Home environment factors associated with child BMI changes during COVID-19 pandemic.

BACKGROUND: The influence of home obesogenic environments, as assessed by the validated Family Nutrition and Physical Activity (FNPA) tool, and child obesity during the COVID pandemic were evaluated using electronic health records in this retrospective cohort study. METHODS: Historical data on BMI and the FNPA screening tool were obtained from annual well-child visits within the Geisinger Health System. The study examined youth ages 2-17 that had a BMI record and an FNPA assessment prior to the pandemic (BMI 3/1/19-2/29/20), 1 BMI record 3 months into the pandemic (6/1/20-12/31/20) and 1 BMI in the second year of the pandemic (1/1/21-12/31/21). Tertiles of obesity risk by FNPA score were examined. Mixed-effects linear regression was used to examine change in BMI slope (kg/m2 per month) pre-pandemic to pandemic using FNPA summary and subscales scores as predictors and adjusting for confounding factors. RESULTS: The analyses included 6,746 children (males: 51.7%, non-Hispanic white: 86.6%, overweight:14.8%, obesity:10.3%, severe obesity: 3.9%; mean(SD) age: 5.7(2.8) years). The rate of BMI change in BMI was greatest from early pandemic compared to pre-pandemic for children in lowest versus highest tertiles of FNPA summary score (0.079 vs. 0.044 kg/m2), FNPA-Eating (0.068 vs. 0.049 kg/m2), and FNPA-Activity (0.078 vs. 0.052 kg/m2). FNPA summary score was significantly associated with change in BMI from the pre-pandemic to early pandemic period (p = 0.014), but not associated with change in BMI during the later pandemic period. CONCLUSIONS: This study provides additional insight into the changes in the rate of BMI change observed among children and adolescents in the United States during the COVID-19 pandemic. The FNPA provides ample opportunity to continue our exploration of the negative impact of the COVID-19 pandemic on the longitudinal growth patterns among children and adolescents.

Abated crowding by fast-tracking the Throughput component of the ED for patients in no need of hospitalization with competency managed personnel.

BACKGROUND: Emergency department (ED) crowding is a major patient safety concern and has a negative impact on healthcare systems and healthcare providers. We hypothesized that it would be feasible to control crowding by employing a multifaceted approach consisting of systematically fast-tracking patients who are mostly not in need of a hospital stay as assessed by an initial nurse and treated by decision competent physicians. METHODS: Data from 120,901 patients registered in a secondary care ED from the 4tth quarter of 2021 to the 1st quarter of 2024 was drawn from the electronic health record's data warehouse using the SAP Web Intelligence tool and processed in the Python programming language. Crowding was compared before and after ED transformation from a uniform department into a high flow (α) and a low flow (ß) section with patient placement in gurneys/chairs or beds, respectively. Patients putatively not in need of hospitalization were identified by nurse, placed in in the α setting and assessed and treated by decision competent physicians. Incidence of crowding, number of patients admitted per day and readmittances within 72 h following ED admission before and after changes were determined. Values are number of patients, mean ± SEM and mean differences with 95% CIs. Statistical significance was ascertained using Student's two tailed t-test for unpaired values. RESULTS: Before and after ED changes crowding of 130% amounted to 123.8 h and 19.3 h in the latter. This is a difference of -104.6 ± 23.9 h with a 95% CI of -159.9 to -49.3, Δ% -84 (p = 0.002). There was the same amount of patients / day amounting to 135.8 and 133.5 patients / day Δ% = -1.7 patients 95% CI -6.3 to 1.6 (p = 0.21). There was no change in readmittances within 72 h before and after changes amounting to 9.0% versus 9.5%, Δ% = 0.5, 95%, CI -0.007 to 1.0 (p > 0.052). CONCLUSION: It appears feasible to abate crowding with unchanged patient admission and without an increase in readmittances by fast-track assessment and treatment of patients who are not in need of hospitalization.

Development of a text mining algorithm for identifying adverse drug reactions in electronic health records.

