Hospital Information System Research Articles

Decadal Analysis of Age-Adjusted Mortality Rates for Acute and Chronic Kidney Disease in Brazil, 2000-2021.

Introduction Renal failure, comprising acute kidney injury (AKI) and chronic kidney disease (CKD), involves a decline or loss of kidney function. AKI is sudden and reversible, with a rapid decline in function over hours to days, while CKD involves persistent abnormalities lasting at least three months. Developing countries are seeing a rise in AKI cases, especially in critically ill patients. Globally, there's a growing occurrence and mortality rate linked to CKD. Methods The study used a retrospective cross-sectional design to analyze AKIand CKDmortality rates in Brazil from 2019 to 2022. Data on population and demographics, including sex and age, were obtained from the Brazilian Institute of Geography and Statistics. Mortality data for kidney diseases were sourced from the Brazilian Hospital Information System. The analysis utilized the Joinpoint Regression Programto calculate average annual percentage changes (AAPCs) and their respective 95% confidence intervals. Weighted Bayesian information criterion was used to determine the significance levels and identify the best-fitting combination of line segments and joinpoints. Results The study findings revealed a significant rise in AKI mortality rates for both males and females, from 2008 to 2021 (APC = 3.16;CI: 2.29 to 5.93), with higher mortality rates recorded among males compared to women over the entire study period. Analyses according to age groups showed that males between the ages 40 to 49 experienced the most rapid increase in mortality during the 2019 - 2021 period (APC = 35.41; CI: 16.72 to 46.57); meanwhile, the most rapid increase in mortality for females was observed from 2019 to 2021, and this was among those aged 30 to 39 (APC = 40.33; CI = 6.48 to 59.78). Furthermore, there was an observable upward trend in mortality related to CKD(APC = 0.70; CI: 0.41 to 1.01), with males consistently having higher mortality rates throughout the entire study period. The elderly population, both males and females, experienced the most rapid increase in CKD-related mortality, with AAPCvalues of 2.32 (CI: 1.82 to 2.89) for males and 1.62 (CI: 1.08 to 2.10) for females. Conclusion We observed a consistent increase in mortality rates from acute kidney diseases for both males and females since 2008, with males experiencing higher mortality rates overall. The study highlighted the need for further researchto understand the underlying factors contributing to these trends. Additionally, interventions targeting modifiable risk factors and improving access to healthcare could help reduce mortality related to renal failure.

The six scoring systems' prognostic value in predicting 24-hour mortality in septic patients.

The use of scoring systems contributes to the faster identification of septic patients, especially those at a high risk of a fatal outcome. The best scoring system does not exist, so the search for the optimal one is always current. The aim of this study is to estimate the prognostic value of the six scoring systems in predicting 24-hour mortality among septic patients presented at the emergency department. An observational retrospective study was conducted in the Emergency Triage Room (ETR) of the Emergency Center (EC) at the University Clinical Center of Serbia (UCCS) in Belgrade. Consecutive septic patients, according to the Sepsis-3 definition, with or without shock, presented to the ETR and then hospitalized in Intensive Care Units were included in the study. Mortality data within 24 h and on the 28th day were extracted from the Hospital information system or the National mortality database. Scoring systems including sequential organ failure assessment (SOFA), quick sequential organ failure assessment (qSOFA), systemic inflammatory response syndrome (SIRS), National early warning score (NEWS), sepsis patient evaluation in the emergency department (SPEED), and mortality in emergency department sepsis (MEDS) were analyzed for all patients utilizing the available data. The primary outcome of this study was death within 24 hours of triage. Receiver operating characteristic (ROC) analysis was used to determine the most effective scoring system. Lactate was then added to this system to enhance its predictive accuracy. Nineteen out of 120 patients included in the study (15.8%) experienced death within 24 hours of triage. The twenty-eight-day mortality rate was 55%. SOFA score demonstrated the highest predictive value for 24-hour mortality but was only moderately predictive overall, with an area under the receiver operating curve (AUC) of 0.755 (95% CI 0.625-0.885). SPEED, MEDS, and NEVS exhibited modest discriminatory power [0.673 (95% CI 0.543-0.803), 0.665 (95% CI 0.536-0.794), 0.630 (95% CI 0.528-0.724)], while SIRS and qSOFA remained insignificant in predicting 24-hour mortality. The predictive value of the SOFA score was increased by the addition of lactate (AUC 0.865, 95% CI 0.736-0.995; p=0.0081). All scores demonstrated better and satisfactory predictive power for 28-day mortality. SOFA, with the addition of lactate, is a complex but reliable tool for the early stratification of septic patients who are presenting at an emergency department.

