Association of Patient Social, Cognitive, and Functional Risk Factors with Preventable Hospitalizations: Implications for Physician Value-Based Payment

Association between governmental spending on social services and health care use among low-income older adults

Prior research demonstrates that local government spending on social policies, excluding health care, is linked to improved population health. Whether such spending is associated with better access to primary care and reduced acute care utilization remains unclear. In this cross-sectional study, we evaluated the associations between county-level social spending and individual-level health care utilization among low-income Medicare beneficiaries, aged ≥65 years, from 2016 to 2018. We linked claims data to 4 categories of county-level government expenditures from the US Government Finance Database, including (1) public welfare, (2) public transit, (3) housing/community development, and (4) infrastructure-related social services. The main outcomes were annual primary care visit rates, emergency department visits, and preventable hospitalizations. After adjusting for patient and county characteristics, beneficiaries living in counties with higher spending on housing/community development had 11% higher primary care visit rates. Additionally, those living in counties with higher public transit and housing/community development spending experienced 6%-10% lower preventable hospitalization rates. Lower preventable hospitalization rates were especially pronounced among acute conditions. These findings suggest that investments in social services that address the health-related social needs of low-income older adults may be an important factor to consider in population-level efforts to reduce acute care utilization.

Functional Impairments, Phenotypic Frailty, and Sector-Specific Incremental Healthcare Costs in Older Adults

BACKGROUND

This study quantifies incremental healthcare expenditures of functional impairments and phenotypic frailty in specific healthcare sectors.

METHODS

Pooled 2023 analysis of 4 prospective cohort studies linked with Medicare claims including 4 318 women and 3 847 men attending an index examination (2002-2011). Annualized inpatient, skilled nursing facility (SNF), home healthcare (HHC), and outpatient costs (2023 dollars) ascertained for 36 months following index examination. Functional impairments (difficulty performing 4 activities of daily living) and frailty phenotype (operationalized using 5 components) derived from cohort data. Weighted multimorbidity index including demographics derived from claims.

RESULTS

Mean age at index examination was 79.2 years. After accounting for multimorbidity and each other, average annualized incremental costs of 3-4 functional impairments versus no impairment in women (men) were $2 838 ($5 516) in inpatient, $1 572 ($1 446) in SNF, and $1 349 ($1 060) in HHC sectors; average incremental costs of phenotypic frailty versus robust in women (men) was $4 100 (not significant for men) in inpatient, $1 579 ($1 254) in SNF, and $645 ($526) in HHC sectors. Incremental inpatient costs were primarily due to a higher hospitalization risk, while incremental SNF and HHC costs were related to both increased risks of utilization and higher costs among individuals with utilization. Neither geriatric domain was associated with outpatient costs.

CONCLUSIONS

In this study of community-dwelling beneficiaries, functional impairments were independently associated with higher subsequent expenditures in inpatient, SNF, and HHC sectors among both sexes. Phenotypic frailty was independently associated with higher subsequent inpatient costs in women, and higher SNF and HHC costs in both sexes.

Value-Based Payment for Clinicians Treating Cardiovascular Disease: A Policy Statement From the American Heart Association

Clinician payment is transitioning from fee-for-service to value-based payment, with reimbursement tied to health care quality and cost. However, the overarching goals of value-based payment-to improve health care quality, lower costs, or both-have been largely unmet. This policy statement reviews the current state of value-based payment and provides recommended best practices for future design and implementation. The policy statement is divided into sections that detail different aspects of value-based payment: (1) key program design features (patient population, quality measurement, cost measurement, and risk adjustment), (2) the role of equity during design and evaluation, (3) adjustment of payment, and (4) program implementation and evaluation. Each section introduces the topic, describes important considerations, and lists examples from existing programs. Each section includes recommended best practices for future program design. The policy statement highlights 4 key themes for successful value-based payment. First, programs should carefully weigh the incentives between lowering cost and improving quality of care and ensure that there is adequate focus on quality of care. Second, the expansion of value-based payment should be a tool for improving equity, which is central to quality of care and should be a focal point of program design and evaluation. Third, value-based payment should continue to move away from fee for service toward more flexible funding that allows clinicians to focus resources on the interventions that best help patients. Last, successful programs should find ways to channel clinicians' intrinsic motivation to improve their performance and the care for their patients. These principles should guide the future development of clinician value-based payment models.

Association of Functional Status, Cognition, Social Support, and Geriatric Syndrome With Admission From the Emergency Department

Importance

The role of patient-level factors that are unrelated to the specific clinical condition leading to an emergency department (ED) visit, such as functional status, cognitive status, social supports, and geriatric syndromes, in admission decisions is not well understood, partly because these data are not available in administrative databases.

Objective

To determine the extent to which patient-level factors are associated with rates of hospital admission from the ED.

Design, Setting, and Participants

This cohort study analyzed survey data collected from participants (or their proxies, such as family members) enrolled in the Health and Retirement Study (HRS) from January 1, 2000, to December 31, 2018. These HRS data were linked to Medicare fee-for-service claims data from January 1, 1999, to December 31, 2018. Information on functional status, cognitive status, social supports, and geriatric syndromes was obtained from the HRS data, whereas ED visits, subsequent hospital admission or ED discharge, and other claims-derived comorbidities and sociodemographic characteristics were obtained from Medicare data. Data were analyzed from September 2021 to April 2023.

