Rural-urban disparities in health care delivery for children with medical complexity and moderating effects of payer, disability, and community poverty.

PURPOSE: Children with medical complexity (CMC) may be at increased risk of rural-urban disparities in health care delivery given their multifaceted health care needs, but these disparities are poorly understood. This study evaluated rural-urban disparities in health care delivery to CMC and determined whether Medicaid coverage, co-occurring disability, and community poverty modified the effects of rurality on care delivery. METHODS: This retrospective cohort study of 2012-2017 all-payer claims data from Colorado, Massachusetts, and New Hampshire included CMC <18 years. Health care delivery measures (ambulatory clinic visits, emergency department visits, acute care hospitalizations, total hospital days, and receipt of post-acute care) were compared for rural- versus urban-residing CMC in multivariable regression models, following established methods to evaluate effect modification. FINDINGS: Of 112,475 CMC, 7307 (6.5%) were rural residing and 105,168 (93.5%) were urban residing. A total of 68.9% had Medicaid coverage, 33.9% had a disability, and 39.7% lived in communities with >20% child poverty. In adjusted analyses, rural-residing CMC received significantly fewer ambulatory visits (risk ratio [RR] = 0.95, 95% confidence interval [CI]: 0.94-0.96), more emergency visits (RR = 1.12, 95% CI: 1.08-1.16), and fewer hospitalization days (RR = 0.90, 95% CI = 0.85-0.96). The estimated modification effects of rural residence by Medicaid coverage, disability, and community poverty were each statistically significant. Differences in the odds of having a hospitalization and receiving post-acute care did not persist after incorporating sociodemographic and clinical characteristics and interaction effects. CONCLUSIONS: Rural- and urban-residing CMC differed in their receipt of health care, and Medicaid coverage, co-occurring disabilities, and community poverty modified several of these effects. These modifying effects should be considered in clinical and policy initiatives to ensure that such initiatives do not widen rural-urban disparities.

A Regional Analysis of Low Back Pain Treatments in the Military Health System.

STUDY DESIGN: Claims-based analysis of cohorts of TRICARE Prime beneficiaries. OBJECTIVE: To compare rates of utilization of 5 low back pain (LBP) treatments (physical therapy (PT), manual therapy, behavioral therapies, opioid, and benzodiazepine prescription) across catchment areas and assess their association with the resolution of LBP. SUMMARY OF BACKGROUND: Guidelines support focusing on nonpharmacologic management for LBP and reducing opioid use. Little is known about patterns of care for LBP across the Military Health System. PATIENTS AND METHODS: Incident LBP diagnoses were identified data using the International Classification of Diseases ninth revision before October 2015 and 10th revision after October 2015; beneficiaries with "red flag" diagnoses and those stationed overseas, eligible for Medicare, or having other health insurance were excluded. After exclusions, there were 159,027 patients remained in the final analytic cohort across 73 catchment areas. Treatment was defined by catchment-level rates of treatment to avoid confounding by indication at the individual level; the primary outcome was the resolution of LBP defined as an absence of administrative claims for LBP during a 6 to 12-month period after the index diagnosis. RESULTS: Adjusted rates of opioid prescribing across catchment areas ranged from 15% to 28%, physical therapy from 17% to 39%, and manual therapy from 5% to 26%. Multivariate logistic regression models showed a negative and marginally significant association between opioid prescriptions and LBP resolution (odds ratio: 0.97, 95% CI: 0.93-1.00; P = 0.051) but no significant association with physical therapy, manual therapy, benzodiazepine prescription, or behavioral therapies. When the analysis was restricted to the subset of only active-duty beneficiaries, there was a stronger negative association between opioid prescription and LBP resolution (odds ratio: 0.93, 95% CI: 0.89-0.97). CONCLUSIONS: We found substantial variability across catchment areas within TRICARE for the treatment of LBP. Higher rates of opioid prescription were associated with worse outcomes.

Specialties Providing Ambulatory Care and Associated Health Care Utilization and Quality for Children With Medical Complexity.

