Search

Background We developed an artificial neural network (ANN) model to predict prostate cancer pathological staging in patients prior to when they received radical prostatectomy as this is more effective than logistic regression (LR), or combined use of age, prostate-specific antigen (PSA), body mass index (BMI), digital rectal examination (DRE), trans-rectal ultrasound (TRUS), biopsy Gleason sum, and primary biopsy Gleason grade. Methods Our study evaluated 299 patients undergoing retro-pubic radical prostatectomy or robotic-assisted laparoscopic radical prostatectomy surgical procedures with pelvic lymph node dissection. The results were intended to predict the pathological stage of prostate cancer (T2 or T3) after radical surgery. The predictive ability of ANN was compared with LR and validation of the 2007 Partin Tables was estimated by the areas under the receiving operating characteristic curve (AUCs). Results Of the 299 patients we evaluated, 109 (36.45%) displayed prostate cancer with extra-capsular extension (ECE), and 190 (63.55%) displayed organ-confined disease (OCD). LR analysis showed that only PSA and BMI were statistically significant predictors of prostate cancer with capsule invasion. Overall, ANN outperformed LR significantly (0.795 ± 0.023 versus 0.746 ± 0.025, p = 0.016). Validation using the current Partin Tables for the participants of our study was assessed, and the predictive capacity of AUC for OCD was 0.695. Conclusion ANN was superior to LR at predicting OCD in prostate cancer. Compared with the validation of current Partin Tables for the Taiwanese population, the ANN model resulted in larger AUCs and more accurate prediction of the pathologic stage of prostate cancer. [ABSTRACT FROM AUTHOR]

Sex-related factors play an important role in the pathophysiology of heart failure (HF). However, trends in sex-related differences in hospital management for HF are not clear. We identified patients hospitalized for HF through a nationwide database (National Health Insurance in Taiwan), containing 722,272 subjects from 1999 to 2008. Higher incidences of diabetes mellitus (37 vs. 25 %, p < 0.001), thyroid dysfunction (2 vs. 0 %, p < 0.001), and transient cerebral ischemia (2 vs. 1 %, p < 0.05), as well as a lower incidence of chronic lung disease (14 vs. 22 %, p < 0.001) differentiated female HF patients from male HF patients. During this 10-year period, both percentage of HF hospitalization and age-adjusted HF rates significantly increased for total HF sample (1.92 vs. 2.49  ‰, p < 0.05, and 20.44 vs. 27.38/100,000, p < 0.05) and for female (1.76 vs. 2.86  ‰, p < 0.05, and 20.94 vs. 32.12/100,000, p < 0.05), but such changes did not occur among male patients (2.12 vs. 2.09  ‰, p > 0.05, and 19.93 vs. 22.51/100,000, p > 0.05). The age at the time of hospitalization and the length of the hospital stay increased significantly for all HF patients during the 10-year study period. However, the daily cost of hospitalization increased in males, but not in females. Compared to the survivors, patients who died were older and had a longer hospitalization and higher daily cost both in males and females. Through our analysis of the NHI database, we observed trends in factors related to hospitalization of HF patients in Taiwan that may be attributable to sex-related differences in the pathophysiology and treatment strategies for HF. [ABSTRACT FROM AUTHOR]

The present study investigated dietary intake, glucose metabolism and sex hormones in women with polycystic ovary syndrome (PCOS). A total of forty-five women (aged 25–40 years) with PCOS and 161 control women (aged 25–43 years) with non-PCOS-related infertility were recruited. Anthropometry, glucose tolerance and sex hormones were determined and dietary intake was assessed. Women with PCOS had lower serum sex hormone-binding globulin and increased BMI, waist:hip ratio, luteinising hormone, ratio of luteinising hormone:follicle-stimulating hormone, testosterone and free androgen index (FAI). Postprandial glucose, fasting insulin and insulin resistance were elevated in women with PCOS. Women with PCOS had reduced energy and carbohydrate intake but higher fat intake. Serum sex hormone-binding globulin level was negatively associated with BMI in both groups and negatively correlated with macronutrient intake in the PCOS group with hyperandrogenism. However, FAI was positively correlated with BMI, waist circumference and glucose metabolic parameters in both groups. Therefore, women with PCOS consume lower energy and carbohydrate compared with those with non-PCOS-related infertility and macronutrient intake is only negatively associated with serum sex hormone-binding globulin level in the PCOS group with hyperandrogenism. [ABSTRACT FROM PUBLISHER]

Abstract: This paper presents a research of constructing a web-based expert system for nutrition diagnosis by utilizing the expert system techniques in artificial intelligence. The research implements Nutritional Care Process and Model (NCPM) defined by American Dietetic Association (ADA) in 2008 and integrate the nutrition diagnosis knowledge from dietetics professionals to establish the basics of building the rule-based expert system with its knowledge base. The system is built using Microsoft Visual Studio 2008 on .NET Framework 3.5SP1 utilizing the built in rule engine which comes with Windows Workflow Foundation. With the help of this system, it is easier for dietetics professionals to adapt to the newly introduced concept of nutrition diagnosis. At the heart of the web based expert system is a knowledge base, it has a rule engine which contains the nutrition diagnosis rules converted from signs and symptoms for nutrition diagnosis from dietetics professionals and are expressed in XML format which are then stored in a SQL database. A knowledge engineer will be able to use a rule editor to add new rules or to update existing rules within the rule database. Dietetics professionals would be able to enter patient’s basic data, anthropometric data, physical exam findings, biochemical data, and food/nutrition history into the program. After dietetics professionals complete nutrition assessment, the program will make inference to the rule base and make nutrition diagnosis. Dietetics professionals could then make the final diagnosis decision for the patient based on the diagnosis report generated by the web based nutrition diagnosis expert system. For this study, I have selected 100 chronic kidney disease patients under hemodialysis from a university hospital, recorded their albumin, cholesterol, creatinine before dialysis, height, and dry weight and then use these data to perform nutrition diagnosis with both the expert system and a practicing dietitian. After comparing the result, I found that the expert system is faster and more accurate than human dietitian. [Copyright &y& Elsevier]

Abstract: Background: Adverse drug reactions increase morbidity and mortality, and potential drug interactions (DIs) increase the probability of adverse drug reactions. Objectives: To survey the potential DIs of dermatologic outpatient prescriptions from the National Health Insurance Research Database of Taiwan. Methods: All prescriptions written by dermatologists in 2000 were analyzed to identify potential DIs among drugs appearing on the same prescription sheet. Results: Of 150.6 million prescription sheets with 669.5 million prescriptions registered in the National Health Insurance Research Database of Taiwan, we identified 6.6 million (4.4%) dermatology prescription sheets with 19 million (2.8%) prescriptions. The findings of the study showed that 283,458 potential DIs were found in this category, accounting for 1.49% per prescription. The most common significance Level 1 interaction (1.1%) was between the less-sedative antihistamines (terfenadine/astemizole) and azole antifungal agents. Among the category of severity, the most common was terfenadine interacting with cimetidine and ketoconazole (4.4%), followed by astemizole interacting with cimetidine and ketoconazole (2.9%). The most common drug class interaction occurred between corticosteroids and antacids (48.5%). Overall, DI incidence in dermatologic patients was lower than that of the general patient population. Conclusions: Based on the study findings, we concluded that dermatologists need to be reminded of having possible potential DIs when prescribing medications. Introducing information technology into the computerized physician order entry system into the daily practice may reduce potential DIs. [Copyright &y& Elsevier]

