Electronic Medical Record System Research Articles

Optimization of Outpatient Waiting Times to Improve the Achievements of National Quality Indicators at TNI AD 05.08.04 Hospital Lawang

The waiting time for outpatient services in a hospital is one of the important factors determining patient satisfaction with the hospital, so it is hoped that patients will not wait too long while in the hospital. This study aimed to optimize outpatient waiting times so that it can increase the achievement of national quality indicators at TNI AD 05.08.04 Hospital, Lawang. This study used fishbone diagrams, USG (Urgency, Seriousness, Growth), and SWOT Analysis (Strength, Weakness, Opportunity, Treats) to formulate problems and find solutions. The results of this study showed that priority problems in waiting time include: standard operating procedure (SOP) for outpatient service flow are still not available, the electronic medical record system is still often slow, and evaluation of national quality indicators is still not carried out routinely. Furthermore, the proposed strategy offered is the creation of SOP regarding the flow of outpatient services and routine outreach regarding the use of electronic medical records. With the implementation of these two strategies, it is hoped that they will be able to speed up waiting times for outpatient services, thus improving the achievement of national quality indicators.

Early diagnostic and prognosis prediction of circ_0054633 for acute lung injury/acute respiratory distress syndrome in children with severe pneumonia

To explore the value of circ_0054633 in early diagnosis and prognosis prediction of acute lung injury/acute respiratory distress syndrome (ALI/ARDS) in children with severe pneumonia. A retrospective case-control study was conducted on children with diagnosed severe pneumonia admitted to Tianjin Children's Hospital from July 1, 2022, to February 29, 2024. The clinical data was collected by electronic medical record system and clinical follow-up, including gender, age, lung injury prediction score (LIPS), pediatric critical illness score (PCIS), serum circ_0054633, interleukin-6 (IL-6), the indicators of the arterial blood-gas analysis, oxygenation index (PaO2/FiO2) within 24 hours of admission and the survival status of 28 days. According to whether ALI/ARDS occurred, they were divided into the ALI/ARDS group and the non-ALI/ARDS group. The differences of clinical data between the two groups were compared, and multivariate Logistic regression was used to analyze the risk factors for ALI/ARDS in children with severe pneumonia. The receiver operator characteristic curve (ROC curve) will be used to explore the early diagnostic value of ALI/ARDS in children with severe pneumonia. The patients of ALI/ARDS were divided into mild group, moderate group and severe group according to the level of PaO2/FiO2. The levels of serum circ_0054633 and IL-6 in various severity ALI/ARDS were compared. The differences of serum circ_0054633, IL-6 levels, PCIS score and LIPS score were compared between the two groups of ALI/ARDS patients according to different prognoses in 28 days, as well as the correlation between various risk factors and circ_0054633. A total 74 children with severe pneumonia were included, with 34 cases in the ALI/ARDS group and 40 cases in the non-ALI/ARDS group. In ALI/ARDS group, there were 9 cases in the mild group, 15 cases in the moderate group and 10 cases in the severe group; while 12 cases died and 22 cases survived after 28 days. The serum circ_0054633, IL-6 level and LIPS score were higher in the ALI/ARDS group than the non-ALI/ARDS group, while the PCIS score was lower, and the two groups had significant difference. Multivariate Logistic regression analysis showed that circ_0054633 was independent predictors of ALI/ARDS in children with severe pneumonia [odds ratio (OR) = 3.853, 95% confidence interval (95%CI) was 1.912-7.805, P = 0.017]. ROC curve analysis showed that the cut-off values for circ_0054633 in the diagnosis of ALI/ARDS were 3.955, sensitivity was 79.4%, specificity was 92.5%, area under the ROC curve (AUC) was 0.892. The serum circ_0054633 and IL-6 levels were higher in the children who died in 28 days than the children who were survived, while the PCIS score was lower, and the two groups had significant difference. Spearman correlation analysis showed that the level of circ_0054633 in children with ALI/ARDS was positively correlated with 28-day mortality and IL-6 (r value was 0.675, 0.763, respectively, all P < 0.001), but negatively correlated with PCIS score (r = -0.626, P < 0.001), while no significant correlation with LIPS score (r = 0.389, P = 0.023). The level of serum circ_0054633 has a better value in early diagnosis and prognosis prediction of ALI/ARDS caused in children with severe pneumonia.

