We use cookies to give you the best experience possible. By continuing we’ll assume you’re on board with our cookie policy

CHAPTER ONE- introduction Essay

Paper type: Essay Pages: 12 (2861 words)

Views: 254

CHAPTER ONEINTRODUCTION1.1 BACKGROUND OF THE STUDYBig data has rapidly made its way into a wide range of industries and has changed the way we manage, analyze and leverage data in any industry. One of the most promising areas where it can be applied to make a change is healthcare. The healthcare sector is one of the largest and most complex industries. Healthcare analytics have the potential to reduce costs of treatment, predict outbreaks of epidemics, avoid preventable diseases and improve the quality of life in general.

The application of big data analytics in healthcare has a lot of positive and also life-saving outcomes. Big data refers to the vast quantities of information created by the digitization of everything, that gets consolidated and analyzed by specific technologies. Applied to healthcare, it will use specific health data of a population (or of a particular individual) and potentially help to prevent epidemics, cure disease, cut down costs, etc.Big data in healthcare and medicine refers to these various large and complex data, which they are difficult to analyze and manage with traditional software or hardware.

Particularly, big data analytics in medicine and healthcare enables analysis of the large datasets from thousands of patients, identifying clusters and correlation between datasets, as well as developing predictive models using data mining techniques. Big data analytics in medicine and healthcare integrates analysis of several scientific areas such as bioinformatics, medical imaging, sensor informatics, medical informatics and health informatics. Treatment models in our present health care system, have changed and many of these changes are namely driven by data. Doctors want to understand as much as they can about a patient and as early in their life as possible, to pick up warning signs of serious illness as they arise. This is because treating any disease at an early stage is far simpler and less expensive. With healthcare data analytics, prevention is better than cure. Indeed, for years gathering huge amounts of data for medical use has been costly and time-consuming. With today’s always-improving technologies, it becomes easier not only to collect such data but also to convert it into relevant critical insights, that can then be used to provide better care. The healthcare industry is changing, and like any other, big data is starting to transform it in several ways. Application areas of big data analytics in health care include:Improvement of hospital staff as a result of daily and hourly predictions of how many patients are expected to be at each hospital.Electronic Health Records (EHRs)Real-time alerting for instant careEnhancement of patient engagement in their own healthUsage of health data for a better-informed strategic planningMore extensive research to cure cancerPredictive analyticsReduction of fraud and enhancement of data securityTelemedicineIntegrating medical imaging for a broader diagnosisPreventing unnecessary ER visits.This research work focuses on the area of telemedicine as an application of big data to the Nigerian Health Care System.1.1.1TELEMEDICINETelemedicine has been present on the market for over 40 years, but only today, with the arrival of online video conferences, smartphones, wireless devices, and wearables, has it been able to come into full bloom. The term refers to delivery of remote clinical services using technology.It is used for primary consultations and initial diagnosis, remote patient monitoring, and medical education for health professionals. Some more specific uses include telesurgery ” doctors can perform operations with the use of robots and high-speed real-time data delivery without physically being in the same location with a patient.Clinicians use telemedicine to provide personalized treatment plans and prevent hospitalization or re-admission. Such use of healthcare data analytics can be linked to the use of predictive analytics. It allows clinicians to predict acute medical events in advance and prevent deterioration of patient’s conditions.1.1.2THE NIGERIAN HEALTH CARE SYSTEMThe Nigerian health care has suffered several down-falls. Despite Nigerian’s strategic position in Africa, the country is greatly underserved in the health care sphere. Health facilities (health centers, personnel, and medical equipment) are inadequate in this country, especially in rural areas. While various reforms have been put forward by the Nigerian government to address the wide-ranging issues in the health care system, they are yet to be implemented at the state and local government area levels. According to the 2009 communiqu© of the Nigerian national health conference, health care system remains