Beyond volume: does hospital complexity matter?: an analysis of inpatient surgical mortality in the United States. Med Care. 2014;52:235-242. [PMID: 24509361 DOI: 10.1097/mlr.0000000000000077]

Diagnosing an overcrowded emergency department from its Electronic Health Records

Emergency department overcrowding is a complex problem that persists globally. Data of visits constitute an opportunity to understand its dynamics. However, the gap between the collected information and the real-life clinical processes, and the lack of a whole-system perspective, still constitute a relevant limitation. An analytical pipeline was developed to analyse one-year of production data following the patients that came from the ED (n = 49,938) at Uppsala University Hospital (Uppsala, Sweden) by involving clinical experts in all the steps of the analysis. The key internal issues to the ED were the high volume of generic or non-specific diagnoses from non-urgent visits, and the delayed decision regarding hospital admission caused by several imaging assessments and lack of hospital beds. Furthermore, the external pressure of high frequent re-visits of geriatric, psychiatric, and patients with unspecified diagnoses dramatically contributed to the overcrowding. Our work demonstrates that through analysis of production data of the ED patient flow and participation of clinical experts in the pipeline, it was possible to identify systemic issues and directions for solutions. A critical factor was to take a whole systems perspective, as it opened the scope to the boundary effects of inflow and outflow in the whole healthcare system.

Association of Academic Medical Center Presence With Clinical Outcomes at Neighboring Community Hospitals Among Medicare Beneficiaries

IMPORTANCE

Studies suggest that academic medical centers (AMCs) have better outcomes than nonteaching hospitals. However, whether AMCs have spillover benefits for patients treated at neighboring community hospitals is unknown.

OBJECTIVE

To examine whether market-level AMC presence is associated with outcomes for patients treated at nonteaching hospitals within the same markets.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective, population-based cohort study assessed traditional Medicare beneficiaries aged 65 years and older discharged from US acute care hospitals between 2015 and 2017 (100% sample). Data were analyzed from August 2021 to December 2022.

EXPOSURES

The primary exposure was market-level AMC presence. Health care markets (ie, hospital referral regions) were categorized by AMC presence (percentage of hospitalizations at AMCs) as follows: no presence (0%), low presence (>0% to 20%), moderate presence (>20% to 35%), and high presence (>35%).

MAIN OUTCOMES AND MEASURES

The primary outcomes were 30-day and 90-day mortality and healthy days at home (HDAH), a composite outcome reflecting mortality and time spent in facility-based health care settings.

RESULTS

There were 22 509 824 total hospitalizations, with 18 865 229 (83.8%) at non-AMCs. The median (IQR) age of patients was 78 (71-85) years, and 12 568 230 hospitalizations (55.8%) were among women. Of 306 hospital referral regions, 191 (62.4%) had no AMCs, 61 (19.9%) had 1 AMC, and 55 (17.6%) had 2 or more AMCs. Markets characteristics differed significantly by category of AMC presence, including mean population, median income, proportion of White residents, and physicians per population. Compared with markets with no AMC presence, receiving care at a non-AMC in a market with greater AMC presence was associated with lower 30-day mortality (9.5% vs 10.1%; absolute difference, -0.7%; 95% CI, -1.0% to -0.4%; P < .001) and 90-day mortality (16.1% vs 16.9%; absolute difference, -0.8%; 95% CI, -1.2% to -0.4%; P < .001) and more HDAH at 30 days (16.49 vs 16.12 HDAH; absolute difference, 0.38 HDAH; 95% CI, 0.11 to 0.64 HDAH; P = .005) and 90 days (61.08 vs 59.83 HDAH; absolute difference, 1.25 HDAH; 95% CI, 0.58 to 1.92 HDAH; P < .001), after adjustment. There was no association between market-level AMC presence and mortality for patients treated at AMCs themselves.

