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Applying Strategy and Measuring Impact of Key Population Health - - PowerPoint PPT Presentation
Applying Strategy and Measuring Impact of Key Population Health - - PowerPoint PPT Presentation
Applying Strategy and Measuring Impact of Key Population Health Activities DATE HFMA Tri-State Institute September 12, 2019 Session Objectives Learn how to bring a strategic orientation to one of the most operationally leveraged capabilities
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Agenda
Front Health – background Anticipating key financial roadblocks in VBC transitions A thoughtful approach to care management Measuring the impact of clinical interventions
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Who we are
Greg Long, MD CMO
greg.long@fronthealth.com
▪ Greg has deep population health and
physician leadership expertise and partners with clients to help them achieve success in their value-based care transformation
▪ Greg is a board-certified Family Medicine
physician with more than 25 years of clinical and executive experience, including 10 years as CMO of ThedaCare, a progressive, integrated health system in Wisconsin
▪ Prior to that, he helped lead ThedaCare’s
primary care division through care model redesign resulting in the best clinical quality performance in the state of Wisconsin
▪ We were born from the Midwest
Health Collaborative (MHC), a consortium of six health systems throughout Ohio1, dedicated to delivering exceptional clinical
- utcomes and increased
satisfaction at lower costs
▪ We incubated our solutions at
MHC and demonstrated their value within our member systems’ at-risk populations
▪ Front Health, a team of analysts,
strategists, designers, and clinicians, now offers these solutions to payers and providers committed to transforming healthcare
1: Cleveland Clinic, OhioHealth (Columbus), ProMedica (Toledo), Premier (Dayton), TriHealth (Cincinnati), and Aultman (Canton)
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How we work with organizations
Our focus has been on high value capabilities that best enable success in value-based care
Data visualization that surfaces meaningful insights is a part of our DNA
▪ Building a stronger
performance improvement “muscle”
▪ Maximizing contract
performance
▪ Creating consistent and data
driven care management
▪ Measuring the impact of
clinical programs
Primary focus of today’s discussion
Performance improvement Rapid and in-depth performance diagnostic and improvement program against individual populations (e.g., EHP) and/or high impact capabilities Contract management Achieving
- perational
simplicity while managing inherent contractual complexity
Chronic Condition Breakdown Allowed PMPM1, 2017 $107 $449 $81 $32 $30 $26 $21 $20 $19 $17 $13 $13 $71 Hypertension Healthy Active Cancer Diabetes w/o CAD Neurological Disorders Chronic musculoskeletal/ OA/ Osteoperosis All other (12) Total Mental Health/ Substance Abuse Asthma Severe heart failure/ transplant/ heart disease Renal Failure Severer Rheumatic Disease 1% 11%- 12%
- 15%
- 20%
- 12%
- 1%
- 1%
- 16%
Service lines & episodes General waste/ misuse Chronic conditions
CONTRACT / POP 3 Metrics/standards
▪
Quality measure 2
▪
Quality measure 9
▪
Quality measure 10
▪
Quality measure...
▪
Quality measure 20
▪
Risk adj. standard 1 CONTRACT / POP 2 Metrics/standards
▪
Quality measure 1
▪
Quality measure 4
▪
Quality measure 7
▪
Quality measure...
▪
Quality measure 25
▪
Risk adj. standard 1 CONTRACT / POP 1 Metrics/standards
▪
Quality measure 1
▪
Quality measure 2
▪
Quality measure 3
▪
Quality measure...
▪
Quality measure 20
▪
Risk adj. standard 1 CONTRACT 3 CONTRACT 2 CONTRACT 1
Pt w/gaps Pt w/gaps, in care mgmt.