Effects of pay-for-performance based antimicrobial stewardship on antimicrobial consumption and expenditure: An interrupted time series analysis

ObjectivesTo evaluate the impact of pay-for-performance on antimicrobial consumption and antimicrobial expenditure in a large teaching hospital in Guangzhou, China. MethodsWe collected data from hospital information system from January 2018 through September 2022 in the inpatient wards. Antimicrobial consumption was evaluated using antibiotic use density (AUD) and antibiotic use rate (AUR). The economic impact of intervention was assessed by antimicrobial expenditure percentage. The data was analyzed using interrupted time series (ITS) analysis. ResultsFollowing the implementation of the intervention, immediate decreases in the level of AUD were observed in Department of Hematology Unit 3 (β = −66.93 DDDs/100PD, P = 0.002), Urology (β = −32.80 DDDs/100PD, P < 0.001), Gastrointestinal Surgery Unit 3 (β = −11.44 DDDs/100PD, P = 0.03), Cardiac Surgery (β = −14.30 DDDs/100PD, P = 0.01), ICU, Unit 2 (β = −81.91 DDDs/100PD, P = 0.02) and Cardiothoracic Surgery ICU (β = −41.52 DDDs/100PD, P = 0.05). Long-term downward trends in AUD were also identified in Organ Transplant Unit (β = −1.64 DDDs/100PD, P = 0.02). However, only Urology (β = −6.56 DDDs/100PD, P = 0.02) and Gastrointestinal Surgery Unit 3 (β = −8.50 %, P = 0.01) showed an immediate decrease in AUR, and long-term downward trends in AUR were observed in Pediatric ICU (β = −1.88 %, P = 0.05) and ICU Unit 1 (β = −0.55 %, P = 0.02). ConclusionThis study demonstrates that the adoption of pay-for-performance effectively reduces antibiotic consumption in specific departments of a hospital in Guangzhou in the short term. However, it is important to recognize that the long-term impact of such interventions is often limited. Additionally, it should be noted that the overall effectiveness of the intervention across the entire hospital was not significant.

Histological Chorioamnionitis - Experience from a Tertiary Care Center.

Chorioamnionitis (CA) mostly represents the presence of intra-amniotic infection. The features of the disease can be detected during histopathological examination of the delivered fetal membranes. The current study aims to explore the features of all histological chorioamnionitis cases received in the Pathology Department of a university hospital over a period of five years. This retrospective cross-sectional study was conducted between January 2015 and December 2019 and used data from 78 women with histologically confirmed chorioamnionitis. All data were gathered from the hospital information system. The SPSS software's statistical methods were used to show and analyze descriptive and categorical data. The selected patients had an average age of 36.18 ± 6.153 years (age range 21-50 years) and different stages of the disease: 29 (37.2%) in the first stage, 25 (32%) in the second stage and the remaining 24 (30.7%) subjects in the third stage. Nearly half of cases showed concomitant umbilical cord inflammation, whereas placental inflammation occurred much less frequently. The most common cause of chorioamnionitis was bacterial infection, where Streptococcus agalactiae was the most prevalent. This study showed that the majority of histological chorioamnionitis were of mild intensity (stage 1). Many cases were associated with umbilical cord and, to a lesser extent, with placental inflammation. Bacteria were the most typical cause of chorioamnionitis. The most common strain was Streptococcus agalactiae.