CONCLUSIONS AND RELEVANCE

AMCs may have spillover effects on outcomes for patients treated at non-AMCs, suggesting that they have a broader impact than is traditionally recognized. These associations are greatest in markets with the highest AMC presence and persist to 90 days.

Using Iterative RE-AIM to enhance hospitalist adoption of lung ultrasound in the management of patients with COVID-19: an implementation pilot study

BACKGROUND

Lung ultrasound (LUS) is a clinician-performed evidence-based imaging modality that has multiple advantages in the evaluation of dyspnea caused by multiple disease processes, including COVID-19. Despite these advantages, few hospitalists have been trained to perform LUS. The aim of this study was to increase adoption and implementation of LUS during the 2020 COVID-19 pandemic by using recurrent assessments of RE-AIM outcomes to iteratively revise our implementation strategies.

METHODS

In an academic hospital, we implemented guidelines for the use of LUS in patients with COVID-19 in July 2020. Using a novel "RE-AIM dashboard," we used an iterative process of evaluating the high-priority outcomes of Reach, Adoption, and Implementation at twice monthly intervals to inform revisions of our implementation strategies for LUS delivery (i.e., Iterative RE-AIM process). Using a convergent mixed methods design, we integrated quantitative RE-AIM outcomes with qualitative hospitalist interview data to understand the dynamic determinants of LUS Reach, Adoption, and Implementation.

RESULTS

Over the 1-year study period, 453 LUSs were performed in 298 of 12,567 eligible inpatients with COVID-19 (Reach = 2%). These 453 LUS were ordered by 43 out of 86 eligible hospitalists (LUS order adoption = 50%). However, the LUSs were performed/supervised by only 8 of these 86 hospitalists, 4 of whom were required to complete LUS credentialing as members of the hospitalist procedure service (proceduralist adoption 75% vs 1.2% non-procedural hospitalists adoption). Qualitative and quantitative data obtained to evaluate this Iterative RE-AIM process led to the deployment of six sequential implementation strategies and 3 key findings including (1) there were COVID-19-specific barriers to LUS adoption, (2) hospitalists were more willing to learn to make clinical decisions using LUS images than obtain the images themselves, and (3) mandating the credentialing of a strategically selected sub-group may be a successful strategy for improving Reach.

CONCLUSIONS

Mandating use of a strategically selected subset of clinicians may be an effective strategy for improving Reach of LUS. Additionally, use of Iterative RE-AIM allowed for timely adjustments to implementation strategies, facilitating higher levels of LUS Adoption and Reach. Future studies should explore the replicability of these preliminary findings.

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background

Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.

Methods

A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.

Findings

Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.

Interpretation

Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised.

Funding

National Institute for Health and Care Research.

A Remote Surveillance Platform to Monitor General Care Ward Surgical Patients for Acute Physiologic Deterioration

BACKGROUND

The traditional paradigm of hospital surgical ward care consists of episodic bedside visits by providers with periodic perusals of the patient's electronic health record (EHR). Vital signs and laboratory results are directly pushed to the EHR but not to providers themselves. Results that require intervention may not be recognized for hours. Remote surveillance programs continuously monitor electronic data and provide automatic alerts that can be routed to multidisciplinary providers. Such programs have not been explored in surgical general care wards.

METHODS

We performed a quality improvement observational study of otolaryngology and ophthalmology patients on a general care ward from October 2017 to March 2019 during nighttime hours (17:00-07:00). The study was initiated due to the loss of on-site anesthesiology resources that historically helped respond to acute physiologic deterioration events. We implemented a remote surveillance software program to continuously monitor patients for severe vital signs and laboratory abnormalities and automatically alert the ward team and a remote critical care anesthesiology team. The primary end point was the true positive rate, defined as the proportion of alerts that were associated with a downstream action that changed the care of the patient. This was determined using systematic chart review. The secondary end point, as a measure of alarm fatigue, was the average number of alerts per clinician shift.