Main Outcomes and Measures

The primary outcome measure was hospital admission after an ED visit. A baseline logistic regression model was estimated, with a binary indicator of admission as the dependent variable of interest. For each primary variable of interest derived from the HRS data, the model was reestimated, including the HRS variable of interest as an independent variable. For each of these models, the odds ratio (OR) and average marginal effect (AME) of changing the value of the variable of interest were calculated.

Results

A total of 42 392 ED visits by 11 783 unique patients were included. At the time of the ED visit, patients had a mean (SD) age of 77.4 (9.6) years, and visits were predominantly for female (25 719 visits [60.7%]) and White (32 148 visits [75.8%]) individuals. The overall percentage of patients admitted was 42.5%. After controlling for ED diagnosis and demographic characteristics, functional status, cognition status, and social supports all were associated with the likelihood of admission. For instance, difficulty performing 5 activities of daily living was associated with an 8.5-percentage point (OR, 1.47; 95% CI, 1.29-1.66) AME increase in the likelihood of admission. Having dementia was associated with an AME increase in the likelihood of admission of 4.6 percentage points (OR, 1.23; 95% CI, 1.14-1.33). Living with a spouse was associated with an AME decrease in the likelihood of admission of 3.9 percentage points (OR, 0.84; 95% CI, 0.79-0.89), and having children living within 10 miles was associated with an AME decrease in the likelihood of admission of 5.0 percentage points (OR, 0.80; 95% CI, 0.71-0.89). Other common geriatric syndromes, including trouble falling asleep, waking early, trouble with vision, glaucoma or cataract, use of hearing aids or trouble with hearing, falls in past 2 years, incontinence, depression, and polypharmacy, were not meaningfully associated with the likelihood of admission.

Conclusion and Relevance

Results of this cohort study suggest that the key patient-level characteristics, including social supports, cognitive status, and functional status, were associated with the decision to admit older patients to the hospital from the ED. These factors are critical to consider when devising strategies to reduce low-value admissions among older adult patients from the ED.

Quality of Care and Clinical Outcomes for Patients With Heart Failure at Hospitals Caring for a High Proportion of Black Adults: Get With The Guidelines-Heart Failure Registry

Importance

Black adults with heart failure (HF) disproportionately experience higher population-level mortality than White adults with HF. Whether quality of care for HF differs at hospitals with high proportions of Black patients compared with other hospitals is unknown.

Objective

To compare quality and outcomes for patients with HF at hospitals with high proportions of Black patients vs other hospitals.

Design, Setting, and Participants

Patients hospitalized for HF at Get With The Guidelines (GWTG) HF sites from January 1, 2016, through December 1, 2019. These data were analyzed from May 2022 through November 2022.

Exposures

Hospitals caring for high proportions of Black patients.

Main Outcomes and Measures

Quality of HF care based on 14 evidence-based measures, overall defect-free HF care, and 30-day readmissions and mortality in Medicare patients.

Results

This study included 422 483 patients (224 270 male [53.1%] and 284 618 White [67.4%]) with a mean age of 73.0 years. Among 480 hospitals participating in GWTG-HF, 96 were classified as hospitals with high proportions of Black patients. Quality of care was similar between hospitals with high proportions of Black patients compared with other hospitals for 11 of 14 GWTG-HF measures, including use of angiotensin-converting enzyme inhibitors/angiotensin receptor blocker/angiotensin receptor neprilysin inhibitors for left ventricle systolic dysfunction (high-proportion Black hospitals: 92.7% vs other hospitals: 92.4%; adjusted odds ratio [OR], 0.91; 95% CI, 0.65-1.27), evidence-based β-blockers (94.7% vs 93.7%; OR, 1.02; 95% CI, 0.82-1.28), angiotensin receptor neprilysin inhibitors at discharge (14.3% vs 16.8%; OR, 0.74; 95% CI, 0.54-1.02), anticoagulation for atrial fibrillation/flutter (88.8% vs 87.5%; OR, 1.05; 95% CI, 0.76-1.45), and implantable cardioverter-defibrillator counseling/placement/prescription at discharge (70.9% vs 71.0%; OR, 0.75; 95% CI, 0.50-1.13). Patients at high-proportion Black hospitals were less likely to be discharged with a follow-up visit made within 7 days or less (70.4% vs 80.1%; OR, 0.68; 95% CI, 0.53-0.86), receive cardiac resynchronization device placement/prescription (50.6% vs 53.8%; OR, 0.63; 95% CI, 0.42-0.95), or an aldosterone antagonist (50.4% vs 53.5%; OR, 0.69; 95% CI, 0.50-0.97). Overall defect-free HF care was similar between both groups of hospitals (82.6% vs 83.4%; OR, 0.89; 95% CI, 0.67-1.19) and there were no significant within-hospital differences in quality for Black patients vs White patients. Among Medicare beneficiaries, the risk-adjusted hazard ratio (HR) for 30-day readmissions was higher at high-proportion Black vs other hospitals (HR, 1.14; 95% CI, 1.02-1.26), but similar for 30-day mortality (HR 0.92; 95% CI,0.84-1.02).

