OK, Jotting down bits on a notepad while staring over the Panamanian countryside slurping high quality coffee brewed in the most hideous way ever invented (Los perculatores hacer el cafe malo!), I spent a good amount of time figuring how I was going to pull together database generation for a fairly simple proof of concept that might pass clinical muster. I settled on Hypertension. I figured I would take the following elements into consideration:
- Height
- Weight
- Calculated BMI (possibly tested body fat)
- Age
- Gender
- Exercise and activity levels/types
- Diet factors/eating habits
- The usual lifestyle factors of alcohol/caffine/nicotine
- Medications
- Systolic
- Diastolic
- Heart Rate
- Respiration Rate
- O2 saturation
- Genetic factors
- geopolitical factors
Naturally the above list needs to be compared against a real risk-factor screening list, as I had no access to such at the time.
So, the idea is this:
- Generate baseline vital statistics for a hypertension risk patient.
- Randomly determine a compliance factor for that patient, meaning how well the person is going to stick to any given regimen.
- Factor the above into how well the patient is going to be monitored, which will determine how frequent/regular the generated patient encounters will be.
- Use flow-chart logic to determine interventions and outcomes as each “visit” is generated with random statistically relevant variations.
The “constants” that affect the outcomes are in a configurable list so that if you decide that eating beef, smoking cigars and drinking sherry are a sure cure for hypertension, you could skew the data to that effect
I have everything in place to do the above, meaning create the notes with appropriate text and empirical data points in the vitals, medications etc…, with the exception of the range of factors that determine a HPB patient, the logic that says what interventions/regimens are prescribed, and the co-factor and recombient effects.
I would like assistance with the logic flow and deterministic factors of this, as well as determining the relevance of interventions, contraindicated events etc…