Designing payment for collaborative depression care management in primary care
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Designing Payment for Collaborative Depression Care Management in Primary Care. Yuhua Bao, Ph.D. Assistant Professor Division of Health Policy, Department of Public Health Weill Cornell Medical College. Acknowledgement.

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Designing Payment for Collaborative Depression Care Management in Primary Care

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Designing Payment for Collaborative Depression Care Management in Primary Care

Yuhua Bao, Ph.D.

Assistant Professor

Division of Health Policy, Department of Public Health

Weill Cornell Medical College


This work is supported by grants from the National Institute of Mental Health (K01 MH090087, P30 MH085943). The IMPACT study was funded by grants from the John A. Hartford Foundation and the California Healthcare Foundation.

I thank the following individuals contributed to the work or provided helpful discussion:

Martha Bruce, PhD, MPH,Lawrence Casalino, MD, PhD, Susan Ettner, Ph.D., Heather Gold, PhD, Andrew Ryan, PhD, Bruce Schackman, PhD, Leif Solberg, M.D, Jürgen Unützer, MD, MPH

Depression in Primary Care

  • Depression is prevalent, debilitating, and costly

  • The de facto mental health treatment system in the U.S.

    • Psychiatrist: 29%

    • Non-psychiatrist mental health providers: 39%

    • General medical providers: 56%

    • Human services providers: 19%

    • CAM providers: 17%

  • Primary care is an important sector for depression care

    • Major depression affects 10-15% of primary care patients

    • Quality of depression care is poor

Phases of Depression Treatment





No Depression




Treatment Phases




6-12 wks

4-9 mo.

1 or more yrs

Kupfer DJ. J Clin Psychiatry. 52(5s):28-34,1991.

Collaborative Depression Care Management (DCM): A Promising Clinical Model

  • Consistent with the Chronic Care Model

    • A team of clinicians: primary care physician, supervising psychiatrist, depression care manager

      • Assessment, Follow-up, Collaboration

  • Effectively implementing “Stepped Care”

  • Strong evidence of efficacy from >30 trials

  • At great odds with the fee-for-service, visit- based physician payment system

    • Lack of reimbursement identified as most prominent barrier to implementation


Antidepressant or psychotherapy (if preferred)

Reassessment by care manager and discussion with PCP; Psychiatric consultation if needed.

8-12 wks

Persistent Depression


Relapse Prevention

Monthly contact w/ care manager


Switch to (or augmentation with) other antidepressant or psychotherapy

6-10 wks

Reassessment by care manager and discussion with PCP; Psychiatric consultation if needed

Persistent Depression



Combination of antidepressant and psychotherapy; Consider referral to specialty MH services

6-12 wks

Persistent Depression


Adapted from Unutzer et al. (2001)

Monthly contact w/ care manager to maintain therapeutic gains

Current Implementation Initiatives and Payment Arrangements

  • Depression Improvement Across Minnesota, Offering a New Direction (DIAMOND)

    • All major health plans and medical groups in the state

    • A flat monthly case rate based on average monthly cost of a 12-month program

  • Washington State Mental Health Integration Program (MHIP)

    • >200 community health centers and mental health centers in the state

    • A flat fee based on 75% of cost of a 12-month program

    • Remaining 25% as bonus payment upon achieving process- and outcome- based quality

The Need for a Conceptual Discussion of Payment Design Issues

  • Goals of the payment?

  • Important features to consider?

  • Incentives provided by certain features?

Goals of Payment

  • Goal 1: To adequately compensate providers with the cost of delivering collaborative DCM

  • Goal 2: To align incentives with evidence-based practice and quality of care

Payment Design Features


(Not considered)

Bundled Case Rate

+ P4P?



Not Adjusted

Not Adjusted



What should be adjusted, what should not?

What should (not) be adjusted?

  • Should adjust

    • Factors accounting for major variation in resource intensity if indicated by evidence-based protocol

  • May not wish to adjust

    • if serious principal-agent problems exist

      • Adjustment factor is something providers can potentially manipulate

      • Hard to observe/determine whether manipulation is present

      • Incentives associated with adjustment run counter to treatment goals

  • Example: non-response to treatment

Alternative Designs, Incentives, and Implementation Issues: Episode

Alternative Designs, Incentives, and Implementation Issues: Monthly (I)

Alternative Designs, Incentives, and Implementation Issues: Monthly (II)

Conclusions Based on Conceptual Discussion

  • A bundled case rate w/o explicit quality incentives may not be sufficient to achieve payment goals

  • Episode payment with LOS adjustment reduces to monthly payment

  • Each adjustment feature considered has pros and cons

  • Payment design will need to balance payment goals and administrative cost/feasibility

Empirical Investigation

  • Variation in DCM intensity over time and across patients

    • Using registry data from a multi-site RCT

      • Probably the closest to EBP one could expect in community settings

    • Identifying factors accounting for variation in resource use (and how much)

  • What the analysis can do

    • Confirm assumptions made in conceptual discussion

    • Inform decisions regarding payment adjustment

    • Inform payment rate and/or adjustment formulae

  • Analysis will not provide empirical evidence on

    • Provider behavior in response to alternative designs

The IMPACT Study and Data

  • RCT of DCM among older primary care patients

    • 18 primary care clinics, 8 health care organizations, 5 states

    • DCM program designed for 12 months

  • IMPACT registry data

    • Web-based clinical system documenting DCM activities

    • Patient-care manager contacts

      • Date and duration of contact

      • Patient Health Questionnaire-9 (PHQ-9)

      • Current tx, changes in tx plan, care coordination

    • 767 unique patients with >=1 contact & baseline PHQ-9 >=5

    • 7,433 patient-months with >=1 contact

DCM Intensity at the Episode and Monthly Levels: Descriptive Results

Statistical Models

  • Zero-truncated count data (Poisson or negative binomial) models

  • Episode

    • Measures: total contacts / total direct patient contact time

    • Predictors: baseline severity,

      length of stay in DCM (1, 2, …, 12 mos),

      baseline severity x months

  • Monthly

    • Measures: contacts / direct patient contact time, in a month

    • Predictors:

      • Model for first-month: baseline severity

      • Model for Months 2-12:

        baseline severity,

        month indicator (2nd, 3rd, …, 12th mo.),

        tx response/remission at beginning of month,

        bl severity x month indicator,

        tx response/remission x month indicator

Episode, Contacts

Episode, Time

Monthly, Contacts

BL severity did not predict monthly DCM intensity statistically and was not shown in this graph.

Monthly, Time

Conclusions from Empirical Investigation

  • Episode

    • Resource use may vary widely depending on LOS

    • LOS adjustment or mandate reduces it to monthly payment

  • Monthly

    • Strong time trend regardless of response/remission

      • Sharp decline in the first 6 months, but stable afterwards

    • BL severity associated with limited difference

  • Persistently depressed patients

    • 30-35% even with DCM closest to EBP

    • Maintenance of high intensity DCM during Steps 2&3 (Months 4-8) may not be feasible

Two Alternative Payment Schemes

  • Episode, adjusted by # of months patients stayed in the program

  • Monthly, adjusted by the ordinal month in the first months, flat for months 7-12

  • For comparison, also consider

    • Episode, fixed

    • Monthly, fixed


  • Adjusted payment over fixed payment

  • Should not adjust for response/remission in a monthly design

    • Perverse incentives

    • Difference in intensity not substantial

    • Administrative burden high

    • Can design a case rate reflecting weighted average cost of treating responding and non-responding patients

  • Performance/quality incentives are a must (next study)

    • Outcome-based?

    • Process-based if outcome not met?

    • How much should be at stake?


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