Evaluation of 30-Day Hospital Readmission and Mortality Rates Using Regression-Discontinuity Framework

Health Services Costs of Clinical Heart Failure With Reduced Ejection Fraction in Singapore

OBJECTIVES

This study aimed to estimate the annual healthcare burden of heart failure (HF) with reduced ejection fraction (<40%) in Singapore.

METHODS

Retrospective longitudinal descriptive cohort study was conducted using a linked national administrative data set (Singapore Cardiovascular Longitudinal Outcomes Database). In Singapore, during 2011, there were a total of 3267 HF-related hospital admissions. Among these, 1631 patients (49.9%), who had an ejection fraction of less than 40%, were followed up for 9 years. The primary outcomes were annual healthcare costs related to hospital admissions and outpatient visits.

RESULTS

There was a consistent decline in HF-related hospital admissions over the years, and the average per-hospital admission cost and average cost per day for HF varied over the 9 years. The average all-cause per-patient admission cost remained stable annually, ranging between S$16 000 and S$18 800. In the final year of life, there was a significant increase in both all-cause and HF-related hospital admission costs (by 24% and 54% from the previous year, respectively), and this rise in costs reflected increased frequency of admissions and longer hospital stays. There was an upward trend in the cost of outpatient visits as the patients neared death.

CONCLUSIONS

Hospital-based HF care imposes a significant financial impact on Singapore's healthcare system. This suggests a need for cost-efficient management strategies to reduce the reliance on hospital-based treatment, thus mitigating economic pressures on the healthcare system.

Impact of Pharmacist-Driven Transitions of Care Interventions on Post-hospital Outcomes Among Patients With Coronary Artery Disease: A Systematic Review

Background: Transitions of care (ToC) aim to provide continuity while preventing loss of information that may result in poor outcomes such as hospital readmission. Readmissions not only burden patients, they also increase costs. Given the high prevalence of coronary artery diseases (CAD) in the United States (US), patients with CAD often make up a significant portion of hospital readmissions. Objective: To conduct a systematic review evaluating the impact of pharmacist-driven ToC interventions on post-hospital outcomes for patients with CAD. Methods: MEDLINE, Scopus, and CINAHL were searched from database inception through 03/2020 using key words for CAD and pharmacists. Studies were included if they: (1) identified adults with CAD at US hospitals, (2) evaluated pharmacist-driven ToC interventions, and (3) assessed post-discharge outcomes. Outcomes were summarized qualitatively. Results: Of the 1612 citations identified, 11 met criteria for inclusion. Pharmacist-driven ToC interventions were multifaceted and frequently included medication reconciliation, medication counseling, post-discharge follow-up and initiatives to improve medication adherence. Hospital readmission and emergency room visits were numerically lower among patients receiving vs not receiving pharmacist-driven interventions, with statistically significant differences observed in 1 study. Secondary prevention measures and adherence tended to be more favorable in the pharmacist-driven intervention groups. Conclusion: Eleven studies of multifaceted, ToC interventions led by pharmacists were identified. Readmissions were numerically lower and secondary prevention measures and adherence were more favorable among patients receiving pharmacist-driven interventions. However, sufficiently powered studies are still required to confirm these benefits.

Deep learning approach for analyzing chest x-rays to predict cardiac events in heart failure

Background

A deep learning (DL) model based on a chest x-ray was reported to predict elevated pulmonary artery wedge pressure (PAWP) as heart failure (HF).

Objectives

The aim of this study was to (1) investigate the role of probability of elevated PAWP for the prediction of clinical outcomes in association with other parameters, and (2) to evaluate whether probability of elevated PAWP based on DL added prognostic information to other conventional clinical prognostic factors in HF.

Methods

We evaluated 192 patients hospitalized with HF. We used a previously developed AI model to predict HF and calculated probability of elevated PAWP. Readmission following HF and cardiac mortality were the primary endpoints.

