TUFTS CTSI team provides analytical support to stakeholders across Tufts Medical Center to meet their health services research and quality improvement data needs. This support includes data collection and management, develop databases, and identify study participants. Responsibilities:⦁ Involved in migration of EPIC Data to OMOP (Common Data Model).⦁ Supporting various research projects in their clinical data need and writing sql queries against Epic database for the specific research.⦁ Performed data extraction, cleaning, and transformation of EMR data to develop a prediction model for 30-day readmission and mortality in patients with heart failure. Extracted various data points like clinical data, transplantation data, mortality, hospital length of stay and various other data points needed for analysis.⦁ Performed data extraction, cleaning, and transformation of Patient EMR (Electronic medical record) data for investigating cases of PMR (Polymyalgia Rheumatica) after COVID vaccine within the TMC population.⦁ Research Data fields in EPIC data model to service stakeholder data request. Created various research reports using Epic Caboodle and Clarity databases.

Account Planning and Market Analytics team provides data-driven insight that enables the business to be more proactive in pursuing and closing new cross-business sales opportunities and renewals while maximizing the time of sellers to do what they do best …sell. Responsibilities:⦁ Implemented Customer Scorecard development to identify key potential customer using SAS and SQL tool.⦁ Implemented various attribution analysis report in power bi for ex: Win-Loss dashboard, Partner One Stop Shop etc.⦁ Optimizing the process and performance improvement for power Bi reports.⦁ Involved in D365 migration for new CRM Datawarehouse.⦁ Developed a forecasting model to predict Win rate.

OSUP Managed care team provide analytical support across OSU WEXNR medical center for bundle payment performance evaluation and reporting purpose.Responsibilities:⦁ Analyzing Bundle payment performance and report creation⦁ Use caboodle framework to fetch data from ETL warehouse

The CHSR DASC team provides analytical support to stakeholders across UK to meet their health services research and quality improvement data needs. This support includes data collection and management, extraction of data from clinical data management systems, survey development, program evaluation, study design, methodology, dashboard design, server support for datasets, and statistical analysis such as descriptive statistics describing the population of interest and/or a multivariate analysis. Responsibilities:⦁ Successfully implemented quality improvement measures on several healthcare projects resulting in better utilization of hospital resources by 12% and reduction of patient wait time by 10%.⦁ Successfully interpreted data to identify patterns and to draw conclusions to be further implemented by physicians on usage of drugs, patient care, and resource utilization.⦁ Created pivot tables, graphs, charts and built Tableau dashboards.⦁ Expert in understanding, documenting, and investigating front end to warehouse mapping of Electronic Health Record Systems like Allscripts Electronic Health Record Systems and Sunrise Clinical Manager.⦁ Worked simultaneously on multiple projects and efficiently handled different clients and followed AGILE and Sprint models.⦁ Involved in creating research reports to determine the relation between mechanical ventilation and Acute Kidney Injury (AKI).⦁ Implemented Post CABG research to compare the efficacy and outcome of different chemical, mechanical and non-preventative DVT/PE prophylactic measure in patients POST CABG.⦁ Created Visualization reports and dynamic dashboard for Markey Infusion Chair utilization (Cancer Branch) for various scenario like pre-post utilization, Monthly utilization by floor, Daily Gantt, Early morning appointments.⦁ Used REDCAP tool to set up survey for data collection of child physical activity before and after medical intervention and generating reports from underlying data.