Outcomes of Ticagrelor Versus High-dose Clopidogrel in CYP2C19 Intermediate Metabolizer Undergoing Percutaneous Coronary Intervention for Acute Coronary Syndromes.

Guidelines on antiplatelet recommendation for CYP2C19 intermediate metabolizer (IM) havenotcometoanagreement. This study aimed to evaluate the clinical benefit of ticagrelor when compared with high-dose clopidogrel in CYP2C19 IM after percutaneous coronary intervention for acute coronary syndromes. Patients were enrolled according to CYP2C19 genotype and individual antiplatelet therapy. Patient characteristics and clinical outcomes were collected through electronic medical record system. The primary outcome was major adverse cardiac and cerebrovascular event (MACCE), namely a composite of death from cardiovascular causes, myocardial infarction, stroke, and stent thrombosis within 12 months. The secondary outcome was Bleeding Academic Research Consortium scale bleeding events within 12 months. The Cox proportional hazards regression model was performed, with inverse probability treatment weighting (IPTW) adjusting for potential confounders. A total of 532 CYP2C19 IM were enrolled in this retrospective single-center study. No statistically significant difference in incidence rate of MACCE was found between patients receiving ticagrelor versus clopidogrel (7.01 vs. 9.52 per 100 patient-years; IPTW-adjusted hazard ratio 0.71; 95% confidence interval: 0.32-1.58; adjusted log-rank P = 0.396), but the incidence rate of Bleeding Academic Research Consortium type 2, 3, or 5 bleeding events was statistically higher in the loss of function-ticagrelor group than in the loss of function-clopidogrel group (13.53 vs. 6.16 per 100 patient-years; IPTW-adjusted hazard ratio: 2.29; 95% confidence interval: 1.10-4.78; adjusted log-rank P = 0.027). Ticagrelor treatment in CYP2C19 IM resulted in a statistically higher risk of bleeding compared with high-dose clopidogrel, whereas a clear association between treatments and MACCE warrants further investigations.

Abstract P330: Next-Gen Hypertension Control: Integrating Clinical Pharmacists And Cutting-Edge EPIC Electronic Medical Record For Quality And Result Driven Approaches at Federally Qualified Health Centers

Hypertension management in Federally Qualified Health Centers (FQHCs) requires innovative and comprehensive strategies beyond traditional methods. This study explores a collaborative approach by integrating clinical pharmacists into the healthcare team and utilizing the EPIC Electronic Medical Record (EMR) system. The model addresses medical and non-medical health determinants, offering comprehensive treatment for underserved communities regardless of their ability to pay. We hypothesized that integrating clinical pharmacists would improve and sustain blood pressure control, resulting in more patients achieving their target health outcomes. As part of multidisciplinary teams, clinical pharmacists identify, track, and analyze patient data, manage medication therapies under collaborative practice agreements, and coordinate with other healthcare providers to ensure continuous care. By leveraging EPIC EMR’s data management and patient monitoring capabilities, clinical pharmacists use real-time data to tailor medication regimens, ensure timely interventions, and conduct follow-ups every 2 to 4 weeks via telemedicine or in-clinic visits until patients reach their goals. This approach enhances patient engagement and medication adherence, which is crucial for adequate blood pressure control and cost management. It also supports personalized care addressing medical needs, lifestyle, and socioeconomic factors affecting patient health. The study, initiated in January 2024, involves adult patients with hypertension at one of the largest FQHC in Houston, TX. Key performance indicators include the percentage of patients achieving target blood pressure levels, medication adherence rates, and the frequency of follow-up visits. Preliminary data from quarter 1, 2024, shows that out of 327 patients, 58% have had at least 2 consultations with a clinical pharmacist. Out of those patients, 46% reached blood pressure control below 140/90 mmHg, while 27% showed improvement toward their goal. This quality and result-driven approach elevates hypertension management standards, reduces health disparities, and enhances healthcare delivery within FQHCs. Clinical pharmacists have proven to be indispensable members of the healthcare team. This session aims to provide practical insights and strategies for healthcare professionals to implement similar models, paving the way for the future of hypertension care.