Results

Probability of elevated PAWP was associated with diastolic function by echocardiography. During a median follow-up period of 58 months, 57 individuals either died or were readmitted. Probability of elevated PAWP appeared to be associated with worse clinical outcomes. After adjustment for readmission score and laboratory data in a Cox proportional-hazards model, probability of elevated PAWP at pre-discharge was associated with event free survival, independent of elevated left atrial pressure (LAP) based on echocardiographic guidelines (p < 0.001). In sequential Cox models, a model based on clinical data was improved by elevated LAP (p = 0.005), and increased further by probability of elevated PAWP (p < 0.001). In contrast, the addition of pulmonary congestion interpreted by a doctor did not statistically improve the ability of a model containing clinical variables (compared p = 0.086).

Conclusions

This study showed the potential of using a DL model on a chest x-ray to predict PAWP and its ability to add prognostic information to other conventional clinical prognostic factors in HF. The results may help to enhance the accuracy of prediction models used to evaluate the risk of clinical outcomes in HF, potentially resulting in more informed clinical decision-making and better care for patients.

Effectiveness of daily activity record-based self-monitoring intervention for patients with chronic heart failure: A study protocol

Background

The prevention of recurrent readmission among heart failure (HF) patients requires support for appropriate self-care behaviors to prevent exacerbation of HF and self-monitoring to allow for patients’ early perception of physical changes during exacerbations. Such support may enable patients to seek early consultation. This study developed a self-monitoring intervention that aimed at increasing the perception of patient-unique physical sensations caused by HF, based on daily activity records of patients.

Method

A parallel two-arm randomized controlled trial is being conducted with 68 HF patients early after their discharge. Participants in both groups wear a wristwatch activity tracker from time-of-discharge. Participants in the self-monitoring intervention group receive support to reflect on their actual daily activities and the associated physical sensations they experienced, based on their daily activity records. The primary outcome is participants’ “Asking for Help” dimension of self-care behavior, measured using the European Heart Failure Self-Care Behavior Scale at one month follow-up after intervention.

Conclusion

This study is the first trial to use an activity tracker as a tool for symptom perception among HF patients. The problem of delayed consultations during exacerbations may be resolved by assisting patients in improving their perception of their unique physical sensations associated with specific daily activities, based on their daily activity records. If the effect is clarified, it could lead to the construction of new nursing interventions for continuous disease management that aim towards re-hospitalization prevention.

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This is the first trial using an activity tracker for symptom perception in HF.

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Intervention focuses on physical sensations perception along with daily activities.

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Trial will test intervention's effect on early consultation behavior and readmission.

Readmission After ACS: Burden, Epidemiology, and Mitigation

PURPOSE OF REVIEW

The past decade has brought increased efforts to better understand causes for ACS readmissions and strategies to minimize them. This review seeks to provide a critical appraisal of this rapidly growing body of literature.

RECENT FINDINGS

Prior to 2010, readmission rates for patients suffering from ACS remained relatively constant. More recently, several strategies have been implemented to mitigate this including improved risk assessment models, transition care bundles, and development of targeted programs by federal organizations and professional societies. These strategies have been associated with a significant reduction in ACS readmission rates in more recent years. With this, improvements in 30-day post-discharge mortality rates are also being appreciated. As we continue to expand our knowledge on independent risk factors for ACS readmissions, further strategies targeting at-risk populations may further decrease the rate of readmissions. Efforts to understand and reduce 30-day ACS readmission rates have resulted in overall improved quality of care for patients.

A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations

Diagnosis codes are used to study SARS-CoV2 infections and COVID-19 hospitalizations in administrative and electronic health record (EHR) data. Using EHR data (April 2020-March 2021) at the Yale-New Haven Health System and the three hospital systems of the Mayo Clinic, computable phenotype definitions based on ICD-10 diagnosis of COVID-19 (U07.1) were evaluated against positive SARS-CoV-2 PCR or antigen tests. We included 69,423 patients at Yale and 75,748 at Mayo Clinic with either a diagnosis code or a positive SARS-CoV-2 test. The precision and recall of a COVID-19 diagnosis for a positive test were 68.8% and 83.3%, respectively, at Yale, with higher precision (95%) and lower recall (63.5%) at Mayo Clinic, varying between 59.2% in Rochester to 97.3% in Arizona. For hospitalizations with a principal COVID-19 diagnosis, 94.8% at Yale and 80.5% at Mayo Clinic had an associated positive laboratory test, with secondary diagnosis of COVID-19 identifying additional patients. These patients had a twofold higher inhospital mortality than based on principal diagnosis. Standardization of coding practices is needed before the use of diagnosis codes in clinical research and epidemiological surveillance of COVID-19.

