The healthcare analytics market is expected to reach USD 50.5 Billion by 2024. This growth is not merely the outcome of big data and technological developments that have disrupted practically every industry. For healthcare, the growth in analytics corresponds to a far more deep-seated transformation in the approach to patient well-being.

Care providers around the world are debating fundamental questions such as:

Who should have control over the treatment approach? Patient or doctor?

How much patient data can be made available, and to whom?

Is the patient, a 'patient' or a 'customer'? What is the difference?

How can hospitals reduce the cost to customers, yet be profitable?

Hence, analytics in healthcare is not merely a tool. It is an inseparable part of the healthcare evolution that is underpinned by customer experience, treatment efficacy, technology enablement and economic cost.

Experience of Customers

Strangely, a ‘patient’ paying hundreds of dollars to settle medical bills could never wield the same power as a ‘customer’ buying a pack of chocolates for a few dollars. However, that is changing. A study found that more than 90 percent of both patients and providers feel patient satisfaction is important. Further, 88 percent of patients confirmed that they would switch providers, if unsatisfied.

Advanced analytics is enabling providers to address key aspects of patient satisfaction such as transparency, personalized care and giving more control to the patients over their treatment. For example, a Minnesota-based academic medical center uses patient data to predict the risk of kidney stone recurrence. Further, patients are empowered to decide the treatment approach and predictive insights can be shared with them by doctors.

Efficacy of Treatment

According to McKinsey, healthcare expenses represent 17.6 percent of the U.S. GDP, which is almost USD 600 Billion more than what is expected for a country of its size and wealth. This has caused a shift from compensating physicians on the volume of treatment to outcomes. Analytics is helping drive the efficacy of patient treatment and enabling outcomes such as reduced patient re-admissions based on prediction of risk factors. For example, a large hospital group could reduce 6000 occurrences of patient re-admission by generating individualized predictions of patients’ re-admission risks during diagnosis. This enabled the hospital staff to proactively deliver additional medical care. Similarly, a Boston-based behavioral health company uses Machine Learning (ML) to generate insights from patient data to deliver individualized care.

Enablement of Technology

Artificial Intelligence (AI) and ML are game-changers for the healthcare industry. According to a Stanford health trends report, the size of AI in healthcare is expected to reach USD 6.6 Billion by 2021, and has the potential to reduce healthcare costs by USD 150 Billion by 2026. Advanced analytics is a key enabler of these technologies. For example, a California-based healthcare service provider analyzes patient data from a home monitoring system using its AI-based command center. Predictive analytics helps flag risks and enables actions such as proactive follow-ups. Data skills are also fast becoming a requisite skill for healthcare workers. A PwC study found that 55 percent of payer executives consider it important for new hires to be trained in informatics and data analytics.

Economic Cost

Analytics translates to revenue generation and cost savings for healthcare providers. For example, Operating Rooms (OR) account for a significant cost for hospitals. But ORs also have a high potential to generate revenue. Factors such as cancellations, no-shows by patients and transition time between surgeries result in inefficient use of ORs. Analytics can pinpoint these efficiencies and enable remediation. A Colorado-based hospital leveraged analytics to improve OR utilization by 4 percent, translating to USD 400,000 per room annually.

The healthcare evolution is often described in terms of technological innovations. However, the essential core of this transformation is healthcare providers recognizing the ‘patient’ as a ‘customer.’ Today 1 in every 25 American adults has access to their personal genetic data. While this data helps healthcare providers in researching and improving services, it empowers customers to take decisions about their own health. Thus, customers become the ultimate beneficiaries of their own data as a result of analytics.

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