Objective: Adverse drug reactions (ADRs) are a significant healthcare concern. They are often documented as free text in electronic health records (EHRs), making them challenging to use in clinical decision support systems (CDSS). The study aimed to develop a text mining algorithm to identify ADRs in free text of Dutch EHRs. Materials and Methods: In Phase I, our previously developed CDSS algorithm was recoded and improved upon with the same relatively large dataset of 35 000 notes (Step A), using R to identify possible ADRs with Medical Dictionary for Regulatory Activities (MedDRA) terms and the related Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) (Step B). In Phase II, 6 existing text-mining R-scripts were used to detect and present unique ADRs, and positive predictive value (PPV) and sensitivity were observed. Results: In Phase IA, the recoded algorithm performed better than the previously developed CDSS algorithm, resulting in a PPV of 13% and a sensitivity of 93%. For The sensitivity for serious ADRs was 95%. The algorithm identified 58 additional possible ADRs. In Phase IB, the algorithm achieved a PPV of 10%, a sensitivity of 86%, and an F-measure of 0.18. In Phase II, four R-scripts enhanced the sensitivity and PPV of the algorithm, resulting in a PPV of 70%, a sensitivity of 73%, an F-measure of 0.71, and a 63% sensitivity for serious ADRs. Discussion and Conclusion: The recoded Dutch algorithm effectively identifies ADRs from free-text Dutch EHRs using R-scripts and MedDRA/SNOMED-CT. The study details its limitations, highlighting the algorithm's potential and significant improvements.

Bridging the Gap in Genomic Implementation: Identifying User Needs for Precision Nephrology.

Introduction: Genomic medicine holds transformative potential for personalized nephrology care; however, its clinical integration poses challenges. Automated clinical decision support (CDS) systems in the electronic health record (EHR) offer a promising solution but have shown limited impact. This study aims to glean practical insights into nephrologists' challenges using genomic resources, informing precision nephrology decision support tools. Methods: We conducted an anonymous electronic survey among US nephrologists from January 19, 2021 to May 19, 2021, guided by the Consolidated Framework for Implementation Research. It assessed practice characteristics, genomic resource utilization, attitudes, perceived knowledge, self-efficacy, and factors influencing genetic testing decisions. Survey links were primarily shared with National Kidney Foundation members. Results: We analyzed 319 surveys, with most respondents specializing in adult nephrology. Although respondents generally acknowledged the clinical use of genomic resources, varying levels of perceived knowledge and self-efficacy were evident regarding precision nephrology workflows. Barriers to genetic testing included cost/insurance coverage and limited genomics experience. Conclusion: The study illuminates specific hurdles nephrologists face using genomic resources. The findings are a valuable contribution to genomic implementation research, highlighting the significance of developing tailored interventions to support clinicians in using genomic resources effectively. These findings can guide the future development of CDS systems in the EHR. Addressing unmet informational and workflow support needs can enhance the integration of genomics into clinical practice, advancing personalized nephrology care and improving kidney disease outcomes. Further research should focus on interventions promoting seamless precision nephrology care integration.

Evaluating and Enhancing the Fitness-for-Purpose of Electronic Health Record Data: Qualitative Study on Current Practices and Pathway to an Automated Approach Within the Medical Informatics for Research and Care in University Medicine Consortium.

BACKGROUND: Leveraging electronic health record (EHR) data for clinical or research purposes heavily depends on data fitness. However, there is a lack of standardized frameworks to evaluate EHR data suitability, leading to inconsistent quality in data use projects (DUPs). This research focuses on the Medical Informatics for Research and Care in University Medicine (MIRACUM) Data Integration Centers (DICs) and examines empirical practices on assessing and automating the fitness-for-purpose of clinical data in German DIC settings. OBJECTIVE: The study aims (1) to capture and discuss how MIRACUM DICs evaluate and enhance the fitness-for-purpose of observational health care data and examine the alignment with existing recommendations and (2) to identify the requirements for designing and implementing a computer-assisted solution to evaluate EHR data fitness within MIRACUM DICs. METHODS: A qualitative approach was followed using an open-ended survey across DICs of 10 German university hospitals affiliated with MIRACUM. Data were analyzed using thematic analysis following an inductive qualitative method. RESULTS: All 10 MIRACUM DICs participated, with 17 participants revealing various approaches to assessing data fitness, including the 4-eyes principle and data consistency checks such as cross-system data value comparison. Common practices included a DUP-related feedback loop on data fitness and using self-designed dashboards for monitoring. Most experts had a computer science background and a master's degree, suggesting strong technological proficiency but potentially lacking clinical or statistical expertise. Nine key requirements for a computer-assisted solution were identified, including flexibility, understandability, extendibility, and practicability. Participants used heterogeneous data repositories for evaluating data quality criteria and practical strategies to communicate with research and clinical teams. CONCLUSIONS: The study identifies gaps between current practices in MIRACUM DICs and existing recommendations, offering insights into the complexities of assessing and reporting clinical data fitness. Additionally, a tripartite modular framework for fitness-for-purpose assessment was introduced to streamline the forthcoming implementation. It provides valuable input for developing and integrating an automated solution across multiple locations. This may include statistical comparisons to advanced machine learning algorithms for operationalizing frameworks such as the 3×3 data quality assessment framework. These findings provide foundational evidence for future design and implementation studies to enhance data quality assessments for specific DUPs in observational health care settings.

