An Enhanced Standardization and Qualification Mechanism for Heterogeneous Healthcare Data.

Given the challenge that healthcare related data are being obtained from various sources and in divergent formats there is an emerging need for providing improved and automated techniques and technologies that perform qualification and standardization of these data. The approach presented in this paper introduces a novel mechanism for the cleaning, qualification, and standardization of the collected primary and secondary data types. The latter is realized through the design and implementation of three (3) integrated subcomponents, the Data Cleaner, the Data Qualifier, and the Data Harmonizer that are further evaluated by performing data cleaning, qualification, and harmonization on top of data related to Pancreatic Cancer to further develop enhanced personalized risk assessment and recommendations to individuals.

Using Artificial Intelligence-based models to predict the risk of Mucormycosis among COVID-19 Survivors: An Experience from India

IntroductionIndia reported a severe public health challenge not only due to the COVID-19 outbreak but also the increasing number of associated mucormycosis cases since 2021. This study aimed at developing artificial intelligence-based models to predict the risk of mucormycosis among the patients at the time of discharge from the hospital. MethodsThe dataset included 1229 COVID-19 positive patients, and additional 214 inpatients, COVID-19 positive as well as infected with mucormycosis. We used logistic regression, decision tree, and random forest, and the extreme gradient boosting algorithm. All our models were evaluated with 5-fold validation to derive a reliable estimate of the model error. ResultsThe logistic regression, XGBoost, and random forest performed equally well with AUROC 95.0, 94.0, and 94.0 respectively. This study also determined the top five variables namely obesity, anosmia, de novo diabetes, myalgia, and nasal discharge, which showed a positive impact on the risk of mucormycosis. ConclusionThe developed model has the potential to predict the patients at high risk and thus, consequently initiating preventive care or aiding in early detection of mucormycosis infection. Thus, this study holds potential for early treatment and better management of patients suffering from COVID-19 associated mucormycosis.

Adverse outcomes of long-term use of proton pump inhibitors: a systematic review and meta-analysis.

The association between the long-term use of proton pump inhibitors (PPIs) and the risks of various diseases remains controversial. Therefore, the primary objective of this study was to quantify the associations as presented in the literature and to also provide this information to healthcare professionals and patients about their potentially adverse effects. In July 2016, we searched through Medline (PubMed), Embase, and the Cochrane Library from inception using common keywords. We included observational studies that provided risk estimates on the long-term use of PPIs and their adverse effects. Overall, 43 studies were included in the systematic review, of which 28 studies were also included in the random effect meta-analysis. Odds of community-acquired pneumonia, hip fracture, and colorectal cancer were 67% [odds ratio (OR)=1.67; 95% confidence interval (CI): 1.04-2.67], 42% (OR=1.42; 95% CI: 1.33-1.53), and 55% (OR=1.55; 95% CI: 0.88-2.73) higher in patients with long-term PPIs use compared with patients who did not use PPIs. Although the use of PPIs provides short-term health benefits, their prolonged use is associated with minor and also potentially major adverse health outcomes. Hence, we strongly recommend that the prescription of PPIs should be done with caution to improve the medication's efficacy and patients' safety.

Exploring the Association between Statin Use and the Risk of Parkinson's Disease: A Meta-Analysis of Observational Studies.

