07/19/2023
👩⚕️Tech Solutions to Enhance Cancer Screenings in Rural Communities 👩⚕️
We recently consulted with a cancer screening organization in Southeast Asia. During a quick call we mapped out the end-to-end patient journey and then brainstormed potential solutions to address some of their organizational pains. We put together a product vision board which is a simple, high-level birds eye-view of the organization vision, the current challenge(s), and potential solutions to address those challenges.
VISION
The organization's vision was founded on a simple premise: they believed early detection leads to early treatment and that everyone is entitled to free cancer screenings.
CHALLENGE
The organization faced unique challenges providing cancer screenings in rural communities:
1. Data Entry
- The rural communities were located in areas with no wifi and the communities themselves lacked familiarity with basic technology.
- The staff resorted to filling out paperwork by hand, scanned into a PDF, and uploaded to Google Drive .😲
2. Legacy Data
- They had thousands of patient records stored from previous years.
- The patient records were in multiple languages.
3. Impact Tracking
- The patient data wasn't in a format they could easily track down the line as patients went to other healthcare providers for treatment.
SOLUTION
We identified 3.5 potential solutions to address the organization's different needs at different phases.
1. Tablet Application
- Create a database to store patient data. This would not only make it easier to retrieve data, but standardized how data was being entered in the first place. (Not to mention it would be more secure and better protect patient privacy).
- A tablet application would minimize fat fi*****ng (as opposed to a mobile application which might be too small for reliable data entry.
2. Data Migration
- Convert the unstructured data in PDF's into structured data that could be stored into a database.
- We recommended they use AWS Textract or AWS Comprehend Medical to extract the text from the PDFs and if needed using AWS TranslateText to translate the text. Once the text was extracted, it could be easily stored into the database of their choosing.
3. Data Integration
- The organization wanted to see what happened with the patient's treatment after their screening which they had with another healthcare provider.
- We recommended they either create an API that other healthcare providers could use or find out the technology solutions they were using and see if they had an API that they could integrate into their own platform.
3.5 ML Models
- Lastly, we recommended they also experiment with ML models that might enhance not only screenings but potential diagnoses of certain cancers.
