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.

OBJECTIVE: To organize and display systematically the ancient medical records of stroke treated with acupuncture and moxibustion based on the knowledge element theory of information technology, so as to provide the path and paradigm for the construction of ancient acupuncture and moxibustion knowledge model. METHODS: The medical records of stroke treated with acupuncture and moxibustion were collected from the monographs of acupuncture and moxibustion and tuina, medical reports, the ancient works of traditional Chinese medicine of comprehensive collection and clinical disorders of each medical department, from the pre-Qin period to the late Qing Dynasty, collected in Zhonghua Yidian (Canon of Chinese Medicine), the fifth edition. Using "knowledge processing platform of ancient Chinese medicine books", the medical records of stroke treated with acupuncture and moxibustion in ancient time were deeply analyzed and indexed. With the MS SQL Server database adopted, the indexing results were exported into logical data; and Neo4j database was employed to build the knowledge graph of stroke treatment with acupuncture and moxibustion in ancient time. RESULTS: There were 43 medical records in 18 ancient books that met the inclusion criteria, and a logical structure was organized and composed of 65 knowledge bodies, 462 knowledge elements, 1,413 semantic types and 315 semantic associations. CONCLUSION Based on the knowledge element theory, the medical records of stroke treated with acupuncture and moxibustion in ancient time have been explored, and the logical data formed can accurately reflect the knowledge of the different attributes inside these medical records. It displays the knowledge organization category from the overall to the local. The knowledge graph generated according to the logical data is conducive to presenting the ancient acupuncture knowledge in view of the "vertical and horizontal" dimensions.
Moxibustion/history* ; Humans ; Acupuncture Therapy/history* ; Stroke/history* ; History, Ancient ; Medical Records ; China

Surgical records are the core components of medical documents in clinical centers of surgery. Standardization of surgical records contributes to standardizing surgical procedures, improving the quality of surgery, and ensuring patient safety. To ensure that surgical records more objectively, visually, and comprehensively reflect the actual surgical process, numerous high-level university hospitals' surgical centers have long adhered to the good tradition of documenting surgical records in a "combination of text and images" format. Graphic surgical records not only benefit postoperative review and structured data collection but also facilitate the implementation of high-quality clinical research and surgical training. As early as 2015, Group of Operative Surgery, Chinese Society of Surgery, Chinese Medical Association already formulated the "Expert Consensus on Advocating the use of graphic surgical records".In recent years, rapid development of information technology has provided technical support for the further promotion of graphical surgical records. After extensive and multiple rounds of professional discussions and investigations, and based on a thorough consideration of relevant national policy requirements, information standards, the 2025 edition of the "Expert Consensus" is intended to be revised, aiming to enhance the standardization of graphical surgical records, improve the quality of surgery and training system, as well as clinical researches, thereby contributing to the development of Healthy China.
Humans ; Consensus ; Medical Records

OBJECTIVES: To analyze the multimorbidity patterns and core diseases among hospitalized patients in different age groups and to explore the impacts of multimorbidity patterns on hospitalization costs. METHODS: Electronic medical records of adult inpatients (aged ≥18 years) from Ningbo Medical Center Lihuili Hospital between January 1, 2018, and June 30, 2023 were collected. The multimorbidity status involving 53 specific diseases was analyzed across different age groups. Association rule mining was used to identify common multimorbidity patterns. Complex network analysis was used to identify core diseases within the multimorbidity networks. Generalized estimating equations (GEE) were used to analyze the impact of different multimorbidity patterns on hospitalization costs. RESULTS: The prevalence of multimorbidity among the 359 402 adult inpatients was 38.51%, with higher rates observed in males (43.60%) and elderly patients (58.29%). Association rule mining identified 15 common multimorbidity patterns, which exhibited differences across age groups. The most prevalent multimorbidity pattern overall was "diabetes→hypertension" (support=7.04%, confidence=62.17%, lift=2.17). In the young adult group, the most prevalent pattern was "dyslipidemia→chronic liver disease" (support=1.19%, confidence=53.17%, lift=6.04). In the middle-aged group, it was "diabetes→hypertension" (support=4.84%, confidence=50.28%, lift=2.15). In the elderly group, it was "coronary heart disease, diabetes→hypertension" (support=2.38%, confidence=77.43%, lift=1.63). Complex network analysis revealed that the core diseases within multimorbidity networks differed across age groups. The core disease identified in the young adult group was chronic liver disease (degree centrality=50, betweenness centrality=0.055, closeness centrality=0.963). Core diseases in the middle-aged group included hypertension, chronic liver disease, and diabetes (all with degree centrality=52, betweenness centrality=0.022, closeness centrality=1.000). Core diseases in the elderly group comprised hypertension, diabetes, malignant tumors, chronic liver disease, thyroid disease, anemia, and arrhythmia (all with degree centrality=52, betweenness centrality=0.009, closeness centrality=1.000). Generalized estimating equations analysis indicated that, most multimorbidity patterns were significantly associated with increased hospitalization costs. However, the magnitude of cost increase varied across different multimorbidity patterns. Specifically, hospitalization costs for patients with patterns such as "heart failure→hypertension", "stroke→hypertension", "malignant tumor, diabetes→hypertension", "stroke, diabetes→hypertension", and "diabetes, heart failure→hypertension" were more than double those of patients without any target diseases. CONCLUSIONS Multimorbidity patterns and core diseases among hospitalized patients differ significantly across age groups, and different patterns exert varying impacts on hospitalization costs. These findings underscore the necessity for age-stratified and multimorbidity pattern specific management strategies.
Humans ; Multimorbidity ; Male ; Hospitalization/economics* ; Female ; Aged ; Middle Aged ; Adult ; Age Factors ; Young Adult ; Adolescent ; Diabetes Mellitus/epidemiology* ; Electronic Health Records ; Aged, 80 and over ; Hospital Costs ; China/epidemiology* ; Hypertension/economics* ; Liver Diseases/epidemiology*

OBJECTIVES: Accurate identification of risk factors for precocious puberty is essential for clinical diagnosis and management, yet the performance of natural language processing methods applied to unstructured electronic medical record (EMR) data remains to be fully evaluated. This study aims to assess the performance of a prompt engineering method for extracting individual risk factors of precocious puberty from EMRs. METHODS: Based on the capacity and role-insight-statement-personality-experiment (CRISPE) prompt framework, both simple and optimized prompts were designed to guide the large language model GLM-4-9B in extracting 10 types of risk factors for precocious puberty from 653 EMRs. Accuracy, precision, recall, and F1-score were used as evaluation metrics for the information extraction task. RESULTS: Under simple and optimized prompt conditions, the overall accuracy, precision, recall, and F1-score of the model were 84.18%, 98.09%, 81.99%, and 89.32% versus 97.15%, 98.31%, 98.16%, and 98.23%, respectively. The optimized prompts achieved more stable performance across age (<9 years vs ≥9 years) and visit-time (<2023 vs ≥2023) subgroups compared with simple prompts. The accuracy range for extracting each risk factor was 60.03%-97.24%, while with optimized prompts, the range improved to 92.19%-99.85%. The largest performance improvement occurred for "beverage intake" (60.03% vs 92.19%), and the smallest for "maternal age of menarche" (97.24% vs 99.23%). In comparing distributions among simple prompts, optimized prompts, and ground truth, statistically significant differences were observed for snack intake, beverage intake, soy milk intake, honey intake, supplement use, tonic use, sleep quality, and sleeping with the light on (all P<0.001), while exercise (P=0.966) and maternal menarche age (P=0.952) showed no significant differences. CONCLUSIONS Compared with simple prompts, optimized prompts substantially improved the extraction performance of individual risk factors for precocious puberty from EMRs, underscoring the critical role of prompt engineering in enhancing large language model performance.
Humans ; Puberty, Precocious/epidemiology* ; Risk Factors ; Electronic Health Records ; Female ; Child ; Natural Language Processing

BACKGROUND

Primary care for pediatric patients focuses on providing comprehensive, accessible, and coordinated healthcare from the neonatal period to adolescence. The implementation and use of electronic medical records (EMR) in pediatric primary care facilities is an efficient strategy to gather necessary information on the epidemiology of common pediatric diseases in the Philippines.

This study aimed to determine the frequency distribution of pediatric diseases in a rural primary healthcare facility in the Philippines.

This cross-sectional study reviewed the EMR of all pediatric patients who consulted in a primary care facility in Samal, Bataan from April 2019 to March 2021. Data gathered include sex, age in years, chief complaint, diagnosis, and month of consultation. Data was summarized using descriptive statistics.

A total of 14,462 pediatric consults were recorded from April 2019 to March 2021. There were slightly more male patients (52.1%). The mean age of the patients was 6.5 years (standard deviation 5.22). The highest number of consults came from the 1- to 4-year-old age group (41.5%). The most common chief complaints were cough (45.9%), fever (25.5%), and colds (24.9%). The most frequent diagnoses were upper respiratory tract infections (47.4%), followed by lower respiratory tract infections (6.9%), and skin and soft tissue infections (5.3%). Majority of the consults for respiratory tract infections, skin and soft tissue infections, gastroenteritis, asthma, and dermatitis were in the 1- to 4-year-old age group. Urinary tract infections and otitis media or externa were recorded more frequently in the 5- to 9-year-old age group.

Respiratory tract infections, followed by skin and soft tissue infections, were the most frequently identified diseases in children consulting a primary care facility at a rural site in the Philippines. The most common chief complaints, defined as the primary reason for seeking consult, were cough, fever, and colds. Data was gathered through EMR review, which may aid in the planning of programs and policies to improve primary care service delivery.