Abstract: Personal Health Record (PHR) systems are growing in popularity and are receiving increased attention from the Biomedical Informatics research community. Information Collection is one PHR research topic and includes system functionality that helps patients retrieve their data from external sources. One of the most potentially useful external sources of information is the data stored in patients’ EHRs at medical institutions. PHR systems that support Information Collection from EHR systems are thus interesting to investigate. In this paper we present PHR system that allows patients to receive data from 10 participating hospitals in Taiwan via a USB flash memory device. The overall design goals and architecture for the system are presented. Based on our experiences in designing and implementing the system we propose a three step method for accomplishing Information Collection from EHR systems at medical institutions for similar PHR systems in the future. [Copyright &y& Elsevier]

This paper compares the interoperability approaches of three countries: Taiwan, Denmark and Canada. The work maps out how various countries have addressed the interoperability problems as well as what factors affect decisions and the result, and in what manner. The key findings are as follows: (1) The federal government's ability to mandate standards affects choice of interoperability strategy; (2) E-Health status influences choice of interoperability strategy; (3) Differences in geography, population, and demographics affect the selection of national strategies towards interoperability. [ABSTRACT FROM AUTHOR]

Based on researches, the most time-consuming nursing activities, in teaching hospital, are: room patrols, the blood pressure survey, the body temperature pulse breath survey, the nursing record maintenance [1]. The nursing record is one way to communicate data. It can allow the medical service team to understand what measures the nursing staff once did for sickness, as well as responses from sickness. Nevertheless, it is the key component to utilize the record with a clinical nursing plan, so as to provide a proficient health management. Since the maintenance of nursing plan is costly and time-consuming, therefore, it is essential to establish the nursing plan information system, which can effectively promote the nursing quality. This research main body comes from one infectious disease division nursing plan information system, which was developed in 1992, and its data base covers entire courtyard compatibility and various faculties characteristic nursing plan. The nursing staff often complained that this system is not user-friendly, its contents are not comprehensive, and sometimes it does not let staff choose the right diagnosis. Therefore this research is based on history analysis and the questionnaire survey procedure first, the infectious disease nursing plan use number of times, the frequency and the project content, then by the literature scientific theory and result of the improvement group discussion together. The original 38 infectious disease division nursing plan will be expanded to 45 nursing plans. Moreover, the common 38 infectious disease code (ICD-9), and its corresponding diagnosis items, shall automatically appear in the disease diagnose code field, so it would be better off for the nursing staff to set up the nursing plan efficiently. Infectious disease division nursing plan information system utilization ratio is promoted 9.6-folds, according to research outcome. Each task consumes 3.68 minutes beforehand—including computer program operation, the printing of nursing plan, and now it turned out that it shall not take more than 3.08 minutes. The time efficiency is raised by 17% (0.6 minute). Yet only 17% of the users are satisfied with it before, and now 74% nursing staffs are happy with the new tool.Therefore, it shall not only improve our service quality, but also save labor cost by using this information supplementary system. [ABSTRACT FROM AUTHOR]

Simple Summary: Pancreatic cancer has been ranked seventh in the top ten cancer mortality rates for the past three year in Taiwan. It is one of the more difficult cancers to detect early due to the lack of early diagnostic tools. This is a population-based study from NHIRD. A higher performance pancreatic cancer prediction model has been established. This predictive model can improve the awareness of the risk of pancreatic cancer and give patients with pancreatic cancer a simpler tool for early screening in the golden period when the disease can still be eradicated. (1) Background: Cancer has been the leading cause of death in Taiwan for 39 years, and among them, pancreatic cancer has been ranked seventh in the top ten cancer mortality rates for the past three years. While the incidence rate of pancreatic cancer is ranked at the bottom of the top 10 cancers, the survival rate is very low. Pancreatic cancer is one of the more difficult cancers to detect early due to the lack of early diagnostic tools. Early screening is important for the treatment of pancreatic cancer. Only a few studies have designed predictive models for pancreatic cancer. (2) Methods: The Taiwan Health Insurance Database was used in this study, covering over 99% of the population in Taiwan. The subset sample was not significantly different from the original NHIRD sample. A machine learning approach was used to develop a predictive model for pancreatic cancer disease. Four models, including logistic regression, deep neural networks, ensemble learning, and voting ensemble were used in this study. The ROC curve and a confusion matrix were used to evaluate the accuracy of the pancreatic cancer prediction models. (3) Results: The AUC of the LR model was higher than the other three models in the external testing set for all three of the factor combinations. Sensitivity was best measured by the stacking model for the first factor combinations, and specificity was best measured by the DNN model for the second factor combination. The result of the model that used only nine factors (third factor combinations) was equal to the other two factor combinations. The AUC of the previous models for the early assessment of pancreatic cancer ranged from approximately 0.57 to 0.71. The AUC of this study was higher than that of previous studies and ranged from 0.71 to 0.76, which provides higher accuracy. (4) Conclusions: This study compared the performances of LR, DNN, stacking, and voting models for pancreatic cancer prediction and constructed a pancreatic cancer prediction model with accuracy higher than that of previous studies. This predictive model will improve awareness of the risk of pancreatic cancer and give patients with pancreatic cancer a simpler tool for early screening in the golden period when the disease can still be eradicated. [ABSTRACT FROM AUTHOR]

The nursing process consists of five interrelated steps: assessment, diagnosis, planning, intervention, and evaluation. In the nursing process, the nurse collects a great deal of data and information. The amount of data and information may exceed the amount the nurse can process efficiently and correctly. Thus, the nurse needs assistance to become proficient in the planning of nursing care, due to the difficulty of simultaneously processing a large set of information. Computer systems are viewed as tools to expand the capabilities of the nurse's mind. Using computer technology to support clinicians' decision making may provide high-quality, patient-centered, and efficient healthcare. Although some existing nursing information systems aid in the nursing process, they only provide the most fundamental decision support – i.e., standard care plans associated with common nursing diagnoses. Such a computerized decision support system helps the nurse develop a care plan step-by-step. But it does not assist the nurse in the decision-making process. The decision process about how to generate nursing diagnoses from data and how to individualize the care plans still reminds of the nurse. The purpose of this study is to develop a pilot structure in electronic nursing record system integrated with international nursing standard for improving the proficiency and accuracy of plan of care in clinical pathway process. The proposed pilot systems not only assist both student nurses and nurses who are novice in nursing practice, but also experts who need to work in a practice area which they are not familiar with. [ABSTRACT FROM AUTHOR]

The nursing process consists of five interrelated steps: assessment, diagnosis, planning, implementation, and evaluation. In the nursing process, the nurse confronts a great deal of data and information. The amount of data and information may exceed the amount the nurse can process efficiently and correctly. Thus, the nurse needs assistance to become proficient in the planning of nursing care, due to the difficulty of simultaneously processing a large set of information. Thus, some form of assistance will be needed to help nurses to become more proficient in planning nursing care. Using computer technology to support clinicians' decision making may provide high-quality, patient-centered, and efficient healthcare. Although some existing nursing information systems aid in the nursing process, they only provide the most rudimentary decision support – i.e., standard care plans associated with common nursing diagnoses. Such a computerized decision support system helps the nurse develop a care plan step-by-step. But it does not assist the nurse in the decision-making process. The decision process about how to derive nursing diagnoses from data and how to individualize the care plans still remains in the mind of the nurse. The purpose of this study is to develop a pilot structure in an electronic nursing record system integrated with international nursing standards for improving the proficiency and accuracy of the plan of care in the clinical pathway process. The pilot system has shown promise in assisting both student nurses and beginner nurses. It also shows promise in helping experts who need to work in a practice area that is outside of their immediate domain. [ABSTRACT FROM AUTHOR]

