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System and method for patients to self adjust treatments

IP.com Disclosure Number: IPCOM000247999D
Publication Date: 2016-Oct-14

Publishing Venue

The IP.com Prior Art Database

Abstract

We present in this paper a system for patient medical treatment efficiency

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This is the abbreviated version, containing approximately 25% of the total text.

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System and method for patients to self adjust treatments

We know that Patients under long-term medical prescriptions have to respect a predetermined prescribed protocol (same for all patients). Drugs have a specific profile to deliver their effects and patients offer different reactions to drugs.

    Several factors can influence the drug efficiency and the comfort zone feeling can only by defined by the patient itself. No flexibility is allowed and no big data analysis is available about the efficient comfort zone for a given drug.

The system tackles the following problem:
- How to maximize the patients' medical treatment efficiency (when the

drug produces its best effect with minimal negative impacts) taking into account the patients' feedback

    - How to use patient's experience in addition to doctor's experience
It redefines the doctor-patient relationship by moving from a defined prescription to a variable one that is auto-adjusted by the patient who is assisted by an agile and cognitive logic taking into account all available elements include systematic patient's feedback.

The consequences are:

    - the increase of the treatment adjustment frequency,
- the increase of the patient's autonomy,
- the possibility for the doctor to prescribe/change a medication within an authorized range (e.g. 3 +- 1 pill / day) at any time,

    - the enrichment of the disease corpus of knowledge with the systematic anonymous patient's feedback

    - the real-time doctor reaction in case of anomaly using the patient's feedback with multi factor system control (or the synthesis of factors)

An ideal current system could be:


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By current, we mean:

    - Disease profile: all medical information about each disease - Molecule profile: mainly pharmaceutical data about their products - Literature profile: all other information related to health and illnesses - Disease corpus: collection of the above 3 - Medical interaction: known effects when 2 drugs are combined in body - Biologic dosage: all analysis about body elements (blood, DNA, urine, skin, spinal cord…)

    - Patient profile: all shared information about the patient (age, sex, race, leaving place, historical illnesses, parent's history, working conditions, sports, allergies, surgery…) or in other words the patient medical file

    - Symptoms: Patient self assessment (I feel well, not well; I feel pain or not), all personal IOT(Internet Of Things) device inputs (accelerometer, temperature, strength, any other measurement such as sugar level in blood…) without any

limitation as technology invents new stuff…

    - Illness stage: level set up by the doctor based on his experience - Medical Delivery: drug absorption (pharmaceutical form, quantity, time) (a smart drug delivery box helps the patient capture the info)

    - Treatment: the prescription the doctor delivers to the patient - Pharmacokinectics: determines the fate of substances administered externally to a living organism
We come up with a feedback piece that all...