RESULTS

The software monitored 3926 hospital visits and analyzed 1,560,999 vitals signs and 16,635 laboratories. It generated 151 alerts, averaging 2.6 alerts per week. Of these, 143 (94.7%) were numerically accurate and 8 (5.3%) were inaccurate. Hypoxemia with oxygen saturation <88% was the most common etiology (92, 63%) followed by tachycardia >130 beats per minute (19, 13.3%). Among the accurate alerts, 133 (88.1%) were true positives with an associated clinical action. Actions included a change in management 113 (67.7%), new diagnostic test 26 (15.6%), change in discharge planning 20 (12.0%), and change in level of care to the intensive care unit (ICU) 8 (4.8%). As a measure of alarm fatigue, there were 0.4 alerts per clinician shift.

CONCLUSIONS

In a surgical general care ward, a remote surveillance software program that continually and automatically monitors physiologic data streams from the EHR and alerts multidisciplinary providers for severe derangements provided highly actionable alarms at a rate that is unlikely to cause alarm fatigue. Such programs are feasible and could be used to change the paradigm of monitoring.

Contributors to Increased Mortality Associated With Care Fragmentation After Emergency General Surgery

Importance

Care fragmentation at time of readmission after emergency general surgery (EGS) is associated with high mortality; however, the factors underlying this finding remain unclear.

Objective

To identify patient and hospital factors associated with increased mortality among patients after EGS readmitted within 30 days of discharge to a nonindex hospital.

Design, Setting, and Participants

Retrospective cohort study using the 2014 Healthcare Cost and Utilization Project Nationwide Readmissions Database. Participants were all adult patients (18 years or older) who underwent 1 of the 15 most common EGS procedures in the United States from January 1 to November 30, 2014, and survived to discharge. The dates of analysis were October through December 2019.

Exposures

Thirty-day readmission to a hospital other than that of the index surgical procedure. The study examined the association of interventions during readmission, change in hospital resource level, and severity of patient illness during readmission.

Main Outcomes and Measures

Ninety-day inpatient mortality.

Results

In total, 71 944 patients who underwent EGS (mean [SD] age, 59.0 [18.3] years; 53.5% [38 487 of 71 944] female) were readmitted within 30 days of discharge, of whom 10 495 (14.6%) were readmitted to a nonindex hospital. Compared with patients readmitted to index hospitals, patients readmitted to nonindex hospitals were more likely to be readmitted to hospitals with low annual EGS volume (33.5% vs 25.6%, P < .001) and be in the top half of illness severity profile (37.2% vs 31.2%, P < .001). Overall 90-day mortality was higher in the patients readmitted to nonindex hospitals (6.1% vs 4.3%, P < .001). When adjusted for baseline patient and hospital characteristics, care fragmentation was independently associated with increased mortality (adjusted odds ratio [aOR], 1.36; 95% CI, 1.17-1.58; P < .001). After adjustment for interventions performed during readmission, change in EGS hospital volume level, and severity of patient illness, care fragmentation was no longer independently associated with mortality (aOR, 1.05; 95% CI, 0.88-1.26; P = .58). In this complete model, severity of illness was the strongest risk factor of mortality during readmission.

Conclusions and Relevance

In this cohort study of adult patients who require rehospitalization after EGS, 14.6% are readmitted to a hospital other than where the index procedure was performed. Although the overall mortality rate is higher for this population, the excess mortality appears to be primarily associated with severity of patient illness at time of readmission. These data underscore the need to develop systems of care to rapidly triage patients to hospitals best equipped to manage their condition.

Association of balanced abdominal organ transplant center volumes with patient outcomes

BACKGROUND

The volume-outcome relationship for organ-specific transplantation is well-described; it is unknown if the relative balance of kidney compared with liver volumes within an institution relates to organ-specific outcomes. We assessed the association between relative balance within a transplant center and outcomes.