The reuse of electronic health records information models in the oncology domain: Studies with the bioframe framework.

OBJECTIVE: The reuse of Electronic Health Records (EHR) information models (e.g., templates and archetypes) may bring various benefits, including higher standardization, integration, interoperability, increased productivity in developing EHR systems, and unlock potential Artificial Intelligence applications built on top of medical records. The literature presents recent advances in standards for modeling EHR, in Knowledge Organization Systems (KOS) and EHR data reuse. However, methods, development processes, and frameworks to improve the reuse of EHR information models are still scarce. This study proposes a software engineering framework, named BioFrame, and analyzes how the reuse of EHR information models can be improved during the development of EHR systems. METHODS: EHR standards and KOS, including ontologies, identified from systematic reviews were considered in developing the BioFrame framework. We used the structure of the OpenEHR to model templates and archetypes, as well as its relationship to international KOS used in the oncology domain. Our framework was applied in the context of pediatric oncology. Three data entry forms concerning nutrition and one utilized during the first pediatric oncology consultations were analyzed to measure the reuse of information models. RESULTS: There was an increase in the adherence rate to international KOS of 18% to the original forms. There was an increase in the concepts reused in all 12 scenarios analyzed, with an average reuse of 6.55% in the original forms compared to 17.1% using BioFrame, resulting in significant differences. CONCLUSIONS: Our results point to higher reuse rates achieved due to an engineering process that provided greater adherence to EHR standards combined with semantic artifacts. This reveals the potential to develop new methods and frameworks aimed at EHR information model reuse. Additional research is needed to evaluate the impacts of the reuse of the EHR information model on interoperability, EHR data reuse, and data quality and assess the proposed framework in other health domains.

Impact of coordination mechanisms based on information and communication technologies on cross-level clinical coordination: A scoping review.

Background: Coordination mechanisms based on information and communication technologies (ICTs) are gaining attention, especially since the pandemic, due to their potential to improve communication between health professionals. However, their impact on cross-level clinical coordination remains unclear. The aim is to synthesize the evidence on the impact of ICT-based coordination mechanisms on clinical coordination between primary care and secondary care (SC) doctors and to identify knowledge gaps. Methods: A scoping review was conducted by searching for original articles in six electronic databases and a manual search, with no restrictions regarding time, area, or methodology. Titles and abstracts were screened. Full texts of the selected articles were reviewed and analysed to assess the impact of each mechanism, according to the cross-level clinical coordination conceptual framework. Results: Of the 6555 articles identified, 30 met the inclusion criteria. All had been conducted in high-income countries, most (n = 26) evaluated the impact of a single mechanism - asynchronous electronic consultations via electronic health records (EHR) - and were limited in terms of design and types and dimensions of cross-level clinical coordination analysed. The evaluation of electronic consultations showed positive impacts on the appropriateness of referrals and accessibility to SC, yet the qualitative studies also highlighted potential risks. Studies on other mechanisms were scarce (shared EHR, email consultations) or non-existent (videoconferencing, mobile applications). Conclusions: Evidence of the impact of ICT-based mechanisms on clinical coordination between levels is limited. Rigorous evaluations are needed to inform policies and strategies for improving coordination between healthcare levels, thus contributing to high-quality, efficient healthcare.