Conclusions and Relevance

Quality of care for HF was similar across 11 of 14 measures at hospitals caring for high proportions of Black patients compared with other hospitals, as was overall defect-free HF care. There were no significant within-hospital differences in quality for Black patients vs White patients.

Association Between Community-Level Social Risk and Spending Among Medicare Beneficiaries: Implications for Social Risk Adjustment and Health Equity

Importance

Payers are increasingly using approaches to risk adjustment that incorporate community-level measures of social risk with the goal of better aligning value-based payment models with improvements in health equity.

Objective

To examine the association between community-level social risk and health care spending and explore how incorporating community-level social risk influences risk adjustment for Medicare beneficiaries.

Design, Setting, and Participants

Using data from a Medicare Advantage plan linked with survey data on self-reported social needs, this cross-sectional study estimated health care spending health care spending was estimated as a function of demographics and clinical characteristics, with and without the inclusion of Area Deprivation Index (ADI), a measure of community-level social risk. The study period was January to December 2019. All analyses were conducted from December 2021 to August 2022.

Exposures

Census block group-level ADI.

Main Outcomes and Measures

Regression models estimated total health care spending in 2019 and approximated different approaches to social risk adjustment. Model performance was assessed with overall model calibration (adjusted R2) and predictive accuracy (ratio of predicted to actual spending) for subgroups of potentially vulnerable beneficiaries.

Results

Among a final study population of 61 469 beneficiaries (mean [SD] age, 70.7 [8.9] years; 35 801 [58.2%] female; 48 514 [78.9%] White; 6680 [10.9%] with Medicare-Medicaid dual eligibility; median [IQR] ADI, 61 [42-79]), ADI was weakly correlated with self-reported social needs (r = 0.16) and explained only 0.02% of the observed variation in spending. Conditional on demographic and clinical characteristics, every percentile increase in the ADI (ie, more disadvantage) was associated with a $11.08 decrease in annual spending. Directly incorporating ADI into a risk-adjustment model that used demographics and clinical characteristics did not meaningfully improve model calibration (adjusted R2 = 7.90% vs 7.93%) and did not significantly reduce payment inequities for rural beneficiaries and those with a high burden of self-reported social needs. A postestimation adjustment of predicted spending for dual-eligible beneficiaries residing in high ADI areas also did not significantly reduce payment inequities for rural beneficiaries or beneficiaries with self-reported social needs.

Conclusions and Relevance

In this cross-sectional study of Medicare beneficiaries, the ADI explained little variation in health care spending, was negatively correlated with spending conditional on demographic and clinical characteristics, and was poorly correlated with self-reported social risk factors. This prompts caution and nuance when using community-level measures of social risk such as the ADI for social risk adjustment within Medicare value-based payment programs.

Clinical risk calculators informing the decision to admit: A methodologic evaluation and assessment of applicability

INTRODUCTION

Clinical prediction and decision tools that generate outcome-based risk stratification and/or intervention recommendations are prevalent. Appropriate use and validity of these tools, especially those that inform complex clinical decisions, remains unclear. The objective of this study was to assess the methodologic quality and applicability of clinical risk scoring tools used to guide hospitalization decision-making.

METHODS

In February 2021, a comprehensive search was performed of a clinical calculator online database (mdcalc.com) that is publicly available and well-known to clinicians. The primary reference for any calculator tool informing outpatient versus inpatient disposition was considered for inclusion. Studies were restricted to the adult, acute care population. Those focused on obstetrics/gynecology or critical care admission were excluded. The Wasson-Laupacis framework of methodologic standards for clinical prediction rules was applied to each study.

RESULTS

A total of 22 calculators provided hospital admission recommendations for 9 discrete medical conditions using adverse events (14/22), mortality (6/22), or confirmatory diagnosis (2/22) as outcomes of interest. The most commonly met methodologic standards included mathematical technique description (22/22) and clinical sensibility (22/22) and least commonly met included reproducibility of the rule (1/22) and measurement of effect on clinical use (1/22). Description of the studied population was often lacking, especially patient race/ethnicity (2/22) and mental or behavioral health (0/22). Only one study reported any item related to social determinants of health.

CONCLUSION

Studies commonly do not meet rigorous methodologic standards and often fail to report pertinent details that would guide applicability. These clinical tools focus primarily on specific disease entities and clinical variables, missing the breadth of information necessary to make a disposition determination and raise significant validation and generalizability concerns.

Association of Function, Symptoms, and Social Support Reported in Standardized Outpatient Clinic Questionnaires With Subsequent Hospital Discharge Disposition and 30-Day Readmissions

OBJECTIVE

To determine whether patient-reported information, routinely collected in an outpatient setting, is associated with readmission within 30 days of discharge and/or the need for post-acute care after a subsequent hospital admission.

DESIGN

Retrospective cohort study. Six domains of patient-reported information collected in the outpatient setting (psychological distress, respiratory symptoms, musculoskeletal pain, family support, mobility, and activities of daily living [ADLs]) were linked to electronic health record hospitalization data. Mixed effects logistic regression models with random intercepts were used to identify the association between the 6 domains and outcomes.

SETTING

Outpatient clinics and hospitals in a Midwestern health system.

PARTICIPANTS

7671 patients who were hospitalized 11,445 times between May 2004 and May 2014 (N=7671).