OBJECTIVE: Although children with medical complexity (CMC) have substantial health care needs, the extent to which they receive ambulatory care from primary care versus specialist clinicians is unknown. We aimed to determine the predominant specialty providing ambulatory care to CMC (primary care or specialty discipline), the extent to which specialists deliver well-child care, and associations between having a specialty predominant provider and health care utilization and quality. METHODS: In a retrospective cohort analysis of 2012-17 all-payer claims data from Colorado, New Hampshire, and Massachusetts, we identified the predominant specialty providing ambulatory care for CMC <18 years. Propensity score weighting was used to create a balanced sample of CMC and assess differences in outcomes, including adequate well-child care, continuity of care, emergency visits, and hospitalizations, between CMC with a primary care versus specialty predominant provider. RESULTS: Among 67,218 CMC, 75.3% (n = 50,584) received the plurality of care from a primary care discipline. Body system involvement, age > 2 years, urban residence, and cooccurring disabilities were associated with predominantly receiving care from specialists. After propensity score weighting, there were no significant differences between CMC with a primary care or specialist "predominant specialty seen" (PSS) in ambulatory visit counts, adequate well-child care, hospitalizations, or overall continuity of care. Specialists were the sole providers of well-child care and vaccines for 49.9% and 53.1% of CMC with a specialist PSS. CONCLUSIONS: Most CMC received the plurality of care from primary care disciplines, and there were no substantial differences in overall utilization or quality based on the PSS.

Trends of Concomitant Diabetes and Peripheral Artery Disease and Lower Extremity Amputation in US Medicare Patients, 2007 to 2019.

BACKGROUND: Previous studies demonstrate geographic and racial/ethnic variation in diagnosis and complications of diabetes and peripheral artery disease (PAD). However, recent trends for patients diagnosed with both PAD and diabetes are lacking. We assessed the period prevalence of concurrent diabetes and PAD across the United States from 2007 to 2019 and regional and racial/ethnic variation in amputations among Medicare patients. METHODS: Using Medicare claims from 2007 to 2019, we identified patients with both diabetes and PAD. We calculated period prevalence of concomitant diabetes and PAD and incident cases of diabetes and PAD for every year. Patients were followed to identify amputations, and results were stratified by race/ethnicity and hospital referral region. RESULTS: 9 410 785 patients with diabetes and PAD were identified (mean age, 72.8 [SD, 10.94] years; 58.6% women, 74.7% White, 13.2% Black, 7.3% Hispanic, 2.8% Asian/API, and 0.6% Native American). Period prevalence of diabetes and PAD was 23 per 1000 beneficiaries. We observed a 33% relative decrease in annual new diagnoses throughout the study. All racial/ethnic groups experienced a similar decline in new diagnoses. Black and Hispanic patients had on average a 50% greater rate of disease compared with White patients. One- and 5-year amputation rates remained stable at ≈1.5% and 3%, respectively. Native American, Black, and Hispanic patients were at greater risk of amputation compared with White patients at 1- and 5-year time points (5-year rate ratio range, 1.22-3.17). Across US regions, we observed differential amputation rates, with an inverse relationship between the prevalence of concomitant diabetes and PAD and overall amputation rates. CONCLUSIONS: Significant regional and racial/ethnic variation exists in the incidence of concomitant diabetes and PAD among Medicare patients. Black patients in areas with the lowest rates of PAD and diabetes are at disproportionally higher risk for amputation. Furthermore, areas with higher prevalence of PAD and diabetes have the lowest rates of amputation.

Association Between Opening a Palliative Care Unit and Hospital Care for Patients With Serious Illness.

Background: Palliative care units (PCUs) are devoted to intensive management of symptoms and other palliative care needs. We examined the association between opening a PCU and acute care processes at a single U.S. academic medical center. Methods: We retrospectively compared acute care processes for seriously ill patients admitted before and after the opening of a PCU at a single academic medical center. Outcomes included rates of change in code status to do-not-resuscitate (DNR) and comfort measures only (CMO) status, and time to DNR and CMO. We calculated unadjusted and adjusted rates and used logistic regression to assess interaction between care period and palliative care consultation. Results: There were 16,611 patients in the pre-PCU period and 18,305 patients in the post-PCU period. The post-PCU cohort was slightly older, with a higher Charlson index (p < 0.001 for both). Post-PCU, unadjusted rates of DNR and CMO increased from 16.4% to 18.3% (p < 0.001) and 9.3% to 11.5% (p < 0.001), respectively. Post-PCU, median time to DNR was unchanged (0 days), and time to CMO decreased from 6 to 5 days. The adjusted odds ratio was 1.08 (p = 0.01) for DNR and 1.19 (p < 0.001) for CMO. Significant interaction between care period and palliative care consultation for DNR (p = 0.04) and CMO (p = 0.01) suggests an important role for palliative care engagement. Conclusions: The opening of a PCU at a single center was associated with increased rates of DNR and CMO status for seriously ill patients.

