In 2020, Massachusetts Medicaid launched the Flexible Services Program (FSP) to fund housing and nutrition assistance services for beneficiaries in accountable care organizations. To evaluate the program's impact on health outcomes for beneficiaries with behavioral health conditions, we compared changes in total health care costs, hospitalizations, emergency department (ED) visits, primary care visits, and hospital readmissions among 6,575 FSP participants enrolled during the period 2020-23 with those of a comparison group of people who were eligible for but did not receive FSP services. We also conducted the analysis with a secondary comparison group of 6,419 similar beneficiaries enrolled in Medicaid managed care organizations that did not offer FSP services. Relative to the primary comparison group, per person health care costs for FSP participants were $2,117 lower six months after beginning the program and $3,260 lower at twelve months. ED visits were 5 percent lower and readmissions were 36 percent lower at twelve months among FSP participants compared with the primary comparison group. Analyses using the secondary comparison group found similar reductions in costs at six months after FSP initiation, larger cost reductions at twelve months, and similar twelve-month declines in readmissions. These findings support the continuation of housing assistance programs for Medicaid beneficiaries with behavioral health conditions.

IntroductionMedically tailored meals (MTMs) are home-delivered, nutritionally tailored meals designed for patients with complex or advanced diet-sensitive medical conditions and social stressors. Although MTM use can improve food security, diet quality, and health outcomes, and reduce overall healthcare use and cost, little is known about why patients enroll in, stay in, or withdraw from such programs.MethodsBetween June 2023 and May 2024, we explored factors related to MTM program completion or withdrawal using semi-structured qualitative interviews among 28 patient participants in a program run by the non-profit Community Servings. Half had completed the 6-month program (“completers”), and half had requested early discontinuance (“non-completers”). The interviews covered patient factors (health status, health goals, motivation to participate) and program characteristics (perceptions of the program overall, logistics, meal characteristics). Interviews were recorded and transcribed, and then coded using NVivo software. We used directed qualitative content analyses and included matrix coding queries to compare themes overall and between the groups.ResultsBoth completers and non-completers described enrolling to alleviate symptoms, regain physical function, and engage in desired activities. Many non-completers also focused on weight loss. Before joining, non-completers had been more enthusiastic about changing their diets, while completers were more interested in alleviating financial strain and the time and physical challenges associated with meal preparation. Both groups had very positive perceptions of the program. Both groups initially found the meals bland and portion sizes small, but completers more readily adapted to both taste and portion size. In contrast, among non-completers, taste was a reason for discontinuation for some. Other non-completers withdrew for “good reasons”: they felt better or their circumstances otherwise changed, making the meals seem unnecessary. Both groups found the experience of eating the meals to be educational, which supported sustained dietary changes.DiscussionThese novel findings explore patients’ reasons for starting, completing, and stopping MTMs. Findings suggest strategies to improve program completion, such as addressing expectations about weight outcomes, taste, and portion size. Our study demonstrates the value of patient feedback for learning how to improve program effectiveness.

Importance In 2023, the Massachusetts Medicaid and Children’s Health Insurance Program (MassHealth) required accountable care organizations (ACOs) to increase payments to primary care practices and shift to monthly payments, currently calibrated to historical revenues and enhanced practice capabilities, such as being staffed to address behavioral health needs. To prevent rewarding practices for avoiding difficult patients, future payments to primary care practices should reflect their patients’ apparent need. Objective To describe MassHealth’s initiative and a complexity-adjusted payment model. Design, Setting, and Participants This cross-sectional study of payment model development and performance was conducted between February 2022 and November 2024. Participants included all 2019 Massachusetts Medicaid managed-care eligible members who were enrolled for 183 days or longer. Exposures Medical and social complexity. Main Outcomes and Measures For each member, the primary care activity level (PCAL) outcome proxies the resources that primary care clinicians need to provide comprehensive, coordinated care. Models were evaluated via R 2 and through ratios of observed-to-expected (ie, estimated by the model) outcomes for selected subgroups, which will be approximately 1.0 when payments and expected costs are well matched. The implications of paying practices using PCAL (vs a model based only on age and sex) were explored by examining financial and practice-level characteristics in high and low deciles of practice-level estimated mean. Results Among 1 092 742 MassHealth members enrolled in 3602 primary care practices (1 014 252 person-years; mean [SD] age, 25.9 [18.4] years; 538 065 [53.1%] female), the PCAL model achieved R 2 = 69.6% and estimates within 10% of observed PCAL spending for high-risk populations (mental health disorders, substance use disorders, complex chronic conditions, and disabilities) and across racial and ethnic groups. Age-adjusted and sex-adjusted payments would overpay practices in the lowest-need decile by 10% and underpay those in the highest-need decile by 34%, while the PCAL model would match payment to estimated need almost exactly in the lowest decile and underpay by just 6% in the highest decile. Conclusions and Relevance MassHealth’s 2023 reform invests in primary care. This cross-sectional study developed a risk model that can adjust primary care payments to patient needs. Neither age and sex adjustments nor inflated historical payments would provide adequate resources to primary care practices caring for the most complex patients.

