Publications by Year: 2020

BACKGROUND: The inclusion of Z-codes for social determinants of health (SDOH) in the 10th revision of the International Classification of Diseases (ICD-10) may offer an opportunity to improve data collection of SDOH, but no characterization of their utilization exists on a national all-payer level.

OBJECTIVE: To examine the prevalence of SDOH Z-codes and compare characteristics of patients with and without Z-codes and hospitals that do and do not use Z-codes.

RESEARCH DESIGN: Retrospective cohort study using 2016 and 2017 National Inpatient Sample.

PARTICIPANTS: Total of 14,289,644 inpatient hospitalizations.

MEASURES: Prevalence of SDOH Z-codes (codes Z55-Z65) and descriptive statistics of patients and hospitals.

RESULTS: Of admissions, 269,929 (1.9%) included SDOH Z-codes. Average monthly SDOH Z-code use increased across the study period by 0.01% per month (P<0.001). The cumulative number and proportion of hospitals that had ever used an SDOH Z-code also increased, from 1895 hospitals (41%) in January 2016 to 3210 hospitals (70%) in December 2017. Hospitals that coded at least 1 SDOH Z-code were larger, private not-for-profit, and urban teaching hospitals. Compared with admissions without an SDOH Z-code, admissions with them were for patients who were younger, more often male, Medicaid recipients or uninsured. A higher proportion of admissions with SDOH Z-codes were for mental health (44.0% vs. 3.3%, P<0.001) and alcohol and substance use disorders (9.6% vs. 1.1%, P<0.001) compared with those without.

CONCLUSIONS: The uptake of SDOH Z-codes has been slow, and current coding is likely poorly reflective of the actual burden of social needs experienced by hospitalized patients.

To understand how clinicians with high caseloads of socially at-risk patients fare under Medicare's new outpatient Merit-based Incentive Payment System (MIPS), we examined the first (2019) round of MIPS performance data for 510,020 clinicians. Compared with clinicians with the lowest socially at-risk caseloads, those with the highest had 13.4 points lower MIPS performance scores, were 99 percent more likely to receive a negative payment adjustment, and were 52 percent less likely to receive an exceptional performance bonus payment. The lower performance scores were partly explained by lower clinician reporting of and performance on technology-dependent measures, which may reflect a lack of practice-level technological capability. If the Complex Patient Bonus were in effect, the performance scores and likelihood of receiving an exceptional performance bonus (payment of clinicians with the highest socially at-risk caseloads) would have increased by 4.7 percent and 2.8 percent, respectively; however, the proportion receiving negative payment adjustments would have remained unchanged. The Complex Patient Bonus appears unlikely to mitigate the most regressive effects of MIPS.

OBJECTIVE: Certain antihyperglycemic therapies modify cardiovascular and kidney outcomes among patients with type 2 diabetes, but early uptake in practice appears restricted to particular demographics. We examine the association of Medicaid expansion with use of and expenditures related to antihyperglycemic therapies among Medicaid beneficiaries.

RESEARCH DESIGN AND METHODS: We employed a difference-in-difference design to analyze the association of Medicaid expansion on prescription of noninsulin antihyperglycemic therapies. We used 2012-2017 national and state Medicaid data to compare prescription claims and costs between states that did (n = 25) and did not expand (n = 26) Medicaid by January 2014.

RESULTS: Following Medicaid expansion in 2014, average noninsulin antihyperglycemic therapies per state/1,000 enrollees increased by 4.2%/quarter in expansion states and 1.6%/quarter in nonexpansion states. For sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP-1RA), quarterly growth rates per 1,000 enrollees were 125.3% and 20.7% for expansion states and 87.6% and 16.0% for nonexpansion states, respectively. Expansion states had faster utilization of SGLT2i and GLP-1RA than nonexpansion states. Difference-in-difference estimates for change in volume of prescriptions after Medicaid expansion between expansion versus nonexpansion states was 1.68 (95% CI 1.09-2.26; P < 0.001) for all noninsulin therapies, 0.125 (-0.003 to 0.25; P = 0.056) for SGLT2i, and 0.12 (0.055-0.18; P < 0.001) for GLP-1RA.

CONCLUSIONS: Use of noninsulin antihyperglycemic therapies, including SGLT2i and GLP-1RA, increased among low-income adults in both Medicaid expansion and nonexpansion states, with a significantly greater increase in overall use and in GLP-1RA use in expansion states. Future evaluation of the population-level health impact of expanded access to these therapies is needed.

Massachusetts has one of the highest cumulative incidence rates of coronavirus disease 2019 (COVID-19) cases in the US. Understanding which specific demographic, economic, and occupational factors have contributed to disparities in COVID-19 incidence rates across the state is critical to informing public health strategies. We performed a cross-sectional study of 351 Massachusetts cities and towns from January 1 to May 6, 2020, and found that a 10-percentage-point increase in the Black non-Latino population was associated with an increase of 312.3 COVID-19 cases per 100,000 population, whereas a 10-percentage-point increase in the Latino population was associated with an increase of 258.2 cases per 100,000. Independent predictors of higher COVID-19 rates included the proportion of foreign-born noncitizens living in a community, mean household size, and share of food service workers. After adjustment for these variables, the association between the Latino population and COVID-19 rates was attenuated. In contrast, the association between the Black population and COVID-19 rates persisted but may be explained by other systemic inequities. Public health and policy efforts that improve care for foreign-born noncitizens, address crowded housing, and protect food service workers may help mitigate the spread of COVID-19 among minority communities.

