A Comprehensive Research Study Literature Review of EPIC© in Terms of Enabling Healthcare Agility: A Report Card

Background As healthcare markets have become more dynamic and turbulent, healthcare organizations have evolved by becoming increasingly “Smart-Agile” in their business practices. Smart-Agility definition-ally ensures success due to its inherent ability to rapidly detect and react appropriately to varied and evolving unclear, complex, and seemingly tumultuous situations and produce high-quality, low-cost goods and services with high customer satisfaction. Thus, there is a vital need for Smart-Agile healthcare IT systems for collection, analyses, and reporting of substantial quantities of healthcare data to inform patient treatment and organizational decisions. EPIC® and its meaningful-use components appear increasingly popular, capturing a majority portion of the healthcare Electronic Healthcare Records (EHR) IT market (>~30%).Yet, there are few, if any, studies reporting on EPIC in terms of Smart-Agility. Aim The intent of this article is to report a systematic review of scientific literature regarding EPIC’s healthcare IT systems meaningful-use features cross-compared with Smart-Agility aspects to produce a positive vs. negative report card—and whether its features are critical vs. non-critical in terms of Smart-Agility. Method Findings reported herein derive from a grounded, iterative review of open-source, peer-reviewed scientific literature following PRISMA. Findings Report card results were mixed. EPIC clearly succeeds and excels (better than average) on Smart-Agile healthcare IT system core aspects that are the most central, critical and valuable in terms of informing healthcare organizations’ decisions and their patients’ care (6 out of 7; B+, -A), specifically: Standardized Data Collection / Connectivity, Real-Time Data Warehousing/Outcome Measures, Enhanced Patient Safety, Patient Tracking and Follow-up (Continuity of Care), Patient Involvement, and Potential Use in Medical Education. The only critical core criterion it failed on was End-User Satisfaction, and some of that appears to dissipate with new users’ software familiarity. Conclusion EPIC provides a solid and relatively inexpensive foundation with great potential for enabling Smart Agility in healthcare organizations with its high-quality collection and management of vast amounts of inter-connected raw data, auto-analysis, and fast report generation. But it does so with hidden costs and inefficiencies. Avenues of further inquiry are suggested.

Wrist Wearable Health Band for COVID-19 Testing

Testing people for COVID-19 in a country like India with a huge population is a near impossible task therefore the government is using body temperature as a testing parameter to cover the whole population. Infrared thermometers are used to find the temperature because it is a cheaper and faster way. This testing rate can be done even faster, without the need of manpower and with far more accuracy using smart watches and bands. These wrist-wearables are mostly used for fitness purposes which have more measuring equipment that is used for preliminary testing done for COVID. This equipment’s are in the form of electric sensors which are small enough to be used in wearables. So we can get even more insight and accuracy compared to the standard method. In this study an application is created to use an array of sensors (Pulse sensor, Pulse oximeter, Accelerometer and temperature sensor) are being used in these wearables to find the chance, that a person is affected due to COVID-19 and the information can be seen real time in mobile phone through the application. All the information can be sent to the health organization’s if required.

Knowledge, Attitudes and Practices of Prescribers towards Antimicrobial Stewardship at Hospitals in Khartoum State - Sudan

Introduction Antimicrobial stewardship (ASP) is of the utmost importance as a way to optimize the use of antimicrobials to prevent the development of resistance and improve patient outcomes. So, it is worthwhile to assess the knowledge, attitude and awareness regarding antimicrobial stewardship in hospitals. Objective The aim of this study is to assess knowledge, attitudes and practices (KAP) of prescribers towards antimicrobial stewardship at hospitals in Khartoum state and to identify the associations between prescriber’s demographic information and their knowledge. Methodology This descriptive cross-sectional study multi-centered study conducted in 10 hospitals at Khartoum state -Sudan, during period from November to December 2018. Study population included all prescribers who is available at study’s hospitals during study period and willing to participate in the study. A self-administered questionnaire addressing participants’ knowledge, attitudes, and practice (KAP) regarding antibiotic resistance and ASP distributed in the selected hospitals among attending house-officers, registrars and consultants completed then analyzed. Results Of the 294 medical staff targeted, 287 responded to the survey (response rate 97.6%). Only (26.4%) were familiar with the term ASP and (31.5%) claimed that it is effective in reducing resistance. (43.0%) of respondents believe that ASP play vital role on antibiotic prescribing. Only (9.5%) had ASP in their hospital and (13.5%) having policy and team. (45.3%) of participants had good level of knowledge about antimicrobial stewardship, but majority show negative attitude (63.1%), and poor practices (92.0%) regarding ASP. There was no observed correlation between knowledge and attitude, knowledge with practice (p-value ≥ 0.05). Only attitude with practice shows significance correlation (P=0.0001), which means that prescribers with positive attitude had the better practices towards antimicrobial stewardship. Age, occupation and experience are the only significant predictors of prescriber's knowledge and attitude towards antibiotic stewardship, while no association between these factors and practice. Conclusion The present study concludes that the knowledge of prescribers regarding ASP is moderate and their attitude is negative. Unfortunately, practices regarding ASP were poor, despite, the good knowledge regarding the effects of ASP on antimicrobial resistance.