BACKGROUND:More than 1 million total knee arthroplasties (TKAs) are performed annually in the United States to reduce knee pain, restore physical function, and enhance quality of life. However, nearly 1 in 5 patients are not satisfied after 1 year. We aimed to compare patient satisfaction with the U.S. Centers for Medicare & Medicaid Services (CMS) definition of success in TKA. METHODS:We studied a multicenter cohort of patients undergoing primary unilateral TKA, comparing patient satisfaction with CMS-defined surgery success, which is a minimum 20-point improvement in the Knee Injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS JR, scored 0 to 100) at 1 year. We cross-classified surgeries by satisfaction and success and used multivariable logistic regression to identify factors associated with satisfied patients being deemed as having undergone surgeries that failed. RESULTS:We studied 8,444 patients with a mean age of 68 years (with patients grouped by age: 30 to 64 years and 65 to 95 years). Of the patients, 67% were women and 60% were obese. With regard to the patients' race and/or ethnicity, 81% were White, 17% were Black, 1% were Asian, 0.6% were Native American or Alaskan Native, and 0.3% were native Hawaiian or other Pacific Islander. Although 84% of all patients reported satisfaction with the surgery, only 64% of surgeries were deemed successful. Among satisfied patients, only 71% underwent a surgery that was deemed to be successful, and discordance depended strongly on their baseline score. For satisfied patients with the worst baseline status (KOOS JR of <40), the CMS deemed the surgeries to be successful 91% of the time. In contrast, for satisfied patients with better baseline status (KOOS JR of ≥60), the CMS determined that only 39% of the surgeries were successful. Surgical failure in satisfied patients was also associated with younger age, back pain, contralateral knee pain, lower health literacy, diabetes, and poorer mental health. Including the baseline KOOS JR in the model significantly increased predictive accuracy (the area under the receiver operating characteristic curve rose from 0.58 to 0.79). CONCLUSIONS:We found substantial discordance between patients' satisfaction with the procedure and how the CMS currently assesses TKA success. A graded success metric, risk-adjusted for patients' baseline status, would align better with satisfaction. It is also worth exploring whether adding a few questions on joint-specific pain and function could better capture meaningful changes in patients whose high baseline status leaves little room for improvement on the KOOS JR. LEVEL OF EVIDENCE:Therapeutic Level III . See Instructions for Authors for a complete description of levels of evidence.

IntroductionMedically tailored meals (MTMs) are home-delivered, nutritionally tailored meals for individuals living with complex or advanced diet-sensitive medical conditions. In 2020, Massachusetts Medicaid implemented the Flexible Services Program (FSP) through a Section 1115 Demonstration, which funded novel nutrition programs, including MTMs, for high-risk patients through Accountable Care Organizations (ACOs). Little is known from the practitioners’ perspective regarding the facilitators and barriers to reaching and enrolling patients in MTM programs.MethodsWe interviewed 19 staff across four ACOs that had implemented MTM interventions. Interviews were conducted from Feb to Aug 2023 and included staff who participated in patient screening, referral, or enrollment. The interview guide was informed by the Health Equity Implementation Framework. Interviews were recorded and transcribed and coded using NVivo software. We used directed qualitative content analyses. The study team identified and discussed common themes and presented them back to our ACO partners.ResultsStaff described facilitators of and barriers to reach and enrollment related to several domains of the Health Equity Implementation Framework. For program (innovation) factors, facilitators included perceived positive effects on patient health outcomes and a relative advantage over both the status quo and other nutrition assistance programs; outreach by care team members rather than other staff; the eligibility criteria, which were viewed as appropriate and evidence-based; and the simplicity of the program, which aided communication with patients. Patient-related facilitators included patients being more in need of the program due to more severe illness and being more motivated to change dietary behaviors. Patient-related barriers included lacking a working phone or stable housing and concern about meals meeting taste and cultural food preferences. Staff-related barriers included limited time and especially knowledge about the MTM program.DiscussionThis study highlights the perspectives of front-line staff during the implementation of an MTM program in a state-wide 1,115 Demonstration. Staff may require multiple trainings to gain full knowledge about the program and increase self-efficacy in describing it with sensitivity. These new findings elevate voices from front-line healthcare staff in MTM delivery and can help inform strategies for effective, equitable implementation of MTM programs.

