Ethical Issues with Big Data and Artificial Intelligence in the Healthcare Industry

 

 Abstract

            Health industry deals with medical issues and is essential in giving estimates of gross domestic products. Its various goals are achievement of better health of the people, provision of care in equal manner to all citizens and to allow affordability of the healthcare services among all the people.  It also aims at holding campaigns to impact people with knowledge concerning the illnesses that impact serious complications towards their life. Big data has been impacting positively in the health industry; however there is the need to improve on the risks associated with it.

Introduction

            This is an industry that has been dealing with heath issues and it is very important in offering employment to many people. It also determines investment, export status, capital as well as employment of the nation. It is essential in giving estimates of gross domestic products. The various goals of this industry include; achieving better health of the people, provision of care in equal manner to all citizens and to allow affordability of the healthcare services among all the people.  It also aims at holding campaigns to impact people with knowledge concerning the illnesses that impact serious complications towards their life. There is also the aim of educating the people concerning the available services in the industry that can be of beneficial to them. It also has an objective of explaining to people on how the healthcare facilities are in the position of offering quality care and offer the nice experience to the clients at the best cost. Big data has been impacting positively in the health industry; however there is the need to improve on the risks associated with it.

Use of Analytical Data in the Health Industry

            Big data is being used by the doctors to carry t immediate assessment and come out with diagnoses without much waste of time. This is usually through the use of electronic health records. It is as well used by the clients in tracking the processing their symptoms using the data app in their phones to notify the clinicians about their conditions (Madsen, 2014). The big data is also being used as a method of engaging the patient in the treatment process. There is the ability to track the habit of drug compliance by the patient, level of activities done by the patient, their diet and their level of stress. The money incurred during the care of the client as well as the balance in their health accounts are also easily tracked by the use of wireless data app. The big data is being used to measure the heart rates, clinical tests, expenses, the profiles of DNAs and pressure of the blood. The big data has been in use for treating and measuring the rates of recovery of the patient with an aim of looking for the effective and top most drugs in the treatment of cancer disease.

Types of Analytical Data

Descriptive Analytics 

            This is the biggest data form in the health care industry and it focuses on investigating on the unintended operations or unexpected results. This data is much securing the wellbeing of many clients (Wang, Kung, Wang & Cegielski, 2018). One of the examples is offering the health facility improved knowledge on the trending assessments.

Predictive Analytics

            This type of data has been in use to offer predictions about the future outcome and avoidance of events that can facilitate to high costs in the healthcare services. For example, it is being used to identify the patients who are at risk by having any chronic illness thereby enabling the caregivers to establish effective ways of providing care to such patients (Wang, Kung, Wang & Cegielski, 2018).

Prescriptive Analytics 

            This type of analytical data helps the healthcare providers to be in the position of estimating the number of the patients. It enables to the care providers to give attention on obese clients and measure morbidity rate (Wang, Kung, Wang & Cegielski, 2018).  An example is; the number of diabetic cases to know if they call for immediate attention.

Comparative Analytics

            This involves comparing the health providence practices with other health facilities. This enables the care providers to gain knowledge on the current trending treatment practices (Wang, Kung, Wang & Cegielski, 2018). They can be able to make comparison of their way of work using aggregate network and a given number of patients. The information acquired after comparison can be put into practice by the caregivers with an aim of doing better in their performance.

Business Applications of the Big Data

Big data has been in use for estimating or measuring the expenses incurred during the medical care providence. It enables for transparency and accountability of money. The health industry is aiming to cut the amount of money that is being incurred (Madsen, 2014). This practice will enable to prioritize quality care of the patient rather the high amount of money being paid by the patients.

Ethical Issues in Big Data

There are various ethical issues regarding the handling of big data. To begin with, the information obtained from the usage of big data should remain private. This also includes the identity of the patient (Mittelstadt & Floridi, 2016).  That data that the patient has shared with the caregivers in their consent should only remain known to the two parties; caregiver and the patient. Secondly, the information should be handled with much confidentiality. This is because other people might share the data inappropriately to others. Another ethical issue is that there should be openness to the customer who is the owner of the information. In case the data is being sold, they are supposed to know clearly how it is happening so that they can be able to control how the third party is using the information. Lastly, there should not be any kind of discrimination, for example in terms of race or color.

Negative Impacts of Disclosing the Big Data Information

            There are cases of personal data being in use by robots and marketers. They take the actual data and maximize it to use for their own benefits (Bang, Lyndon & Ana, 2015). The continuity of use of personal data by companies has not been appealing. The companies have been having the tendency of disclosing the data of people and this has been leading to increased need for confidentiality concerning personal data. In case the companies go to an extent of changing the individual’s information, exaggerating, confusing or misleading the customers, they are at risk of being sued for ambiguous and manipulative tactics.

Resolution of Ethical Issues

            he issue of the openness during selling of the personal information has already been put into practice. The fact that people have not been confident with disclosure of the information has lead to implementation of laws. These laws allow any individual who feel that their information has been disclosed in a manner that will harm them to sue them (Bang, Lyndon & Ana, 2015). This has significantly been impacting positively in matters concerning individual information especially by the companies. However, the issue of biasness has still been trending where people are being discriminated under race or sex. There is therefore the need for the issue to undergo resolution.

Risks

            There are greater risks in using data analytics in terms of privacy. There is danger of exposing the individual’s medical information that has been given with consent when using analytical data (Groves, Kayyali, Knott, & Kuiken, 2016). This is because there is usually the need to take much of the patient’s personal information hence there is probability that in one time there can be disclosure of the information. The caregivers have therefore been having fears of sued by individuals since it can lead them to court of law.

Conclusion

            Health industry usually determines investment, export status, capital as well as employment of the nation. It is also essential in giving estimates of gross domestic products. The various goal of this industry include; achieving better health of the people, provision of care in an equal manner to all citizens and to allow affordability of the healthcare services among all the people. Big data has been in use for making medical diagnoses and engaging the patient in the treatment process. There are various types of analytical data which include comparative, prescriptive, predictive and descriptive analytics. There are also a number of ethical issues in handling the big data information. These include; ensuring privacy and confidentiality of the information given by the patient, openness when the information of an individual is to be sold and lastly but not the least, there should not be any kind of biasness in the processing of data base information. Usage of big data can lead to exposure of personal information to other people. This usually happens with robots and marketers. This information has the probability of being changed by the third party hence people might end up getting the wrong information concerning an individual. Privacy as an ethical issue has been resolved through implementation of laws. There is however the need for resolution of biasness as an ethical issue. There are dangers associated with exposure of individual’s information by the medical caregivers by use of analytical data. . Big data has been impacting positively in the health industry; however there is the need to improve on the risks associated with it.

 

 

 

 

 

 

 

 

Reference

Wang, Y., Kung, L., Wang, W. Y. C., & Cegielski, C. G. (2018). An integrated big data   analytics-enabled transformation model: Application to health care. Information &     Management, 55(1), 64-79.

Madsen, L. B. (2014). Data-driven healthcare: How analytics and BI are transforming the           industry. Hoboken, New Jersey: John Wiley and Sons, Inc.

Mittelstadt, B. D., & In Floridi, L. (2016). The ethics of biomedical big data.

Bang Nguyen, Lyndon Simkin, Ana Isabel Canhoto. (2015). The Dark Side of CRM: Customers,             Relationships and Management, Routledge, 2015

Groves, P., Kayyali, B., Knott, D., & Kuiken, S. V. (2016). The'big data'revolution in healthcare:             Accelerating value and innovation.