in dilation and SBSs while at home and reported general satisfaction with the outpatient program experience. · Outpatient use of osmotic dilators or Foley balloon catheters improved Bishop scores.. · Patient and device complications were comparable to other research findings.. · Patients reported overall satisfaction with outpatient cervical ripening..

Equity-Focused Evaluation of a Medicaid-Funded Statewide Diabetes Quality Improvement Project Collaborative.

To evaluate the Ohio Diabetes Quality Improvement Project (QIP) equity aim to reduce the percentage of Non-Hispanic Black (NHB) and Hispanic patients with A1C >9% by ≥20% over 2 years. The Ohio Department of Medicaid, Ohio Colleges of Medicine Government Resource Center, Ohio Medicaid managed care plans, and seven medical schools in Ohio formed the Diabetes QIP collaborative using the collective impact model to improve diabetes outcomes and equity in 20 practices across 11 health systems. The quality improvement (QI) strategies included data audit and feedback, peer-to-peer learning, QI coaching/practice facilitation, and subject matter expert consultation through coaching calls, monthly webinars, and annual virtual learning sessions. Electronic health record data were collected for preintervention (2019-2020) and intervention (2020-2022) periods. Assessments of improvements in A1C were based on prevalence of A1C >9% from preintervention, year 1, and year 2 with stratification by race and ethnicity. The Diabetes QIP included 7,689 (54% female) sociodemographically diverse patients, self-identifying as non-Hispanic White (NHW) (42%), NHB (43%), Hispanic (8%), non-Hispanic Asian (4%), or other (3%). In year 2 compared with baseline, there were decreases in the proportion of patients with A1C >9% among NHW, NHB, and Hispanic patients (NHW from 19% to 12% [37% reduction], NHB 23% to 18% [22% reduction], and Hispanic 29% to 23% [20% reduction]). The Ohio Diabetes QIP, focused on multisector collaborative approaches, reduced the percentage of patients with A1C >9% by ≥20% among NHW, NHB, and Hispanic populations. Given the persistence of disparities, further equity-focused refinements are warranted to address disparities in diabetes control.

The Impact of Leadership and Management on the Implementation of Electronic Health Record Systems in the Primary Healthcare Centers.

In the last three decades, Electronic Health Records Systems (EHRSs) have become one of the top priorities of policymakers globally. Nowadays, EHRS reform is fast becoming a priority in developed countries. The introduction of EHRSs in Saudi healthcare organizations is considered one of the highest priorities of policymakers. Saudi Arabian e-health strategy pays reasonable attention to the EHRS implementation project. According to Saudi Vision 2030, the e-health transformation will be on top of IT projects in the country. However, an estimated 50% of EHRS implementations have failed. Project leadership and type of project management have been found to be crucial components of effective EHRS implementation. To evaluate the role of centralized project management (CPM) in the implementation of large-scale EHRSs in Primary Healthcare Centers (PHCs) in Saudi Arabia (SA). A sequential explanatory mixed-methods approach involving a survey and semi-structured qualitative interview methods were utilized. A total of 39 (75%) out of 53 policymakers at the Saudi Ministry of Health completed the survey, and 14 project team members were interviewed. Findings from both illustrated that adopting centralized project management approaches to implementation was beneficial in facilitating large-scale EHRS implementation and helped to overcome barriers that may have otherwise led to the failure of the project. EHRS interoperability and software selection were the factors that CPM influenced most positively.

Creating a Learning Health System in a Cancer Center: Generalizability of an Electronic Health Record Phenotype for Advanced Solid Cancer.

To test the generalizability of an electronic health record (EHR) phenotype for patients with advanced solid cancer, which was previously developed in a single cancer center. We compared an algorithm to identify patients with advanced solid cancer from a random sample of patients with active cancer in the Veterans Health Administration (VA) and an academic cancer center with a human-coded reference standard between January 1, 2016, and December 31, 2019. Compared with the human-coded reference standard, the algorithm had high specificity (93%; 95% CI, 87 to 99 and 97%; 95% CI, 93 to 100) and reasonable sensitivity (85%; 95% CI, 76 to 94 and 87%; 95% CI, 77 to 97) in the VA and academic cancer center populations, respectively. Patients with advanced cancer (compared with those with active nonadvanced cancer) had higher mortality at the VA and academic cancer center (29.2% and 17.0% 6-month mortality v 6.8% and 3.5%), respectively. This EHR phenotype can be used to measure and improve the quality of palliative care for patients with advanced cancer within and across health care settings.

