Business Intelligence & Data Visualization in Health Care Industry

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Business Intelligence & Data Visualization in Health Care Industry

The healthcare industry is one of the world’s largest, with a direct impact on people’s quality of life in each country. To fulfil the health requirements of people and populations, the contemporary health care industry is split into several sub-sectors and relies on multidisciplinary teams of trained professionals and paraprofessionals.

Along with the industry growing year by year, the data generated by the healthcare industry is growing monumentally every year. But, why is this important? It’s important because data is a treasure trove of valuable information, insights (more importantly actionable insights) and trends. If dealt with and used in the right way, it can help practitioners deliver better and more personalized care and can also help healthcare enterprises streamline internal processes, operations and lower costs of delivering optimal healthcare.

In Today’s time the data analysis has incredible power dealing with the most medial studies. It’s also essential for the Healthcare Professional during their everyday practice to know the Patient Health Whether it is individual Patient or the whole Population. But with the heap of data it is of little use without the data visualization. Data Visualization brings the realistic facts to the absolute ease making data analysis more efficient for physicians, nurses and other health professionals.

What is Data Analytics?

In simple words, it is the process of examining and analyzing the data generated by computational and scientific methods to obtain valuable and actionable insights. By obtaining these insights, practitioners and healthcare enterprises can fine tune and provide better healthcare and services and gauge patient satisfaction and strive to improve it.

What is Health Data?

Any information on a patient’s or a population’s health is considered health data. Health care providers, insurance firms, and government agencies use a variety of health information systems (HIS) and other technologies to collect this data such as:

·        Electronic Health Records (EHRs)

·        Patient Portals

·        Health related Smartphone apps and more

Healthcare Data Analytics

Applying the computational and scientific methods of analyzing data on health data gives rise to Healthcare Data Analytics with it’s importance growing year by year. For ex: With the help of Healthcare Data Analytics, Practitioners can spot individuals who are at high risk of acquiring chronic diseases and intervene before it becomes a problem. Preventive therapy may assist to avoid long-term problems and costly hospitalizations, lowering expenses for the practitioner, insurance company, and patient.Healthcare Data Analytics can be broadly classified into 3 categories:

·        Descriptive Analytics: focuses on historical data and can be used to answer questions about what has already
occurred. What happened? Why did it happen?

·        Predictive Analytics: uses various techniques (modeling, AI, statistics) to evaluate historical and real-time data
to make predictions about the future. It is used to optimize operations, prevent patient leakage, identify at-risk patient cohorts etc.

·        Prescriptive Analytics: gathers data from both, descriptive and predictive sources, and applies them to the process of decision making. It considers information such as potential situations or scenarios, available resources, previous performance, and present performance to recommend a course of action or strategy.

These techniques can also be used on a much larger scale. Population health management is impossible without the use of these models. Outbreaks can be predicted and in knowing what is to come, preventive measures can be taken.

We now know what and how important healthcare data analytics is, but who actually does it?

Health Data Analysts! 

Data Analysis Dashboard

Analytical Dashboards help the Healthcare Professionals to quickly analyse the large set of data by saving the time and these dashboard helps to access the information on their Projected Interest easiest way with the enhanced Health Intelligence giving them scope to improvise their future actions by the study of their historical data.

The Representational Model of the Data analysis and Visualizations helps the end-user to analyse the data by presenting it in human readable format without digging into the actual data or without any prior technical skills/Trained Professionals.

These data analysis Dashboards with the statistical analysis of the data provides the useful information for the end-user by highlighting the insights of their needs: Displaying an Interactive and Customization visual in the form of graphs, Charts, Maps etc…

Insights on Relevant Information based on User Role

Each set of Members in the Healthcare Organization (Clinical, Financial, Executives etc.) are looking for the different Metrics. Since, each set of members in Organization have specific key points to be Considered not all the Departmental or Organizational level.

For Example:

  1. Revenue: The Financial Team of the Organisation interested only in the Revenue generated from each of the department, Year to Year Historic trends on Revenue in the organisation which will help them to analyse the Success rates, lower the risks on the losses and also help the organisation make better Decision.
  2. Physician: Dashboard helps Control the Narcotic Medication. Data analysis and Visualization helps the Physician to the track and reduce the number of Narcotics for a single Patient gets. Physicians will monitor the Patient history before dispensing the medicine which will reduce the risk of narcotic medication abuse.

Conclusion

In Current Healthcare Industry with the rapid growth on the volume of data and the large Audience associated with this Industry needs to have the Data Visualization Reports which will provide Clear Insights, better Decision-Making Capabilities and enhance the scope of more effective/actionable strategies toward their success.

Santéware’s Health Data Analysts work in the intersection of business and engineering and hence are well-versed with the technical side (SQL, Excel, use of advanced reporting systems such as SSRS, Power BI, Amazon Quicksight) and the business side (healthcare domain expertise, analytical and creative thinking, requirement gathering, strong communication skills) to deliver meaningful insights from health care data. Please find out more here.

Authors

Shivanagauda Patil is a Senior Consultant at Santeware.

Kushaal Kanavi is a EMR Analyst at Santeware

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