BACKGROUND AND OBJECTIVE

In the Philippines, patients are constrained from accessing their own records, restricting their ability to freely choose who to seek care from. To address this, the study makes a case for the development of the health smart card in the Philippines, an integrative tool unique to each citizen carrying their lifetime medical record.

The prototype is developed using no-code programming technology and validated through a series of focus group discussions and stakeholder consultations with patients (n=4), healthcare administrators (n=4), and hospital personnel (n=13). It was then revised based on the collected insights and recommendations.

Findings report that the current facility-centric model utilizing paper records constrains patients’ access to their records due to long wait times, slow turnaround periods, constant intra- and inter-hospital transfers, and even charging of fees to acquire a copy of their own data. The health smart card alternative was widely accepted by the participants, particularly for its contribution to increasing data accessibility, patient empowerment, and advancing patient data ownership. Nevertheless, several considerations for the upscale implementation of the health smart card emerged, including creating an interoperable environment through harmonizing standards and capacity-building programs, and ensuring data security through robust cybersecurity measures. Issues on scalability and funding of the project were also raised, centering on the critical role of the government in stepping up as regulator and potential funder. Concerns over potential abuse, dataveillance, and the digital divide are tackled, highlighting the need to account for socioeconomic factors to ensure that no one is left behind in the implementation.

The study makes a case for the development and adoption of a health smart card to address the inaccessibility of records to patients. The study concludes by recommending the conduct of a pilot implementation to comprehensively demonstrate and analyze the features of the proposed scheme.

BACKGROUND AND OBJECTIVE

There are mixed reports on nurses’ satisfaction with electronic medical records (EMR) in literature, and facilitators and barriers to its adoption were reported frequently. A Philippine public tertiary hospital developed an EMR to facilitate remote access to patient charts outside its COVID-designated areas during the pandemic. This study aims to assess nurses’ satisfaction with EMR use in order to improve their user experience. The Delone and McLean Information System (D&M IS) Success Model was used as its framework. This offers a unique perspective to EMR adoption by accounting for the effects of the pandemic.

A descriptive, cross-sectional, quantitatively driven, concurrent mixed-methods design was employed. Nurses from the hospital were recruited for the survey (n=353) and the focus group discussions (n=14). Ethical approval was obtained prior to its conduct. Analysis was done through descriptive statistics, multiple linear regression, and thematic analysis. Data were integrated to appreciate the differences in their experiences from the point of adoption up to their current experiences.

Nurses initially faced challenges with the EMR when it was introduced, but improvements and continuous use have led to their current high satisfaction. Despite mandatory use and high usage scores, some daily tasks are still done manually. Use, length of service, number of patients handled, designation, and area of assignment were found to be associated with satisfaction. Thematic analysis highlighted several adoption prerequisites in this setup, including assessment of user competence and experience, and the provision of training, structural necessities, and organizational support.

This study found high use and satisfaction scores, aligning with the D&M IS Success Model, despite initial adoption challenges. Recommendations include maintaining high EMR use and improving efficiency, communication, and collaboration. Emphasis was placed on the provisions of better training and continuous feedback gathering.

Background and Objective: There are mixed reports on nurses’ satisfaction with electronic medical records (EMR) in literature, and facilitators and barriers to its adoption were reported frequently. A Philippine public tertiary hospital developed an EMR to facilitate remote access to patient charts outside its COVID-designated areas during the pandemic. This study aims to assess nurses’ satisfaction with EMR use in order to improve their user experience. The Delone and McLean Information System (D&M IS) Success Model was used as its framework. This offers a unique perspective to EMR adoption by accounting for the effects of the pandemic. Methods: A descriptive, cross-sectional, quantitatively driven, concurrent mixed-methods design was employed. Nurses from the hospital were recruited for the survey (n=353) and the focus group discussions (n=14). Ethical approval was obtained prior to its conduct. Analysis was done through descriptive statistics, multiple linear regression, and thematic analysis. Data were integrated to appreciate the differences in their experiences from the point of adoption up to their current experiences. Results: Nurses initially faced challenges with the EMR when it was introduced, but improvements and continuous use have led to their current high satisfaction. Despite mandatory use and high usage scores, some daily tasks are still done manually. Use, length of service, number of patients handled, designation, and area of assignment were found to be associated with satisfaction. Thematic analysis highlighted several adoption prerequisites in this setup, including assessment of user competence and experience, and the provision of training, structural necessities, and organizational support. Conclusions This study found high use and satisfaction scores, aligning with the D&M IS Success Model, despite initial adoption challenges. Recommendations include maintaining high EMR use and improving efficiency, communication, and collaboration. Emphasis was placed on the provisions of better training and continuous feedback gathering.
Human ; electronic health records ; health information systems ; nurses ; pandemics ; Philippines

