Data & Analytics in HealthCare
Data & Analytics Adoption Model in HealthCare for Access, Cost, Quality (ACQ)
- Three stages of data management via EDW – 1) data collection 2) data sharing / access and 3) data analytics
- Bulk of Data Collection are done via electronic health records (EMR/EHR) and health information exchanges (HIE/HIX)
- Data & Analytics is playing a big role in Health System Quality improvement and cost reduction efforts
- Healthcare Analytics Adoption Model borrows & leverage recommendations from HIMSS EMR Model, Health & Human Services (HHS), Food & Drugs Administration (FDA rules for Clinical Trials) and Center for Medicare & Medicaid (CMS)
- The Adoption Model may include – evaluating the industry’s adoption of analytics, roadmap for measure progress toward analytics adoption and evaluating vendor products for improving the quality of care while lowering costs and enhancing clinician and patient satisfaction
8 Stages of the Data & Analytics Adoption Model
- Adoption Stage 1 – Enterprise Data Warehouse (EDW) using Physical or Virtual Servers
- Adoption Stage 2 – Registration & Billing System including Patient Registries via Personal Portal
- Adoption Stage 3 – Electronic Health Record &Electronic Prescription System (EMR & eRX) for clinical observations and lab results
- Adoption Stage 4 – Management & Internal Reporting Tool / Dashboard
- Adoption Stage 5 – Statutory& External Reporting Tool / Dashboard i.e. Meaningful Use Reporting
- Adoption Stage 6 – Fraud & Abuse reduction using Claims Data
- Adoption Stage 7 – Population Health Management (PHM) & Care Management Analytics
- Adoption Stage 8 – Predictive Analytics (PA) leveraging PHM, CM, UM Data for Preventive Care to Cost Curve and Patient Care / Patient Satisfaction
Top use cases for data and analytics for Health IT organization
- Adoption Analytics – Clinical Workflows & Applications
- Claims Analytics – Fraud & Abuse
- Cost Analytics – Planning & Control
- Customer insight Analytics – Customer Care
- Discovery/search Analytics – Clinical Trials
- Meaningful Use Analytics – Positive Outcome
- Operations Analytics – Customer Service
- Predictive Analytics – Bend the Cost Curve
- Risk and Compliance Analytics – PHI & HIPAA
How much data and analytics contribute to Health organization’s decision?
- See the future
- Drive revenue growth or Bend the Cost Curve
- Clinical Workflows & Software Applications
- Customer Care
- Fraud & Abuse
- Guide future strategy
- PHI & HIPAA Compliance
- Planning & Control
- Product research and development
- Product research and development – Clinical Trials for Drugs discovery & approval for medical equipment by FDA
Challenges in Health organization in adopting data and analytics strategy
- Budget & Priority
- Information Explosion
- Inoperability of Data
- Managing Data Vs Analyzing Data
- PHI / HIPAA Challenge
- Quality of Data – Data duplication or Data Integrity
- Varied Application System within Health System
Metrics or benefits /business outcomes for data and analytics in HealthCare
- Cost Curve
- Ethical intent
- Go-to-Market for Drugs
- Legal compliance for PHI (Privacy) & HIPAA
- Population Health Management (PHM)
Proof of Data & Analytics working for Health Organization
- A code of ethics around data and analytics
- C-level support
- Claims Dashboard
- HEDIS STAR Rating
- Meaningful Use Metrics
- Pain Management Dashboard
- Prescription Dashboard for Controlled Substances
- Tracking customer views
- Transparency on what customer data is being used
Posted on June 29, 2015 | Categories: Analytics, Data Analytics, Data Mining, IT Services, Tech Cusp, TechCusp.com | Posted by: admin
Data Mining v/s Data Analytics – which is more Suitable?
The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, a repository of data gathered from various sources, including corporate databases, summarized information from internal systems, and data from external sources. Analysis of the data includes simple query and reporting, statistical analysis, more complex multidimensional analysis, and data mining.
Data Analytics and Data Mining are a subset of Business Intelligence (BI), which also incorporates data warehousing, database management systems, and Online Analytical Processing (OLAP).
Let us first talk about what Data Mining can deliver? And how will it be benefit your organization?
Data mining involves collecting, processing, storing and analyzing data in order to discover (and extract) new information from it. There are numerous benefits of data mining, but to understand them fully, you have to have some basic knowledge of what data mining actually is.
In the following areas, we believe Data Mining can benefit your organization:
- In finance and banking, data mining is used to create accurate risk models for loans and mortgages. They are also very helpful when detecting fraudulent transactions.
- In Marketing, data mining techniques are used to improve conversions, increase customer satisfaction and created targeted advertising campaigns.
- Retail stores use customer shopping habits/details to optimize the layout of their stores in order to improve customer experience and increase profits.
- Tax governing bodies use data mining techniques to detect fraudulent transactions and single out suspicious tax returns or other business documents.
- In Manufacturing, data discovery is used to improve product safety, usability and comfort.
Previously, we talked Data Mining, now we need to know about Data Analytics and how it can benefit your organization?
Data Analytics is about applying a mechanical or algorithmic process to derive the insights for example running through various data sets looking for meaningful correlations between them. Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. It is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify or disprove existing models or theories.
Techcusp believes the following are the benefits DA can deliver for your Organization:
- Cost Reduction
- Faster, better decision making
- New Products & Services
- Ready for Prime Time
Now we can surely say which is more suitable Data Mining or Data Analytics.
Techcusp.com has deep understanding of your growing business and operational needs. Our Data Mining & Data Analytics Engineers and Consultants are on stand-by to help you deliver your IT vision & Projects. Reach out to us for our seasoned & domain rich IT Consultants; Developers & Software Engineers for short term and long term projects.
To know more about our offerings feel free to reach out to us at firstname.lastname@example.org or
Manger Sales – IT Consulting & Technology Services
Phone: +1 646.644.3049 / 201.258.4704 / 201.589.5962
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Tags: Consulting Services, Data Analytics, Data Mining, IT Services, Outsourcing services