CONFIDENTIAL & PROPRIETARY Impact Pro HMGs: Using information to further describe population health Presentation at the Ingenix Health Care Conference Michael Manocchia, Ph.D. Director, Outcomes and Evaluation [email protected](work)781-419-8427 May 15, 2008 ● Orlando, FL
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CONFIDENTIAL & PROPRIETARY
Impact Pro HMGs: Using information to further describe population health
Presentation at the Ingenix Health Care ConferenceMichael Manocchia, Ph.D. Director, Outcomes and [email protected](work)781-419-8427
Medical Management Identify and manage the right patients, at the right time, with the right
intervention
Identify members at greatest risk for future healthcare problems Understand key clinical drivers of risk – support steerage to appropriate
programs Identify care opportunities – members with gaps in care, complications and
co-morbidities
UnderwritingSet the right premium rate, attract and retain good business, promote stability
and profit
Historically, underwriters have used experience and other factors (age/gender, geographic and industry factors) to set healthcare premiums for individuals & groups
Information on health risk for groups and individuals is used to enhance the underwriting process
Clinical Indicators– Disease prevalence– Disease stage, advanced markers– Significant medical and pharmacy utilization events– More than 1,000 markers available– Rules engine to support custom rules
Care Opportunities– Gaps in care based on comparisons with evidence-
based medicine and guidelines– Future – supplemented by Symmetry’s EBM
– St. George’s Respiratory Questionnaire– MOS-HIV instrument
Productivity Gold Book (2001): covered a number of instruments IHPM leads the way today in this regard today
Behavioral Health Clinical diagnostic assessments used in behavioral health that are administered via survey Psychological assessments, including substance use and abuse
Highly reliable instruments are used Valid with clinical and cost measures Measure domains not accessible by administrative data
Health behaviors and attitudes Health states, pain and function and disease severity Mental health indicators Perceptions of productivity impacted by health Values around medical decisions Satisfaction with health care Social Support
Validating your measurement See predicted response and benchmark with norms
To include or exclude members with all HRA responses for a particular survey All members that also took an HRA
To include members with a sub-set of responses to particular survey questions All members that reported missing work days frequently do to health
To create AND statements within the entries within the Included or Excluded boxes, or to create a combination of AND/OR statements between selections within the Included or Excluded boxes
Advanced Filters allows you to create AND statements or a combination of AND/OR statements between selections within the (Included or Excluded) boxes
Filtered records can also be reported on through customized reports within the IPRO reporting engine.
• Unlike Filters which query data that has already been processed, creating a Case Definition is creating a Rule to be run through the Processing Engine – results will not be seen until the next data run
NOTE: This is true for ALL rules – Clinical Indicators, Care Opportunities and Case Definitions
• Once the Rule has been created though, it will be persistent for every future data run AND it can be used as a Filter itself.
– New Insulin Rx…..or– New oral Hypoglycemic Rx…..or– Gaps in refills or no refills for oral hypoglycemic agents…….and
Case Definition– Exclude members who meet Case Definition of “High Impact – Diabetes”– Include members with stages of change self report question related to
improvement of diet
37 Ingenix created Case Definitions “out of the box” 37 Ingenix created Case Definitions “out of the box” for demonstration purposes onlyfor demonstration purposes only
No standardization of HRA data from various sources Clients are left to create their own standards
No use of national standards with some self-report concepts that are widely understood and can add further depth to understanding health (e.g. CDC definitions) Similar to an EBM type model
The processing engine does not use the data for further calculation of cost and risk in a precise way
No current way to reconcile contradictions between administrative claims and self report data
No current way to build multi-dimensional variables with distinct levels that combine HRA, lab and administrative claims presently
Introduction and IPRO refresher Self Report Domains Current Self Report IPRO incorporation
Impact Pro Active Filtering Case Definitions Limitations in current self report IPRO approach
Introduction of HMG Making the business case Self report standardization HMG introduction HMG testing with smoking, physical activity, nutrition and obesity
Information tools and methodologies to support care and health management – current state: Primary focus is on disease populations or individuals of
moderate to higher risk Clinical information and concepts supported by administrative
medical and pharmacy claims, some use clinical data Outputs include measures of risk, some add gaps in care Many tools add reporting and some cohort modeling capabilities Limited use of alternative sources of data today Include alternative sources for identification and stratification
methods, prediction and risk adjustment– How can data from various sources be combined into meaningful
Health care organizations and employers are increasingly interested in focusing on healthier members in a population, or members of emerging risk Extend interventions to the lower end of the risk spectrum Improve wellness, healthy behaviors and lifestyle Improve attitudes on health Intervene in a more pro-active way, e.g., pre-diabetes, and