Using a cohort study of diabetes and peripheral artery disease to compare logistic regression and machine learning via random forest modeling.

BACKGROUND: This study illustrates the use of logistic regression and machine learning methods, specifically random forest models, in health services research by analyzing outcomes for a cohort of patients with concomitant peripheral artery disease and diabetes mellitus. METHODS: Cohort study using fee-for-service Medicare beneficiaries in 2015 who were newly diagnosed with peripheral artery disease and diabetes mellitus. Exposure variables include whether patients received preventive measures in the 6 months following their index date: HbA1c test, foot exam, or vascular imaging study. Outcomes include any reintervention, lower extremity amputation, and death. We fit both logistic regression models as well as random forest models. RESULTS: There were 88,898 fee-for-service Medicare beneficiaries diagnosed with peripheral artery disease and diabetes mellitus in our cohort. The rate of preventative treatments in the first six months following diagnosis were 52% (n = 45,971) with foot exams, 43% (n = 38,393) had vascular imaging, and 50% (n = 44,181) had an HbA1c test. The directionality of the influence for all covariates considered matched those results found with the random forest and logistic regression models. The most predictive covariate in each approach differs as determined by the t-statistics from logistic regression and variable importance (VI) in the random forest model. For amputation we see age 85 + (t = 53.17) urban-residing (VI = 83.42), and for death (t = 65.84, VI = 88.76) and reintervention (t = 34.40, VI = 81.22) both models indicate age is most predictive. CONCLUSIONS: The use of random forest models to analyze data and provide predictions for patients holds great potential in identifying modifiable patient-level and health-system factors and cohorts for increased surveillance and intervention to improve outcomes for patients. Random forests are incredibly high performing models with difficult interpretation most ideally suited for times when accurate prediction is most desirable and can be used in tandem with more common approaches to provide a more thorough analysis of observational data.

Prevalence of Children With Medical Complexity and Associations With Health Care Utilization and In-Hospital Mortality.

Importance: Children with medical complexity (CMC) have substantial health care needs and frequently experience poor health care quality. Understanding the population prevalence and associated health care needs can inform clinical and public health initiatives. Objective: To estimate the prevalence of CMC using open-source pediatric algorithms, evaluate performance of these algorithms in predicting health care utilization and in-hospital mortality, and identify associations between medical complexity as defined by these algorithms and clinical outcomes. Design, Setting, and Participants: This retrospective cohort study used all-payer claims data from Colorado, Massachusetts, and New Hampshire from 2012 through 2017. Children and adolescents younger than 18 years residing in these states were included if they had 12 months or longer of enrollment in a participating health care plan. Analyses were conducted from March 12, 2021, to January 7, 2022. Exposures: The pediatric Complex Chronic Condition Classification System, Pediatric Medical Complexity Algorithm, and Children With Disabilities Algorithm were applied to 3 years of data to identify children with complex and disabling conditions, first in their original form and then using more conservative criteria that required multiple health care claims or involvement of 3 or more body systems. Main Outcomes and Measures: Primary outcomes, examined over 2 years, included in-hospital mortality and a composite measure of health care services, including specialized therapies, specialized medical equipment, and inpatient care. Outcomes were modeled using logistic regression. Model performance was evaluated using C statistics, sensitivity, and specificity. Results: Of 1 936 957 children, 48.4% were female, 87.8% resided in urban core areas, and 45.1% had government-sponsored insurance as their only primary payer. Depending on the algorithm and coding criteria applied, 0.67% to 11.44% were identified as CMC. All 3 algorithms had adequate discriminative ability, sensitivity, and specificity to predict in-hospital mortality and composite health care services (C statistic = 0.76 [95% CI, 0.73-0.80] to 0.81 [95% CI, 0.78-0.84] for mortality and 0.77 [95% CI, 0.76-0.77] to 0.80 [95% CI, 0.79-0.80] for composite health care services). Across algorithms, CMC had significantly greater odds of mortality (adjusted odds ratio [aOR], 9.97; 95% CI, 7.70-12.89; to aOR, 69.35; 95% CI, 52.52-91.57) and composite health care services (aOR, 4.59; 95% CI, 4.44-4.73; to aOR, 18.87; 95% CI, 17.87-19.93) than children not identified as CMC. Conclusions and Relevance: In this study, open-source algorithms identified different cohorts of CMC in terms of prevalence and magnitude of risk, but all predicted increased health care utilization and in-hospital mortality. These results can inform research, programs, and policies for CMC.