METHODS

National retrospective analysis of isolated kidney and liver transplants in United States 2005-2014 followed through 2019. Latent class analysis defined transplant center phenotypes. Multivariate Cox models estimated death-censored graft loss and mortality.

RESULTS

Latent class analysis identified four phenotypes: kidney only (n = 117), kidney dominant (n = 36), mixed/balanced (n = 90), and liver dominant (n = 13). Compared to mixed centers, the risk of kidney graft loss was higher at kidney-dominant (HR 1.07, p < .001) and liver-dominant (HR 1.10, p < .001) centers, while kidney-only (HR 1.06, p = .01) centers had higher mortality. Liver graft loss was not associated with phenotype, but risk of patient death was lower (HR 0.93, p = .02) at liver dominant and higher (HR 1.06, p = .02) at kidney-dominant centers.

CONCLUSIONS

A mixed phenotype was associated with improved kidney transplant outcomes, whereas liver transplant outcomes were best at liver-dominant centers. While these findings need to be verified with center-level resources, optimization of shared resources could improve patient and organ outcomes.

Implications of Hospital Volume on Costs Following Esophagectomy in the United States

BACKGROUND

With increasing focus on health care quality and cost containment, volume-based referral strategies have been proposed to improve value in high-cost procedures, such as esophagectomy. While the effect of hospital volume on outcomes has been demonstrated, our goal was to evaluate the economic consequences of volume-based referral practices for esophagectomy.

METHODS

The nationwide inpatient sample (NIS) was queried for the years 2004-2013 for all patients undergoing esophagectomy. Patients were stratified by hospital volume quartile and substratified by preoperative risk and age. Clustered multivariable hierarchical logistic regression analysis was used to assess adjusted costs and mortality.

RESULTS

In total, 9270 patients were clustered based on annual hospital volume quartiles of < 7, 7 to 22, 23 to 87, and > 87 esophagectomies. After stratification by patient variables, high-volume centers performed esophagectomies in high-risk patients at the same cost as low-volume centers without significant difference in resource utilization. Overall, mortality decreased across volume quartiles (lowest 8.9 versus highest 3.6%, p < 0.0001). The greatest volume-mortality differences were observed among patients aged between 70 and 80 years (lowest 12.2 versus highest 6.2%, p = 0.009). Patients with high preoperative risk also derived mortality benefits with increasing hospital volume (lowest 17.5 versus highest 11.8%, p < 0.0001).

CONCLUSIONS

This study demonstrates that the mortality improvements for high-risk patients undergoing esophagectomy at high-volume centers do not come at increased costs. These results suggest that health systems should consider selectively referring high-risk patients to high-volume centers within their region.

Trans-catheter aortic valve replacement program in a community hospital - Comparison with US national data

Symptomatic aortic stenosis remains a surgical disease, with aortic valve replacement resulting in symptom reduction and improvement in survival. For patients who are deemed a higher surgical risk, Transcatheter aortic-valve replacement (TAVR) is a viable, less invasive and increasingly common alternative. The study compares early outcomes in patients treated within one year of the commencement of TAVR program in a community hospital against outcomes of TAVR patients from nationwide reported data (Society of Thoracic Surgeons/ American College of Cardiology TVT registry). Preoperative characteristics and standardized procedural outcomes of all patients who underwent TAVR in Cape Cod Hospital between June 2015 and May 2016 (n = 62, CCH group) were compared using standardized data format to those of TAVR patients operated during the same time period in other centers within the United States participating in the STS/ACC TVT Registry (n = 24,497, USA group). Most preoperative patient characteristics were similar between groups. However, CCH patients were older (age≥80 years: 77.4% versus 64.3%, p = 0.032) and more likely to be non-elective cases (37.1% versus 9.7%, p<0.001). All 62 TAVR procedures in CCH were performed in the catheterization laboratory unlike most (89.7%) of the procedures in the USA group that were performed in hybrid rooms. A larger proportion of patients in the USA registry underwent TAVR under general anesthesia (78.2% vs.37.1%, P<0.001). Early aortic valve re- intervention rate was 0/62 (0%) in the CCH group VS. 74/ 24,497 (0.3%) in the USA group. In hospital mortality, which was defined as death of any cause during thirty days from date of operation, (CCH: 0% vs. USA: 2.5%, p = 0.410) and occurrence of early adverse events (including postoperative para-valvular leaks, conduction defects requiring pacemakers, neurologic and renal complications) were similar in the two groups. The study concludes that with specific team training and co-ordination, and with active support of experienced personnel, high risk patients with severe aortic valve stenosis can be managed safely with a TAVR procedure in a community hospital.