Assessment of Prescribing and Dispensing Practices Based on WHO Core Prescribing Indicators in Hospital and Community Pharmacies in Khartoum State - Sudan

Background Rational drug management has become an increasingly important topic in order to make optimal use of the drug budget to offer health services of the highest possible standard. It is important that continuous assessment for rational prescribing and use of drug have to be carried. Objective of this study was to gather data on existing drug prescription and dispensing practices and to evaluate the prescribing and dispensing indicators as described by the WHO. Method Observational, cross-sectional, prospective study was designed and conducted to evaluate the performance of hospital and community pharmacies in Khartoum state, related to rational drug use and prescribing and dispensing practices during the period from November 2018 to March 2019. 297 Hospital and community pharmacies from public and private sectors were contacted for carrying out this study survey and the collected data were analysed against WHO standards for core drug use indicators. Results The average number of drugs per encounter was 3.98 drugs. Hospital pharmacies had a higher (4.18±1.516) number of drugs prescribed than community pharmacies (3.87±1.331) with significance difference between mean of two types of pharmacies (P = 0.015). The percentage of antibiotic per prescription was (53.7%). Antibiotic prescribing was much higher (54.0%) in the hospital pharmacies compared to (48.6 %) in community pharmacies. The average percentage of injections per prescription at the facilities was found to be (57.6%). The percentage of prescription with written diagnosis was (26%.0) and the percentage of prescriptions with written dose was (78%.0). The average dispensing time was (1.75) minutes, The Percentage of drugs actually dispensed was (55.99%), the average adequacy of labelling of drugs was (30.4%). Overall prescribing and dispensing indicators were higher than WHO standard. Conclusion The degree of poly pharmacy was greater than of WHO criteria. The completeness and rationality of prescription was found suboptimal and components were missed.

Closed Frequent Itemsets Mining Based on It-Tree

In the last decade, the amount of collected data, in various computer science applications, has grown considerably. These large volumes of data need to be analysed in order to extract useful hidden knowledge. This work focuses on association rule extraction. This technique is one of the most popular in data mining. Nevertheless, the number of extracted association rules is often very high, and many of them are redundant. In this paper, we propose an algorithm, for mining closed itemsets, with the construction of an it-tree. This algorithm is compared with the DCI (direct counting & intersect) algorithm based on min support and computing time. CHARM is not memery-efficient. It needs to store all closed itemsets in the memory. The lower min-sup is, the more frequent closed itemsets there are so that the amounts of memory used by CHARM are increasing.

Study of The ID3 and C4.5 Learning Algorithms

Data Mining is a process of exploring against large data to find patterns in decision-making. One of the techniques in decision-making is classification. Data classification is a form of data analysis used to extract models describing important data classes. There are many classification algorithms. Each classifier encompasses some algorithms in order to classify object into predefined classes. Decision Tree is one such important technique, which builds a tree structure by incrementally breaking down the datasets in smaller subsets. Decision Trees can be implemented by using popular algorithms such as ID3, C4.5 and CART etc. The present study considers ID3 and C4.5 algorithms to build a decision tree by using the “entropy” and “information gain” measures that are the basics components behind the construction of a classifier model

The Knowledge and Perception of Hand Hygiene Among Health Care Workers in Clinical Settings in Khartoum State - Sudan

Objective This study conducted to assess health care practitioners’ knowledge and perceptions of hand hygiene among health professional working in clinical settings in Khartoum State - Sudan. with the specific objective of determining the association between their stance on hand hygiene and the general demographic characteristics of these health-care professionals. Methodology This is a cross-sectional study conducted between July and November 2017 using a modified form of WHO questionnaire for knowledge and perception that was included 22 items was sent online to health care workers via social media. The data obtained entered and analyzed by SPSS version 24. Chi-square and test of independence were used as a test of significance. A p-value of < 0.05 was considered statistically significant for all purposes. Result 437 hospital staff were responded to the questionnaire. (99.3%) was found to have good knowledge. 197(45.2%) had good perception and 239(54.8%) had fair perception. Formal hand hygiene training was found to have no association with knowledge levels of hand hygiene, but the fair perception was higher in the respondents who didn’t receive formal training. Conclusion The present study highlights the hand hygiene knowledge and perception. Most health care workers were found to have good knowledge, and the majority was found to have a fair perception. Formal hand hygiene training courses were found to have no association with knowledge but it may be reflected in practice. The importance of training sessions regarding hand hygiene was noticed in the perception level.