Designing an interoperable patient portal to augment an Advanced Nurse Practitioner service for Children with hydrocephalus.

Background: Children's Health Ireland (CHI), who govern and operate acute paediatric services for the greater Dublin area, are also the client for the new children's hospital project which will be Ireland's first fully digital hospital. Design, development and implementation of digital solutions has been prioritised by the National Strategy for Children's Nursing to transform and accelerate nurse-led services. Aim: The aim of this phase of a larger study was to explore the perspectives and opinions of key stakeholders on the requirements, benefits, and challenges for a bespoke patient portal, with a specific focus on the ANP-led Neurosurgical Service and children and young people with hydrocephalus. Methods: Interviews and focus groups were held online, and data were recorded and transcribed verbatim. Twenty-three participants across eight sites were interviewed including parents, healthcare professionals, experts and management/administrators. Data were analysed using Braun and Clarke's (2006) framework. Results: Four key findings and considerations were identified in relation to patient portals in general and their interoperability with Electronic Health Records, as well as a bespoke patient portal for children and young people with hydrocephalus. Conclusions: The availability of a patient portal for children and young people with hydrocephalus would be hugely advantageous to their parents, the ANP led nursing service, and healthcare professionals in both the neurosurgical service at CHI and at regional healthcare organisations as well as for administration, research, and reports. More timely access to health data as well as a consistent log of information and communications between patients and healthcare professionals, would be more efficient and effective than current practices.The augmented ANP-led Neurosurgical Nursing Service at CHI will act as a pilot project from which other nurse-led digital patient services can learn from. Study Registration: This study was conducted between September 2022 and June 2023. It was registered in Trinity College Dublin, Ireland. Twitter Abstract: A study exploring requirements, benefits, & challenges for an interoperable patient portal in an ANP led Service for children with hydrocephalus.

Enhancing Patient Understanding of Laboratory Test Results: Systematic Review of Presentation Formats and Their Impact on Perception, Decision, Action, and Memory.

BACKGROUND: Direct access of patients to their web-based patient portal, including laboratory test results, has become increasingly common. Numeric laboratory results can be challenging to interpret for patients, which may lead to anxiety, confusion, and unnecessary doctor consultations. Laboratory results can be presented in different formats, but there is limited evidence regarding how these presentation formats impact patients' processing of the information. OBJECTIVE: This study aims to synthesize the evidence on effective formats for presenting numeric laboratory test results with a focus on outcomes related to patients' information processing, including affective perception, perceived magnitude, cognitive perception, perception of communication, decision, action, and memory. METHODS: The search was conducted in 3 databases (PubMed, Web of Science, and Embase) from inception until May 31, 2023. We included quantitative, qualitative, and mixed methods articles describing or comparing formats for presenting diagnostic laboratory test results to patients. Two reviewers independently extracted and synthesized the characteristics of the articles and presentation formats used. The quality of the included articles was assessed by 2 independent reviewers using the Mixed Methods Appraisal Tool. RESULTS: A total of 18 studies were included, which were heterogeneous in terms of study design and primary outcomes used. The quality of the articles ranged from poor to excellent. Most studies (n=16, 89%) used mock test results. The most frequently used presentation formats were numerical values with reference ranges (n=12), horizontal line bars with colored blocks (n=12), or a combination of horizontal line bars with numerical values (n=8). All studies examined perception as an outcome, while action and memory were studied in 1 and 3 articles, respectively. In general, participants' satisfaction and usability were the highest when test results were presented using horizontal line bars with colored blocks. Adding reference ranges or personalized information (eg, goal ranges) further increased participants' perception. Additionally, horizontal line bars significantly decreased participants' tendency to search for information or to contact their physician, compared with numerical values with reference ranges. CONCLUSIONS: In this review, we synthesized available evidence on effective presentation formats for laboratory test results. The use of horizontal line bars with reference ranges or personalized goal ranges increased participants' cognitive perception and perception of communication while decreasing participants' tendency to contact their physicians. Action and memory were less frequently studied, so no conclusion could be drawn about a single preferred format regarding these outcomes. Therefore, the use of horizontal line bars with reference ranges or personalized goal ranges is recommended to enhance patients' information processing of laboratory test results. Further research should focus on real-life settings and diverse presentation formats in combination with outcomes related to patients' information processing.