BACKGROUND: Parkinson's disease (PD) is a progressive disorder of the central nervous system. The prevalence of PD varies considerably by age group; it has a higher prevalence in patients aged 60 years and more. Several studies have shown that statin, a cholesterol-lowering medication, reduces the risk of developing PD, but evidence for this is so far inconclusive. The objective of this study is to evaluate the association between statin use and the risk of developing PD. METHODS: PubMed, EMBASE, and the bibliographies of articles were searched for studies published between January 1, 1990, and January 1, 2017, which reported on the association between statin use and PD. Articles were included if they (1) were published in English, (2) reported patients treated with statin, and the outcome of interest was PD, (3) provided OR/HR with 95% CI or sufficient information to calculate the 95% CI. All abstracts, full-text articles, and sources were reviewed, with duplicate data excluded. Summary relative risk (RRs) with 95% CI was pooled using a random-effects model. Subgroup and sensitivity analyses were also conducted. RESULTS: We selected 16 out of 529 unique abstracts for full-text review using our selection criteria, and 13 out of these 16 studies, comprising 4,877,059 persons, met all of our inclusion criteria. The overall pooled RR of PD was 0.70 (95% CI 0.58-0.84) with significant heterogeneity between estimates (I2 = 93.41%, p = 0.000) for the random-effects model. In subgroup analysis, the greater decreased risk was found in studies from Asia (RR 0.62 95% CI 0.51-0.76), whereas a moderate reduction was observed in studies from North America (RR 0.69 95% CI 0.47-1.00), but less reduction was observed in studies from Europe (RR 0.86 95% CI 0.80-0.92). Also, long-term statin use, simvastatin, and atorvastatin showed a higher rate of reduction with significance heterogeneity. CONCLUSION: Our results showed that statin use is significantly associated with a lower risk of developing PD. Physicians should consider statin drug therapy, monitor its outcomes, and empower their patients to improve their knowledge, therapeutic outcomes, and quality of life. However, preventive measures and their associated mechanisms must be further assessed and explored.

Determinants and development of a web-based child mortality prediction model in resource-limited settings: A data mining approach.

BACKGROUND: Improving child health and reducing child mortality rate are key health priorities in developing countries. This study aimed to identify determinant sand develop, a web-based child mortality prediction model in Ethiopian local language using classification data mining algorithm. METHODS: Decision tree (using J48 algorithm) and rule induction (using PART algorithm) techniques were applied on 11,654 records of Ethiopian demographic and health survey data. Waikato Environment for Knowledge Analysis (WEKA) for windows version 3.6.8 was used to develop optimal models. 8157 (70%) records were randomly allocated to training group for model building while; the remaining 3496 (30%) records were allocated as the test group for model validation. The validation of the model was assessed using accuracy, sensitivity, specificity and area under Receiver Operating Characteristics (ROC) curve. Using Statistical Package for Social Sciences (SPSS) version 20.0; logistic regressions and Odds Ratio (OR) with 95% Confidence Interval (CI) was used to identify determinants of child mortality. RESULTS: The child mortality rate was 72 deaths per 1000 live births. Breast-feeding (AOR= 1.46, (95% CI [1.22. 1.75]), maternal education (AOR= 1.40, 95% CI [1.11, 1.81]), family planning (AOR= 1.21, [1.08, 1.43]), preceding birth interval (AOR= 4.90, [2.94, 8.15]), presence of diarrhea (AOR= 1.54, 95% CI [1.32, 1.66]), father's education (AOR= 1.4, 95% CI [1.04, 1.78]), low birth weight (AOR= 1.2, 95% CI [0.98, 1.51]) and, age of the mother at first birth (AOR= 1.42, [1.01-1.89]) were found to be determinants for child mortality. The J48 model had better performance, accuracy (94.3%), sensitivity (93.8%), specificity (94.3%), Positive Predictive Value (PPV) (92.2%), Negative Predictive Value (NPV) (94.5%) and, the area under ROC (94.8%). Subsequent to developing an optimal prediction model, we relied on this model to develop a web-based application system for child mortality prediction. CONCLUSION: In this study, nearly accurate results were obtained by employing decision tree and rule induction techniques. Determinants are identified and a web-based child mortality prediction model in Ethiopian local language is developed. Thus, the result obtained could support child health intervention programs in Ethiopia where trained human resource for health is limited. Advanced classification algorithms need to be tested to come up with optimal models.

Benzodiazepine Use and Risk of Dementia in the Elderly Population: A Systematic Review and Meta-Analysis.

