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 suitable habitat for the endangered and valuable medicinal herb Panax ginseng is gradually decreasing. It is crucial to investigate its suitable growing areas in China for global protection and sustainable utilization of P. ginseng. In this study, 371 distribution points of P. ginseng were collected, and 21 environmental factors were used as ecological indicators. The geographic information system for global medicinal plants(GMPGIS) system, MaxEnt model, and Thiessen polygon method were used to analyze the potential suitable areas for P. ginseng globally. The results showed that the key environmental variables affecting P. ginseng were precipitation in the hottest quarter(Bio18) and the coefficient of temperature seasonality(Bio4). The suitable habitats for P. ginseng were mostly located in the "One Belt, One Road" countries such as China, Japan, South Korea, North Korea, and Russia. The highly suitable habitats were mainly distributed along mountain ranges in southeastern Shandong, southern Shanxi and Shaanxi, northern Jiangsu, and northwestern Henan of China. Data analysis indicated that the current P. ginseng planting sites were all in high suitability zones, and the Thiessen polygon results showed that the geographic locations of P. ginseng production companies were unbalanced and urgently needed optimization. This study provides data support for P. ginseng planting site selection, scientific introduction, production layout, and long-term development planning.
Panax ; Ecosystem ; China ; Geographic Information Systems ; Temperature ; Plants, Medicinal

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: 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

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

OBJECTIVE: To solve the ESB bus performance and safety problems caused by the explosive growth of the hospital's business, and to ensure the stable interaction of the hospital's business system. METHODS: Taking the construction of our hospital's information system as an example, we used AlwaysOn, load balancing and other technologies to optimize the ESB bus architecture to achieve high availability and scalability of the hospital's ESB bus. RESULTS: The ESB bus high-availability architecture effectively eliminates multiple points of failure. Compared with the traditional dual-machine Cluster solution, the security is significantly improved. The nodes based on load balancing can be scaled horizontally according to the growth of the hospital's business volume. CONCLUSIONS The construction of the ESB bus high-availability architecture effectively solves the performance and security issues caused by business growth, and provides practical experience for medical information colleagues. It has certain guiding significance for the development of regional medical information.
Hospital Information Systems ; Information Systems

Background: Health information systems (HIS) such as Electronic Medical Record (EMR) systems are essential in the integration of fragmented local health systems. Investing in HIS is crosscutting; it can address multiple interrelated health system gaps. However, public health authorities, especially those in resource-constrained communities, are often faced with the dual challenge of upgrading and digitalizing local HIS and addressing other more apparent health system gaps. Objectives: The study aimed to identify and document strategies that not only motivate policy change towards adoption of electronic HIS but also address other health system gaps. Methodology: The author, in his capacity as a local health official in a resource-constrained community, developed, implemented, and documented a social marketing strategy wherein community stakeholders were influenced to invest in an electronic medical record (EMR) system because it was shown to also have the capacity to address other priority health system gaps identified. Results: The strategy, based on situational, stakeholder, and risk analyses, prompted local governance to first invest in improving the delivery of services accredited by the national health insurance program (PhilHealth), for which reimbursements would require electronically submitted claim forms. Community stakeholders then supported the proposal to invest in an EMR system because they were persuaded that it can facilitate increased financing from PhilHealth claims reimbursements, which could be used to enable not only improvement in existing health services but to also initiate other health programs. Conclusion Social marketing using the perspective of health as an investment influenced stakeholders to invest in an EMR system.
Public Health ; Health Information Systems ; Health Communication ; Social Marketing

Objectives: Since the effectiveness of the Zero Open Defecation (ZOD) program as a scaling-up approach in lowering the rates of soil-transmitted helminth (STH) infections has not yet been locally explored, this study aimed to (1) describe the association between environmental determinants and STH cumulative prevalence, and (2) to predict the 2020 STH cumulative prevalence. Methods: A generalized linear regression (GLR) model was used to determine the association of 2014–2015 environmental determinants and observed 2015 STH cumulative prevalence, while a geographically weighted regression (GWR) model was used to produce predicted 2020 STH cumulative prevalence. Results: ArcGIS’ GLR tool with R2 of 63% found that statistically significant environmental determinants include distance near to water bodies, forest land use, access to sanitary toilet, level one water source, and ZOD status, while the ArcGIS’ GWR tool found that barangays, Cabangcalan, Matalangtalang, Talabaan, and Talib in Aroroy hypothetically met the national target below 30% for 2020 STH cumulative prevalence. Conclusion This study showed that barangays with a moderately low percentage of area with freshwater bodies, a moderately high percentage of households with sanitary toilet and level one water source, and a 100% status of ZOD have lower rates of STH cumulative prevalence in preschool-aged children in the selected municipalities in Masbate.
Mass Drug Administration ; Hygiene ; Sanitation ; Geographic Information Systems

Dengue is a global health issue and is also regarded as one of the major public health concerns in the Philippines. Presented in this paper is the application of a geographic information system (GIS) in mapping dengue cases in Baguio City. A descriptive research design was utilized and mapped dengue cases were reconciled with environmental correlates such as land cover, housing information (independent, mixed, or interconnected), hydrology (water bodies and canals), urbanization level (urban or rural), elevation, soil, and land surface temperature. Moreover, demographic factors and practices were utilized for further analysis. Results show that interconnected housing, urbanization, land surface temperature, hydrology, and population density are predictors of dengue cases in Baguio City with the predictive power of 0.3810 (strong), 0.3426 (strong), 0.2509 (medium), 0.1675 (medium), and 0.1323 (medium), respectively. In the context of dengue, several data gaps in health information systems exist. Although the Manual of Procedures for the Philippine Integrated Disease Surveillance and Response (PIDSR) published by the Department of Health (DOH) of 2014 provides a detailed guide in the management and surveillance of communicable disease, the use of GIS was noted to be unspecified. Using GIS provides the possibility of harmonizing several data sets to better inform policymakers.
Dengue ; Geographic Information Systems