Proposed framework for medication delivery system in the Jordanian public health sector

BackgroundIn Jordan, the confluence of traffic congestion and overcrowding in public hospitals poses a significant challenge for patients to collect their medications timely. This challenge was further intensified during the COVID-19 pandemic. Recognizing this issue, the Ministry of Health (MOH) and Electronic Health Solutions (EHS) intend to establish a Medication Delivery System (MDS), designed to provide patients with home delivery of medications and ensure proper treatment. This paper outlines a comprehensive framework to guide requirements engineers in devising an effective MDS framework, with a focus on expediting the development and testing processes and mitigating the risks associated with constructing such a system.MethodThe proposed methodology entails a robust, structured approach to requirements development for an MDS that integrates an electronic health record system, billing system, pharmacy application, the patient-oriented My Hakeem app, and a delivery tracking system. The requirements elicitation and analysis processes were undertaken by a multidisciplinary committee from MOH and EHS teams, ensuring a diverse understanding of stakeholder needs and expectations. The requirement specifications were meticulously documented via a data dictionary, unified modeling language (UML), and context diagrams. The quality and accuracy of the requirements were verified through an extensive validation process, involving thorough review by various EHS teams and the MOH committee.ResultsThe MDS was implemented across numerous MOH facilities within a timeline that was a third of the original projection, leveraging the same level of resources and expertise. Post the requirements development phase, there were no changes requested by any stakeholders, indicating a high level of requirement accuracy and satisfaction.ConclusionThe study illustrates that our proposed methodology significantly results in a comprehensive, well-documented, and validated set of requirements, which streamlines the development and testing phases of the project and effectively eliminates requirement errors at an early stage of the requirements development process.

An Ethics Consult Documentation Simplification Project: Summation of Participatory Processes, User Perceptions, and Subsequent Use Patterns.

Healthcare ethics consultants in the Veterans Health Administration (VHA) document consults in an enterprise-wide web-based database entitled IEWeb, serving as a system of record for healthcare ethics documentation at 1300 VA facilities. The need arose to evolve the database from an ethics process training resource into a more streamlined documentation repository that captures essential consult elements. A VHA National Center for Ethics in Health Care (NCEHC) Improvement Team convened for three tasks: (1) Specify and prioritize IEWeb changes (occurred via six focus groups composed of "new user" and "super user" cohorts with analysis of existing documentation patterns); (2) Pilot the changes regionally (via regional communication, training, and reviews of pre-post use patterns); and (3) Measure the impact of national change implementation on user perspectives (via pre-and post-change implementation polls). Focus groups identified six implementable priority areas for ethics consult documentation improvement, including the development of a usable consult summary note for ready conversion from IEWeb fields into the electronic health record. Post-IEWeb updates showed an increased number of consults documented, a reduction in "time to consult documentation closure" by a mean of 4.5days, and a clinically-meaningful improvement in the quality of documentation (78% of ethics questions scored "above-bar" on the validation tool pre- vs. 89% scored "above-bar" post-IEWeb changes, n = 140). According to national survey findings, the number of consultants documenting "all" consults in IEWeb increased, satisfaction increased, and perception of documentation difficulty decreased. IEWeb simplification enabled ethics consultants to re-focus their documentation completion efforts by decreasing perception of documentation burden while improving documentation frequency and quality in a clinically-meaningful way.

Evaluating the impact of a specialized and centralized online medical consultation system for paramedics: pilot study.

