Electronic Health Records

The same as ID 108(KDI Project). A Medical Data Solution for hospitals and governments. They are primary using the software solution parts developed by Big Data International (https://www.bigdatainternational.com).

Type of content: Assets
Type of asset:
Use case
Application
Big data potential
Yes
Policy domains: Health
Phase in the policy cycle:
Policy Design and Analysis
Open license availability
No
Ease of use
Low
Tags: Cloud computing Real time information
Addresses:
SWOT Analysis for
Electronic Health Records
Helpful Harmful
Internal
Strengths• Genome Processing and DNA Sequencing: There is exponential growth occurring in the genomics sequencing market, as evidenced by increases in data volume produced by DNA sequencers and in the number of individuals being sequenced. MapR provides efficient storage and compute in a single platform, is well suited for storing large volumes of sequencing data at a lower cost, while enabling efficient data processing with minimal downtime.
• Personalized treatment planning is a way to customize treatment for a patient to continuously monitor the effects of medication. Providing real-time access, at both the summary and detailed level when it comes to patient data making treatment decisions easy to adjust in a timely manner.
• Assisted Diagnosis: Being able to access a broad combination of knowledge across multiple data sources aids in the accuracy of diagnosing patient conditions. The Platform can allow for predictive modelling and machine learning to be performed on large sample sizes and uncover the nuances that couldn’t be previously uncovered.
• Fraud Detection: The Platform uses anomaly detection to detect these incidents in real time and alert providers to investigate them before payment is made.
• Monitor Patient Vital Signs: Helps in collecting the very fast growing data and stream it in real-time for actionable alerts that can help in detecting changes. Improved algorithms can be built that improve the likelihood of knowing when a particular patient might have an emergency and allow for effective interventions.
• MapR provides efficient storage and compute in a single platform, is well suited for storing large volumes of sequencing data at a lower cost, while enabling efficient data processing with minimal downtime. This will accelerate the development of clinical applications, including drug re-targeting and diagnostic testing.
Weaknesses• Low ease of use
• Training personnel
• Data security patient’s privacy
• Lack of system Integration: Clinical, administrative, and financial systems are not linked, and as a result, many healthcare institutions are not yet maximizing their IT potential
• Slow IT Adoption: Traditionally, healthcare has been slow to adopt IT and has lagged significantly behind other industries in the use of IT.
External
Opportunities• Healthcare organizations need to be able to detect fraud based on analysis of anomalies in billing data, procedural benchmark data or patient records.
• Reduce healthcare spending
• Improving patient care and increasing efficiency: Unstructured data forms close to 80% of information in the healthcare industry and is growing exponentially. Getting access to this unstructured data (such as output from medical devices, doctor’s notes, lab results, imaging reports, medical correspondence, clinical data, and financial data) is an invaluable resource for improving patient care and increasing efficiency.
Threats• Lack of system Integration: Clinical, administrative, and financial systems are not linked, and as a result, many healthcare institutions are not yet maximizing their IT potential
• Slow IT Adoption: Traditionally, healthcare has been slow to adopt IT and has lagged significantly behind other industries in the use of IT.
• Economic and medical challenges
• Data protection
• Cyber-attack
• Rapid changes in technology and IT systems
• State deregulations

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