Trends and Variations in the Rates of Hospital Complications, Failure-to-Rescue and 30-Day Mortality in Surgical Patients in New South Wales, Australia, 2002-2009 (original) (raw)
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Perioperative patient safety indicators and hospital surgical volumes
BMC Research Notes, 2014
Background: Since the late 1990s, patient safety has been an important policy issue in developed countries. To evaluate the effectiveness of the activities of patient safety, it is necessary to quantitatively assess the incidence of adverse events by types of failure mode using tangible data. The purpose of this study is to calculate patient safety indicators (PSIs) using the Japanese Diagnosis Procedure Combination/per-diem payment system (DPC/PDPS) reimbursement data and to elucidate the relationship between perioperative PSIs and hospital surgical volume. Methods: DPC/PDPS data of the Medi-Target project managed by the All Japan Hospital Association were used. An observational study was conducted where PSIs were calculated using an algorithm proposed by the US Agency for Healthcare Research and Quality. We analyzed data of 1,383,872 patients from 188 hospitals who were discharged from January 2008 to December 2010. Results: Among 20 provider level PSIs, four PSIs (three perioperative PSIs and decubitus ulcer) and mortality rates of postoperative patients were related to surgical volume. Low-volume hospitals (less than 33rd percentiles surgical volume per month) had higher mortality rates (5.7%, 95% confidence interval (CI), 3.9% to 7.4%) than mid-(2.9%, 95% CI, 2.6% to 3.3%) or high-volume hospitals (2.7%, 95% CI, 2.5% to 2.9%). Low-volume hospitals had more deaths among surgical inpatients with serious treatable complications (38.5%, 95% CI, 33.7% to 43.2%) than high-volume hospitals (21.4%, 95% CI, 19.0% to 23.9%). Also Low-volume hospitals had lower proportion of difficult surgeries (54.9%, 95% CI, 50.1% to 59.8%) compared with high-volume hospitals (63.4%, 95% CI, 62.3% to 64.6%). In low-volume hospitals, limited experience may have led to insufficient care for postoperative complications. Conclusions: We demonstrated that PSIs can be calculated using DPC/PDPS data and perioperative PSIs were related to hospital surgical volume. Further investigations focusing on identifying risk factors for poor PSIs and effective support to these hospitals are needed.
Relationship between Patient Safety and Hospital Surgical Volume
Health Services Research, 2012
Objective. To examine the relationship between hospital volume and in-hospital adverse events. Data Sources. Patient safety indicator (PSI) was used to identify hospital-acquired adverse events in the Nationwide Inpatient Sample database in abdominal aortic aneurysm, coronary artery bypass graft, and Roux-en-Y gastric bypass from 2005 to 2008. Study Design. In this observational study, volume thresholds were defined by mean year-specific terciles. PSI risk-adjusted rates were analyzed by volume tercile for each procedure. Principal Findings. Overall, hospital volume was inversely related to preventable adverse events. High-volume hospitals had significantly lower risk-adjusted PSI rates compared to lower volume hospitals (p < .05). Conclusion. These data support the relationship between hospital volume and quality health care delivery in select surgical cases. This study highlights differences between hospital volume and risk-adjusted PSI rates for three common surgical procedures and highlights areas of focus for future studies to identify pathways to reduce hospital-acquired events. Key Words. Patient safety indicators, adverse events, hospital surgical volume With the Institute of Medicine's 1999 landmark report, To Err Is Human (Kohn, Corrigan, and Donaldson 1999), patient safety became a key component of health care quality. Patient safety is measured by monitoring preventable adverse events (PAEs), which are injuries caused by medical management rather than by the underlying disease of the patient . Numerous studies have shown an association between PAE and increased mortality, length of stay, and readmissions (Zhan and Miller 2003;). To monitor PAE in hospitals, the Agency for Healthcare Research and Quality (AHRQ) established a set of