BACKGROUND: Benzodiazepines are a widely used medication in developed countries, particularly among elderly patients. However, benzodiazepines are known to affect memory and cognition and might thus enhance the risk of dementia. The objective of this review is to synthesize evidence from observational studies that evaluated the association between benzodiazepines use and dementia risk. SUMMARY: We performed a systematic review and meta-analysis of controlled observational studies to evaluate the risk of benzodiazepines use on dementia outcome. All control observational studies that compared dementia outcome in patients with benzodiazepine use with a control group were included. We calculated pooled ORs using a random-effects model. Ten studies (of 3,696 studies identified) were included in the systematic review, of which 8 studies were included in random-effects meta-analysis and sensitivity analyses. Odds of dementia were 78% higher in those who used benzodiazepines compared with those who did not use benzodiazepines (OR 1.78; 95% CI 1.33-2.38). In subgroup analysis, the higher association was still found in the studies from Asia (OR 2.40; 95% CI 1.66-3.47) whereas a moderate association was observed in the studies from North America and Europe (OR 1.49; 95% CI 1.34-1.65 and OR 1.43; 95% CI 1.16-1.75). Also, diabetics, hypertension, cardiac disease, and statin drugs were associated with increased risk of dementia but negative association was observed in the case of body mass index. There was significant statistical and clinical heterogeneity among studies for the main analysis and most of the sensitivity analyses. There was significant statistical and clinical heterogeneity among the studies for the main analysis and most of the sensitivity analyses. Key Messages: Our results suggest that benzodiazepine use is significantly associated with dementia risk. However, observational studies cannot clarify whether the observed epidemiologic association is a causal effect or the result of some unmeasured confounding variable. Therefore, more research is needed.

Organizational Benefits of Computerized Physican Order Entry (CPOE) System in Pakistan.

Electronic prescribing is also known as Computerized Physician Order Entry (CPOE). It is a computer-aided system which offers the health professionals a robust platform for entering the prescription electronically. Due to paucity of facilities in Pakistan which are available around the world, there is an observable overburden on the health professionals and practitioners. CPOE system has shown to be very effective in minimizing medication errors. CPOE is beneficial for both patient and health organizations. There is great deal of interest in the adoption of this system in our healthcare system. The results state clearly that this system is equally beneficial for organizations who want to adopt this system as perceived by the health professionals. It supports the idea of adoption and implementation of CPOE in healthcare facilities healthcare institutes. CPOE must be adopted to ease and optimize nursing services in Pakistani healthcare system.

Lessons learnt from a MOOC about social media for digital health literacy.

Nowadays, the Internet and social media represent prime channels for health information seeking and peer support. However, benefits of health social media can be reduced by low digital health literacy. We designed a massive open online course (MOOC) course about health social media to increase the students' digital health literacy. In this course, we wanted to explore the difficulties confronted by the MOOC users in relation to accessing quality online health information and to propose methods to overcome the issues. An online survey was carried out to assess the students' digital health literacy. This survey was one of the activities for the enrolled learners in an online course entitled "Social Media in Health Care" on "FutureLearn", one of the popular MOOC platforms. The course was hosted by Taipei Medical University, Taiwan. Data from a total of 300 respondents were collected through the online survey from 14 December 2015 to 10 January 2016. Most participants (61%) considered finding online health information is easy or very easy, while 39% were unsure or found it difficult to retrieve online health information. Most (63%) were not sure about judging whether available information can be used for making health decisions. This study indicates a demand for more training to increase skills to improve the capability of health consumers to identify trustworthy, useful health information. More research to understand the health information seeking process will be crucial in identifying the skillsets that need to be further developed. MOOCs about digital health can be a great source of knowledge when it comes to studying patients' needs.