Assessing disparities through missing race and ethnicity data: results from a juvenile arthritis registry.

Introduction: Ensuring high-quality race and ethnicity data within the electronic health record (EHR) and across linked systems, such as patient registries, is necessary to achieving the goal of inclusion of racial and ethnic minorities in scientific research and detecting disparities associated with race and ethnicity. The project goal was to improve race and ethnicity data completion within the Pediatric Rheumatology Care Outcomes Improvement Network and assess impact of improved data completion on conclusions drawn from the registry. Methods: This is a mixed-methods quality improvement study that consisted of five parts, as follows: (1) Identifying baseline missing race and ethnicity data, (2) Surveying current collection and entry, (3) Completing data through audit and feedback cycles, (4) Assessing the impact on outcome measures, and (5) Conducting participant interviews and thematic analysis. Results: Across six participating centers, 29% of the patients were missing data on race and 31% were missing data on ethnicity. Of patients missing data, most patients were missing both race and ethnicity. Rates of missingness varied by data entry method (electronic vs. manual). Recovered data had a higher percentage of patients with Other race or Hispanic/Latino ethnicity compared with patients with non-missing race and ethnicity data at baseline. Black patients had a significantly higher odds ratio of having a clinical juvenile arthritis disease activity score (cJADAS10) of ≥5 at first follow-up compared with White patients. There was no significant change in odds ratio of cJADAS10 ≥5 for race and ethnicity after data completion. Patients missing race and ethnicity were more likely to be missing cJADAS values, which may affect the ability to detect changes in odds ratio of cJADAS ≥5 after completion. Conclusions: About one-third of the patients in a pediatric rheumatology registry were missing race and ethnicity data. After three audit and feedback cycles, centers decreased missing data by 94%, primarily via data recovery from the EHR. In this sample, completion of missing data did not change the findings related to differential outcomes by race. Recovered data were not uniformly distributed compared with those with non-missing race and ethnicity data at baseline, suggesting that differences in outcomes after completing race and ethnicity data may be seen with larger sample sizes.

Self-attention with temporal prior: can we learn more from the arrow of time?

Many diverse phenomena in nature often inherently encode both short- and long-term temporal dependencies, which especially result from the direction of the flow of time. In this respect, we discovered experimental evidence suggesting that interrelations of these events are higher for closer time stamps. However, to be able for attention-based models to learn these regularities in short-term dependencies, it requires large amounts of data, which are often infeasible. This is because, while they are good at learning piece-wise temporal dependencies, attention-based models lack structures that encode biases in time series. As a resolution, we propose a simple and efficient method that enables attention layers to better encode the short-term temporal bias of these data sets by applying learnable, adaptive kernels directly to the attention matrices. We chose various prediction tasks for the experiments using Electronic Health Records (EHR) data sets since they are great examples with underlying long- and short-term temporal dependencies. Our experiments show exceptional classification results compared to best-performing models on most tasks and data sets.

Understanding the predictors of health professionals' intention to use electronic health record system: extend and apply UTAUT3 model.

BACKGROUND: The implementation of Electronic Health Record (EHR) systems is a critical challenge, particularly in low-income countries, where behavioral intention plays a crucial role. To address this issue, we conducted a study to extend and apply the Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) model in predicting health professionals' behavioral intention to use EHR systems. METHODS: A quantitative research approach was employed among 423 health professionals in Southwest Ethiopia. We assessed the validity of the proposed model through measurement and structural model statistics. Analysis was done using SPSS AMOS version 23. Hypotheses were tested using structural equation modeling (SEM) analysis, and mediation and moderation effects were evaluated. The associations between exogenous and endogenous variables were examined using standardized regression coefficients (ß), 95% confidence intervals, and p-values, with a significance level of p-value < 0.05. RESULTS: The proposed model outperformed previous UTAUT models, explaining 84.5% (squared multiple correlations (R2) = 0.845) of the variance in behavioral intention to use EHR systems. Personal innovativeness (ß = 0.215, p-value < 0.018), performance expectancy (ß = 0.245, p-value < 0.001), and attitude (ß = 0.611, p-value < 0.001) showed significant associations to use EHR systems. Mediation analysis revealed that performance expectancy, hedonic motivation, and technology anxiety had significant indirect effects on behavioral intention. Furthermore, moderation analysis indicated that gender moderated the association between social influence, personal innovativeness, and behavioral intention. CONCLUSION: The extended UTAUT3 model accurately predicts health professionals' intention to use EHR systems and provides a valuable framework for understanding technology acceptance in healthcare. We recommend that digital health implementers and concerned bodies consider the comprehensive range of direct, indirect, and moderating effects. By addressing personal innovativeness, performance expectancy, attitude, hedonic motivation, technology anxiety, and the gender-specific impact of social influence, interventions can effectively enhance behavioral intention toward EHR systems. It is crucial to design gender-specific interventions that address the differences in social influence and personal innovativeness between males and females.