Abstract Objectives: This study aims to assess the potential for deriving 2 mortality based failure to rescue indicators and a proxy measure, based on exceptionally long length of stay, from English hospital administrative data by exploring change in coding practice over time and measuring associations between failure to rescue and factors which would suggest indicators derived from these data are valid. Design: Cross sectional observational study of routinely collected administrative data. Setting: 146 general acute hospital trusts in England Participants: Discharge data from 66,100,672 surgical admissions (1997 to 2009) Results: Median percentage of surgical admissions with at least one secondary diagnosis recorded increased from 26% in 1997/8 to 40% in 2008/9. The failure to rescue rate for a hospital appears to be relatively stable over time: inter-year correlations between 2007/8 and 2008/9 were r=0.92 to r=0.94. No failure to rescue indicator was significantly correlated with average number of secondary diagnoses coded per hospital. Regression analyses showed that failure to rescue was significantly associated (p<0.05) with several hospital characteristics previously associated with quality including staffing levels. Higher medical staffing (doctors + nurses) per bed and more doctors relative to the number of nurses were associated with lower failure to rescue. Conclusion: Coding practice has improved, and failure to rescue can be derived from English administrative data. The suggestion that it is particularly sensitive to nursing is not clearly supported. Although the patient population is more homogenous than for other mortality measures, risk adjustment is still required.
International journal of nursing studies, 2012
2 Is "failure to rescue" derived from administrative data in England a nurse sensitive patient safety indicator for surgical care? Observational study Abstract Background: 'Failure to rescue' -death after a treatable complication -is used as a nursing sensitive quality indicator in the USA. It is associated with the size of the nursing workforce relative to patient load, for example patient to nurse ratio, although assessments of nurse sensitivity have not previously considered other staff groups. This study aims to assess the potential to derive failure to rescue and a proxy measure, based on long length of stay, from English hospital administrative data. By exploring change in coding practice over time and measuring associations between failure to rescue and factors including staffing, we assess whether these are useful nurse sensitive indicators.
Quality and safety on an acute surgical ward: an exploratory cohort study of process and outcome
Annals of …, 2009
Objective: To evaluate patient safety in an emergency surgical unit using process and outcome measures in parallel. Background: Patient harm from errors in care is common in modern surgical practice. Measurement of the problem is essential to any solution, but current methods of evaluating patient harm are either impractical or inadequate. We have therefore analyzed compliance with safety-relevant care processes, with the aim of developing a process-based system for evaluating ward safety. Methods: Adverse events (AE), potential adverse events (PAE), and 7 safety-relevant processes were measured on a 38-bed surgical emergency unit over a 16-week period. AE, PAE, and process measures were studied by prospective direct observation in large convenience samples, using objective measures. Possible influences on AE and PAE risk were analyzed. Results: Compliance with the 7 processes studied ranged from 23% to 89%. The AE and PAE rates were 11.9% and 13.8% in a 63% sample of admissions (n ϭ 607). Length of stay was significantly associated with both AE (P Ͻ 0.001) and PAE (P Ͻ 0.001). Having an operation was also associated with AE (P ϭ 0.001) but not with PAE. No other factors appeared to influence AE/PAE rates. Delays were the commonest causes of both AE and PAE. Conclusions: Compliance with individual care processes on a ward with average levels of patient harm is poor. Length of hospital stay increases the risk of both AE and PAE, suggesting a system defect. A bundle of care processes may be useful for monitoring safety improvement.