There are many limitations to utilizing on-duty emergency department (ED) physicians as Base Hospital Physicians for paramedic telephone consultations. We aimed to examine the impact of a specialized and centralized Online Medical Consultation program for paramedic consultations on system-relevant performance. This is a before-after study with concurrent control using health record review of audio recordings over a 6-month period before and after implementation of the Online Medical Consultation program. The primary outcome was the duration of paramedic consultation calls. The secondary outcomes included number of calls with orders that contradicted existing medical directives, number of calls with orders outside of paramedic scope of practice, number of calls with Base Hospital Physician requiring clarification on medical directives, and number of calls with Base Hospital Physician interrupting the paramedic during the call. We included 220 consultation calls. The patients' mean age was 54.5years. Most consultation calls (70.5%) were for mandatory consultations and 22.7% were voluntary. Most consultations were related to cardiac arrest (43.6%), combative patients (15.0%), and analgesia (13.6%). Before-after comparisons for total call duration showed that mean call duration decreased in Ottawa from 4:28 to 4:05min (p = 0.77) and decreased in Kingston from 4:50 to 4:13min (p = 0.49). There were no significant differences in our secondary outcomes. The Online Medical Consultation program was implemented and removed the responsibility of responding to online medical consultations for on-duty emergency physicians in Ottawa. The total call duration was not significantly different between groups. Additional time intervals and adherence to protocol benefits were also not statistically significant due to low baseline incidence.

Tree-based classification model for Long-COVID infection prediction with age stratification using data from the national COVID cohort collaborative (N3C)

Abstract Objectives We propose and validate a domain knowledge-driven classification model for diagnosing Post-acute sequelae of SARS-CoV-2 infection (PASC), also known as Long COVID, using Electronic Health Records (EHR) data. Materials and Methods We developed a robust model that incorporates features strongly indicative of PASC or associated with the severity of COVID-19 symptoms as identified in our literature review. The XGBoost tree-based architecture was chosen for its ability to handle class-imbalanced data and its potential for high interpretability. Using the training data provided by the Long COVID Computation Challenge (L3C), which was a sample of the National COVID Collaborative (N3C), our models were fine-tuned and calibrated to optimize Area Under the Receiver Operating Characteristic curve (AUROC) and the F1 score, following best practices for the class-imbalanced N3C data. Results Our age-stratified classification model demonstrated strong performance with an average 5-fold cross-validated AUROC of 0.844 and F1 score of 0.539 across the young adult, mid-aged, and older-aged populations in the training data. In an independent testing dataset, which was made available after the challenge was over, we achieved an overall AUROC score of 0.814 and F1 score of 0.545. Discussion The results demonstrated the utility of knowledge-driven feature engineering in a sparse EHR data and demographic stratification in model development to diagnose a complex and heterogeneously presenting condition like PASC. The model's architecture, mirroring natural clinician decision-making processes, contributed to its robustness and interpretability, which are crucial for clinical translatability. Further, the model’s generalizability was evaluated over a new cross-sectional data as provided in the later stages of the L3C challenge. Conclusion The study proposed and validated the effectiveness of age-stratified, tree-based classification models to diagnose PASC. Our approach highlights the potential of machine learning in addressing the diagnostic challenges posed by the heterogeneity of Long COVID symptoms.

Taking a Team Approach: Keep up with the EHR with a Training and Optimization Program.

This study aimed to describe the current landscape of electronic health record (EHR) training and optimization programs (ETOPs) and their impact on healthcare workers' (HCWs) experience with the EHR. A 72-question electronic survey was developed and distributed to healthcare organization (HCO) leaders in clinical informatics through various channels such as national informatics conferences, social media, and email distribution lists of vendors and informatics associations. The survey collected data on the characteristics, resourcing, approach, and outcomes of ETOPs. Descriptive statistics were applied to analyze the data. There were 193 responses from 147 distinct HCOs. Of these, 69% offer ongoing EHR training, and 52% offer some version of an ETOP. Offered ETOPs vary in their timing, modality, audience, team composition, duration, and EHR build strategy. The most commonly measured outcomes were EHR satisfaction, efficiency, and provider burnout, and most ETOPs reported improvement in these areas. The findings suggest that ETOPs are inconsistently implemented across HCOs, and while there are some commonalities, there is a wide variety of design and methods of evaluation for the programs. Though the problems to solve for (EHR efficiency, proficiency, and satisfaction) are the same, the organizational structure and culture of HCOs varies widely, which may partially explain the variability seen in reported ETOPs. When considering the measured outcomes, ETOPs may have direct and indirect effects on HCW burnout by improving EHR efficiency and satisfaction, as well as driving organizational culture towards teamwork and flexible problem solving. For this reason, ETOPs may also serve as a model for addressing other challenges in healthcare delivery. ETOPs are a promising intervention to enhance HCW experience with the EHR and reduce burnout. More research is needed to identify the optimal features, methods, and outcomes of ETOPs, and to disseminate them across HCOs.

