Population Health Management

Analyzing Risk

Population Risk Models
(Predicts future 12 months)

  • Risk of inpatient admission
  • Risk of ED visit
  • Risk of AMI
  • Risk of asthma
  • Risk of cerebrovascular accident (CVA)
  • Risk of congestive heart failure
  • Risk of COPD
  • Risk of diabetes
  • Risk of hypertension
  • Risk of mortality

Event Based Risk Models
(Predicts future 30 days)

  • Risk of 30 day hospital readmission
  • Risk of 30 day ED re-visit

Analyzing Patient Data to Improve Population Health

Healthix transforms patient data into actionable intelligence that can help Healthix participants anticipate and mitigate chronic health problems within the communities they serve.

Healthix helps participating organizations identify:

  • Which community members are more likely to use ER services?
  • Which patients are at high risk of returning to a hospital within 30 days?
  • Which chronic conditions are most problematic in the patient community?
  • Which patients may require care in the near or distant future for type 2 diabetes, COPD, hypertension, as well as many other chronic conditions?

Predictive analytics for encounters

Our predictive analytics solution applies sophisticated algorithms to patient data points to better predict which patients are likely to require emergency care, inpatient visit or drive hospital readmissions.

Predictive analytics for clinical based conditions

For patients with chronic conditions, we leverage clinical data collected in real time as well as publically available social data on incomes and education levels to help clinicians and care coordinators improve care by proactively identifying high risk patients. The data we provide can also reduce the risk of disease onset in those patients who are trending toward chronic illness.

Population health insights

Besides improving care for individual patients, we deliver insights about patient populations. The Healthix analytics dashboard allows filtering of data so that population profiles and trends can be targeted, whether by age, gender, chronic condition, geographical region or more. Participating organizations can compare their subsets of patients against patients with similar clinical or demographic profiles within the exchange.

Interested in a demonstration? Contact us