Background and objectives: Insulin resistance (IR) is frequently associated with chronic low-grade inflammation and has an important role as a mediator in the development of liver disease. Thus, this study aimed to explore the relationship between two indexes of IR and abnormal liver function parameters. Materials and Methods: This cross-sectional study obtained data of 41,510 men and 92,357 women aged ≥30 years from a private health screening institute in Taiwan. Two IR indexes namely triglyceride-glucose (TyG) index and triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio were used to examine their relationship to predict abnormal liver function parameters (aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), and alkaline phosphatase (ALP)). Results: Positive trend was shown for the association of TyG index in the highest quintile (Q5) and risk of high AST (OR = 1.45, 95% CI: 1.33–1.57), high ALT (OR = 1.85, 95% CI: 1.73–1.97), high GGT (OR = 2.04, 95% CI: 1.93–2.15), and high ALP (OR = 1.13, 95% CI: 1.07–1.19) compared with the median quintile (Q3) in the fully adjusted model. Similarly, participants in the Q5 of the TG/HDL-C ratio were associated with 1.38 (95% CI: 1.27–1.49), 1.71 (95% CI: 1.61–1.82), 1.75 (95% CI: 1.66–1.84), and 1.21 (1.16–1.27) odds for having high AST, ALT, GGT, and ALP respectively. The AUC (95% CI) value of the TyG index for predicting high AST, high ALT, and high GGT was 0.699 (0.692–0.705), 0.738 (0.734–0.742), and 0.752 (0.749–0.755), respectively. Meanwhile, the AUC (95% CI) of the TG/HDL-C ratio for predicting high AST, high ALT, and high GGT was 0.680 (0.673–0.686), 0.738 (0.734–0.742), 0.734 (0.731–0.738), respectively. Conclusions: Our study supported that the TyG index and TG/HDL-C ratio may be useful as non-invasive methods to predict the existence of impaired liver function in the early stage. [ABSTRACT FROM AUTHOR]

While diet and lifestyle are independently implicated in the etiology of liver disease, the interaction of diet and lifestyle may be more helpful for determining the risk of liver abnormality. Thus, our study aimed to evaluate the interaction between the dietary pattern associated with liver biomarkers and lifestyle factors among Taiwanese adults with abnormal liver enzymes. A liver-associated dietary pattern, generated using reduced rank regression, was characterized by high intake of soy sauce or other dips, sugar sweetened beverages, and preserved and processed foods, but low intake of seafood, fruits, eggs, and dark-colored vegetables. In the fully adjusted model, liver-associated dietary patterns or unhealthy concordance lifestyle factors were associated with an increased risk of having liver function abnormality (OR = 1.08, 95% CI: 1.04, 1.12 and OR = 1.42, 95% CI: 1.31, 1.53, respectively). Moreover, the interaction between liver-associated dietary pattern and unhealthy concordance lifestyle factors showed more significant correlation, with an elevated risk of abnormal liver function (OR = 2.14, 95% CI: 2.02, 2.26). Therefore, our study suggests that participants who have a strong liver-associated dietary pattern along with unhealthy concordance lifestyles are likely to have increased odds of abnormal liver function. [ABSTRACT FROM AUTHOR]

Background and Objective: Logical Observation Identifiers Names and Codes (LOINC) is a universal standard for identifying laboratory tests and clinical observations. It facilitates a smooth information exchange between hospitals, locally and internationally. Although it offers immense benefits for patient care, LOINC coding is complex, resource-intensive, and requires substantial domain expertise. Our objective was to provide training and evaluate the performance of LOINC mapping of 20 pathogens from 53 hospitals participating in the National Notifiable Disease Surveillance System (NNDSS). Methods: Complete mapping codes for 20 pathogens (nine bacteria and 11 viruses) were requested from all participating hospitals to review between January 2014 and December 2016. Participating hospitals mapped those pathogens to LOINC terminology, utilizing the Regenstrief LOINC mapping assistant (RELMA) and reported to the NNDSS, beginning in January 2014. The mapping problems were identified by expert panels that classified frequently asked questionnaires (FAQs) into seven LOINC categories. Finally, proper and meaningful suggestions were provided based on the error pattern in the FAQs. A general meeting was organized if the error pattern proved to be difficult to resolve. If the experts did not conclude the local issue's error pattern, a request was sent to the LOINC committee for resolution. Results: A total of 53 hospitals participated in our study. Of these, 26 (49.05%) used homegrown and 27 (50.95%) used outsourced LOINC mapping. Hospitals who participated in 2015 had a greater improvement in LOINC mapping than those of 2016 (26.5% vs. 3.9%). Most FAQs were related to notification principles (47%), LOINC system (42%), and LOINC property (26%) in 2014, 2015, and 2016, respectively. Conclusions: The findings of our study show that multiple stage approaches improved LOINC mapping by up to 26.5%. [ABSTRACT FROM AUTHOR]

Purpose: Vitamin D supplementation positively impacts anemia, but the relationship between a ferritin-related dietary pattern, iron parameters, and vitamin D in anemia is unclear. Methods: This cross-sectional study analyzed data from the 2017–2019 National Nutrition and Health Survey, including 1423 pregnant women over 15 years old. Dietary intake was assessed using a semi-quantitative food frequency questionnaire and a 24-hour dietary recall. The FrDP was identified using reduced rank regression with blood parameters as response variables and 32 food groups as predictors. Linear and binomial logistic regression analyses evaluated the associations between the FrDP and serum biomarkers, adjusting for demographic and dietary variables. Risk associations between the FrDP and vitamin D concentrations were also assessed. Results: The FrDP explained 18.5% of the variation in 6 response variables and was characterized by high consumption of fish, soy, gluten pasta, nuts, organ meat, pickled vegetables, and marine plants. The FrDP correlated positively with serum hemoglobin (r = 0.76), iron (r = 0.52), ferritin (r = 0.79), folate (r = 0.86), and vitamin B12 (r = 0.86). Linear regression revealed a positive association between the FrDP and serum iron. Women in the highest FrDP tertile were less likely to have low serum iron (OR = 0.65, 95% CI 0.50–0.85) but more likely to have low 25(OH) vitamin D concentrations (OR = 1.79, 95% CI 1.32–2.43). Conclusions: The FrDP was positively associated with serum iron but negatively associated with serum 25(OH) vitamin D in pregnant women. [ABSTRACT FROM AUTHOR]

This study explored the association between dietary patterns and kidney function parameters in adults with metabolic syndrome in Taiwan. This cross-sectional study was undertaken in 56,476 adults from the health screening centers in Taiwan from 2001 to 2010. Dietary intake and dietary patterns were assessed using a food frequency questionnaire and principal component analysis, respectively. Blood urea nitrogen (BUN), creatinine, estimated glomerular filtration rate (eGFR), and uric acid were measured as clinical parameters of kidney function. Multivariate linear regression was conducted to explore the relationship between dietary patterns and kidney function parameters. After adjusting for confounders, the highest tertiles of the processed food–sweets dietary pattern and the meat–seafood–eggs dietary pattern were associated with increased BUN, creatinine, and uric acid but decreased eGFR (all adjusted p < 0.05). Meanwhile, the highest tertiles of the veggie–fruit–grains dietary pattern and the milk–dairy dietary pattern were associated with decreased BUN, creatinine, and uric acid but increased eGFR (all adjusted p < 0.05). A processed food–sweets dietary pattern or a meat–seafood–eggs dietary pattern is associated with worse kidney function parameters in adults with metabolic syndrome. In contrast, a veggie–fruit–grains dietary pattern or a milk–dairy dietary pattern is associated with better kidney function parameters. [ABSTRACT FROM AUTHOR]