weak as evidenced by lack of coordination, fragmentation of services, dearth of resources, including drug and supplies, inadequate and decaying infrastructure, inequity in resource distribution, and access to care and very deplorable quality of care. The communiqu© further outlined the lack of clarity of roles and responsibilities among the different levels of government to have compounded the situation. The challenges continue to mount as people keep dying of minor illnesses that could have been prevented or treated with simple medications and healthy lifestyle. People in Nigeria continue to experience avoidable deaths. The habit of periodic medical check-up has still not been formed and swaths of the population only go to the doctor or to the hospital when seriously ill only to be misdiagnosed or wrongly medicated.Most of the time, people seek medical assistance when the illness has reached an advanced stage. In some cases, no medical attention is sought due to paucity of funds. In such situations, individuals are forced to seek quack doctors. Generally speaking, lack of access to quality healthcare coupled with the prevalence of quack hospitals and doctors, fake drugs and substandard products, seemingly put staggering financial burdens on families and the nation.According to statistics, in Nigeria, primary healthcare centres do not get at least 20% of their medications every year. People are forced to travel from clinic to clinic to find a doctor with the right medicine. This situation creates additional lines at doctors` offices. Moreover, lack of medicines leads to death of hundreds of Nigerians every year. People from rural areas have no choice besides travelling to the nearest city for medical help. Lack of facilities lead to the overpopulation of available facilities. It also leads to a situation when doctors and nurses overwork. 1.2OBJECTIVES OF THE STUDYThis study is aimed at developing a Medical Diagnosis and Prescription Software that will mimic a medical doctor and exclusively:Carry out accurate and precise diagnosis based on the symptom(s) selected by the patient or usersGive appropriate medical recommendations to the patient to get prescribed medications, chat online with a medical doctor or visit the hospital immediately depending on the severity of the illness diagnosed.1.3STATEMENT OF THE PROBLEMThe Healthcare sector is booming at a faster rate and the necessity to manage patient care and innovate medicines has increased synonymously. Diagnosis of tropical diseases in Africa has been a long-time problem due to poverty and lack of good healthcare facilities. Most people could not even afford the available ones. The Nigerian health care, in particular had suffered several infectious disease outbreaks and mass chemical poisoning for several years. Hence, there is immense need to incorporate smart, data-driven thinking and large swathes of research and clinical data into the traditional method of medical diagnosis as opposed to relying solely on physician’s schooling and professional opinion.In recent years, records have shown an increase in inaccuracy and imprecision in medical diagnosis as most patient who are unable to visit a clinic for proper diagnosis end up treating sickness inappropriately or treating the sickness when it has escalated into an advanced and severe stage, thereby leading to deaths. This software will go a long way to eliminate these problems.1.4SIGNIFICANCE OF THE PROJECTThe importance of this project cannot be over- emphasized. The design, development and implementation of the medical diagnosis and prescription software which can be classified as an application of telemedicine in health care can help to save money by reducing the cost of medical services and most importantly, save people’s lives, if well deployed. This is because it allows for early identification of illnesses of individual patients and socioeconomic groups and taking preventive actions because, as we all know, prevention is better than cure. The medical diagnosis and prescription software can help patients avoid waiting lines or long queues. Also, doctors will not need to waste time for unnecessary consultations and paperwork. It can help to bring good health care closer to the unreached while improving the quality of service offered by health care professionals.1.5SCOPE AND LIMITATION OF STUDY This project covers the diagnosis of the tropical diseases, illnesses and medical conditions stated below:Simple or Uncomplicated MalariaTyphoid feverStomach ulcerCholeraTuberculosisBreast cancerDiabetics (Type 1)HypertensionInternal/ External HemorrhoidsGastroesophageal Reflux disease (GERD)Sleep apneaInsomniaDiarrheaPre-Menstrual Syndrome (PMS)In addition, the software interacts with the patients and prescribes drugs or gives other medical recommendations based on the symptoms they have selected.1.6SIGNIFICANT BENEFITS OF BIG DATA ANALYTICS IN THE HEALTHCARE