Analyze FAQ Answers to common questions about MX Analyze

What is MX Analyze?

MX Analyze is a predictive analytics tool for Participants to receive actionable insight into managing population risks to improve patients’ health and lower costs.

Where does the data from MX Analyze come from?

The data comes from EHR, claims, pharmacy, laboratory, member/enrollment data in the MX
network, as well as publicly available community/census information.

Will I be able to see data at a patient-level in addition to the population level?FAQ

Your view in MX Analyze depends on your use case and assigned role. MX Analyze displays population health information at an aggregate level. In order to see patient-level data, you must be assigned a person level role which will display a Patient / Member List and Encounter List.

What modules are included in MX Analyze?

MX Analyze includes Population Risk Management and Transition Risk Management.

What is Population Risk Management?

Population Risk Management is a predictive analytics solution that deploys predictive risk scores, risk features and analysis of populations being managed by entities at risk or share risk for the cost and quality of their care.

What components can be found in the Population Risk Management module?

Components include the Population Counts, Population Statistics, Future Risk Bins, Risk Change Bins, Descriptive Statistics and the Patient / Member List. Note: You’ll only be able to see the Patient / Member List if you’re assigned a person level role.

In the Population Risk Management module, what is the difference between the At-Risk Population and the Total Population?

The At-Risk Population is a count of all individuals being managed in the population, not including deceased individuals or those who have otherwise left the population more than 12 months ago. The Total Population is a count of all individuals in the population.

What does it mean when a patient has left the population?

This means the patient has left the user’s attributed population. For example, for an ambulatory clinic, the patient could no longer appear in the patient panel; for a hospital the
patient could be discharged longer than 2 years prior; for a health plan member they could disenroll. Opted-out patients that were previously attributed could be another reason.

What is the Transition Risk Management module?

Transition Risk Management is a predictive analytics solution that deploys predictive risk scores, risk features and analysis of individuals facing the critical 30 days immediately after an inpatient discharge or emergency department visit.

What components can be found in the Transition Risk Management module?

Components include Date Ranges and Refresh Date, Encounter Toggles, Encounter Count, Readmission or Revisit Risk Bins, Age and Gender Distribution, Patient Origin, and an Encounter List. Note: You’ll only be able to see the Encounter List if you’re assigned a person level role.

What are risk scores in MX Analyze?

There are two types of risk scores included in MX Analyze, events and cost. Risk scores for events (e.g., ED visit, mortality) are numerical values assigned to an individual representing the risk or likelihood that an event will take place within the stated risk time frame. Risk scores for cost are expressed in dollars and represent the predicted total cost of care for an individual in the future 12 months.

What risk models are included in Analyze?

Risk scores are produced for every population member on each risk model included in
Analyze as defined in the table below.

Population Risk Transition Risk
 Timeframe  - Future 12 Months  - Within 30 Days of
Encounter Discharge
 Utilization Cost  - Total Cost
 Utilization Event  - Emergency Department Visit
- Inpatient Admission
 - IP Readmission
- ED Revisit
 Disease Event  - Mortality  - Mortality
How does Analyze utilize social determinants of health?

Analyze calibrates each risk model specifically to the MX population, including social determinants of health at the individual and community level. MX uses over 30 SDOH from census and CDC data to evaluate the place-based risk of the patient/member place of residence. In addition, factors influencing health (Z-codes) are used to identify additional risk at the person level. These codes are increasingly used in records to provide insight for occasions when
circumstances other than a disease, injury or external cause classifiable to other codes influence
the encounter.

How does Analyze estimate cost?

Actual costs are not known in the MX data. A proxy method based on cost per encounter is applied to future cost models and historical costs. The intent in predictive risk modeling is to
guide users in prioritization and stratification methods and is not intended for precise cost analyses of any kind.

What determines my population in analyze?

Your population is determined by your patient panel(s), which vary by participant. Contact your Organization Administrator or support@manifestmedex.org for more information.

Why do I see patients outside of California in my population?

Your patients could have a home address outside of California.

Where can I find more information than what is available in the Individual Profile?

To find more details on individual patients, such as filled & prescribed medications, problems & diagnoses, labs, and procedures, please visit MX Access.

Why do I only see risk scores for the last few months?

MX Analyze is a new product, and we began generating future risk scores in the summer of 2019. Your risk trend will become more robust overtime.

Why is there a Stats Source toggle in the Population Statistics?

The EHR and claims data cannot be mapped together at the encounter level. When multiple data sources exist, the statistics are calculated either on claims data or clinical (EHR) data.

Why is the utilization (population and patient level) presented in the last 12 months?

Historical statistics are shown for the previous 12 months as rule, because the predictive models are looking forward 12 months. This gives the user a balanced point in time.