International Journal of Health Sciences and Pharmacy (IJHSP) <p><strong>International Journal of Health Sciences and Pharmacy (IJHSP) (ISSN - 2581-6411)</strong> is an international, not-for-profit, open-access bi-annually online Refereed journal that accepts research works from scholars, academicians, professors, doctorates, lecturers and corporate in their respective expertise of studies. The aim of IJHSP is to publish peer-reviewed research and review articles. The mission of this journal is to publish original contributions in its field to promote research in various disciplines. IJHSP aims to bring pure academic research and more practical publications. So it covers the full range of research applied to various sciences that meet future demands. All submitted articles should report original, previously unpublished (experimental or theoretical) research and results. All the submissions in the scope of IJHSP will be peer-reviewed. All submissions are also checked for plagiarism. The length of the manuscript must be between five (5) to twenty (20) journal pages excluding references.</p> en-US (Managing Editor) (Ubitech Solutions Pvt Ltd.) Tue, 16 Mar 2021 10:43:47 +0000 OJS 60 Zuber’s Ten Principles of Patient- Centric Patient Experience and a Framework <p>A patient-centric patient experience is a key to high-quality healthcare service industry since; it has been observed that the patients with good experience add trust, cohesiveness with treating the healthcare team and a better continuity of care, which leads to a better outcome and excels patient experience. Objective: To develop a patient-centric patient experience framework. Method: This is a review of literature study and the data were collected with comprehensive searches in the online databases of goggle scholars and research gate. Conclusions: The study concluded with “Zuber’s ten principles of patient-centric patient experience and a framework.”</p> Zuber Mujeeb Shaikh Copyright (c) 2021 Mon, 15 Feb 2021 00:00:00 +0000 Judging Mental Health Disorders Using Decision Tree Models <p>This research presents a categorization replica to have the discernment of the result of distinct psychological health hazard which got improved with the implementation of the replica of decision tree. Among 3000 contestants approximately for different medical analysis, we get the instruction data regarding decision tree information from the answers of the queries. It is displayed by the exploratory outcomes that the suggested replica of the decision tree can find the significant framing of conclusion which influences Clinical discernment Precision. Such conclusions framing comprising in result such as recurrence or non-recurrence for clinical physical sickness, maturity, sex, duration of psychologically physical sickness, span for having drugs as well as suggested drugs that will be able to be applied as an instance of the assessment of the comprehensive precision of medical professionals.</p> Sandip Roy, Aithal P. S., Rajesh Bose Copyright (c) 2021 Tue, 09 Mar 2021 00:00:00 +0000 Human Resource Professional Priorities and Challenges in Times of COVID-19 Pandemic <p>There has been a world alarming and warming situation due to global outbreak of COVID-19 pandemic taking along most important the human cost, mentally, physically with economic cost too. All of a sudden organization across have been alerted themselves to adapt toward this unforeseen unprecedented event and thereby find new solutions. Organizations around the world are taking measures as it’s important to stay at home for social distancing, this leading to drastic increase in economic loss, poor job satisfaction, reduced motivation and workplace depression crisis among organization’s employees with far reaching impacts. The sudden work culture shift has created new challenges for Human Resource (HR) professionals and in this time of global critical condition, the companies and organizations need their HR professionals to help the employees out of this badly driven health and economic crisis. The HR Professionals has been actively partnering with Business to solve some of the trickiest questions the business world faces today. This article discusses some of the priorities and challenges faced by HR professionals in helping the employees to adjust and cope with their changed work environment during COVID-19 pandemic.</p> Shammy Shiri, Laveena D’Mello Copyright (c) 2021 Mon, 15 Mar 2021 00:00:00 +0000 An Overview of Drugs Used in COVID-19: A Pharmacotherapeutic Approach <p>Coronavirus originated pandemic disease also called Corona Virus Disease 2019 (COVID-19) is spread all over the world causing severe acute respiratory syndrome (SARS) called SARS-CoV-2 poses a difficult challenge to scientists, researchers, and practitioners to discover effective drugs for prevention and treatment. By using a huge amount of clinical data obtained from many SARS-CoV2 infected people, clinicians are trying to gather accurate evidence for effective treatment and also developing a suitable vaccine system for the prevention of spread of infection for many more people. With no proven therapies which can treat and prevent SARS-CoV-2 is developed until now, there is an opportunity for new researchers in virology to make such an attempt at this crucial time. In this regard, currently, two strategies are active. The first kind of strategy is on developing completely new molecules to prevent and treat this disease, or the second strategy is on testing the effectiveness of already available