Bibliometric Analysis of Factors Affecting Performance and Completeness of Electronic Medical Records (EMR) in Primary Health Services

ABSTRACT Electronic Medical Records (EMR) completeness and accuracy are fundamental to effective patient care, clinical decision-making, and overall healthcare management. In recent years, there has been increasing attention to improving EMR documentation by healthcare professionals to improve data quality and patient care outcomes. This bibliometric study aimed to explore the trends, research focus, and gaps in the literature regarding EMR completeness from 2019 to 2024. The study used Publish or Perish software to collect data from Google Scholar with specific keywords such as Performance, Factors, Electronic Medical Record (EMR), EMR Completeness, Primary Healthcare, Filling, Documentation, and Medical Record Accuracy. The analysis included the 30 highest ranked journals. In addition, VOS Viewer was used for network visualization, overlay, and density to analyze thematic linkages and identify potential research gaps. Bibliometric analysis showed that Indonesia, the United States, and Ethiopia were the main contributors in EMR-related publications. Frequent themes such as data completeness, quality, and accuracy, emphasize their crucial role in the EMR research field. These findings emphasize the importance of continuously improving EMR data completeness and accuracy, which are critical for reliable clinical decision making and effective healthcare delivery. Future research should focus on developing methodologies to improve data quality and integration of EMR systems with other health information systems. In addition, exploration of policy and regulatory implications related to EMR completeness may provide valuable insights for healthcare practice. Keywords: EMR Completeness, Data Quality, Bibliometric Analysis, Health Documentation, VOS Viewer.

Optimizing Coagulation Profile E-Reporting: A Design Thinking Perspective on Healthcare and Technological Integration

The coagulation profile report is crucial for assessing blood clots and diagnosing various bleeding disorders. Key metrics in these reports include the international normalized ratio (INR), activated partial thromboplastin time (APTT), platelet count, and fibrinogen levels. Traditionally, these reports have been delivered through paper-based methods, which often face significant challenges such as human errors, delays in distribution, and limited accessibility. To address these issues, this preliminary investigation explores integrating technology into the reporting process for coagulation profiles. By leveraging a design-thinking approach, the study aims to understand the needs and preferences of stakeholders and users. This approach includes creating personas to represent different user types, mapping their experiences through empathy and journey maps, and generating and testing ideas through ideation and prototyping. The core objective of the study is to develop a mobile application that simplifies and enhances the reporting process of coagulation profiles. This application is designed to integrate seamlessly with Electronic Medical Record (EMR) systems, providing real-time notifications to healthcare providers when laboratory results are available. The proposed solution aims to improve the timeliness and accuracy of reporting, facilitating better patient care and more efficient workflows. The paper details the components of this solution, including the prototype design and the validation procedures used to ensure its effectiveness. The study seeks to revolutionize how coagulation profiles are documented and communicated in healthcare by adopting a digital reporting system.

Establishment and Verification of a Risk Prediction Model for Chronic Rhinosinusitis.

Objective: Factors influencing chronic rhinosinusitis (CRS) are usually studied in terms of genetics and environment; however, clinical indicators have not been reported. This case-control study was conducted in Ningbo, China, to explore new independent risk factors for CRS. Methods: A total of 695 participants, including 440 healthy controls and 255 patients with CRS, were included in this study. Clinical data were retrieved from questionnaires and electronic medical record systems of hospitals. Independent risk factors were screened using logistic regression and 10-fold cross-validation combined with the least absolute shrinkage and selection operator. A CRS risk prediction model was established using logistic regression, and nomograms were visualized. The model was validated and evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results: Ten independent risk factors, including alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, creatinine, triglyceride, total cholesterol, red blood cell count, hemoglobin, lymphocyte percentage, and monocyte percentage were screened. ROC analysis showed that the area under the curve of the training set was 0.890, indicating that the predictive model had excellent discriminant ability. The calibration curves showed that the fitting curves of the training set were close to the reference curves, indicating that the model had a good fit. The DCA showed that the threshold probability range of the training set was 1% to 89%. Conclusions: Independent risk factors for CRS were screened, and a prediction model was constructed, which is of significance for the prevention, control, and treatment of the disease.

Gender Reassignment and the Role of the Laboratory in Monitoring Gender-Affirming Hormone Therapy.

