COVID-19 Multi-State Project Data Dashboard Assessment OCHIN

NACHC has created data dashboards for COVID-19 and we need your help ensuring they are as good as they can get.

Please review the dashboard of the project and your organization and provide an assessment of the data status and condition by close of business April 29, 2022.

There are 4 areas of data currently mapped to the dashboard:

Patients characteristics
Encounters and Vaccines
Diagnosis
Testing

1. Highest level question:

Does your organization’s data match your assessment of its condition? Do numbers and percentages seem to match your internal assessment?

We’re showing different percentages for age and for race. 51% of our population is 65 and over. 42% are between the ages of 50-64. 31% are 30-49, 25% 18-29, 29% are 12-17, and 11% are 5-11.

For ethnicity, White is 33%, Asian is 30%, Pacific Islander is 29% and Black is 23%.

2. Demographics:

Are there categories you seem to have a lot of missing data or no data (blank graphs or figures)? Do you think this data can be improved? If so, what would be a feasible improvement plan?

There are blanks in the race category here but our organization data does not show the same results. Additionally, the patient geographical distribution was surprising but understandable. Since the extract Mark sent had around 447,000 patients, a few from states outside of the PNW makes sense since they could visit a clinic while traveling. It would be interesting to see the actual numbers of how many are coming from the states outside of WA, OR, or ID.

3. Encounters and Vaccinations

Are you missing data? Do you see all the months and years? Do the data patterns make sense? Do you think this data can be improved? If so, what would be a feasible improvement plan?

All the months and years are there and the vaccination trends make sense. The encounters make sense given that it includes more than COVID visit types.

4. Diagnosis (Dx)

Look at the Project Dx Distribution, it contains all the diagnosis codes that were requested in our data dictionary. In looking at your organization’s data, do you think this data can be improved? If so, what would be a feasible improvement plan?

This data seems reasonable. There are no vague dx codes and it seems in line with what we would expect.

5. Testing (There are 2 partner testing pages)

Are you missing data? Do you see all the months and years? Do the data patterns make sense? Do you think this data can be improved? If so, what would be a feasible improvement plan?

The test trends make sense as they range from 5-20%.