The Massachusetts Medicaid and Children's Health Insurance Program launched the Flexible Services Program to address food insecurity through partnerships with social service organizations under its Section 1115 demonstration waiver. We evaluated the effects of Flexible Services Program nutritional services (or Food Is Medicine programs) on health care use and costs during the first three-year program cycle (January 2020-March 2023). Our analyses pooled data on 20,403 Flexible Services Program participants from seventeen accountable care organizations. In propensity score-weighted analyses, program participation was associated with a 23 percent reduction in hospitalizations and a 13 percent reduction in emergency department visits compared with the number of hospitalizations and visits for 2,108 eligible nonparticipants. Modestly lower health care costs for Flexible Services Program participants were not statistically significant. Health care costs were $1,721 lower among participants after the COVID-19 emergency (2022-23) and $2,502 lower among adults with more than ninety days of enrollment during all study years (2020-23). These findings are important for Medicaid policy nationwide as other state Medicaid programs pursue similar Section 1115 demonstrations.

ImportanceModels predicting health care spending and other outcomes from administrative records are widely used to manage and pay for health care, despite well-documented deficiencies. New methods are needed that can incorporate more than 70 000 diagnoses without creating undesirable coding incentives.ObjectiveTo develop a machine learning (ML) algorithm, building on Diagnostic Item (DXI) categories and Diagnostic Cost Group (DCG) methods, that automates development of clinically credible and transparent predictive models for policymakers and clinicians.Design, Setting, and ParticipantsDXIs were organized into disease hierarchies and assigned an Appropriateness to Include (ATI) score to reflect vagueness and gameability concerns. A novel automated DCG algorithm iteratively assigned DXIs in 1 or more disease hierarchies to DCGs, identifying sets of DXIs with the largest regression coefficient as dominant; presence of a previously identified dominating DXI removed lower-ranked ones before the next iteration. The Merative MarketScan Commercial Claims and Encounters Database for commercial health insurance enrollees 64 years and younger was used. Data from January 2016 through December 2018 were randomly split 90% to 10% for model development and validation, respectively. Deidentified claims and enrollment data were delivered by Merative the following November in each calendar year and analyzed from November 2020 to January 2024.Main Outcome and MeasuresConcurrent top-coded total health care cost. Model performance was assessed using validation sample weighted least-squares regression, mean absolute errors, and mean errors for rare and common diagnoses.ResultsThis study included 35 245 586 commercial health insurance enrollees 64 years and younger (65 901 460 person-years) and relied on 19 clinicians who provided reviews in the base model. The algorithm implemented 218 clinician-specified hierarchies compared with the US Department of Health and Human Services (HHS) hierarchical condition category (HCC) model’s 64 hierarchies. The base model that dropped vague and gameable DXIs reduced the number of parameters by 80% (1624 of 3150), achieved an R2 of 0.535, and kept mean predicted spending within 12% ($3843 of $31 313) of actual spending for the 3% of people with rare diseases. In contrast, the HHS HCC model had an R2 of 0.428 and underpaid this group by 33% ($10 354 of $31 313).Conclusions and RelevanceIn this study, by automating DXI clustering within clinically specified hierarchies, this algorithm built clinically interpretable risk models in large datasets while addressing diagnostic vagueness and gameability concerns.