The present study aimed to explore the main active components and underlying mechanisms of Marsdenia tenacissima in the treatment of ovarian cancer(OC) through network pharmacology, molecular docking, and in vitro cell experiments. The active components of M. tenacissima were obtained from the literature search, and their potential targets were obtained from SwissTargetPrediction. The OC-related targets were retrieved from Therapeutic Target Database(TTD), Online Mendelian Inheritance in Man(OMIM), GeneCards, and PharmGKB. The common targets of the drug and the disease were screened out by Venn diagram. Cytoscape was used to construct an "active component-target-disease" network, and the core components were screened out according to the node degree. The protein-protein interaction(PPI) network of the common targets was constructed by STRING and Cytoscape, and the core targets were screened out according to the node degree. GO and KEGG enrichment analyses of potential therapeutic targets were carried out with DAVID database. Molecular docking was used to determine the binding activity of some active components to key targets by AutoDock. Finally, the anti-OC activity of M. tenacissima extract was verified based on SKOV3 cells in vitro. The PI3K/AKT signaling pathway was selected for in vitro experimental verification according to the results of GO function and KEGG pathway analyses. Network pharmacology results showed that 39 active components, such as kaempferol, 11α-O-benzoyl-12β-O-acetyltenacigenin B, and drevogenin Q, were screened out, involving 25 core targets such as AKT1, VEGFA, and EGFR, and the PI3K-AKT signaling pathway was the main pathway of target protein enrichment. The results of molecular docking also showed that the top ten core components showed good binding affinity to the top ten core targets. The results of in vitro experiments showed that M. tenacissima extract could significantly inhibit the proliferation of OC cells, induce apoptosis of OC cells through the mitochondrial pathway, and down-regulate the expression of proteins related to the PI3K/AKT signaling pathway. This study shows that M. tenacissima has the characteristics of multi-component, multi-target, and multi-pathway synergistic effect in the treatment of OC, which provides a theoretical basis for in-depth research on the material basis, mechanism, and clinical application.
Humans ; Female ; Marsdenia ; Molecular Docking Simulation ; Network Pharmacology ; Phosphatidylinositol 3-Kinases ; Proto-Oncogene Proteins c-akt ; Ovarian Neoplasms/genetics* ; Databases, Genetic ; Plant Extracts ; Drugs, Chinese Herbal/pharmacology*

OBJECTIVE: In order to record the whole life process information of medical equipment and improve the management efficiency, this study proposes an informatization scheme for the whole life cycle management of medical equipment. METHODS: Relying on cloud-native, based on the software architecture of front-end and back-end separation, a mode of sub-account and sub-authority management of medical equipment was designed to integrate maintenance work orders, operation reports and other functions, and manage medical equipment data in a structured and platform-based manner. RESULTS: Comparing the equipment failure rate, maintenance response time, and average inventory time per device before and after the system operation, the differences are statistically significant (P<0.05). CONCLUSIONS The system can realize the work collaboration of maintenance engineers, equipment users, and equipment management personnel, and can trace the information of the whole life cycle of the equipment.
Software ; Information Systems