Background: Turnaround time is an integral component of primary healthcare and is a key performance indicator of healthcare delivery. It is defined as the time patients spend during a healthcare facility visit. In this study, turnaround time is defined as the time elapsed from registration to the end of consultation. Objectives: This study aimed to determine the turnaround time of consults in the primary care system in a rural site in the Philippines, and compare turnaround time during the pre-pandemic and COVID-19 pandemic periods. Methods: This is a retrospective cohort study of patients seen at the primary care facility under the Philippine Primary Care Studies (PPCS) rural site from April 2019 to March 2021. Patients included in this study were chosen through random sampling. Electronic medical records (EMR) of these patients were reviewed. Turnaround time was computed electronically from time of registration to end of consultation. Descriptive statistics was used to summarize data and report turnaround time. The turnaround time before and during the pandemic was compared using an independent sample t-test (if normally distributed) or Mann Whitney U test (if not normally distributed). A p-value of <0.05 was considered statistically significant. Results: A random sample of 342 patients out of the total 45,501 patient consults seen at the rural primary healthcare facility from April 2019 to March 2021 were included in this study. The median turnaround time was 29.0 minutes (interquartile range [IQR] 68.3), with range of 0.9 to 437.2 minutes. During the pre-pandemic period, the median turnaround time of consults is 29.3 minutes (IQR 70.4) which is 1.8 minutes longer than the pandemic period which showed median turnaround time of 27.5 minutes (IQR 72.7). The difference between the two time periods was not statistically significant (P = 0.39). Conclusion The study showed that the median turnaround time of medical consults was 29.0 minutes, which was shorter by 80 minutes compared to other published Philippine studies. The turnaround time did not differ significantly in the pandemic and prepandemic period, despite new policies and systems that were implemented during the pandemic.
primary care ; electronic medical records ; pandemic ; Philippines

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

Evaluation of primary care allows for identification of problems in the healthcare system, such as poor health outcomes, inappropriate health services, overuse of unnecessary resources, or underuse of recommended strategies. Assessment of adherence to existing clinical practice guidelines as quality indicators is critical for evaluating the effectiveness of primary care and shaping healthcare policies.

To determine the adherence of primary care providers to existing practice guidelines for common pediatric concerns in remote, rural, and urban areas in the Philippines.

This cross-sectional study included data from the electronic medical records (EMR) of patients aged 19 years and below who consulted at the three pilot sites of the Philippine Primary Care Studies (PPCS) from January to December 2019. Relevant demographic data and quality indicator measures (e.g., immunization history, adolescent smoking history, medication and supplement prescription) were extracted from the EMR by the PPCS data management team. Adherence to existing guidelines on pediatric history taking and management of common illnesses (e.g., diarrhea, upper respiratory tract infections, malnutrition) was evaluated.

This study included 8,724 pediatric patients seen across the three pilot sites from January to December 2019. Immunization history was taken in only 0.4% of pediatric patients. Smoking history was taken in only 6.8% of adolescent patients. Zinc was prescribed in only 40.1% of patients with diarrhea. No infants were prescribed with vitamin A, while iron was prescribed in only 2.5% of children and 3% of adolescent females. In contrast to the recommendations of existing guidelines, antibiotics were prescribed in 38.5% of patients with AGE and 62.5% of patients with viral URTI. Montelukast was prescribed as first-line asthma treatment in 4.7% of cases. Multivitamins were prescribed in 57.2% of all pediatric patients.

Overuse of inappropriate medications and underuse of appropriate interventions were observed in this study. There was low adherence to evaluation of pediatric immunization history, adolescent smoking history, zinc supplementation for diarrhea, and iron and vitamin A supplementation among identified vulnerable population groups. Over prescription of the following were observed: (1) antibiotics for acute gastroenteritis and probable viral URTI, (2) multivitamins for the general pediatric population, and (3) montelukast among newly diagnosed asthma patients.

BACKGROUND AND OBJECTIVES

The adoption of electronic medical records (EMRs) in the Philippines has been initiated and adjusted since the last decade through the Philippine eHealth Agenda framework. EMRs are known to improve clinical management and have been widely adopted in advanced economies. However, empirical research on EMR implementation remains limited. This study aims to determine how public primary health care facilities in the country interacted with EMRs before and during the COVID-19 pandemic to understand EMR adoption.

More than 270,000 records generated from EMR usage logs in six rural primary health facilities in Western Visayas were analyzed. Average time of EMR use during work hours was estimated and compared before and during the pandemic. EMR adoption based on specific EMR features used was also determined.

In 2020, EMR use ranged from less than one hour to more than eight hours in selected rural health units (RHUs). There was a statistical increase and decrease in use of features during the pandemic. Some EMR users had efficient use indicated by complete adoption of EMR features although such features were not as frequently used as those pertaining to basic adoption.

This study demonstrates that for EMR use in rural settings, progressive use from basic to complete may vary among users. Public health emergencies such as a pandemic may also affect EMR use. Future research directions should explore other mechanisms which affect user behavior and encourage full adoption of technology such as use of games or non-monetary incentives.