Personal health records (PHRs) have lots of benefits for things such as health surveillance, epidemiological surveillance, self-control, links to various services, public health and health management, and international surveillance. The implementation of an international standard for interoperability is essential to accessing personal health records. In Taiwan, the nationwide exchange platform for electronic medical records (EMRs) has been in use for many years. The Health Level Seven International (HL7) Clinical Document Architecture (CDA) was used as the standard of the EMRs. However, the complication of implementing CDA became a barrier for many hospitals to realize the standard EMRs. In this study, we implemented a Fast Healthcare Interoperability Resources (FHIR)-based PHR transformation process including a user interface module to review the contents of PHRs. We used "My Health Bank, MHB", a PHR data book developed and issued to all people by the Taiwan National Health Insurance, as the PHRs contents in this study. Network Time Protocol (NTP)/Simple Network Time Protocol (SNTP) was used in the security and user authentication mechanism when processing and applying personal health information. Transport Layer Security (TLS) 1.2 (such as HyperText Transfer Protocol Secure (HTTPS) was used for protection in data communication. User authentication is important in the platform. OAuth (OAuth 2.0) was used as a user authentication mechanism to confirm legitimate user access to ensure data security. The contents of MHB were analyzed and mapped to the FHIR, and then converted to FHIR format according to the mapping logic template. The function of format conversion was carried out by using ASP.NET. XPath and JSPath technologies filtered out specific information tags. The converted data structure was verified through an HL7 Application Programming Interface (HAPI) server, and a new JSON file was finally created. This platform can not only capture any PHR based on the FHIR format but also publish FHIR-based MHB records to any other platform to bridge the interoperability gap between different PHR systems. Therefore, our implementation/application with the automatic transformation from MHB to FHIR format provides an innovative method for people to access their own PHRs (MHB). No one has published a similar application like us using a nationwide PHR standard, MHB, in Taiwan. The application we developed will be very useful for a single person to use or for other system developers to implement their own standard PHR software. [ABSTRACT FROM AUTHOR]

Background: Personal health record (PHR) security, correctness, and protection are essential for health and medical services. Blockchain architecture can provide efficient data retrieval and security requirements. Exchangeable PHRs and the self-management of patient health can offer many benefits to traditional medical services by allowing people to manage their own health records for disease prevention, prediction, and control while reducing resource burdens on the health care infrastructure and improving population health and quality of life.Objective: This study aimed to build a blockchain-based architecture for an international health record exchange platform to ensure health record confidentiality, integrity, and availability for health management and used Health Level 7 Fast Healthcare Interoperability Resource international standards as the data format that could allow international, cross-institutional, and patient/doctor exchanges of PHRs.Methods: The PHR architecture in this study comprised 2 main components. The first component was the PHR management platform, on which users could upload PHRs, view their record content, authorize PHR exchanges with doctors or other medical health care providers, and check their block information. When a PHR was uploaded, the hash value of the PHR would be calculated by the SHA-256 algorithm and the PHR would be encrypted by the Rivest-Shamir-Adleman encryption mechanism before being transferred to a secure database. The second component was the blockchain exchange architecture, which was based on Ethereum to create a private chain. Proof of authority, which delivers transactions through a consensus mechanism based on identity, was used for consensus. The hash value was calculated based on the previous hash value, block content, and timestamp by a hash function.Results: The PHR blockchain architecture constructed in this study is an effective method for the management and utilization of PHRs. The platform has been deployed in Southeast Asian countries via the Asia eHealth Information Network (AeHIN) and has become the first PHR management platform for cross-region medical data exchange.Conclusions: Some systems have shown that blockchain technology has great potential for electronic health record applications. This study combined different types of data storage modes to effectively solve the problems of PHR data security, storage, and transmission and proposed a hybrid blockchain and data security approach to enable effective international PHR exchange. By partnering with the AeHIN and making use of the network's regional reach and expert pool, the platform could be deployed and promoted successfully. In the future, the PHR platform could be utilized for the purpose of precision and individual medicine in a cross-country manner because of the platform's provision of a secure and efficient PHR sharing and management architecture, making it a reasonable base for future data collection sources and the data analytics needed for precision medicine. [ABSTRACT FROM AUTHOR]

The best cochlear–neural delay model for designing a chirp that can produce the largest auditory brainstem response (ABR) has not been established. This study comprised two experiments. Experiment I aimed to estimate the delay model by measuring derived-band ABR latencies at different levels. The results demonstrated that, as the level decreased, the delay between the center frequencies of 0.7 and 5.7 kHz increased. The aim of experiment II was to compare ABRs generated by three stimuli: (1) a level-dependent derived-band (DB)-Chirp, designed based on the model in experiment I; (2) a level-dependent level specific (LS)-Chirp from Kristensen and Elberling [(2012). J. Am. Acad. Audiol. 23, 712–721]; and (3) a click. The results demonstrated that the DB-Chirp produced significantly larger wave V than the LS-Chirp at 45 dB normal hearing level (nHL); however, no differences were observed at other levels. The wave I generated by the DB-Chirp and LS-Chirp were significantly larger than those evoked by the click at 45 and 60 dB nHL and at 30 and 45 dB nHL, respectively; however, at all levels, no differences between these two chirps were observed. The DB-Chirp may be a valuable stimulus for producing ABRs for clinical applications such as assessing cochlear synaptopathy and estimating hearing sensitivity. [ABSTRACT FROM AUTHOR]

• The short version of HLS-EU-Q47 was needed to construct and to apply in health literacy research in Indonesia because the previous health literacy study using HLS-EU-Q47 found difficulties on the interviewing process because the time-consuming of the interview. • This is the first study applied data mining technique to form a short questionnaire on health literacy research. • A data mining technique using feature selection can be applied to develop a short version of the questionnaire and has been proven to have better accuracy compared to the short versions generated by a traditional statistical technique. • The combination between genetic and k-NN algorithm make the selection of the features more precise to predict the label even though fewer features are included in the construct of the questionnaire. • The result of the study (HLS-EU-SQ10 IDN) as the measurement tool of health literacy in Indonesia should accustom in Indonesia's circumstances. HLS-EU-SQ10 IDN focus on features of finding information on health because health information seeking behavior still challenging in developing countries such as Indonesia even though for the health care professionals. Measuring health literacy becomes more important because its association with health status and healthcare outcomes. Studies have developed at least 133 measurement tools for health literacy. HLS-EU-Q47 is a questionnaire consisting of 12 sub-dimensions and 47 questions developed by the Europe Health Literacy Consortium. Many countries in Europe and Asia have used HLS-EU-Q47 as a tool for measuring health literacy in the general public. Indonesia has conducted general health literacy survey using HLS-EU-Q47 but finding the difficulties because of the time-consuming interview. A shorter version of HLS-EU-Q47 is needed to apply in health literacy researches in Indonesia. This paper reports the results of feature reduction to develop a short Indonesian version HLS-EU questionnaire and measures the accuracy of the model compared with other short form like HLS-EU-SQ16 or HLS-SF12. The analysis was performed on a population-based dataset from Indonesia-Semarang Health Literacy Survey for which there were specific target variables as the classification of health literacy level. All attributes were assessed as potential targets in the models derived from the full dataset and its subsets. The feature selection methods with genetic algorithm were used as the filter as well as validation (cross validation) and classification (k-NN:k-nearest neighbor). The predictive accuracy of health literacy level and the complexity of models based on the reduced datasets were compared among the methods and other short versions such as HLS-EU-SQ16, HLS-SF12. The accuracy of the existing short form models were 90.64% with the HLS-EU-SQ16 and 88.67% with the HLS-SF12. This study proposed a model with 10 features as the construct of a short Indonesian-version (proposed as the HLS-EU-SQ10-IDN) since the model was with higher accuracy than the HLS-SF12, but fewer features for measuring general health literacy index. Moreover, the short version only completed part of 12 dimensions of the full questionnare. A data mining technique using feature selection with combination of genetic algorithm and k-NN algorithm was applied to develop a short version questionnaire and proved to have better accuracy, as compared with the short version developed by traditional statistical technique. [ABSTRACT FROM AUTHOR]