Support analysis of healthier populations and patients of emerging risk
Leverage existing and new sources of data, including HRA/self report, biometric data and socio-economic data
Integrate these different sources of data in innovative ways: Improve on existing concepts, e.g., measures of future risk Support new domains of measurement, including behaviors, attitudes,
and social context Accommodate different data scenarios – consistent data
availability unlikely across and within populations Create a useful context for analysis
We are pulling together a larger number of concepts and variables than are currently available in Impact Pro
Add value for customers by developing a context – organize information for analysis, presentation, and operations – in a flexible way
Key Advance: HMG Standardizes Alternative sources of data
The HMG methodology will: Standardize self report and biometric data found on HRAs and
other surveys into meaningful sets of building blocks– Smokers: current, quitting, former never– BMI: underweight, normal weight, overweight, obese and morbidly
obese– We call these standardized measures dimensional concepts
Will require the user to map their items through a standardized common HRA map with leading HRA tools in the field
– Also maintain flexibility for the user to develop meaningful HRA categories or build case definitions present in Impact Pro Active
We will use a scoring framework to map variable attributes into consistent scores and indicators of risk
Standardized self-reported concepts include: Condition, treatment, utilization via self report Health behaviors: lifestyle, preventive testing, immunizations,
safety and other forms of risk aversion Health attitudes: readiness, activation and awareness HRQOL: physical, emotional, bodily pain, role function Productivity: absenteeism and presenteeism Social Support Social Context: race, ethnicity, education, income Biometric markers: cholesterol, BMI, BP, etc.
This data could extend the risk spectrum for those that answer an HRA and some variables could be used to tailor communication and intervention
Scope out identification and stratification algorithms for HMGs Solicit clinical input and review
Apply algorithms to current analytic data warehouse that has claims, lab and HRA for seven large employers Interested in other clients participating in this process
Test hypotheses related to expected levels associated with HMGs to see if levels are distinct and valid
Begin to look at emerging risk associated with certain behaviors or conditions
HMG Levels Current Quitting Former smoker Never smoked
Information used to identify and stratify HRA: smoking status, quantity of use, quitting stage Medical and pharmacy: diagnoses, drug therapies, procedures indicating
quit attempts, quit treatments and counseling Map relevant clinical and family history to further define levels
Ask ourselves: If I run a smoking cessation program what would I want to understand about my members? Levels of smoking use How does smoking relate to cost and risk? What does the emerging risk across smoking groups look like?
Information used to identify and stratify HRA: many physical, exercise items to standardize Medical and pharmacy: limited set of procedures to increase or counsel
on PA
Ask ourselves: If I run a PA program, program what would I want to understand about my members? Levels of activity How does PA relate to cost and risk? What does the emerging risk of inactivity look like?
HMG Levels Severe nutrition problems Moderate nutrition problems Low nutrition problems No nutrition problems
Information used to identify and stratify Medical and pharmacy: nutrition and weight management counseling
appointments and obesity HMG (claims and biometric data) HRA: items related to nutrition behaviors and choices
Ask ourselves: If I run a nutrition behavior change program what would I want to understand about my members before enacting programming? Levels of nutrition problems How do nutrition problems relate to cost and risk? What does the emerging risk across nutrition groups look like?
Provide a context to organize and focus information in a way that is consistent from both a clinical perspective and also from a health management operational perspective
Describe both clinical and wellness intervention opportunities Have defined levels – that map to potential cohorts for intervention –
e.g., level of acuity; categories of smoking status; level of physical activity
Have rules and algorithms that assign an individual to a clinical or behavioral status (HMG) and levels of problems within an HMG (reconcile data sources, conflicts, timing, frequency) Allow users to further define or combine levels that fit program goals
using Impact Pro Active
Incorporate methods to accommodate different data availability scenarios for each individual
Validity and reliability of input data is key to its use not only with claims data, but also with self report
With self report, you want to see key elements that are included in the input tables, pass through properly, and can be used for filtering and selecting patients Answer_Desc: Each answer should be unique, and should provide
information about the question the answer responds to. For example, an appropriate answer description is “Yes, I am a smoker.”
Quest_Desc: Each answer should be unique, and should provide information about the question topic. For example, an appropriate question description is “Do you smoke?” An inappropriate response description is “Question 1.”
Impact Pro uses the MEMBER field to uniquely link information regarding each member to the Impact Pro output datamart. MEMBER should uniquely define an individual. Every member ID in the HRADATA table must also have an entry in the MEMBER table.
Lastly, check to see number of questions and members is correct and duplicates and invalid records indicated in the validation output.