The problem Healthcare Harmony solves

We aim to tackle various inefficiencies of the HealthCare System.
Use case for target user-

Patients:
Problem: Difficulty accessing and managing health data like prescription, test reports.
Solution: Secure portal which provides a crucial hub for all clinical information (medicines, lab results, hypersensitive reactions).

Doctors:
Problem: Incomplete view of patients' medical condition. Repetitive exams and delays in analysis due to lack of complete medical records.
Solution: Healthcare Harmony gives a unified view of a patient's medical history from diverse institutions. Doctors can make informed diagnoses quicker, lowering redundant checks..

Hospitals and Clinics:
Problem: Data mismanagement in departments and programs. It is difficult to coordinate with other organisations.
Solution: Healthcare Networks streamline the flow of data within an organisation and facilitate secure Health Information Exchange with other healthcare providers, improving operational efficiency.

Departments of Public Health:
Problem: Limited access to comprehensive health data for population health research. Disease trends and incidence are difficult to monitor due to fragmented data.
Solution: Healthcare Harmony provides anonymized and aggregated data to public health agencies. This allows for tracking of disease trends, close monitoring of outbreaks, and targeted public health interventions.

Concluding, key aspects of our project-

Faster diagnoses: Doctors get complete picture, reducing unnecessary tests, delay.

Improved care coordination: Seamless Health Information Exchange b/w institutions.

Reduced errors: Unified data minimises the risk of medication errors and misdiagnoses.

Empowered patients: Patients take a more active role in their health journey with easy access to their data.

Public health improvements: Data analysis allows for better disease prevention strategies.

Challenges we ran into

Dataset-
Public health data are inconsistent, missing standards, and full of errors.
Solution: We use preprocessing techniques such as data cleaning, imputation, and outlier handling to transform noisy data sets into valuable products. This ensures high quality data for accurate research.

Anonymization-
Maintaining anonymity of patients’ data for privacy, still preserving its utility for the research.
Solution: We examine data quality checks and cleaning techniques to ensure integrity. For privacy and anonymity we are investigating advanced techniques like blockchain, that can ensure privacy as future prospects.

User capture-
Tough for widespread adoption of new platforms within the healthcare system.
Solution: We design a user-friendly system with nice ui/ux. Guides and training programs will be provided to healthcare professionals and patients to capture more users.

Scalability and performance-
As the platform matures and integrates data from multiple healthcare organisations, managing large volumes of data becomes increasingly important to maintain productivity.
Solution: for database Optimization: We optimise the selected database (PostgreSQL) for healthcare data by applying appropriate indexing and query optimization techniques.