The work relative value estimation assessment in China: an empirical research for common surgical procedures.

Objectives: China's National Health Service Items Standard (NHSIS) establishes a relative value system and plays an important role in pricing. However, there are few empirical evaluations of the objectivity of the NHSIS-estimated relative value. Methods: This paper presents a comparison between physician work relative value units (wRVUs) estimates for 70 common surgical procedures from NHSIS and those from the U.S. Medicare Physician Fee Schedule (MPFS). We defined the ratio of the wRVUs for sample procedures to the benchmark procedure (inguinal hernia repair) as a standardized relative value unit (SRVU), which was used to standardize the data for both schedules. We examined the variances in the ranking and quantification of SRVUs across specialties and procedures, as well as how SRVUs impact procedure reimbursement prices between the two schedules. Results: There was no systematic difference between MHSIS-estimated SRVUs and MPFS-estimated, but the dispersion of MPFS-estimated SRVU was greater than that of MHSIS-estimated, and the discrepancies increased with surgical risk and technical complexity. The discrepancies of SRVUs were significant in cardiothoracic procedures. Additionally, whether SRVUs were based on MPFS or MHSIS, there was a positive association between them and payment prices. However, in terms of the impact of SRVUs on payment pricing, the NHSIS system was lower than the MPFS system. Conclusion: China has made incremental progress in estimating the relative value of healthcare services, but there are shortcomings in valuation methods and their impact on pricing. The modular assessment method should be considered as a component to optimize reform.

Measurements of Impoverishing and Catastrophic Surgical Health Expenditures in Low- and Middle-Income Countries and Reduction Interventions in the Last 30 Years: A Systematic Review.

INTRODUCTION: Approximately 33 million people suffer catastrophic health expenditure (CHE) from surgery and/or anesthesia costs. The aim of this systematic review is to evaluate catastrophic and impoverishing expenditure associated with surgery and anesthesia in low- and middle-income countries (LMICs). METHODS: We performed a systematic review of all studies from 1990 to 2021 that reported CHE in LMICs for treatment of a condition requiring surgical intervention, including cesarean section, trauma care, and other surgery. RESULTS: 77 studies met inclusion criteria. Tertiary facilities (23.4%) were the most frequently studied facility type. Only 11.7% of studies were conducted in exclusively rural health-care settings. Almost 60% of studies were retrospective in nature. The cost of procedures ranged widely, from $26 USD for a cesarean section in Mauritania in 2020 to $74,420 for a pancreaticoduodenectomy in India in 2018. GDP per capita had a narrower range from $315 USD in Malawi in 2019 to $9955 USD in Malaysia in 2015 (Median = $1605.50, interquartile range = $1208.74). 35 studies discussed interventions to reduce cost and catastrophic expenditure. Four of those studies stated that their intervention was not successful, 18 had an unknown or equivocal effect on cost and CHE, and 13 concluded that their intervention did help reduce cost and CHE. CONCLUSIONS: CHE from surgery is a worldwide problem that most acutely affects vulnerable patients in LMICs. Existing efforts are insufficient to meet the true need for affordable surgical care unless assistance for ancillary costs is given to patients and families most at risk from CHE.

Assessing the Impact of Neighborhood and Built Environment on Pediatric Perioperative Care: A Systematic Review of the Literature.