Economic Issues in Heart Failure in the United States

The cost of heart failure care is high owing to the cost of hospitalization and chronic treatments. Heart failure treatments vary in their benefit and cost. The cost effectiveness of therapies can be determined by comparing the cost of treatment required to obtain a certain benefit, often defined as an increase in 1 year of life. This review was sponsored by the Heart Failure Society of America and describes the growing economic burden of heart failure for patients and the health care system in the United States. It also provides a summary of the cost effectiveness of drugs, devices, diagnostic tests, hospital care, and transitions of care for patients with heart failure. Many medications that are no longer under patent are inexpensive and highly cost-effective. These include angiotensin-converting enzyme inhibitors, beta-blockers and mineralocorticoid receptor antagonists. In contrast, more recently developed medications and devices, vary in cost effectiveness, and often have high out-of-pocket costs for patients.

Depression and Hospital Readmissions in Patients with Heart Failure

Depression increases the risk of mortality in patients with heart failure (HF). Less is known about whether depression predicts multiple readmissions or whether multiple hospitalizations worsen depression in patients with HF. This study aimed to test the hypotheses that depression predicts multiple readmissions in patients hospitalized with HF, and conversely that multiple readmissions predict persistent or worsening depression. All-cause readmissions were ascertained over a 2-year follow-up of a cohort of 400 patients hospitalized with HF. The Patient Health Questionnaire-9 was used to assess depression at index and 3-month intervals. At enrollment in the study, 21% of the patients were mildly depressed and 22% were severely depressed. Higher Patient Health Questionnaire-9 depression scores predicted a higher rate of readmissions (adjusted hazard ratio 1.02, 95% confidence interval 1.00 to 1.04, p = 0.03). The readmission rate was higher in those who were severely depressed than in those without depression (p = 0.0003), but it did not differ between patients who were mildly depressed and patients without depression. Multiple readmissions did not predict persistent or worsening depression, but younger patients in higher New York Heart Association classes were more depressed than other patients. Depression is an independent risk factor for multiple all-cause readmissions in patients hospitalized with HF. Severe depression is a treatable psychiatric co-morbidity that warrants ongoing clinical attention in patients with HF.

Clinical Utility of Overlap Time for Incomplete Relaxation to Predict Cardiac Events in Heart Failure

BACKGROUND

The overlap time of transmitral flow can be a novel marker of subclinical left ventricular dysfunction for predicting adverse events in heart failure (HF). We aimed to (1) investigate the role of overlap time of the E-A wave in association with clinical parameters and (2) evaluate whether the overlap time could add prognostic information with respect to other conventional clinical prognosticators in HF.

METHODS

We prospectively evaluated 153 patients hospitalized with HF (mean age 68 ± 15 years; 63% male). The primary endpoint was readmission following HF or cardiac death.

RESULTS

During a median period of 25 months, 43 patients were readmitted or died. Overlap time appeared to be associated with worse outcomes. After adjustment for readmission scores and ratios of diastolic filling period and cardiac cycle length in a Cox proportional-hazards model, overlap time was associated with event-free survival, independent of elevated left atrial pressure based on guidelines. When overlap time was added to the model based on clinical variables and elevated left atrial pressure, the C-statistic significantly improved from 0.70 (95% CI: 0.63-0.77) to 0.77 (95% CI: 0.69-0.83, compared) (P = 0.035).

CONCLUSION

This preliminary study suggested that prolonged overlap time may have potential for predicting readmission and cardiac mortality risk assessment in patients with HF.

Accuracy of Computable Phenotyping Approaches for SARS-CoV-2 Infection and COVID-19 Hospitalizations from the Electronic Health Record

Objective:

Real-world data have been critical for rapid-knowledge generation throughout the COVID-19 pandemic. To ensure high-quality results are delivered to guide clinical decision making and the public health response, as well as characterize the response to interventions, it is essential to establish the accuracy of COVID-19 case definitions derived from administrative data to identify infections and hospitalizations.

