Automatically identify loggable information for health monitoring and other important notes

[nehanims]

blocks #11

Process the audio transcript to try and identify important metrics like symptoms, diet, supplement and show the identified loggable metrics as a list to the user for their approval. Add the approved logs to a database (make sure to add the foreign key of the corresponding audio recording metadata to the logs whenever metrics are collected in this automated way instead of manual logging).

Try to craft some features up front. Also allow LLM to suggest new features to log over time based on the conversations.

Instruct the LLM to generate json output for each loggable item identified in the transcript.

To start with, identify the following recordable data:

• Diet
• Medication/supplement ingested
• Symptoms
• Student appointment
• Doctor appointment

After every interaction - whether it is voice note, llm chat or any other future mode of interaction - save the interaction in the object store. Metadata for every interaction should contain its timestamp.

After every interaction, Identify any important loggable information and present to the user to approve/edit/reject. When saving the metric, add a reference to the interaction from which it was extracted.

Provide a view to filter this logged information by date ranges.

Whenever the data needs to be extracted again, present an option to fetch "reference artifacts" i.e. the interaction from which the metric was collected.

Allow attaching links, uploading PDFs along with these artifacts.

[nehanims]

ChatGPT summarization

To build an effective system for logging important information for someone with a chronic illness, it's crucial to capture a comprehensive set of data categories daily. This helps monitor the condition, manage symptoms, and make informed decisions about treatment. Here is a synthesized list of key data categories to consider:

1. Symptoms and Health Status

• Pain Levels: Record the intensity and location of pain.
• Fatigue: Note the severity and duration of fatigue.
• Mood and Mental Health: Track feelings of depression, anxiety, or other mood changes.
• Sleep Quality: Document hours of sleep and any disturbances.

2. Vital Signs

• Blood Pressure: Measure systolic and diastolic pressure.
• Heart Rate: Record resting heart rate.
• Blood Glucose Levels: Essential for diabetes management.
• Weight: Monitor for any significant changes.
• Oxygen Saturation: Measure blood oxygen levels.

3. Medication and Treatment

• Medication Intake: Log the name, dosage, and timing of all medications.
• Side Effects: Note any adverse reactions to medications.
• Treatment Adherence: Ensure compliance with prescribed treatments.
• Therapies and Procedures: Document physical therapy, occupational therapy, and other treatments.

4. Diet and Nutrition

• Food Intake: Track meals, snacks, and beverages.
• Nutritional Content: Record macronutrients and any dietary restrictions.
• Hydration: Monitor daily water intake.

5. Physical Activity

• Exercise Routine: Log type, duration, and intensity of physical activities.
• Daily Movement: Track steps or general activity levels.

6. Medical Appointments and Tests

• Doctor Visits: Note dates, times, and key takeaways from medical appointments.
• Lab Results: Record results from blood tests, imaging, and other diagnostics.

7. Lifestyle Factors

• Smoking and Alcohol Use: Document any tobacco or alcohol consumption.
• Stress Levels: Track sources and intensity of stress.
• Social Interactions: Note significant social activities and their impact on well-being.
• Work or School Activities: Document major activities and any related stress or fatigue.

8. Environmental Factors

• Air Quality: Note any exposure to pollutants or allergens.
• Weather Conditions: Record weather conditions that might affect symptoms.

9. Disease-Specific Data

• Frequency and Severity of Symptoms: Log specifics related to the chronic illness.
• Flare-Ups or Remissions: Document periods of worsening or improvement.
• Specific Treatments: Detail treatment plans and any adjustments.

10. Additional Considerations

• Emergency Visits: Note date, time, and reason for emergency visits.
• Hospitalizations: Record dates, reasons, and procedures performed.
• Allergies: Document allergens and reactions.
• Triggers: Identify factors that worsen symptoms.

Data Format and Storage

• User-Friendly Interface: Consider using a mobile app or online platform for easy data entry.
• Data Security: Ensure data is securely stored and protected.
• Data Visualization: Incorporate graphs and charts to identify trends and patterns easily.

Regularly reviewing the collected data with healthcare providers can help optimize treatment plans and improve the overall management of the chronic illness.

