Connecting Data to Business Problems

Connecting Data to Business Problems

1. Problem Description

Rise in price of precision Medicine-Data Management cost

Most healthcare organizations are implementing precision medicine strategies and applying them to new disease areas while studying how genes affect an individual’s response to drugs, a process called pharmacogenomics. High data management and storage costs drive up costs for storing large chunk of patient information like genetic data for patients needing specialized care and need precision medicine; thus, increases the price of precision drugs. An important measure of the rise in prices is the data management costs. The problem of measuring the rise in prices of precision medicine using data management costs is the variation in the type of data stored driven by the amount of the patient’s data collected, the type and quality of prescribed medicine. Data managers could benefit from taking into account such factors.

2. Hypothesis and data

The Data Management costs of any particular health organization can be predicted from the following factors:

-The amount of the collected patient’s data

-The type of prescribed precision medicine

-The quality of the prescribed precision medicine

The data gives information on the rise in prices and data management costs

Value Add

This model enables a more precise view of the prices of precision medicine while taking into account the contextual factors in data management. Healthcare institutions can use this model to precisely determine the prices of prescription medicine and set effective prices that are efficient and manageable by their patients. On the other hand, these health institutions can turn into machine learning and artificial intelligence (AI) to maximize the potential that these large datasets offer. Data managers can also find a compromise in this model and offer competitive prices to health organizations to reduce the prices of precision medicine.