Background: Lifestyle factors were associated with an increased risk of cardiovascular disease (CVD) occurrence. We explored the associations between lifestyle factors and CVD risk factors, and assessed the interactive effects of lifestyle factors on CVD risk factors.Methods: A cross-sectional data of 114,082 (57,680 men and 56,402 women) middle-aged adults and elderly in Taiwan were collected from 2001 to 2010. Logistic regression analysis was used to assess the associations between lifestyle factors and CVD risk factors. The relative excess risk due to interaction (RERI) and the attributable proportion due to interaction were used to explore the interactive effect of lifestyle factors on CVD risk factors.Results: The interaction between alcohol consumption and smoking exhibited an excess risk of high triglycerides (RERI = 0.21; 95% CI: 0.14-0.29), and that of alcohol consumption and physical activity had an excess risk of high LDL-cholesterol (RERI = 0.11; 95% CI: 0.06-0.16) and high blood glucose (RERI = 0.05; 95% CI: 0.01-0.11). Alcohol consumption and vegetable-rich diet (intake of high vegetables with no or low meat) had an excess risk of high LDL-cholesterol and low HDL-cholesterol, but a reduced risk of high triglycerides (RERI = - 0.10; 95% CI: - 0.17 - -0.04). Smoking and physical activity had an increased risk of high blood glucose and a reduced risk of low HDL-cholesterol. Smoking and vegetable-rich diet reduced the risk of high triglycerides (RERI = - 0.11; 95% CI: - 0.18 - - 0.04), high blood glucose (RERI = - 0.14; 95% CI: - 0.21 - - 0.07) and low HDL-cholesterol (RERI = - 0.10; 95% CI: - 0.19 - -0.01).Conclusions: The interaction between smoking, alcohol consumption, physical activity and diet were associated with lipid profile and blood glucose, hence there was an interaction between these lifestyle factors in an additive scale. Public health promotion should therefore consider multifaceted promotional activities that are likely to make a positive impact on the health status of the Taiwanese population. [ABSTRACT FROM AUTHOR]

Background: Chronic Kidney Disease (CKD), characterized by impaired kidney function, affects over 1.5 million individuals in Taiwan. Cardiovascular disease (CVD) is commonly found in patients with CKD, and the increased prevalence of obesity can have some implications for the risk of both CKD and CVD. Since diet plays an important role in the development of obesity, CVD and CKD, our study was designed to investigate the association of kidney function-related dietary pattern with weight status, cardiovascular risk factors, and the severity of impaired kidney function in middle-aged and older adults in Taiwan.Methods: A total of 41,128 participants aged 40 to 95 years old with an estimated glomerular filtration rate (eGFR) less than 90 mL/min/1.73 m2 and proteinuria were recruited from Mei Jau Health Institute between 2008 and 2010. The kidney function-related dietary pattern was identified using reduced rank regression (RRR) and was known as high consumption of preserved or processed food, meat, organ meats, rice/flour products, and, low consumption of fruit, dark-colored vegetables, bread, and beans. A multivariable logistic regression analysis was used to identify the association of weight status and cardiovascular risk factors with moderately/severely impaired kidney function (eGFR < 60 mL/min/1.73 m2) and the association of dietary pattern with the outcomes aforementioned.Results: Moderately/severely impaired kidney function participants were heavier and had higher abnormality of cardiovascular risk factors compared with those with mildly impaired kidney function. Weight status (OR = 1.28, 95% CI 1.12-1.45, P <  0.001 for obesity) and cardiovascular risk factors (OR = 1.52, 95% CI 1.31-1.77, P <  0.001 for high total cholesterol/HDL-C ratio and OR = 1.56, 95% CI 1.41-1.72, P <  0.001 for hypercalcemia) were positively associated with increased risk of moderately/severely impaired kidney function. The kidney function-related dietary pattern was correlated with overweight or obese (OR = 2.07, 95% CI 1.89-2.27, P <  0.01) weight status, increased cardiovascular risk by 10-31%, and the risk of moderately/severely impaired kidney function (OR = 1.15, 95% CI 1.02-1.29, P <  0.05).Conclusions: The RRR-derived kidney function-related dietary pattern, characterized by high intake of processed and animal foods and low intake of plant foods, predicts the risks for developing cardiovascular disease and moderately/severely impaired kidney function among middle-aged and older adults. [ABSTRACT FROM AUTHOR]

Background: Metabolic syndrome is commonly associated with inflammation. The underlying factors of inflammation in metabolic syndrome are not fully understood. The objective of the study was to determine the association of dietary patterns, anthropometric measurements, and metabolic parameters with inflammatory markers in middle-aged and older adults with metabolic syndrome in Taiwan.Methods: A total of 26,016 subjects aged ≥35 y with metabolic syndrome were recruited from Mei Jau institution between 2004 and 2013 for a cross sectional study. Metabolic syndrome was defined by the International Diabetes Federation. Multivariate logistic regression was performed to evaluate the association of dietary patterns, anthropometric measurements, and metabolic parameters with C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio (NLR) in men and women with metabolic syndrome. Crude and adjusted models were analyzed by gender.Results: The western dietary pattern, obesity, high body fat, high waist or hip circumference, and high waist-to-hip ratio were significantly associated with increased odds ratios of high CRP and NLR in both genders. High systolic or diastolic blood pressure (BP), low high-density lipoprotein-cholesterol (HDL-C), high low-density lipoprotein-cholesterol (LDL-C), high total cholesterol (TC), high serum triglycerides (TG), and high fasting blood glucose (FBG) were significantly correlated with increased odds ratios of high CRP in both genders. Low HDL-C, high LDL-C, high serum TG, and high FBG were significantly associated with increased odds ratios of high NLR in both genders. However, high systolic (OR = 1.124, 95% CI 1.047-1.206, P < 0.01) or diastolic BP (OR = 1.176, 95% CI 1.087-1.273, P < 0.001) and high TC (OR = 1.138, 95% CI 1.062-1.220, P < 0.001) were significantly correlated with increased odds ratios of high NLR only in men.Conclusions: The western dietary pattern, obese-related anthropometric parameters, and most components of metabolic syndrome are positively associated with CRP levels and NLR in men and women with metabolic syndrome. [ABSTRACT FROM AUTHOR]