Health Services Research, 2009
Objectives. To examine the criterion validity of the Agency for Health Care Research and Quality (AHRQ) Patient Safety Indicators (PSIs) using clinical data from the Veterans Health Administration (VA) National Surgical Quality Improvement Program (NSQIP). Data Sources. Fifty five thousand seven hundred and fifty two matched hospitalizations from 2001 VA inpatient surgical discharge data and NSQIP chart-abstracted data. Study Design. We examined the sensitivities, specificities, positive predictive values (PPVs), and positive likelihood ratios of five surgical PSIs that corresponded to NSQIP adverse events. We created and tested alternative definitions of each PSI. Data Collection. FY01 inpatient discharge data were merged with 2001 NSQIP data abstracted from medical records for major noncardiac surgeries. Principal Findings. Sensitivities were 19-56 percent for original PSI definitions; and 37-63 percent using alternative PSI definitions. PPVs were 22-74 percent and did not improve with modifications. Positive likelihood ratios were 65-524 using original definitions, and 64-744 using alternative definitions. ''Postoperative respiratory failure'' and ''postoperative wound dehiscence'' exhibited significant increases in sensitivity after modifications. Conclusions. PSI sensitivities and PPVs were moderate. For three of the five PSIs, AHRQ has incorporated our alternative, higher sensitivity definitions into current PSI algorithms. Further validation should be considered before most of the PSIs evaluated herein are used to publicly compare or reward hospital performance.
Patient Safety in Surgery, 2011
We need to know the scale and underlying causes of surgical adverse events (AEs) in order to improve the safety of care in surgical units. However, there is little recent data. Previous record review studies that reported on surgical AEs in detail are now more than ten years old. Since then surgical technology and quality assurance have changed rapidly. The objective of this study was to provide more recent data on the incidence, consequences, preventability, causes and potential strategies to prevent AEs among hospitalized patients in surgical units. Methods: A structured record review study of 7,926 patient records was carried out by trained nurses and medical specialist reviewers in 21 Dutch hospitals. The aim was to determine the presence of AEs during hospitalizations in 2004 and to consider how far they could be prevented. Of all AEs, the consequences, responsible medical specialty, causes and potential prevention strategies were identified. Surgical AEs were defined as AEs attributable to surgical treatment and care processes and were selected for analysis in detail. Results: Surgical AEs occurred in 3.6% of hospital admissions and represented 65% of all AEs. Forty-one percent of the surgical AEs was considered to be preventable. The consequences of surgical AEs were more severe than for other types of AEs, resulting in more permanent disability, extra treatment, prolonged hospital stay, unplanned readmissions and extra outpatient visits. Almost 40% of the surgical AEs were infections, 23% bleeding, and 22% injury by mechanical, physical or chemical cause. Human factors were involved in the causation of 65% of surgical AEs and were considered to be preventable through quality assurance and training. Conclusions: Surgical AEs occur more often than other types of AEs, are more often preventable and their consequences are more severe. Therefore, surgical AEs have a major impact on the burden of AEs during hospitalizations. These findings concur with the results from previous studies. However, evidence-based solutions to reduce surgical AEs are increasingly available. Interventions directed at human causes are recommended to improve the safety of surgical care. Examples are team training and the surgical safety checklist. In addition, specific strategies are needed to improve appropriate use of antibiotic prophylaxis and sustainable implementation of hygiene guidelines to reduce infections.
Research Paper: Risk Assessment of Surgical Procedures in a Referral Hospital
Background: Adverse Events (AEs) due to failure in healthcare procedures are common. These procedures are often evaluated independently. The objectives of this study are to investigate the nature of the failures in healthcare procedures of the surgical patients, assessing the frequency of these failures and preventability, and exploring their consequences, underlying causes, and prevention strategies in a referral hospital in the center of Iran. Materials and Methods: This study is a prospective quantitative and qualitative research. Focus Group Discussion (FGD) meetings have been conducted to understand potential failures, their consequences, causes, and prevention strategies. Afterwards, the frequencies of these concepts have been determined separately in predefined subcategories in each step of the process. Results: The first phase of the patient care process was the most risk-prone phase. Temporary or permanent disability at the time of discharge (final impacts), inflammation/infection (injuries), the rule-based behavior associated with coordination (causes), information and communication, preventability more than 50 were the most frequent failures and had achieved the highest score. Conclusion: Failures of healthcare processes are preventable to a high degree, although patients injure frequently. Interventions to mitigate these failures will enhance the reliability of surgical procedures.