[nehanims]

Claude Summarization:

Comprehensive Data Categories for Chronic Illness Tracking

1. Personal Information

• Name, age, gender
• Contact information
• Emergency contact details

2. Core Health Metrics

Vital Signs

• Blood pressure
• Heart rate
• Respiratory rate
• Temperature
• Oxygen saturation (if applicable)
• Weight

Symptoms

• Pain levels (location, intensity, duration)
• Fatigue levels
• Nausea, dizziness, or other discomforts
• Frequency and severity of specific symptoms related to the illness
• Any new or unusual symptoms

Medication

• Medication name and dosage
• Time of administration
• Effectiveness
• Side effects experienced
• Any missed doses

Sleep

• Hours of sleep
• Sleep quality (e.g., poor, fair, good)
• Sleep schedule (bedtime, wake-up time)
• Sleep disturbances
• Sleep aids used

3. Lifestyle Factors

Diet and Nutrition

• Food intake (types, quantities, meals, snacks)
• Nutritional supplements
• Fluid intake
• Caloric intake
• Specific dietary restrictions or preferences
• Any dietary triggers or reactions

Physical Activity

• Type of exercise or activity
• Duration and intensity
• How they felt during and after activity
• Daily movement (e.g., step count)

Mental and Emotional Health

• Mood tracking (e.g., happy, sad, anxious)
• Stress levels (scale or qualitative assessment)
• Stress management techniques used
• Cognitive function (e.g., focus, memory)

4. Illness-Specific Data

• Disease-specific symptoms and their frequency/severity
• Flare-ups or remissions
• Treatment plans and adjustments
• Therapy sessions (if applicable)

5. Lab Results and Tests

• Relevant lab values (e.g., blood glucose, cholesterol)
• Dates of tests
• Types of tests performed
• Results and interpretations

6. Environmental Factors

• Identification of factors that worsen symptoms
• Allergens and reactions
• Exposure to potential irritants or pollutants
• Weather conditions
• Air quality (if relevant to the illness)

7. Medical History and Appointments

• Chronic conditions and diagnoses
• Past surgeries or procedures
• Allergies
• Upcoming or completed medical appointments
• Healthcare provider details
• Notes or outcomes from visits
• New instructions from healthcare providers

8. Treatments and Therapies

• Any treatments received (e.g., physical therapy, acupuncture)
• Effectiveness of treatments
• Changes to treatment plans

9. Emergency Information

• Emergency visits (date, time, reason)
• Hospitalizations (dates, reasons, procedures)

10. Lifestyle and Daily Activities

• Work or school activities
• Social interactions
• Hobbies and leisure activities

11. Additional Notes

• General observations or concerns
• Daily reflections
• Any significant events or changes

Data Management Considerations

• User-friendly interface (e.g., mobile app or online platform)
• Data security and protection measures
• Data visualization (graphs and charts for trend identification)
• Regular review of data with healthcare providers

Disclaimer: This list is comprehensive but should be tailored to the specific chronic illness in consultation with healthcare professionals. The goal is to collect data that provides valuable insights into the illness and its management while avoiding unnecessary burden on the patient.

[nehanims]

Prompt:

You are a personal assistant to a person suffering from a chronic illness. To keep track of their health and the effects of their diet, activity-level, medication and supplementation they are tracking various metrics like physical or neurological symptoms like memory issues, concentration probelms, tinnitus, chest pain, headache, cough, sore throat, fatigure PEM, etc (get a full list from somewhere and allow tool use). They are also tracking their dietary, medication and supplement intake. They also would like to keep track of other therapeutic interventions like Red light therapy, fasting, breathing exercises, cold water therapy. They would like to keep track of each of these metrics as separate entities in tables for future trend analysis to see if their diet/activities/therapeutic interventions affect their symptoms. You are a helpful attentive assistant that helps identify specific entities like medications, symptoms, or medical procedures in the following text input from the person, and return each identified class as separate JSON objects with the attributes: 1) type of entity being referred to: diet/medications/symptoms/medical procedures/therapeutic intervention/activity (maybe provide a tool to detect if something is an entity worth consideration?), 2) summary of entity: a brief summary of the entity identified in the text 3) timestamp provided to you(provide a timestamp from the voice note)

Text to parse:{input-text}