Asthma is the most common chronic disease in children, disproportionately affects families with lower incomes, and is a leading reason for acute care visits and hospitalizations. This retrospective cohort study used the Massachusetts All Payer Claims Database (2014-2018) to examine differences in acute care utilization and quality of care for asthma between Medicaid- and privately insured children in Massachusetts. Outcomes included acute care use (emergency department [ED] or hospitalization), ED visits with asthma, routine asthma visits, and filled prescriptions for asthma medications. Multivariable logistic regression was used to account for differences in demographics, ZIP codes, health status, and asthma severity. Overall, 10.0% of Medicaid-insured children and 5.6% of privately insured were classified as having asthma. Among 317,596 child-year observations for children with asthma, 64.4% were insured by Medicaid. Medicaid-insured children had higher rates of any acute care use (50.4% vs. 30.0%) and ED visits with an asthma diagnosis (27.2% vs. 13.3%) compared to privately insured children. Only 65.4% of Medicaid enrollees had at least one routine asthma visit compared to 74.3% of privately insured children. Most children received at least one asthma medication (88.6% Medicaid vs. 83.3% privately insured), but a higher percentage of Medicaid-insured children received at least one rescue medication (84.0% vs. 73.7%), and a lower percentage of Medicaid-insured (46.1% vs. 49.2%) received a controller medication. These results suggest that opportunities for improvement in childhood asthma persist, particularly for children insured by Medicaid.

Importance:Nearly 6 million children in the US have asthma, and over one-third of US children are insured by Medicaid. Although 23 state Medicaid programs have experimented with accountable care organizations (ACOs), little is known about ACOs' effects on longstanding insurance-based disparities in pediatric asthma care and outcomes. Objective:To determine associations between Massachusetts Medicaid ACO implementation in March 2018 and changes in care quality and use for children with asthma. Design, Setting, and Participants:Using data from the Massachusetts All Payer Claims Database from January 1, 2014, to December 31, 2020, we determined child-years with asthma and used difference-in-differences (DiD) estimates to compare asthma quality of care and emergency department (ED) or hospital use for child-years with Medicaid vs private insurance for 3 year periods before and after ACO implementation for children aged 2 to 17 years. Regression models accounted for demographic and community characteristics and health status. Data analysis was conducted between January 2022 and June 2024. Exposure:Massachusetts Medicaid ACO implementation. Main Outcomes and Measures:Primary outcomes were binary measures in a calendar year of (1) any routine outpatient asthma visit, (2) asthma medication ratio (AMR) greater than 0.5, and (3) any ED or hospital use with asthma. To determine the statistical significance of differences in descriptive statistics between groups, χ2 and t tests were used. Results:Among 376 509 child-year observations, 268 338 (71.27%) were insured by Medicaid and 73 633 (19.56%) had persistent asthma. There was no significant change in rates of routine asthma visits for Medicaid-insured child-years vs privately insured child-years post-ACO implementation (DiD, -0.4 percentage points [pp]; 95% CI, -1.4 to 0.6 pp). There was an increase in the proportion with AMR greater than 0.5 for Medicaid-insured child-years vs privately insured in the postimplementation period (DiD, 3.7 pp; 95% CI, 2.0-5.4 pp), with absolute declines in both groups postimplementation. There was an increase in any ED or hospital use for Medicaid-insured child-years vs privately insured postimplementation (DiD, 2.1 pp; 95% CI, 1.2-3.0 pp), an 8% increase from the preperiod Medicaid use rate. Conclusions and Relevance:Introduction of Massachusetts Medicaid ACOs was associated with persistent insurance-based disparities in routine asthma visit rates; a narrowing in disparities in appropriate AMR rates due to reductions in appropriate rates among those with private insurance; and worsening disparities in any ED or hospital use for Medicaid-insured children with asthma compared to children with private insurance. Continued study of changes in pediatric asthma care delivery is warranted in relation to major Medicaid financing and delivery system reforms.