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Agenda
Front Health – background Anticipating key financial roadblocks in VBC transitions A thoughtful approach to care management Measuring the impact of clinical interventions
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1: Cost, Quality and Experience, i.e., the Triple Aim; 2: PCMH = Patient-Centered Medical Home; 3: CM = Care Management; 4: BH = Behavioral Health
Design and deploy VBC care model(s) Predict systemic P + L fluctuations Description Understand impact
▪
Analyze outcomes for each VBC intervention
▪
Apply statistical methods to ensure validity
▪
Study and adjust until desired results
▪
Segment populations
▪
Customize care for each segment
▪
PCP-led team models, e.g., PCMH2, CM3, BH4, PharmD
▪
Virtual care options
▪
Strive for net neutral care team costs, e.g., increase panel size for team
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Account for all VBC payments
▪
Estimate FFS losses with improved care
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Focus on new patient growth
▪
Use data to influence decisions
Maximize
- perational care
standards
▪
Use best practice care models
▪
Standardize when possible
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Create transparency of performance by team member
▪
Study and adjust until desired results 1
Proactively managing the value-based care (VBC) transition will increase confidence in achieving a return1 on the transformational investment
2 3 4
Key Elements Realized value
Invest in proven VBC delivery models in a fiscally responsible way Create leader and operational visibility to the system profitability impact of the VBC transformation; informed adjustments as necessary Ensure clinical team resources are highly productive and effective in achieving desired VBC outcomes Objectively assess the effectiveness of each VBC clinical intervention; informed adjustments as necessary
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Agenda
Front Health – background Anticipating key financial roadblocks in VBC transitions A thoughtful approach to care management Measuring the impact of clinical interventions
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A best in class care management function delivers on a range of key elements
CARE MANAGEMENT
A singular, well-coordinated team that is connected to the primary care givers with resources aligned to reflect population prioritization Org construct & staffing Sophisticated stratification that leverages key data sets and evolves
- ver time to incorporate increasing access to add’l data (e.g., social
determinants)—for care mgmt, end of life discussions, general risk Risk stratification
▪
Defined measures of success
▪
Clear visibility into daily operational metrics
▪
Systematic view of impact and insight into what drives impact for further program refinement Performance reporting:
- perational + impact
▪
A compelling message to patients that drives enrollment
▪
An end to end patient engagement and management model that empowers patient to understand and effectively manage their health
▪
A model that balances ongoing patient involvement with the need to maximize the impact across many patients Interventions
▪
Engage/enroll
▪
Assess
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Develop plan
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Manage
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Graduate
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Organizational buy-in and support of care management with a clearly defined strategy for where and how (e.g., programs) you want to apply CM
▪
A roadmap where/when resources will be applied (populations) Strategy: populations & programs Key characteristics Key outcomes
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Program design
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Prioritization of populations Model to align staffing by population Customized risk stratification and patient prioritization
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Successful enrollment approach
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Targeted interventions based on disease state
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Maximizing impact through defined & flexible graduation criteria
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Operational dashboard
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Systematic impact tracking End to end approach to Care Management This comprehensive approach is easily adapted to improve any system’s or payer’s care management operation
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The first step in a care management strategy is defining where—and to what extent—you are supporting a given population
STRATEGY
Highest priority Population (in order of priority) Total lives (est.) Employee Health Plan 6,000 MSSP 31,400 Medicaid 5,000 Payer 1 MA 5,300 Anthem (CML + MA) 18,000 Aetna (MA) 2,500 MMO (MA) 13,000 ~85,000 ILLUSTRATIVE Payer 2 CML 5,300 High risk support Rising risk support What are the right programs for a specific population to maximize impact? Further, where do you set the “dials”
- n each of those
programs?
