CASE STUDY

How Data Analytics in Healthcare Helped Client Realize 10% Higher Profit Margin?

Nov 29, 2022

Game-Changing Solutions for the Healthcare Industry 

If you’ve ever worked in the healthcare industry, then you must know the high level of protection implemented to safeguard patient health history from loss, cyberattacks, or fraud to ensure against privacy violations. Due to these hazards, many healthcare organizations have taken a conservative approach when it comes to data collection and usage. They also attempt to avoid cases where privacy issues might occur and hence, they lose out on various value-creation opportunities. 

Considering the recent technological advancement across the globe there has been emergence of a more customized approach when it comes to the healthcare and medical sector. A strategy dubbed tailored medicine or personalized treatment has been adopted by various providers, it entails developing more reliable and beneficial drugs for each individual based on their genetic make-up.  

Data analytics in healthcare are implemented by using huge amounts of clinical and organizational data, and eventually converts it into actionable insights. These insights enable the organizations to take informed decisions faster, solve complex problems, and drive growth. With the increasing cost of operations, patient needs, and more, the organization in the industry needs to look toward data analytics to solve their woes and develop innovative ways to improve profits and quality. 

Organizations need to spot upcoming market trends and make smart decisions to benefit from those trends. Through data analytics in the healthcare industry, organizations are able to extract valuable information that helps them make the right decisions. With the investment in real-world evidence (RWE) analytics increasing, the prominent players in the healthcare industry have observed differential success rates.  

Real-world evidence helps the organizations realize substantial value across the product and drug development lifecycle. On top of this, a majority of healthcare organizations have started to focus more on a systematic approach rather than an opportunistic approach due to the enhancement of data analytics in the healthcare industry.  Such healthcare players are implementing such analytics solutions to cross-over from only narrow search-based approaches to develop sustained value through the product lifecycle and development processes. 

This is where we come in, our data analytics solutions for the healthcare industry enable our clients to extract and collate essential data from patient-doctor interactions. This data can be further processed to develop bespoke solutions for the patients, enabling the organizations to adapt to changing regulations in real-time while also enhancing pharmacovigilance at the same time. 

Data Analytics Challenges Faced by the Healthcare Client 

The client, based out of the US, with majority of its operations spread across the globe, wanted to leverage our advanced data and analytics solutions to enhance visibility into the risk profile of patients in a bid to gauge high-risk individuals that might lead to potential losses. The client was developing huge amounts of data but were unable to do anything with it, sorting through the huge amount of data generated post patient interactions becomes a complex task. When focusing on patient management, the client was having problems such as:  

  • Security breached during data access   
  • High investments in setting up contact centers  
  • High investment in targeted marketing strategies   
  • Inability to perform patient screening and disease profiling   

While focusing on the other end of the spectrum, the client was also facing trouble delivering personalized content across digital platforms. The client wanted to go one-step ahead than just deliver marketing initiatives to the patients and develop a clinical workflow that enhanced patient engagement, coordination, health assessments, health risk assessments, therapy schedules, and patient goals. Implementing a personalized health plan for each patient is a complex and resource-intensive task, so the client was to understand the feasibility of developing a similar plan in their patient journey. 

Gain limited-time complimentary access to our healthcare data analytics platform and analyze the true potential of data to aid decision-making, drive learning, and optimize patient care. 

Through superior AI and ML-driven strategies, the client wanted to generate insights and eventually empower clinician decisions. Another issue was frequent inventory runouts and supply chain data silos. The client had operations in an expanded pool and an inability to scale according to patients’ needs negatively impacted their patient journey and experience. The traditional supply chain was becoming increasingly redundant for the client as the traditional process included several inconvenient processes that resulted in operational inefficiencies. 

