ResolveData - Actualizing Data to Drive Transformational Healthcare
ResolveData - Actualizing Data to Drive Transformational Healthcare
Data Integration. A Crucial step for healthcare and pharma industries. – ResolveDatas
Data Integration. A Crucial step for healthcare and pharma industries.

Data Integration. A Crucial step for healthcare and pharma industries.

Data Analytics

Data Integration.
A Crucial step for healthcare
and pharma industries.

Healthcare providers and the pharmaceutical industry are facing substantial challenges to improve patient outcomes and introduce new drugs. Data plays a significant role in the functioning of these industries. They not only have to deal with data collection but also with proper data management. When data is handled the right way, pharma and healthcare providers will be able to gain insights faster, leading to improved care.

Data is collected to improve healthcare and generate meaningful insights.


What is Data Integration and How Can it Help the Healthcare and Pharmaceutical Industry?

The pharmaceutical and healthcare industry have adopted advanced technologies for various aspects of their operations. However, when it comes to adoption and dealing with data, things have been running at a slower pace.

Apart from the technical issue of data integration, there has been the problem of ability and willingness between patients and healthcare providers. So, it shouldn’t come as a surprise that collecting, storing, and integrating data for accessing iton-demand is still a broken process. No doubt, the healthcare, and pharmaceutical industry are in dire need of integration tools. With the right data integration tools, the healthcare system can function when dealing with data.

Advantages of Having Data Integration in the Healthcare Industry


The healthcare industry is adopting new measures to facilitate digital electronic exchange. Data Interoperability is the key element in healthcare data sharing. An integrated system helps healthcare providers to exchange data and get access to it through a user-friendly and comprehensive interface.

Meaningful use of data can help in overcoming the problem of the electronic exchange of information. With this, it is possible to have an effective interface between the system from different vendors.

Healthcare data from different sources contain various details and all these need to be unified using a certain terminologymapping and standards.

What are the Challenges of Data Integration in Healthcare and Pharma?

No doubt, healthcare, and pharma are in dire need of data integration. However, there are some significant challenges that are being faced by the industry.

Data in pharma comes from a myriad of sources. These days even wearables are uploading health data. Sure, these technological trends are helping individuals to stay updated on their health but it also led to the collection of excessive amounts of data. Not only does this lead to problems of compliance by the healthcare providers but also increases privacy concerns.

Apart from maintaining the data, they also have to be presented in a way that is accessible to the healthcare professionals and the patients.

So, here is a look at the most common challenges faced by these industries when it comes to data integration,

Advancing Healthcare Analytics through Data Lakes

Data lakes predictive analytics in pharma brings value to the industry. It can store data in a central repository and is easily accessible when required. The data lake approach brings data in and then gives it a structure as required by the specific need.

Data in healthcare comes from two major sources-clinical data and claims data. The former is scattered and unstructured data across systems, such as warehouses, data marts, and other external data sources. While the latter represents data from the medical insurance companies that claim for the reimbursements of patients. The data from these medical insurance companies are mostly available in a structured format.

Data lakes predictive analytics in pharma and healthcare and transform the industry and provide robust architecture. So, healthcare analysts can get access to data easily, predict results, and treat patients better. With healthcare and pharma data lake, there is significant scope for data-driven decision making.

Challenges of Data in Pharma and Healthcare


  • Ever-Changing Data:
    Data is being collected every day. Patients are moving, changing professionals, developing new diseases, retiring, or passing away. Even data related to healthcare providers are also changing. Moreover, the introduction of new treatments and drugs can change the scenario of the healthcare and pharma industry. Hence, keeping data clean and updated can be a major challenge.
  • Fragmented Data:
    Data is collected from different sources and is hence fragmented. Thus, extraction and integration of data can pose a real problem. When it comes to healthcare and pharma, a large number of entities are collecting data, including patients, doctors, and insurance providers. So, fragmentation can lead to inaccurate health profiles. In fact, a Health Affair study shows that about 12% of patient revenue is used on administrative costs, while 74% of this amount is mis-spent on billing inaccuracies.
  • Security Policy:
    Healthcare needs to have an effective ecosystem to function efficiently. But it is necessary to make sure data is secure to protect the privacy of patients. It must be HIPAA2 compliant. Improper data security strategy can cause pharma and healthcare to abide by the regulatory requirements, So, the data security and privacy issues have to be addressed.

    But pharma data lake can harness data from various sources and put them in a structured format to be used later. It becomes easier for the research and development team to work on their hypothesis and assess results. Hence, it enables pharma and healthcare to choose the right medicine for the patients.

    No doubt, data lakes in pharma and healthcare industry offer incredible value.

Advantages of Using Data Lakes in Pharma and Healthcare


  • Scalability:
    Data Lake can handle large volumes of data and helps keep costs low.
  • Ensures Easy Adaptability to Future Technological Changes:
    As the saying goes –
    Change is constant. This holds even more true when it comes to technology. Data lakes are highly malleable and help with easy adoption of latest technology development. Data plays a crucial role in healthcare. With a data lake, healthcare and pharma companies can store data innative formats before being transformed into a structured database. So, any data can be extracted easily whenever required.
  • Hordes Data Legitimately:
    Not all data is important at all times. Thus, a data lake can store data that is not valuable at present to be used in the future. As data is stored in native format, it can used anytimefor analysis.

This is the Best Time to Implement Data Lake

Today, there are a host of devices and technologies monitoring patients as well as individual’s health, and each of them is generating data. With digitalization, there has been an excessive amount of data and healthcare demands for disease management, wellness, and diagnosis are changing rapidly.

These new opportunities are creating a gaping hole between reality and big data analytics promises. But this can be mitigated through the use of data lakes.

There is the serious hullabaloo around data lakes, particularly for the healthcare and pharma industry. But given the architecture required and the technological necessity to support this technology, organizations might require some time to adapt to it. ResolveData helps craft and build customized data lake solutions for the healthcare and pharma industries. If you have accumulated a large amounts of data but have not been able to progress in your mission, we can help you with the process. Medicine and healthcare cannot be left to decisions based on inaccurate and poor-quality data. So, make the best use of your data to offer improved healthcare outcomes.

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ResolveData - Actualizing Data to Drive Transformational Healthcare
  • ResolveData - Actualizing Data to Drive Transformational Healthcare
  • ResolveData - Actualizing Data to Drive Transformational Healthcare
  • ResolveData - Actualizing Data to Drive Transformational Healthcare
  • ResolveData - Actualizing Data to Drive Transformational Healthcare

© 2021 ResolveData. All Rights Reserved

© 2021 ResolveData. All Rights Reserved

  • ResolveData - Actualizing Data to Drive Transformational Healthcare
  • ResolveData - Actualizing Data to Drive Transformational Healthcare
  • ResolveData - Actualizing Data to Drive Transformational Healthcare