Healthcare Data Analytics using Power BI

2022 ◽  
Vol 10 (1) ◽  
pp. 0-0
Keyword(s):  
Health Care ◽  
Cost Reduction ◽  
Data Analytics ◽  
Medical Services ◽  
Predictive Analysis ◽  
System Management ◽  
Effective Utilization ◽  
Healthcare Data ◽  
Promising Tool ◽  
Systematic Collection

Innovations in computer technologies have revolutionized attention in recent years. Data analytics has emerged as a promising tool for determination problems in various health care connected disciplines. The effective utilization of knowledge mining in deeply noticeable fields like e-business, promoting and retail has prompted application in completely different businesses and divisions. Among these components merely finding is the medical services. Medical services organizations can reduce down on medical services expense and furnish better consideration with the help of predictive analysis. Enormous information likewise helps in diminishing medicine mistakes by improving budgetary and regulatory execution, and decrease readmission. The paper aims at systematic collection of patient-related healthcare data ,analyse through Microsoft Power BI after some transformations of data and determine major disciplines to improve the patient engagement, health system management, diagnosis and cost reduction.

scholarly journals Challenges and Trends in Clinical Data Analytics

2020 ◽  
pp. 348-360
Keyword(s):  
Health Care ◽  
Data Analysis ◽  
Clinical Data ◽  
Data Analytics ◽  
Health Care Systems ◽  
Data Sets ◽  
Handwritten Documents ◽  
Healthcare Data ◽  
Clinical Data Analysis ◽  
Care Systems

:Today’s technological advancements facilitated the researcher in collecting and organizing various forms of healthcare data. Data is an integral part of health care analytics. Drug discovery for clinical data analytics forms an important breakthrough work in terms of computational approaches in health care systems. On the other hand, healthcare analysis provides better value for money. The health care data management is very challenging as 80% of the data is unstructured as it includes handwritten documents, images; computer-generated clinical reports such as MRI, ECG, city scan, etc. The paper aims at providing a summary of work carried out by scientists and researchers who worked in health care domains. More precisely the work focuses on clinical data analysis for the period 2013 to 2019. The organization of the work carried out is specifically with concerned to data sets, Techniques, and Methods used, Tools adopted, Key Findings in clinical data analysis. The overall objective is to identify the current challenges, trends, and gaps in clinical data analysis. The pathway of the work is focused on carrying out on the bibliometric survey and summarization of the key findings in a novel way.

scholarly journals BIG DATA ANALYSIS IN HEALTH CARE DOMAIN: A SYSTEMATIC REVIEW

2020 ◽  
Vol 5 (2) ◽  
pp. 1-8
Author(s):  
Abhishek Bajpai ◽  
Dr. Sanjiv Sharma
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Healthcare Data ◽  
Challenges And Opportunities ◽  
Business Profit

As the Volume of the data produced is increasing day by day in our society, the exploration of big data in healthcare is increasing at an unprecedented rate. Now days, Big data is very popular buzzword concept in the various areas. This paper provide an effort is made to established that even the healthcare industries are stepping into big data pool to take all advantages from its various advanced tools and technologies. This paper provides the review of various research disciplines made in health care realm using big data approaches and methodologies. Big data methodologies can be used for the healthcare data analytics (which consist 4 V’s) which provide the better decision to accelerate the business profit and customer affection, acquire a better understanding of market behaviours and trends and to provide E-Health services using Digital imaging and communication in Medicine (DICOM).Big data Techniques like Map Reduce, Machine learning can be applied to develop system for early diagnosis of disease, i.e. analysis of the chronic disease like- heart disease, diabetes and stroke. The analysis on the data is performed using big data analytics framework Hadoop. Hadoop framework is used to process large data sets Further the paper present the various Big data tools , challenges and opportunities and various hurdles followed by the conclusion.                                      

scholarly journals Understanding the Difference Between Healthcare Informatics and Healthcare Data Analytics in the Present State of Health Care Management