Methods:

Electronic Health Record (EHR) data were obtained from the clinical data warehouse of the Yale New Haven Health System (Yale, primary site) and 3 hospital systems of the Mayo Clinic (validation site). Detailed characteristics on demographics, diagnoses, and laboratory results were obtained for all patients with either a positive SARS-CoV-2 PCR or antigen test or ICD-10 diagnosis of COVID-19 (U07.1) between April 1, 2020 and March 1, 2021. Various computable phenotype definitions were evaluated for their accuracy to identify SARS-CoV-2 infection and COVID-19 hospitalizations.

Results:

Of the 69,423 individuals with either a diagnosis code or a laboratory diagnosis of a SARS-CoV-2 infection at Yale, 61,023 had a principal or a secondary diagnosis code for COVID-19 and 50,355 had a positive SARS-CoV-2 test. Among those with a positive laboratory test, 38,506 (76.5%) and 3449 (6.8%) had a principal and secondary diagnosis code of COVID-19, respectively, while 8400 (16.7%) had no COVID-19 diagnosis. Moreover, of the 61,023 patients with a COVID-19 diagnosis code, 19,068 (31.2%) did not have a positive laboratory test for SARS-CoV-2 in the EHR. Of the 20 cases randomly sampled from this latter group for manual review, all had a COVID-19 diagnosis code related to asymptomatic testing with negative subsequent test results. The positive predictive value (precision) and sensitivity (recall) of a COVID-19 diagnosis in the medical record for a documented positive SARS-CoV-2 test were 68.8% and 83.3%, respectively. Among 5,109 patients who were hospitalized with a principal diagnosis of COVID-19, 4843 (94.8%) had a positive SARS-CoV-2 test within the 2 weeks preceding hospital admission or during hospitalization. In addition, 789 hospitalizations had a secondary diagnosis of COVID-19, of which 446 (56.5%) had a principal diagnosis consistent with severe clinical manifestation of COVID-19 (e.g., sepsis or respiratory failure). Compared with the cohort that had a principal diagnosis of COVID-19, those with a secondary diagnosis had a more than 2-fold higher in-hospital mortality rate (13.2% vs 28.0%, P<0.001). In the validation sample at Mayo Clinic, diagnosis codes more consistently identified SARS-CoV-2 infection (precision of 95%) but had lower recall (63.5%) with substantial variation across the 3 Mayo Clinic sites. Similar to Yale, diagnosis codes consistently identified COVID-19 hospitalizations at Mayo, with hospitalizations defined by secondary diagnosis code with 2-fold higher in-hospital mortality compared to those with a primary diagnosis of COVID-19.

Conclusions:

COVID-19 diagnosis codes misclassified the SARS-CoV-2 infection status of many people, with implications for clinical research and epidemiological surveillance. Moreover, the codes had different performance across two academic health systems and identified groups with different risks of mortality. Real-world data from the EHR can be used to in conjunction with diagnosis codes to improve the identification of people infected with SARS-CoV-2.

Readmission and mortality among heart failure patients with history of hypertension in a statewide database

Objective was to examine the temporal trends in readmission and mortality of heart failure (HF) patients with history of hypertension. This study includes 51 141 patients with history of hypertension who were discharged with a first diagnosis of HF between January 1, 2000, and December 31, 2014. Data were obtained from the Myocardial Infarction Data Acquisition System (MIDAS), a statewide database of all hospitalizations for cardiovascular (CV) disease in New Jersey. The temporal trends of mortality, rates of HF-specific readmission, and all-cause readmissions up to 1 year after discharge were examined using multivariable logistic regression. The difference in all-cause mortality at 3 years between patients who were readmitted compared to those who were not readmitted at 1 year was examined. The number of patients with history of hypertension and HF remained unchanged during the study period. Male gender, black race, comorbidities, and admission to non-teaching hospitals were predictors of HF readmission and CV mortality (P < .05 for all). Readmission rate for any cause increased during the study period (P < .001) while rates of HF readmissions and mortality remained relatively unchanged. Patients that had been readmitted within a year exhibited a significantly higher 3-year mortality (P < .001). CV mortality among HF patients with history of hypertension did not change significantly between 2000 and 2014, while the rates of all-cause readmission increased. Patients who were readmitted had higher 3-year mortality (P < .001) than those who were not.