Multidisciplinary PAIN management features of pediatric oncology patients in a pediatric cancer center in Turkiye: A developing country experience.

e22002 Background: Pain is one of the most important problems that affects more than half of cancer patients at any stage of the disease and disrupts the quality of life of patients. The aim should be to relieve pain as soon as possible and prevent its recurrence. In this study, we aimed to evaluate the clinical characteristics of our patients who were followed up with a diagnosis of cancer in our clinic and whose pain management was planned in a multidisciplinary manner with the department of Algology. The clinic where the study was conducted is the reference center of a middle income developing country. Therefore, the data obtained will represent the characteristics of developing countries. Methods: In this retrospective descriptive study, patients followed up with diagnosis of cancer at Ankara University Faculty of Medicine, Department of Pediatric Oncology between 2018 and 2023 and consulted to Department of Algology for pain management were included. Patients whose file information could not be accessed from the hospital information system were excluded from the study. Demographic and clinical parameters of the patients were recorded. The data were evaluated with descriptive statistical methods appropriate to distribution. Results: A total of 33 patients, 19 girls and 14 boys, aged between 2.2 and 23.5 (median 14.4) were evaluated in the study. For each case, a median of 2 (1-16) consultations were made. The most frequent cancer diagnosis was bone tumors with 42% (n:14). Nociceptive pain was present in 25 of the patients, nociceptive and neuropathic pain were present together in 8 patients. It was determined that the most commonly used treatment for pain management was paracetamol, which was used in all patients. Other agents used, in order of frequency: Fentanyl in 19 (57.6%) of the patients, NSAID in 13 (39.4%), gabapentin in 9 (27.3%), oxycodone in 12 (36.4%), 7 (3%) 21.2) were tramadol, 4 (12.5%) were morphine, and 1 (3%) was codeine-paracetamol. Intravenous patient-controlled analgesia (PCA) was used in one patient. Side effects were observed in 3 patients. Fentanyl-related constipation was observed in 1 patient, fentanyl-related globe vesicale was observed in 1 patient, and thrombocytopenia was observed in 1 patient due to gabapentin. Conclusions: Pain is an important factor affecting the quality of life and treatment compliance of children with cancer. Therefore, it is important to ensure effective treatment and to raise the awareness of physicians and care providers by keeping it constantly on the agenda especially in developing countries. Prospective studies will be most useful guide for clinicians.

COVID-19 Vaccines and COVID-19 in People Living with HIV.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly around the world, and COVID-19 and HIV co-infection also became common. In this study, we aimed to investigate the impact of vaccination preferences and vaccination rates on the severity of COVID-19 in patients with HIV co-infection. People living with HIV who were followed in our hospital during the COVID-19 pandemic (January 2020- December 2022) were retrospectively included in the study. The diagnosis of COVID-19 was made by detecting SARS-CoV-2 RNA in nasopharyngeal swab specimens using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). Patients requiring hospital admission were classified as severe. The patient's demographics and vaccination status were collected from the hospital data system. Our study included 205 patients using antiretroviral therapy for HIV. The mean day count between the last vaccine date and SARS-CoV-2 PCR positivity was 163 days in the Comirnaty® group,149 days in the CoronaVac® group, and 154 days in the mixed-vaccinated group. Those vaccinated with Comirnaty® were statistically significantly less infected with COVID-19 after vaccination (p<0.05). The course and the outcomes of COVID-19 among SARS-CoV-2 vaccinated people living with HIV, especially with well-controlled HIV infection, seem to be similar to people living without HIV.

Impact of the COVID-19 Pandemic on Elective and Emergency Surgeries, and Postoperative Mortality in a Brazilian Metropolitan Area: A Time-Series Cohort Study.

The COVID-19 pandemic posed a worldwide challenge, leading to radical changes in surgical services. The primary objective of the study was to assess the impact of COVID-19 on elective and emergency surgeries in a Brazilian metropolitan area. The secondary objective was to compare the postoperative hospital mortality before and during the pandemic. Time-series cohort study including data of all patients admitted for elective or emergency surgery at the hospitals in the Public Health System of Federal District, Brazil, between March 2018 and February 2022, using data extracted from the Hospital Information System of Brazilian Ministry of Health (SIH/DATASUS) on September 30, 2022. A causal impact analysis was used to evaluate the impact of COVID-19 on elective and emergency surgeries and hospital mortality. There were 174,473 surgeries during the study period. There was a reduction in overall (absolute effect per week: -227.5; 95% CI: -307.0 to -149.0), elective (absolute effect per week: -170.9; 95% CI: -232.8 to -112.0), and emergency (absolute effect per week: -57.7; 95% CI: -87.5 to -27.7) surgeries during the COVID-19 period. Comparing the surgeries performed before and after the COVID-19 onset, there was an increase in emergency surgeries (53.0% vs 68.8%, P < 0.001) and no significant hospital length of stay (P = 0.112). The effect of the COVID-19 pandemic on postoperative hospital mortality was not statistically significant (absolute effect per week: 2.1, 95% CI: -0.01 to 4.2). Our study showed a reduction in elective and emergency surgeries during the COVID-19 pandemic, possibly due to disruptions in surgical services. These findings highlight that it is crucial to implement effective strategies to prevent the accumulation of surgical waiting lists in times of crisis and improve outcomes for surgical patients.