Complications and Mortality Following CRT-D Versus ICD Implants in Older Medicare Beneficiaries With Heart Failure.

OBJECTIVES: This study sought to assess the comparative effectiveness of cardiac resynchronization therapy with defibrillator (CRT-D) over implantable cardioverter-defibrillator (ICD) alone in older Medicare patients with heart failure with reduced ejection fraction (HFrEF). BACKGROUND: Despite growing numbers of older patients with HFrEF, the benefits of cardiac resynchronization therapy (CRT) in this group are largely unknown. METHODS: A cohort of fee-for-service Medicare beneficiaries ≥65 years of age with HFrEF and enrolled in Medicare Part D who underwent CRT-D or ICD implantation from January 2008 to August 2015 was identified. Beneficiaries were divided by age (65-74, 75-84, and 85+ years), and outcomes were compared between the CRT-D and ICD groups after inverse probability weighting. RESULTS: Compared with the ICD group, the CRT-D group was older and more likely to be White, be female, and have left bundle branch block. After weighting, overall complications were high across age and device groups (14%-20%). The 1-year mortality was high across all groups. In the 2 oldest age strata, the hazard of death was lower in the CRT-D group (HR: 0.90; 95% CI: 0.86-0.95 and HR: 0.81; 95% CI: 0.72-0.90, respectively; P < 0.001); the hazard of heart failure hospitalization was lower for CRT-D vs ICD in the 85+ years age group (HR: 0.82; 95% CI: 0.74-0.92; P < 0.001). CONCLUSIONS: In older Medicare beneficiaries undergoing ICD with or without CRT, complications and 1-year mortality were high. Compared with ICD alone, CRT-D was associated with a lower hazard of mortality in patients ≥74 years of age and lower hazard of HF hospitalization in those ≥85 years of age. These findings support the use of CRT in eligible older patients undergoing ICD implantation.

Utilization Patterns and Outcomes of People With Diabetes and COVID-19: Evidence From United States Medicare Beneficiaries in 2020.

Objective: Determine differences in utilization patterns, disease severity, and outcomes between patients with and without diabetes mellitus diagnosed with COVID-19 in 2020. Research Design and Methods: We used an observational cohort comprised of Medicare fee-for-service beneficiaries with a medical claim indicating a COVID-19 diagnosis. We performed inverse probability weighting between beneficiaries with and without diabetes to account for differences in socio-demographic characteristics and comorbidities. Results: In the unweighted comparison of beneficiaries, all characteristics were significantly different (P<0.001). Beneficiaries with diabetes were younger, more likely to be black, had more comorbidities, higher rates of Medicare-Medicaid dual-eligibility, and were less likely to be female. In the weighted sample, hospitalization rates for COVID-19 among beneficiaries with diabetes was higher (20.5% vs 17.1%; p < 0.001). Outcomes of hospitalizations were similarly worse among beneficiaries with diabetes: admissions to ICU during hospitalizations (7.78% vs. 6.11%; p < 0.001); in-hospital mortality (3.85% vs 2.93%; p < 0.001); and ICU mortality (2.41% vs 1.77%). Beneficiaries with diabetes had more ambulatory care visits (8.9 vs. 7.8, p < 0.001) and higher overall mortality (17.3% vs. 14.9%, p < 0.001) following COVID-19 diagnosis. Conclusion: Beneficiaries with diabetes and COVID-19 had higher rates of hospitalization, ICU use and overall mortality. While the mechanism of how diabetes impacts the severity of COVID-19 may not be fully understood, there are important clinical implications for persons with diabetes. A diagnosis of COVID-19 leads to greater financial and clinical burden than for their counterparts, persons without diabetes, including perhaps most significantly, higher death rates.

Resource Use Among Diabetes Patients Who Mainly Visit Primary Care Physicians Versus Medical Specialists: a Retrospective Cohort Study.

