{"id":6968,"date":"2024-03-25T07:53:34","date_gmt":"2024-03-25T14:53:34","guid":{"rendered":"https:\/\/news.nnlm.gov\/nec\/?p=6968"},"modified":"2024-03-25T09:15:48","modified_gmt":"2024-03-25T16:15:48","slug":"the-importance-of-data-standardization-in-evaluation","status":"publish","type":"post","link":"https:\/\/news.nnlm.gov\/nec\/2024\/03\/25\/the-importance-of-data-standardization-in-evaluation\/","title":{"rendered":"The Importance of Data Standardization in Evaluation"},"content":{"rendered":"

Whether we\u2019re thinking about patient records and outcomes, sports statistics, or NNLM membership and activity records, data standardization is critical to unlocking the story held within the data. While not always an easy endeavor (and one that often requires intergroup compromise), data standardization pays significant dividends when it comes time to analyze, interpret, and disseminate findings.<\/p>\n

Now, you may be asking, \u201cWhat do they mean by data standards and standardization?\u201d That\u2019s a fair question! The International Organization for Standardization defines data<\/a> standards this way: “Standards define what great looks like, setting consistent benchmarks for businesses and consumers alike \u2014 ensuring reliability, building trust, and simplifying choices.\u201d The goal of standards is to provide a common approach and repeatable outcomes.<\/p>\n

Some common examples include standardization \u2014 or, said another way, consistency \u2014 in how we define and collect Zip\/postal codes, phone numbers, organization type descriptors, and so on. For example, are Zip\/postal codes 5 or 9 digits? Do the phone numbers include area code (and are the components of the phone number separated by parentheses, dashes, or both)? And, are NNLM member organizations assigned to a single, well-defined organization type?<\/p>\n

Thinking specifically about the NNLM, here are a few important benefits of data standardization.<\/p>\n

Apples to Apples Reporting<\/strong>. While fruit salad may be delicious, it is not desirable in the context of data collection, analysis, reporting, and dissemination. For NNLM, data standardization ensures that data entered by member organization primary contacts (formerly known as liaisons) or ROC staff are entered in a consistent manner. This, in turn, allows ROC and UEP leadership to query data systems and report on findings with confidence in data quality. Moreover, adherence to federal standards<\/a> makes it easier for individuals and decision-makers outside of the Network to understand our data.<\/p>\n

Inclusivity in Data Reporting<\/strong>. Data standardization \u2014 when combined with controlled vocabularies and a strategic approach to making fields required or optional \u2014 ensures that all groups are counted and included in outputs such as infographics, dashboards, and formal reports.<\/p>\n

Simplicity in Documentation, Training, and Data Entry<\/strong>. Once implemented, data standardization makes life easier for NNLM ROC staff. For example, it is significantly easier to prepare and maintain documentation and training resources when data are standardized across the Network. Also, especially in instances where repeated data entry is required, standardization increases the accuracy of data entered into the database system.<\/p>\n

Do you want to learn more about data standardization, including its benefits and real-world applications? Here are a few useful resources:<\/p>\n