Optimal surgeon and hospital volume thresholds to reduce mortality and length of stay for CABG

Use of computer simulation to identify effects on hospital census with reduction of transfers for non-procedural patients in community hospitals

OBJECTIVE

In-person healthcare delivery is rapidly changing with a shifting employment landscape and technological advances. Opportunities to care for patients in more efficient ways include leveraging technology and focusing on caring for patients in the right place at the right time. We aim to use computer modelling to understand the impact of interventions, such as virtual consultation, on hospital census for referring and referral centres if non-procedural patients are cared for locally rather than transferred.

PATIENTS AND METHODS

We created computer modelling based on 25 138 hospital transfers between June 2019 and June 2022 with patients originating at one of 17 community-based hospitals and a regional or academic referral centre receiving them. We identified patients that likely could have been cared for at a community facility, with attention to hospital internal medicine and cardiology patients. The model was run for 33 500 days.

RESULTS

Approximately 121 beds/day were occupied by transferred patients at the academic centre, and on average, approximately 17 beds/day were used for hospital internal medicine and nine beds/day for non-procedural cardiology patients. Typical census for all internal medicine beds is approximately 175 and for cardiology is approximately 70.

CONCLUSION

Deferring transfers for patients in favour of local hospitalisation would increase the availability of beds for complex care at the referral centre. Potential downstream effects also include increased patient satisfaction due to proximity to home and viability of the local hospital system/economy, and decreased resource utilisation for transfer systems.

Care fragmentation in hepatopancreatic surgery and postoperative outcomes

BACKGROUND

Practice fragmentation in surgery may be associated with poor quality of care. We sought to define the association between fragmented practice and outcomes in hepatopancreatic surgery relative to surgeon volume and sex.

METHODS

Medicare beneficiaries who underwent hepatopancreatic surgery between 2016 and 2021 were identified. Multivariable analysis was performed to determine provider sex-based differences in the rate of fragmented practice relative to the achievement of a textbook outcome and health care expenditures after adjusting for procedure-specific case volume.

RESULTS

Among 37,416 patients, almost one-half were female (n = 18,333, 49.0%) with the majority treated by male surgeons (n = 33,697, 90.8%). Female surgeons were more likely to have a greater rate of fragmented practice (females: n = 242, 84.9% vs males: n = 1,487, 78.4%, P = .003; odds ratio 2.66, 95% confidence interval 2.33-3.03, P < .001). Patients treated by high rate of fragmented practice surgeons had increased odds of postoperative complications (odds ratio 1.40, 95% confidence interval 1.28-1.54), extended length-of-stay (odds ratio 1.52, 95% confidence interval 1.38-1.68), 90-day-mortality (odds ratio 1.49, 95% confidence interval 1.28-1.72), and lower odds of achieving a textbook outcome (odds ratio 0.76, 95% confidence interval 0.71-0.83). This association persisted independent of surgeon-specific volume (textbook outcome, high vs low rate of fragmented practice: high-volume surgeon, odds ratio 0.53, 95% confidence interval 0.31-0.91, P = .021 vs. low-volume surgeon, odds ratio 0.76, 95% confidence interval 0.69-0.82, P < .001). Among patients treated by male surgeons, a high rate of fragmented practice was associated with reduced odds of achieving a textbook outcome (male surgeons: odds ratio 0.76, 95% confidence interval 0.70-0.82, P < .001; female surgeons: odds ratio 0.81, 95% confidence interval 0.63-1.05, P = .110). Treatment by surgeons with higher fragmented practice was associated with higher expenditures (index expenditure: percentage difference 9.87, 95% confidence interval, 7.42-12.36; P < .05).

CONCLUSION

A high rate of fragmented practice adversely affected postoperative outcomes and healthcare expenditures even among high-volume surgeons with the impact varying based on surgeon sex.

The volume-outcome relationship in free-flap reconstruction: A nationwide study based on the Clinical Database

BACKGROUND

The association between successful reconstructive surgery with a free flap and hospital volume has not been well established. This study was designed to retrospectively analyze the outcome of free-flap surgery registered in a nationwide surgical registration system in Japan to clarify the relationship between free-flap survival and facilities' average annual number of free-flap surgeries.

METHODS

We analyzed data from 19,482 free flaps performed during 2017-2020 at 407 facilities throughout Japan. After adjusting for sex, age, and disease classification that differ between the groups, we examined the differences in the flap survival rates among the different facilities in terms of the average number of free-flap surgeries performed annually.

RESULTS

The total overall necrosis rate was 2.8%. Of all procedures, 14.9%, 12.9%, 33.4%, and 38.8% were performed at facilities with an average number of free-flap procedures <10, 10-19, 20-49, and ≥ 50 per year, respectively, and the respective rates of total necrosis were 6.0%, 3.8%, 2.1%, and 1.7%, respectively. The odds ratios and 95% confidence intervals of flap necrosis for facilities with ≥ 50 cases per year relative to those <10 were 2.70 (1.98-3.68) for nonbreast reconstruction cases and 5.72 (2.77-11.8) for breast reconstruction cases.

