Reducing Cost of Patient Care in Hospitals with Data Analytics
Posted on 24 April 2019
Reducing Cost of Patient Care in Hospitals with Data Analytics
Hospitals need to provide the best treatment for their patients with low cost. It is tough to maintain the balance between cost and quality. Data Analytics helps to reduce the cost of patient care which helps to provide more personalized services. Health care professionals could use data analytics and predictive modelling techniques as well as business intelligence (BI). 7 effective ways to cut down cost are-
1.Cut down of administrative cost- Administrative cost can be decreased with electronic medical records; healthcare encounter into cash flow can be significantly enhanced with automated coding.
2.Clinical Decision Support- The decision-making process by clinicians can be improved by bringing lab reports, medical tests and prescribed medications on one electronic board.
3.Cutting down fraud and abuse- Analytics not only helps to track incorrect payments and fraudulent but also to know about the history of an individual patient.
4. For better care coordination- Analytics helps with patient handoff which not only helpful within the system but also across all the healthcare organisations across the country.
5.Improved patient wellness- With the help of Analytics, healthcare organizations will help to remind patients to keep a healthy lifestyle. This will also help to keep track of patients’ lifestyle choices. This makes the patient feel their health as a top priority with continuous reminders.
6.Reducing emergency room visits- Appropriate preventive care will reduce health care costs and overall hospital care because early care can reduce the severity of the disease.
7.Better use of analytical tools helps to produce better results-
a.Optimization of Block Scheduling-
In order to identify the inefficiencies and revenue losses, health care analytical team uses BI tools which are used to drill out the patterns. For example, the operation room area is suffering inefficiency and the problem in this area can be rectified through analytics. Whereas an empty room is a source of waste which doesn’t need any kind of analytics. The data is to be collected and analyzed with the help of data analytics. Combining the operation room information and providing with automated access to usage will make a huge difference.
b.Scrutinizing the Supply Chain-
To identify supplier performance and invoice billing data, health care providers can drill into invoice billing data and procurement with the help of analytics tools and BI. Supplier performance can be analyzed with the help of pricing, quality, quantity and timeliness.
c.Maximize the machines-
Essential hardware can be monitored to detect the breakdowns using BI and analytical tools. This can be done by optimizing service and operations and ensuring work to be performed at the right time, monitoring and analyzing equipment data, sensing remotely operational data from the equipment.