Temporal Trends in Heart Failure Incidence Among Medicare Beneficiaries Across Risk Factor Strata, 2011 to 2016

IMPORTANCE

Heart failure (HF) incidence is declining among Medicare beneficiaries. However, the epidemiological mechanisms underlying this decline are not well understood.

OBJECTIVE

To evaluate trends in HF incidence across risk factor strata.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective, national cohort study of 5% of all fee-for-service Medicare beneficiaries with no prior HF followed up from 2011 to 2016. The study examined annual trends in HF incidence among groups with and without primary HF risk factors (hypertension, diabetes, and obesity) and predisposing cardiovascular conditions (acute myocardial infarction [MI] and atrial fibrillation [AF]).

EXPOSURES

The presence of comorbid HF risk factors including hypertension, diabetes, obesity, acute MI, and AF identified by International Classification of Diseases, Ninth Revision, Clinical Modification codes and International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes.

MAIN OUTCOMES AND MEASURES

Incident HF, defined using at least 1 inpatient HF claim or at least 2 outpatient HF claims among those without a previous diagnosis of HF.

RESULTS

Of 1 799 027 unique Medicare beneficiaries at risk for HF (median age, 73 years [interquartile range, 68-79 years]; 56% female [805 060-796 253 participants during the study period]), 249 832 had a new diagnosis of HF. The prevalence of all 5 risk factors increased over time (0.8% mean increase in hypertension per year, 1.9% increase in diabetes, 2.9% increase in obesity, 0.2% increase in acute MI, and 0.4% increase in AF). Heart failure incidence declined from 35.7 cases per 1000 beneficiaries in 2011 to 26.5 cases per 1000 beneficiaries in 2016, consistent across subgroups based on sex and race/ethnicity. A greater decline in HF incidence was observed among patients with prevalent hypertension (relative excess decline, 12%), diabetes (relative excess decline, 3%), and obesity (relative excess decline, 16%) compared with those without corresponding risk factors. In contrast, there was a relative increase in HF incidence among individuals with acute MI (26% vs no acute MI) and AF (22% vs no AF).

CONCLUSIONS AND RELEVANCE

Findings of this study suggest that the temporal decline in HF incidence among Medicare beneficiaries reflects a decrease in HF incidence among those with primary HF risk factors. The increase in HF incidence among those with acute MI and those with AF highlights potential targets for future HF prevention strategies.

Financial Toxicity in Atherosclerotic Cardiovascular Disease in the United States: Current State and Future Directions

Atherosclerotic cardiovascular disease (ASCVD) has posed an increasing burden on Americans and the United States healthcare system for decades. In addition, ASCVD has had a substantial economic impact, with national expenditures for ASCVD projected to increase by over 2.5‐fold from 2015 to 2035. This rapid increase in costs associated with health care for ASCVD has consequences for payers, healthcare providers, and patients. The issues to patients are particularly relevant in recent years, with a growing trend of shifting costs of treatment expenses to patients in various forms, such as high deductibles, copays, and coinsurance. Therefore, the issue of “financial toxicity” of health care is gaining significant attention. The term encapsulates the deleterious impact of healthcare expenditures for patients. This includes the economic burden posed by healthcare costs, but also the unintended consequences it creates in form of barriers to necessary medical care, quality of life as well tradeoffs related to non‐health–related necessities. While the societal impact of rising costs related to ASCVD management have been actively studied and debated in policy circles, there is lack of a comprehensive assessment of the current literature on the financial impact of cost sharing for ASCVD patients and their families. In this review we systematically describe the scope and domains of financial toxicity, the instruments that measure various facets of healthcare‐related financial toxicity, and accentuating factors and consequences on patient health and well‐being. We further identify avenues and potential solutions for clinicians to apply in medical practice to mitigate the burden and consequences of out‐of‐pocket costs for ASCVD patients and their families.