CONTEXT: Neighborhood and built environment encompass one key area of the Social Determinants of Health (SDOH) and is frequently assessed using area-level indices. OBJECTIVE: We sought to systematically review the pediatric surgery literature for use of commonly applied area-level indices and to compare their utility for prediction of outcomes. DATA SOURCES: A literature search was conducted using PubMed, Ovid MEDLINE, Ovid MEDLINE Epub Ahead of Print, PsycInfo, and an artificial intelligence search tool (1/2013-2/2023). STUDY SELECTION: Inclusion required pediatric surgical patients in the US, surgical intervention performed, and use of an area-level metric. DATA EXTRACTION: Extraction domains included study, patient, and procedure characteristics. RESULTS: Area Deprivation Index is the most consistent and commonly accepted index. It is also the most granular, as it uses Census Block Groups. Child Opportunity Index is less granular (Census Tract), but incorporates pediatric-specific predictors of risk. Results with Social Vulnerability Index, Neighborhood Deprivation Index, and Neighborhood Socioeconomic Status were less consistent. LIMITATIONS: All studies were retrospective and quality varied from good to fair. CONCLUSIONS: While each index has strengths and limitations, standardization on ideal metric(s) for the pediatric surgical population will help build the inferential power needed to move from understanding the role of SDOH to building meaningful interventions towards equity in care. TYPE OF STUDY: Systematic Review. LEVEL OF EVIDENCE: Level III.

Changes in social care after major emergency general surgery procedures.

BACKGROUND: Emergency general surgery (EGS) is a major part of the provision of healthcare, and patients undergoing EGS are at elevated risk of morbidity and mortality. This study aimed to determine factors contributing to patients losing their independence and being discharged to residential and nursing homes having previously lived in their own residences. METHODS: Our local data uploaded to the National Emergency Laparotomy Audit (NELA) (2014-2022) were analyzed. This national database encompasses all major EGS cases undertaken in the United Kingdom. The variables considered were patient demographics, American Society of Anesthesiologists score, admission and discharge dates, presenting pathology, operation type, and discharge destination. Comparative analyses segmented patients based on postdischarge EGS destinations. Multivariable logistic regression identified factors linked to residential/nursing home placement after discharge. Significance was set at P < .05. RESULTS: Data from all patients in the NELA database (n = 1611) were analyzed. Approximately 1 in 10 patients older than 70 years never returned home. Patients requiring additional support were on average 8.6 years older (P = .008). At older than 80 years, the need for extra social support increased substantially with each increasing year in age, and those older than 85 years were more than twice as likely to require extra support than 80-year-olds (P < .001). Patients who died were 11.4 years older than those discharged without additional support (P < .001). CONCLUSION: A significant proportion of patients, particularly the elderly, do not return to their usual place of residence and require a higher level of care postemergency surgery. These important social factors need to be considered before operating given that they may have significant quality of life and economic implications.

Association of social determinants of health-related diagnosis codes with postoperative outcomes.

BACKGROUND: The association of an individual's social determinants of health-related problems with surgical outcomes has not been well-characterized. The objective of this study was to determine whether documentation of social determinants of a health-related diagnosis code (Z code) is associated with postoperative outcomes. METHODS: This retrospective cohort study included surgical cases from a single institution's national surgical quality improvement program (NSQIP) clinical registry from October 2015 to December 2021. The primary predictor of interest was documentation of a Z code for social determinants of health-related problems. The primary outcome was 30-day postoperative morbidity. Secondary outcomes included postoperative length of stay, disposition, and 30-day postoperative mortality, reoperation, and readmission. Multivariable regression models were fit to evaluate the association between the documentation of a Z code and outcomes. RESULTS: Of 10,739 surgical cases, 348 patients (3.2%) had a documented social determinants of health-related Z code. In multivariable analysis, documentation of a Z code was associated with increased odds of morbidity (20.7% vs. 9.9%; adjusted odds ratio [aOR], 1.88; 95% confidence interval [CI], 1.39-2.53), length of stay (median, 3 vs. 1 day; incidence rate ratio, 1.49; 95% CI, 1.33-1.67), odds of disposition to a location other than home (11.3% vs. 3.9%; aOR, 2.86; 95% CI, 1.89-4.33), and odds of readmission (15.3% vs. 6.1%; aOR, 1.99; 95% CI, 1.45-2.73). CONCLUSIONS: Social determinants of health-related problems evaluated using Z codes were associated with worse postoperative outcomes. Improved documentation of social determinants of health-related problems among surgical patients may facilitate improved risk stratification, perioperative planning, and clinical outcomes.

