# data[].attributes.headline
Comparisons would have to be with previous time periods, therefore historical data would have to be of high quality and may limit the questions that can be asked of the data.

# data[].attributes.subject
Comparisons would have to be with previous time periods, therefore historical data would have to be of high quality and may limit the questions that can be asked of the data.

# data[].attributes.headline
Data quality is a concern - depending on how it's acquired and how accurate it is - if total counts of sales are off or if a column shifts that may be problematic

# data[].attributes.subject
Data quality is a concern - depending on how it's acquired and how accurate it is - if total counts of sales are off or if a column shifts that may be problematic

# data[].attributes.headline
DC DOH may have had OTC sales - similar to the lab data, actual pharmacies included were proprietary so it wasn't supposed to be known who was reporting the data. Could be a trust issue for the datasource in whether it is truly representative

# data[].attributes.subject
DC DOH may have had OTC sales - similar to the lab data, actual pharmacies included were proprietary so it wasn't supposed to be known who was reporting the data. Could be a trust issue for the datasource in whether it is truly representative

# data[].attributes.headline
Thermometer sales - things like supply chain may create issues when there is a product backlog. This means it misses what's going on in terms of actual demand.

# data[].attributes.subject
Thermometer sales - things like supply chain may create issues when there is a product backlog. This means it misses what's going on in terms of actual demand.

# data[].attributes.headline
Geographic location - ZIP code, preferablly

# data[].attributes.subject
Geographic location - ZIP code, preferablly

# data[].attributes.headline
How many do they have in stock vs what is out on the shelf

# data[].attributes.subject
How many do they have in stock vs what is out on the shelf

# data[].attributes.headline
If included as a HSA item - people may be trying to use up funds at the end of the year

# data[].attributes.subject
If included as a HSA item - people may be trying to use up funds at the end of the year

# data[].attributes.headline
Units - the actual tabs or the box unit - curation of the dataset; how frequently is it updated with new products, cleaned up (e.g. new products added or old products removed)

# data[].attributes.subject
Units - the actual tabs or the box unit - curation of the dataset; how frequently is it updated with new products, cleaned up (e.g. new products added or old products removed)

# data[].attributes.body
Do we limit to ingestibles or to things that could be used such as other first aid devices - such as thermometer, etc. Or other things to breathe well.

# data[].attributes.headline
Can you access naloxone OTC yet? If so, that would be a great use case for this data

# data[].attributes.subject
Can you access naloxone OTC yet? If so, that would be a great use case for this data

# data[].attributes.headline
OTC could help identify uninsured who may use medications more - or capture conditions that are not included in the hospital system since they are using it as a remedy given no insurance

# data[].attributes.subject
OTC could help identify uninsured who may use medications more - or capture conditions that are not included in the hospital system since they are using it as a remedy given no insurance

# data[].attributes.headline
We had this data but found it challenging to use because of the varied nature of how sales work

# data[].attributes.subject
We had this data but found it challenging to use because of the varied nature of how sales work

# data[].attributes.headline
Inability to follow up about about data anomalies

# data[].attributes.subject
Inability to follow up about about data anomalies

# data[].attributes.headline
Useful in both big events (e.g. Superbowl, large storm)

# data[].attributes.subject
Useful in both big events (e.g. Superbowl, large storm)

# data[].attributes.headline
Need a specified list of product sales to measure

# data[].attributes.subject
Need a specified list of product sales to measure

# data[].attributes.body
Antifebrile medications, thermometer sales, cold medications, COVID rapid tests, other rapid tests. Hydrocortisone creams. Kleenex.

# data[].attributes.headline
What is a data artifact vs an actual signal?

# data[].attributes.subject
What is a data artifact vs an actual signal?

# data[].attributes.headline
Sales on product may drive purchasing, not just symptoms

# data[].attributes.subject
Sales on product may drive purchasing, not just symptoms

# data[].attributes.body
Need the ability to know what is on sale to address potenital confounding

# data[].attributes.headline
Timeliness - some people self-treat so could show illness trends before they show up in the ED or hospital

# data[].attributes.subject
Timeliness - some people self-treat so could show illness trends before they show up in the ED or hospital

# data[].attributes.body
This includes COVID rapid tests