Informatics Common Metrics Year Two Membership Survey

Purpose

To improve the interoperability of data within multiple systems by making the data adhere to the FAIR data principles to ultimately enable rich machine-readable data.

Executive Summary

This report provides hub-level feedback for the iDTF Membership Survey – Year 2 of the Informatics Common Metric. This survey was implemented October 7 – 11, 2019 to solicit information for enhancing/adding new measures to the Informatics metric. The survey was distributed by CLIC to the iDTF listserv (98 members), resulting in 31 total responses (31.62% response rate). Data collected included feedback in the following areas (see Survey Results for further details):

♦ Hub data models
♦ Usefulness of the metric data
♦ Additional data elements

This report includes data tables and qualitative text-based survey responses. The Informatics metric was implemented with the understanding that it would evolve into a comprehensive characterization of the research data warehouses (RDWs) as well as a quality improvement tool, the intent of this report is to further assist the metric development team in the advancement of the Informatics metric, and to communicate this hub-level feedback to the CTSA Program community.

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Instrument Fields
Order Instrument Field
1

Select the data model that you will be using to report on the Informatics Common Metric.

2

Please provide additional comments on the data models.

3

In what ways was the informatics Common Metric useful to your hub?

4

Did the Informatics Common Metric help you identify ways to improve the data quality in the clinical research data warehouse(s)?

5

Please provide additional comments on improving the data quality.

6

Did the Informatics metric help you identify ways to address the errors in the clinical research data warehouse?

7

Please provide additional comments on identifying errors in the clinical research data warehouse.

8

For your hub, how valuable is the measure of the total number of medication records and the % of medications that have an RxNorm value?

9

How easy was it for your hub to acquire this data?

10

Please provide additional comments on acquiring this data, and how valuable it is for your hub.

11

For your hub, how valuable is the measure of the types of encounters?

12

How easy was it for your hub to acquire this data?

13

Please provide additional comments on acquiring this data, and how valuable it is for your hub.

14

For your hub, how valuable is the measure of including new data domains? (i.e. oncology, genomics, pathology)

15

How easy was it for your hub to acquire this data?

16

Please provide additional comments on acquiring this data, and how valuable it is for your hub.

17

For your hub, how valuable was it to include short- and long-term time frames of RDW measure? (i.e., last 12 months and last 5 years)

18

How easy was it for your hub to acquire this data?

19

Please provide additional comments on acquiring this data, and how valuable it is for your hub.

20

For your hub, how valuable was it to extend the demographics characterization measure?


Submitted by Laura Hassinger on Fri, 02/28/2020 - 14:33