Human ; Research ; Information Dissemination ; Reference Standards

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.

OBJECTIVES

To assess the clients’ perceptions of the UP College of Pharmacy (UPCP) Telepharmacy Service on their knowledge, decision-making, and medication safety.

The study employed a cross-sectional design administered through guided voice-call interviews using an online survey questionnaire as the data collection instrument. The inclusion criteria of the study were as follows: (1) must be at least 18 years old, (2) with no cognitive impairment, (3) must have sent a medication-related query in the UPCP Telepharmacy Service between October 2020 and July 2022, and (4) must be contacted through voice call platforms.

A total of 72 respondents participated in the study. Majority were from 30 to 59-year-old age category (51.39%), females (72.22%), from Region IV-A (36.11%), college graduates (44.44%), and with average monthly income of below PhP 11,000 (47.22%). Overall, clients reported very positive perceptions on the drug information advice received (X̅4.510) and were very satisfied with the service (X̅ 4.625). They perceived that the advice influenced their decision-making about their medications (X̅ 4.514) and increased their understanding of medication safety (X̅ 4.522). Multiple regression analysis revealed that clients’ perception on drug information advice is positively associated with perceived effect on decision-making (r = 0.5033; p = 0.000) and medication safety (r = 0.4320; p = 0.004).

The pharmacist-led drug information service, such as the UPCP Telepharmacy Service, is a helpful program to provide accurate and reliable medication information to clients who need them amidst the increasing accessibility of medical information on the internet. It can help improve knowledge of patients about appropriate use of medicines, drug interactions, and adverse drug reactions that will enable them to make informed decisions regarding their medications, identify the need to consult with healthcare providers, and ultimately ensure medication safety.

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

BACKGROUND: Before the COVID-19 vaccine became available, many Japanese people were undecided about whether or not to receive them. Their decisions were keys to achieving herd immunity. The impact of the type of information source on the COVID-19 vaccine uptake decision-making process remains unclear. We aimed to investigate the association between information source usage on COVID-19 and subsequent vaccine uptake status among those who have yet to decide whether to receive vaccines from non-prioritized people for vaccination. METHODS: Prospective cohort online self-administered surveys were conducted in February 2021 (T1), before the start of the mass vaccination program, and September-October 2021 (T2), when the vaccines were available to all citizens. The survey's target population was registered monitors of an Internet research company. Participants who answered "I want to get vaccinated after waiting to see how it goes." at T1 were eligible for analysis. The outcome variable was the COVID-19 vaccine uptake status in T2, and the predictors were 20 types of information sources, categorized based on people (family members, etc.), institutions (governments, etc.), or media (TV news, etc.). Adjusted odds ratio and 95% confidence intervals were estimated using logistic regression adjusted for possible confounders. RESULTS: The 5,139 respondents, mean age and standard deviation was 42.8 ± 12.5, 55.7% female, were eligible for analysis. 85.7% completed vaccination (including reserved/intended people) in T2. In the multivariate logistic analysis, odds ratios (95% confidence interval) for vaccine uptake were 1.49 (1.18-1.89) for workplaces/schools, 1.81 (1.33-2.47) for LINE, 0.69 (0.55-0.86) for Internet news and 0.62 (0.48-0.82) for video sharing sites. CONCLUSIONS The type of information source usage played an important role in the decision to vaccinate against COVID-19. Although caution is needed in interpreting the results, obtaining information from workplaces/schools and LINE was influential in promoting immunization.
Humans ; Female ; Male ; Information Sources ; COVID-19 Vaccines ; Prospective Studies ; Intention ; Japan ; COVID-19/prevention & control* ; Vaccination

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

The common data model (CDM) is an important tool to facilitate the standardized integration of multi-source heterogeneous healthcare big data, enhance the consistency of data semantic understanding, and promote multi-party collaborative analysis. The data collections standardized by CDM can provide powerful support for observational studies, such as large-scale population cohort study. This paper provides an in-depth comparative analysis of the data storage structure, term mapping pattern, and auxiliary tools development of the three international typical CDMs, then analyzes the advantages and limitations of each CDM and summarizes the challenges and opportunities faced in the CDM application in China. It is expected that exploring the advanced technical concepts and practical patterns of foreign countries in data management and sharing will provide references for promoting FAIR (findable, accessible, interoperable, reusable) construction of healthcare big data in China and solving the current practical problems, such as the poor quality of data resources, the low degree of semantization, and the inabilities of data sharing and reuse.
Humans ; Big Data ; China ; Cohort Studies ; Data Collection ; Information Dissemination

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