Intra-hospital correlations among 30-day mortality rates in 18 different clinical and surgical settings

Objective

To examine whether a correlation exists in hospitals among 30-day mortality rates for different types of hospitalizations.

Design

Cross-sectional study of hospital care based on publically available Italian data from the National Outcome Evaluation Program Edition 2015 of the Italian Agency for Regional Health Services.

Setting and Participants

Patients hospitalized with a diagnosis of congestive heart failure, acute myocardial infarction, chronic renal failure, chronic obstructive pulmonary disease exacerbation, femoral neck fracture, ischemic stroke and non-variceal upper gastrointestinal bleeding, or those who underwent isolated cardiac valve procedure, isolated coronary artery bypass graft surgery, non-ruptured abdominal aortic aneurysm repair and interventions for the following tumors: colon, kidney, brain, lung, stomach, rectal, liver or pancreatic cancer.

Main Outcome Measures

Condition-specific 30-day crude and risk-adjusted mortality rates.

Results

A total of 808 280 admissions were reported from 844 institutions (median of 4 conditions evaluated per hospital; interquartile range 2-8). Volumes and outcome varied by clinical and surgical conditions across hospitals. Out of 153 pairs of different conditions, 41 were statistically significant in terms of concordance with crude mortality rates and 44 for their adjusted values. The hospital mean percentile rank for 30-day mortality, a composite measure that summarized the multiple indicators, increased significantly alongside number of conditions per hospital with a significant reduction of mortality when most of the studied conditions were treated in the same hospital.

Conclusions

The variability in 30-day mortality rates at hospital level and the correlation between risk mortality rates suggest that there may be common hospital-wide factors influencing short-term mortality.

Looking Under the Streetlight? A Framework for Differentiating Performance Measures by Level of Care in a Value-Based Payment Environment

The majority of quality measures used to assess providers and hospitals are based on easily obtained data, focused on a few dimensions of quality, and developed mainly for primary/community care and population health. While this approach supports efforts focused on addressing the triple aim of health care, many current quality report cards and assessments do not reflect the breadth or complexity of many referral center practices.In this article, the authors highlight the differences between population health efforts and referral care and address issues related to value measurement and performance assessment. They discuss why measures may need to differ across the three levels of care (primary/community care, secondary care, complex care) and illustrate the need for further risk adjustment to eliminate referral bias.With continued movement toward value-based purchasing, performance measures and reimbursement schemes need to reflect the increased level of intensity required to provide complex care. The authors propose a framework to operationalize value measurement and payment for specialty care, and they make specific recommendations to improve performance measurement for complex patients. Implementing such a framework to differentiate performance measures by level of care involves coordinated efforts to change both policy and operational platforms. An essential component of this framework is a new model that defines the characteristics of patients who require complex care and standardizes metrics that incorporate those definitions.

