There is a lot of value in studying other industries outside higher education to gain perspective on issues we face and how we may adapt practices and technologies for our use. Amid rising student debt, claims of administrative bloat, call for higher accountability, and questions about the value of higher education, there seem to be more discussions about assessment within student affairs to improve the quality of services and provide evidence of our contribution to student success. A key component in assessment is data and the ability to aggregate them from different data sources and perform analysis for different purposes. Information systems within the same campus do not communicate with each other leading to siloed data. Regarding assessment, this issue of systems’ inability to communicate and exchange data leads to less than accurate analysis and evaluation. In addition, the quality of service provided to students and other customers suffer. As one who oversees our campus suite of student health and counseling information systems, I see some parallels between higher education and the medical care industry regarding data-related challenges.
One concept I came across from reading a book called Connected Health: How Mobile Phones, Cloud and Big Data Will Reinvent Healthcare by Jody Ranck is “data liquidity,” which the author describes as “the ability to move data from one part of the health system to another.” Another definition offered by this article is “more ways and more choices for patients to own their computable health data, thus enabling patients to use their data to get help and advice.” Conceptually, data should be able to move freely from health providers and be accessible to patients.
The idea that students/learners should own their data and be portable across institutions is a topic I discussed in this blog post, “Common Learning Portfolio Markup Language (CLPML) – A Proposal.” One of the major challenges to this concept I proposed is the lack of a common standard in how data can be shared across student information systems in terms of data format and interfaces (how different systems communicate). What I know is that an interface standard exists in the medical industry called HL7 used for clinical applications to communicate. Furthermore, older legacy systems designed to be stand-alone require modifications/enhancements to interface with other systems. These enhancement projects may require significant financial and human resources.
For “data liquidity” to improve, other obstacles beyond technology must be overcome. Data privacy rules and policies exist to protect student data. Still, it seems so convenient for some to use the same rules and policies as inappropriate reasons not to share data, even to students who have the right to view their data. Furthermore, some existing data policies must be revised to reflect current needs and technological advances, including cloud and mobile computing. In addition, designs of information systems must be designed from the customers’ perspective. It’s too convenient to design systems without consulting with those we serve, leading to silos instead of an integrated set of student information systems and services.
It will be interesting to follow how the medical care industry will address the lack of data liquidity and how solutions they arrive at within their industry can be adapted for higher education.
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April 3rd, 2014 on 10:56 am
[…] exchange data with each other. This is one of the challenges I discussed in this blog post about Higher Education and Data Liquidity. Moving forward, there has to be a way for these separate systems to be able to communicate and […]
March 10th, 2016 on 1:47 am
[…] the lack of data liquidity (ability to move data from one system to another) which I shared in this post is even a bigger constraint. That there is not a single common structured data model in higher […]