Transgender people experience distress due to gender incongruence (i.e., a discrepancy between their gender identity and sex assigned at birth). Gender-affirming hormone treatment (GAHT) is a part of gender reassignment treatment. The therapeutic goals of the treatment are to develop the physical characteristics of the affirmed gender as far as possible. Guidelines have been developed for GAHT, which recommend dosage as well as different formulations of oestrogen and testosterone for treatment. Questions arise about the metabolic side effects of hormone treatment. Establishing reference ranges for common analytes in transgender individuals remains a task for laboratory medicine. It has been suggested once GAHT is commenced, the reference ranges for affirmed gender are reported for red blood cells, haemoglobin and haematocrit. For transgender assigned-female-at-birth (AFAB) people, testosterone concentrations are recommended to be within the reference interval established for cisgender men and for transgender assigned-male-at-birth (AMAB) people, estradiol concentrations are within the reference range for cisgender women. Sex-specific reference ranges are available for certain laboratory tests, and these may be organ (e.g., heart)-specific. Transgender-specific reference ranges may be a requirement for such tests. Laboratories may need to make decisions on how to report other tests in the transgender population, e.g., eGFR. Interpretation of further tests (e.g., reproductive hormones) can be individualized depending on clinical information. Electronic medical record systems require fields for gender identity/biological sex at birth so that laboratory results can be flagged appropriately. In this review, we aim to summarise the current position of the role of the laboratory in the clinical care of the transgender individual. Prior to the review, we will summarise the genetics of sex determination, the aetiology of gender incongruence, and the recommendations for GAHT and monitoring for the transgender population.

Automated data collection tool for real-world cohort studies of chronic hepatitis B: Leveraging OCR and NLP technologies for improved efficiency

BackgroundCollecting and standardizing clinical research data is a very tedious task. This study is to develop an intelligent data collection tool, named CHB-EDC, for real-world cohort studies of chronic hepatitis B (CHB), which can assist in standardized and efficient data collection. MethodsCHB_EDC is capable of automatically processing various formats of data, including raw data in image format, using internationally recognized data standards, OCR, and NLP models. It can automatically populate the data into eCRFs designed in the REDCap system, supporting the integration of patient data from electronic medical record systems through commonly used web application interfaces. This tool enables intelligent extraction and aggregation of data, as well as secure and anonymous data sharing. ResultsFor non-electronic data collection, the average accuracy of manual collection was 98.65 %, with an average time of 63.64 min to collect information for one patient. The average accuracy CHB-EDC was 98.66 %, with an average time of 3.57 min to collect information for one patient. In the same data collection task, CHB-EDC achieved a comparable average accuracy to manual collection. However, in terms of time, CHB-EDC significantly outperformed manual collection (p < 0.05). Our research has significantly reduced the required collection time and lowered the cost of data collection while ensuring accuracy. ConclusionThe tool has significantly improved the efficiency of data collection while ensuring accuracy, enabling standardized collection of real-world data.

Establishment of predictive models and determinants of preoperative gastric retention in endoscopic retrograde cholangiopancreatography.

Study on influencing factors of gastric retention before endoscopic retrograde cholangiopancreatography (ERCP) background: With the wide application of ERCP, the risk of preoperative gastric retention affects the smooth progress of the operation. The study found that female, biliary and pancreatic malignant tumor, digestive tract obstruction and other factors are closely related to gastric retention, so the establishment of predictive model is very important to reduce the risk of operation. To analyze the factors influencing preoperative gastric retention in ERCP and establish a predictive model. A retrospective analysis was conducted on 190 patients admitted to our hospital for ERCP preparation between January 2020 and February 2024. Patient baseline clinical data were collected using an electronic medical record system. Patients were randomly matched in a 1:4 ratio with data from 190 patients during the same period to establish a validation group (n = 38) and a modeling group (n = 152). Patients in the modeling group were divided into the gastric retention group (n = 52) and non-gastric retention group (n = 100) based on whether gastric retention occurred preoperatively. General data of patients in the validation group and modeling group were compared. Univariate and multivariate logistic regression analyses were performed to identify factors influencing preoperative gastric retention in ERCP patients. A predictive model for preoperative gastric retention in ERCP patients was constructed, and calibration curves were used for validation. The receiver operating characteristic (ROC) curve was analyzed to evaluate the predictive value of the model. We found no statistically significant difference in general data between the validation group and modeling group (P > 0.05). The comparison of age, body mass index, hypertension, and diabetes between the two groups showed no statistically significant difference (P > 0.05). However, we noted statistically significant differences in gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction between the two groups (P < 0.05). Multivariate logistic regression analysis showed that gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction were independent factors influencing preoperative gastric retention in ERCP patients (P < 0.05). The results of logistic regression analysis revealed that gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction were included in the predictive model for preoperative gastric retention in ERCP patients. The calibration curves in the training set and validation set showed a slope close to 1, indicating good consistency between the predicted risk and actual risk. The ROC analysis results showed that the area under the curve (AUC) of the predictive model for preoperative gastric retention in ERCP patients in the training set was 0.901 with a standard error of 0.023 (95%CI: 0.8264-0.9567), and the optimal cutoff value was 0.71, with a sensitivity of 87.5 and specificity of 84.2. In the validation set, the AUC of the predictive model was 0.842 with a standard error of 0.013 (95%CI: 0.8061-0.9216), and the optimal cutoff value was 0.56, with a sensitivity of 56.2 and specificity of 100.0. Gender, primary disease, jaundice, opioid use, and gastrointestinal obstruction are factors influencing preoperative gastric retention in ERCP patients. A predictive model established based on these factors has high predictive value.

Prediction model establishment and validation for enteral nutrition aspiration during hospitalization in patients with acute pancreatitis.

Acute pancreatitis (AP) is a disease caused by abnormal activation of pancreatic enzymes and can lead to self-digestion of pancreatic tissues and dysfunction of other organs. Enteral nutrition plays a vital role in the treatment of AP because it can meet the nutritional needs of patients, promote the recovery of intestinal function, and maintain the barrier and immune functions of the intestine. However, the risk of aspiration during enteral nutrition is high; once aspiration occurs, it may cause serious complications, such as aspiration pneumonia, and suffocation, posing a threat to the patient's life. This study aims to establish and validate a prediction model for enteral nutrition aspiration during hospitalization in patients with AP. To establish and validate a predictive model for enteral nutrition aspiration during hospitalization in patients with AP. A retrospective review was conducted on 200 patients with AP admitted to Chengdu Shangjin Nanfu Hospital, West China Hospital of Sichuan University from January 2020 to February 2024. Clinical data were collected from the electronic medical record system. Patients were randomly divided into a validation group (n = 40) and a modeling group (n = 160) in a 1:4 ratio, matched with 200 patients from the same time period. The modeling group was further categorized into an aspiration group (n = 25) and a non-aspiration group (n = 175) based on the occurrence of enteral nutrition aspiration during hospitalization. Univariate and multivariate logistic regression analyses were performed to identify factors influencing enteral nutrition aspiration in patients with AP during hospitalization. A prediction model for enteral nutrition aspiration during hospitalization was constructed, and calibration curves were used for validation. Receiver operating characteristic curve analysis was conducted to evaluate the predictive value of the model. There was no statistically significant difference in general data between the validation and modeling groups (P > 0.05). The comparison of age, gender, body mass index, smoking history, hypertension history, and diabetes history showed no statistically significant difference between the two groups (P > 0.05). However, patient position, consciousness status, nutritional risk, Acute Physiology and Chronic Health Evaluation (APACHE-II) score, and length of nasogastric tube placement showed statistically significant differences (P < 0.05) between the two groups. Multivariate logistic regression analysis showed that patient position, consciousness status, nutritional risk, APACHE-II score, and length of nasogastric tube placement were independent factors influencing enteral nutrition aspiration in patients with AP during hospitalization (P < 0.05). These factors were incorporated into the prediction model, which showed good consistency between the predicted and actual risks, as indicated by calibration curves with slopes close to 1 in the training and validation sets. Receiver operating characteristic analysis revealed an area under the curve (AUC) of 0.926 (95%CI: 0.8889-0.9675) in the training set. The optimal cutoff value is 0.73, with a sensitivity of 88.4 and specificity of 85.2. In the validation set, the AUC of the model for predicting enteral nutrition aspiration in patients with AP patients during hospitalization was 0.902, with a standard error of 0.040 (95%CI: 0.8284-0.9858), and the best cutoff value was 0.73, with a sensitivity of 91.9 and specificity of 81.8. A prediction model for enteral nutrition aspiration during hospitalization in patients with AP was established and demonstrated high predictive value. Further clinical application of the model is warranted.

