Obtaining a follow-up appointment before discharge protects against readmission for patients with acute coronary syndrome and heart failure: A quality improvement project

Recent functional decline and outpatient follow-up after hospital discharge: a cohort study

BACKGROUND

Functional decline is common following acute hospitalization and is associated with hospital readmission, institutionalization, and mortality. People with functional decline may have difficulty accessing post-discharge medical care, even though early physician follow-up has the potential to prevent poor outcomes and is integral to high-quality transitional care. We sought to determine whether recent functional decline was associated with lower rates of post-discharge physician follow-up, and whether this association changed during the COVID-19 pandemic, given that both functional decline and COVID-19 may affect access to post-discharge care.

METHOD

We conducted a retrospective cohort study using health administrative data from Ontario, Canada. We included patients over 65 who were discharged from an acute care facility during March 1st, 2019 - January 31st, 2020 (pre-COVID-19 period), and March 1st, 2020 - January 31st, 2021 (COVID-19 period), and who were assessed for home care while in hospital. Patients with and without functional decline were compared. Our primary outcome was any physician follow-up visit within 7 days of discharge. We used propensity score weighting to compare outcomes between those with and without functional decline.

RESULTS

Our study included 21,771 (pre-COVID) and 17,248 (COVID) hospitalized patients, of whom 15,637 (71.8%) and 12,965 (75.2%) had recent functional decline. Pre-COVID, there was no difference in physician follow-up within 7 days of discharge (Functional decline 45.0% vs. No functional decline 44.0%; RR = 1.02, 95% CI 0.98-1.06). These results did not change in the COVID-19 period (Functional decline 51.1% vs. No functional decline 49.4%; RR = 1.03, 95% CI 0.99-1.08, Z-test for interaction p = 0.72). In the COVID-19 cohort, functional decline was associated with having a 7-day physician virtual visit (RR 1.15; 95% CI 1.08-1.24) and a 7-day physician home visit (RR 1.64; 95% CI 1.10-2.43).

CONCLUSIONS

Functional decline was not associated with reduced 7-day post-discharge physician follow-up in either the pre-COVID-19 or COVID-19 periods. In the COVID-19 period, functional decline was positively associated with 7-day virtual and home-visit follow-up.

Values and tensions of a health education program based on evidence-based medicine: a qualitative study

Aim

This study explored how patients, caregivers, clinicians, designers, and funders who worked collaboratively on a health education program experienced its design. The program was based on evidence-based medicine and knowledge transmission.

Subject and methods

Through exploratory qualitative research, the authors conducted 21 semistructured interviews, collected six nonparticipatory observations, and conducted a documentary analysis. Data were analyzed using thematic analysis, producing rich descriptions about the participants’ experiences. The researchers’ interpretations were validated through peer review.

Results

Three themes were revealed by the findings: background, values, and tensions. All participants had a range of assumptions about this experience regarding which evidence-based recommendations should be prioritized and disseminated to patients/caregivers in program implementation. These assumptions were based on participants’ beliefs about how people make evidence-informed decisions, allowing them to take charge of their health. The authors found a gap between these assumptions and the purposes of the educational program.

Conclusion

Although health education programs aim to foster patients’ informed decision making and health empowerment, in our case we found some assumptions that were not in line with the objectives of the educational program. We hypothesize that some gaps in the program design, derived from different assumptions, such as (a) conflicts of particular interests, (b) knowledge gaps about health-disease processes, and (c) power asymmetries between doctors and patients/caregivers, could hinder the goals of health education (e.g., engagement) in the practice of evidence-based medicine.

Follow-up Post-discharge and Readmission Disparities Among Medicare Fee-for-Service Beneficiaries, 2018

BACKGROUND

Previous studies have identified disparities in readmissions among Medicare beneficiaries hospitalized for the Hospital Readmissions Reduction Program's (HRRP's) priority conditions. Evidence suggests timely follow-up is associated with reduced risk of readmission, but it is unknown whether timely follow-up reduces disparities in readmission.

OBJECTIVE

To assess whether follow-up within 7 days after discharge from a hospitalization reduces risk of readmission and mitigates identified readmission disparities.