Racial Disparities in Pediatric Mortality Following Transfusion Within 72 Hours of Operation.

BACKGROUND: Postoperative bleeding and transfusion are correlated with mortality risk. Furthermore, postoperative bleeding may often initiate the cascade of complications that leads to death. Given that minority children have increased risk of surgical complications, this study aimed to investigate the association of race with pediatric surgical mortality following postoperative transfusion. METHODS: We used the NSQIP-P PUF to assemble a retrospective cohort of children <18 who underwent inpatient surgery during 2012-2021. We included White, Black, Hispanic, and 'Other' children who received a transfusion within 72 h of surgery. The primary outcome was defined as all-cause mortality within 30 days following the primary surgical procedure. Using logistic regression models, we estimated the risk-adjusted odds ratio (aOR) and 95% confidence intervals (CI) of mortality, comparing each racial/ethnic cohort to White children. RESULTS: A total of 466,230 children <18 years of age underwent inpatient surgical procedures from 2012 to 2021. Of these, 46,200 required transfusion and were included in our analysis. The majority of patients were non-Hispanic White (64.6%, n = 29,850), while 18.9% (n = 8752) were non-Hispanic Black, 11.7% (n = 5387) were Hispanic, and 4.8% (n = 2211) were 'Other' race. The overall rate of mortality following transfusion was 2.5%. White children had the lowest incidence of mortality (2.0%), compared to children of 'Other' race (2.5%), Hispanic children (3.1%), and Black children (3.6%). After adjusting for sex, age, comorbidities, case status, preoperative transfusion within 48 h, and year of operation, we found that Black children experienced 1.24 times the odds of mortality following a postoperative transfusion compared to a White child (aOR: 1.24; 95%CI, 1.03-1.51; P = 0.025). Hispanic children were also significantly more likely to die following a postoperative transfusion than White children (aOR: 1.19; 95%CI, 1.02-1.39; P = 0.027). CONCLUSION: We found that minority children who required a postoperative transfusion had a higher odds of death than White children. Future studies should explore adverse events following postoperative transfusion and the differences in their management by race that may contribute to the higher mortality rate for minority children. LEVEL OF EVIDENCE: Level II. CLINICAL TRIAL NUMBER AND REGISTRY: Not applicable.

Racial Disparities in General Surgery Outcomes.

INTRODUCTION: While disparities in Black and Hispanic and Latino patients undergoing general surgeries are well described, most analyses leave out Asian, American Indian or Alaskan Native (AIAN), and native Hawaiian or Pacific Islander patients. This study identified general surgery outcomes for each racial group in the National Surgical Quality Improvement Program. METHODS: National Surgical Quality Improvement Program was queried to identify all procedures conducted by a general surgeon from 2017 to 2020 (n = 2,664,197). Multivariable regression models were used to investigate the impact of race and ethnicity on 30-day mortality, readmission, reoperation, major and minor medical complications, and non-home discharge destinations. Adjusted odds ratios (AOR) and 95% confidence intervals were calculated. RESULTS: Compared to non-Hispanic White patients, Black patients had higher odds of readmission and reoperation, and Hispanic and Latino patients had higher odds of major and minor complications. AIAN patients had higher odds of mortality (AOR: 1.003 (1.002-1.005), P < 0.001), major complication (AOR: 1.013 (1.006-1.020), P < 0.001), reoperation (AOR: 1.009, (1.005-1.013), P < 0.001), and non-home discharge destination (AOR: 1.006 (1.001-1.012), P = 0.025), while native Hawaiian or Pacific Islander patients had lower odds of readmission (AOR: 0.991 (0.983-0.999), P = 0.035) and non-home discharge destination (AOR: 0.983 (0.975-0.990), P < 0.001) compared to non-Hispanic White patients. Asian patients had lower odds of each adverse outcome. CONCLUSIONS: Black, Hispanic and Latino, and AIAN patients are at higher odds for poor postoperative results than non-Hispanic White patients. AIANs had some of the highest odds of mortality, major complications, reoperation, and non-home discharge. Social health determinants and policy adjustments must be targeted to ensure optimal operative results for all patients.