Meteorological influences on dengue transmission in Pakistan

OBJECTIVE@#To identify the influences of local and regional climate phenomena on dengue transmission in Lahore District of Pakistan, from 2006 to 2014.@*METHODS@#Time-series models were applied to analyze associations between reported cases of dengue and climatic parameters. The coherence trend of regional climate phenomena (IOD and ENSO) was evaluated with wavelet analysis.@*RESULTS@#The minimum temperature 4 months before the dengue outbreak played the most important role in the Lahore District (P = 0.03). A NINO 3.4 index 9 months before the outbreaks exhibited a significant negative effect on dengue transmission (P = 0.02). The IOD exhibited a synchronized pattern with dengue outbreak from 2010 to 2012. The ENSO effect (NINO 3.4 index) might have played a more important role after 2012.@*CONCLUSIONS@#This study provides preliminary results of climate influences on dengue transmission in the Lahore District of Pakistan. An increasing dengue transmission risk accompanied by frequent climate changes should be noted. Integrating the influences of climate variability into disease prevention strategies should be considered by public health authorities.

Meteorological influences on dengue transmission in Pakistan

Objective To identify the influences of local and regional climate phenomena on dengue transmission in Lahore District of Pakistan, from 2006 to 2014. Methods Time-series models were applied to analyze associations between reported cases of dengue and climatic parameters. The coherence trend of regional climate phenomena (IOD and ENSO) was evaluated with wavelet analysis. Results The minimum temperature 4 months before the dengue outbreak played the most important role in the Lahore District (P = 0.03). A NINO 3.4 index 9 months before the outbreaks exhibited a significant negative effect on dengue transmission (P = 0.02). The IOD exhibited a synchronized pattern with dengue outbreak from 2010 to 2012. The ENSO effect (NINO 3.4 index) might have played a more important role after 2012. Conclusions This study provides preliminary results of climate influences on dengue transmission in the Lahore District of Pakistan. An increasing dengue transmission risk accompanied by frequent climate changes should be noted. Integrating the influences of climate variability into disease prevention strategies should be considered by public health authorities.

A global travelers' electronic health record template standard for personal health records.

Tourism as well as international business travel creates health risks for individuals and populations both in host societies and home countries. One strategy to reduce health-related risks to travelers is to provide travelers and relevant caregivers timely, ongoing access to their own health information. Many websites offer health advice for travelers. For example, the WHO and US Department of State offer up-to-date health information about countries relevant to travel. However, little has been done to assure travelers that their medical information is available at the right place and time when the need might arise. Applications of Information and Communication Technology (ICT) utilizing mobile phones for health management are promising tools both for the delivery of healthcare services and the promotion of personal health. This paper describes the project developed by international informaticians under the umbrella of the International Medical Informatics Association. A template capable of becoming an international standard is proposed. This application is available free to anyone who is interested. Furthermore, its source code is made open.

The Taiwanese method for providing patients data from multiple hospital EHR systems.

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.

Comparison of documentation time between an electronic and a paper-based record system by optometrists at an eye hospital in south India: a time-motion study.

PURPOSE: The adoption of electronic medical record (EMR) system is gradually increasing. However, various time-motion studies reveal conflicting data regarding time effectiveness on workflow due to computerization. One of the major issues for physicians is their uncertainty with EMRs' potential impact of time on workflow. A tertiary eye hospital in south India was in the process of implementing an EMR system in their ambulatory care unit. Many of the staff did not have previous computing experience and there were conflicting views on the time effectiveness of the computerized system after implementation. The management was thus interested to know the real time effectiveness of EMR in their hospital. The study compliments existing studies of this type by comparing the time efficiency of documentation time using EMR system with paper documentation in a hospital in a developing country where a transition between paper and EMR documentation was currently in progress. METHODS: Ten randomly selected optometrists documented the time they spent during consultation with both paper and EMR documentation. The time spent was documented for a total of 200 records (100 EMR and 100 paper records). The independent-samples t-test and analysis of variance were used to compare the means of the consultation time and calculated documentation time spent between the electronic and paper records. RESULTS: There was no statistically significant difference in the time spent for documentation between electronic and paper records. The mean time spent in documenting electronic records was 0.92min (95% CI -3.06 to 1.14) longer than in paper records. CONCLUSION: EMR systems can be adopted in eye hospitals without having significant negative impact on duration of consultation and documentation for optometrists. More time-motion studies that include ophthalmologists are however needed in order to get a more complete picture of time impact of the EMR system on clinical workflow in eye hospitals.