BACKGROUND: It is not uncommon for medical specialists to predominantly care for patients with certain chronic conditions rather than primary care physicians (PCPs), yet the resource implications from such patterns of care are not well understood. OBJECTIVE: To assess resource use of diabetes patients who predominantly visit a PCP versus a medical specialist. DESIGN: Retrospective cohort study of diabetes patients aging into the traditional Medicare program. Patients were attributed to a PCP or medical specialist annually based on a preponderance of ambulatory care visits and categorized according to whether attribution changed year to year. Propensity score weighting was used to balance baseline demographic characteristics, diabetes complications, and underlying health conditions between patients attributed to PCPs and to medical specialists. Spending and utilization were measured up to 3 patient-years. SUBJECTS: A total of 141,558 patient-years. MAIN MEASURES: Total visits, unique physicians, hospital admissions, emergency department visits, procedures, imaging, and tests. KEY RESULTS: Each year, roughly 70% of patients maintained attribution to a PCP and 15% to a medical specialist relative to the previous year. After propensity weighting, patients continuously attributed to a PCP versus medical specialist from 1 year to the next had lower average total payer payments ($10,326 [SD $57,386] versus $14,971 [SD $74,112], P<0.0001) and lower total patient out-of-pocket payments ($1,707 [SD $6,020] versus $2,443 [SD $7,984], P<0.0001). Rates of hospitalization, emergency department visits, procedures, imaging, and tests were lower among patients attributed to PCPs as well. CONCLUSIONS: Older adults with diabetes who receive more of their ambulatory care from a PCP instead of a medical specialist show evidence of lower resource use.

Variation in early diffusion of sacubitril/valsartan and implications for understanding novel drug diffusion.

OBJECTIVES: In the PARADIGM-HF trial, sacubitril/valsartan demonstrated a 20% reduction in mortality and heart failure hospitalization compared with standard angiotensin-converting enzyme inhibitor therapy. Despite this and a class I indication, drug diffusion has been much slower than anticipated. This study aims to examine the variation in early diffusion of sacubitril/valsartan and describe the factors associated with high and low rates of early use. STUDY DESIGN: Annual, cross-sectional analyses between January 2016 and December 2018. METHODS: We created a nationally representative cohort of Medicare fee-for-service beneficiaries with heart failure with reduced ejection fraction fully enrolled in parts A, B, and D for at least 1 year between 2016 and 2018. Sacubitril/valsartan use was determined using National Drug Codes. We generated age, sex, and race-adjusted rates of sacubitril/valsartan prescribing by hospital referral region from 2016 to 2018. We also examined the factors associated with high and low rates of early use. RESULTS: Early use rates of sacubitril/valsartan were low: 1.9% in 2016, 3.3% in 2017, and 4.0% in 2018. Even after controlling for out-of-pocket co-payments, there was substantial geographic variation in early use, with most early use concentrated in the Northeast and South. CONCLUSIONS: There has been substantial variation in the early diffusion of sacubitril/valsartan. In addition to drug cost, geographic prescribing patterns appear to play a major role in early drug diffusion.

Association Between Diagnosis Code Expansion and Changes in 30-Day Risk-Adjusted Outcomes for Cardiovascular Diseases.

BACKGROUND In January 2011, Centers for Medicare and Medicaid Services expanded the number of inpatient diagnosis codes from 9 to 25, which may influence comorbidity counts and risk-adjusted outcome rates for studies spanning January 2011. This study examines the association between (1) limiting versus not limiting diagnosis codes after 2011, (2) using inpatient-only versus inpatient and outpatient data, and (3) using logistic regression versus the Centers for Medicare and Medicaid Services risk-standardized methodology and changes in risk-adjusted outcomes. METHODS AND RESULTS Using 100% Medicare inpatient and outpatient files between January 2009 and December 2013, we created 2 cohorts of fee-for-service beneficiaries aged ≥65 years. The acute myocardial infarction cohort and the heart failure cohort had 578 728 and 1 595 069 hospitalizations, respectively. We calculate comorbidities using (1) inpatient-only limited diagnoses, (2) inpatient-only unlimited diagnoses, (3) inpatient and outpatient limited diagnoses, and (4) inpatient and outpatient unlimited diagnoses. Across both cohorts, International Classification of Diseases, Ninth Revision (ICD-9) diagnoses and hierarchical condition categories increased after 2011. When outpatient data were included, there were no significant differences in risk-adjusted readmission rates using logistic regression or the Centers for Medicare and Medicaid Services risk standardization. A difference-in-differences analysis of risk-adjusted readmission trends before versus after 2011 found that no significant differences between limited and unlimited models for either cohort. CONCLUSIONS For studies that span 2011, researchers should consider limiting the number of inpatient diagnosis codes to 9 and/or including outpatient data to minimize the impact of the code expansion on comorbidity counts. However, the 2011 code expansion does not appear to significantly affect risk-adjusted readmission rate estimates using either logistic or risk-standardization models or when using or excluding outpatient data.