antivirals and antimalarials for possible potential recovery and prevention. This is done by testing several antivirals (Remdesivir, Favipiravir, etc) and antimalarials (Chloroquine, Hydroxychloroquine, etc) for their potential therapies. Studies show that the most promising therapy is the use of antiviral Remdesivir. Remdesivir has shown the potential ability to exhibit vitro activity to control COVID-19. The drug is currently being tested by ongoing randomized trials. Until a widely accepted drug reaches the global market, different antiviral treatment strategies are used under urgent investigation. In this article, we review the latest research developments related to the systematic treatments for COVID-19 reported from various research labs of different countries. The article also provides a summary of various clinical research experience, intermediate results, and treatment guidance to combat the novel coronavirus epidemic based on pharmacotherapeutic analysis, along with insights to the attempts on vaccine development across the world in order to curb the COVID pandemic.</p> Architha Aithal, Edwin Dias Copyright (c) 2021 Mon, 15 Mar 2021 00:00:00 +0000 An Integration of Cardiovascular Event Data and Machine Learning Models for Cardiac Arrest Predictions <p><strong>Purpose:</strong> Predicting and then preventing cardiac arrest of a patient in ICU is the most challenging phase even for a most highly skilled professional. The data been collected in ICU for a patient are huge, and the selection of a portion of data for preventing cardiac arrest in a quantum of time is highly decisive, analysing and predicting that large data require an effective system. An effective integration of computer applications and cardiovascular data is necessary to predict the cardiovascular risks. A machine learning technique is the right choice in the advent of technology to manage patients with cardiac arrest.</p> <p><strong>Methodology:</strong> In this work we have collected and merged three data sets, Cleveland Dataset of US patients with total 303 records, Statlog Dataset of UK patients with 270 records, and Hungarian dataset of Hungary, Switzerland with 617 records. These data&nbsp;are&nbsp;the most comprehensive data set with a combination of all three data sets consisting of 11 common features with 1190 records.</p> <p><strong>Findings/Results:</strong> Feature extraction phase extracts 7 features, which contribute to the event. In addition, extracted features are used to train the selected machine learning classifier models, and results are obtained and obtained results are then evaluated using test data and final results are drawn. Extra Tree Classifier has the highest value of 0.957 for average area under the curve (AUC).</p> <p><strong>Originality:</strong> The originality of this combined Dataset analysis using machine learning classifier model results Extra Tree Classifier with highest value of 0.957 for average area under the curve (AUC).</p> <p><strong>Paper Type:</strong> Experimental Research</p> <p>&nbsp;</p> Krishna Prasad K, Aithal P. S., Navin N. Bappalige, Soumya S Copyright (c) 2021 International Journal of Health Sciences and Pharmacy (IJHSP) Sat, 17 Apr 2021 00:00:00 +0000 Tracking and Monitoring Fitness of Athletes Using IoT Enabled Wearables for Activity Recognition and Random Forest Algorithm for Performance Prediction <p><strong>Purpose</strong>:&nbsp;&nbsp; The progression in technology is made the best use of&nbsp;in&nbsp;every field. Sports analytics is an essential sector that has gained importance in this technology-driven era. It is used to determine the hidden relationships among different quantitative parameters that affect the performance of athletes. This type of analysis requires a large amount of data to be stored periodically. Cloud acts as a scalable centralized repository that can store the massive data essential for analysis purpose.&nbsp;&nbsp; From the technological perspective there are numerous wearable activity tracking devices, which will be able to provide feedback of physical activities. With the help of random forest (RF) algorithm it is possible to classify huge datasets to perform predictions. In this paper, different smart devices that can be used to measure physical activity, use of RF algorithm for converting data obtained from smart devices into knowledge are explored. A conceptual model that uses&nbsp;&nbsp; wearable devices for tracking and monitoring&nbsp;&nbsp;&nbsp; and RF algorithm to predict the performance is suggested.</p> <p><strong>Methodology</strong>:&nbsp; The study was conducted by referring to&nbsp;scholarly documents available online and by referring to websites of companies offering healthcare and sports related services. A conceptual model is developed based on the theoretical perception that incorporates the components needed for measuring the physical activities to predict the performance of athletes.&nbsp;&nbsp;</p> <p><strong>Findings/Result</strong>: In this paper the proposed system contains four major activities as Capture, Store, Analyze, and Predict. The model considers use of IoT-enabled wearable devices to measure the physical activities of athletes and the information collected will in turn be used to analyze predict their performance and suggest them how to increase the chances of winning. However, the outcome of a game does not only depend upon the PA of athletes. It depends also upon the physical, mental, emotional health, nutrition and many other factors.