Article

Rates and patterns of death after surgery in the United States, 1996 and 2006

Brigham andWomen’s Hospital, Department of Health Policy and Management, Harvard School of Public Health, Boston, MA 02115, USA.
Surgery (Impact Factor: 3.37). 02/2012; 151(2):171-82. DOI: 10.1016/j.surg.2011.07.021
Source: PubMed

ABSTRACT Nationwide rates and patterns of death after surgery are unknown.
Using the Nationwide Inpatient Sample, we compared deaths within 30 days of admission for patients undergoing surgery in 1996 and 2006. International Classification of Diseases codes were used to identify 2,520 procedures for analysis. We examined the inpatient 30-day death rate for all procedures, procedures with the most deaths, high-risk cardiovascular and cancer procedures, and patients who suffered a recorded complication. We used logistic regression modeling to adjust 1996 mortality rates to the age and gender distributions for patients undergoing surgery in 2006.
In 1996, there were 12,573,331 admissions with a surgical procedure (95% confidence interval [CI], 12,560,171-12,586,491) and 224,111 inpatient deaths within 30 days of admission (95% CI, 221,912-226,310). In 2006, there were 14,333,993 admissions with a surgical procedure (95% CI, 14,320,983-14,347,002) and 189,690 deaths (95% CI, 187,802-191,578). Inpatient 30-day mortality declined from 1.68% in 1996 to 1.32% in 2006 (P < .001). Of the 21 procedures with the most deaths in 1996, 15 had significant declines in adjusted mortality in 2006. Among these 15 procedures, 8 had significant declines in operative volume. The inpatient 30-day mortality rate for patients who suffered a complication decreased from 12.10% to 9.84% (P < .001).
Nationwide reporting on surgical mortality suggests that the number of inpatient deaths within 30 days of surgery has declined. Additional research to determine the underlying causes for decreased mortality is warranted.

0 Bookmarks
 · 
123 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: OBJECTIVES: Despite the burden of venous thromboembolism (VTE) among surgical patients on health systems in Australia, data on VTE incidence and its variation within Australia are lacking. We aim to explore VTE and subsequent mortality rates, trends and variations across Australian acute public hospitals. SETTING: A large retrospective cohort study using all elective surgical patients in 82 acute public hospitals during 2002-2009 in New South Wales, Australia. PARTICIPANTS: Patients underwent elective surgery within 2 days of admission, aged between 18 and 90 years, and who were not transferred to another acute care facility; 4 362 624 patients were included. OUTCOME MEASURES: VTE incidents were identified by secondary diagnostic codes. Poisson mixed models were used to derive adjusted incidence rates and rate ratios (IRR). RESULTS: 2/1000 patients developed postoperative VTE. VTE increased by 30% (IRR=1.30, CI 1.19 to 1.42) over the study period. Differences in the VTE rates, trends between hospital peer groups and between hospitals with the highest and those with the lowest rates were significant (between-hospital variation). Smaller hospitals, accommodated in two peer groups, had the lowest overall VTE rates (IRR=0.56:0.33 to 0.95; IRR=0.37:0.23 to 0.61) and exhibited a greater increase (64% and 237% vs 19%) overtime and greater between-hospital variations compared to larger hospitals (IRR=8.64:6.23 to 11.98; IRR=8.92:5.49 to 14.49 vs IRR=3.70:3.32 to 4.12). Mortality among patients with postoperative VTE was 8% and remained stable overtime. No differences in post-VTE death rates and trends were seen between hospital groups; however, larger hospitals exhibited less between-hospital variations (IRR=1.78:1.30 to 2.44) compared to small hospitals (IRR>23). Hospitals performed differently in prevention versus treatment of postoperative VTE. CONCLUSIONS: VTE incidence is increasing and there is large variation between-hospital and within-hospital peer groups suggesting a varied compliance with VTE preventative strategies and the potential for targeted interventions and quality improvement opportunities.
    BMJ Open 10/2014; 4(10-10):e005502. DOI:10.1136/bmjopen-2014-005502 · 2.06 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: BackgroundHigh-risk surgery patients may lose decision-making capacity as a result of surgical complications. Advance care planning prior to surgery may be beneficial, but remains controversial and is hindered by a lack of appropriate decision aids. This study sought to examine stakeholders’ views on the appropriateness of using decision aids, in general, to support advance care planning among high-risk surgery populations and the design of such a decision aid.MethodsKey informants were recruited through purposive and snowball sampling. Semi-structured interviews were conducted by phone until data collected reached theoretical saturation. Key informants were asked to discuss their thoughts about advance care planning and interventions to support advance care planning, particularly for this population. Researchers took de-identified notes that were analyzed for emerging concordant, discordant, and recurrent themes using interpretative phenomenological analysis.ResultsKey informants described the importance of initiating advance care planning preoperatively, despite potential challenges present in surgical settings. In general, decision aids were viewed as an appropriate approach to support advance care planning for this population. A recipe emerged from the data that outlines tools, ingredients, and tips for success that are needed to design an advance care planning decision aid for high-risk surgical settings.ConclusionsStakeholders supported incorporating advance care planning in high-risk surgical settings and endorsed the appropriateness of using decision aids to do so. Findings will inform the next stages of developing the first advance care planning decision aid for high-risk surgery patients.
    BMC Palliative Care 06/2014; 13:32. DOI:10.1186/1472-684X-13-32 · 1.79 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Despite the wide acceptance of Failure-to-Rescue (FTR) as a patient safety indicator (defined as the deaths among surgical patients with treatable complications), no study has explored the geographic variation of FTR in a large health jurisdiction. Our study aimed to explore the spatiotemporal variations of FTR rates across New South Wales (NSW), Australia. We conducted a population-based study using all admitted surgical patients in public acute hospitals during 2002-2009 in NSW, Australia. We developed a spatiotemporal Poisson model using Integrated Nested Laplace Approximation (INLA) methods in a Bayesian framework to obtain area-specific adjusted relative risk. Local Government Area (LGA) was chosen as the areal unit. LGA-aggregated covariates included age, gender, socio-economic and remoteness index scores, distance between patient residential postcode and the treating hospital, and a quadratic time trend. We studied 4,285,494 elective surgical admissions in 82 acute public hospitals over eight years in NSW. Around 14% of patients who developed at least one of the six FTR-related complications (58,590) died during hospitalization. Of 153 LGAs, patients who lived in 31 LGAs, accommodating 48% of NSW patients at risk, were exposed to an excessive adjusted FTR risk (10% to 50%) compared to the state-average. They were mostly located in state's centre and western Sydney. Thirty LGAs with a lower adjusted FTR risk (10% to 30%), accommodating 8% of patients at risk, were mostly found in the southern parts of NSW and Sydney east and south. There were significant spatiotemporal variations of FTR rates across NSW over an eight-year span. Areas identified with significantly high and low FTR risks provide potential opportunities for policy-makers, clinicians and researchers to learn from the success or failure of adopting the best care for surgical patients and build a self-learning organisation and health system.
    PLoS ONE 10/2014; 9(10-10):e109807. DOI:10.1371/journal.pone.0109807 · 3.53 Impact Factor