Abstract

BackgroundQuality metrics, pay for performance (P4P), and value-based payments are prominent aspects of the current and future American healthcare system. However, linking clinic payment to clinic quality measures may financially disadvantage safety-net clinics and their patient population because safety-net clinics often have worse quality metric scores than non-safety net clinics. The Minnesota Safety Net Coalition’s Quality Measurement Enhancement Project sought to collect data from primary care providers’ (PCPs) experiences, which could assist Minnesota policymakers and state agencies as they create a new P4P system. Our research study aims are to identify PCPs’ perspectives about 1) quality metrics at safety net clinics and non-safety net clinics, 2) how clinic quality measures affect patients and patient care, and 3) how payment for quality measures may influence healthcare.MethodsQualitative interviews with 14 PCPs (4 individual interviews and 3 focus groups) who had worked at both safety net and non-safety net primary care clinics in Minneapolis-St Paul Minnesota USA metropolitan area. Qualitative analyses identified major themes.ResultsThree themes with sub-themes emerged. Theme #1: Minnesota’s current clinic quality scores are influenced more by patients and clinic systems than by clinicians. Theme #2: Collecting data for a set of specific quality measures is not the same as measuring quality healthcare. Subtheme #2.1: Current quality measures are not aligned with how patients and clinicians define quality healthcare. Theme #3: Current quality measures are a product of and embedded in social and structural inequities in the American health care system. Subtheme #3.1: The current inequitable healthcare system should not be reinforced with financial payments. Subtheme #3.2: Health equity requires new metrics and a new healthcare system. Overall, PCPs felt that the current inequitable quality metrics should be replaced by different metrics along with major changes to the healthcare system that could produce greater health equity.ConclusionAligning payment with the current quality metrics could perpetuate and exacerbate social inequities and health disparities. Policymakers should consider PCPs’ perspectives and create a quality-payment framework that does not disadvantage patients who are affected by social and structural inequities as well as the clinics and providers who serve them.

Highlights

  • Quality metrics, pay for performance (P4P), and value-based payments are prominent aspects of the current and future American healthcare system

  • Our study aims were to identify primary care providers’ (PCPs) perspectives about 1) quality metrics at both safety net clinics (SNCs) and non-safety net clinics (NSNCs), 2) how clinic quality measures affect patients and patient care, and 3) how payment for quality measures may influence health care

  • Minnesotans who attend NSNCs are seen as being more able to act in concert with the quality measures because they generally have low burden of structural determinants of health (SDOH), have health insurance, and have literacy levels, education, and cultural backgrounds that are generally congruent with mainstream medical culture

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Summary

Introduction

Pay for performance (P4P), and value-based payments are prominent aspects of the current and future American healthcare system. Models have indicated that Medicare’s Merit Based Incentive Payment System (MIPS) may exacerbate existing disparities due to its focus on specific clinical outcomes with failure to measure other aspects of healthcare quality such as access to care or patient experience [10]. These currently unmeasured aspects of healthcare are often more important to minority and low-income patients [11] as healthcare quality perception differs across race, ethnicity, and language preference [12]. Medicare adjustment with a VBP Modifier could lead to exacerbation of racial and ethnic health care disparities due to inequitable payment differences to systems that serve higher-risk and lower- risk patient populations [13]

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