P4p Payment Model

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Quality Topic
The Pay-for-Performance (P4P) Payment Model
Quality Topic Description
Description: The P4P is a payment model, which offers financial incentives to health care providers for meeting specific performances measures. Medical care providers receive Medicare reimbursements that reflect the provider’s performance on specific metrics, which are based on adherence to expected health care processes, patient satisfaction survey (PSS) scores, or patient quality outcomes (Nix, 2013). Miller, et al. (2017) referred to it as a “modified FFS (fee-for-service)” method. Evidently, this model acts as a payment template for many of Medicare’s programs. These programs include the Premier Hospital Quality Incentive (PHQI), the Hospital-Acquired Condition
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In effect, the legislative objective in enacting a mechanism for the expansion of the P4P programs was to improve health care delivery quality and efficiency for the benefit of the patients.
Impacts on stakeholders: After more than a decade since the launching of the first P4P project in 2003, there had been limited improvement in the medical institutions’ process efficiency and close to nothing had been observed in terms of improvements in patient outcomes (Nix, 2013). Similarly, with regards to physicians, there had been no noticeable change in their performance in improving significantly health outcomes among their patients.
More recent data tell a comparable outcome of the P4P programs. Markovitz and Ryan (2017), for instance, reviewed the literature on the programs and noted “contradictory effects of bonus likelihood, bonus size, and marginal costs” among medical institutions, indicating a lack of appropriate strategic response to the financial incentives. Moreover, poor and minority patients had been consistently reporting the worst health care delivery
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Rajaram, Barnard, and Bilimoria (2015), for instance, noted five serious flaws in the current PSI-90 core metric used the hospital programs: the HACR and the HVBP. Problems evidently exists with flawed component measures; incorrectly identified targeted clinical areas; inaccurateness in identified adverse events; inadequate risk adjustment; and flawed composite measure formulation. Vulnerability to surveillance bias, which is the inherent tendency for increased testing to increase detection outcomes, had been observed (Rajaram, Barnard, & Bilimoria, 2015).
There had also been redundancy in specific measure components that had been observed in two different P4P programs, which can result to double penalization of the hospital due to a single redundant measure component (Rajaram, Barnard, & Bilimoria, 2015). Other problems include inaccurate measurement of clinically relevant complications of a medical condition; inconsistent capturing of comorbidities across hospitals; and numerating weighting shortcomings. With all these problems added together, hospitals maybe unfairly penalized financially, which may have adversely affected their clinician quality
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