Advancing Refugee Health Data Management: The Implementation of ICD-11 in UNRWA's Primary Care System.

The United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) was one of the earliest healthcare systems globally to implement the International Classification of Diseases, Eleventh Revision (ICD-11) across its 140 clinics serving 5.9 million Palestine refugees. This paper discusses the integration of ICD-11 into UNRWA's cloud-based electronic medical record (EMR) system, identifying both the barriers and facilitators involved and analyzing trends in clinical documentation and healthcare utilization. The key challenges included data privacy provisions, integration into a coordinated care model, complex classification schema for primary care settings, frequent staff turnover, and limited data analysis capabilities. Conversely, facilitators included physician-tailored training and on-site support, system compatibility, a multidisciplinary team approach, policy support from UNRWA and the World Health Organization (WHO), and leadership commitment and effective change management. Medical officers (MOs) using ICD-11 reported greater satisfaction with the system's capabilities in managing and visualizing health information. This article contributes to the discourse on health data management in complex humanitarian settings, offering insights into the benefits and challenges of implementing advanced classification systems like ICD-11. Future research should explore longitudinal impacts and further integration with global health systems, ensuring that the advancements in classification continue to support the overarching goal of health equity and access in vulnerable and hard-to-reach populations.

Performance of nutritional and inflammatory markers in patients with pancreatic cancer.

Systemic inflammation and nutrition play pivotal roles in cancer progression and can increase the risk of delayed recovery after surgical procedures. To assess the significance of inflammatory and nutritional indicators for the prognosis and postoperative recovery of patients with pancreatic cancer (PC). Patients who were diagnosed with PC and underwent surgical resection at our hospital between January 1, 2019, and July 31, 2023, were enrolled in this retrospective observational cohort study. All the data were collected from the electronic medical record system. Seven biomarkers - the albumin-to-globulin ratio, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), nutritional risk index (NRI), and geriatric NRI were assessed. A total of 446 patients with PC met the inclusion criteria and were subsequently enrolled. Patients with early postoperative discharge tended to have higher PNI values and lower SII, NLR, and PLR values (all P < 0.05). Through multivariable logistic regression analysis, the SII value emerged as an independent risk factor influencing early recovery after surgery. Additionally, both univariable and multivariable Cox regression analyses revealed that the PNI value was the strongest prognostic marker for overall survival (OS; P = 0.028) and recurrence-free survival (RFS; P < 0.001). The optimal cutoff PNI value was established at 47.30 using X-tile software. Patients in the PNI-high group had longer OS (P < 0.001) and RFS (P = 0.0028) times than those in the PNI-low group. Preoperative systemic inflammatory-nutritional biomarkers may be capable of predicting short-term recovery after surgery as well as long-term patient outcomes.

Similarity Analysis of Clinical Notes for Revealing Writing Styles in an Electronic Medical Record System.

One of the disadvantages of medical documentation in Electronic Medical Record (EMR) systems is that records tend to be redundant by "copying and pasting", a writing style to duplicate and revise previous records. In this study, we analyzed the similarity between records to identify the factors affecting the writing style of clinical notes. We analyzed 98,038 records of 4,149 patients from two years in the Department of Obstetricians and Gynecology at Kyoto University Hospital, Japan. We observed the correlation between the distribution of the record similarity and string amounts, as well as the disease codes and ratios of outpatient visit. The patient group with high record similarity and large number of strings was the group with reproductive medicine, followed by the group of malignant tumor follow-up or Women's Healthcare. In reproductive medicine, physicians have a demand for an overarching evaluation, and in follow-up malignancies or in Women's Healthcare, they have a demand to check for subtle differences from the last time. These facts along with our data insist that the writing style in EMR systems is related to the patient's status. We declared that the writing style in EMR systems is affected by the patient's status. The writing style of duplicating and revising is preferred (1) when there is a clinical demand for an overarching evaluation, and (2) when there is a clinical demand to check for subtle differences from the last time.

Effective Privacy Protection Strategies for Pregnancy and Gestation Information From Electronic Medical Records: Retrospective Study in a National Health Care Data Network in China.

