Why Analytics Should Be Used In The Healthcare Industry

1933 words (8 pages) Essay in Information Technology

18/05/20 Information Technology Reference this

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Do you know about data analytics? These data analytics allow for an industry to obtain any insights from patters and connections that are found so they can make better decisions. Businesses are able to achieve multiple advantages by using these statistics. Analytics help find meaning in real-time or historical data so there can be prediction made about the future to improve the probability of success. Due to the healthcare industry using data analytics they will be able to benefit their business by improving patient care quality, improve operational efficiency, and prevent diseases. 

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Every business is curious on how they can make their operations better whether it’s for money savings or for the care of patients. Using analytics will allow for the improvement of operational efficiencies. The ERP systems allow for them to collect all the information that they want to include in their statistics. Analytics allow for businesses to find the gaps that are causing them to work dysfunctional. An ERP system allows for the firms to achieve their goal of cutting costs. In healthcare, there are a few challenges such as being unable to handle the information that is gathered daily, the increased cost of supplies, the failure of patient census, the medical payments, and the lack of specialized staff. ERP systems will also be able to improve the facilities functionality, simplify their business processes, assures the quality of care services and helps their finance such as management accounting and controlling. Healthcare reform will depend on cost saving that are derived from the data collections about their patients. A common goal of analytics is to perform cost containment and efficient delivery of high-quality healthcare. Analytics allow for businesses to figure out which doctors are more costly versus the others. They also offer recommendations to reduce these costs such as which services, insurances, etc. are costing them more. These analytics are supposed to encourage healthy behaviors and decrease healthcare costs. Big data analysis allows for business to have financial risk management. There are challenges with determining patient outcomes and to decide the payment, lower reimbursement, unpaid patient bills, and underused billing. These predictive analytics will be able to help manage cash flow and predict which payments may remain unpaid in the future. The improvement of operational efficiency from analytics will also include the help of preventing fraud and abuse. There are fraudulent activities that can occur in healthcare such as erroneous billings, wasteful diagnostic tests, false claims, and etc. Analytics identify patterns that lead to fraud and abide in healthcare insurance. 

Predictive analytics combine patient information to aid prognostic outcome results. Analysts are able to gather all of the information regarding patients and detect any patterns. Then they are able to convert the information in actionable insights and work towards achieving better health outcomes. With this information and the results of any patterns, they are to check for any disease outbreaks and provide treatment and respond to emergencies. Also with these analytics, there is the benefit of figuring out preventive techniques, medicines, and vaccines for diseases. A few years back it was hard to prevent diseases because of the lack of timely data, but with analytics the healthcare industry has able to overcome the challenges and epidemics can be monitored now. There is also the benefit of reducing mortality rates caused by the disease by checking where prompt care should be provided. Another advantage of predictive analytics allow for those in healthcare to recognize those patients that are likely to develop disease or possess certain risks to their health. Healthcare organization will have the ability to identify patients with high risk of developing serious diseases and provide them with better outcomes so they won’t have to face long-term health problems. For example, analysts are able to view the results and determine when someone may become diabetic down the road. They can develop specific wellness programs that can serve the interests of patients for their better health. Analytics can predict whether a patient will be likely to be readmitted due to a relapse or adverse effect and they can make suggestions on how to prevent it. Healthcare will also have the ability to prevent substance abuse such as with opioids. Analysts can study the patterns and identify all of the risk factors that predict whether someone is at risk for abusing. The uses of big data analytics also allow for the managers of healthcare to review the results among patients in different demographic groups and help identify what factors may be discouraging patient’s from receiving the treatment. Everyone wants to find a cure and to prevent the spread of diseases, however it can be like a puzzle when trying to do so. You have to study the patterns and hidden secrets. This can be extremely hard for any human to study, they may make mistakes, and it make take a long time. Analytics are able to collect information in a timely manner and give out different recommendations based of the patterns and secrets that they’ve found. Everyone would like to see a cure to cancer or the ability to foresee any diseases that may come to him or her later on in life. So why not use a software that has been able to prevent outbreaks and try to prevent your patients from having diseases down the road or find a cure to something that causes millions around the world to suffer. 