Medicare's Bundled Payment initiative: most hospitals are focused on a few high-volume conditions

The Bundled Payments for Care Improvement initiative is a federally funded innovation model mandated by the Affordable Care Act. It is designed to help transition Medicare away from fee-for-service payments and toward bundling a single payment for an episode of acute care in a hospital and related postacute care in an appropriate setting. While results from the initiative will not be available for several years, current data can help provide critical early insights. However, little is known about the participating organizations and how they are focusing their efforts. We identified participating hospitals and used national Medicare claims data to assess their characteristics and previous spending patterns. These hospitals are mostly large, nonprofit, teaching hospitals in the Northeast, and they have selectively enrolled in the bundled payment initiative covering patient conditions with high clinical volumes. We found no significant differences in episode-based spending between participating and nonparticipating hospitals. Postacute care explains the largest variation in overall episode-based spending, signaling an opportunity to align incentives across providers. However, the focus on a few selected clinical conditions and the high degree of integration that already exists between enrolled hospitals and postacute care providers may limit the generalizability of bundled payment across the Medicare system.

Characterizing the role of a high-volume cancer resection ecosystem on low-volume, high-quality surgical care

BACKGROUND

Our objective was to determine the hospital resources required for low-volume, high-quality care at high-volume cancer resection centers.

METHODS

Patients who underwent esophageal, pancreatic, and rectal resection for malignancy were identified using Healthcare Cost and Utilization Project State Inpatient Database (Florida and California) between 2007 and 2011. Annual case volume by procedure was used to identify high- and low-volume centers. Hospital data were obtained from the American Hospital Association Annual Survey Database. Procedure risk-adjusted mortality was calculated for each hospital using multilevel, mixed-effects models.

RESULTS

A total of 24,784 patients from 302 hospitals met the inclusion criteria. Of these, 13 hospitals were classified as having a high-volume, oncologic resection ecosystem by being a high-volume hospital for ≥2 studied procedures. A total of 11 of 31 studied hospital factors were strongly associated with hospitals that performed a high volume of cancer resections and were used to develop the High Volume Ecosystem for Oncologic Resections (HIVE-OR) score. At low-volume centers, increasing HIVE-OR score resulted in decreased mortality for rectal cancer resection (P = .038). HIVE-OR was not related to risk-adjusted mortality for esophagectomy (P = .421) or pancreatectomy (P = .413) at low-volume centers.

CONCLUSION

Our study found that in some settings, low-volume, high-quality cancer surgical care can be explained by having a high-volume ecosystem.

Beyond volume: hospital-based healthcare technology as a predictor of mortality for cardiovascular patients in Korea

To examine whether hospital-based healthcare technology is related to 30-day postoperative mortality rates after adjusting for hospital volume of cardiovascular surgical procedures.This study used the National Health Insurance Service-Cohort Sample Database from 2002 to 2013, which was released by the Korean National Health Insurance Service. A total of 11,109 cardiovascular surgical procedure patients were analyzed. The primary analysis was based on logistic regression models to examine our hypothesis.After adjusting for hospital volume of cardiovascular surgical procedures as well as for all other confounders, the odds ratio (OR) of 30-day mortality in low healthcare technology hospitals was 1.567-times higher (95% confidence interval [CI] = 1.069-2.297) than in those with high healthcare technology. We also found that, overall, cardiovascular surgical patients treated in low healthcare technology hospitals, regardless of the extent of cardiovascular surgical procedures, had the highest 30-day mortality rate.Although the results of our study provide scientific evidence for a hospital volume-mortality relationship in cardiovascular surgical patients, the independent effect of hospital-based healthcare technology is strong, resulting in a lower mortality rate. As hospital characteristics such as clinical pathways and protocols are likely to also play an important role in mortality, further research is required to explore their respective contributions.