Measuring Availability and Prices of Locally Produced and Imported Medicines in Sudan

Introduction The objective of this study was to compare the availability and prices of locally produced and imported medicines, in particular after one year from medicines importation restriction and to answer the key questions, did local manufacturers able to coverage national needs of medicines and what is the patient prices for locally produced compared to imported medicines in different sectors and regions of Sudan. Methodology The WHO/HAI methodology survey tool was adapted to measure the availability and price of locally produced and imported medicines. Patient price and availability were collected from capital cities of 6 states as per WHO/HAI methodology. Data were collected and analyzed for 50 medicines from the 104 medicines restricted to local manufacturer. Availability was based on whether the medicine was in stock on the day of data collection at the surveyed facility. Prices were expressed as median price ratio (MPR). Results Availability of locally manufactured medicines (LMM) was much better than imported medicines (IM), in the public, (47.2% vs. 14%, respectively) and private (63.9% vs. 23.5%, respectively) sectors. Based on median price ratio (MPR), public sector patient prices for locally manufactured medicines were lowered priced and had a median MPR of 2.4 (n=42) than imported medicines which had a median MPR of 4.99 (n=20). In private sector patient prices for locally manufactured medicines were also lowered priced and had a median MPR of 2.76 (n=45) than imported medicines which had a median MPR of 5.53 (n=27). Thus; patients were paying about 52% less for locally produced than for imported medicines in both sectors Conclusion The survey showed low availability of the basket of medicines surveyed in the public and private sectors for imported medicines (I.M), while not achieving WHO’s target of 80 % for locally manufactured medicines (LMM). In developing countries a lot of barriers are well known to business and industrial need to be resolved in order to maintain availability and self-reliance in drug production as a mean of increasing access to medicines.

Sampling Defective Pathways in Parkinson Disease

Discrimination of case-control status based on gene expression differences has potential to identify novel pathways relevant to neurodegenerative diseases including Parkinson’s disease (PD). In this paper we applied two different novel algorithms to predict dysregulated pathways of gene expression across several different regions of the brain in PD and controls. The Fisher’s ratio sampler uses the Fisher’s ratio of the most discriminatory genes as prior probability distribution to sample the genetic networks and their likelihood (accuracy) was established via Leave-One-Out-Cross Validation (LOOCV). The holdout sampler finds the minimum-scale signatures corresponding to different random holdouts, establishing their likelihood using the validation dataset in each holdout. Phenotype prediction problems have by genesis a very high underdetermined character. We used both approaches to sample different lists of genes that optimally discriminate PD from controls and subsequently used gene ontology to identify pathways affected by disease. Both algorithms identified common pathways of Insulin signaling, FOXA1 Transcription Factor Network, HIF-1 Signaling, p53 Signaling and Chromatin Regulation/Acetylation. This analysis provides new therapeutic targets to treat PD.

Analysis of Clinical Prognostic Variables for Triple Negative Breast Cancer Histological Grading and Lymph Node Metastasis

Background: Triple Negative Breast Cancer (TNBC) is a type of breast cancer with very bad prognosis. Predicting the histological grade (HG) and the lymph nodes metastasis is crucial for developing more suitable treatment strategies. Methods: We present the main clinical and pathological variables to predict the histological grade and lymph nodes metastasis via novel machine learning techniques. These variables are currently being used for prognosis and treatment in medical practice. This analysis was performed using a database of 102 Caucasian women diagnosed with TNBC. The results were cross-validated using random simulations of this dataset. Results: HG was predicted with an accuracy of 93.8% using a list of 6 prognostic variables with significant implications: Ki67 expression, use of Oral contraceptives, Col11A1 expression, Col11A1 score, E-cad truncated and Tumor size. The lymph nodes metastasis was predicted with an accuracy of almost 85% using only 6 prognostic variables: Vascular invasion, Tumor size, Perineural invasion, Age at diagnosis, Ki67 expression, and Col11A1 score. This analysis also served to establish the median signatures of the groups with and without lymph node metastasis, and proved the existence of a kind of small-size tumors (around 2.15 cm) with lymph node metastasis but not showing vascular and perineural invasions and higher protein Col11A1 score. Besides, these signatures proved to be very stable. Conclusions: The additional information conveyed by the prognostic variables found in these two classification problems provides new insight about the genesis and progression of this disease and can be used in medical practice to improve decisions in patient diagnosis and further treatment.