Metabolic reprogramming is a common phenomenon in cancer, with aerobic glycolysis being one of its important characteristics. Hypoxia-inducible factor-1α (HIF1Α) is thought to play an important role in aerobic glycolysis. Meanwhile, naringin is a natural flavanone glycoside derived from grapefruits and many other citrus fruits. In this work, we identified glycolytic genes related to HIF1Α by analyzing the colon cancer database. The analysis of extracellular acidification rate and cell function verified the regulatory effects of HIF1Α overexpression on glycolysis, and the proliferation and migration of colon cancer cells. Moreover, naringin was used as an inhibitor of colon cancer cells to illustrate its effect on HIF1Α function. The results showed that the HIF1Α and enolase 2 (ENO2) levels in colon cancer tissues were highly correlated, and their high expression indicated a poor prognosis for colon cancer patients. Mechanistically, HIF1Α directly binds to the DNA promoter region and upregulates the transcription of ENO2; ectopic expression of ENO2 increased aerobic glycolysis in colon cancer cells. Most importantly, we found that the appropriate concentration of naringin inhibited the transcriptional activity of HIF1Α, which in turn decreased aerobic glycolysis in colon cancer cells. Generally, naringin reduces glycolysis in colon cancer cells by reducing the transcriptional activity of HIF1Α and the proliferation and invasion of colon cancer cells. This study helps to elucidate the relationship between colon cancer progression and glucose metabolism, and demonstrates the efficacy of naringin in the treatment of colon cancer.
Glycolysis ; Colonic Neoplasms/metabolism* ; Humans ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Phosphopyruvate Hydratase/metabolism* ; Flavanones/pharmacology* ; Cell Line, Tumor ; Databases, Genetic ; Cell Proliferation/drug effects* ; Transfection ; Warburg Effect, Oncologic

Objectives: This study explores the potential of the HeLe Service Delivery Model, a community-based newborn hearing screening (NHS) program supported by a web-based referral system, in improving provision of hearing care services. Methods: This prospective observational study evaluated the HeLe Service Delivery Model based on records review and user perspectives. We collected system usage logs from July to October 2018 and data on patient outcomes. Semi-structured interviews and review of field reports were conducted to identify implementation challenges and facilitating factors. Descriptive statistics and content analysis were used to analyze quantitative and qualitative data, respectively. Results: Six hundred ninety-two (692) babies were screened: 110 in the RHUs and 582 in the Category A NHS hospital. Mean age at screening was 1.4±1.05 months for those screened in the RHU and 0.46±0.74 month for those in the Category A site. 47.3% of babies screened at the RHU were ≤1 month old in contrast to 86.6% in the Category A hospital. A total of 10 babies (1.4%) received a positive NHS result. Eight of these ten patients were referred via the NHS Appointment and Referral System; seven were confirmed to have bilateral profound hearing loss, while one patient missed his confirmatory testing appointment. The average wait time between screening and confirmatory testing was 17.1±14.5 days. Facilitating factors for NHS implementation include the presence of champions, early technology adopters, legislations, and capacity-building programs. Challenges identified include perceived inconvenience in using information systems, cost concerns for the patients, costly hearing screening equipment, and unstable internet connectivity. The lack of nearby facilities providing NHS diagnostic and intervention services remains a major block in ensuring early diagnosis and management of hearing loss in the community. Conclusion The eHealth-enabled HeLe Service Delivery Model for NHS is promising. It addresses the challenges and needs of community-based NHS by establishing a healthcare provider network for NHS in the locale, providing a capacity-building program to train NHS screeners, and deploying health information systems that allows for documentation, web-based referral and tracking of NHS patients. The model has the potential to be implemented on a larger scale — a deliberate step towards universal hearing health for all Filipinos.
Neonatal Screening ; Hearing Loss ; Health Information Systems ; Community Health Services ; Delivery of Health Care

