In a July 2022 Health Affairs Forefront blog, the Centers for Medicare & Medicaid (CMS) discussed its review of implicit bias in the Comprehensive Care for Joint Replacement (CJR) model. For its purpose, CMS defined implicit bias as unintentional differential care and/or treatment of certain racial and ethnic beneficiaries created by an algorithm, set of rules or processes within a model. The CJR aims to reduce the costs of lower-extremity joint replacement, while maintaining or improving patient outcomes. CMS found that financial incentives related to meeting episode-based target prices led providers to reduce costs by shifting patients to lower-cost settings (i.e., home health agencies) following joint replacement. However, CMS cited literature that has found that Black and low-income Medicare beneficiaries tend to use skilled nursing facilities (SNFs) and inpatient rehabilitation hospitals (IRFs) more than other patients following joint replacement surgery, making them potentially more expensive than their counterparts. Because CMS did not adjust spending targets for socioeconomic factors, it concluded that participating providers may have had a disincentive to offer joint replacement to Black and low-income beneficiaries.
In this blog, we explore the root causes of disparities in joint replacement and post-acute care (PAC) use among Black beneficiaries that could lead to higher use of SNFs and IRFs. We argue that a chain of factors leads to disparities in access and use of joint replacement treatment as well as the care setting following surgery.
Black beneficiaries and low-income populations may represent more severe cases when receiving joint replacement due to delays in accessing care
Prior to joint replacement surgery, Black patients present with more severe conditions, have more comorbidities, and, as a result, tend to be at greater risk for complications than their non-Black counterparts. There are documented differences in preferences for the elective joint replacement treatment, accessibility, and disease progression between Black individuals and non-Black individuals. Some studies have shown that poorer health status during surgery leads to slower and more difficult recovery. Another study showed that Black patients undergoing an elective total hip arthroplasty were more likely to require functional assistance than White patients. These findings are in line with observed longer hospital lengths of stay and non-home discharges following surgery for Black patients.
Factors other than financial concerns contribute to the underutilization of joint replacement among Black individuals
A study by KNG Health researchers found lower utilization of joint replacement in elderly Black individuals with osteoarthritis, particularly among Black women. In addition, the study found that lack of familial support at home contributes to lower rates of joint replacement for certain age and gender groups. Lack of familial support could also contribute to higher likelihood of utilizing institutional care post treatment, as these patients may need more support during recovery. While poverty status affects the utilization of joint replacement surgeries, it does not appear to completely explain lower rates of joint replacement among Black patients relative to White patients, given that disparities were observed for both Medicare-Medicaid eligible beneficiaries and Medicare-only patients. Moreover, for Medicare beneficiaries whose surgical expenses are covered by Medicare, disparities are less likely to be due to financial reasons.
The low use of joint replacement by Black individuals can also be traced to differences in preferences and lack of communication of the benefits related to surgical intervention (e.g., pain relief and impact on functional improvement). Preference-based discussions and shared decisionmaking tools, which explain the risk and benefits of surgical procedures, have been shown to increase uptake of knee replacement surgeries among Black individuals, who otherwise might have opted for conservative therapy. Finally, disparities in utilization might be related to access and other community-specific reasons, as fewer total hip and knee replacements were conducted in hospital service areas with higher proportions of Medicare-Medicaid enrollees and Black population.
Minorities more likely to utilize institutional PAC settings, such as IRFs and SNFs
After joint replacement, Black patients use more IRFs and SNFs, rather than home health (HH) care or home without PAC. As noted earlier, minorities may represent a sicker patient population, which would make them better candidates for institutionalized care. Shifting patients who may benefit from institutional post-acute care to HH may have negative consequences, as these patients care needs may not be met optimally at home, leading to poorer patient outcomes. Furthermore, not all patients referred to HH care receive that care. Another study with KNG Health researchers found that one-third of patients referred to HH after a hospital stay did not receive HH care. Patients with “incomplete HH care referrals” were more likely to be people of color, dual eligible, from non-rural communities, have higher prior utilization of health care, and have more comorbidities. Since people of color and dual-eligible patients may be at a greater risk of incomplete HH referrals, any efforts to reduce cost by shifting patients to low-cost PAC settings, such as HH, have the potential to increase disparities.
Implications for policy makers and health care in general
Policy makers must recognize that baseline treatment patterns may reflect pre-existing biases and disparities in a study population. It is essential to understand these existing disparities and the underlying causes of the inequities. When designing value-based payment models, designers must consider these inequities and develop approaches to either reduce or, at a minimum, not acerbate them.
CMS is focused on eliminating implicit bias in its alternative payment models and reducing disparities in access to beneficial treatments and outcomes. To be successful, CMS should move beyond just reshaping existing models that focus on the point of service but use population health approaches to reduce inequities in accessing appropriate care.