Pregnancy and gestation information is routinely recorded in electronic medical record (EMR) systems across China in various data sets. The combination of data on the number of pregnancies and gestations can imply occurrences of abortions and other pregnancy-related issues, which is important for clinical decision-making and personal privacy protection. However, the distribution of this information inside EMR is variable due to inconsistent IT structures across different EMR systems. A large-scale quantitative evaluation of the potential exposure of this sensitive information has not been previously performed, ensuring the protection of personal information is a priority, as emphasized in Chinese laws and regulations. This study aims to perform the first nationwide quantitative analysis of the identification sites and exposure frequency of sensitive pregnancy and gestation information. The goal is to propose strategies for effective information extraction and privacy protection related to women's health. This study was conducted in a national health care data network. Rule-based protocols for extracting pregnancy and gestation information were developed by a committee of experts. A total of 6 different sub-data sets of EMRs were used as schemas for data analysis and strategy proposal. The identification sites and frequencies of identification in different sub-data sets were calculated. Manual quality inspections of the extraction process were performed by 2 independent groups of reviewers on 1000 randomly selected records. Based on these statistics, strategies for effective information extraction and privacy protection were proposed. The data network covered hospitalized patients from 19 hospitals in 10 provinces of China, encompassing 15,245,055 patients over an 11-year period (January 1, 2010-December 12, 2020). Among women aged 14-50 years, 70% were randomly selected from each hospital, resulting in a total of 1,110,053 patients. Of these, 688,268 female patients with sensitive reproductive information were identified. The frequencies of identification were variable, with the marriage history in admission medical records being the most frequent at 63.24%. Notably, more than 50% of female patients were identified with pregnancy and gestation history in nursing records, which is not generally considered a sub-data set rich in reproductive information. During the manual curation and review process, 1000 cases were randomly selected, and the precision and recall rates of the information extraction method both exceeded 99.5%. The privacy-protection strategies were designed with clear technical directions. Significant amounts of critical information related to women's health are recorded in Chinese routine EMR systems and are distributed in various parts of the records with different frequencies. This requires a comprehensive protocol for extracting and protecting the information, which has been demonstrated to be technically feasible. Implementing a data-based strategy will enhance the protection of women's privacy and improve the accessibility of health care services.

Intraocular pressure and gonioscopic findings in primary angle-closure disease in India-a big data study.

To describe the gonioscopic profile and intraocular pressure (IOP) in primary angle-closure (PAC) disease in patients presenting to a tertiary eye care network in India. A cross-sectional hospital-based study that included 31 484 new patients presenting between 2011 and 2021. Patients with a clinical diagnosis of PAC/suspect/glaucoma were included. The data was collected from an electronic medical record system. PAC glaucoma (PACG) (47.55%) was the most common diagnosis followed by PAC (39.49%) and PAC suspect (PACS; 12.96%). Female preponderance (54.6%) was noted with higher mean age at presentation among males (P<0.0001). PACS and PAC showed the highest prevalence in 6th decade but PACG was higher at 7th decade. The probability of angle opening was 95.93%, 90.32% and 63.36% in PACS, PAC and PACG eyes respectively post peripheral iridotomy (PI). Plateau iris syndrome (PIS) was noted in 252 eyes and all showed post dilated rise of IOP. A post dilated IOP rise was also noted with 8.86%, 33.95% and 57.19% eyes with PACS, PAC and PACG respectively with IOP rise between 6-8 mm Hg across the disease spectrum. The superior quadrant is the narrowest angle and difficult to open with indentation and post PI. The probability of angle opening is less in PIS especially the complete variety along with post dilated IOP rise. The post dilated IOP rise in angle closure eyes warrants a careful dilatation, especially with PIS.

Synoptic operative reports for pediatric surgical oncology.

Synoptic operative notes for pediatric surgical oncology provide standardized and structured documentation of surgical procedures performed on pediatric patients with cancer. These reports capture essential details such as preoperative diagnosis, intraoperative findings, surgical technique, and tumor characteristics in a concise and uniform format. By promoting consistency, accuracy, and completeness in reporting, synoptic operative notes facilitate effective communication among multidisciplinary healthcare teams, enhance quality assurance efforts, and streamline data extraction for research purposes. The integration of synoptic reporting within electronic medical record systems further enhances accessibility and usability, ensuring efficient documentation practices and improved patient care outcomes in pediatric surgical oncology.

Bridging Real-World Data Gaps: Connecting Dots Across 10 Asian Countries.