Revolutionary Data Analytics Solutions for the Healthcare Industry 

With the challenges identified, our research experts were ready to start the process of tackling each and all challenges and help the client realize superior results. Our experts developed healthcare analytics solutions to help the client extract and process data including, health history and genetically carried-on diseases. Our tool helped the client use the data derived from their patients and develop tailor-made processes accordingly. Our tool accessed data such as lifestyle, consumption habits, genetics, and more to identify patterns on likelihood of disease risk among the patients.  

Through this endeavor, our client was able to plan the patient’s health insurance policy by deriving insights into each patient’s progression and disease trajectories. Our solutions have helped a plethora of clients enhance their efficiency, satisfaction, and clinical outcomes through a sophisticated use of analytics. Another mountainous task that the team undertook was to improve diagnostics and predictive analytics by capturing data from electronic health records (EHRs) to effectively collect data from wearable devices and sensors of the patients. 

To tackle the scalability challenge of the client, we implemented a predictive analytics tool, allowing our client to access customer health history to ensure the availability of supplies based on their medical history. Our AI-driven advanced analytics solutions were able to define new algorithms and integrate several analytics techniques to effectively predict supply forecasts. This ultimately led to a reduction in stock-outs and expired inventory.   

At the supply stage, our experts identified discrepancies in the distribution process. Our solutions offered multiple distribution channels – same-day pickup, in-store delivery, and courier delivery — for the client to overcome their supply chain bottlenecks. This was followed by the creation of a centralized data warehouse management system that collected, analyzed, and interpreted the client’s organizational and research data. This centralized warehouse allowed the client the leverage years of medical history records, demographics, results, previous diseases, and allergies of the patients. This ultimately helped the client deliver proactive solutions to the patients by providing exact solutions to their problems, treatment plans, and eventually led to optimized patient care. 

This warehouse also allowed the client to create risk models of patients through understanding their medical conditions and predicting high-risk patients. From the patient’s point of view, this process significantly improved the quality of patient care provided by the client, early intervention for high-risk diseases, and reduction in medical expenses as well. Once this was dealt with, the last stage of challenges was to develop an effective application to help the patients and EHRs. 

Our healthcare data analytics experts started developing an in-house AI-driven healthcare application available of various platforms to provide real-time access to patient engagement maps and actionable medical insights. This app not only allowed the officials to derive ample details to serve the patients better, but also integrated automation-based chatbots to engage patients and reduce any missed opportunities. Borrowing from the centralized data warehouse, the app also included the entire history of the patient’s medical records to help the physicians understand the needs of the patients even before the examinations. Moreover, the app also helped the healthcare client transform their insurance offerings by gaining a granular approach to customer policies, monitor premiums, and open claims. 

How can healthcare data analytics be successfully deployed? Request a free proposal of our advanced data analytics solutions to understand where to begin and how we can help you solve complex business problems, aid in data-based decision-making, and optimize patient care.  

Impact Analysis of Quantzig’s Data Analytics Solutions for Healthcare Client 

Through our advanced analytics solutions, the client was able to develop strategies based on predicted risk profiles through patients’ potential threats and medical history. Following which, the client was able to effectively create risk pooling strategies to charge a high premium cost from high-risk individuals and offset the low premium charges on low-risk patients. This resulted in significantly lower premiums for the low-risk individuals compared to any other competitor, and catapulted the client ahead of their competition. 

Key-Takeaways 

Our AI-driven offerings leveraged customer insights that helped our client run successful clinical trials, drug analysis, and inventory management. Compared to traditional solutions implemented to analyze product demand, our solution was much more effective and convenient. Our solutions enabled the client to unlock the following benefits.  

  • Improve clinical trial efficiency and enhance commercial spend effectiveness by 47% 
  • Increased profit margin by approximately 10% as supply expenses decreased by 17.7%.  
  • Our customer analytics framework helped improve the success rate of clinical trials by 10%. 
  • Frame customized strategies for multiple customer groups based on risk analysis.   
  • Implement a healthcare app that provided real-time information to optimize patient care 
  • Created a centralized data warehouse management system to collect all organizational, clinical, and research data in one place 
  • 15% increase in patient conversion rates over three months 

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