An Integrated Pipeline for Phenotypic Characterization, Clustering and Visualization of Patient Cohorts in a Rare Disease-Oriented Clinical Data Warehouse.

Rare diseases pose significant challenges due to their heterogeneity and lack of knowledge. This study develops a comprehensive pipeline interoperable with a document-oriented clinical data warehouse, integrating cohort characterization, patient clustering and interpretation. Leveraging NLP, semantic similarity, machine learning and visualization, the pipeline enables the identification of prevalent phenotype patterns and patient stratification. To enhance interpretability, discriminant phenotypes characterizing each cluster are provided. Users can visually test hypotheses by marking patients exhibiting specific keywords in the EHR like genes, drugs and procedures. Implemented through a web interface, the pipeline enables clinicians to navigate through different modules, discover intricate patterns and generate interpretable insights that may advance rare diseases understanding, guide decision-making, and ultimately improve patient outcomes.

Federated Electronic Health Records Using a Blockchain.

The Valkyrie project aims to develop a demonstration Federated Electronic Health Record for the use of mental health practitioners in Norway. Information for the record is drawn from existing records in Source Systems operating across primary and secondary care. Recording of information in any such system, in response to a healthcare event, triggers the generation of an Encrypted Token, containing summary metadata about the event, clinical coding indicating its clinical context and a locator that can be used to retrieve the full record of the event from the original Source System. The Valkyrie architecture consists of a number of interlinked Security Domains, each with its own private and public keys, through which the Encrypted Tokens are passed. Each Security Domain performs a specific function on a set of Tokens and only has access to the information within each Token that is necessary to perform that function. This paper describes the structure of the Encrypted Token, the function of each Security Domain and the orchestration of the flow of Tokens through the Domains. Together this allows a user to run a Valkyrie Session, in which they can view the content of a patient record, where all content has been drawn in real-time from heterogenous Source Systems (ISO13606- and openEHR-based) and is destroyed when the session terminates.

HCE2RNFC: An Efficient Methodology for Reusing the EHR in the Spanish National Hip Fracture Registry.

Hip fracture is a condition associated with ageing and frailty, with an associated prevalence of 7 per 10000 population in Spain. Evidence suggests that factors in the healthcare process can influence clinical outcomes, so the creation of a national registry is an opportunity to monitor and improve this process. In this regards, Electronic Health Record (EHR) can provide a large amount of data, that can be used to populate the Spanish National Hip Fracture Registry (RNFC, by its acronym in Spanish). However, this reuse of the EHR requires a prior effort in modelling and standardization to build the extraction, transformation, and loading (ETL) processes in a flexible, transparent, and scalable manner. In this work, a robust EHR reuse methodology is implemented to obtain EHR-derived data for the RNFC. The main result of this work was the design and implementation of an EHR data reuse methodology, which was able to load 1279 hip fracture cases and almost 68% of the required concepts from the RNFC.

Optimizing Integration with the Italian EHR: The Use of LOINC Codes.

According to the regulation "Decreto del Presidente del Consiglio dei Ministri" (DPCM) of September 29, 2015, n.178, the Logical Observation Identifiers Names and Codes (LOINC) system is included among the coding systems adopted in the Italian Electronic Health Record (EHR). As part of the Digital Health Solutions in Community Medicine (DHEAL-COM) project, one key goal is to categorize parameters using international classification systems. This enables the identification of appropriate Information and Communication Technology (ICT) solutions tailored to support people's health needs. Our objective is to incorporate LOINC codes for parameter categorization, thus anticipating the future use of EHR.