CONCLUSION

This analysis of a nationwide plastic surgery database showed that free-flap surgeries in institutions with a low average annual number of free-flap surgeries had a higher risk of total necrosis. Measures should be taken to either aggregate cases into high-volume centers or improve management at low-volume centers.

Understanding the Influence of Hospital Volume on Inpatient Outcomes Following Hospitalization for Status Epilepticus

BACKGROUND

Prior studies show hospital admission volume to be associated with poor outcomes following elective procedures and inpatient medical hospitalizations. However, it is unknown whether hospital volume impacts Inpatient outcomes for status epilepticus (SE) hospitalizations. In this study, we aimed to assess the impact of hospital volume on the outcome of patients with SE and related inpatient medical complications.

METHODS

The 2005 to 2013 National Inpatient Sample database was queried using International Classification of Diseases 9th Edition diagnosis code 345.3 to identify patients undergoing acute hospitalization for SE. The National Inpatient Sample hospital identifier was used as a unique facility identifier to calculate the average volume of patients with SE seen in a year. The study cohort was divided into three groups: low volume (0-7 patients with SE per year), medium volume (8-22 patients with SE per year), and high volume (> 22 patients with SE per year). Multivariate logistic regression analyses were used to assess whether medium or high hospital volume had lower rates of inpatient medical complications compared with low-volume hospitals.

RESULTS

A total of 137,410 patients with SE were included in the analysis. Most patients (n = 50,939; 37%) were treated in a low-volume hospital, 31% (n = 42,724) were treated in a medium-volume facility, and 18% (n = 25,207) were treated in a high-volume hospital. Patients undergoing treatment at medium-volume hospitals (vs. low-volume hospitals) had higher odds of pulmonary complications (odds ratio [OR] 1.18 [95% confidence interval {CI} 1.12-1.25]; p < 0.001), sepsis (OR 1.24 [95% CI 1.08-1.43] p = 0.002), and length of stay (OR 1.13 [95% CI 1.0 -1.19] p < 0.001). High-volume hospitals had significantly higher odds of urinary tract infections (OR 1.21 [95% CI 1.11-1.33] p < 0.001), pulmonary complications (OR 1.19 [95% CI 1.10-1.28], p < 0.001), thrombosis (OR 2.13 [95% CI 1.44-3.14], p < 0.001), and renal complications (OR 1.21 [95% CI 1.07-1.37], p = 0.002). In addition, high-volume hospitals had lower odds of metabolic (OR 0.81 [95% CI 0.72-0.91], p < 0.001), neurological complications (OR 0.80 [95% CI 0.69-0.93], p = 0.004), and disposition to a facility (OR 0.89 [95% CI 0.82-0.96], p < 0.001) compared with lower-volume hospitals.

CONCLUSIONS

Our study demonstrates certain associations between hospital volume and outcomes for SE hospitalizations. Further studies using more granular data about the type, severity, and duration of SE and types of treatment are warranted to better understand how hospital volume may impact care and prognosis of patients.

Associations of acute medical care with the transfer and acceptance functions of hospitals in a region in Japan with limited medical resources

BACKGROUND

Japan's health care system may be providing inpatient care inefficiently with a low number of physicians per hospital bed and a long average length of stay (LOS). The present study examined associations of acute medical care with hospital-level factors, such as the transfer and acceptance rates, and mediation effect of LOS, using medical service fees per day as an outcome measure for the provision of acute medical care in hospitals in a region with limited medical resources.

METHODS

To analyze the associations of acute medical care with hospital-level factors, this research used multilevel structural equation modeling (SEM) of a dataset that included 225,203 patients admitted to 99 hospitals in Fukushima, Japan. The characteristics of the patients, medical activities, and hospitals, such as the transfer and acceptance rates, were assumed to have both direct and indirect effects through LOS on medical service fees per day.

RESULTS

The final analysis used data from 165,413 patients discharged or transferred from 79 hospitals. After separating patient-level effects using multilevel SEM, the results revealed that, at the hospital level, the transfer rate had a significant and positive association with increased medical service fees per day, both directly (standardized coefficient [SC] = 0.215) and indirectly (SC = 0.057) through shortened LOS. The number of first hospitalized patients per physician had a significant and positive association with increased medical service fees per day only indirectly through shortened LOS (SC = 0.063). The acceptance rate had a significant and negative association with medical service fees per day only indirectly through prolonged LOS (SC = -0.078).

CONCLUSIONS

Hospital-level factors, such as enhanced transfer function, reduced acceptance function, and a large number of patients for treatment of acute episodes per physician, had positive associations with increased medical service fees per day, either directly or indirectly through LOS.