Influence of hospital volume and outcomes of adult structural heart procedures

Hospital volume is regarded amongst many in the medical community as an important quality metric. This is especially true in more complicated and less commonly performed procedures such as structural heart disease interventions. Seminal work on hospital volume relationships was done by Luft et al more than 4 decades ago, when they demonstrated that hospitals performing > 200 surgical procedures a year had 25%-41% lower mortality than those performing fewer procedures. Numerous volume-outcome studies have since been done for varied surgical procedures. An old adage “practice makes perfect” indicating superior operator and institutional experience at higher volume hospitals is believed to primarily contribute to the volume outcome relationship. Compelling evidence from a slew of recent publications has also highlighted the role of hospital volume in predicting superior post-procedural outcomes following structural heart disease interventions. These included transcatheter aortic valve repair, transcatheter mitral valve repair, septal ablation and septal myectomy for hypertrophic obstructive cardiomyopathy, left atrial appendage closure and atrial septal defect/patent foramen ovale closure. This is especially important since these structural heart interventions are relatively complex with evolving technology and a steep learning curve. The benefit was demonstrated both in lower mortality and complications as well as better economics in terms of lower length of stay and hospitalization costs seen at high volume centers. We present an overview of the available literature that underscores the importance of hospital volume in complex structural heart disease interventions.

Beyond Volume: Hospital-Based Healthcare Technology for Better Outcomes in Cerebrovascular Surgical Patients Diagnosed With Ischemic Stroke: A Population-Based Nationwide Cohort Study From 2002 to 2013

We examined whether the level of hospital-based healthcare technology was related to the 30-day postoperative mortality rates, after adjusting for hospital volume, of ischemic stroke patients who underwent a cerebrovascular surgical procedure. Using the National Health Insurance Service-Cohort Sample Database, we reviewed records from 2002 to 2013 for data on patients with ischemic stroke who underwent cerebrovascular surgical procedures. Statistical analysis was performed using Cox proportional hazard models to test our hypothesis. A total of 798 subjects were included in our study. After adjusting for hospital volume of cerebrovascular surgical procedures as well as all for other potential confounders, the hazard ratio (HR) of 30-day mortality in low healthcare technology hospitals as compared to high healthcare technology hospitals was 2.583 (P < 0.001). We also found that, although the HR of 30-day mortality in low healthcare technology hospitals with high volume as compared to high healthcare technology hospitals with high volume was the highest (10.014, P < 0.0001), cerebrovascular surgical procedure patients treated in low healthcare technology hospitals had the highest 30-day mortality rate, irrespective of hospital volume. Although results of our study provide scientific evidence for a hospital volume/30-day mortality rate relationship in ischemic stroke patients who underwent cerebrovascular surgical procedures, our results also suggest that the level of hospital-based healthcare technology is associated with mortality rates independent of hospital volume. Given these results, further research into what components of hospital-based healthcare technology significantly impact mortality is warranted.

Outcomes and Costs for Major Lung Resection in the United States: Which Patients Benefit Most From High-Volume Referral?

BACKGROUND

Accountable care organizations are designed to improve value by decreasing costs and maintaining quality. Strategies to maximize value are needed for high-risk surgery. We wanted to understand whether certain patient groups were differentially associated with better outcomes at high-volume hospitals in terms of quality and cost.

METHODS

In all, 37,746 patients underwent elective major lung resection in 1,273 hospitals in the Nationwide Inpatient Sample from 2007 to 2011. Patients were stratified by hospital volume quartile and substratified by preoperative mortality risk, age, and chronic obstructive pulmonary disease status. Mortality was evaluated using clustered multivariable hierarchical logistic regression controlling for patient comorbidity, demographics, and procedure. Adjusted cost was evaluated using generalized linear models fit to a gamma distribution.

RESULTS

Patients were grouped into volume quartiles based on cases per year (less than 21, 21 to 40, 40 to 78, and more than 78). Patient characteristics and procedure mix differed across quartiles. Overall, mortality decreased across volume quartiles (lowest 1.9% versus highest 1.1%, p < 0.0001). Patients aged more than 80 years were associated with greater absolute and relative mortality rates than patients less than 60 years old in highest volume versus lowest volume hospitals (age more than 80 years, 4.2% versus 1.3%, p < 0.0001, odds ratio 3.31, 95% confidence interval: 1.89 to 5.80; age less than 60 years, 1.0% versus 0.8%, p = 0.19, odds ratio 1.38, 95% confidence interval: 0.74 to 2.56). Patients with high preoperative risk (more than 75th percentile) were also associated with lower absolute mortality in high-volume hospitals. Adjusted costs were not significantly different across quartiles or patient strata.