INTERVENTION

None.

MAIN OUTCOME MEASURES

30-day hospital readmission and discharge home vs facility.

RESULTS

Domains were significantly associated with 30-day readmission and placement in a facility. Specifically, mobility (odds ratio [OR]=1.30; 95% confidence interval [CI], 1.16, 1.46), ADLs (OR=1.27; 95% CI, 1.13, 1.42), respiratory symptoms (OR=1.26; 95% CI, 1.12, 1.41), and psychological distress (OR=1.20; 95% CI, 1.07, 1.35) had the strongest associations with 30-day readmission. The ADL (OR=2.52; 95% CI, 2.26, 2.81), mobility (OR=2.35; 95% CI, 2.10, 2.63), family support (OR=2.28; 95% CI, 1.98, 2.62), and psychological distress (OR=1.38; 95% CI, 1.25, 1.52) domains had the strongest associations with discharge to an institution.

CONCLUSIONS

Patient-reported function, symptoms, and social support routinely collected in outpatient clinics are associated with future 30-day readmission and discharge to an institutional setting. Whether these data can be leveraged to guide interventions to address patient needs and improve outcomes requires further research.

Association of Social Determinants of Health and Their Cumulative Impact on Hospitalization Among a National Sample of Community-Dwelling US Adults

IMPORTANCE

While the association between Social Determinants of Health (SDOH) and health outcomes is well known, few studies have explored the impact of SDOH on hospitalization.

OBJECTIVE

Examine the independent association and cumulative effect of six SDOH domains on hospitalization.

DESIGN

Using cross-sectional data from the 2016-2018 National Health Interview Surveys (NHIS), we used multivariable logistical regression models controlling for sociodemographics and comorbid conditions to assess the association of each SDOH and SDOH burden (i.e., cumulative number of SDOH) with hospitalization.

SETTING

National survey of community-dwelling individuals in the US PARTICIPANTS: Adults ≥18 years who responded to the NHIS survey EXPOSURE: Six SDOH domains (economic instability, lack of community, educational deficits, food insecurity, social isolation, and inadequate access to medical care) MEASURES: Hospitalization within 1 year RESULTS: Among all 55,186 respondents, most were ≤50 years old (54.2%), female (51.7%, 95% CI 51.1-52.3), non-Hispanic (83.9%, 95% CI 82.4-84.5), identified as White (77.9%, 95% CI 76.8-79.1), and had health insurance (90%, 95% CI 88.9-91.9). Hospitalized individuals (n=5506; 8.7%) were more likely to be ≥50 years old (61.2%), female (60.7%, 95% CI 58.9-62.4), non-Hispanic (87%, 95% CI 86.2-88.4), and identify as White (78.5%, 95% CI 76.7-80.3), compared to those who were not hospitalized. Hospitalized individuals described poorer overall health, reporting higher incidence of having ≥5 comorbid conditions (38.9%, 95% CI 37.1-40.1) compared to those who did not report a hospitalization (15.9%, 95% CI 15.4-16.5). Hospitalized respondents reported higher rates of economic instability (33%), lack of community (14%), educational deficits (67%), food insecurity (14%), social isolation (34%), and less access to health care (6%) compared to non-hospitalized individuals. In adjusted analysis, food insecurity (OR: 1.36, 95% CI 1.22-1.52), social isolation (OR: 1.17, 95% CI 1.08-1.26), and lower educational attainment (OR: 1.12, 95% CI 1.02-1.25) were associated with hospitalization, while a higher SDOH burden was associated with increased odds of hospitalization (3-4 SDOH [OR: 1.25, 95% CI 1.06-1.49] and ≥5 SDOH [OR: 1.72, 95% CI 1.40-2.06]) compared to those who reported no SDOH.

CONCLUSIONS

Among community-dwelling US adults, three SDOH domains: food insecurity, social isolation, and low educational attainment increase an individual's risk of hospitalization. Additionally, risk of hospitalization increases as SDOH burden increases.

CAPABLE program improves disability in multiple randomized trials

BACKGROUND

Programs to reduce disability are crucial to the quality of life for older adults with disabilities. Reducing disability is also important to avert unnecessary and costly hospitalizations, relocation, or nursing home placements. Few programs reduce disability and few have been replicated and scaled beyond initial research settings. CAPABLE is one such program initially tested in a randomized control trial and has now been tested and replicated in multiple settings. CAPABLE, a 10-session, home-based interprofessional program, provides an occupational therapist, nurse, and handyworker to address older adults' self-identified functional goals by enhancing individual capacity and home environmental supports. We examine evidence for the CAPABLE program from clinical trials embedded in different health systems on outcomes that matter most to older adults with disability.

METHODS

Six trials with peer-reviewed publications or reports were identified and included in this review. Participants' outcomes included basic and instrumental activities of daily living (ADLs, IADLs), fall efficacy, depression, pain, and cost savings.

RESULTS

A total of 1144 low-income, community-dwelling older adults with disabilities and 4236 matched comparators were included in the six trials. Participants were on average ≥74-79 years old, cognitively intact, and with self-reported difficulty with ≥1 ADLs. All six studies demonstrated improvements in ADLs and IADLs, with small to strong effect sizes (0.41-1.47). Outcomes for other factors were mixed. Studies implementing the full-tested dose of CAPABLE showed more improvement in ADLS and cost savings than studies implementing a decreased dose.