Methodology in coronary artery bypass surgery quality assessment

Coronary artery bypass graft (CABG) is associated with a high risk of mortality and morbidity; thus, assessment of surgery quality is necessary. In this perspective, we will focus on the structure, process, and outcomes measured as quality assessment. A set of 21 evidence-based structure, process, and outcome measures were selected as National Quality Forum. Of these, the Society of Thoracic Surgeons ultimately chose 11 individual quality measures grouped them into four domains used to assess the quality of CABGs. These four domains consisted of perioperative medical care, operative care, risk-adjusted operative mortality and postoperative risk-adjusted major morbidity. These measures have been useful as quality improvement tools in assessing the quality of CABG surgery.

Fragmentation of practice: The adverse effect of surgeons moving around

BACKGROUND

Whether surgical team familiarity is associated with improved postoperative outcomes remains unknown. We sought to characterize the impact of fragmented surgical practice on the likelihood that a patient would experience a textbook outcome, which is a validated patient-centric composite outcome representing an "ideal" postoperative outcome.

METHOD

Medicare beneficiaries aged 65 and older who underwent elective inpatient abdominal aortic aneurysm repair, coronary artery bypass graft, cholecystectomy, colectomy, or lung resection were identified. Rate of fragmented practice was calculated based on the total number of surgical procedures of interest performed over the study period (2013-2017) divided by the number of different hospitals in which the surgeon operated. Surgeons were categorized into "low," "average," "above average," or "high" rate of fragmented practice categories using an unsupervised machine learning technique known k-medians cluster analysis.

RESULTS

Among 546,422 Medicare beneficiaries who underwent an elective surgical procedure of interest (coronary artery bypass graft: n = 156,384, 28.6%; lung resection: n = 83,164, 15.2%; abdominal aortic aneurysm: n = 112,578, 20.6%; cholecystectomy: n = 42,955, 7.9%; colectomy: n = 151,341, 27.7%), median patient age was 74 years (interquartile range: 69-80), and most patients were male (n = 319,153, 58.4%). Machine learning identified 3 cutoffs to categorize rate of fragmented practice: 2.8%, 5.6%, and 10.6%. Overall, the majority of surgical procedures were performed by surgeons with a low rate of fragmented practice (n = 382,504, 70.0%); other surgical procedures were performed by surgeons with average (n = 109,141, 20.0%), above average (n = 44,249, 8.1%), or high (n = 10,528, 1.9%) rate of fragmented practice. On multivariable analyses, after controlling for patient demographics, individual surgeon volume, procedure type, and a random effect for hospital, patients who underwent a surgical procedure by a high versus low rate of fragmented practice surgeon had lower odds to achieve a postoperative textbook outcome (odds ratio 0.71, 95% confidence interval 0.77-0.84). Patients who underwent a procedure by a high rate of fragmented practice surgeon also had increased odds of a perioperative complication (odds ratio 1.30, 95% confidence interval: 1.23-1.37), extended length of stay (odds ratio 1.17, 95% confidence interval: 1.11-1.24), 90-day readmission (odds ratio 1.17, 95% confidence interval: 1.11-1.23), and 90-day mortality (odds ratio 1.29, 95% confidence interval: 1.17-1.42) (all P < .05).

CONCLUSION

Patients undergoing a surgical procedure by a surgeon with a high rate of fragmented practice had lower odds of achieving an optimal postoperative textbook outcome. Surgical team familiarity, measured by a surgeon rate of fragmented practice, may represent a modifiable mechanism to improve surgical outcomes.

What underlies the observed hospital volume-outcome relationship?

Background

Studies of the hospital volume-outcome relationship have highlighted that a greater volume activity improves patient outcomes. While this finding has been known for years, most studies to date have failed to delve into what underlies this relationship.

Objective

This study aimed to shed light on the basis of the hospital volume effect on patient outcomes by comparing treatment modalities for epithelial ovarian carcinoma patients.

Data

An exhaustive dataset of 355 patients in first-line treatment for Epithelial Ovarian Carcinoma (EOC) in 2012 in three regions of France was used. These regions account for 15% of the metropolitan French population.

Methods

In the presence of endogeneity induced by a reverse causality between hospital volume and patient outcomes, we used an instrumental variable approach. Hospital volume of activity was instrumented by the distance from patients’ homes to their hospital, the population density, and the median net income of patient municipalities.

Results

Based on our parameter estimates, we found that the rate of complete tumor resection would increase by 15.5 percentage points with centralized care, and by 8.3 percentage points if treatment decisions were coordinated by high-volume centers compared to decentralized care.

Conclusion

As volume alone is an imperfect correlate of quality, policy-makers need to know what volume is a proxy for in order to devise volume-based policies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07449-2.