An IoT Cloud Security System Powered by Blockchain for Secure Preservation of Electronic Health Records

An IoT Cloud Security System Powered by Blockchain for Secure Preservation of Electronic Health Records

Collaboration to Remove Barriers to Pump Integration With the Electronic Health Record.

The Institute for Safe Medication Practices and The Joint Commission recommend the implementation of bidirectional smart infusion pump interoperability with the electronic health record (EHR) to improve medication safety. However, there are barriers associated with implementation of this process. The purpose of this process improvement project was to identify, evaluate, and implement improvements in pump integration with the EHR to decrease manual programming and increase the use of the smart pump functions (the dose error reduction system or infusion guardrails). A medication safety task force was formed, and end users were surveyed for barriers. The task force found and implemented solutions to improve the process. Infusion pump integration rates for seven hospitals improved from 79.4% to 91.8% (p < .001), and the use of smart pump programming increased from 84.7% to 93.6%. Including all stakeholders in the project allowed barriers to be identified and solutions to be implemented. As more healthcare systems implement technology-related processes to improve patient safety, this work can guide medication safety teams on how to optimize technology use by removing barriers to the use of pump integration with the EHR.

Recent Advances in Intraoral Scanners.

Intraoral scanners (IOSs) have emerged as a cornerstone technology in digital dentistry. This article examines the recent advancements and multifaceted applications of IOSs, highlighting their benefits in patient care and addressing their current limitations. The IOS market has seen a competitive surge. Modern IOSs, featuring continuous image capture and advanced software for seamless image stitching, have made the scanning process more efficient. Patient comfort with IOS procedures is favorable, mitigating the discomfort associated with conventional impression taking. There has been a shift toward open data interfaces, notably enhancing interoperability. However, the integration of IOSs into large dental institutions is slow, facing challenges such as compatibility with existing health record systems and extensive data storage management. IOSs now extend beyond their use in computer-aided design and manufacturing, with software solutions transforming them into platforms for diagnostics, patient communication, and treatment planning. Several IOSs are equipped with tools for caries detection, employing fluorescence technologies or near-infrared imaging to identify carious lesions. IOSs facilitate quantitative monitoring of tooth wear and soft-tissue dimensions. For precise tooth segmentation in intraoral scans, essential for orthodontic applications, developers are leveraging innovative deep neural network-based approaches. The clinical performance of restorations fabricated based on intraoral scans has proven to be comparable to those obtained using conventional impressions, substantiating the reliability of IOSs in restorative dentistry. In oral and maxillofacial surgery, IOSs enhance airway safety during impression taking and aid in treating conditions such as cleft lip and palate, among other congenital craniofacial disorders, across diverse age groups. While IOSs have improved various aspects of dental care, ongoing enhancements in usability, diagnostic accuracy, and image segmentation are crucial to exploit the potential of this technology in optimizing patient care.

Digital Health Readiness: Making Digital Health Care More Inclusive.

This paper proposes an approach to assess digital health readiness in clinical settings to understand how prepared, experienced, and equipped individual people are to participate in digital health activities. Existing digital health literacy and telehealth prediction tools exist but do not assess technological aptitude for particular tasks or incorporate available electronic health record data to improve efficiency and efficacy. As such, we propose a multidomain digital health readiness assessment that incorporates a person's stated goals and motivations for use of digital health, a focused digital health literacy assessment, passively collected data from the electronic health record, and a focused aptitude assessment for critical skills needed to achieve a person's goals. This combination of elements should allow for easy integration into clinical workflows and make the assessment as actionable as possible for health care providers and in-clinic digital health navigators. Digital health readiness profiles could be used to match individuals with support interventions to promote the use of digital tools like telehealth, mobile apps, and remote monitoring, especially for those who are motivated but do not have adequate experience. Moreover, while effective and holistic digital health readiness assessments could contribute to increased use and greater equity in digital health engagement, they must also be designed with inclusivity in mind to avoid worsening known disparities in digital health care.