Physicians' Experiences of EHR Technical Quality: Results from Four Large Cross-Sectional Surveys in 2010-2021.

Unexpected downtime and long response times of electronic health record (EHR) systems not only impact user satisfaction and clinicians' work efficiency but also bring about potential harm for patients. Despite improvements in the performance of EHR systems' architecture, hardware, and networks, technical challenges continue to cause problems. We explored the end-user experiences of EHR technical functionality and quality from four large national cross-sectional surveys conducted among Finnish physicians in 2010-21. The results were analyzed by healthcare sector/specialty groups. In most groups, the experiences of stability and reaction speed became worse in 2010-17, which is readily explained by the implementation of the national patient data repository services, but improvements were seen in 2021, suggesting that EHR vendors have solved at least some of the slowness problems. The proportion of physicians reporting having experienced faulty system function with potential or actualized harm for the patient had decreased in operative and medical specialties and in the private sector but remained stable in other groups. Our findings underline the importance of continuing to develop technical qualities - including the implementations of national integrations.

Optimizing the Transition from Written Prescriptions into E-Prescriptions in Germany.

The study will use a mixed-method approach, the qualitative research method will be used through conducting interviews to explore the opinions of the stakeholders while the quantitative method will be used through conducting surveys. Results collected from both approaches were analyzed and recommendations for various stakeholders such as the German Ministry of Health with the cooperation of the German government, Software developers, Gematik, Insurance companies, Physicians and pharmacists, and Patients for optimizing the transition phase were derived.

Insights from the Implementation of Open Notes in Sweden.

The implementation of Open Notes in Sweden, granting patients access to their clinical records, has been a complex and nuanced endeavor, marked by regional variations in strategy and challenges arising from the diverging needs of healthcare providers and patients. This paper presents an interview study with managers about the implementation process in five of the 21 regions in Sweden. The aim of this study is to explore the experiences and strategies of these managers in navigating the implementation challenges. The study sheds light on the prevalent theme of uncertainty throughout the implementation journey and the strategies used to balance conflicting perspectives. The findings contribute to our understanding of Open Notes implementation and offer policymakers and healthcare organizations insights about enhancing the implementation process to optimize patient care.

Strategies to Address Statin Medication Intolerance Among Patients at Risk of Cardiovascular Disease Identified Through Electronic Health Records: A Literature Review and Pooled Analysis.

Statins are a group of medications that lower lipid and are used for primary and secondary prevention of cardiovascular diseases (CVD). Patients can either be partially (15%) or completely (5%) intolerant to statins. Symptoms of statin intolerance can include muscle aches (myalgia), weakness, cramps, myopathy, diabetes mellitus, and elevated creatine kinase levels. Decreasing statin intolerance also improves statin adherence, which in turn results in lower number of CVD events among patients. Studies on statin intolerance is often embedded within studies of statin adherence. However, relevant data can be obtained from digital health systems. This preliminary literature review looks at studies from the past 10 years to identify and determine the effectiveness of strategies to address statin intolerance. The NLA definition for statin intolerance was used in this review. The initial search results on EMBASE, PubMed, SCOPUS, and CINAHL showed 91 articles and applying the inclusion and exclusion criteria, four articles were used in this review and pooled analysis. The study patients were identified through electronic health records. The pooled analysis was done using the Metafor package in R, applying a random-effect model to estimate pooled effect size. The findings suggest that using fixed dose combination therapy and switching from a lipophilic statin to a hydrophilic statin, while correcting metabolic abnormalities, or initiating evolocumab alongside statin can address statin intolerance. The overall relative risk (RR) was 0.40 (95% CI, 0.09 to 1.70) with I2 90%, and the overall odds ratio (OR) was 0.11 (95% CI, 0.01 to 1.59) with I2 94%, suggesting that the interventions work well in addressing statin intolerance. Since statin intolerance is has a vast range of effects, further research works may be done on exploring the possibility of using digital health systems to identify and provide targeted interventions to patients.