Abstract In this study, a cooling system with shallow-geothermal energy is experimentally investigated to mitigate the photovoltaic panel conversion efficiency decline problem, and a mathematical model is built for predicting the system performance. This cooling system cools the panel by spraying water onto the reverse of the panel, and returns the water to the tank. To enhance the cooling capacity, the recycled water is collected in a U-shaped borehole heat exchanger (UBHE), which is installed in an existing well, and the water exchanges heat with shallow-geothermal energy. Finally, the panel is again sprayed with water to cool it. The experiments are comprised of three stages: The first involved the panel operating without cooling system. The second involved the panel operating with a cooling system but without a UBHE. The third is the cooling system operating with a UBHE. The experimental results and the mathematical models show the same trend: The cooling system can improve the panel conversion efficiency; moreover, as the temperatures and the number of panels increase, the benefit becomes obvious. For a plant factory powered by panels, for example, this cooling system can improve the efficiency by 14.3%, and its equipment costs recovered in 8.7 years with this system. Graphical abstract Image Highlights • A cooling system, combined with shallow geothermal energy, is applied to a photovoltaic panel system for the mitigation of the efficiency decline caused by high temperatures. • The U-shaped borehole heat exchanger can maintain the cooling capacity of the cooling system while reducing energy consumption. • A mathematical model is developed for estimating a photovoltaic panel's temperature and conversion efficiency under different conditions. [ABSTRACT FROM AUTHOR]

• Pool boiling heat transfer of helical tube in R513A and R134a is studied. • Boiling heat transfer coefficient of the helical tubes is significantly higher than that of straight tubes. • The heat transfer enhancement ratio of the helical tube depends on tube pitch and heat flux. • Bubble activities and the bubbly flow phenomena of helical tube were observed by high speed video. • Larger and faster moving bubbles appeared in the upper part of the helical tube as compared to the bottom. This research utilizes experimental measures to investigate the heat transfer mechanism of helical tubes during saturated pool boiling. Experiments were carried out using R-134a and R-513A as working fluids, with saturation temperatures of 4.4 °C and 15 °C and heat fluxes ranging from 5 to 50 kW/ m 2. The helical tube surface was heated by hot water with ascending heat flux. The helical test tubes used in this study are annealed smooth copper tubes with an outer diameter of 6.35 mm, tube thickness of 0.7 mm, coil diameter of 58.85 mm, number of turns of 3.5, and tube pitches ranging from 7 to 21 mm. Experimental results show that the tube bundle effect also exists in helical tubes as the boiling heat transfer coefficient obtained from helical tubes is significantly higher than that of single straight tubes predicted by the Cooper correlation. Furthermore, the boiling heat transfer coefficients obtained are greatly influenced by the tube pitch and show a tendency to increase with the decrease in tube pitch. In addition, larger and faster-moving bubbles are observed near the upper part of the helical tube due to agitations generated from the bottom part. [ABSTRACT FROM AUTHOR]

Public health informatics has been defined as the systematic application of information and computer science and technology to public health practice, research, and learning [1]. Unfortunately, limited reports exist concerning to the capacity building strategies to improve public health informatics workforce in limited-resources setting. In Indonesia, only three universities, including Universitas Gadjah Mada (UGM), offer master degree program on related public health informatics discipline. UGM started a new dedicated master program on Health Management Information Systems in 2005, under the auspice of the Graduate Program of Public Health at the Faculty of Medicine. This is the first tracer study to the alumni aiming to a) identify the gaps between curriculum and the current jobs and b) describe their perception on public health informatics competencies. We distributed questionnaires to 114 alumni with 36.84 % response rate. Despite low response rate, this study provided valuable resources to set up appropriate competencies, curriculum and capacity building strategies of public health informatics workforce in Indonesia. [ABSTRACT FROM AUTHOR]

Although the electronic medical record (EMR) has been applied extensively, the sharing and exchange of medical records between hospitals are still very difficult because of the variety of the size of hospitals and the absence of a standard form for clinical records. As the network technology is developed fast, constructing standardized forms and modules for medical information exchange becomes a necessary beside the numerous services provided by any hospitals. For the purpose of the development of the medical informatics in Taiwan, the Department of Health Executive Yuan initiated a project in 2004 for establishing a standard template of medical record and unified medical vocabulary. The project also put forward the preferential order of carrying out for which levels that the EMR standard template. In this research, we used the idea of Delphi Method to assemble an expert decision-working group, 11 experts in the domain of nursing care were enrolled. The experts were from different clinical agencies including medical centers and regional hospitals. They had one meeting every month from November 2004 to March 2005. We analyzed 869 nursing data fields, defined 33 record modules, and created six forms (or templates) including Vital Signs, Nursing Assessment, Nursing Intervention, Nursing Diagnosis, Care Plan, and Nursing Record of electronic nursing care. The standard templates have been used as the carrier of the nursing information exchange. XML structured documents were created to build a web-based EMR prototype system. After that, HTML-based documents were transformed to support the functions of data querying and downloading from the patients and clinical institutes using the interface of Web browser. [ABSTRACT FROM AUTHOR]

Introduction Trauma admissions are associated with weather and temporal factors; however, previous study results regarding these factors are contradictory. We hypothesised that weather and temporal factors have different effects on specific trauma events in an emergency medical service (EMS) system. Methods EMS data from January 1, 2009, to December 31, 2010, were obtained from the fire department of Taipei City and associated with the local weather data. EMS trauma events were categorised into total trauma, traffic accidents (TAs), motorbike accidents (MBAs), and falls. Hourly data on trauma patients were analysed using the zero-inflated Poisson model. Results The hourly incidence of total trauma increased with the magnitude of precipitation (incidence rate ratio [IRR] = 1.06, 1.09, and 1.11 in light, moderate, and heavy rain, respectively), and this effect was more prominent in fall patients than in patients with other injuries (IRR = 1.07, 1.21, and 1.32). However, the hourly incidence of TAs and MBAs was associated only with light rain (IRR = 1.11 and 1.06, respectively). An hour of sunshine exposure was associated with an increase in the hourly incidence of all groups, and higher temperatures were associated with an increased hourly incidence of total trauma, TAs, and MBAs, but not falls. The hourly incidence of falls increased only in late fall and winter. Compared with the hourly incidence between 3 am and 7 am, the hourly incidence of all groups plateaued between 7 am and 11 pm and declined from 11 pm to 3 am. During the plateau period, 2 peaks in the incidence of TAs (IRR = 5.03 and 5.07, respectively) and MBAs (IRR = 5.81 and 5.51, respectively) were observed during 7–11 am and 3–7 pm. The hourly incidence of total trauma, TAs, and MBAs plateaued during workdays, peaked on Fridays, declined on Saturdays, and troughed on Sundays. The incidence of falls increased only on Mondays (IRR = 1.09). Conclusions Weather and temporal factors had different impacts on the incidence of traffic-related accidents and falls. Therefore, EMS data may have implications in preventing injuries and planning resource use for prehospital trauma rescue. [ABSTRACT FROM AUTHOR]

Background: Angiotensin receptor blockers (ARBs), which are commonly used antihypertensives, have been proposed to lower the risk of Parkinson disease by reducing oxidative stress based on animal and in vitro studies. Thus, this study aimed to test this association in patients with newly diagnosed hypertension.Methods: This retrospective cohort study enrolled 107,207 patients with newly diagnosed hypertension between 2001 and 2013. The hazard ratios for Parkinson disease were calculated for ARB treatment compared with those who never used ARBs and among the 5 subgroups receiving different cumulative ARB dosages.Results: We identified 527 (1.1%) Parkinson disease cases among patients with ARB treatment in a median observation period of 8.4 years compared to the 1,255 (2.2%) Parkinson disease cases among those without ARB treatment in a median observation period of 6.8 years. Overall, risk for developing Parkinson disease was statistically lower in the ARB-treated group with a hazard ratio of 0.56 (95% confidence interval: 0.51-0.63) than those without ARB.Conclusions: ARB treatment was associated with a statistically important reduction of Parkinson disease risk in patients with newly diagnosed hypertension. Therefore, ARB may constitute an effective neuroprotective strategy to lower Parkinson disease risk in such patients. [ABSTRACT FROM AUTHOR]