Advancing ICU patient care with a Real-Time predictive model for mechanical Power to mitigate VILI

BackgroundInvasive Mechanical Ventilation (IMV) in Intensive Care Units (ICU) significantly increases the risk of Ventilator-Induced Lung Injury (VILI), necessitating careful management of mechanical power (MP). This study aims to develop a real-time predictive model of MP utilizing Artificial Intelligence to mitigate VILI. MethodologyA retrospective observational study was conducted, extracting patient data from Clinical Information Systems from 2018 to 2022. Patients over 18 years old with more than 6 h of IMV were selected. Continuous data on IMV variables, laboratory data, monitoring, procedures, demographic data, type of admission, reason for admission, and APACHE II at admission were extracted. The variables with the highest correlation to MP were used for prediction and IMV data was grouped in 15-minute intervals using the mean. A mixed neural network model was developed to forecast MP 15 min in advance, using IMV data from 6 h before the prediction and current patient status. The model’s ability to predict future MP was analyzed and compared to a baseline model predicting the future value of MP as equal to the current value. ResultsThe cohort consisted of 1967 patients after applying inclusion criteria, with a median age of 63 years and 66.9 % male. The deep learning model achieved a mean squared error of 2.79 in the test set, indicating a 20 % improvement over the baseline model. It demonstrated high accuracy (94 %) in predicting whether MP would exceed a critical threshold of 18 J/min, which correlates with increased mortality. The integration of this model into a web platform allows clinicians real-time access to MP predictions, facilitating timely adjustments to ventilation settings. ConclusionsThe study successfully developed and integrated in clinical practice a predictive model for MP. This model will assist clinicians allowing for the adjustment of ventilatory parameters before lung damage occurs.

User Satisfaction Management Information System Hospitals in Kuala Pembuang Regional General Hospital

A computer-based Management Information System for hospitals is very important. Data was obtained that there were 89 hospitals (3%) that reported already having SIMRS but not running functionally, 294 hospitals (10%) did not have SIMRS, and 365 hospitals (12%) did not report SIMRS. Most of the employees are 20 – 35 years old. The purpose of this study is to determine the relationship between the age of the hospital management information system, the quality of the information, the quality of the system, and the quality of services provided to patients at Kuala Pembuang Hospital. This study uses cross-sectional design and observational analytical methods. For the sampling technique used the type probability sampling with 89 participants. Chi-square analysis results showed the value of age p values (p= 0.587), system quality (p= 0.000), information quality (p= 0.000) and service quality (p= 0.000). The results of multivariate analysis with logistic regression showed the p and ExpB values of the information quality variable (p=0.000, Exp B=10.267). There is a substantial relationship between user satisfaction with system quality, information quality, and service quality. In addition, there is no significant relationship between age and user satisfaction of the hospital management information system at Kuala Pembuang Hospital.

Measuring the impact of pharmaceutical care bundle delivery on patient outcomes: an observational study.

Clinical pharmacists perform activities to optimise medicines use and prevent patient harm. Historically, clinical pharmacy quality indicators have measured individual activities not linked to patient outcomes. To determine the proportion of patients who receive a pharmaceutical care bundle (PCB) (consisting of a medication history, medication review, discharge medication list and medicines information on the discharge summary) as well as investigate the relationship between delivery of this PCB and patient outcomes. Pharmaceutical care bundle activities were defined within state-wide (Queensland, Australia)clinical information systems and datasets were linked. An observational study using routinely recorded data was performed at ten participating sites for adult patients who had a non-same day hospital stay. The association between extent of PCB delivery and three patient outcomes were investigated: length of stay (LOS), unplanned readmission, and mortality. In total 283,813 patient hospital stays were evaluated. The delivery of the PCB occurred in 26.9% of patients at the ten participating hospital sites, ranging from 0.6 to 61.2% across sites. Patients with a longer LOS were more likely to receive delivery of the complete PCB (P < 0.001). There was no correlation between PCB and hospital standardised mortality ratio (r = 0.03, p = 0.93). Higher rates of delivery of the PCB were associated with lower rates of unplanned readmission within 30 days (r = - 0.993, p < 0.001). A complete PCB was delivered to 26.9% of patients and was associated with a significantly lower rate of unplanned readmission within 30 days.