Enhancing the Functionalities of Personal Health Record Systems: Empirical Study Based on the HL7 Personal Health Record System Functional Model Release 1.

The increasing demand for personal health record (PHR) systems is driven by individuals' desire to actively manage their health care. However, the limited functionality of current PHR systems has affected users' willingness to adopt them, leading to lower-than-expected usage rates. The HL7 (Health Level Seven) PHR System Functional Model (PHR-S FM) was proposed to address this issue, outlining all possible functionalities in PHR systems. Although the PHR-S FM provides a comprehensive theoretical framework, its practical effectiveness and applicability have not been fully explored. This study aimed to design and develop a tethered PHR prototype in accordance with the guidelines of the PHR-S FM. It sought to explore the feasibility of applying the PHR-S FM in PHR systems by comparing the prototype with the results of previous research. The PHR-S FM profile was defined to meet broad clinical data management requirements based on previous research. We designed and developed a PHR prototype as a web application using the Fast Healthcare Interoperability Resources R4 (FHIR) and Logical Observation Identifiers Names and Codes (LOINC) coding system for interoperability and data consistency. We validated the prototype using the Synthea dataset, which provided realistic synthetic medical records. In addition, we compared the results produced by the prototype with those of previous studies to evaluate the feasibility and implementation of the PHR-S FM framework. The PHR prototype was developed based on the PHR-S FM profile. We verified its functionality by demonstrating its ability to synchronize data with the FHIR server, effectively managing and displaying various health data types. Validation using the Synthea dataset confirmed the prototype's accuracy, achieving 100% coverage across 1157 data items. A comparison with the findings of previous studies indicated the feasibility of implementing the PHR-S FM and highlighted areas for future research and improvements. The results of this study offer valuable insights into the potential for practical application and broad adoption of the PHR-S FM in real-world health care settings.

On the atout ticket learning problem for neural networks and its application in securing federated learning exchanges

Artificial Neural Networks (ANNs) have become the backbone of many real-world applications, including distributed applications relying on Federated Learning (FL). However, several vulnerabilities/attacks have emerged in recent years, affecting the benefits of using ANNs in FL, such as reconstruction attacks and membership inference attacks. These attacks can have severe impacts on both the societal and professional levels. For instance, inferring the presence of a patient’s private health record in a medical study or a clinic database violates the patient’s privacy and can have legal or ethical consequences. Therefore, protecting the data and model from malicious attacks in FL systems is important. This paper introduces the Atout Ticket Learning (ATL) problem. This new problem consists of identifying sensitive parameters (atout tickets) of a neural network model, which, if modified, will increase the model’s loss by at least a given threshold ϵ. First, we formulate ATL as an ℓ0-norm minimization problem, and we derive a lower bound on the number of atout tickets needed to achieve a model degradation of ϵ. Second, we design the Atout Ticket Protocol (ATP) as an effective solution for privacy-preserving in FL systems using atout tickets, along with the benefit of noise perturbations and secure aggregation techniques. Finally, we experiment ATP against FL reconstruction attacks using new selection strategies, namely Inverting Gradients, Deep Leakage, and Improved Deep Leakage. The results show that ATP is highly robust against these attacks.

Barriers and facilitators of the use of clinical informatics resources to facilitate pharmacogenomic implementation in resource-limited settings.