ImportanceAlthough children with asthma are often successfully treated by primary care clinicians, outpatient specialist care is recommended for those with poorly controlled disease. Little is known about differences in specialist use for asthma among children with Medicaid vs private insurance.ObjectiveTo examine differences among children with asthma regarding receipt of asthma specialist care by insurance type.Design, Setting, and ParticipantsIn this cross-sectional study using data from the Massachusetts All Payer Claims Database (APCD) between 2014 to 2020, children with asthma were identified and differences in receipt of outpatient specialist care by whether their insurance was public (Medicaid and the Children’s Health Insurance Program) or private were examined. Eligible participants included children with asthma in 2015 to 2020 aged 2 to 17 years. Data analysis was conducted from January 2023 to April 2024.ExposureMedicaid vs private insurance.Main Outcomes and MeasuresThe primary outcome was receipt of specialist care (any outpatient visit with a pulmonology, allergy and immunology, or otolaryngology physician). Multivariable logistic regression models estimated differences in receipt of specialist care by insurance type accounting for child and area characteristics including demographics, health status, persistent asthma, calendar year, and zip code characteristics. Additional analyses examined if the associations of specialist care with insurance type varied by asthma persistence and severity, and whether associations varied over time.ResultsAmong 198 101 unique children, there were 432 455 child-year observations (186 296 female [43.1%] and 246 159 male [56.9%]; 211 269 aged 5 to 11 years [48.9%]; 82 108 [19.0%] with persistent asthma) including 286 408 (66.2%) that were Medicaid insured and 146 047 (33.8%) that were privately insured. Although persistent asthma was more common among child-year observations with Medicaid vs private insurance (57 381 [20.0%] vs 24 727 [16.9%]), children with Medicaid were less likely to receive specialist care. Overall, 64 239 child-year observations (14.9%) received specialist care, with substantially lower rates for children with Medicaid vs private insurance (34 093 child-year observations [11.9%] vs 30 146 child-year observations [20.6%]). Regression-based estimates confirmed these disparities; children with Medicaid had 55% lower odds of receiving specialist care (adjusted odds ratio, 0.45; 95% CI, 0.43 to 0.47) and a regression-adjusted 9.7 percentage point (95% CI, −10.4 percentage points to −9.1 percentage points) lower rate of receipt of specialist care. Compared with children with private insurance, there was an additional 3.2 percentage point (95% CI, 2.0 percentage points to 4.4 percentage points) deficit for children with Medicaid with persistent asthma.Conclusions and RelevanceIn this cross-sectional study, children with Medicaid were less likely to receive specialist care, with the largest gaps among those with persistent asthma. These findings suggest that closing this care gap may be one approach to addressing ongoing disparities in asthma outcomes.

Background: Palliative care can enhance quality of life during a terminal hospitalization. Despite advances in diagnostic and treatment tools, blood cancers lag behind solid malignancies in palliative use. It is not clear what factors affect palliative care use in blood cancer. Methods: We used the 2016 to 2019 National Inpatient Sample to identify demographic and socioeconomic factors associated with receiving palliative care among patients over age 18 with any malignant hematological diagnosis during a terminal hospitalization lasting at least 3 days, excluding those receiving a stem cell transplant. Results: Palliative care use was documented 54% of the time among 49,720 weighted cases (9944 distinct individual hospitalizations), approximately evenly distributed across the years 2016-2019. Palliative care use was lowest in 2016 (51%) and highest in 2018 (58%), and increased with age, reaching 58% for those 80 years and older. Men and women were similarly likely to receive care. Patients of Hispanic ethnicity and African Americans received less palliative care (47% and 49%, respectively), as did those insured by Medicaid (48%), and those admitted to small or rural hospitals (52% and 47%, respectively). Charges for hospitalizations with palliative care were 19% lower than for those without it. Conclusions: This study highlights disparities in palliative care use among blood-cancer patients who died in the hospital. It seems likely that many of the 46% who did not receive palliative care could have benefitted from it. Interventions are likely needed to achieve equitable access to ideal levels of palliative care services in late-stage blood cancer.

The existing literature has considered accountable care organizations (ACOs) as whole entities, neglecting potentially important variations in the characteristics and experiences of the individual practice sites that comprise them. In this observational cross-sectional study, our aim is to characterize the experience, capacity, and process heterogeneity at the practice site level within and between Medicaid ACOs, drawing on the Massachusetts Medicaid and Children’s Health Insurance Program (MassHealth), which launched an ACO reform effort in 2018. We used a 2019 survey of a representative sample of administrators from practice sites participating in Medicaid ACOs in Massachusetts (n = 225). We quantified the clustering of responses by practice site within all 17 Medicaid ACOs in Massachusetts for measures of process change, previous experience with alternative payment models, and changes in the practices’ ability to deliver high-quality care. Using multilevel logistic models, we calculated median odds ratios (MORs) and intraclass correlation coefficients (ICCs) to quantify the variation within and between ACOs for each measure. We found greater heterogeneity within the ACOs than between them for all measures, regardless of practice site and ACO characteristics (all ICCs ≤ 0.26). Our research indicates diverse experience with, and capacity for, implementing ACO initiatives across practice sites in Medicaid ACOs. Future research and program design should account for characteristics of practice sites within ACOs.