Factors Influencing Insulin Adherence among Outpatients with Type 2 Diabetes Mellitus and the Impact of Pharmaceutical Intervention: A Randomized Clinical Trial

Aims. This study aimed to identify and analyze the factors significantly influencing long-term insulin medication adherence among outpatients and to evaluate whether pharmaceutical interventions targeting these factors can improve patient medication adherence and glycemic control. Methods. A cohort of 180 patients was recruited from a tertiary hospital in Nanjing, China. Factors potentially influencing insulin adherence were scrutinized employing the KAP (knowledge, attitude/belief, and practice) health behavior model. Baseline characteristics were extracted from the hospital information system, while patient knowledge of the disease and medication, medication adherence, medication beliefs, and management self-efficacy were assessed, respectively, using self-developed questionnaires, MMAS-8, C-DMSES, and BMQ scales. Univariate and multivariate analyses were conducted to determine the impact of these factors on insulin adherence. Following this, participants were randomly allocated to either the intervention or control group. The intervention group received three months of weekly telephone sessions and educational interventions targeting facets such as medication knowledge and beliefs, while the control group received standard care. After the intervention, insulin adherence and glycemic control conditions of both groups were collected and re-evaluated. Results. After excluding lost-to-follow-up patients, 152 individuals were analyzed (intervention: 75 and control: 77). Multivariate analyses revealed factors influencing insulin adherence, including age, diabetes duration, health insurance status, HbA1c level, disease and medication knowledge, diabetes management self-efficacy, and medication beliefs (P&lt;0.05). Before targeted pharmaceutical care, no significant differences existed in insulin adherence, HbA1c levels, management self-efficacy, knowledge, or medication beliefs between intervention and control groups (P&gt;0.05). However, subsequent pharmaceutical intervention notably improved adherence, HbA1c levels, self-efficacy, knowledge, and medication beliefs (P&lt;0.05). Conclusion. This study examines the impact of glycemic control, health insurance status, management self-efficacy, level of knowledge, and medication beliefs on improving insulin medication adherence in patients with type 2 diabetes mellitus. Targeted pharmaceutical intervention can enhance medication adherence, improve glucose control, and promote rational insulin use. This trial is registered with ChiCTR2300074444.

EFFICACY OF A SEPSIS CLINICAL DECISION SUPPORT SYSTEM IN IDENTIFYING PATIENTS WITH SEPSIS IN THE EMERGENCY DEPARTMENT.

Background: Early prediction of sepsis onset is crucial for reducing mortality and the overall cost burden of sepsis treatment. Currently, few effective and accurate prediction tools are available for sepsis. Hence, in this study, we developed an effective sepsis clinical decision support system (S-CDSS) to assist emergency physicians to predict sepsis. Methods: This study included patients who had visited the emergency department (ED) of Taipei Tzu Chi Hospital, Taiwan, between January 1, 2020, and June 31, 2022. The patients were divided into a derivation cohort (n = 70,758) and a validation cohort (n = 27,545). The derivation cohort was subjected to 6-fold stratified cross-validation, reserving 20% of the data (n = 11,793) for model testing. The primary study outcome was a sepsis prediction ( International Classification of Diseases , Tenth Revision , Clinical Modification ) before discharge from the ED. The S-CDSS incorporated the LightGBM algorithm to ensure timely and accurate prediction of sepsis. The validation cohort was subjected to multivariate logistic regression to identify the associations of S-CDSS-based high- and medium-risk alerts with clinical outcomes in the overall patient cohort. For each clinical outcome in high- and medium-risk patients, we calculated the sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and accuracy of S-CDSS-based predictions. Results: The S-CDSS was integrated into our hospital information system. The system featured three risk warning labels (red, yellow, and white, indicating high, medium, and low risks, respectively) to alert emergency physicians. The sensitivity and specificity of the S-CDSS in the derivation cohort were 86.9% and 92.5%, respectively. In the validation cohort, high- and medium-risk alerts were significantly associated with all clinical outcomes, exhibiting high prediction specificity for intubation, general ward admission, intensive care unit admission, ED mortality, and in-hospital mortality (93.29%, 97.32%, 94.03%, 93.04%, and 93.97%, respectively). Conclusion: Our findings suggest that the S-CDSS can effectively identify patients with suspected sepsis in the ED. Furthermore, S-CDSS-based predictions appear to be strongly associated with clinical outcomes in patients with sepsis.

