Functional Responsibilities
• Consult with team, technology partners, and key internal and external stakeholders to determine interface and supporting application requirements
• Support the design, development, deployment, and operation of an architectural data model and associated processes which supports the detection and prevention of fraud in patient medical systems (including e-prescription applications)
• Coordinate the successful design, development, deployment and implementation of automated systems for the real-time collection and integration of detailed medical events at all staged of patient care (including the pharmaceutical reimbursement program)
• Ensure that all applications, databases, and hardware are performing within specifications established with IT service cards
• Design, develop, and deploy a set of eHealth real-time services that perform advanced e-prescription clinical capabilities:
dynamic dosing evaluation including disease-state, gender, age, and weight
detection of drug-disease contraindications
detection of drug-drug contraindications
• Identify, develop, and deploy a technical solution that prevents duplicative reimbursements for pharmaceuticals for the same or similar therapeutic classes for the same patient within a specified time period
• Support the integration and use of the state register of medicines in eHealth application and reporting systems
Deliverables:
• Processes and architectural model of fraud prevention capabilities in reimbursement program
• Programs, models, interfaces, scripts, and operational documentation supporting the proactive evaluation of fraud detection and prevention capabilities
• Definition and utilization of data structures for identifying medical products interactions, undesirable effect and appropriateness of prescribed medical products to the diagnosis provided for inclusion in the Centralized Data Base
• UAT plan approved by NHSU, Final documents – UAT results approved by NHSU
Required Qualifications
• Healthcare technology experience is preferred
• Advanced knowledge of SQL queries, stored procedures, triggers, indexes, data types, table structures, and database design principles
• Experience with Python/R is preferred
• Knowledge of instruments for data visualization (Power BI, Tableau, or analogs) will be an advantage
• Experience in different versions of DB (POSTGRESQL/MONGODB) will be an advantage
• Advanced level of English
Management Sciences for Health provides with:
• Location: NHSU office, Pochaynaya metro station
• Salary level: by agreement
• Registration form of work- FOP
• Official contract for a year
The job ad is no longer active
Job unpublished on
19 June 2020
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