Respecting Patient Choice in Attribution Methodologies: An Example - - PowerPoint PPT Presentation

www.rti.org

RTI International is a registered trademark and a trade name of Research Triangle Institute.

Respecting Patient Choice in Attribution Methodologies: An Example from Medicare’s Comprehensive Primary Care Plus Model

Fang He, PhD; Yan Tang, PhD; Kristen Henretty, BA; Chris Beadles, PhD, MD RTI International June 3, 2019

Funder: This research was funded by the Centers for Medicare and Medicaid Services under contract number HHSM-500-2014- 00037I / 75FCMC18F0001. The contents of this publication are those of the authors and do not necessarily reflect the views or policies of the Centers for Medicare and Medicaid Services.

Outline

▪ Background ▪ Study Objectives ▪ Data ▪ Methodology ▪ Results ▪ Conclusion ▪ Policy Implications

Background: Alternative payment models

▪ Medicare and other payers are transitioning from fee-for-service to

alternative payment models

– Since 2010, the Centers for Medicare & Medicaid Services (CMS) has

piloted more than 20 new payment models

– By March 2016, Medicare had achieved its goal of making 30% of its

payments for providers through alternative payment models

– More broadly, 34% of total U.S. health care payments were tied to

alternative payment models in 2017, an increase from 23% in 2015, according to the Health Care Payment Learning & Action Network

Background: Attribution

▪ A key feature in designing alternative payment models is the method

• f attributing patients to providers held accountable for their care

▪ Accurate payment and quality of care calculations hinge on timely,

accurate attribution

– Otherwise providers may be held responsible for patients they do not treat,

which could discourage providers from pursuing population health management

Background: Using claims in attribution

• Readily available source of information
• Does not impose any burden on providers
• Reliable, as claims are used to pay providers

Advantages

• May be difficult for patients and providers to understand
• Potential misalignment between the provider to which the

patient is attributed and the patient’s chosen provider

• May exclude newly enrolled patients or patients with gaps

in enrollment

• Patients are not actively engaged in the attribution process

Disadvantages

Background: Prioritizing patient choice in attribution

▪ CMS is now prioritizing a patient’s active choice of primary provider

within attribution methodologies for several alternative payment models

– Next Generation Accountable Care Organizations model (started 2017) – Medicare Shared Savings Program (started 2018) – Comprehensive Primary Care Plus (CPC+) Initiative (started 2019)

▪ Attribution via patient choice enhances beneficiary attribution

Background: How patients choose their primary provider

Background: CMS’s CPC+ Initiative

▪ The nation’s largest ever multi-payer initiative to improve primary

care

– Began January 2017 – 18 regions across the country – 2,879 primary care practices – 14,810 practitioners – ≈15 million patients, including more than 2 million Medicare patients

▪ Primary care practices are responsible for the care of attributed

patients

– From January 2017 through December 2018, based on attribution results,

Medicare paid $1.12 billion to practices for

▪ Managing their patients’ care ▪ Meeting annual performance targets ▪ Lump sum prospective payments aimed at giving flexibility to practices beyond

traditional fee-for-service payments

Background: Attribution in CPC+

The patient makes their choice via MyMedicare.gov Claims-based attribution Does the chosen provider meet the provider eligibility requirements? The patient is attributed to the chosen provider Yes No Does the patient meet the CPC+ eligibility requirements? Yes The patient is not eligible for attribution No STOP

Study Objectives

▪ How many patients have been attributed to CPC+ practices using

patient choice?

▪ How do the patients’ choices compare with results from claims-

based attribution?

▪ How do the characteristics of attributed patients making a provider

choice compare to those attributed via traditional claims-based attribution?