CONCLUSIONS

The CAPABLE program resulted in substantial improvements in ADLs and IADLs in all six trials with other outcomes varying across studies. A dose lower than the original protocol tested resulted in less benefit. The four studies examining cost showed that CAPABLE saved more than it costs to implement.

Qualitative analysis of disposition decision making for patients referred for admission from the emergency department without definite medical acuity

OBJECTIVE

To map the physician approach when determining disposition for a patient who presents without the level of definite medical acuity that would generally warrant hospitalisation.

DATA SOURCES/STUDY SETTING

Since 2018, our US academic county hospital/trauma centre has maintained a database in which hospitalists ('triage physicians') document the rationale and outcomes of requests for admission to the acute care medical ward during each shift.

STUDY DESIGN

Narrative text from the database was analysed using a grounded theory approach to identify major themes and subthemes, and a conceptual model of the admission decision-making process was constructed.

PARTICIPANTS

Database entries were included (n=300) if the admission call originated from the emergency department and if the triage physician characterised the request as potentially inappropriate because the patient did not have definite medical acuity.

RESULTS

Admission decision making occurs in three main phases: evaluation of unmet needs, assessment of risk and re-evaluation. Importantly, admission decision making is not solely based on medical acuity or clinical algorithms, and patients without a definite medical need for admission are hospitalised when physicians believe a potential issue exists if discharged. In this way, factors such as homelessness, substance use disorder, frailty, etc, contribute to admission because they raise concern about patient safety and/or barriers to appropriate treatment. Physician decision making can be altered by activities such as care coordination, advocacy by the patient or surrogate, interactions with other physicians or a change in clinical trajectory.

CONCLUSIONS

The decision to admit ultimately remains a clinical determination constructed between physician and patient. Physicians use a holistic process that incorporates broad consideration of the patient's medical and social needs with emphasis on risk assessment; thus, any analysis of hospitalisation trends or efforts to impact such should seek to understand this individual-level decision making.

Adjusting Quality Measures For Social Risk Factors Can Promote Equity In Health Care

Risk adjustment of quality measures using clinical risk factors is widely accepted; risk adjustment using social risk factors remains controversial. We argue here that social risk adjustment is appropriate and necessary in defined circumstances and that social risk adjustment should be the default option when there are valid empirical arguments for and against adjustment for a given measure. Social risk adjustment is an important way to avoid exacerbating inequity in the health care system.

Clinicians With High Socially At-Risk Caseloads Received Reduced Merit-Based Incentive Payment System Scores

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.

National profile of the growing population of older adults who access community health centers

BACKGROUND

Community health centers (CHCs) are federally funded safety-net clinics that provide care to low income and medically underserved persons. The proportion of CHC patients aged ≥65 doubled in the last ten years, yet little is known about this population. We aim to describe the demographic and clinical characteristics of the older adult CHC population.

DESIGN

Cross sectional analysis.

SETTING

The nationally representative 2014 Health Center Patient Survey.

PARTICIPANTS

CHC patients ≥55 years.

MEASURES

We used descriptive statistics to characterize older adults across demographic and clinical variables. To determine differences by age, we stratified into three groups (55-64, 65-74, 75+ years). We used t-tests and chi-squared to calculate p values and survey weights to make national estimates.

RESULTS

We included 1875 older adults ≥55 years, representing over 4.2 million people. Older adults were mostly aged 55-64 (60%), female (51%), and white (60%). The majority (73%) had Medicare or Medicaid and 47% reported fair or poor health. Regardless of age, older adults had an average of three chronic conditions and 0.6 impairments in activities of daily living (ADL). Healthcare utilization was not significantly different across age groups with most taking ≥5 prescription medications (54%) and one in five reporting ≥2 emergency department visits or ≥1 hospitalization in the last year.

CONCLUSIONS

Adults 55-64 who attend CHCs have similar disease burden as adults ≥65. As the population of older adults who access CHCs grow, our findings highlight the opportunity to enhance focus on key principles of geriatric medicine, such as measurement of functional impairment for those who are <65 while also addressing underlying health disparities.

Utilization of Social Determinants of Health ICD-10 Z-Codes Among Hospitalized Patients in the United States, 2016-2017

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.

Performance in Federal Value-Based Programs of Hospitals Recognized by the American Heart Association and American College of Cardiology for High-Quality Heart Failure and Acute Myocardial Infarction Care

Importance

The US Centers for Medicare & Medicaid Services have implemented national value-based programs that incentivize hospitals to deliver better cardiovascular care. However, it is unclear how hospitals recognized for high-quality cardiovascular care by American Heart Association (AHA) and American College of Cardiology (ACC) national quality improvement initiatives (termed award hospitals) have performed under value-based programs.

Objective

To determine if hospitals that received awards for high-quality cardiovascular care from the AHA/ACC were less likely to be penalized under the Hospital Readmissions Reduction Program (HRRP) and the Hospital Value-Based Purchasing Program (VBP) compared with other hospitals.

Design, Setting, and Participants

This national cross-sectional study included data from short-term acute care hospitals in the United States that were participating in the HRRP or VBP in fiscal year 2018.