SECTORBig Data Analytics have huge potentials and presents us with several benefits that can help and change the entire scenario of the Healthcare sector. These include:1. Health TrackingBig Data Analytics along with the Internet of Things (IoT), is revolutionizing the way one can track various user statistics and vitals. Apart from the basic wearables that can detect the patient’s sleep, heart rate, exercise, distance walked, etc. there are new medical innovations that can monitor the patient’s blood pressure, pulse Oximeters, glucose monitors, and more. The continuous monitoring of the body vitals along with the sensor data collection will allow healthcare organizations to keep people out of the hospital since they can identify potential health issue and provide care before the situation goes worse.2. Reducing hospital costs and wait timesBig Data can be a great way to save costs for hospitals that either over or under book staff members. Predictive analysis can help resolve this issue by predicting the admission rates and help with staff allocation. It can save wait times for patients since the hospital will have adequate staff and beds available as per the analysis all the time. As with many other industries, there is enormous potential for cutting costs with big data in healthcare. There’s also an opportunity to reduce wait times”something that costs everyone money. One hospital in Paris is using predictive analytics to assist with staffing. By predicting admission rates over the next two weeks, the hospital can then allocate staff based on those numbers. 3. Identifying and assisting High-Risk PatientsUsing predictive analytics, some hospitals have been able to reduce the number of emergency room visits by identifying high-risk patients and offering customized, patient-centric care. Digitized hospital records can help to identify the patients approaching the hospital repeatedly and identify their chronic issues. Such understanding will help in giving such patients better care and provide an insight into corrective measures to reduce their frequent visits. It is a great way to keep a list and check on high-risk patients and offer them customized care. Many healthcare systems have to contend with high rates of patients repeatedly using the emergency department, which drives up healthcare costs and does not lead to better care or outcomes for these patients. 4. Preventing Medication ErrorsBig data analytics can be a great tool for physicians who cater to many patients in a day. It has been noted that the professionals tend to either prescribe a wrong medicine or dispatch a different medication by mistake. Such errors, in general, can be reduced since Big Data can be leveraged to analyze user data and the prescribed medication. It can corroborate the data and flag potential out of place prescription to reduce mistakes and save lives. Medication errors are a serious problem in healthcare organizations. Because humans will always make the occasional error (even something as simple as choosing the wrong medication in a pull-down menu), patients sometimes end up with the wrong medication”which could cause harm or even death. Big data can help reduce these error rates dramatically by analyzing the patient’s records with all medications prescribed and flagging anything that seems out of place.MedAware, an Israeli start-up has already developed this type of software, with encouraging results. Records for 747,985 patients were analyzed in a clinical study, and from those, 15,693 were flagged. From a sample of 300, about 75 per cent of these alerts were validated, showing that the software could be an important tool for physicians, potentially saving the industry up to $21bn per year.5. Preventing security breaches and fraudAccording to one study, the healthcare industry is 200 per cent more likely to experience a data breach than other industries, simply because the personal data is so valuable. With this in mind, some organizations have used big data to help prevent fraud and security threats. For example, The Centres for Medicare and Medicaid Services were able to prevent a staggering $210.7m in fraud in just one year using big data analytics.6. Enhancing patient engagement and outcomesConsumer interest in devices that monitor steps taken, hours slept, heart rate, and other data on a daily basis shows that introducing these devices as a physician aid could help improve patient engagement and outcomes.New wearables can track specific health trends and relay them back to the cloud where they can be monitored by physicians. This can be helpful for everything from asthma to blood pressure, and help patients stay independent and reduce unnecessary doctors’ visits.These wearables are unfortunately still in their infancy, and complications with insurance, software compatibility, and many other obstacles are currently limiting their usefulness.7. Advancement in Healthcare SectorApart from the current scenario, Big Data can be a great benefit for advancement in science and technology. For Healthcare, Artificial Intelligence, such as IBM’s Watson can be used to surf through numerous data within seconds to find solutions for various diseases. Such advancement is already in progress and will continue to grow with the amount of research collected by Big Data. It will not only be able to provide accurate solutions, but also offer customized solutions for unique problems. 