Understand perceived barriers to and facilitators of using clinical informatics applications for pharmacogenomic (PGx) implementation in resource-limited settings. We conducted a qualitative research study using a semi-structured interview guide informed by the Consolidated Framework for Implementation Research (CFIR). Interview questions assessed CFIR contextual determinants related to: electronic health record (EHR) infrastructure; clinical informatics personnel and resources; EHR integration of PGx test results; PGx clinical decision support (CDS) tools; institutional resources; and partner receptivity. Transcripts were coded and analyzed to identify themes. We interviewed 24 clinical informaticists and executive leaders working in rural or underserved health care settings in Montana (n = 15) and Colorado (n = 9) and identified three major themes: (1) EHR infrastructure limitations, (2) insufficient supporting resources, and (3) unique contextual considerations for resource-limited settings. EHR infrastructure limitations included limited agency related to EHR build and interoperability concerns. Theme 1 highlighted challenges associated with integrating structured data into the EHR and inadequate vendor support. Theme 2 included limited familiarity with PGx across the care team, cost concerns, and allocation of non-financial resources. Theme 3 highlighted perceptions about the clinical utility of PGx within rural and underrepresented populations. Potential facilitators, such as being able to act nimbly, were found to coexist among the reported barriers. Our results provide insight into the clinical informatics infrastructure in resource-limited settings and identify unique considerations for clinical informatics-facilitated PGx implementation. Future efforts in these settings should consider innovative partnerships and strategies to leverage facilitators and minimize barriers associated with integrating PGx CDS applications.

Association Between a Mother's Cervical Cancer Screening and Child's Human Papillomavirus (HPV) Vaccination Status.

To investigate the association between maternal cervical cancer (CC) screening status and child human papillomavirus (HPV) vaccination uptake. To understand if child sex or social deprivation index (SDI) modify this association. We used a national cohort of children linked to at least one parent using electronic health record (EHR) data from a network of community health centers across the United States. We used SDI scores and child sex as moderating variables. We performed the analysis (1) for the whole sample (with SDI and child sex added as covariates), (2) stratified by SDI quartile (with child sex added as a covariate), and (3) stratified by SDI quartile and child sex, to examine whether associations vary by SDI quartile and by child sex. N = 52,919 linked mother-child pairs. Mother's receipt of CC screening was positively associated with the linked child's odds of receiving HPV vaccination [adjusted odds ratio (AOR) 1.39, 95% confidence interval (CI) 1.32, 1.47]. Neither sex or SDI modified this association. There were no significant differences in odds of HPV vaccination in children between SDI quartiles or between male and female children. An effective way to improve rates of HPV vaccination among children and adolescents may be to target attention towards increasing CC screening rates among mothers. Further, focusing resources and efforts on CC screenings and care of both mothers and their children may be more worthwhile than isolated efforts targeting HPV vaccination for children and adolescents.

Development and validation of an instrument to evaluate the perspective of using the electronic health record in a hospital setting

BackgroundEvaluating healthcare information systems, such as the Electronic Health Records (EHR), is both challenging and essential, especially in resource-limited countries. This study aims to psychometrically develop and validate an instrument (questionnaire) to assess the factors influencing the successful adoption of the EHR system by healthcare professionals in Moroccan university hospitals.MethodsThe questionnaire validation process occurred in two main stages. Initially, data collected from a pilot sample of 164 participants underwent analysis using exploratory factor analysis (EFA) to evaluate the validity and reliability of the retained factor structure. Subsequently, the validity of the overall measurement model was confirmed using confirmatory factor analysis (CFA) in a sample of 368 healthcare professionals.ResultsThe structure of the modified HOT-fit model, comprising seven constructs (System Quality, Information Quality, Information technology Service Quality, User Satisfaction, Organization, Environment, and Clinical Performance), was confirmed through confirmatory factor analysis. Absolute, incremental, and parsimonious fit indices all indicated an appropriate level of acceptability, affirming the robustness of the measurement model. Additionally, the instrument demonstrated adequate reliability and convergent validity, with composite reliability values ranging from 0.75 to 0.89 and average variance extracted (AVE) values ranging from 0.51 to 0.63. Furthermore, the square roots of AVE values exceeded the correlations between different pairs of constructs, and the heterotrait-monotrait ratio of correlations (HTMT) was below 0.85, confirming suitable discriminant validity.ConclusionsThe resulting instrument, due to its rigorous development and validation process, can serve as a reliable and valid tool for assessing the success of information technologies in similar contexts.

Clinicians' use of Health Information Exchange technologies for medication reconciliation in the U.S. Department of Veterans Affairs: a qualitative analysis.