</p> <p><strong>Originality: </strong>In this paper, a theoretical model is deduced to integrate IoT and RF Algorithm to track and monitor fitness of athletes using wearables for activity recognition and performance prediction.</p> <p><strong>Paper Type:</strong> Conceptual Paper</p> Krishna Prasad K., Aithal P. S., Geetha Poornima K., Vinayachandra Copyright (c) 2021 Wed, 21 Apr 2021 00:00:00 +0000 An AI-based Analysis of the effect of COVID-19 Stringency Index on Infection rates: A case of India <p><strong>Purpose</strong>: The impact of the COVID-19 pandemic has already been felt worldwide, disrupting the unremarkable life of individuals. Social consequences and viral transmission are challenges that must be resolved to effectively overcome the problems that occur&nbsp;throughout this pandemic. The COVID-19 infection data about India were represented using different statistical models. In this paper, the authors focus on the data collected between 1<sup>st</sup> January 2020 and 12<sup>th</sup> April 2021, try analyzing the different indexes related to India, and predict the number of infected people in the near future. Based on the infection rate, it is possible to classify a country as “fixed,” “evolving” and “exponential.” Based on the prediction, some recommendations are proposed to contain the outbreak of the disease. This will also help the government and policymakers to identify and analyze various risks associated with 'opening up' and 'shutting down' in response to the outbreak of the disease. With the help of these models, it is possible to predict the number of cases in the near future.</p> <p><strong>Methodology</strong>:&nbsp;&nbsp;&nbsp; COVID-19 Stringency Index, Government Response Index, and Containment Health Index calculated, published, and updated real-time by a research group from Oxford University ( on 21 mitigation and suppression measures employed by different countries were analyzed using a few mathematical models to find the relationship between Stringency Index and infection rates and forecast trends. A new model was proposed after analyzing a few mathematical models proposed by the researchers. Data analytics was also conducted using AI-based data analytics tools available online.&nbsp; The dataset was kept updated until the date April 20, 2021, was downloaded for this purpose. The appropriate values were extracted from the original dataset and used to construct a sub-dataset, which was then used for the analytics. An AI-based online Data Analytics tool provided by datapine was used to forecast trends.</p> <p><strong>Findings/Result</strong>: It was observed that in India, as in other countries, there is a close association between Stringency Level and COVID-19 cases. The higher the degree of stringency, the lower the cases, and vice versa. The same can be said about the government's role and degree of containment &amp; health.</p> <p><strong>Originality: </strong>In this paper, we analyzed various mathematical models for predicting the total number of COVID-19 cases and deaths due to COVID-19 in India. We also examined the relationship between total cases and the Government's Response Index, Containment &amp; Health Index, and Stringency Index indicators. The model we proposed to predict COVID-19 cases on a day-by-day basis had a 98 percent accuracy rate and a 2% error rate.</p> <p><strong>Paper Type:</strong> Analytical. With prerecorded datasets obtained from online resources, and data analysis was conducted using mathematical models and AI-based analytical tools.</p> Krishna Prasad K., Aithal P. S., Vinayachandra, Geetha Poornima K. Copyright (c) 2021 Sun, 02 May 2021 00:00:00 +0000 Zuber’s Coronavirus Disease (COVID- 19) Standards for Hospitals <p><strong><em>Purpose:</em></strong> The&nbsp;Coronavirus&nbsp;Disease (COVID-19) is affecting&nbsp;220 nations and territories in the world. As of May 11th, 2021, there were 158,651,638&nbsp;reported and confirmed cases of COVID-19 to WHO, out of which 3,299,764&nbsp;were reported death to WHO. However, there are no defined, structured and concise Coronavirus Disease&nbsp;(COVID- 19) Standards for Hospitals in order to manage such cases in the hospitals by maintain quality, patient safety, risk management and patient experience.</p> <p><strong><em>Objective:</em></strong> To develop Coronavirus Disease&nbsp;(COVID- 19) Standards for Hospitals.</p> <p><strong><em>Method:</em></strong> This is a review of literature study and the data were collected with comprehensive searches in the online databases of goggle scholars and research gate.</p> <p><strong><em>Conclusions:</em></strong> The study concluded with “Zuber’s Coronavirus Disease&nbsp;(COVID- 19) Standards for Hospitals.”</p> Zuber Mujeeb Shaikh Copyright (c) 2021 Fri, 14 May 2021 00:00:00 +0000 Zuber’s Person-Centered Care Clinical Governance Standards for Hospitals <p><strong>Purpose:</strong> To establish the Clinical Governance standards for hospitals based on the Person-Centered Care concepts since it is crucial in improving standards of care that patients receive.</p> <p><strong>Objective:</strong> To develop Person Centered Care Clinical Governance Standards for Hospitals.</p> <p><strong>Method:</strong> This is a review of literature study and the data were collected with comprehensive searches in the online databases of Google Scholars and Research Gate.</p> <p><strong>Conclusions:</strong> The study concluded with “Zuber’s Person-Centered Care Clinical Governance Standards for Hospitals.”</p> Zuber Mujeeb Shaikh Copyright (c) 2021 Thu, 20 May 2021 00:00:00 +0000