Healthcare is an industry that is complex and overwhelmed with data. When taking into account how much data is collected in a daily timeframe, then multiply that by 365 days in a year, the data obtained can be turned into information and help achieve advancements within the medical field. Data is defined as “uninterpreted elements such as a person’s name, weight, or age. Because they are uninterpreted, they do not have meaning (Nelson & Staggers, 2014).” In order for data to have meaning, an analysis would need to be done to translate the data into becoming information. Information is then used to help the health care industry make informed decisions to assist in the treatment, management, diagnosis, and effective for health care and medicine
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KDDM has the ability to take large amounts of data then extract, clean, and pre-process the data applied to machine learning applications to help develop a hypothesis of future events as well as identify links with complete or incomplete data (Nelson & Staggers, 2014). Due to the fact that KDDM is able to use very large amounts of data for analysis, comprehensive data can be evaluated and detect very subtle patterns within the data with low costs if utilizing electronic health records (EHRs) to obtain the data. With the health care market steadily converting to EHRs the amount of data and availability of data is vast and limitless. EHRs have virtually changed how we collect, maintain, sustain, manage, and use data collected. KDDM allows for the development of medical knowledge which in turn helps improvement in support of clinical decision-making, identifying links in data to help prevent future events, help support validity in studies, detect patterns in data, and support quality improvement efforts (Nelson & Staggers, …show more content…
The overall outcome in the healthcare field is to provide accurate, effective, precise care to a patient to improve their health not to have the patient go into further decline in health. When a patient is diagnosed with cancer there are now more avenues to consider for treatment than 50 years ago, let along 10 years ago. This is because research has identified threats, trends, markers, genetics, and knowledge to providers to learn better ways to treat illnesses. Adding into the mix EHRs that have extensive data stored in their warehouses allows for a more informed approach to what treatment methods have better results based on certain stages of cancer or the approach that would need to be used to effectively help cure a patient of cancer. Research into cures of autism, use of stem cells, gene splicing, amongst many other advancements, allow for not just new advancements in treatment efforts but reducing the chance for genetic conditions inherited to offspring, alternate methods of less invasive approaches to curing diseases, and reversing the effects of human diseases. The Human Genome Project that was launched in 1990 gives us the ability to understand out DNA better by studying the human genome to help detect mutations of our DNA through genetic inheritance, environmental factors, and lifestyle factors (NHGRI,
KDDM has the ability to take large amounts of data then extract, clean, and pre-process the data applied to machine learning applications to help develop a hypothesis of future events as well as identify links with complete or incomplete data (Nelson & Staggers, 2014). Due to the fact that KDDM is able to use very large amounts of data for analysis, comprehensive data can be evaluated and detect very subtle patterns within the data with low costs if utilizing electronic health records (EHRs) to obtain the data. With the health care market steadily converting to EHRs the amount of data and availability of data is vast and limitless. EHRs have virtually changed how we collect, maintain, sustain, manage, and use data collected. KDDM allows for the development of medical knowledge which in turn helps improvement in support of clinical decision-making, identifying links in data to help prevent future events, help support validity in studies, detect patterns in data, and support quality improvement efforts (Nelson & Staggers, …show more content…
The overall outcome in the healthcare field is to provide accurate, effective, precise care to a patient to improve their health not to have the patient go into further decline in health. When a patient is diagnosed with cancer there are now more avenues to consider for treatment than 50 years ago, let along 10 years ago. This is because research has identified threats, trends, markers, genetics, and knowledge to providers to learn better ways to treat illnesses. Adding into the mix EHRs that have extensive data stored in their warehouses allows for a more informed approach to what treatment methods have better results based on certain stages of cancer or the approach that would need to be used to effectively help cure a patient of cancer. Research into cures of autism, use of stem cells, gene splicing, amongst many other advancements, allow for not just new advancements in treatment efforts but reducing the chance for genetic conditions inherited to offspring, alternate methods of less invasive approaches to curing diseases, and reversing the effects of human diseases. The Human Genome Project that was launched in 1990 gives us the ability to understand out DNA better by studying the human genome to help detect mutations of our DNA through genetic inheritance, environmental factors, and lifestyle factors (NHGRI,