2020 ◽  
Vol 7 ◽  
pp. 233339282095266
Author(s):  
Thomas Wan ◽  
Varadraj Gurupur
Keyword(s):  
Health Care ◽  
Data Analytics ◽  
Care Management ◽  
Healthcare Management ◽  
State Of Health ◽  
Healthcare Informatics ◽  
Healthcare Data ◽  
Scientific Analysis ◽  
The Difference ◽  
Future Direction

The purpose of this article is to perform a scientific analysis of the definitions associated with healthcare informatics and healthcare data analytics. Additionally, the authors attempt to redefine the scientific pursuit of healthcare informatics and healthcare data analytics. This commentary can assist the thinking of informaticians and data analysts working in healthcare management and practice. The authors also provide a brief insight on the possible future direction of informatics and analytics associated with healthcare.

Current Practices and Challenges of Medical Services on Health Care System of Mandalay General Hospital

2019 ◽  
Vol 31 (2) ◽  
pp. 131
Keyword(s):  
Health Care ◽  
General Hospital ◽  
Health Care Providers ◽  
Quality Care ◽  
Healthcare Providers ◽  
Medical Services ◽  
Tertiary Level ◽  
Care Providers ◽  
Level Hospital ◽  
Care System

In Myanmar, the main challenge to provide quality healthcare by Universal Health Care approach is documented as low health services coverage with substantial wealth-based inequality. To achieve the effective health care system, strong medical care system is essential. Understanding on challenges and needs in provision of medical services among patients and health care providers is critical to provide quality care with desirable outcomes. The aim of the study was to explore the patients’ and health care providers’ perceptions on the challenges in provision of medical services at the Mandalay General Hospital. This was a qualitative study conducted at the tertiary level hospital (Mandalay General Hospital). The data was collected by using focus group discussions and in-depth interviews with hospitalized patients or attendants, healthcare providers such as medical doctors, nurses, laboratory scientists and hospital administrators in March 2017. The qualitative data was analyzed using themes by themes matrix analysis. Most patients were satisfied with the care provided by the doctors because they believed that they received quality care. However, some patients complained about long waiting time for elective operation, congested conditions in the ward, burden for investigations outside the hospital for urgent needs and impolite manners of general workers. Healthcare providers reported that they had heavy workload due to limited human and financial resources in the hospital, poor compliances with hospital rules and regulation among patients and attendants, and inefficient referral practices from other health facilities. Other challenges experienced by healthcare providers were lack of ongoing training to improve knowledge and skills, limited health infrastructure and inadequate medicinal supplies. The findings highlighted the areas needed to be improved to provide quality health care at the tertiary level hospital. The challenges and problems encountered in this hospital can be improved by allocating adequate financial and human resources. The systematic referral system and hospital management guidelines are needed to reduce workload of health staff.

scholarly journals Big Data Analytics in urology: the story so far and the road ahead

2021 ◽  
Vol 13 ◽  
pp. 175628722199813
Author(s):  
B. M. Zeeshan Hameed ◽  
Aiswarya V. L. S. Dhavileswarapu ◽  
Nithesh Naik ◽  
Hadis Karimi ◽  
Padmaraj Hegde ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Early Stage ◽  
Big Data Analytics ◽  
Positive Trend ◽  
The Road ◽  
Healthcare Data ◽  
Urological Disorders ◽  
Different Sources

Artificial intelligence (AI) has a proven record of application in the field of medicine and is used in various urological conditions such as oncology, urolithiasis, paediatric urology, urogynaecology, infertility and reconstruction. Data is the driving force of AI and the past decades have undoubtedly witnessed an upsurge in healthcare data. Urology is a specialty that has always been at the forefront of innovation and research and has rapidly embraced technologies to improve patient outcomes and experience. Advancements made in Big Data Analytics raised the expectations about the future of urology. This review aims to investigate the role of big data and its blend with AI for trends and use in urology. We explore the different sources of big data in urology and explicate their current and future applications. A positive trend has been exhibited by the advent and implementation of AI in urology with data available from several databases. The extensive use of big data for the diagnosis and treatment of urological disorders is still in its early stage and under validation. In future however, big data will no doubt play a major role in the management of urological conditions.