Patient care is the most important aspect to every doctor. We all know that doctors are doing their job, care about their patients, and want to see them healed. Therefore with analytics, doctors will be able to evaluate their performance from the analysis that shows them the gaps. Everyone’s human and sometimes we tend to not see our faults until they have been pointed out. Some doctors are unaware that they aren’t performing their best or they don’t believe that they are missing in performance until they are presented with statistics that show them the areas for improvement. Therefore, the evidence of statistics and analytics allows for the ability to show proof through their own data that they are lacking in bringing the ultimate care. Since those in healthcare are working for the same goal of achieving the ultimate patient care, these analytics allow for them to capitalize on that goal. With the data that’s being collected, there’s the possibility for predictions on what individual patients would benefit. Analytics are used to explore the different opportunities for improvement and suggest innovative ways to address old challenges that doctors have. Since doctors put their patients first, then this information should be important if they want to improve their patient care quality. So why not use the technology that will allow for a deeper insight into their performance and to make recommendations on how to improve their performance for their patient’s sake. 

Some doctors feel like data analytics aren’t necessary. They believe that they don’t need fancy statistics to improve their performance. I’ve faced doctors who believe that they are perfect or that they can learn from the mistakes that they make. Front line managers feel like they can avoid mistakes and learn from the challenges so that they are able to further their professional development and improve services. Also doctors and healthcare administrators feel that the government is trying to tell them how to do their jobs. They feel this way since as a doctor, the government will decide whether or not they meet the requirements and have to report. If they are required to report then they have to make sure they follow the rules that the government put in place. 

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I understand how the doctors may feel like the government is trying to tell them how to do their jobs, and they tend to take their anger out on analysts. Since I work at a healthcare data analytics company, I can see the middle ground. The healthcare government is constantly changing its requirements and what is expected for performances. Therefore, analysts and the analytics are present to help keep these doctors up to speed on the changes that the government makes. If the doctor must report and they don’t meet the requirements for reporting, then these doctors may receive a 9% penalty based off the Medicare Part B claims. Analysts want to help these doctors from receiving a penalty and instead have them negate the penalty or potentially receive a payment adjustment depending on their performance. Also, analysts want to show that data analytics offers the ability to improve their patient care quality by offering different recommendations and showing where they have gaps in their performance. We know that doctor’s care about their patients, but sometimes it’s hard to keep up with the changes in the industry. You can be doing your absolute hardest, but sometimes everyone needs a little help so they can be on top of their performance. Learning from the past mistakes you’ve made isn’t enough; how many mistakes are you willing to make in a patient’s life before realizing that some things are out of your hand? In any area of healthcare, such as cancer specialists, surgeons, pediatricians, and so on, I think that there could be an agreement that mistakes are something that can be made often. Everyone makes mistakes, but if you have the ability to use software that offers an amazing opportunity to figure out the diagnosis sooner for your patients then why wouldn’t you want to use the software? If you can prevent a patient from undergoing unnecessary expenses, pain, and time, then why would you want to continue the same behavior that hasn’t been offering the best results for your patient care? 

In conclusion, the healthcare industry is constantly changing. Instead of learning from mistakes or being lost in the changes, there is the ability for healthcare officials to use data analytics. With data analytics, there are many advantages that become possible for those in healthcare. A few examples of advantages include the ability to improve patient care quality, improve operational efficiency, and the ability to prevent diseases. Don’t pass up the opportunity to use analytics to study the patterns that will save your patients from long-term diseases, the ability to cut down on costs and better your operations, and the ability to show others where there’s a gap for their performance to improve for their patient’s sake and to avoid penalties. 

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