Evaluation of Blood Culture Results in Patients with Malignancy in Erzurum Province, Turkey.

Bloodstream infections are a serious public health problem that requires follow-up with blood culture; this negatively affects the course of the disease and patient healthcare costs in patients with malignancy. This study aimed to determine the growth frequency of pathogens and their antibiotic resistance profiles in the blood cultures of patients with hematological and oncogenic malignancies. The results of 7451 blood cultures, obtained from 2926 patients between January 2017 and January 2022, were evaluated retrospectively. Of these cultures, 3969 were obtained from patients with malignancy (diagnostic codes C00-D48 in ICD-10) and 3482 from patients without malignancy. The hospital information management system modules were used to acquire patient data and blood culture results. Various microorganisms grew in 10.1% of blood cultures. Of these organisms, 64.1% were isolated from cases of malignancy. Of the pathogens, 49.2% were gram-negative bacteria, 47.7% were gram-positive bacteria, and 3.1% were fungi. The most frequently isolated bacteria were methicillin-resistant coagulase-negative staphylococci (3.2%), Escherichia coli (2.3%), Klebsiella pneumoniae (1.0%), methicillin-sensitive coagulase-negative staphylococci (0.7%), and Staphylococcus aureus (0.6%). Pathogen positivity was highest in the patient cultures with urinary system cancer (23.9%), thyroid and other endocrine gland cancers (20.6%), female and male genital organ cancers (18.2%/16.9%), and digestive organ cancer (14.2%). Gram-negative bacteria to ampicillin, piperacillin, and sulfamethoxazole-trimethoprim and Gram-positive bacteria to penicillin, erythromycin, and sulfamethoxazole-trimethoprim were highly resistant. Combined resistance to imipenem and meropenem was observed in 25 Gram-negative bacteria. Twelve (48%) of the carbapenem-resistant bacteria were isolated from patients with lymphoid, hematopoietic, and related tissue malignant neoplasia. This study reported microorganisms and their antimicrobial resistance in the blood cultures of malignant patients, a special patient group. It pointed out that the antibiotic resistance of Staphylococcus, Klebsiella pneumoniae, and E. coli is high enough to cause problems in the treatment of patients with malignancy.

#782 Latent profiles of patients undergoing maintenance hemodialysis based on hemodynamic indicators

Abstract Background and Aims Both intradialytic hypotension and intradialytic hypertension are conditions occurring frequently during hemodialysis and are associated with unfavorable clinical outcomes. However, they remain incompletely understood and poorly defined in the literature. Since intradialytic parameters are now captured automatically in electronic medical records in many institutions, machine learning could emerge as an innovative tool for hemodialysis clinical research. Latent Profile Analysis is a model-based clustering method. It allows to identify hidden subpopulations derived from a set of observed indicator variables, maximizing between-group differences and within-group similarities. Method The objectives of this study were to identify latent profiles using a set of hand-crafted indicators and to interpret these subgroups of patients in a clinically meaningful manner. We conducted a retrospective single-center cohort study of adult patients receiving hemodialysis between January 2017 and December 2022 in Montreal. Given the highly heterogeneous nature of this population, we only enrolled incidental patients. The data were extracted from the NephroCare database, which is the clinical information system used by dialysis teams in our center. Sixteen indicators were derived from time series of blood pressure and heart rate measurements, capturing various patient-centric aspects of intradialytic hemodynamics, including trends, zeniths, nadirs, and time-related features. Latent Profile Analysis involved fitting a series of models, and the best model was selected based on fit indices, evaluation metrics, and clinical interpretation of the distribution of indicator within identified profiles. The primary analysis used complete-case data, and a sensitivity analysis assessed the impact of missing data through multiple imputation. Internal model validation was conducted using k-fold cross-validation. Results The selected model consisted of four profiles with varying variance and null covariance across indicators. Fig. 1 presents radar plots summarizing the identified profiles. Profile 1 included patients with prolonged early nadirs and a nadir-to-zenith transition pattern at the session level. Profile 2 was characterized by frequent nadirs and zeniths without a specific timing preference. Profile 3 comprised patients with infrequent blood pressure variations altogether. Profile 4 included patients with frequent early nadirs but no zeniths. The model demonstrated good generalization to unseen cases and exhibited relative robustness to missing data. Conclusion In this preliminary study, we demonstrated that Latent Profile Analysis can identify clinically meaningful subpopulations of hemodialysis patients based on hemodynamic indicators. The association between the identified profiles and hard clinical endpoints remains to be established.

