By Chris Christy, Director of Health Solutions at Qlik
Data is essential for decision making within healthcare organizations, but having a unified view is essential. Today, it is vital that any company understands its customers' data, whether they are consumers or patients. The problem is when the numbers don't work, and you need to start digging.
Having wrong data at your base is like walking in a minefield: it becomes more difficult for everyone to define the next steps. After all, we have already experienced data that figuratively exploded in our faces because it was incorrect. Reliable information, on the other hand, becomes big business. They can provide insight into human resource needs, supply chain opportunities, operational improvements, and more.
In order to minimize disagreements within the organization and focus on a unified version, the quality of the data must be guaranteed. But how can this be done with large sets of multivariate information, such as those in the area of Health? Understanding where any suspicious data lives is the first step towards better decision making. Being able to see the whole story allows you to perceive and solve the difficulties.
The data captured by the Health sector can be divided into tangibles, such as the number of patients treated, or intangibles, such as information about care for these patients - and hospitals have a central role in both. Their efforts in health and direct care to the population save lives, but they also produce a multitude of content that can be analyzed to determine the best standards and protocols of care.
The implications of this are great. The digital transformation leads companies to adopt the best practices based on the results obtained. Therefore, the quality of the data becomes essential for accurate diagnoses and treatments. If similar organizations adopt standards for presenting data, it will be possible to compare their results to understand what works best in certain clinical situations of similar patients. When aggregated, this information can reveal how to achieve the best service at the lowest cost.
But how do you know if there is quality in your data? The answer is to take advantage of the same analytics platform that the rest of the organization uses - adding hospital data is just one more way to use these solutions. When this information is in a good data tool, it is possible to aggregate it to define inconsistencies and lack of data.
As the health area is systematized, so that having a complete view of the patient determines the next clinical stage, data collection becomes increasingly important. The Internet of Things also has a prominent role in the health area, Wellness devices become cheaper and easier to use, so the interest of consumers in self-assessment is growing.
All of this means more data - but the question remains: did they come from a gold mine or is it a minefield?
Having wrong data at your base is like walking in a minefield: it becomes more difficult for everyone to define the next steps. After all, we have already experienced data that figuratively exploded in our faces because it was incorrect. Reliable information, on the other hand, becomes big business. They can provide insight into human resource needs, supply chain opportunities, operational improvements, and more.
In order to minimize disagreements within the organization and focus on a unified version, the quality of the data must be guaranteed. But how can this be done with large sets of multivariate information, such as those in the area of Health? Understanding where any suspicious data lives is the first step towards better decision making. Being able to see the whole story allows you to perceive and solve the difficulties.
The data captured by the Health sector can be divided into tangibles, such as the number of patients treated, or intangibles, such as information about care for these patients - and hospitals have a central role in both. Their efforts in health and direct care to the population save lives, but they also produce a multitude of content that can be analyzed to determine the best standards and protocols of care.
The implications of this are great. The digital transformation leads companies to adopt the best practices based on the results obtained. Therefore, the quality of the data becomes essential for accurate diagnoses and treatments. If similar organizations adopt standards for presenting data, it will be possible to compare their results to understand what works best in certain clinical situations of similar patients. When aggregated, this information can reveal how to achieve the best service at the lowest cost.
But how do you know if there is quality in your data? The answer is to take advantage of the same analytics platform that the rest of the organization uses - adding hospital data is just one more way to use these solutions. When this information is in a good data tool, it is possible to aggregate it to define inconsistencies and lack of data.
As the health area is systematized, so that having a complete view of the patient determines the next clinical stage, data collection becomes increasingly important. The Internet of Things also has a prominent role in the health area, Wellness devices become cheaper and easier to use, so the interest of consumers in self-assessment is growing.
All of this means more data - but the question remains: did they come from a gold mine or is it a minefield?
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