The economic trend and the health care landscape are rapidly evolving across Asia. Effective real-world data (RWD) for regulatory and clinical decision-making is a crucial milestone associated with this evolution. This necessitates a critical evaluation of RWD generation within distinct nations for the use of various RWD warehouses in the generation of real-world evidence (RWE). In this article, we outline the RWD generation trends for 2 contrasting nation archetypes: "Solo Scholars"-nations with relatively self-sufficient RWD research systems-and "Global Collaborators"-countries largely reliant on international infrastructures for RWD generation. The key trends and patterns in RWD generation, country-specific insights into the predominant databases used in each country to produce RWE, and insights into the broader landscape of RWD database use across these countries are discussed. Conclusively, the data point out the heterogeneous nature of RWD generation practices across 10 different Asian nations and advocate for strategic enhancements in data harmonization. The evidence highlights the imperative for improved database integration and the establishment of standardized protocols and infrastructure for leveraging electronic medical records (EMR) in streamlining RWD acquisition. The clinical data analysis and reporting system of Hong Kong is an excellent example of a successful EMR system that showcases the capacity of integrated robust EMR platforms to consolidate and produce diverse RWE. This, in turn, can potentially reduce the necessity for reliance on numerous condition-specific local and global registries or limited and largely unavailable medical insurance or claims databases in most Asian nations. Linking health technology assessment processes with open data initiatives such as the Observational Medical Outcomes Partnership Common Data Model and the Observational Health Data Sciences and Informatics could enable the leveraging of global data resources to inform local decision-making. Advancing such initiatives is crucial for reinforcing health care frameworks in resource-limited settings and advancing toward cohesive, evidence-driven health care policy and improved patient outcomes in the region.

The Effect of Maternal Parity on Preterm Birth Risk in Women with Short Mid-Trimester Cervical Length: A Retrospective Cohort Study.

Objectives: To evaluate the effect of maternal parity on the association between mid-trimester cervical length and preterm birth to elucidate the potential intricacies of this relationship. Methods: A retrospective cohort study using Electronic Medical Records (EMR) data. The study population included pregnant women with a singleton fetus and a short mid-trimester cervical length, recorded in the EMR system at a large health maintenance organization. Women were categorized by parity in the current pregnancy, and a statistical analysis was conducted to examine the relationship between parity and premature delivery. Results: Data were collected from 1144 records of cervical length measurements of 738 pregnancies obtained from the HMO database. The study population consisted of 259 nulliparous women (35.1%), 451 multiparous women (61.1%), and 28 grand multiparous women (3.8%). The results from the multivariate analysis of the primary outcome showed that nulliparity was significantly associated with an increased risk of premature delivery, with a risk of 1.557 for nulliparous women compared to parous women. Conclusions: In this study, a statistically significant association was found between nulliparity and preterm birth among women with a short mid-trimester cervical length. Nulliparous women were found to have a higher risk of preterm birth in the current pregnancy compared to parous women. Further research is needed to understand the underlying mechanisms and to develop targeted interventions to reduce the risk of premature birth in this population. These findings highlight the need to consider nulliparity as a potential risk factor in the management of pregnancies with a shortened cervix.

Analysis of the Characteristics of Patients Visiting the Tokyo 2020 Olympics Polyclinic.

To evaluate the characteristics of patients who visited the Polyclinic during the Tokyo 2020 Olympics and analyze geographical and economic correlations with the number of clinic visits. Cross-sectional study. Polyclinic during the Tokyo 2020 Olympics. Patients who visited the Polyclinic. Data from the electronic medical record system of the Polyclinic were extracted. The number of visits for each athlete or team official was calculated by country. Relationship between number of visits per patient and total number of team members, total health expenditure per capita, density of medical doctors, life expectancy at birth, and education expenditure per gross domestic product (GDP) were investigated. Independent variables related to medal tables were also investigated. The average number of visits per athlete was 0.67, and it was higher in athletes from non-high-income countries compared with high-income countries for both male and female athletes. Number of visits per athlete was higher in countries with low life expectancy at birth (95% CI, -0.16 to -0.02, P = 0.012) and education expenditure per GDP (95% CI, -0.17 to -0.04, P = 0.003). During the Tokyo 2020 Olympics, the number of visits to the Polyclinic per athlete was higher in countries with low life expectancy at birth and education expenditure per GDP.