BACKGROUND:When performed well on appropriate patients, total knee arthroplasty (TKA) can dramatically improve quality of life. Patient-reported outcome measures (PROMs) are increasingly used to measure outcome following TKA. Accurate prediction of improvement in PROMs after TKA potentially plays an important role in judging the surgical quality of the health-care institutions as well as informing preoperative shared decision-making. Starting in 2027, the U.S. Centers for Medicare & Medicaid Services (CMS) will begin mandating PROM reporting to assess the quality of TKAs. METHODS:Using data from a national cohort of patients undergoing primary unilateral TKA, we developed an original model that closely followed a CMS-proposed measure to predict success, defined as achieving substantial clinical benefit, specifically at least a 20-point improvement on the Knee injury and Osteoarthritis Outcome Score, Joint Arthroplasty (KOOS, JR) at 1 year, and an enhanced model with just 1 additional predictor: the baseline KOOS, JR. We evaluated each model's performance using the area under the receiver operator characteristic curve (AUC) and the ratio of observed to expected (model-predicted) outcomes (O:E ratio). RESULTS:We studied 5,958 patients with a mean age of 67 years; 63% were women, 93% were White, and 87% were overweight or obese. Adding the baseline KOOS, JR improved the AUC from 0.58 to 0.73. Ninety-four percent of those in the top decile of predicted probability of success under the enhanced model achieved success, compared with 34% in its bottom decile. Analogous numbers for the original model were less discriminating: 77% compared with 57%. Only the enhanced model predicted success accurately across the spectrum of baseline scores. The findings were virtually identical when we replicated these analyses on only patients ≥65 years of age. CONCLUSIONS:Adding a baseline knee-specific PROM score to a quality measurement model in a nationally representative cohort dramatically improved its predictive power, eliminating ceiling and floor effects and mispredictions for readily identifiable patient subgroups. The enhanced model neither favors nor discourages care for those with greater knee dysfunction and requires no new data collection. LEVEL OF EVIDENCE:Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.

OBJECTIVE:Annual influenza vaccination rates for children remain well below the Healthy People 2030 target of 70%. We aimed to compare influenza vaccination rates for children with asthma by insurance type and to identify associated factors.METHODS:This cross-sectional study examined influenza vaccination rates for children with asthma by insurance type, age, year, and disease status using the Massachusetts All Payer Claims Database (2014-2018). We used multivariable logistic regression to estimate the probability of vaccination accounting for child and insurance characteristics.RESULTS:The sample included 317,596 child-year observations for children with asthma in 2015-18. Fewer than half of children with asthma received influenza vaccinations; 51.3% among privately insured and 45.1% among Medicaid insured. Risk modeling reduced, but did not eliminate, this gap; privately insured children were 3.7 percentage points (pp) more likely to receive an influenza vaccination than Medicaid-insured children (95% confidence interval [CI]: 2.9-4.5pp). Risk modeling also found persistent asthma was associated with more vaccinations (6.7pp higher; 95% CI: 6.2-7.2pp), as was younger age. The regression-adjusted probability of influenza vaccination in a non-office setting was 3.2pp higher in 2018 than 2015 (95% CI: 2.2-4.2pp), and significantly lower for children with Medicaid.CONCLUSIONS:Despite clear recommendations for annual influenza vaccinations for children with asthma, low rates persist, particularly for children with Medicaid. Offering vaccines in non-office settings such as retail pharmacies may reduce barriers, but we did not observe increased vaccination rates in the first years after this policy change.

Letters Health AffairsVol. 42, No. 5: Markets, Payments & More Risk Adjustment And Health Equity: The Authors ReplyJ. Michael McWilliams, Gabe Weinreb, Chima D. Ndumele, and Jacob Wallace Affiliations Harvard University and Brigham and Women’s Hospital Boston, Massachusetts Harvard University Boston, Massachusetts Yale University New Haven, ConnecticutPUBLISHED:May 2023No Accesshttps://doi.org/10.1377/hlthaff.2023.00297AboutSectionsView articleView Full TextSupplemental MaterialView PDFPermissions ShareShare onFacebookTwitterLinked InRedditEmail ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions View article"Risk Adjustment And Health Equity: The Authors Reply." Health Affairs, 42(5), p. 732TOPICSRisk adjustmentHealth equityPayment Loading Comments... Please enable JavaScript to view the comments powered by Disqus. DetailsExhibitsReferencesRelated Supplemental Materials Article Metrics History Published online 1 May 2023 Information© 2023 Project HOPE—The People-to-People Health Foundation, Inc.PDF download