Big data analysis for Covid-19 in hospital information systems.

The COVID-19 pandemic has triggered a global public health crisis, affecting hundreds of countries. With the increasing number of infected cases, developing automated COVID-19 identification tools based on CT images can effectively assist clinical diagnosis and reduce the tedious workload of image interpretation. To expand the dataset for machine learning methods, it is necessary to aggregate cases from different medical systems to learn robust and generalizable models. This paper proposes a novel deep learning joint framework that can effectively handle heterogeneous datasets with distribution discrepancies for accurate COVID-19 identification. We address the cross-site domain shift by redesigning the COVID-Net's network architecture and learning strategy, and independent feature normalization in latent space to improve prediction accuracy and learning efficiency. Additionally, we propose using a contrastive training objective to enhance the domain invariance of semantic embeddings and boost classification performance on each dataset. We develop and evaluate our method with two large-scale public COVID-19 diagnosis datasets containing CT images. Extensive experiments show that our method consistently improves the performance both datasets, outperforming the original COVID-Net trained on each dataset by 13.27% and 15.15% in AUC respectively, also exceeding existing state-of-the-art multi-site learning methods.

Analisis Efektivitas Penggunaan Aplikasi Hospital Information System Atas Penerimaan Kas Pada Rumah Sakit Islam Ibnu Sina

In the era of business digitization and globalization, the role of accounting information systems has become a key pillar in managing the financial operations of a company. One critical aspect that requires close monitoring is cash receipts, an essential element in measuring the financial health of an organization. The process of recording, managing, and reporting cash receipts through the accounting information system reflects the readiness level of a company in facing financial challenges. This research aims to assess the level of adoption and utilization of information technology at Ibnu Sina Islamic Hospital by using the Hospital Information System application for cash receipts as a key factor in enhancing its effectiveness. The study employs a qualitative descriptive approach to analyze the effectiveness of the Hospital Information System (HIS) application on cash receipts at Ibnu Sina Islamic Hospital in Pekanbaru. Primary data is obtained through in-depth interviews with the accounting staff at Ibnu Sina Islamic Hospital. The research findings indicate that the Hospital Information System application for cash receipts at Ibnu Sina Islamic Hospital plays a significant role in improving cash receipts. The strategies employed to overcome challenges reflect Ibnu Sina Islamic Hospital's commitment to providing more efficient healthcare services focused on patients. By involving all relevant parties, the hospital has successfully faced obstacles and laid a solid foundation for a more digital future in the healthcare industry.

Trends in managing femoral neck fractures with arthroplasty in the ≥ 50 years age group.

To know about the trends in the management of neck of femur fractures with arthroplasty in patients ≥ 50 years. It is a retrospective cross-sectional study with data collection from Hospital Management Information System from 1st January 2020 to 31st July 2023. SPSS version 25 was used for data analysis. Mean & standard deviation was reported for quantitative variable & frequency and proportion were reported for qualitative variables. The cross- tabulations were performed to evaluate the association between the variables. Total number of patients in this study was 305. Mean age was 67.80 ± 10.5 SD. Male to female ratio was 150:155. Co-morbidities were found in 126 patients. The surgical options used were Austin Moore prosthesis (64), Cemented Bipolar (36), Hybrid Total Hip Replacement (7), Non-cemented Total Hip Replacement (86), Cemented Total Hip Replacement (32), Uncemented Bipolar (71). Garden Type-2 fracture was noted in 33 patients, Type-3 in 170 patients and Type-4 in 87 patients. Cemented stem was used in 74 patients while 222 patients had non-cemented stem. One quarter of the patients had cemented stem implanted compared to three quarter of the patients who had non-cemented stem.