OBJECTIVE: To develop a mortality prediction model for critically ill patients based on multidimensional and dynamic clinical data collected by the hospital information system (HIS) using random forest algorithm, and to compare the prediction efficiency of the model with acute physiology and chronic health evaluation II (APACHE II) model. METHODS: The clinical data of 10 925 critically ill patients aged over 14 years old admitted to the Third Xiangya Hospital of Central South University from January 2014 to June 2020 were extracted from the HIS system, and APACHE II scores of the critically ill patients were extracted. Expected mortality of patients was calculated according to the death risk calculation formula of APACHE II scoring system. A total of 689 samples with APACHE II score records were used as the test set, and the other 10 236 samples were used to establish the random forest model, of which 10% (n = 1 024) were randomly selected as the validation set and 90% (n = 9 212) were selected as the training set. According to the time series of 3 days before the end of critical illness, the clinical characteristics of patients such as general information, vital signs data, biochemical test results and intravenous drug doses were selected to develope a random forest model for predicting the mortality of critically ill patients. Using the APACHE II model as a reference, receiver operator characteristic curve (ROC curve) was drawn, and the discrimination performance of the model was evaluated through the area under the ROC curve (AUROC). According to the precision and recall, Precision-Recall curve (PR curve) was drawn, and the calibration performance of the model was evaluated through the area under the PR curve (AUPRC). Calibration curve was drawn, and the consistency between the predicted event occurrence probability of the model and the actual occurrence probability was evaluated through the calibration index Brier score. RESULTS: Among the 10 925 patients, there were 7 797 males (71.4%) and 3 128 females (28.6%). The average age was (58.9±16.3) years old. The median length of hospital stay was 12 (7, 20) days. Most patients (n = 8 538, 78.2%) were admitted to intensive care unit (ICU), and the median length of ICU stay was 66 (13, 151) hours. The hospitalized mortality was 19.0% (2 077/10 925). Compared with the survival group (n = 8 848), the patients in the death group (n = 2 077) were older (years old: 60.1±16.5 vs. 58.5±16.4, P < 0.01), the ratio of ICU admission was higher [82.8% (1 719/2 077) vs. 77.1% (6 819/8 848), P < 0.01], and the proportion of patients with hypertension, diabetes and stroke history was also higher [44.7% (928/2 077) vs. 36.3% (3 212/8 848), 20.0% (415/2 077) vs. 16.9% (1 495/8 848), 15.5% (322/2 077) vs. 10.0% (885/8 848), all P < 0.01]. In the test set data, the prediction value of random forest model for the risk of death during hospitalization of critically ill patients was greater than that of APACHE II model, which showed by that the AUROC and AUPRC of random forest model were higher than those of APACHE II model [AUROC: 0.856 (95% confidence interval was 0.812-0.896) vs. 0.783 (95% confidence interval was 0.737-0.826), AUPRC: 0.650 (95% confidence interval was 0.604-0.762) vs. 0.524 (95% confidence interval was 0.439-0.609)], and Brier score was lower than that of APACHE II model [0.104 (95% confidence interval was 0.085-0.113) vs. 0.124 (95% confidence interval was 0.107-0.141)]. CONCLUSIONS The random forest model based on multidimensional dynamic characteristics has great application value in predicting hospital mortality risk for critically ill patients, and it is superior to the traditional APACHE II scoring system.
Female ; Male ; Humans ; Aged ; Adult ; Middle Aged ; Adolescent ; Critical Illness ; Hospitalization ; Length of Stay ; APACHE ; Hospital Information Systems

