Insights

Lifemesh InsightsTM is a rich solution for reporting, analysis, and Business Intelligence that can shape the way you do your business.

The Comprehensive Assessment is a critical component to the optimized health of the elderly and has standardized the way in which care is provided. It does, however, have limitations. The Lifemesh InsightsTM solution was designed to address these limitations and to empower care providers to become proactive in the care they provide to their members.

How it Works

Analysis of assessment data by section provides valuable information, but it is the ability to combine responses from other sections that uncovers the greatest insight. For example, if you believe those who live alone suffer from depression more often, you can now validate it. If you are hoping to understand the value of transitioning out of a nursing home, you can now assess the value based on history. The combination of demographic, caregiver, medical condition, living situation, diet, activity, vitals, claims, and other data can deliver on the promise of evidence-based and proactive care.

Use the existing 15+ dashboards, build your own, or perform ad-hoc reporting and visualizations through this powerful and secure analytics tool.

Assessment

Consolidate assessment data with actual health, claims, and remote monitoring data to gain greater visibility into individual and population correlations with the comprehensive assessment and care plans.

Gain insight into how well your assessment process is working. Difficult questions to ask? Determine the responses gained from members by Assessor to see if there are training opportunities. Understand your broader population and identify care resource needs based on this overall population data for smarter hiring.

Additional Features Included

  • Filters – ability to filter one or all visualizations on a single value or parameter (i.e. diet by health condition)

 

  • Insights – Plain English translation of visualization into useful summaries (i.e. Top X meals)

 

  • Contributors – Identify time-based contributing factors to results (i.e. Contribution statistical relevance for movement to a Nursing Home such as Primary Caregiver, Living condition, etc.)

 

  • Anomalies – look for data-based outliers (exceptions) that alert to potential issues that should be investigated further