1.7HOW BIG DATA IMPACTS HEALTHCARE Google Flu Trends: a service that predicts and locates outbreaks of flu by making use of information aggregate search queries. The San Francisco-based Global Viral (GV) uses advanced data analysis on information mined from the Internet to identify comprehensively the locations, sources and drivers of local outbreaks before they become global epidemics. IBM’s Watson: Health has been the first area of commercial application of this technology for IBM. Watson’s ability to understand questions and context, and to rife through 200 million pages of data and provide precise responses in just seconds. This can help a physician treating a patient to consider all related texts, reference materials, prior cases, and the latest knowledge in journals and medical literature. Accenture targets the 4% chronically ill patients that tie up more than 60% of the hospital resources through a service that monitors the chronically ill patients that can live at home, avoiding readmission to hospital. IBM, through their Smarter Cities’ initiatives, has supported home care of chronically ill patients (e.g. Stavanger Hospital in Norway).Monitoring patients’ conditions is made on the basis of medical and lab records, as well as self-reporting of key parameters from instruments available to the patients.In the area of patient monitoring and management, many hospitals have started to apply big data analytics in the care of chronically ill patients to reduce cost per patient and to avoid unnecessary admissions to hospitals.1.8 BASIC QUALITIES OF BIG DATA IN HEALTHCAREIn the healthcare industry, Big Data can be explained by reviewing its basic qualities, commonly called the 3 Vs; Velocity, Volume, and variety. VolumeVolume refers to the rapid rate of data-growth in the healthcare sector. In 2020, it is estimated there will be more than 44 times more data than there was in 2009. Big data software and techniques work to manage these large chunks of data and turn them into valuable information. VelocityVelocity represents the frequency at which data is being transmitted and shared. Technologies such as monitoring and sensing devices, social media, and embedded chips ” today added in almost every device from airplanes, refrigerators to bodily implants ” all contribute to the expanding mounds of available data. And in the healthcare sector, the velocity of data-sharing continues to rise by the day.VarietyVariety represents the numerous forms in which data exists today. In healthcare, this includes unstructured data in text format, streams of date from monitoring and sensing gadgets, test or email messages, scanned documents, video or audio, and procedures that add to the variety of unstructured healthcare data.1.12 DEFINITION OF TERMSEHR: ELECTRONIC HEALTH RECORD. Electronic health record (EHR) is a digital version of a patient’s paper chart. EHRs are real-time, patient-centered records that make information available instantly and securely to authorized users.ER: EMERGENCY ROOM. The ER is the part of a hospital where people who have severe injuries or sudden illnesses are taken for emergency treatment.IOT: INTERNET OF THINGS. The Internet of Things refers to the billions of physical devices around the world that are now connected to the internet, collecting and sharing data.IBM: INTERNATIONAL BUSINESS MACHINES. International Business Machines Corporation is an American multinational information technology company headquartered in Armonk, New York, United States.GV: GLOBAL VIRAL. Global Viral (GV) is an independent non-profit research organization focusing on innovative and disruptive research in Ecology, Biodiversity and Public Health GERD: GASTROESOPHAGEAL REFLUX DISEASE. Gastroesophageal reflux disease is a digestive disorder that affects the lower esophageal sphincter (LES), the ring of muscle between the esophagus and stomach.

Cite this page

CHAPTER ONE- introduction. (2019, Aug 20). Retrieved from https://studymoose.com/chapter-one-introduction-essay

How to Avoid Plagiarism
  • Use multiple resourses when assembling your essay
  • Use Plagiarism Checker to double check your essay
  • Get help from professional writers when not sure you can do it yourself
  • Do not copy and paste free to download essays
Get plagiarism free essay

Not Finding What You Need?

Search for essay samples now

image

Your Answer is very helpful for Us
Thank you a lot!