Breaking the Fee-for-Service Addiction: Don’t Throw the Baby Out with the Bathwater

By | October 21, 2015

baby“Breaking The Fee-For-Service Addiction: Let’s Move To A Comprehensive Primary Care Payment Model,” a recent Health Affairs blog post by Rushika Fernandopulle of Iora Health, argues for replacing FFS payment with risk-adjusted comprehensive payments for primary care. We agree. However, the post portrays sponsors’ continuing to require submission of “dummy claims” as an unproductive addiction to FFS norms, because quality shouldn’t be judged based on “process measures” (their example: “how many visits [we] do”) but rather on “patient experience, clinical outcomes, and impact on downstream costs.” This argument does not hold.  

First, some processes are essentially synonymous with evidence-based, high-quality clinical care (such as providing immunizations), while others may be our best short-term way of judging whether needed care is given. For example, having a primary care visit within 30 days of a hospital discharge is associated with reduced risk of mortality. While increased survival is a goal of better care, mortality is too rare and too confounded with other patient factors and events beyond the control of a health plan to be useful for judging the adequacy of post-discharge care. We agree that quality measures should be adapted to recognize the value of “touching” patients in ways other than through an in-office visit with an MD, but responsible oversight requires verifying that plans do not neglect recently discharged patients.

Further, transactional records, be they claims or dummy claims, are needed to 1) monitor care (identify services offered), 2) learn what works (study the costs and outcomes associated with different strategies), 3) detect fraud (such as, “ghost” services or employees), and 4) measure the risk associated with each person’s medical problems. Indeed, given that plans should want such data to manage themselves, providing it to sponsors is the natural way to enable both fair comparisons on quality and risk-adjusted payments that embody existing relationships between patient risk factors and the resources needed to address them.   

Some health maintenance organizations in the 1990s appeared to be both avoiding sick patients and skimping on care. Under current models of health reform, payment is tied to both patient risk and quality measures – structure, process, and outcomes – to guard against the poor-quality care practices that flourish when no one is looking.

Iora Health is right to challenge fee-for-service payment, especially in primary care. In a paper published in Medical Care in 2012, Ash and Ellis describe an encounter-data-based model for primary care that tailors payments to the complexity of each practice’s patients. Since encounter data enables risk-adjusted payments, more – not less – documentation of care practices (including potentially valuable services that are not currently reimbursed) is the right prescription.

Arlene Ash

Arlene Ash

Professor and Division Chief at University of Massachusetts Medical School
Arlene Ash is Professor and Division Chief in the Quantitative Health Sciences Department at the University of Massachusetts Medical School.
Arlene Ash

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Lisa Lines

Lisa Lines

Health services researcher at RTI International
Lisa M. Lines, PhD, MPH is a health services researcher at RTI International, an independent, non-profit research institute. She is also an Instructor in Quantitative Health Sciences at the University of Massachusetts Medical School. Her research focuses on quality of care, care experiences, and health outcomes among people with chronic illnesses; emergency department utilization; and person-centered care and patient-centered medical homes, among other topics. She is co-editor of TheMedicalCareBlog.com and serves on the Medical Care Editorial Board. She also serves as chair of the APHA Medical Care Section's Health Equity Committee. Views expressed are the author's and do not necessarily reflect those of RTI or UMass Medical School.
Lisa Lines
Lisa Lines

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