Services : Blog, Health Economics & Outcomes Research, Payment Policy & Delivery System Innovation, Quality & Performance Measurement Expertise: Comparative Effectiveness, Disparities, Health Outcomes and Evaluation, Healthcare Cost and Utilization, home health care, Medicare, Payment and Delivery System Innovation, post-acute care
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Inna Cintina is a Principal Research Associate in the Evaluation and Health Economics Practice. Dr. Cintina is an applied microeconomist with over a decade of research experience in the area of health economics. At KNG Health, Dr. Cintina is leading evaluations of the impact of managed care on high-need Medicare beneficiaries. Specifically, in work supported by a grant from Arnold Ventures, she is studying the distribution of high-need beneficiaries across enrollment types (Traditional Medicare, Accountable Care Organization (ACOs); and Medicare Advantage (MA)), healthcare services utilization and health outcomes in high-need beneficiaries attributed to ACOs relative to those in MA; and characteristics of MA plans associated with better health outcomes among enrollees. In other work, she studied disparities in utilization of new cardio- and neuro-vascular technologies and impacts of post-acute care settings on beneficiary outcomes. She is an expert in using matching techniques, difference-in-difference methodologies, and other quasi-experimental statistical approaches, as well as producing client-oriented materials, white papers, and manuscripts. She has authored/co-authored more than a dozen articles, which have been published in peer-reviewed journals such as World Bank Economic Review, Health Economics, JAMA, Value in Health, and the American Journal of Managed Care. Prior to joining KNG Health, Dr. Cintina worked at the Lewin Group/OptumServe and the University of Hawaii at Manoa. She has extensive experience in developing and implementing methodologies for identification of causal relationships, advanced analytics, project management, economic burden/cost of illness studies, and impact evaluations of alternative payment models, such as CMMI’s Bundled Payments for Care Improvement Initiative and Oncology Care Model. Dr. Cintina has a PhD in economics from Clemson University, a MSC in European Economics and Public Affairs from University College Dublin, and an MA and a BA in economics from the University of Latvia. |
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Lane Koenig is President and Founder of KNG Health Consulting and Director of the Healthcare Reform and Payment Innovation Practice. He is a healthcare economist with over 20 years’ experience in the public and private sectors. As President of KNG Health Consulting, Dr. Koenig has overall responsibility for the quality and direction of KNG Health’s research. He serves as Project Director and Principal Investigator for many studies, particularly those related to healthcare reform proposals, healthcare provider payments, value-based purchasing, and delivery system innovations. With expertise on hospital and post-acute care payment and quality issues, his work regularly assesses the potential impact on hospitals and other providers of proposed legislation or regulations. He has assisted both industry and Federal and state governments in the development and assessment of healthcare provider payment policies and value-base purchasing initiatives. Prior to founding KNG Health in 2007, Dr. Koenig was the senior economist in the Office of Policy at the Centers for Medicare & Medicaid Services (CMS). Before joining CMS, Dr. Koenig was a Senior Scientist in the healthcare finance practice at The Lewin Group. Dr. Koenig has led over 100 quantitative and qualitative health policy and health economic studies and has published over 20 peer-reviewed studies in journals, such as Health Affairs, Health Services Research, and Medical Care. He graduated with Honors from the University of Florida, Gainesville and earned his PhD in Economics from the University of Maryland, College Park. |
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Elizabeth Hamlett is a Senior Research Associate in the Evaluation and Health Economics practice at KNG Health. Ms. Hamlett has extensive experience in project management, the design and implementation of qualitative research (e.g., systematic literature reviews, surveys, and interviews), and in conducting analyses using Medicare inpatient and post-acute care claims data. Since joining KNG Health in 2015, her work has focused on evaluating the efficiency, effectiveness, and value of medical interventions, and supporting the Center for Medicare and Medicaid Services (CMS) Comprehensive Care for Joint Replacement model through learning system activities, such as dissemination of information and data analysis. Ms. Hamlett has experience performing quantitative analyses with a variety of health care data sources, namely Medicare claims and Maryland Health Services Cost Review Commission data. Specifically, she has performed facility-level and condition specific outcome analyses and provided statistical support to multiple pharmaceutical companies in obtaining approval for New Technology Add-on Payments. In addition, Ms. Hamlett has led the design and development of interactive spreadsheet models for multiple projects including the Medicare Payment Advisory Committee’s proposed Hospital Value Incentive Program (HVIP) and CMS State Innovations Model (SIM) Maryland All-Payer Model. She has also performed statistical evaluation of quality measures proposed for inclusion in CMS’ ASC Quality Reporting Program in terms of reliability, validity, feasibility, and interpretability based on data collected through pilot testing for the Ambulatory Surgery Center Quality Collaboration (ASC QC). Prior to joining KNG Health, Ms. Hamlett managed a social psychology laboratory and worked with the non-profit organization, the Dialysis Clinic. Ms. Hamlett earned a Bachelor of Science in policy analysis and management from Cornell University in 2015. |
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