Observational study assessing changes in timing of readmissions around postdischarge day 30 associated with the introduction of the Hospital Readmissions Reduction Program

BACKGROUND

The Hospital Readmissions Reduction Program (HRRP) initially penalised hospitals for excess readmission within 30 days of discharge for acute myocardial infarction (AMI), congestive heart failure (CHF) or pneumonia (PNA) and was expanded in subsequent years to include readmissions for chronic obstructive pulmonary disease, elective total hip arthroplasty, total knee arthroplasty and coronary artery bypass graft surgery. We assessed whether HRRP was associated with delays in readmissions from immediately before the 30-day penalty threshold to just after it.

METHODS

We included Medicare fee-for-service beneficiaries discharged between 1 January 2007 and 31 October 2015. Readmissions were assessed until December 31, 2015. The study period was divided into three phases: January 2007 to March 2009 (pre-HRRP), April 2009 to September 2012 (implementation) and October 2012 to December 2015 (penalty). We estimated additional readmissions between postdischarge days 31-35 compared with days 26-30 using a negative binomial difference-in-differences model, comparing target HRRP versus non-HRRP conditions at the same hospital in the same month in the pre-HRRP and penalty phases.

RESULTS

HRRP was not associated with a significant difference in AMI readmissions between postdischarge days 31-35 versus postdischarge days 26-30 for each hospital in the penalty phase, as compared with non-HRRP conditions and the pre-HRRP phase (p=0.19). There were statistically significant increases in readmissions CHF (0.040%, 95% CI 0.024% to 0.056%, p<0.01), PNA (0.022%, 95% CI 0.002% to 0.042%, p=0.03) and stroke (0.035%, 95% CI 0.010% to 0.060%, p<0.01); however, these readmissions represent <0.01% of readmissions during this time period.

CONCLUSION

We did not identify consistently significant associations between HRRP and delayed readmissions, and importantly, any findings suggesting delayed readmissions were extremely small and unlikely to be clinically relevant.

Post-discharge acute care and outcomes following readmission reduction initiatives: national retrospective cohort study of Medicare beneficiaries in the United States

OBJECTIVES

To determine whether patients discharged after hospital admissions for conditions covered by national readmission programs who received care in emergency departments or observation units but were not readmitted within 30 days had an increased risk of death and to evaluate temporal trends in post-discharge acute care utilization in inpatient units, emergency departments, and observation units for these patients.

DESIGN

Retrospective cohort study.

SETTING

Medicare claims data for 2008-16 in the United States.

PARTICIPANTS

Patients aged 65 or older admitted to hospital with heart failure, acute myocardial infarction, or pneumonia-conditions included in the US Hospital Readmissions Reduction Program.

MAIN OUTCOME MEASURES

Post-discharge 30 day mortality according to patients' 30 day acute care utilization; acute care utilization in inpatient and observation units and the emergency department during the 30 day and 31-90 day post-discharge period.

RESULTS

3 772 924 hospital admissions for heart failure, 1 570 113 for acute myocardial infarction, and 3 131 162 for pneumonia occurred. The overall post-discharge 30 day mortality was 8.7% for heart failure, 7.3% for acute myocardial infarction, and 8.4% for pneumonia. Risk adjusted mortality increased annually by 0.05% (95% confidence interval 0.02% to 0.08%) for heart failure, decreased by 0.06% (-0.09% to -0.04%) for acute myocardial infarction, and did not significantly change for pneumonia. Specifically, mortality increased for patients with heart failure who did not utilize any post-discharge acute care, increasing at a rate of 0.08% (0.05% to 0.12%) per year, exceeding the overall absolute annual increase in post-discharge mortality in heart failure, without an increase in mortality in observation units or the emergency department. Concurrent with a reduction in 30 day readmission rates, stays for observation and visits to the emergency department increased across all three conditions during and beyond the 30 day post-discharge period. Overall 30 day post-acute care utilization did not change significantly.

CONCLUSIONS

The only condition with increasing mortality through the study period was heart failure; the increase preceded the policy and was not present among patients who received emergency department or observation unit care without admission to hospital. During this period, the overall acute care utilization in the 30 days after discharge significantly decreased for heart failure and pneumonia, but not for acute myocardial infarction.