Healthcare Analytics Consulting

What we do:

• Assess organizational requirements to maximize benefits from data analysis
• Formulate comprehensive health analytics blueprint
• Formulate data analytics strategy, outline project roadmap for execution
• Contribute to your organization throughout project development, execution, and advancement

We take over:

• Custom healthcare analytics solutions require needs assessment
• Choosing a Healthcare Data Analytics Platform & Tech Stack for optimal insights
• Secure, compliant system implementation for enhanced app analytics development
• Cloud analytics solution support, upkeep, and advancement provided upon request

Analyze therapy irregularities and patterns.

Sample reports:

• Demographic variables shape diverse results across age, income, and lifestyle groups
• Internal factors of a healthcare organization, such as unique physicians, treatments, and facilities, influence the diverse results observed

Data sources:

• EHR / EMR
• ADT
• Multiple department-specific systems (Cardiology, Dentistry, Neurology): Streamlined for efficiency
• Disease management/population health management

For continuous patient health surveillance, identifying anomalies, assessing treatment plan effectiveness, and promptly recognizing potential complication signs, regular monitoring is essential.

Sample reports:

• Diabetes: Monitoring Blood Glucose Levels is Crucial
• COPD patients: Oxygen saturation fluctuations to note
• Trend analysis of patient's nutritional status, hydration levels, body temperature, weight fluctuations, and blood pressure readings

Mobile patient apps and portals for:

• Effective Chronic Condition Care
• Appointment scheduling
• Track Medication Consumption
• Post-surgery Recovery Assistance Available

Determining costs associated with specific health conditions or patient groups involves careful analysis.

Sample reports:

• Treatment cost variations per condition: Specific expenditures analyzed
• Analysis of patient outcomes and associated costs over specific durations, providing valuable insights on the effects of care process modifications

Data sources:

• EHR / EMR
• LIS.
• RIS
• Specific departmental software solutions
• Accounting system / ERP

Enhance financial planning & optimization for future prosperity.

Sample reports:

• Cash Flow from RCM Data Estimated
• Actual cash flow
• Identify overdue payments from particular debtors (e.g., departments, institutions, illness categories)
• Investment Return on Types: New Facilities & Medical Equipment (e.g., CT/MRI) Determine ROI Efficiently

Data sources:

• ERP or FMS
• Streamlined Revenue Cycle Operations

Calculate and monitor key performance indicators (KPIs) for effective management of laboratories, facilities, and equipment. Pinpoint process inefficiencies and their root causes, forecast service and asset demand.

Sample reports:

• Inventory turnover rate
• Nurse-to-patient ratio
• Test Execution vs Actual Tests: Distinction Explained
• Supplier Efficiency Rating
• Weekly staff requirements due soon

Data sources:

• EHR
• HR software
• LIMS/LIS
• Software for practice management
• Streamlined inventory control: Systems
• SCM systems
• Efficient Facility Management System Usage

Monitoring patient satisfaction, detecting service and care shortcomings, and executing necessary enhancements.

Sample reports:

• Patient Portal Usage Rate
• Patient dropout rate
• Enhancing Activity Efficiency in Engagements

Data sources:

• Patient portal
• Telemedicine app
• Patient surveys

Enhancing clinical decisions via machine learning (ML) and artificial intelligence (AI) outcomes.

Possible output:

• AI-driven personalized drug dose recommendations enhance patient care
• Custom treatment plan
• Warns of potential health hazards and complexities

Data sources:

• EHR
• LIS
• RIS
• Wearable devices

Analyze enrollment trends, adherence to protocols, discern patterns within clinical trial results, forecast workforce and intellectual property requirements, perform post-market surveillance for continuous improvement.

Sample reports:

• Study Startup Trial Site Overview: Patient Demographics, Disease Prevalence, Key Risk Indicators
• Trial evaluation includes dropout rates and final patient visits
• Pharmacokinetics metrics: Cmax & Tmax

Data sources:

• CTMS + EDC
• LIMS/LIS
• IRT/RTSM software
• EHR/EMR + PACS
• RPM software

Transparently assessing performance for clarity.

Sample reports:

• Optimizing bed usage efficiency
• Efficient equipment usage rates
• Efficient use of operating rooms crucial
• Medication use
• Streamlined Human Resources Analytics: Encompassing employee qualifications, certifications, hiring processes, and beyond

Data sources:

• PMS
• EHR
• LIS
• RIS
• Efficient Workforce Management System
• Departmental specialized software

• Healthcare Data Warehouse and Mart Design: Organizing health data for analytical queries and reports, enhancing data accessibility and insights in the healthcare sector
• Secure PHI Storage Essential
• Centralized data storage combines EHR/EMR, ERP, HR, public medical databases, and R&D results, streamlining access to integrated information sources

• Streamlined analytics for staff scheduling, facility upkeep, and claim administration enhance efficiency
• Analytics encompasses patient segmentation, journey analysis, and optimizing treatment plans
• Financials: Fraud Detection, Risk Management
• Healthcare Staff Performance Surveillance
• Pharmaceutical Data Analytics specializes in optimizing production cycles and analyzing clinical trial data

• Operational dashboards: Real-time analysis of hospital admission rates, EMR/EHR data, and more for self-service
• Interactive strategic dashboards encompass key performance metrics, patient trends, and hospital performance evaluation

• Gathering and preserving Electronic Health Record (EHR), Electronic Medical Record (EMR), medical device, app, portal, and various patient data
• Real-Time Medical Device Data Analysis
• Remote patient monitoring identifies trends and patterns in patients' health status, prompting medical intervention when necessary
• Custom Care Plan Recommendations

• Optimizing healthcare supply chains involves implementing machine learning for demand forecasting, mitigating supplier risks, among other strategies
• ML-driven disease management: Predicting patient readmissions, validating diagnoses, and more
• Streamlining health insurance operations involves optimizing healthcare plans, detecting suspicious claims, and mitigating high-value losses

• Establishing diagnosis
• 3D VR education enhances interactive learning for healthcare professionals and students
• AI-driven virtual health aides offer customized advice and suggestions, leveraging patient's medical records, unique requirements, et al