Medication reconciliation is essential for optimizing medication use. In part to promote effective medication reconciliation, the Department of Veterans Affairs (VA) invested substantial resources in health information exchange (HIE) technologies. The objectives of this qualitative study were to characterize VA clinicians' use of HIE tools for medication reconciliation in their clinical practice and to identify facilitators and barriers. We recruited inpatient and outpatient prescribers (physicians, nurse practitioners, physician assistants) and pharmacists at four geographically distinct VA medical centers for observations and interviews. Participants were observed as they interacted with HIE or medication reconciliation tools during routine work. Participants were interviewed about clinical decision-making pertaining to medication reconciliation and use of HIE tools, and about barriers and facilitators to use of the tools. Qualitative data were analyzed via inductive and deductive approaches using a priori codes. A total of 63 clinicians participated. Over half (58%) were female, and the mean duration of VA clinical experience was 7 (range 0-32) years. Underlying motivators for clinicians seeking data external to their VA medical center were having new patients, current patients receiving care from an external institution, and clinicians' concerns about possible medication discrepancies among institutions. Facilitators for using HIE software were clinicians' familiarity with the HIE software, clinicians' belief that medication information would be available within HIE, and their confidence in the ability to find HIE medication-related data of interest quickly. Six overarching barriers to HIE software use for medication coordination included visual clutter and information overload within the HIE display; challenges with HIE interface navigation; lack of integration between HIE and other electronic health record interfaces, necessitating multiple logins and application switching; concerns with the dependability of HIE medication information; unfamiliarity with HIE tools; and a lack of HIE data from non-VA facilities. This study is believed to be the first to qualitatively characterize clinicians' HIE use with respect to medication reconciliation. Results inform recommendations to optimize HIE use for medication management activities. We expect that healthcare organizations and software vendors will be able to apply the findings to develop more effective and usable HIE information displays.

Pilot study for the development of an automatically generated and wearable-based early warning system for the detection of deterioration of hospitalized patients of an acute care hospital.

Acute deteriorations of health status are common in hospitalized patients and are often preceded by changes in their vital signs. Events such as heart attacks, death or admission to the intensive care unit can be averted by early detection, therefore so-called Early Warning Scores (EWS) such as the National Early Warning Score 2 (NEWS2), including basic vital parameters such as heart rate, blood pressure, respiratory rate, temperature and level of consciousness, have been developed for a systematic approach. Although studies have shown that EWS have a positive impact on patient outcomes, they are often limited by issues such as calculation errors, time constraints, and a shortage of human resources. Therefore, development of tools for automatic calculation of EWS could help improve quality of EWS calculation and may improve patient outcomes. The aim of this study is to analyze the feasibility of wearable devices for the automatic calculation of NEWS2 compared to conventional calculation using vital signs measured by health care professionals. We conducted a prospective trial at a large tertiary hospital in Switzerland. Patients were given a wristband with a photoplethysmogram (PPG) sensor that continuously recorded their heart rate and respiratory rate for 3 consecutive days. Combined with data from the electronic health record (EHR), NEWS2-score was calculated and compared to NEWS2 score calculated from vital parameters in the EHR measured by medical staff. The main objective of our study was to assess the agreement between NEWS2 scores calculated using both methods. This analysis was conducted using Cohen's Kappa and Bland-Altman analysis. Secondary endpoints were compliance concerning the medical device, patient acceptance, data quality analysis and data availability and signal quality for all time stamps needed for accurate calculation. Of 210 patients enrolled in our study, NEWS2 was calculated in 904 cases, with 191 cases being directly compared to conventional measurements. Thirty-three of these measurements resulted in a NEWS2 ≥ 5, 158 in a NEWS2 < 5. Comparing all 191 measurements, accordance was substantial (K = 0.76) between conventional and automated NEWS2. No adverse effects due to the device were recorded. Patient acceptance was high. In conclusion, the study found strong agreement between automated and conventional NEWS2 calculations using wearable devices, with high patient acceptance despite some data quality challenges. To maximize the potential of continuous monitoring, further research into fully automated EWS calculations without relying on spot measurements is suggested, as this could provide a reliable alternative to traditional methods. January 26, 2023, NCT05699967.