Association Between Beta-Blockers and Mortality and Readmission in Older Patients with Heart Failure: an Instrumental Variable Analysis.

BACKGROUND: The demographics of heart failure are changing. The rate of growth of the "older" heart failure population, specifically those ≥ 75, has outpaced that of any other age group. These older patients were underrepresented in the early beta-blocker trials. There are several reasons, including a decreased potential for mortality benefit and increased risk of side effects, why the risk/benefit tradeoff may be different in this population. OBJECTIVE: We aimed to determine the association between receipt of a beta-blocker after heart failure discharge and early mortality and readmission rates among patients with heart failure and reduced ejection fraction (HFrEF), specifically patients aged 75+. DESIGN AND PARTICIPANTS: We used 100% Medicare Parts A and B and a random 40% sample of Part D to create a cohort of beneficiaries with ≥ 1 hospitalization for HFrEF between 2008 and 2016 to run an instrumental variable analysis. MAIN MEASURE: The primary measure was 90-day, all-cause mortality; the secondary measure was 90-day, all-cause readmission. KEY RESULTS: Using the two-stage least squared methodology, among all HFrEF patients, receipt of a beta-blocker within 30-day of discharge was associated with a - 4.35% (95% CI - 6.27 to - 2.42%, p < 0.001) decrease in 90-day mortality and a - 4.66% (95% CI - 7.40 to - 1.91%, p = 0.001) decrease in 90-day readmission rates. Even among patients ≥ 75 years old, receipt of a beta-blocker at discharge was also associated with a significant decrease in 90-day mortality, - 4.78% (95% CI - 7.19 to - 2.40%, p < 0.001) and 90-day readmissions, - 4.67% (95% CI - 7.89 to - 1.45%, p < 0.001). CONCLUSION: Patients aged ≥ 75 years who receive a beta-blocker after HFrEF hospitalization have significantly lower 90-day mortality and readmission rates. The magnitude of benefit does not appear to wane with age. Absent a strong contraindication, all patients with HFrEF should attempt beta-blocker therapy at/after hospital discharge, regardless of age.

The association between neurohormonal therapy and mortality in older adults with heart failure with reduced ejection fraction.

BACKGROUND/OBJECTIVES: Neurohormonal therapy, which includes beta-blockers and angiotensin-converting enzyme inhibitor/angiotensin receptor blockers (ACEi/ARBs), is the cornerstone of heart failure with reduced ejection fraction (HFrEF) treatment. While neurohormonal therapies have demonstrated efficacy in randomized clinical trials, older patients, which now comprise the majority of HFrEF patients, were underrepresented in those original trials. This study aimed to determine the association between short- (30 day) and long-term (1 year) mortality and the use of neurohormonal therapy in HFrEF patients, across the age spectrum. DESIGN/SETTING/PARTICIPANTS: This is a population-based, retrospective, cohort study between January 2008 and December 2015. We used 100% Medicare Parts A and B and a random 40% sample of Part D to create a cohort of 295,494 fee-for-service beneficiaries with at least one hospitalization for HFrEF between 2008 and 2015. All analyses were performed between May 2019 and July 2020. EXPOSURE: We used Part D data to determine exposure to beta-blocker and ACEi and ARB therapy. RESULTS: We found that in 295,494 patients admitted for HFrEF between 2008 and 2015, the average age was 80 years, 54% were female and 17% were non-white. The baseline mortality rate was higher among those aged ≥85, but the mortality benefits of neurohormonal therapy were preserved across the age spectrum. Among those ≥85 years old, the hazard ratio for death within 30 days was 0.59 (95% confidence interval [CI] 0.56-0.62; p < 0.001) for beta-blockers and 0.47 (95% CI 0.44-0.49; p < 0.001) for ACEi/ARBs. The hazard ratio for death within 1 year was 0.37-0.56 (95% CI 0.35-0.58; p < 0.001) for beta-blockers and 0.38-0.53 (95% CI 0.37-0.55; p < 0.001) for ACEi/ARB. CONCLUSION: At a population level, neurohormonal therapy was associated with lower short- and long-term mortality across the age spectrum.