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It’s important to think through the construct of your operation and define the level of standardization expected at each step
STRATEGY
Level of standardization (in this example) High All will use the same stratification definitions coming
- ut of Platform ABC
High Agree on the minimum programs to offer and ideal levels of staffing Medium Specific pathways and processes defined together, but execution and implementation are local responsibilities High Mutual accountability to each other for patient, financial, and care manager performance Strategy + org (e.g., programs, resources) Stratification of patients Delivery of care management (interventions) Performance /
- utcomes
Facilitate alignment around common programs & levels of support, incl. a formula for defining staffing Role of the “central” function Propose, refine, implement, and train the local systems on the stratification methodology Lead development of interventions for specific conditions; create standards for hiring/training Align the group on metrics and goals, provide ongoing transparency to performance Local entity role Population-specific decisions on programs & level of support (beyond minimum) Provide input into the methodology and educate own system
- n how it works
Lead the day to day
- perations/delivery of CM
resources Hold each other accountable to your performance HEALTH SYSTEM EXAMPLE
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With programs defined, the next step is to determine the optimal number of resources required, which can inform broader financial VBC modeling
STAFFING MODEL
Population + program inputs Workload inputs Staffing model output 1
Population growth Competition PSA capture SSA capture Outmigration Net new patients
Market share growth
% % % % % Admissions Readmissions ED visits Imaging OP procedures
FFS Revenue Losses
$$ $ $$$ $$ $ CPC + CCM TCM Shared savings Quality payment Downside risk
Value-based contract revenue
$$ $ $$$ $$ $ $$$ MD/DO APP RN/CM Behavioral Pharmacy Diabetes ed.
Care transformation resources
FTE xxx xx xx xx x xx
System profitability predictor for VBC 2
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Description Requirement Primary Criteria Severity/ Disease status
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Severity of patients current health status as determined by presence of current or previous health diagnosis’
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At least one
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HCC-RAF >=2
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Pts with depression
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Pts with stroke condition
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Pts with CKD
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Last eGFR <60
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30 day readmission High utilizers/ High Cost
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Current and continued use
- f acute ED & IP services
which impact high total cost of care
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At least one
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ED visits >=3
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Hospital admits >=2
▪
Allowed amounts >=10K without surgical spend Predictive risk
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Probability that patient will continue to be a high utilizer based on predictive models
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At least one
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Inpatient stay probability (based on 12 months of claims) >=10%
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Likelihood of DM admit >= 80%
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Likelihood of CHF admit >= 80%
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Likelihood of COPD admit >= 80%
AND AND
Identifying patients can be done any number of ways; what’s most important is ensuring that it’s informed by the types of patients you seek to engage
RISK STRATIFICATION
Severity/ disease status Utilization High cost Impactable factors Predictive risk Health status based on current or previously diagnosed health issues High risk Current and continued use
- f acute ED & IP services
High total cost of care that we can impact due to unnecessary utilization Probability that patient will continue to have poor health outcomes based on predictive models Patients with current high cost, high utilization, and predicted continued poor health status who would benefit from intervention Probable future use of acute ED & IP services Current low cost with a potential for future increases that we can impact by avoidance Rising risk Severity probable worsening health status determined by predictive models which will increase cost from unnecessary utilization without intervention Patients whose predicted health status is worse than their historical cost and utilization would suggest Health status at time of discharge, including acuity of admission, discharge diagnosis’, comorbidities, and cognition History of admissions and readmissions Patient has been discharged on new medications or DME that will be crucial to maintain health or continue recovery Transitional Probability of readmission in the next 3 months based on risk score Patients who are being discharged from the hospital after an acute event who are not predicted to maintain their health or continue recovery Patients with newly diagnosed chronic conditions (within the last 6 months) or multiple comorbidities
A few critical steps to stratification…
- Define the types of patients you seek
to engage
- Create criteria that enables
identifying those types of patients
- Develop a way to prioritize identified
patients The goals of a program define the types of patients to engage…
Organizaion- specific
…and should inform the stratification criteria
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▪ Near real-time view of how efficient
care managers (e.g., engagement, graduation rates; panel size) are w/ability to cut in multiple ways
▪ Comparative reports across multiple
dimensions to identify top performers/areas and those with room for improvement Operational performance/ efficiency Outcomes: financial and utilization—Impact tracking
▪ Patient outcomes across cost and
key utilization measures: – Cost (Allowed PMPM – Utilization (ED, IP admits, PCP visits, high-tech radiology)
A best in class CM function can provide near real-time insight into
- perational performance and measures patient impact
PERFORMANCE
Key types of performance transparency Description 3 4
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What is my current workload? What populations are patients from? How long have patients been in the program? How is the panel distributed across my team? What kind of patients are enrolled?
