Healthcare data analytics services

From wearable-collected vitals to daily symptom logs, Innowise’s apps can dissect a wide range of PGHD and spot connections between them. With these insights, providers understand treatment progress better, identify early warning signs, and measure care adherence.

• Activity trends by patient or patient group
• Engagement drop-off points
• Remote patient monitoring alerts

By analyzing CTs, MRIs, ultrasounds, and lab tests, our software reveals clinical insights that support accurate decisions across healthcare organizations. Based on imaging and lab data, you can detect care patterns, validate diagnoses, and track disease evolution in real time.

• Diagnostic results accuracy trends
• Imaging turnaround times
• Lab test quality analytics

With years in healthcare data consulting, we craft apps that work with information on staff productivity, scheduling, patient flow, and more. Detecting deep correlations between data, our apps help spot operational bottlenecks, improve resource allocation, and optimize labor use.

• Patient wait time breakdown
• Staffing efficiency by shift
• Appointment no-show rates

With analytics of insurance claims, reimbursements, and denials, you get a 360-degree view of the process. The insights generated by our healthcare data analytics software let you reduce payment delays, detect billing inefficiencies, and reveal gaps in payer communication.

• Claims denial root causes
• Reimbursement cycle times
• Payer-specific claim trends

Innowise’s healthcare software analyzes operational costs, patient group expenses, and overall cash flow. As a result, healthcare providers can detect financial leaks, plan budgets more accurately, and understand how treatment costs affect margins.

• Cost per diagnosis group
• Revenue by department
• Operational costs breakdown

For pharma companies, we implement data analytics software that processes clinical trial data to track protocol compliance, identify recruitment gaps, monitor trial progress, and accelerate drug development.

• Trial progress monitoring
• Participant dropout rate by site
• Recruitment timeline analysis