DESIGN

A retrospective cohort study using Cox proportional hazards models to estimate the associations between sociodemographic characteristics (race and ethnicity, dual-eligibility status, rurality, and area social deprivation), follow-up, and readmission. Mediation analysis was used to examine if disparities in readmission were mitigated by follow-up.

PARTICIPANTS

We analyzed data from 749,402 Medicare fee-for-service beneficiaries hospitalized for acute myocardial infarction, chronic obstructive pulmonary disease, heart failure, or pneumonia, and discharged home between January 1 and December 1, 2018.

MAIN MEASURE

All-cause unplanned readmission within 30 days after discharge.

KEY RESULTS

Post-discharge follow-up within 7 days of discharge was associated with a substantially lower risk of readmission (HR: 0.52, 95% CI: 0.52-0.53). Across all four HRRP conditions, beneficiaries with dual eligibility and beneficiaries living in areas with high social deprivation had a higher risk of readmission. Non-Hispanic Black beneficiaries had higher risk of readmission after hospitalization for pneumonia relative to non-Hispanic Whites. Mediation analysis suggested that 7-day follow-up mediated 21.2% of the disparity in the risk of readmission between dually and non-dually eligible beneficiaries and 50.7% of the disparity in the risk of readmission between beneficiaries living in areas with the highest and lowest social deprivation. Analysis suggested that after hospitalization for pneumonia, 7-day follow-up mediated nearly all (97.5%) of the increased risk of readmission between non-Hispanic Black and non-Hispanic White beneficiaries.

CONCLUSIONS

Improving rates of follow-up could be a strategy to reduce readmissions for all beneficiaries and reduce disparities in readmission based on sociodemographic characteristics.

Outcomes of Hospitalizations With Septic Shock Complicated by Types 1 and 2 Myocardial Infarction

Septic shock is a life-threatening host response to infection and a significant contributor to cost burden in the United States. Furthermore, sepsis-related inflammation has been linked to myocardial infarction (MI). We sought to examine the association of type 1 and type 2 MI with outcomes in hospitalizations admitted with septic shock. The National Readmission Database 2018 was queried to identify hospitalizations with hospital discharge diagnoses of septic shock without MI, septic shock with type 1 MI, or septic shock with type 2 MI. Complex-sample multivariable logistic and linear regression models were used to determine the association of these conditions with clinical outcomes. Of 354,528 hospitalizations with septic shock, 11,519 had type 1 MI (3.2%) and 13,970 had type 2 MI (3.9%). Compared with septic shock without MI, type 1 MI was associated with higher mortality (adjusted odds ratio [OR] 1.67, 95% confidence interval [CI] 1.57 to 1.77), costs (adjusted parameter estimate $4,571, 95% CI 3,020 to 6,122), and discharge to facility (adjusted OR 1.09, 95% CI 1.01 to 1.17). In contrast, septic shock with type 2 MI was associated with similar mortality and discharge to nursing facility and higher costs (adjusted parameter estimate 1,798, 95% CI 549 to 3,047). Septic shock hospitalizations with type 1 MI had higher in-hospital mortality (adjusted OR 1.74, 95% CI 1.60 to 1.90, p <0.001) compared with type 2 MI. In conclusion, type 1 MI is associated with higher mortality and resource utilization among septic shock hospitalizations. Furthermore, type 2 MI was associated with higher resource utilization.

Machine learning prediction model of acute kidney injury after percutaneous coronary intervention

Acute kidney injury (AKI) after percutaneous coronary intervention (PCI) is associated with a significant risk of morbidity and mortality. The traditional risk model provided by the National Cardiovascular Data Registry (NCDR) is useful for predicting the preprocedural risk of AKI, although the scoring system requires a number of clinical contents. We sought to examine whether machine learning (ML) techniques could predict AKI with fewer NCDR-AKI risk model variables within a comparable PCI database in Japan. We evaluated 19,222 consecutive patients undergoing PCI between 2008 and 2019 in a Japanese multicenter registry. AKI was defined as an absolute or a relative increase in serum creatinine of 0.3 mg/dL or 50%. The data were split into training (N = 16,644; 2008-2017) and testing datasets (N = 2578; 2017-2019). The area under the curve (AUC) was calculated using the light gradient boosting model (GBM) with selected variables by Lasso and SHapley Additive exPlanations (SHAP) methods among 12 traditional variables, excluding the use of an intra-aortic balloon pump, since its use was considered operator-dependent. The incidence of AKI was 9.4% in the cohort. Lasso and SHAP methods demonstrated that seven variables (age, eGFR, preprocedural hemoglobin, ST-elevation myocardial infarction, non-ST-elevation myocardial infarction/unstable angina, heart failure symptoms, and cardiogenic shock) were pertinent. AUC calculated by the light GBM with seven variables had a performance similar to that of the conventional logistic regression prediction model that included 12 variables (light GBM, AUC [training/testing datasets]: 0.779/0.772; logistic regression, AUC [training/testing datasets]: 0.797/0.755). The AKI risk model after PCI using ML enabled adequate risk quantification with fewer variables. ML techniques may aid in enhancing the international use of validated risk models.

Identify Early and Involve Everyone: Interdisciplinary Comprehensive Care Pathway Developed for Inpatient Management and Transitions of Care for Heart Failure Patients Reported Using SQUIRE 2.0 Guidelines

Introduction

Heart failure accounts for 1-2% of overall healthcare costs. While the link between re-hospitalization and mortality is unclear, care pathways that standardize inpatient management and establish outpatient follow-up improve patient outcomes and reduce morbidity.

Aim

To implement a comprehensive interdisciplinary care pathway for heart failure patients with the goal of optimizing inpatient management and improving transitions of care.

Methods

To address this clinical need, New York-Presbyterian Brooklyn Methodist Hospital (NYP-BMH) identified resources needed to optimize patient care, developed an inpatient admission order set (so-called “power plan”), and implemented a multidisciplinary clinical care pathway. The Plan-Do-Study-Act cycle addressed the implementation obstacles. Interdisciplinary rounds guided day-to-day management and addressed barriers. Our team developed a sustainable care pathway, and measured the utilization of pharmacy, nutrition, physical therapy, case management, and social work resources; outpatient appointments were made prior to discharge. We used the Standards for Quality Improvement Reporting Excellence (SQUIRE) 2.0 guidelines to guide our planning and evaluation of this quality improvement initiative.

Results

Our intervention markedly increased the number of heart failure hospitalizations that were identified on admission, and the use of pharmacy/nutrition services was greater after the intervention. The utilization of our “power plan” promoted adherence to a series of evidence-based best practices, but these measures had no significant impact on readmissions as a whole. The involvement of the case management support team increased outpatient appointments made for patients prior to discharge and aided in the transition of care from inpatient to outpatient management.

Conclusion

The management of heart failure patients starts in the hospital and continues in the community. Patients who are treated in a standardized dedicated care pathway have reduced morbidity and better outcomes. Identifying these patients early, involving a comprehensive team, and transitioning their care to the outpatient setting improves the quality of care in these patients.

Right on Schedule: Improving the Rate of Clinic Appointments Scheduled Prior to Hospital Hospital Discharge

Introduction:

Children with cancer and blood disorders have many healthcare needs that often require inpatient and outpatient management. There is potential for a lapse in care when patients frequently transition between these settings. We aimed to improve the process and increase the rate of scheduled outpatient follow-up appointments at the time of inpatient discharge for all pediatric hematology-oncology patients from a baseline of 68–80%.

Methods:

A multidisciplinary team developed several Plan-Do-Study-Act cycles to standardize and improve the process of scheduling follow-up appointments, communication to schedulers, and discussion of discharge planning. QI Macros for Excel Version 2019.06 was used for statistical analysis. Our primary outcome was displayed over time with a p-chart.

Results:

Plan-Do-Study-Act interventions had a statistically significant impact in increasing the percentage of patients with follow-up outpatient appointments scheduled at the time of inpatient discharge from a baseline of 68% to consistently over 80%.

Conclusions:

This study demonstrates that standardization of care processes and reminders and education of healthcare providers about the new approaches can improve the rates of outpatient follow-up appointments scheduled at the time of hospital discharge from inpatient care.

Medication Supports at Transitions Between Hospital and Other Care Settings: A Rapid Scoping Review

PURPOSE

Transitions in care (TiC) often involves managing medication changes and can be vulnerable moments for patients. Medication support, where medication changes are reviewed with patients and caregivers to increase knowledge and confidence about taking medications, is key to successful transitions. Little is known about the optimal tools and processes for providing medication support. This study aimed to identify describe patient or caregiver-centered medication support processes or tools that have been studied within 3 months following TiC between hospitals and other care settings.

METHODS

Rapid scoping review; English-language publications from OVID MEDLINE, OVID EMBASE, Cochrane Library and EBSCO CINAHL (2004-July 2019) that assessed medication support interventions delivered within 3 months following discharge were included. A subset of titles and abstracts were assessed by two reviewers to evaluate agreement and once reasonable agreement was achieved, the remainder were assessed by one reviewer. Eligibility assessment for full-text articles and data charting were completed by an experienced reviewer.

RESULTS

A total of 7671 unique citations were assessed; 60 studies were included. Half of the studies (n = 30/60) were randomized controlled trials. Most studies (n = 45/60) did not discuss intervention development, particularly whether end users were involved in intervention design. Many studies (n = 37/60) assessed multi-component interventions with written/print and verbal education components. Few studies (n = 5/60) included an electronic component. Very few studies (n = 4/60) included study populations at high risk of adverse events at TiC (eg, people with physical or intellectual disabilities, low literacy or language barriers).

CONCLUSION

The majority of studies were randomized controlled trials involving verbal counselling and/or physical document delivered to the patient before discharge. Few studies involved electronic components or considered patients at high-risk of adverse events. Future studies would benefit from improved reporting on development, consideration for electronic interventions, and improved reporting on patients with higher medication-related needs.

Updated antithrombotic strategies to reduce the burden of cardiovascular recurrences in patients with chronic coronary syndrome

Despite recent achievements in secondary cardiovascular prevention, the risk of further events in patients with chronic coronary syndromes (CCS) remains elevated. Highest risk is seen in patients with recurrent events, comorbidities or multisite atherosclerosis. Optimising antithrombotic strategies in this setting may significantly improve outcomes. The higher the baseline risk, the higher the absolute event reduction with approaches using combined antithrombotic treatments. Tailoring such strategies to the individual patient risk appears crucial to achieve net benefit (i.e., substantial ischaemic event prevention at a limited cost in terms of bleeding). This paper focuses on antithrombotic and non-pharmacological approaches to secondary cardiovascular disease prevention in CCS. In particular, we critically review current evidence on the use of dual antithrombotic therapy, including the newest approach of aspirin plus low-dose anticoagulation and its net clinical outcome according to baseline risk.

Improving hospital readmission prediction using individualized utility analysis

OBJECTIVE

Machine learning (ML) models for allocating readmission-mitigating interventions are typically selected according to their discriminative ability, which may not necessarily translate into utility in allocation of resources. Our objective was to determine whether ML models for allocating readmission-mitigating interventions have different usefulness based on their overall utility and discriminative ability.

MATERIALS AND METHODS

We conducted a retrospective utility analysis of ML models using claims data acquired from the Optum Clinformatics Data Mart, including 513,495 commercially-insured inpatients (mean [SD] age 69 [19] years; 294,895 [57%] Female) over the period January 2016 through January 2017 from all 50 states with mean 90 day cost of $11,552. Utility analysis estimates the cost, in dollars, of allocating interventions for lowering readmission risk based on the reduction in the 90-day cost.

RESULTS

Allocating readmission-mitigating interventions based on a GBDT model trained to predict readmissions achieved an estimated utility gain of $104 per patient, and an AUC of 0.76 (95% CI 0.76, 0.77); allocating interventions based on a model trained to predict cost as a proxy achieved a higher utility of $175.94 per patient, and an AUC of 0.62 (95% CI 0.61, 0.62). A hybrid model combining both intervention strategies is comparable with the best models on either metric. Estimated utility varies by intervention cost and efficacy, with each model performing the best under different intervention settings.

CONCLUSION

We demonstrate that machine learning models may be ranked differently based on overall utility and discriminative ability. Machine learning models for allocation of limited health resources should consider directly optimizing for utility.

Reduction of the rate of hospitalization in patients with acute coronary syndrome: An action research

Background:

Readmission of patients with Acute Coronary Syndrome (ACS) causes many problems for them and their family. This study aimed to improve the quality of care provided to patients with ACS and discover solutions to reduce the rate of readmission among them.

Materials and Method:

This participatory action research study was done based on Streubert and Carpenter approach. This study included 45 participants (31 patients and 14 stakeholders) and carried out in a hospital affiliated to Isfahan University of Medical Sciences, Iran, from 2013 to 2014. Solutions with high and moderate feasibility, flexibility, and suitability were implemented in each cycle until reaching <15% readmission rate. Data were analyzed using SPSS (V.16) and running descriptive and inferential statistics.

Results:

In this study, several actions were performed in each cycle such as assigning a free and 24-h telephone line was patients to contact nurses and face-to-face patient's education. Second cycle actions included active participation of all nurses in the education of patients and involvement of families in patient care. By carrying out the first action cycle, the readmission rate reached 35%, which was not favorable. By completing the second action cycle, the readmission rate reached 12%, which was desirable and significantly lower than the first cycle.

Conclusion:

Discovering possible solutions with the participation of stakeholders in therapeutic settings that have feasibility, flexibility, and suitability can lead to improved care quality and reduced readmission rate in patients with ACS, especially if the families of the patients also participate in action cycles.

Home Healthcare Nursing Visits for Nonhomebound Patients With Heart Failure After Hospital Discharge: A Quality-Improvement Pilot Project

Frequent rehospitalizations among patients with heart failure (HF) result in patient burden and high cost. Homebound patients with HF qualify for home healthcare after hospital discharge. It is not known if nonhomebound patients with HF could also benefit from home healthcare nursing (HHN) visits to improve the transition from hospital to home. The purpose of this quality-improvement pilot study was to assess the impact of HHN visits provided to nonhomebound HF patients after hospital discharge on 30-day rehospitalization rates. We included patients with HF who were ineligible for home healthcare services due to their nonhomebound status. Home healthcare nurses followed a modified version of the discharge checklist from the American Heart Association's Rise Above Heart Failure materials, and provided education as appropriate based on patients' responses. We enrolled 68 patients in the study. The mean age was 60.2 years; 61.8% were male and 77.9% were White. Based on patient responses to the checklist, key areas addressed during HHN visits were medication management and HF self-care. In the HHN visit group, 15% of the patients experienced rehospitalization within 30 days, compared with 23% in the non-HHN visit group among 540 patients discharged in the same time frame who met the inclusion criteria but were not enrolled in the study (p = .12). Our pilot data show that HHN visits for nonhomebound patients are feasible and result in a numerically lower 30-day rehospitalization rate after discharge. Further study is needed to confirm the clinical efficacy of this approach.

Association of decreasing hemoglobin levels with the incidence of acute kidney injury after percutaneous coronary intervention: a prospective multi-center study

Acute kidney injury (AKI) is common in patients undergoing percutaneous coronary intervention (PCI). One risk factor for AKI is periprocedural hemoglobin drop level (> 3 g/dL); however, whether the relationship between hemoglobin drop and AKI is linear or nonlinear remains unknown. We aimed to investigate the relationship between periprocedural hemoglobin drop and AKI after PCI. We evaluated 14,273 consecutive patients undergoing PCI between September 2008 and March 2019. AKI was defined as an absolute or a relative increase in serum creatinine level of 0.3 mg/dL or 50%, respectively. Restricted cubic spline was constructed to assess the association between hemoglobin drop and AKI by logistic regression and machine learning (ML) models, which were used to predict the risk of AKI. The patients' mean age was 68.4 ± 11.6 years; the AKI incidence was 10.5% (N = 1499). An absolute > 3 g/dL or 20% relative decrease in hemoglobin level was an independent predictor of AKI incidence (odds ratio, OR [95% confidence interval, CI]: 2.24 [1.92-2.61], P < 0.001; 2.35 [2.04-2.71], P < 0.001, respectively). An adjusted restricted cubic spline demonstrated that absolute/relative decrease in hemoglobin was linearly associated with AKI. Logistic and ML models with absolute/relative hemoglobin changes were comparable while estimating the risk of AKI (absolute area under the curve [AUC] (logistic):0.826, AUC (ML): 0.820; relative AUC (logistic): 0.818, AUC (ML): 0.816). An absolute/relative decrease in periprocedural hemoglobin after PCI was linearly associated with AKI. Detection of a relative/absolute decrease in hemoglobin may help clinicians identify individuals as high risk for AKI after PCI.

Prognostic Impact of Previous Hospitalization in Acute Heart Failure Patients

BACKGROUND

The natural course of heart failure (HF) is typically associated with repeated hospitalizations, and subsequently, patient prognosis deteriorates. However, the precise relationship between repeated admissions for HF and long-term prognosis remains unknown. Methods and Results: We analyzed data from 1,730 consecutive acute HF patients registered in the West Tokyo Heart Failure (WET-HF) registry between June 2005 and April 2014 (median age, 76 years). Patients were divided into 3 groups according to the number of previous HF admissions at the time of the index admission (0, n=876 [55.4%]; 1, n=425 [26.9%]; ≥2, n=279 [17.7%] previous admissions). A history of multiple previous admissions was an independent predictor for all-cause death and HF readmission in reference to a history of a single previous admission (hazard ratio (HR), 1.53; 95% confidence interval (CI) 1.10-2.13; HR, 1.90 95% CI, 1.47-2.44, respectively) or no previous admissions (HR, 1.37, 95% CI, 1.01-1.85; HR, 2.83, 95% CI, 2.19-3.65, respectively). On the other hand, a history of a single previous admission was an independent predictor for HF readmission in reference to a history of no previous admissions (HR, 1.51, 95% CI, 1.18-1.92), but not for all-cause death (HR, 0.89, 95% CI, 0.66-1.20).

CONCLUSIONS

Based on a contemporary multicenter HF registry, a history of multiple previous HF admissions was revealed as an independent, strong risk factor of adverse events following the index admission. The number of hospitalizations could be a simple and important surrogate indicating subsequent adverse events in patients with HF.

Effectiveness of a transition plan at discharge of patients hospitalized with heart failure: a before-and-after study

Aims

We evaluated the effectiveness of a multidisciplinary transition plan to reduce early readmission among heart failure patients.

Methods and results

We conducted a before‐and‐after study in a tertiary internal medicine department, comparing 3 years of retrospective data (pre‐intervention) and 13 months of prospective data (intervention period). Intervention was the introduction in 2013 of a transition plan performed by a multidisciplinary team. We included all consecutive patients hospitalized with symptomatic heart failure and discharged to home. The outcomes were the fraction of days spent in hospital because of readmission, based on the sum of all days spent in hospital, and the rate of readmission. The same measurements were used for those with potentially avoidable readmissions. Four hundred thirty‐one patients were included and compared with 1441 patients in the pre‐intervention period. Of the 431 patients, 138 received the transition plan while 293 were non‐completers. Neither the fraction of days spent for readmissions nor the rate of readmission decreased during the intervention period. However, non‐completers had a higher rate of the fraction of days spent for 30 day readmission (19.2% vs. 16.1%, P = 0.002) and for potentially avoidable readmission (9.8% vs. 13.2%, P = 0.001). The rate of potentially avoidable readmission decreased from 11.3% (before) to 9.9% (non‐completers) and 8.7% (completers), reaching the adjusted expected range given by SQLape® (7.7–9.1%).

Conclusions

A transition plan, requiring many resources, could decrease potentially avoidable readmission but shows no benefit on overall readmission. Future research should focus on potentially avoidable readmissions and other indicators such as patient satisfaction, adverse drug events, or adherence.