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How well am I enrolling new patients?
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How well am I graduating patients?
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Agenda
Front Health – background Anticipating key financial roadblocks in VBC transitions A thoughtful approach to care management Measuring the impact of clinical interventions
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▪ Near real-time view of how efficient
care managers (e.g., engagement, graduation rates; panel size) are w/ability to cut in multiple ways
▪ Comparative reports across multiple
dimensions to identify top performers/areas and those with room for improvement Operational performance/ efficiency Outcomes: financial and utilization— Impact tracking
▪ Patient outcomes across cost and
key utilization measures: – Cost (Allowed PMPM – Utilization (ED, IP admits, PCP visits, high-tech radiology)
A best in class CM function can provide near real-time insight into
- perational performance and measures patient impact
IMPACT TRACKING
Key types of performance transparency Description 3 4 The challenges that exist…
▪ Payers, health systems, and self-
insured employers spend meaningful dollars on care interventions -– care management, disease-specific programs, etc. –
▪ However, these investments lack
an adequate understanding of their actual impact – either because they aren’t done (due to analytical difficulty, confounding variables) or they are done poorly
▪ Instead, you are often forced to
rely on either gut feel or insufficient approaches that could be leading to the wrong conclusion altogether
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Significant investments in care interventions require reliable insights to understand their impact and inform a broader value-based strategy
IMPACT TRACKING
▪ Pairing a strategic understanding of
population health with a robust set of analytics to methodically answer the most important – and difficult – questions – What is the impact of your clinical interventions / investments? (e.g., care management, disease management, social determinants of health) – Given those insights, what are the implications to your value-based strategy?
▪ Creating visibility to the impact you’ve
been having – or not, and help you maximize it going forward
% difference – pre and post intervention
Intervened group Matched control Statistically significant difference
▪ A repeatable, comprehensive approach that
delivers statistically-validated insights
▪ Robust matching of intervened and control
patients, including addressing selection bias
▪ Consistent approach across all clinical
interventions
▪ Best in class visualization to surface nuanced
insights
Single population example; see appendix for multiple population synthesis
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A narrow or incomplete view of impact can easily lead to the wrong conclusion, often with major strategic implications
Potential conclusions Example: PMPM impact Discontinue intervention due to perceived lack of impact on cost; Hold on to FFS contracts as long as you can Model cost savings expected on the high cost segment of any population you expect to manage; Insights drive an expansion of risk contracts moving forward What a customer thinks is happening… …what is actually happening PMPM among care managed patients is increasing by 20% in the year after enrollment % difference – pre and post intervention PMPM is increasing by 20%...but control patients are increasing by 80%
Intervened group Intervened group Matched control Statistically significant difference
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Provider case study. Impact tracking – care navigation
- 100
- 75
- 50
- 25
25 50 75 100
Matched (CM’d) - 49 Matched (control) - 49
Admits ED Imaging PCP Rx PMPM % change in performance – pre vs. post enrollment (or similar if control group)
MSSP population
Difference of matched patients is statistically significant
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Provider case study. Impact tracking – CMS annual wellness visits
Statistical analysis + dashboard design
▪ Situation: Provider lacked visibility into
the impact of CMS annual wellness visits
▪ Challenge: Needed expertise to perform
statistical analysis to determine efficacy
- f the AWV + method to track outcomes
- ngoing
▪ Outcomes: Demonstrated avoided
utilization + cost in those CMS beneficiaries with a regular cadence of AWVs; confidence in recommending resources to improve AWV compliance
▪ Statistically valid insights ▪ Repeatable approach ▪ Best-in-class visualizations
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