Exposures

Recognition awards for high-quality care from the AHA's Get With The Guidelines-Heart Failure and ACC's Chest Pain-MI (myocardial infarction) Registry national quality improvement initiatives.

Main Outcomes and Measures

Proportion of hospitals that received a financial penalty or financial reward under the HRRP or VBP, median payment adjustments, and hospital-level 30-day mortality rates.

Results

This study included 3175 hospitals participating in the HRRP and 2781 hospitals participating in the VBP in fiscal year 2018. Under the HRRP, a higher proportion of award hospitals received financial penalties compared with other hospitals (419 [85.5%] vs 2112 [78.7%]; P < .001), although payment reductions were similar (median, 0.39% [interquartile range (IQR), 0.08%-0.84%] vs 0.33% [IQR, 0.03%-0.89%]; P = .17). Under the VBP, a higher proportion of award hospitals received penalties compared with other hospitals (250 [51.7%] vs 950 [41.4%]; P < .001), and fewer award hospitals received financial rewards (234 [48.4%] vs 1347 [58.6%]; P < .001). Median payment reductions were higher for award hospitals than other hospitals (0.01% [IQR, 0.00%-0.38%] vs 0.0% [IQR, 0.00%-0.28%]; P < .001), and median payment increases were lower (0.0% [IQR, 0.00%-0.34%] vs 0.13% [IQR, 0.00%-0.60%]; P < .001). Thirty-day mortality at award hospitals was similar (acute myocardial infarction, 13.2% vs 13.2%; P = .76) or slightly lower (heart failure, 11.3% vs 11.7%; P = .001) compared with other hospitals.

Conclusions and Relevance

Hospitals that received awards for high-quality cardiovascular care from the AHA/ACC were more likely to be penalized and less likely to be financially rewarded by federal value-based programs. These findings highlight the potential need to standardize measurement of cardiovascular care quality.

Evaluation of Hospital Performance Using the Excess Days in Acute Care Measure in the Hospital Readmissions Reduction Program

The Hospital Readmissions Reduction Program (HRRP) has penalized hospitals with higher 30-day readmission rates more than $3 billion to date. Clinicians and policy experts have raised concerns that the 30-day readmission measure used in this program provides an incomplete picture of performance because it does not capture all hospital encounters that may occur after discharge. In contrast, the excess days in acute care (EDAC) measure, which currently is not used in the HRRP, captures the full spectrum of hospital encounters (emergency department, observation stay, inpatient readmission) and their associated lengths of stay within 30 days of discharge. This study of 3173 hospitals that participated in the HRRP in fiscal year 2019 compared performance on the readmission and EDAC measures and evaluated whether using the EDAC measure would change hospitals' penalty status for 3 conditions targeted by the HRRP. Overall, only moderate agreement was found on hospital performance rankings by using the readmission and EDAC measures (weighted κ statistic: heart failure, 0.45 [95% CI, 0.42 to 0.47]; acute myocardial infarction [AMI], 0.37 [CI, 0.35 to 0.40]; and pneumonia, 0.50 [CI, 0.47 to 0.52]). Under the HRRP, the penalty status of 769 (27.0%) of 2845 hospitals for heart failure, 581 (28.3%) of 2055 for AMI, and 724 (24.9%) of 2911 for pneumonia would change if the EDAC measure were used instead of the readmission measure to evaluate performance. Fewer small and rural hospitals would receive penalties. The Centers for Medicare & Medicaid Services should consider using the EDAC measure, which provides a more comprehensive picture of postdischarge hospital use, rather than the 30-day readmission measure to evaluate health care system performance under federal quality, reporting, and value-based programs.

Paying for Performance Improvement in Quality and Outcomes of Cardiovascular Care: Challenges and Prospects

Over the past two decades, Medicare and other payers have been looking at ways to base payment for cardiovascular care on the quality and outcomes of care delivered. Public reporting of hospital performance on a series of quality measures began in 2004 with basic processes of care such as aspirin use and influenza vaccination, and it expanded in later years to include outcomes such as mortality and readmission rates. Following the passage of the Affordable Care Act in March 2010, Medicare and other payers moved forward with pay-for-performance programs, more commonly referred to as value-based purchasing (VBP) programs. These programs are largely based on an underlying fee-for-service payment infrastructure and give hospitals and clinicians bonuses or penalties based on their performance. Another new payment mechanism, called alternative payment models (APMs), aims to move towards episode-based or global payments to improve quality and efficiency. The two most relevant APMs for cardiovascular care include Accountable Care Organizations and bundled payments. Both VBP programs and APMs have challenges related to program efficacy, accuracy, and equity. In fact, despite over a decade of progress in measuring and incentivizing high-quality care delivery within cardiology, major limitations remain. Many of the programs have had little benefit in terms of clinical outcomes yet have led to marked administrative burden for participants. However, there are several encouraging prospects to aid the successful implementation of value-based high-quality cardiovascular care, such as more sophisticated data science to improve risk adjustment and flexible electronic health records to decrease administrative burden. Furthermore, payment models designed specifically for cardiovascular care could incentivize innovative care delivery models that could improve quality and outcomes for patients. This review provides an overview of current efforts, largely at the federal level, to pay for high-quality cardiovascular care and discusses the challenges and prospects related to doing so.