A long history of discriminatory policies in the United States has created disparities in neighborhood resources that shape ethnoracial health inequities today. To quantify these differences, we organized publicly available data on forty-two variables at the census tract level within nine domains affected by structural racism: built environment, criminal justice, education, employment, housing, income and poverty, social cohesion, transportation, and wealth. Using data from multiple sources at several levels of geography, we developed scores in each domain, as well as a summary score that we call the Structural Racism Effect Index. We examined correlations with life expectancy and other measures of health for this index and other commonly used area-based indices. The Structural Racism Effect Index was more strongly associated with each health outcome than were the other indices. Its domain and summary scores can be used to describe differences in social risk factors, and they provide powerful new tools to guide policies and investments to advance health equity.

Background Secure messaging use is associated with improved diabetes-related outcomes. However, it is less clear how secure messaging supports diabetes management. Objective We examined secure message topics between patients and clinical team members in a national sample of veterans with type 2 diabetes to understand use of secure messaging for diabetes management and potential associations with glycemic control. Methods We surveyed and analyzed the content of secure messages between 448 US Veterans Health Administration patients with type 2 diabetes and their clinical teams. We also explored the relationship between secure messaging content and glycemic control. Results Explicit diabetes-related content was the most frequent topic (72.1% of participants), followed by blood pressure (31.7% of participants). Among diabetes-related conversations, 90.7% of patients discussed medication renewals or refills. More patients with good glycemic control engaged in 1 or more threads about blood pressure compared to those with poor control (37.5% vs 27.2%, P=.02). More patients with good glycemic control engaged in 1 more threads intended to share information with their clinical team about an aspect of their diabetes management compared to those with poor control (23.7% vs 12.4%, P=.009). Conclusions There were few differences in secure messaging topics between patients in good versus poor glycemic control. Those in good control were more likely to engage in informational messages to their team and send messages related to blood pressure. It may be that the specific topic content of the secure messages may not be that important for glycemic control. Simply making it easier for patients to communicate with their clinical teams may be the driving influence between associations previously reported in the literature between secure messaging and positive clinical outcomes in diabetes.

ImportanceThe first MassHealth Social Determinants of Health payment model boosted payments for groups with unstable housing and those living in socioeconomically stressed neighborhoods. Improvements were designed to address previously mispriced subgroups and promote equitable payments to MassHealth accountable care organizations (ACOs).ObjectiveTo develop a model that ensures payments largely follow observed costs for members with complex health and/or social risks.Design, Setting, and ParticipantsThis cross sectional study used administrative data for members of the Massachusetts Medicaid program MassHealth in 2016 or 2017. Participants included members who were eligible for MassHealth’s managed care, aged 0 to 64 years, and enrolled for at least 183 days in 2017. A new total cost of care model was developed and its performance compared with 2 earlier models. All models were fit to 2017 data (most recent available) and validated on 2016 data. Analyses were begun in February 2019 and completed in January 2023.ExposuresModel 1 used age-sex categories, a diagnosis-based morbidity relative risk score (RRS), disability, serious mental illness, substance use disorder, housing problems, and neighborhood stress. Model 2 added an interaction for unstable housing with RRS. Model 3 added rurality and updated diagnosis-based RRS, medication-based RRS, and interactions between sociodemographic characteristics and morbidity.Main Outcome and MeasuresTotal 2017 annual cost was modeled and overall model performance (R2) and fair pricing of subgroups evaluated using observed-to-expected (O:E) ratios.ResultsAmong 1 323 424 members, mean (SD) age was 26.4 (17.9) years, 53.4% were female (46.6% male), and mean (SD) 2017 cost was $5862 ($15 417). The R2 for models 1, 2, and 3 was 52.1%, 51.5%, and 60.3%, respectively. Earlier models overestimated costs for members without behavioral health conditions (O:E ratios 0.94 and 0.93 for models 1 and 2, respectively) and underestimated costs for those with behavioral health conditions (O:E ratio >1.10); model 3 O:E ratios were near 1.00. Model 3 was better calibrated for members with housing problems, those with children, and those with high morbidity scores. It reduced underpayments to ACOs whose members had high medical and social complexity. Absolute and relative model performance were similar in 2016 data.Conclusions and RelevanceIn this cross-sectional study of data from Massachusetts Medicaid, careful modeling of social and medical risk improved model performance and mitigated underpayments to safety-net systems.