scholarly journals Health status and health care utilization after discharge from geriatric in-hospital stay – description of a register-based study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
E. Rydwik ◽  
R. Lindqvist ◽  
C. Willers ◽  
L. Carlsson ◽  
G. H. Nilsson ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Health Status ◽  
Health Care Utilization ◽  
Care Utilization ◽  
Future Studies ◽  
Healthcare Data ◽  
Utilization Data ◽  
Hospital Stays ◽  
Socioeconomic Data

Abstract Background This study is the first part of a register-based research program with the overall aim to increase the knowledge of the health status among geriatric patients and to identify risk factors for readmission in this population. The aim of this study was two-fold: 1) to evaluate the validity of the study cohorts in terms of health care utilization in relation to regional cohorts; 2) to describe the study cohorts in terms of health status and health care utilization after discharge. Methods The project consist of two cohorts with data from patient records of geriatric in-hospital stays, health care utilization data from Stockholm Regional Healthcare Data Warehouse 6 months after discharge, socioeconomic data from Statistics Sweden. The 2012 cohort include 6710 patients and the 2016 cohort, 8091 patients; 64% are women, mean age is 84 (SD 8). Results Mean days to first visit in primary care was 12 (23) and 10 (19) in the 2012 and 2016 cohort, respectively. Readmissions to hospital was 38% in 2012 and 39% in 2016. The validity of the study cohorts was evaluated by comparing them with regional cohorts. The study cohorts were comparable in most cases but there were some significant differences between the study cohorts and the regional cohorts, especially regarding amount and type of primary care. Conclusion The study cohorts seem valid in terms of health care utilization compared to the regional cohorts regarding hospital care, but less so regarding primary care. This will be considered in the analyses and when interpreting data in future studies based on these study cohorts. Future studies will explore factors associated with health status and re-admissions in a population with multi-morbidity and disability.

Guidelines for Pediatric Emergency Care Facilities

PEDIATRICS ◽  
1995 ◽  
Vol 96 (3) ◽  
pp. 526-537
Author(s):  
Keyword(s):  
Health Care ◽  
Emergency Medical Services ◽  
Emergency Care ◽  
Pediatric Emergency ◽  
Medical Services ◽  
Emergency Medical ◽  
Care Facilities ◽  
Trained Personnel ◽  
Pediatric Emergency Care

Emergency care for life-threatening pediatric illness and injury requires specialized resources including equipment, drugs, trained personnel, and facilities. The American Medical Association Commission on Emergency Medical Services has provided guidelines for the categorization of hospital pediatric emergency facilities that have been endorsed by the American Academy of Pediatrics (AAP).1 This document was used as the basis for these revised guidelines, which define: 1. The desirable characteristics of a system of Emergency Medical Services for Children (EMSC) that may help achieve a reduction in mortality and morbidity, including long-term disability. 2. The role of health care facilities in identifying and organizing the resources necessary to provide the best possible pediatric emergency care within a region. 3. An integrated system of facilities that provides timely access and appropriate levels of care for all critically ill or injured children. 4. The responsibility of the health cane facility for support of medical control of pre-hospital activities and the pediatric emergency care and education of pre-hospital providers, nurses, and physicians. 5. The role of pediatric centers in providing outreach education and consultation to community facilities. 6. The role of health cane facilities for maintaining communication with the medical home of the patient. Children have their emergency care needs met in a variety of settings, from small community hospitals to large medical centers. Resources available to these health care sites vary, and they may not always have the necessary equipment, supplies, and trained personnel required to meet the special needs of pediatric patients during emergency situations.

Sign in / Sign up

Export Citation Format

Share Document