Hospitalization and Mortality among Black Patients and White Patients with Covid-19

BACKGROUND

Many reports on coronavirus disease 2019 (Covid-19) have highlighted age- and sex-related differences in health outcomes. More information is needed about racial and ethnic differences in outcomes from Covid-19.

METHODS

In this retrospective cohort study, we analyzed data from patients seen within an integrated-delivery health system (Ochsner Health) in Louisiana between March 1 and April 11, 2020, who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, the virus that causes Covid-19) on qualitative polymerase-chain-reaction assay. The Ochsner Health population is 31% black non-Hispanic and 65% white non-Hispanic. The primary outcomes were hospitalization and in-hospital death.

RESULTS

A total of 3626 patients tested positive, of whom 145 were excluded (84 had missing data on race or ethnic group, 9 were Hispanic, and 52 were Asian or of another race or ethnic group). Of the 3481 Covid-19-positive patients included in our analyses, 60.0% were female, 70.4% were black non-Hispanic, and 29.6% were white non-Hispanic. Black patients had higher prevalences of obesity, diabetes, hypertension, and chronic kidney disease than white patients. A total of 39.7% of Covid-19-positive patients (1382 patients) were hospitalized, 76.9% of whom were black. In multivariable analyses, black race, increasing age, a higher score on the Charlson Comorbidity Index (indicating a greater burden of illness), public insurance (Medicare or Medicaid), residence in a low-income area, and obesity were associated with increased odds of hospital admission. Among the 326 patients who died from Covid-19, 70.6% were black. In adjusted time-to-event analyses, variables that were associated with higher in-hospital mortality were increasing age and presentation with an elevated respiratory rate; elevated levels of venous lactate, creatinine, or procalcitonin; or low platelet or lymphocyte counts. However, black race was not independently associated with higher mortality (hazard ratio for death vs. white race, 0.89; 95% confidence interval, 0.68 to 1.17).

CONCLUSIONS

In a large cohort in Louisiana, 76.9% of the patients who were hospitalized with Covid-19 and 70.6% of those who died were black, whereas blacks comprise only 31% of the Ochsner Health population. Black race was not associated with higher in-hospital mortality than white race, after adjustment for differences in sociodemographic and clinical characteristics on admission.

Switching Between Medicare Advantage And Traditional Medicare Before And After The Onset Of Functional Disability

Medicare Advantage (MA) plans have increasing flexibility to provide nonmedical services to support older adults aging in place in the community. However, prior research has suggested that enrollees with functional disability (hereafter, "disability") were more likely than those without disability to leave MA plans. This indicates that MA plans might not meet the needs of older adults with disability. We used data for 2011-16 from the National Health and Aging Trends Study linked to Medicare claims to measure and characterize switches in either direction between Medicare Advantage and traditional Medicare in the twelve months before and after onset of disability. While the rate of switches from Medicare Advantage to traditional Medicare increased slightly after disability onset, people with greater levels of disability were more likely to switch to traditional Medicare, compared to those with lower levels: 36 percent of those who switched from Medicare Advantage to traditional Medicare needed help with two or more activities of daily living, compared to 14.3 percent of those who switched from traditional Medicare to Medicare Advantage. This indicates the potential benefit of including functional measures in MA plan risk adjustment and quality measures. Furthermore, the highest-need older adults with disability may experience lower-quality care in Medicare Advantage and thus leave before accessing the program's expanded benefits.

Social Determinants of Health and 90-Day Mortality After Hospitalization for Heart Failure in the REGARDS Study

Background

Outcomes following heart failure (HF) hospitalizations are poor, with 90‐day mortality rates of 15% to 20%. Although prior studies found associations between individual social determinants of health (SDOH) and post‐discharge mortality, less is known about how an individuals’ total burden of SDOH affects 90‐day mortality.

Methods and Results

We included participants of the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study who were Medicare beneficiaries aged ≥65 years discharged alive after an adjudicated HF hospitalization. Guided by the Healthy People 2020 Framework, we examined 9 SDOH. First, we examined age‐adjusted associations between each SDOH and 90‐day mortality; those associated with 90‐day mortality were used to create an SDOH count. Next, we determined the hazard of 90‐day mortality by the SDOH count, adjusting for confounders. Over 10 years, 690 participants were hospitalized for HF at 440 unique hospitals in the United States; there were a total of 79 deaths within 90 days. Overall, 28% of participants had 0 SDOH, 39% had 1, and 32% had ≥2. Compared with those with 0, the age‐adjusted hazard ratio for 90‐day mortality among those with 1 SDOH was 2.89 (95% CI, 1.46–5.72) and was 3.06 (1.51–6.19) among those with ≥2 SDOH. The adjusted hazard ratio was 2.78 (1.37–5.62) and 2.57 (1.19–5.54) for participants with 1 SDOH and ≥2, respectively.

Conclusions

While having any of the SDOH studied here markedly increased risk of 90‐day mortality after an HF hospitalization, a greater burden of SDOH was not associated with significantly greater risk in our population.

