As per the Market Data Forecast report, the global healthcare prescriptive analytics market is likely to grow at a CAGR of 17.4% from 2022-2027. Organizations use prescriptive analytics to predict outcomes and to identify the logical course of action. Prescriptive Analytics of user-generated data in the healthcare domain indicates what is likely to occur and suggests the best actions to avoid and mitigate risks. To know more about how healthcare is optimizing its operations with prescriptive analytics

1. How to Successfully Use Prescriptive Analytics to Optimize Healthcare Delivery?
A health insurance company analyses its data and discovers that a significant chunk of
diabetic patients also suffers from retinopathy. Armed with this information, the providers
used predictive analytics to determine the likely number of ophthalmology claims they
might receive next year. Through prescriptive analytics, the company defines the scenarios
where reimbursement costs for ophthalmology may fluctuate.
Businesses use predictive analytics to make informed decisions to drive cost-effective
procedures and serve their customers better. In healthcare organizations, prescriptive
analytics can play a vital role. Several data sources include patient-centric information,
treatment plans, patient history, appointments, surgeries, radiological test reports, etc.
When fed into the prescriptive analytics model, this data ensures the proper staffing of
healthcare organizations. Utilizing this data to identify patterns can help save costs from
medical supplies to transport fees to the food budget.
Prescriptive Analytics
Prescriptive analytics is a set of mathematical techniques that help determine complex
targets, requirements, and limitations for improving business outcomes. This approach
determines various alternatives and guides based on descriptive and predictive analytics
results. It is one of the hype cycle’s emerging technologies announced by a Gartner in 2013
and has received increasingly growing attention in business areas.
The prescriptive analysis is the data analysis technique that provides predictions and
context-customized information.
It enables healthcare decision-makers to optimize business outcomes by recommending the
best action for patients or providers. It allows the comparison of multiple “What ifs” to
assess the impact of choosing one step over another.
For example, a health insurer derives a pattern in its claims data for the past year to show a
significant portion of its diabetic patient population suffers from retinopathy. The insurers

2. use predictive analytics to estimate the probability of an increase in ophthalmology claims
during the next plan year. Prescriptive analytics identifies the cost impact of average
ophthalmology reimbursement rate fluctuations and recommends suitable action.
Benefits of Prescriptive Analytics
It is the most innovative and effective tool to scaffold any organization’s business
intelligence. The significant benefits are –
 Maps the path to success – Prescriptive models pull together the data and
operations to produce the roadmap of an efficient workflow for your organization. AI
takes the reins of business intelligence to apply simulated actions to a scenario to
make the steps necessary to avoid failure or achieve success.
 Informed real-time and long-term business operations – Decision makers view real-
time and forecasted data simultaneously to make decisions supporting sustained
growth and success. It streamlines decision-making by offering specific
recommendations.
 Makes time-consuming processes efficient – The instant turnaround of data analysis
and outcome prediction helps reduce team efforts wasted in finding challenges and
their resolution. AI curates and process data in less time as compared to manual
processing.
 Reduces Human errors - Through more advanced algorithms and machine learning
processes, prescriptive analytics provides more comprehensive and accurate data
aggregation and analysis than descriptive and predictive analytics.
Descriptive and Predictive Analytics (Hyperlink - https://47billion.com/blog/empowering-
healthcare-with-predictive-analytics/ )

3. The outcomes of implementing descriptive and predictive analysis are suitable when
organizations simulate them in-house to define the best course of action. Descriptive and
predictive analytics will not help in the given scenarios –
 Streamlining future healthcare marketing efforts
 Resolving inconsistent gaps in workflows
 Recommendations for more optimal results
And that’s where prescriptive analytics come into the picture.
How prescriptive analytics fills the gap?
Once you predict a set of outcomes, prescriptive analytics helps control those outcomes and
channel them to your advantage. It also lets you understand how and which variables can
help achieve the desired results.
These insights fortify the companies to evolve with environmental changes while making
real-time decisions.
The major disciplines of prescriptive analytics are operation research, machine learning,
natural language processing, and applied statistics. The healthcare industry is shifting to
deliver value-based services to its patients, and prescriptive analytics is helping it fill the gap
between information and decision-making.
Reduced Operating Cost
Predictive analytics tools give actionable insights on budgeting, accurate business planning,
staffing levels, capacity and equipment requirement, inventory management, etc. It not only
reduces operational costs but significantly reduces patient billing.
Improved Care
Clinical decision-making based on predictions can sometimes backfire. Prescriptive analytics
with machine learning can provide data-based insights to make clinical decisions critical to
the health and treatment of patients. Data-driven advanced genome studies play a
significant role in developing precision therapies.
Data Security
Increased usage of wearables and health-tracking devices generates a significant amount of
user data. This data helps in clinical diagnostic purposes. The same applies to valuable
clinical and diagnostic patient records that are highly prone to data breaches. Prescriptive
analytics and Machine learning algorithms help identify user activity patterns to avoid
further cyber-attacks.

4. Why Prescriptive analytics in healthcare is the best option?
Healthcare meets all the requirements -
 Decision spaces involve patient information, treatment plans, resources, physical
space, payment structure, and trade-offs (cost vs. quality).
 Objectives are defined, such as quality of care, access to care, probability cost, and
customer satisfaction.
 It can maximize objectives and make their interplay with one another, for example,
personnel hours across the system, treatment plans, patient affliction curves,
minimum quality objectives, regularity, and budgets.
 The complexity and the corresponding impact of deploying optimization are very
high.
Applications of prescriptive analytics in Healthcare
The use cases range from strategic to operational planning. Here are a few examples –
 Long-term business models/risk evaluation (e.g., physician employment, etc.)
 Network optimization of facilities and service lines – market share, quality, cost
 Optimization of facilities and service lines
 Population management/outreach program optimization, downstream, resource
requirements, and financial performance
 Hospital constraint modeling to reduce cost and increase throughput understanding
of cross-constraint impacts
 Optimization of the physician lineup, hospital lineup, hospital resources (capacity,
insources/out-source), and case mix across service lines to meet demand and
financial targets

5.  Data-driven financial planning (such as based on demand source, e.g., physicians, ED)
 Clinical process design and optimization
 Resource allocation for revenue cycle management
47Billion has been working with several healthcare organizations for various data analytics
and visualization solutions to drive unique and valuable insights that improve planning
significantly.
Prescriptive analytics – Paving the future of Healthcare
The final phase of healthcare data analytics involves prescriptive insights. Prescriptive
analytics is beyond the ability to predict an upcoming event and provide the capability to
make a move. It indicates what is likely to occur and suggests the best actions to avoid or
mitigate any adverse circumstance. It has a seamless and wholly integrated data analytic
infrastructure that can engage in the ultimate application of data in a large-scale or
meaningful way. The future of prescriptive analytics is nearly unlimited in its scope and
depth. So many healthcare providers are still trying to claw their way out of locked rooms of
unused EHR data. An industry-wide push towards viewing Healthcare big data as the answer
to so many critical questions is accelerating the development of an infrastructure capable of
becoming the foundation for prescriptive analytics and significant advances in the quality,
timeliness, and effectiveness of patient care.
Write to us at hello@47billion for more information on leveraging Prescriptive Analytics for
your healthcare business.