Case Study
Pinscriptive Inc. employs AI, Big Data Analytics, and the Meteora framework to aid patients afflicted with Hepatitis C.
Pinscriptive Inc., established in 2014 in Greater LA, is dedicated to offering software analytics on specialty drugs for healthcare providers.
These analytics assist healthcare providers in making value-based decisions and provide evidence to identify the most suitable drugs for individual patients, facilitating the production of the most appropriate specialty drugs. As a result, healthcare providers can confidently...
The company's platform utilizes data analytics to pinpoint clinically effective specialty medications at an optimal cost for each patient, empowering healthcare professionals to make informed decisions regarding specialty drugs. This approach reduces costs and enhances outcomes, ensuring more effective treatment for patients.
Pinscriptive undertook the development of a specialized tool designed to process raw data specifically for patients with Hepatitis C stored in MySQL Server. This tool was tasked with transforming the processed data into visual representations.
The functionality and visualization of the tool relied on various parameters. Accuracy was paramount, necessitating identification and handling of missing data.
Furthermore, rigorous verification and authentication protocols were implemented to ensure the utmost accuracy of the represented data, recognizing the critical potential impact on patient outcomes.
This tool was intended for use by physicians, pharmacists, healthcare providers, and insurance companies alike.
-Processing aggregated data from MySQL Server using algorithms tailored specifically for Hepatitis C.
-Visualize data through graphical representations.
-A dashboard to showcase patients' characteristics, payer information, and other pertinent details.
-The dashboard should exhibit distributions such as cost, treatment, and genotype breakdowns using charts and other visualizations.
-Offering filters to search patient details based on age range, ethnicity, and other medical attributes.
-Physicians can access details of specialty drugs from various providers and utilize this information to compare results.
-A feature for physicians to access a list of recommended drugs based on insurance coverage and risk characteristics.
-For pharmacists, there should be a distinct comparison based on various parameters.
-A dedicated Analytics tab for viewing both descriptive and predictive analytics.
-Verification of patient treatment to ensure data accuracy and treatment appropriateness.
Binary Republik was supplied with raw data from Pinscriptive. The task involved processing the data using adaptive algorithms capable of identifying Hepatitis C patients. Additionally, this process encompassed the removal of irrelevant data from the aggregated dataset.
This system was designed specifically for use by physicians, healthcare providers, insurance companies, and pharmacists.
Employing diverse adaptive algorithms and big data analytics techniques, we processed the data and presented it to specialized doctors for authentication. Further segmentation of the data was required based on the users utilizing the system.
We needed to develop an architecture and platform that would be beneficial for various user groups, considering the processed data. This processed data was visualized using custom visualization tools, including Python and various other technologies.
Data analysis is conducted using a set of algorithms to uncover correlations within the clinical data. Subsequently, various charts are generated to visually represent the clinical data. Predictive analytics are then applied to further analyze the data, determining the optimal drug for the patient while considering the ideal scenario. Additionally, predictive models are developed based on the received data to forecast outcomes for unknown patients.
Therefore, this tool proves valuable for specialty biopharmaceutical manufacturers, providing a model that transitions their products "from volume to value." It supports risk-based contracts with precision analytics, thereby boosting sales, fostering innovation in specialty drugs, managing healthcare budgets, and offering insights into current market trends and scenarios.
This product will facilitate the delivery of insights into specialty drug usage and costs, harnessing the power of Big Data analytics, a suite of proprietary algorithms, and the integration of real-world data from Electronic Medical Records (EMRs).
By employing machine learning, population analytics, and leveraging existing knowledge and experience, this tool aids in managing specialty drug trends, thereby enabling the implementation of a disruptive pricing model.
Assists insurance companies, patients, and their physicians in discovering cost-effective specialty drug solutions by identifying the precise drug for the right patient at the appropriate price
Most precise data regarding Hepatitis C patients.
Assists payers, at-risk health systems, and accountable care organizations in optimizing specialty drug decisions through foolproof decision-making, taking into account both quality and cost insights.
Clients can access visualizations to gain insights into the market landscape.
Physicians can determine whether the data is missing or if the treatment is incorrect.
Our proven methodologies and a track record of excellent services backed with by years of experience with SharePoint will ensure a high success ratio and a greater user acceptance.
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