IMPORTANCE: Medicare Advantage (MA), a private insurance plan option, now covers one-third of all Medicare beneficiaries. Although patients with cardiovascular disease enrolled in MA have been reported to receive higher quality of care in the ambulatory setting than patients enrolled in fee-for-service (FFS) Medicare, it is unclear whether MA is associated with higher quality in patients hospitalized with heart failure, or alternatively, if incentives to reduce utilization under MA plans may be associated with worse care.

OBJECTIVE: To determine whether there are differences in quality of care received and in-hospital outcomes among patients enrolled in MA vs FFS Medicare.

DESIGN, SETTING, AND PARTICIPANTS: Observational, retrospective cohort study of patients hospitalized with heart failure in hospitals participating in the Get With the Guidelines-Heart Failure registry.

EXPOSURES: Medicare Advantage enrollment.

MAIN OUTCOMES AND MEASURES: In-hospital mortality, discharge disposition, length of stay, and 4 heart failure achievement measures.

RESULTS: Of 262 626 patients hospitalized with heart failure, 93 549 (35.6%) were enrolled in MA and 169 077 (64.4%) in FFS Medicare. The median (interquartile range) age was 78 (70-85) years for patients enrolled in MA and 78 (69-86) years for patients enrolled in FFS Medicare. Standard mean differences in age, sex, prevalence of comorbidities, or objective measures on admission, including vital signs and laboratory values, were less than 10%. After adjustment, there were no statistically significant differences in receipt of evidence-based β-blockers when indicated; angiotensin-converting enzyme inhibitor, angiotensin II receptor blockers, or angiotensin receptor-neprilysin inhibitors at discharge; measurement of left ventricular function; and postdischarge appointments by Medicare insurance type. Patients enrolled in MA, however, had higher odds of being discharged directly home (adjusted odds ratio [AOR], 1.16; 95% CI, 1.13-1.19; P < .001) relative to patients enrolled in FFS Medicare and lower odds of being discharged within 4 days (AOR, 0.97; 95% CI, 0.93-1.00; P = .04). There was no significant difference in in-hospital mortality between patients with MA and patients with FFS Medicare (AOR, 0.98; 95% CI, 0.92-1.03; P = .42).

CONCLUSIONS AND RELEVANCE: Among patients hospitalized with heart failure, no observable benefit was noted in quality of care or in-hospital mortality between those enrolled in MA vs FFS Medicare, except lower use of post-acute care facilities. As MA continues to grow, it will be important to ensure that participating private plans provide an added value to the patients they cover to justify the higher administrative costs compared with traditional FFS Medicare.

This study evaluates COVID-19 case rates between high- and low-performing nursing homes based on CMS quality measures.

In spring 2018, the American Heart Association convened the Value in Healthcare Summit to begin an important conversation about the challenges patients with cardiovascular disease face in accessing and deriving quality and value from the healthcare system. Following the summit and recognizing the collective momentum it created, the American Heart Association, in collaboration with the Robert J. Margolis Center for Health Policy at Duke University, launched the Value in Healthcare Initiative-Transforming Cardiovascular Care. Four areas of focus were identified, and learning collaboratives were established and proceeded to conduct concrete, actionable problem solving in 4 high-impact areas in cardiovascular care: Value-Based Models, Partnering with Regulators, Predict and Prevent, and Prior Authorization. The deliverables from these groups are being disseminated in 4 stand-alone articles, and their publication will initiate further work to test and evaluate each of these promising areas of reform. This article provides an overview of the initiative's findings and highlights key cross-cutting themes for consideration as the initiative moves forward.

BACKGROUND: Individuals experiencing homelessness have higher hospitalization and mortality rates compared with the housed. Whether they also experience higher readmission rates, and if readmissions vary by region or cause of hospitalization is unknown.

OBJECTIVE: Evaluate the association of homelessness with readmission rates across multiple US states.

DESIGN: Retrospective analysis of administrative claims PATIENTS: All inpatient hospitalizations in Florida, Massachusetts, and New York from January 2010 to October 2015 MAIN MEASURES: Thirty- and 90-day readmission rates KEY RESULTS: Out of a total of 23,103,125 index hospitalizations, 515,737 were for patients who were identified as homeless at the time of discharge. After adjusting for cause of index hospitalization, state, demographics, and clinical comorbidities, 30-day and 90-day readmission rates were higher for index hospitalizations in the homeless compared with those in the housed group. The difference in 30-day readmission rates between homeless and housed groups was the largest in Florida (30.4% vs. 19.3%; p < 0.001), followed by Massachusetts (23.5% vs. 15.2%; p < 0.001) and New York (15.7% vs. 13.4%; p < 0.001) (combined 17.3% vs. 14.0%; p < 0.001). Among the most common causes of hospitalization, 30-day readmission rates were 4.1 percentage points higher for the homeless group for mental illness, 4.9 percentage points higher for diseases of the circulatory system, and 2.4 percentage points higher for diseases of the digestive system.

CONCLUSIONS: After adjusting for demographic and clinical characteristics, homelessness is associated with significantly higher 30- and 90-day readmission rates, with a significant variation across the three states. Interventions to reduce the burden of readmissions among individuals experiencing homelessness are urgently needed. Differences across states point to the potential of certain public policies to impact health outcomes for individuals experiencing homelessness.