15 Aug Reply to your peers discussion post.
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There are 2 dicussion post. Each post shouldnt exceed a paragraph,
1st discusiion
Why do you think data terminology matters so much? What happens if theres not a common understanding of and structure to the data?
Data terminology matters because it provides structure for an organization’s data architecture and there is a higher risk of losing crucial information in translation and transition if the data is not clearly/universally defined. The use of generally excepted and well-documented controlled terminologies by different systems, individuals or groups may facilitate interoperability (Brown et al 2018). If there is no common understanding and structure to data, then value communication can be lost, and the data becomes just noise.
In your opinion how does a great information management strategy help organizations to be more agile and better able to integrate, deliver, and share information?
A great information management strategy help organizations efficiently manage the flow and communication of data throughout the organization. This mitigates some of the issues that can undermine their ability to create and make decisions. Have clear concise data that is universally recognized allows organization to collaborate with each other as each is aware of precisely what the data means..
References:
Brown, G., Pasupathy, K., & Patrick, T., (2018). Health Informatics: A Systems Perspective, Second Edition. Chicago: Health Administration Press
2discussion
- Why do you think data terminology matters so much? What happens if theres not a common understanding of and structure to the data?
If we want to be able to reuse any data put into a system, it needs to be input in a standard language where possible. I was reminded of the Tuskegee syphilis study in this week’s readings, particularly about the “bad blood” jargon used when collecting patient samples. To patients, they had no idea that bad blood = syphilis, and what their study’s protocols were. This was a prime example of how different terminology in science/healthcare can lead to extremely dangerous outcomes. As we’ve gathered from other classes and this one, interoperability becomes a huge issue as well. Not all healthcare systems are the same, nor is their understanding of the value of that data at a later date. The only way around this is through the use of controlled terminology. The reality of this is often an intermediate language standard that can relate one set of terminology to another after the fact (i.e. the methathesaurus). Imagine operations without this tool. We would see numerous areas of disconnect in our field, far more than what has already been corrected due to solutions such as the metathesaurus and terminology mapping. Data terminology comes hand in hand with quality of care.
- In your opinion how does a great information management strategy help organizations to be more agile and better able to integrate, deliver, and share information?
Information management assists in improving existing processes and preparing for the future. My biggest takeaway from our work with information management is that our IT efforts need to match up with our goals and business strategy, without causing an unwarranted increase in cost or disruption in our ability to use our own data. By being fully aware of our end-game, we can make smarter decisions along the way that align with these aspirations. It comes with an understanding that data is more than just information — it is valuable, in-demand, and informative of decision-making. Just “having” data is meaningless as it needs to be interpreted and utilized to understand its value (i.e. it’s not what kind of technology you have, but what you do with that technology that matters). I found a really great schematic that highlights what an information management strategy can mean for business outcomes:
