Failure To Rescue, What Can Be Done To Prevent It?

Introduction: Failure to Rescue (FTR) is the failure to prevent a patient’s death after a complication. It measures the ability of a hospital to prevent the death of patients who develop one or more complication that was not present at the time of admission. Therefore, the aim of this study is to review the factors that contribute to FTR, and the measures and strategies that can be applied to prevent the FTR events, in order to discuss the best way to improve patient outcomes in the hospital setting. Methods: A search was conducted on PUBMED retrieving a total of 464 articles. A review of the selected articles’ bibliography was conducted to find other relevant articles. Sixty studies were reviewed in this paper. Results: Patient factors as increasing age, comorbidities and frailty increase the risk of FTR, as well as an increasing number of complications. Several hospital factors, nursing care, and microsystem also influence FTR. Some track and Trigger Systems (TTS) and Early Warning Scores (EWS) have been shown to predict clinical deterioration. On the other hand, machine learning systems have outperformed EWS. Rapid response teams have become the standard approach to delivery and escalation of care, and cognitive aids and crisis checklists also have potential to help reduce FTR. Conclusion: Patient and hospital factors are often non-modifiable; thus, microsystem factors could be a target for improvement. Creating clinical pathways can improve surveillance, and communication tools like SBAR can help relay information. EWS, machine learning models and continuous monitoring are strategies that can help detect clinical deterioration. In the efferent limb rapid response teams have shown to reduce FTR.

Pre-hospital Prognostic Factors of Out-of-Hospital Cardiac Arrest: The Difference Between Pediatric and Adult

The prognosis of out-of-hospital cardiac arrest (OHCA) is very poor. Although several pre-hospital factors are associated with survival, the different association of pre-hospital factors with OHCA outcomes in pediatric and adult groups remain unclear. To assess the association of pre-hospital factors with OHCA outcomes among pediatric and adult groups, a retrospective observational study was conducted using the emergency medical service (EMS) database in Kaohsiung from January 2015 to December 2019. Pre-hospital factors, underlying diseases, and OHCA outcomes were collected for the pediatric (Age ≤ 20) and adult groups. Kaplan-Meier type plots and multivariable logistic regression were used to analyze the association between pre-hospital factors and outcomes. In total, 7,461 OHCAs were analyzed. After adjusting for EMS response time, bystander CPR, attended by EMT-P, witness, and pre-hospital defibrillation, we found that age [odds ratio (OR) = 0.877, 95% confidence interval (CI): 0.764–0.990, p = 0.033], public location (OR = 7.681, 95% CI: 1.975–33.428, p = 0.003), and advanced airway management (AAM) (OR = 8.952; 95% CI, 1.414–66.081; p = 0.02) were significantly associated with survival till hospital discharge in pediatric OHCAs. The results of Kaplan-Meier type plots with log-rank test showed a significant difference between the pediatric and adult groups in survival for 2 h (p < 0.001), 24 h (p < 0.001), hospital discharge (p < 0.001), and favorable neurologic outcome (p < 0.001). AAM was associated with improved survival for 2 h (p = 0.015), 24 h (p = 0.023), and neurologic outcome (p = 0.018) only in the pediatric group. There were variations in prognostic factors between pediatric and adult patients with OHCA. The prognosis of the pediatric group was better than that of the adult group. Furthermore, AAM was independently associated with outcomes in pediatric patients, but not in adult patients. Age and public location of OHCA were independently associated with survival till hospital discharge in both pediatric and adult patients.

Impact of insurance type on outcomes in cardiac arrest patients from 2004 to 2015: A nation-wide population-based study

Objectives There do not appear to be many studies which have examined the socio-economic burden and medical factors influencing the mortality and hospital costs incurred by patients with cardiac arrest in South Korea. We analyzed the differences in characteristics, medical factors, mortality, and costs between patients with national health insurance and those on a medical aid program. Methods We selected patients (≥20 years old) who experienced their first episode of cardiac arrest from 2004 to 2015 using data from the National Health Insurance Service database. We analyzed demographic characteristics, insurance type, urbanization of residential area, comorbidities, treatments, hospital costs, and mortality within 30 days and one year for each group. A multiple regression analysis was used to identify an association between insurance type and outcomes. Results Among the 487,442 patients with cardiac arrest, the medical aid group (13.3% of the total) had a higher proportion of females, rural residents, and patients treated in low-level hospitals. The patients in the medical aid group also reported a higher rate of non-shockable conditions; a high Charlson Comorbidity Index; and pre-existing comorbidities, such as hypertension, diabetes mellitus, and renal failure with a lower rate of providing a coronary angiography. The national health insurance group reported a lower one-year mortality rate (91.2%), compared to the medical aid group (94%), and a negative association with one-year mortality (Adjusted OR 0.74, 95% CI 0.71–0.76). While there was no significant difference in short-term costs between the two groups, the medical aid group reported lower long-term costs, despite a higher rate of readmission. Conclusions Medical aid coverage was an associated factor for one-year mortality, and may be the result of an insufficient delivery of long-term services as reflected by the lower long-term costs and higher readmission rates. There were differences of characteristics, comorbidities, medical and hospital factors and treatments in two groups. These differences in medical and hospital factors may display discrepancies by type of insurance in the delivery of services, especially in chronic healthcare services.

Patient and hospital factors associated with 30-day readmissions after coronary artery bypass graft (CABG) surgery: a systematic review and meta-analysis

Background Readmission after coronary artery bypass graft (CABG) surgery is associated with adverse outcomes and significant healthcare costs, and 30-day readmission rate is considered as a key indicator of the quality of care. This study aims to: quantify rates of readmission within 30 days of CABG surgery; explore the causes of readmissions; and investigate how patient- and hospital-level factors influence readmission. Methods We conducted systematic searches (until June 2020) of PubMed and Embase databases to retrieve observational studies that investigated readmission after CABG. Random effect meta-analysis was used to estimate rates and predictors of 30-day post-CABG readmission. Results In total, 53 studies meeting inclusion criteria were identified, including 8,937,457 CABG patients. The pooled 30-day readmission rate was 12.9% (95% CI: 11.3–14.4%). The most frequently reported underlying causes of 30-day readmissions were infection and sepsis (range: 6.9–28.6%), cardiac arrythmia (4.5–26.7%), congestive heart failure (5.8–15.7%), respiratory complications (1–20%) and pleural effusion (0.4–22.5%). Individual factors including age (OR per 10-year increase 1.12 [95% CI: 1.04–1.20]), female sex (OR 1.29 [1.25–1.34]), non-White race (OR 1.15 [1.10–1.21]), not having private insurance (OR 1.39 [1.27–1.51]) and various comorbidities were strongly associated with 30-day readmission rates, whereas associations with hospital factors including hospital CABG volume, surgeon CABG volume, hospital size, hospital quality and teaching status were inconsistent. Conclusions Nearly 1 in 8 CABG patients are readmitted within 30 days and the majority of these are readmitted for noncardiac causes. Readmission rates are strongly influenced by patients’ demographic and clinical characteristics, but not by broadly defined hospital characteristics.

Hospital Factors, Performance on Process Measures After Transient Ischemic Attack, and 90-Day Ischemic Stroke Incidence

Background and Purpose: We determined the association between hospital factors, performance on transient ischemic attack (TIA) process measures, and 90-day ischemic stroke incidence. Methods: Longitudinal analysis of retrospectively obtained data on 9168 veterans ≥18 years with TIA presenting to the emergency department or inpatient unit at 69 Veterans Affairs hospitals with ≥10 eligible patients per year in fiscal years 2015 to 2018. Process measures were high/moderate potency statin within 7 days of discharge, antithrombotic by day 2, and hypertension control (<140/90 mm Hg) at 90 days. The outcome was 90-day stroke incidence. Results: During the 4-year study period, hospitals significantly increased statin use (adjusted odds ratio [aOR] per 1-year increase, 1.24 [95% CI, 1.17–1.32]; P <0.001), whereas neither hypertension control ( P =0.44) nor antithrombotic use ( P =0.82) improved over time. Hospitals that admitted a higher proportion of TIA patients versus emergency department discharge had significantly greater use of statins (aOR per 10-percentage point increase in the proportion of TIA patients admitted, 1.09 [1.03–1.16]; P =0.003) and antithrombotics (aOR per 10-percentage point increase in TIA patients admitted, 1.14 [1.06–1.23]; P <0.001). Hospitals with higher emergency physician staffing and lower TIA patient volume had greater use of antithrombotics (aOR per 1 full-time physician increase, 1.05 [1.01–1.08]; P =0.008 and aOR per 10-patient decrease in volume, 1.09 [1.01–1.16]; P =0.02). Higher emergency physician staffing was associated with lower 90-day stroke incidence (aOR per 1 full-time physician increase, 0.96 [0.92–0.99]; P =0.02) but other hospital factors were not. Conclusions: Hospitals admitting higher percentages of TIA patients and having higher emergency physician staffing have greater performance on select guideline-concordant process measures for TIA. Higher emergency physician staffing was associated with improved outcomes 90 days after TIA.