Improving outcomes of type 2 diabetes mellitus patients in primary care with Chronic Care Model: A narrative review.

Designed and implemented over two decades ago, the Chronic Care Model is a well-established chronic disease management framework that has steered several healthcare systems in successfully improving the clinical outcomes of patients with type 2 diabetes mellitus. Research evidence cements the role of the Chronic Care Model (with its six key elements of organization of healthcare delivery system, self-management support, decision support, delivery system design, clinical information systems, and community resources and policies) as an integrated framework to revamp the type 2 diabetes mellitus-related clinical practice and care that betters the patient care and clinical outcomes. The current review is an evidence-lit summary of importance of use of Chronic Care Model in primary care and their impact on clinical outcomes for patients afflicted with one of the most debilitating metabolic diseases, type 2 diabetes mellitus.

Outcomes of patients with thrombotic thrombocytopenic purpura treated in an intensive care unit.

Background Thrombotic thrombocytopenic purpura (TTP) is a multisystem disorder characterized by widespread microthrombosis that can predispose to multiple organ failure. The literature is sparse on the outcomes of critically ill patients with TTP managed in intensive care units (ICUs). We aimed to determine the mortality of ICU patients admitted with TTP and evaluate the predictors of survival. We also compared the incidence of nosocomial infection among those who did or did not receive plasma exchange (PE). Methods We conducted a retrospective study in a tertiary ICU. Two authors screened patients for eligibility from the hospital information system based on peripheral smear reports. Adult critically ill TTP patients managed in ICU were included. Patients with a diagnosis of haemolytic uraemic syndrome, autoimmune causes of haemolysis and pregnancy-related conditions, etc. were excluded. Two authors extracted data from medical charts. No imputation of missing variables was done. Non-parametric statistics were used to report data. Statistical analyses were performed using Stata version 16. Results Of the 535 records that were screened, 33 patients were deemed eligible. Mortality among TTP patients was 14 (42%). The women to men ratio was 7:3. At admission, greater degree of anaemia, thrombocytopenia, and higher lactate dehydrogenase levels were observed in non-survivors compared to survivors (5.4 g/dl [4.8-7.1] v. 7.6 g/dl [6.1-8.9], p=0.05; 17x103 μl v. 21x103 μl, p=0.63; and 2987 (1904-3614) U/L v. 2126 U/L (1941-3319), p=0.71; respectively]. Nineteen (57%) patients had acute kidney injury (AKI), of which 11 survived: 6 recovered completely from renal failure and 5 progressed to end-stage renal disease. Nosocomial infection rates were not different among those receiving and not receiving PE therapy (7 [33%] v. 3 [25%], respectively). Conclusion TTP is more common in women and has a high mortality. Older age, low haemoglobin and higher platelet transfusions are predictors of poor survival. Nosocomial infection rates were similar irrespective of receiving PE therapy.

Non-linear association and benchmark dose of blood pressure on carotid artery intima-media thickening in a general population of southern China.

This study aimed to evaluate whether there is a J-curve association between blood pressure (BP) and carotid artery intima-media thickening (CAIT) and estimate the effect of the turning point of BP on CAIT. Data from 111,494 regular physical examinations conducted on workers and retirees (aged 18 years or older) between January 2011 and December 2016, exported from the hospital information system, were analyzed. Restricted cubic splines (RCS) logistic regression was employed to access the association of BP with CAIT, and Bayesian benchmark dose methods were used to estimate the benchmark dose as the departure point of BP measurements. All the pnon-linear values of BP measurements were less than 0.05 in the RCS logistic regression models. Both systolic blood pressure (SBP) and diastolic blood pressure (DBP) had J-curve associations with the risk of CAIT at a turning point around 120/70 mmHg in the RCS. The benchmark dose for a 1% change in CAIT risk was estimated to be 120.64 mmHg for SBP and 72.46 mmHg for DBP. The J-curve associations between SBP and DBP and the risk of CAIT were observed in the general population in southern China, and the turning point of blood pressure for significantly reducing the risk of CAIT was estimated to be 120.64/72.46 mmHg for SBP/DBP.