This paper aimed to explore the antidepressant effect of the essential oil from Schizonepeta tenuifolia Briq.(EOST) on the treatment of depression and its mechanism by using a combination of network pharmacology and the mouse model of lipopolysaccharide(LPS)-induced depression. The chemical components in EOST were identified using gas chromatography-mass spectrometer(GC-MS), and 12 active components were selected as the study objects. The targets related to EOST were obtained by Traditional Chinese Medicines Systems Pharmacology(TCMSP) and SwissTargetPrediction database. The targets related to depression were screened out through GeneCards, Therapeutic Target Database(TTD), and Online Mendelian Inheritance in Man(OMIM) database. The Venny 2.1 was applied to screen out the common targets of EOST and depression. The targets were imported into Cytoscape 3.7.2 to generate "drug-active component-diease-target" network diagram. The protein-protein interaction(PPI) network was constructed using STRING 11.5 database and Cytoscape 3.7.2, and the core targets were screened out. DAVID 6.8 database was used for Gene Ontology(GO) func-tional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and subsequently the enrichment results were visualized through the bioinformatics platform. The mouse model of depression was induced by intraperitoneally injecting with LPS in mice. Before modeling, mice were administrated orally with EOST. The antidepressant effect of EOST was evalua-ted by tail suspension test(TST), forced swimming test(FST), and novelty suppressed feeding test(NSFT) after modeling. The content of interleukin(IL)-1β was determined by enzyme-linked immunosorbent assay(ELISA), and the protein expression levels of IL-1β and pro IL-1β in the hippocampus were determined by Western blot. There were 12 main components and 179 targets in EOAT, of which, 116 targets were related to depression, mainly involved in neuroactive ligand-receptor interaction, calcium signaling pathway, and cyclic adenosine monophosphate(cAMP) signaling pathway. Biological processes such as synaptic signal transduction, G-protein coupled receptor signaling pathway, and chemical synaptic transmission were involved. Molecular functions such as neurotransmitter receptor activity, RNA polymerase Ⅱ transcription factor activity, and heme binding were involved. In mice experiments, the results showed that EOST at 100 mg·kg~(-1) and 50 mg·kg~(-1) significantly shortened the immobility time in TST and FST as well as the feeding latency in NSFT compared with the model group, decreased the levels of serum IL-1β and NO, and reduced the protein expression levels of IL-1β and pro IL-1β in the hippocampus. In conclusion, EOST shows a good antidepressant effect in a multi-component, multi-target, and multi-pathway manner. The mechanism may be attributed to the fact that EOST can down-regulate the protein expression levels of IL-1β and pro IL-1β, decrease the release of inflammatory factors, and reduce neuroinflammation response.
Animals ; Mice ; Oils, Volatile ; Depression ; Lipopolysaccharides ; Network Pharmacology ; Databases, Genetic ; Calcium Signaling ; Disease Models, Animal

The present study aimed to explore the main active components and potential mechanisms of Panax notoginseng saponins(PNS) and osteopractic total flavone(OTF) in the treatment of osteoporosis(OP) through network pharmacology, molecular docking and in vitro cell experiments, which was expected to provide a theoretical basis for clinical applications. The blood-entering components of PNS and OTF were obtained from literature search and online database, and their potential targets were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) and SwissTargetPrediction. The OP targets were obtained by means of searching Online Mendelian Inheritance in Man(OMIM) and GeneCards. The common targets of the drug and disease were screened by Venn. Cytoscape was used to construct a "drug-component-target-disease" network, and the core components were screened according to the node degree. The protein-protein interaction(PPI) network of the common targets was constructed by STRING and Cytoscape, and the core targets were screened according to the node degree. GO and KEGG enrichment analysis of potential therapeutic targets were carried out by R language. Molecular docking was used to determine the binding activity of some active components to key targets by AutoDock Vina. Finally, HIF-1 signaling pathway was selected for in vitro experimental verification according to the results of KEGG pathway analysis. Network pharmacology showed that there were 45 active components such as leachianone A, kurarinone, 20(R)-protopanaxatriol, 20(S)-protopanaxatriol, and kaempferol, and 103 therapeutic targets such as IL6, AKT1, TNF, VEGFA and MAPK3 involved. PI3K-AKT, HIF-1, TNF and other signaling pathways were enriched. Molecular docking revealed that the core components had good binding ability to the core targets. In vitro experiments found that PNS-OTF could up-regulate the mRNA expression levels of HIF-1α, VEGFA and Runx2, indicating that the mechanism of PNS-OTF in treating OP may be related to the activation of HIF-1 signaling pathway, and thus PNS-OTF played a role in promoting angiogenesis and osteogenic differentiation. In conclusion, this study predicted the core targets and pathways of PNS-OTF in treating OP based on network pharmacology and carried out in vitro experimental verification, which reflected the characteristics of multi-component, multi-target and multi-pathway synergy of PNS-OTF, and provided new ideas for the future clinical treatment of OP.
Humans ; Molecular Docking Simulation ; Network Pharmacology ; Osteogenesis ; Phosphatidylinositol 3-Kinases ; Osteoporosis ; Databases, Genetic