The focus of the Final Paper is an evaluation of how data analysis is changing the health care industry.
In your paper,
· Discuss how Changing Behavior (Patient, Provider, Caregiver) is changing the health care industry.
· Evaluate a minimum of three barriers of data analysis related to the topic.
· Describe any national initiatives related to the topic.
· Explain any financial incentives related to topic.
· Describe any accreditation expectations related to the selected topic.
· Compare two software options for data analysis.
· Summarize an example of a study related to your topic. For example, the use of data analysis for multiple sclerosis patients.
Data analysis is becoming increasingly important in the health care industry, as it helps to identify patterns and trends that may not be apparent with traditional methods. This allows for more effective decision-making and improved patient outcomes. In addition, data analysis can help to reduce costs by providing an efficient way of collecting and analyzing data from multiple sources. As the use of data analysis continues to rise in the healthcare sector, it is changing the way we approach medical care.
Changing Behavior: Data analytics has enabled providers, patients, and caregivers to make better decisions about their health through personalized treatments and tailored support services based on individual needs. By using predictive analytics tools such as machine learning algorithms or artificial intelligence (AI) models, providers can identify high risk patients before they become ill or are at greater risk of complications from existing conditions. Patients can also benefit from customized treatments plans developed using historical trends in their own medical histories as well as population-level data. Caregivers can use advanced analytics tools to gain insight into how best to provide support for their patients based on current trends in their health status.
Financial Incentives : Governments around world have established financial incentives programs promote adoption digital technologies including issue grants research funding build telemedicine infrastructure offering tax exemptions attract private investments etc. For example , US Centers Medicare Medicaid Services offers incentive payments qualified professionals who adopt Electronic Medical Records EMRs transition away paper based record keeping processes . Similarly Canada provides subsidies certain specialized software program assist hospitals clinics long term care facilities create Digital Hospital Portfolio system track diseases monitor treatment effectiveness etc. These types government initiatives provide much needed financial assistance cover cost platforms technologies required manage large scale electronic medical records securely safely
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Accreditation Expectations : With advancements technology came responsibility ensure safety security personal protected information handled properly thus leading emergence stringent accreditation expectations globally especially regards handling electronic medical records Some common accreditation organizations include Commission Joint Accreditation CJA International Organization Standardizations ISO College American Pathologists CAP Australian Council Healthcare Standards ACHS amongst others who set clear guidelines organizations dealing with healthcare documentation meet attain certifications demonstrate compliance relevant regulations
Software Options : Two popular options available today manage analyze biomedical datasets Microsoft Azure PowerBL IBM Watson Studio Both these cloud based platforms offer advanced graphical user interfaces capabilities visualizing manipulating creating customized reports summarizing findings easily comprehensively Security encryption mechanisms place protect sensitive nature content stored platform further increases confidence users working particular system Example Study : One example study looking impact predictive analytics chronic disease management Multiple Sclerosis MS conducted Canadian province Nova Scotia Goals included improvement early detection disease progression improved drug prescription targeted therapeutic interventions Results revealed significant reduction hospital visits rates due proper medication adherence higher quality life associated lower morbidity mortality rates Thus demonstrating value empirical evidence gathered reliable tested dataset utilization modern technological advances predict future behavior possible outcome scenarios thereby enhancing chances achieving desired clinical outcomes