Abstract: The Institute of Medicine has identified both computerized physician order entry and electronic prescription as keys to reducing medication errors and improving safety. Many computerized clinical decision support systems can enhance practitioner performance. However, the development of such systems involves a long cycle time that makes it difficult to apply them on a wider scale. This paper presents a suite of guideline modeling and execution tools, built on Protégé, Jess and Java technologies, which are easy to use, and also capable of automatically synthesizing clinical decision support systems for clinical practice guidelines of moderate complexity. [Copyright &y& Elsevier]

Abstract: Introduction: The Institute of Medicine has identified both Computerized Physician Order Entry (CPOE) and Electronic Prescription (EP) as key in reducing medication errors and improving safety. Many computerized clinical decision support systems (CDSSs) improve practitioner performance. However, the development of CDSSs involves a long cycle time that makes it difficult to apply in a wider scope. Methods: In this study, we integrated the hyperlipidemia treatment guideline ATP III (Adult Treatment Panel III) in a CPOE of a medical center. The first 200 consecutive patients followed up more than 1 year were recorded for analysis. Results: Our study revealed that 130 (65%) patients reached the LDL-C (low density lipoprotein-cholesterol) goal in 1 year. For those who with CDSS finished, 74% reached the LDL-C goal. For those who with CDSS exited, 57% reached the LDL-C goal. The odds ratio is 2.1 (1.2, 3.8) (p =0.022), which means for those who with CDSS finished can have 2 times of chance to reach the LDL-C goal. The mean of days to attain the LDL-C goal level after initiation of antihyperlipidemia therapy was 175±98 days. 11,806 prescribing records from 8023 patients were collected for analyzing the reasons of prematurely exiting the CDSS. The most frequent reason for exiting the system is “too busy to use”. Conclusion: We conclude that a CPOE with CDSS integrated may let more hyperlipidemia patients reach the LDL-C goal. However, data also showed the total prescribing time may increase. The results of a preliminary evaluation are presented to illustrate that the CDSSs can improve the quality of hyperlipidemia management. [Copyright &y& Elsevier]

• The main aim of this study was to complete a security architecture for medical data, and develop a triple encryption authentication architecture to help data owners easily and securely share personal medical records with medical service personnel. • Through the blockchain architecture, the data required by precision medicine can be integrated from different sources, and its correctness can be verified. • The results of this research will be able to develop patient-centered e-commerce medical services in a safer and more effective way, improve patient well-being and promote industrial innovation. COVID-19, a serious infectious disease outbreak started in the end of 2019, has caused a strong impact on the overall medical system, which reflects the gap in the volume and capacity of medical services and highlights the importance of clinical data ex-change and application. The most important concerns of medical records in the medical field include data privacy, data correctness, and data security. By realizing these three goals, medical records can be made available to different hospital information systems to achieve the most complete medical care services. The privacy and protection of health data require detailed specification and usage requirements, which is particularly important for cross-agency data exchange. This research is composed of three main modules. "Combined Encryption and Decryption Architecture", which includes the hybrid double encryption mechanism of AES and RSA, and encrypts medical records to produce "Secured Encrypted Medical Record". "Decentralize EMR Repository", which includes data decryption and an exchange mechanism. After a data transmission is completed, the content verification and data decryption process will be launched to confirm the correctness of the data and obtain the data. A blockchain architecture is used to store the hash value of the encrypted EMR, and completes the correctness verification of the EMR after transmission through the hash value. The results of this study provide an efficient triple encryption mechanism for electronic medical records. SEMRES ensures the correctness of data through the non-repudiation feature of a blockchain open ledger, and complete integrated information security protection and data verification architecture, in order that medical data can be exchanged, verified, and applied in different locations. After the patient receives medical services, the medical record is re-encrypted and verified and stored in the patient's medical record. The blockchain architecture is used to ensure the verification of non-repudiation of medical service, and finally to complete the payment for medical services. The main aim of this study was to complete a security architecture for medical data, and develop a triple encryption authentication architecture to help data owners easily and securely share personal medical records with medical service personnel. [ABSTRACT FROM AUTHOR]

Background and Objective: The implementation of health information systems (HIS) could overcome obstacles in human resources and infrastructure at primary health care centers (PHCs). This study involved an e-Leprosy framework being integrated into the real setting of a leprosy control program in Indonesia. The objectives of this implementation study were to integrate e-Leprosy into a leprosy control program at 27 PHCs in Pekalongan District. Central Java Province, Indonesia to explore factors related the success or failure of such an implementation regarding the usability, involvement, and acceptance of e-Leprosy by PHC staff and to evaluate the effect of the implementation on leprosy patient attendance at PHCs. This paper is based on the Standards for Reporting Implementation Studies (StaRI) statement.Method: This study used mixed methods implementation research with longitudinal analysis and involved two groups of participants: Leprosy Surveillance Officers (LSOs), patients, and the relatives of patients. This study involved four phases consisting of preparation, baseline assessment, intervention, and evaluation. The qualitative study conducted focus group discussions and in-depth interviews. The e-Leprosy program automatically sent SMS reminders regarding leprosy treatment to the LSOs, patients, and patients' relatives every month.Findings: This study determined that LSO had difficulties related to their workloads in PHCs while managing information and monitoring treatment and contact after release from treatment. The baseline assessment phase found that LSOs in Pekalongan District were unfamiliar with email but familiar using the internet. Overall, LSOs had a positive perception of the e-Leprosy program. The usability of this e-Leprosy program tended to increase over time, while acceptance of the e-Leprosy exhibited a significant relationship with computer and internet fluency (r = 0.48, p < 0.05) and age (r = 0.621, p < 0.01). The responsible patients correlated (r = 0.67, p < 0.01) with involvement in the e-Leprosy program. This study revealed that patient reminders increased on-time attendance by 13.9 % (p < 0.01 with OR = 2.41).Conclusion: Factors that should be considered during implementation HIS included the digital gap, PHC's staff workload, as well as the level of commitment and leadership in the health office. [ABSTRACT FROM AUTHOR]

Cancer is the leading cause of death in Taiwan, according to the Ministry of Health and Welfare (2017), with cancers of the trachea, bronchus, and lung being the most prevalent. Thus, it is critically important to study this disease. By using Taiwan's National Health Insurance Research Database (NHIRDB), which covers 99.9% of residents, we are capable of analyzing comorbidities and predicting the outcomes of the clinical therapy. This study focuses on non-small cell lung cancer. We first obtain cancer registration indexes from two million individual patient records in NHIRDB by screening patients of having a clinical diagnosis of ICD C33-34 (trachea, bronchus and lung cancer). Then, we used these cancer registration indexes to find all the therapies and comorbidity of the patients and used them as input parameters to establish a predictive model of survival probability for lung cancer. Linear and nonlinear data mining methods were employed to build prediction models to study the effects of different therapies on the 3-year survival probability of lung cancer patients. We found that the artificial neural network (ANN) model performs better than the logistic regression (LR) model. It comes out that the best point of the ANN model on the ROC curve is at sensitivity = 77.6%, specificity = 76.8% and AUROC = 83%. [ABSTRACT FROM AUTHOR]

