Role of Analytics in disrupting the Healthcare Industry

Gunjan Ahuja Great Lakes of Management, Gurgaon

ABSTRACT Data is the new oil of the contemporary world and analytics is the new engine of the healthcare industry! Analytics solutions are the top priority for health CIOs (chief information officers), particularly as health information systems attempt to use big data to prevent diseases, offer better care, and improve all spectrum sectors. Healthcare analytics is the process of gathering and evaluating data in the healthcare industry to obtain knowledge and support decision making. From critical fields such as clinical data, pharmaceuticals, medical costs, and patient behaviour, healthcare analytics can be employed on micro and macro levels to enhance patient care effectively, streamline operations, and minimize total costs. Compared to other industries, healthcare data is the most complex. From monitoring real-time critical signs to EHR (electronic health records), data originates from different sources and have to abide by federal regulations. It is a delicate and challenging process that needs a level of connectivity and security that only an integrated analytics solution can offer. “Disruption” is one such word that any industry fears and loves the most. The key driver in the field of healthcare would be information and data analysis. And as the events went downhill in the year 2020, it only has raised the alarms for much faster change. ANALYTICS FOR MEDICAL PROVIDERS As healthcare providers change from service charges to a value-based care framework, the necessity to enhance care and efficiency makes analytics a critical function of daily operations. With an integrated analytics solution, providers: ·Minimize patient wait times by evaluating and leveraging staffing and scheduling procedures. ·Offer personalized treatment to patients and boost the general patient experience. ·Enhance performance by providing quality data-based care. ·Enhance care quality and patient satisfaction by streamlining timeconsuming procedures associated with processing insurance, making appointments, and offering referrals.

From the perspective of the health care sector, fraud detection would be one of the most noticeable improvements brought on by the emergence of data analytics. Hospital insurance fraud and pharmacy fraud were always challenging to notice, let alone verify. Data analytics quickly detects potential issues and notable medical record trends to deter fraud and show that it occurred where a crime occurred. Data analytics has had a widespread effect on the health sector, which is just beginning to happen. If technology advances and care providers get

more confident with it, people see the healthcare situation improve. Doctor visits are now supplemented with video conferences and automatic notifications, the focus on health treatment has begun to increase, and eventually, the life quality would grow. It is a bumpy road incorporating data analytics into healthcare, but the result is worth it.

HIGH-RISK PATIENT CARE Healthcare can be complicated and costly for patients looking for emergency services. The price increase is not a guarantee that the patients will receive better results; hospitals need a substantial change in their operations. With digitized clinical records, it is easy to identify patient histories and patterns. Predictive analytics separates individuals with a high risk of experiencing chronic health issues, providing doctors with an opportunity to offer corrective plans that minimize hospital visits. Providing personalized care solutions and monitoring these patients is unattainable without adequate data. Therefore, the utilization of healthcare analytics is of great significance to safeguarding high-risk patients. ROLE OF ANALYTICS IN DISRUPTING HEALTHCARE INDUSTRY 4

PATIENT SATISFACTION Patient engagement and satisfaction are a priority for many medical facilities. With health tracking gadgets and wearables, doctors actively provide preventive care to patients, and patients also gain insights into their health role. Such knowledge strengthens patients' and doctors' relationship, decreases hospitalization rates, and prevent major health issues that could potentially affect the patient.

ANALYTICS FOR MEDICAL PAYERS The ever-changing regulations affect health insurance providers, and since it is the highest cost for families, health insurance depends on performance quality. Through gathering and translating data using an analytics solution, payers:

Evaluate prescription fulfilment and hospital claims data to develop intended campaigns for particular health problems. Quickly adapt to any law modifications

through integrating an analytic solution that accommodates the current security model. Use pricing information instead of quality criteria to recognize less costly but highest value providers for specific procedures.

ANALYTICS FOR POPULATION HEALTH PHM (population health management) is fostering a change in healthcare, with the industry concentrating on prevention and prediction in health instead of treatment and response. Healthcare facilities can leverage predictive analytics to identify patients likely to get chronic diseases in the early level of disease development, offering them a golden opportunity to prevent long-term health complications that lead to repeat hospitalization and expensive care. By gathering and assessing large data sets, well-established analytics.

ROLE OF ANALYTICS IN DISRUPTING HEALTHCARE INDUSTRY 5

Determine high-risk patients to enhance funding and staff allocation. Estimate patient health results to determine the effectiveness of specific treatments and programs. Eliminate care gaps by evaluating ratios between a patient and a provider based on particular conditions. Carefully measure and track patient conditions and intake to intervene and predict potential epidemics.

Staffing: Having a difference in the number of staffers required on a patient adds cost to the management and the patient both. A paper by Intel describes how four hospitals in Paris are utilizing “time series analysis” . The team developed a web-based solution that predicts and helps them in resource allocation for best patient care practices. (Kyle Ambert, 2016) Enhancing patient engagement: Patients are these days very much concerned about their health and smart wearables help them keep a track of their heart rate and blood oxygen levels. Monitoring their own health and taking timely precautions is a way of helping people save lives as well as giving them back the cost of wearing a smartwatch. Predictive Analytics: The goal here is to help doctors track and make decisions in seconds as to who might be at the risk of diabetes or obesity. Predictive analytics is a major role player when it comes to people with complex and hereditary medical conditions. (Wullianular Raghupathi, 2014)

ADVANTAGES OF ANALYTICS IN HEALTHCARE

Augmenting diagnostics and decisionmaking: Big data can come in any form digital or handwritten. Clinical Decision Support (CDS) services are one such offering, which is used in various healthcare providers to evaluate medical data in real-time, thereby influencing treatment, diagnosis and prescriptive decisions. We current observe that the radiologist department isn’t even well connected with cardiology from same hospital, this will be helpful for a patient suffering from multiple ailments. Managing Supply Chain: Exploiting analytics in supply chain management becomes an important aspect because either under storage or over, both are will become a boon for patient care and long-term finances. Optimized storage and housing can help a hospital save up to $10million per year. (LaPointe, 2017) Integrating Big Data with Medical Imaging: Medical Imaging is an important aspect in patient diagnosis and with the usage of algorithmic pattern recognitions and converting single pixel deviation in MRIs can add larger benefits to the healthcare system. Medical imaging diagnosis is a hefty business and with the usage of artificial intelligence it could save both time and money. Fraud Prevention: Medical Insurance scams and prescription frauds have always been difficult to track let alone to be proven. New data analytics and information technology usage by healthcare providers can become a significant player to recognize patterns, red flag them and prove that these patterns have happened when a crime occurs.

Challenges in Healthcare Analytics

Electronic Health Records (EHR): The problem currently is that there are thousands of medical conventions and open access to it is restricted for researchers. The data comes in a variety of forms and building a granular data collection out of it becomes more of a cost than the value extracted out of it. (Cohen, 2019)

Real-time alerting: Not everybody is wearing a smartwatch and the lack of infrastructure for real-time collection of data, analysing and then monitoring it becomes a hindrance to the overall idea of real-time healthcare provision.

Telemedicine: Clinicians can use teleconferencing tools in providing healthcare benefits to the patients but the lack of precision and availability of tools might just cause somebody their life. (Steve Grifiths, 2019)

CONCLUSION

Analytics will play a disruptive role in changing the dynamics of the healthcare industry but how it shapes out will depend on its fair usage. Although the current data privacy and security laws are not turning out to be sufficient to protect the civilians, with the right planning and consideration and keeping an eye on social responsibility as a whole it can change the gameplay in a positive direction.