CONCLUSIONS

Older patients show a significantly stronger volume-outcome relationship than patients less than 60 years of age. Costs were equivalent across volume quartile and patient strata. Selective patient referral may be a strategy to improve outcomes for elderly patients undergoing lung resection.

Do past mortality rates predict future hospital mortality?

BACKGROUND

This study aimed to determine whether hospitals with higher historical mortality rates are independently associated with worse patient outcomes.

METHODS

Observational study of in-hospital mortality in open abdominal aortic aneurysm repair, aortic valve replacement, and coronary artery bypass graft surgery in a California in-patient database was conducted. Hospitals' annual historical mortality rates between 1998 and 2010 were calculated based on 3 years of data before each year. Results were adjusted for race, sex, age, hospital teaching status, admission year, insurance status, and Charlson comorbidity index.

RESULTS

Hospitals were divided into quartiles based on historical mortality rates. For abdominal aortic aneurysm repair, the odds ratio (OR) of in-hospital mortality for hospitals within the highest quartile of prior mortality was 1.30 compared with the lowest quartile (95% confidence interval [CI] 1.03 to 1.63). For aortic valve replacement, the OR was 1.41 for the 3rd quartile (95% CI 1.15 to 1.73) and 1.54 for the highest quartile (95% CI 1.27 to 1.87). For coronary artery bypass graft surgery, the OR was 1.33 for the 3rd (95% CI 1.2 to 1.49) and 1.58 for the highest (95% CI 1.41 to 1.76) quartiles.

CONCLUSION

Patients presenting to hospitals with high historical mortality rates have a 30% to 60% increased mortality risk compared with patients presenting to hospitals with low historical mortality rates.

Incidence and determinants of 1-month mortality after cancer-directed surgery

BACKGROUND

Death within 1 month of surgery is considered treatment related and serves as an important health care quality metric. We sought to identify the incidence of and factors associated with 1-month mortality after cancer-directed surgery.

PATIENTS AND METHODS

We used the Surveillance, Epidemiology and End Results Program to study a cohort of 1 110 236 patients diagnosed from 2004 to 2011 with cancers that are among the 10 most common or most fatal who received cancer-directed surgery. Multivariable logistic regression analyses were used to identify factors associated with 1-month mortality after cancer-directed surgery.

RESULTS

A total of 53 498 patients (4.8%) died within 1 month of cancer-directed surgery. Patients who were married, insured, or who had a top 50th percentile income or educational status had lower odds of 1-month mortality from cancer-directed surgery {[adjusted odds ratio (AOR) 0.80; 95% confidence interval (CI) 0.79-0.82; P < 0.001], (AOR 0.88; 95% CI 0.82-0.94; P < 0.001), (AOR 0.95; 95% CI 0.93-0.97; P < 0.001), and (AOR 0.98; 95% CI 0.96-0.99; P = 0.043), respectively}. Patients who were non-white minority, male, or older (per year increase), or who had advanced tumor stage 4 disease all had a higher risk of 1-month mortality after cancer-directed surgery, with AORs of 1.13 (95% CI 1.11-1.15), P < 0.001; 1.11 (95% CI 1.08-1.13), P < 0.001; 1.02 (95% 1.02-1.03), P < 0.001; and 1.89 (95% CI 1.82-1.95), P < 0.001 respectively.

CONCLUSIONS

Unmarried, uninsured, non-white, male, older, less educated, and poorer patients were all at a significantly higher risk for death within 1 month of cancer-directed surgery. Efforts to reduce 1-month surgical mortality and eliminate sociodemographic disparities in this adverse outcome could significantly improve survival among patients with cancer.