Relationship of a Claims-Based Frailty Index to Annualized Medicare Costs: A Cohort Study

BACKGROUND

Medicare uses the Centers for Medicare & Medicaid Services Hierarchical Condition Category (CMS-HCC) model to predict patients' annualized Medicare costs in value-based payment programs. The CMS-HCC model does not include measures of frailty, and prior research shows that it systematically underpredicts costs for frail Medicare beneficiaries.

OBJECTIVE

To determine whether a claims-based frailty index can improve Medicare cost prediction.

DESIGN

Retrospective cohort study.

SETTING

Medicare Current Beneficiary Survey linked to Medicare claims, 2006 to 2013.

PARTICIPANTS

16 535 community-dwelling, fee-for-service beneficiaries representing 26 705 patient-years.

MEASUREMENTS

Patient frailty status was classified using a validated claims-based frailty index. The association between the frailty index and annualized Medicare costs was examined, and regression methods were used to compare observed Medicare costs versus predictions based on the standard CMS-HCC model with and without the frailty index.

RESULTS

Mean costs were $5724 for the 8910 patients classified as robust (46.4% of patient-years), $12 462 for the 8405 prefrail patients (41.6%), $26 239 for the 2215 mildly frail patients (9.6%), and $44 586 for the 593 patients classified as moderately to severely frail (2.5%). The frailty index addition to the CMS-HCC model predicted on average an additional $2712, $7915, and $16 449 in costs for prefrail, mildly frail, and moderately to severely frail patients, respectively, beyond the CMS-HCC model alone. On average, the model with the frailty index addition resulted in more accurate predictions of costs for patients at all 4 levels of frailty. However, observed costs remained more widely distributed than predictions from the enhanced model at all levels of frailty.

LIMITATION

The claims-based index is a proxy for frailty and is likely less accurate than an in-person examination.

CONCLUSION

The CMS-HCC model with the frailty index addition is an improvement over current Medicare cost prediction.

PRIMARY FUNDING SOURCE

None.

Patient social risk factors and continuity of care for Medicare beneficiaries

OBJECTIVE

To identify patient social risk factors associated with Continuity of Care (COC) index.

DATA SOURCES/STUDY SETTING

Medicare Current Beneficiary Survey (MCBS), the Dartmouth Institute, and Area Resource File for 2006-2013.

STUDY DESIGN

We use regression methods to assess the effect of patient social risk factors on COC after adjusting for medical complexity. In secondary analyses, we assess the effect of social risk factors on annual utilization of physicians and specialists for evaluation and management (E&M).

DATA COLLECTION/EXTRACTION METHODS

We retrospectively identified 59 499 patient years for Medicare beneficiaries with one year of enrollment and three or more E&M visits.

PRINCIPAL FINDINGS

After adjustment for medical complexity, individual-level social risk factors such as lack of education, low income, and living alone are all associated with better patient COC (P < .05). Similarly, area-level social risk factors such as living in areas that are nonurban or high poverty, as well as in areas with low specialist or high primary care physician supply, are all associated with better patient COC (P < .05). We found the opposite pattern of associations between these same risk factors and annual patient utilization of physicians and specialists (P < .05).

CONCLUSIONS

Medicare patients with multiple social risk factors have consistently better COC; these same social risk factors are associated with reduced patient-realized access to specialist physician care.

Inadequate Risk Adjustment Impacts Geriatricians' Performance on Medicare Cost and Quality Measures

OBJECTIVES

Medicare value-based payment programs evaluate physicians' performance on their patients' annual Medicare costs and clinical outcomes. However, little is known about how geriatricians, who disproportionately provide care for medically complex older adults, perform on these measures.

DESIGN

A retrospective study using multivariable regression methods to estimate the association of geriatric risk factors with annualized Medicare costs and preventable hospitalization rates and to compare geriatricians' performance on these outcomes to other primary care physicians (PCPs) under standard Medicare risk adjustment and after adding additional adjustment for geriatric risk factors.

SETTING

Eight years (2006-2013) of cohort data from the Medicare Current Beneficiary Survey.

PARTICIPANTS

Medicare beneficiaries, aged 65 years and older, with primary care services contributing 27 027 person-years of data.

MEASUREMENTS

Outcomes were costs and preventable hospitalization rates; geriatric risk factors were patient frailty, long-term institutionalization, dementia, and depression.

RESULTS

Geriatricians were more likely to care for patients with frailty (22.8% vs 14.1%), long-term institutionalization (12.0% vs 4.7%), dementia (21.6% vs 10.2%), and depression (23.6% vs 17.4%) than other PCPs (P < .001 for each). Under standard Medicare risk adjustment, geriatricians performed more poorly on costs compared to other PCPs (observed-expected [O-E] ratio = 1.24 vs 0.99) and preventable hospitalizations (O-E ratio = 1.16 vs 0.98). Adding frailty, institutionalization, dementia, and depression to risk adjustment improved geriatricians' performance on costs by 25% and on preventable hospitalization rates by 35%, relative to other PCPs. Concurrent-year risk prediction that removed the influence of unpredictable acute events further improved geriatricians' performance vs other PCPs (O-E ratio = 0.99 vs 1.00).

CONCLUSION

Medicare should consider risk adjusting for frailty, long-term institutionalization, dementia, and depression to avoid inappropriately penalizing geriatricians who care for vulnerable older adults. J Am Geriatr Soc 68:297-304, 2020.