Patient-centric health-care data processing using streams and asynchronous technology
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03 ene 2018
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Categoría del artículo: Research-Article
Publicado en línea: 03 ene 2018
Páginas: 1 - 18
DOI: https://doi.org/10.21307/ijssis-2018-003
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© 2018 Kenneth Mbuthia et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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j_ijssis-2018-003_tab_006
| Name | Pharmacy_counts |
|---|---|
| Fields | Name (text) (primary key) events (text) (primary key) count (int) date (text) (primary key, clustering column). |
| Use | This is useful for viewing interactions that pharmacies have with patients through the app over time. It is good for identifying trends in interaction between pharmacies and their customers, e.g. if the number of appointments decrease, you can reach out to users to remind them they can do so through the app. |
| Comments |
j_ijssis-2018-003_tab_005
| Name | Appointment_count |
|---|---|
| Fields | Status (text) (primary key) count (int) date (text) (primary key, clustering column). |
| Use | This is useful for horizontal and vertical comparisons of appointment data. Useful for pie/line charts showing comparison of appointments booked through the app. It is also useful for targeting pharmacies that have a high number of mobile app customers to reward them or look at areas with low app usage and increase marketing there. |
| Comments | Potentially other uses besides marketing. |
j_ijssis-2018-003_tab_008
| Name | Remedy_count |
|---|---|
| Fields | Dose_type (text) (primary key) count (int) date (text) (primary key, clustering column). |
| Use | This is useful for horizontal and vertical comparisons of remedy data. Can be used in line or bar graph to show the comparison of different types of drugs users’ record in the app. This info can be used to create marketing segments/targeted marketing, e.g. if there is low usage of people recording injections, you can create a marketing campaign to attract this target group to the app. |
| Comments | Potentially other uses besides marketing. |
j_ijssis-2018-003_tab_007
| Name | Pharmacy_appointments |
|---|---|
| Fields | Name (text) (primary key) city (text) (primary key) app_date (text) (primary key, clustering column) totals (object) details (object). |
| Use | This is useful for viewing which pharmacies are actively receiving appointments through the mobile app and which are not. This info can therefore be used to incentivize pharmacies to keep using the app to organize or communicate with patients. |
| Comments |
j_ijssis-2018-003_tab_002
| Name | User_locations |
|---|---|
| Fields | Gender (text) (primary key) city (text) (primary key) date_created (text) (primary key, clustering column) last_login (text) (primary key, clustering column) postcode (text) data (object). |
| Use | This is useful for viewing user activity by location. You can view locations of active users within a given time period and determine areas that have high or low usage for marketing purposes. Adding a heatmap layer will also bring out high- and low-usage hotspots. |
| Comments | Created index on postcode as well. |
j_ijssis-2018-003_tab_001
| Name | Resource_counts |
|---|---|
| Fields | Type (text) (primary key) date (text) (primary key, clustering column) count (int). |
| Use | This is useful for counting the number of pharmacies, services, appointments, users, etc. |
| Comments | This table is not suitable for graphing historical data points, but is useful for showing state at specific points in time, e.g. summation that the widgets in the portal need. |
j_ijssis-2018-003_tab_004
| Name | Adherence_drug |
|---|---|
| Fields | Medicine_name (text) (primary key) totals (object) date (text) (primary key, clustering column). |
| Use | This is useful for determining which drugs get low or high adherence. Allows you to profile the performance of the app with respect to different drugs. For example: Does mobile app help ‘drug x’ patients more than ‘drug y’, then investigate the cause from there. |
| Comments | Will need to stream and map remedy ids to medicine name within this cruncher (note: for viewing all drugs within the time period, use adherence_count with “status IN” clause) |
j_ijssis-2018-003_tab_003
| Name | Adherence_count |
|---|---|
| Fields | Status (text) (primary key) count (int) date (text) (primary key, clustering column). |
| Use | This is useful for horizontal and vertical comparisons of adherence data. Useful for pie/line charts showing the percentage of adherence status, or line graph for how the taken status has been growing. |
| Comments | Helpful when identifying fluctuation in adherence so as to investigate further. |