Objective: To assess the factors associated with malnutrition among children <5 years in Burkina Faso.Design: This study was based on secondary analysis of cross-sectional population-based data from Burkina-Faso Demographic Health Surveys 2010.Setting: This study was carried out in Burkina Faso, West Africa.Participants: The participants were 6337 children <5 years and their mothers.Main Outcome Measures: Demographic characteristics, child nutrition and health status, and maternal and household information were collected. Survey-specific SAS procedures for weighting, clustering and stratification in the survey design were used. The distribution of different nutritional status, such as underweight, stunting and wasting and the effects of risk factors on malnutrition was analyzed.Results: Out of 6337 children <5 years, 51.0% of children were male and 57.8% of children had an average size at birth. There were 15.6, 21.5 and 10.6% of children who recently suffered from diarrhea, fever and acute respiratory infection, respectively. Child sex, age, size at birth, child morbidity, mother's education and body mass index and household wealth index were significantly associated with undernutrition among children <5 years in Burkina Faso.Conclusions: In addition to the improvement of household wealth index, more health and nutritional education for mothers should be implemented by the government to improve health and nutritional status of children <5 years in Burkina Faso. [ABSTRACT FROM AUTHOR]

Introduction There have been several reports on the role of human papillomavirus (HPV) in the etiology of breast cancer. To our knowledge, this is first study to use disease-disease association data-mining approach to analyzing viral warts and breast cancer to be conducted in Taiwanese population. Materials and methods We analyzed the Taiwan's National Health Insurance database (NHIDM data comprising of 23 million patient data) to examine the association between viral warts and female breast carcinoma. The patients were categorized into three groups: breast cancer only, viral warts only, and those with both breast cancer and viral warts. The Cox proportion hazard regression analysis was used to measure the effect of HPV on the time to breast cancer diagnosis. Multivariable analyzes and stratified analyzes using hazard ratios (HRs) were presented with 95% confidence intervals (CIs) after adjusting for age, and CCI. Result Among 807,578 HPV population, we identified 6014 breast cancer cases. The HPV group was associated with a significantly higher risk of developing breast cancer (HR, 1.18; 95% CI, 1.15–1.21; p < 0.001) compared with the non-HPV group. HPV patients with age group 18–39 was slightly higher risk of breast cancer occurrence (HR, 1.07; 95% CI, 1.01–1.13; p < .05). The risk of breast cancer in 10-year incidence was 7% higher for females less than 40 years and 23% for over 40 year's patients when compared with non-HPV patients of the same age group. Conclusion Our study indicates that women who develop viral warts are at a significantly higher risk of developing breast cancer than women who have not diagnosed with viral warts. Thus, the presence of viral warts is a potential risk to breast cancer. Therefore, we suggest patients diagnosed with viral warts may get early screening for breast cancer. [ABSTRACT FROM AUTHOR]

Purpose: This retrospective cohort study used a population-based dataset to test the risk for parkinsonism in patients receiving flunarizine and cinnarizine, compared with matched controls. Methods: Data were obtained from the National Health Insurance Research Dataset of Taiwan. Patients receiving flunarizine or cinnarizine for more than 1 month between 2000 and 2005 were enrolled. Exclusion criteria included receiving flunarizine, cinnarizine, or antipsychotics for more than 1 month during 1997-1999, a history of neurodegenerative diseases, and an age of less than 30 years. One matched control for each patient was selected. Each participant was followed for diagnosis of parkinsonism within a 3-year observation period. Stroke, diabetes mellitus, total prescription days, and doses of flunarizine or cinnarizine were recorded. Results: The study and control groups consisted of 9830 subjects. In the study group, 280 patients (2.9 %) were diagnosed with parkinsonism with a median observation period of 1.2 years, and 49 participants (0.5 %) were diagnosed in the control group with a median observation period of 1.9 years. The adjusted hazard ratio for parkinsonism among patients receiving flunarizine and cinnarizine was 5.117 (95 % CI = 3.758-6.967). Age, stroke, and diabetes mellitus were significant risk factors, but female sex and total doses of the study drugs were not. Conclusions: This study demonstrates that flunarizine and cinnarizine significantly increase the risk for parkinsonism. The treatment benefits of these two agents should be balanced with this adverse effect. Physicians must look carefully for early signs of parkinsonism in patients treated with flunarizine and cinnarizine. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: To surveyed the quantities, types, and related information of potential drug–drug interactions (DDIs) and estimate the off-label use percentage of pediatric outpatient prescriptions for newborns and infants from the National Health Insurance Research Database (NHIRD) of Taiwan. Background: Adverse drug reactions (ADR) may cause morbidity and mortality, potential drug–drug interactions (DDI) increase the probability of ADR. Research on ADR and DDI in infants is of particular urgency and importance but the related profiles in these individuals are not well known. Methods: All prescriptions written by physicians in 2000 were analyzed to identify potential DDIs among drugs appearing on the same prescription sheet. Results: Of a total of 150.6 million prescription sheets, with 669.5 million prescriptions registered in the NHIRD of Taiwan, six million (3.99%) prescription sheets were for 2.1 million infants with 19.4 million (2.85%) prescriptions. There were 672,020 potential DDIs in this category, accounting for 3.53% per prescription; an estimated one DDI in every three patients. The interactions between aspirin and aluminum/magnesium hydroxide were most common (4.42%). Of the most significant drug–drug interactions, the interaction of digoxin with furosemide ranked first (20.14%), followed by the interactions of cisapride with furosemide and erythromycin (6.02% and 4.85%, respectively). The interactions of acetaminophen and anti-cholinergic agents comprised most types of drug–drug interactions (6.62%). Conclusion: Although the prevalence rates of DDIs are low, life-threatening interactions may develop. Physicians must be reminded of the potential DDIs when prescribing medications for newborns and infants. [Copyright &y& Elsevier]

Abstract: Purpose: We developed a nursing process decision support system (NPDSS) based on three clinical pathways, including benign prostatic hypertrophy, inguinal hernia, and urinary tract stone. NPDSS included six major nursing diagnoses – acute pain, impaired urinary elimination, impaired skin integrity, anxiety, infection risk, and risk of falling. This paper aims to describe the design, development and validation process of the NPDSS. Methods: We deployed the Delphi method to reach consensus for decision support rules of NPDSS. A team of nine-member expert nurses from a medical center in Taiwan was involved in Delphi method. The Cronbach's α method was used for examining the reliability of the questionnaire used in the Delphi method. The Visual Basic 6.0 as front-end and Microsoft Access 2003 as back-end was used to develop the system. A team of six nursing experts was asked to evaluate the usability of the developed systems. A 5-point Likert scale questionnaire was used for the evaluation. The sensitivity and specificity of NPDSS were validated using 150 nursing chart. Results: The study showed a consistency between the diagnoses of the developed system (NPDSS) and the nursing charts. The sensitivities of the nursing diagnoses including acute pain, impaired urinary elimination, risk of infection, and risk of falling were 96.9%, 98.1%, 94.9%, and 89.9% respectively; and the specificities were 88%, 49.5%, 62%, and 88% respectively. We did not calculate the sensitivity and specificity of impaired skin integrity and anxiety due to non-availability of enough sample size. Conclusions: NPDSS can help nurses in decision making of nursing diagnoses. Besides, it can help them to generate nursing diagnoses based on patient-specific data, individualized care plans, and implementation within their usual nursing workflow. [Copyright &y& Elsevier]