No date for the PROM: the association between patient-reported health events and clinical coding in primary care.

OBJECTIVE: It is unclear whether data from patient-reported outcome measures (PROMs) are captured and used by clinicians despite policy initiatives. We examined the extent to which fall risk and urinary incontinence (UI) reported on PROMS and provided to clinicians prior to a patient visit are subsequently captured in the electronic medical record (EMR). Additionally, we aimed to determine whether the use of PROMs and EMR documentation is higher for visits where PROM data was provided to clinicians. DESIGN: We conducted a cross-sectional patient-reported risk assessment survey and semi-structured interviews with clinicians to identify themes related to the use of PROMs. SETTING: Fourteen primary care clinics in the US (eight intervention and six control clinics), between October 2013 and May 2015. PARTICIPANTS: Primary care clinicians and older adult (≥66 years) patients completing a 46-item health risk assessment, including PROMs for fall risk and UI. INTERVENTION: Risk assessment results provided to the clinician or nurse practitioners prior to the clinic visit in intervention clinics; data was not provided in control clinics. MAIN OUTCOME: 1) Agreement between ICD-9 codes of fall risk or UI in the EMR and patient-reports, and 2) clinician experience of PROMs use and impact on coding. RESULTS: A total of 505 older adult patients were included in the study, 176 at control clinics and 329 at intervention clinics. While patient reports of fall risk and UI were readily captured by PROMs, this information was only coded in the EMR between 3% - 14% of the time (poor Kappa agreement). Intervention clinics performed slightly better than control clinics. Clinician interviews (n = 16) revealed low use of PROMs data with multiple barriers cited including poor access to data, high quantity of data, interruption to workflow, and a lack of training on PROMs. CONCLUSIONS: Current strategies of providing PROMs data prior to clinic visits may not be an effective way of communicating important health information to busy clinicians; ultimately resulting in underuse. Better systems of presenting PROMs data, and clinician training on the importance of PROMs and their use, is needed.

Opportunities and Challenges of Claims-Based Quality Assessment: The Case of Postdischarge ß-Blocker Treatment in Patients With Heart Failure With Reduced Ejection Fraction.

BACKGROUND: To combat the high cost and increasing burden of quality reporting, the Medicare Payment Advisory (MedPAC) has recommended using claims data wherever possible to measure clinical quality. In this article, we use a cohort of Medicare beneficiaries with heart failure with reduced ejection fraction and existing quality metrics to explore the impact of changes in quality metric methodology on measured quality performance, the association with patient outcomes, and hospital rankings. METHODS AND RESULTS: We used 100% Medicare Parts A and B and a random 40% sample of Part D from 2008 to 2015 to create (1) a cohort of 295 494 fee-for-service beneficiaries with ≥1 hospitalization for heart failure with reduced ejection fraction and (2) a cohort of 1079 hospitals with ≥11 heart failure with reduced ejection fraction admissions in 2014 and 2015. We used Part D data to calculate ß-blocker use after discharge and ß-blocker use over time. We then varied the quality metric methodologies to explore the impact on measured performance. We then used multivariable time-to-event analyses to explore the impact of metric methodology on the association between quality performance and patient outcomes and Kendall's Tau to describe impact of quality metric methodology on hospital rankings. We found that quality metric methodology had a significant impact on measured quality performance. The association between quality performance and readmissions was sensitive to changes in methodology but the association with 1-year mortality was not. Changes in quality metric methodology also had a substantial impact on hospital quality rankings. CONCLUSIONS: This article highlights how small changes in quality metric methodology can have a significant impact on measured quality performance, the association between quality performance and utilization-based outcomes, and hospital rankings. These findings highlight the need for standardized quality metric methodologies, better case-mix adjustment and cast further doubt on the use of utilization-based outcomes as quality metrics in chronic diseases.