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Category Archives: Data Scientist

Data & Analytics in HealthCare

Posted on July 26, 2016 | Categories: Big Data, Claims, Clinical Trials, CMS, Data Analytics, Data Mining, Data Scientist, Database | Posted by: admin

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?

  • Differentiate
  • 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
  • Sales/Marketing

 

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
  • Interoperability
  • Legal compliance for PHI (Privacy) & HIPAA
  • Population Health Management (PHM)
  • Transparency

 

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

 

 

 

 

Data Scientist – By Techcusp.com

Posted on June 5, 2015 | Categories: Data Scientist, IT Services | Posted by: admin

Data Scientist – By Techcusp.com

 

We are IT Services & Software Development firm based out of Jersey City, NJ. Our Data Scientists provides exposure to help drive sales, product, marketing and audience development. Reach out to us for our seasoned & domain rich Consultants for short term and long term projects.

 

 

Key Responsibilities Required:

  • Analyzing, processing, evaluating and documenting large data sets.
  • Identify/develop appropriate machine learning /data mining/text mining techniques to uncover the value of the data.
  • Designing data structure and data storage schemes for efficient data manipulation and information retrieval.
  • Developing tools for data processing and information retrieval.
  • Developing data driven models to quantify the value of the given data set.
  • Validating score performance.
  • Applying, modifying and inventing algorithms to solve challenging business problems.
  • Documenting and presenting model process and model performance.
  • Ability to present complex information in an understandable and compelling manner.

 

Preferred Qualifications Required:

  • Proficient in at least one Python, R, Java, C++ or C.
  • Robust Knowledge and experience with statistical methods experience using SAS, SPSS, or other statistical packages a plus.
  • Experience working with noSQL databases, XML, Xquery – MarkLogic a plus.
  • Experience working with SQL, SQL Server, SSIS.
  • Ability to work independently on development of complex models with extremely large and complex data structures.
  • Familiar with Tableau and other BI platforms a plus.

 

Why Techcusp.com?

  • Latest & Greatest IT Solutions.
  • Guaranteed Delivery.
  • Onshore, Onsite & Offshore Team.
  • Competitive Pricing.

 

Contact – Careers with Techcusp.com or

 

Debanuj Sengupta

Manger Sales – IT Consulting & Technology Services

debanuj@Techcusp.com

Phone: +1 646.644.3049 / 201.258.4704 / 201.589.5962

www.TechCusp.com

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