Data

▪ CMS administrative data containing patients’ choices of provider ▪ Medicare claims and enrollment data

– Including January 2017–December 2018 physician and outpatient claims

used in CPC+ claims-based attribution

▪ Data on characteristics of Medicare patients

– 2017–2019 Master Beneficiary Summary File – 2010–2014 American Community Survey 5-year estimate

Methodology

▪ We used data on patients’ choices and Medicare claims and

enrollment data to attribute patients to CPC+ practices

– We examined the number of patients attributed to CPC+ practices using

patient choice

– We compared the patients’ choices and the results from the CPC+ claims-

based attribution method

– We compared the characteristics of patients attributed to CPC+ practices

using patient choice and patients attributed using claims

Results: CPC+ patients attributed via patient choice increased from Q1 to Q2 in 2019

▪ In 2019, the number of patients attributed to CPC+ practices using

patient choice grew 62.6% from 2,334 in Quarter 1 to 3,796 in Quarter 2

▪ The number of patients attributed to CPC+ practices using patient

choice was small relative to the 2,006,982 patients attributed to CPC+ practices via claims-based attribution in 2019 Quarter 2

• 500

1,000 1,500 2,000 2,500 3,000 3,500 4,000 2019 Quarter 1 2019 Quarter 2

Source: RTI International analysis of CMS administrative and enrollment data.

Number of Patients Attributed to CPC+ Practices using Patient Choice

Results: CPC+ patients attributed via patient choice were concentrated in a few CPC+ practices, 2019 Quarter 2

Source: RTI International analysis of CMS administrative and enrollment data.

Distribution of Patients Attributed to CPC+ Practices using Patient Choice by CPC+ Region, 2019 Quarter 2 Distribution of CPC+ Attributed Patients via Patient Choice, 2019 Quarter 2

579 216 130 42 5 100 200 300 400 500 600 700 1 Patient 2 Patients 3-5 Patients 6-99 Patients 100-335 Patients

Number of CPC+ Practices

5 CPC+ practices accounted for 30% of patients attributed to CPC+ practices using patient choice

Results: High agreement between patient choice and claims-based attribution in 2019 Quarter 2

3,237, 85% 319, 9% 240, 6%

Claims-Based Attribution Results, Among Patients Attributed to CPC+ Practices using Patient Choice

Patients attributed to the same CPC+ practice Patients attributed to another CPC+ practice or to a non-CPC+ practice Patients not attributed by claims- based attribution Source: RTI International analysis of CMS administrative, claims, and enrollment data.

Results: CPC+ patients attributed via patient choice differed from claims-based attributed patients in 2019 Quarter 2

Characteristics Patients attributed using claims-based method Patients attributed using patient choice Difference: Patients’ choices minus claims (standard error) Total Number of Patients 2,006,982 3,796 Age 72.77 71.74

• 1.03***

(0.17) Male 0.42 0.49 0.07*** (0.01) White, non-Hispanic 0.87 0.81

• 0.06***

(0.01) Eligibility for Full Medicaid Benefits 0.08 0.03

• 0.04***

(0.00) Agency for Healthcare Research and Quality (AHRQ) Socioeconomic Status Index of Patient’s Zip Code 54.38 55.81 1.43*** (0.07) Number of Chronic Conditions through 2018 6.43 5.88

• 0.55***

(0.06) Medicare Payments for Physician Services in 2017 $507.34 $594.75 $87.41*** (8.95) Total Medicare Payments in 2017 $8,220.81 $7,047.46

• $1,173.35***

(314.18)

Source: RTI International analysis of CMS administrative, claims, and enrollment data (including 2017-2019 Master Beneficiary Summary File) and 2010-2014 American Community Survey 5-year estimate. Note: *** p < 0.001

Conclusion

▪ The number of patients attributed to CPC+ practices using patient

choice has increased

▪ Few patients were attributed to CPC+ practices using patient choice

relative to number of patients attributed to CPC+ practices via claims-based attribution

▪ High agreement between patients’ choices and claims-based

attribution method results, increasing our confidence in both methods

▪ Compared to patients attributed to CPC+ practices using claims,

those attributed using patient choice were:

– Younger – Fewer chronic conditions – More likely to be male

and non-white

– Higher Medicare payments

for physician services

– Higher socioeconomic status – Lower total Medicare payments

Policy Implications

▪ Alternative payment models could consider supplementing their

existing claims-based attribution methods with a process to ask the patient to confirm their provider

▪ This simple to understand method may better engage providers and

patients, and improve the accuracy of attribution

▪ Studies have shown that more engaged patients (which includes

being able to select providers based on performance or quality) have better health outcomes and care experiences (Hibbard and Greene, 2013)