Health System Structure: An Opportunity to Address Structural Racism and Discrimination.

OBJECTIVE: To examine the role of hub-and-spoke systems as a factor in structural racism and discrimination. BACKGROUND: Health systems are often organized in a "hub-and-spoke" manner to centralize complex surgical care to 1 high-volume hospital. Although the surgical health care disparities are well described across health care systems, it is not known how they seem across a single system's hospitals. METHODS: Adult patients who underwent 1 of 10 general surgery operations in 12 geographically diverse states (2016-2018) were identified using the Healthcare Cost and Utilization Project's State Inpatient Databases. System status was assigned using the American Hospital Association dataset. Hub designation was assigned in 2 ways: (1) the hospital performing the most complex operations (general hub) or (2) the hospital performing the most of each specific operation (procedure-specific hub). Independent multivariable logistic regression was used to evaluate the risk-adjusted odds of treatment at hubs by race and ethnicity. RESULTS: We identified 122,236 patients across 133 hospitals in 43 systems. Most patients were White (73.4%), 14.2% were Black, and 12.4% Hispanic. A smaller proportion of Black and Hispanic patient underwent operations at general hubs compared with White patients (B: 59.6% H: 52.0% W: 62.0%, P <0.001). After adjustment, Black and Hispanic patients were less likely to receive care at hub hospitals relative to White patients for common and complex operations (general hub B: odds ratio: 0.88 CI, 0.85, 0.91 H: OR: 0.82 CI, 0.79, 0.85). CONCLUSIONS: When White, Black, and Hispanic patients seek care at hospital systems, Black and Hispanic patients are less likely to receive treatment at hub hospitals. Given the published advantages of high-volume care, this new finding may highlight an opportunity in the pursuit of health equity.

Previsões do número de cirurgias suspensas utilizando o software Power BI® em um hospital universitário / Predictions of the number of suspended surgeries using software Power BI® in a university hospital / Predicciones del número de cirugías suspendidas utilizando software Power BI® en un hospital universitario

Objetivo: analisar as cirurgias suspensas, realizando previsões futuras de três meses, a partir de outubro de 2022, através de um gráfico de linhas utilizando o software Power BI®. Método: se utilizou a técnica de médias moveis ponderada, alisamento exponencial simples, utilizando a ferramenta gráfico de linhas do Power BI®, com intervalo de confiança de 95% e previsões de três meses. Resultados: os resultados demostraram que existem diferentes etapas para construir previsões e alguns pré-requisitos devem ser preenchidos, foram encontradas as seguintes previsões com seus respectivos intervalos de confiança novembro 134(97,172), dezembro 141(102,180), janeiro 147(106.188). Conclusão: a utilização de previsões pode ser uma ferramenta útil para a tomada de decisão, prever problemas e sempre necessário na gestão de um hospital, podendo até suprimir gastos se antecipando a uma variedade de problemas.

Objective: to analyze the suspended surgeries, making future predictions of three months, starting in October 2022, through a line graph using the Power BI software. Method: we used the technique of weighted moving averages, simple exponential smoothing, using the Power BI® line graph tool, with a confidence interval of 95% and predictions of three months. Results: the results showed that there are different steps to construct predictions and some prerequisites must be fulfilled, the following predictions were found with their respective confidence intervals: November 134 (97,172), December 141 (102,180), January 147 (106,188). Conclusion: the use of forecasts can be a useful tool for decision making, predicting problems and always necessary in the management of a hospital, and can even suppress expenses in anticipation of a variety of problems.

Objetivos:analizar las cirugías suspendidas, haciendo predicciones futuras de tres meses, a partir de octubre de 2022, a través de un gráfico lineal utilizando el software Power BI®. Método: se utilizó la técnica de medias móviles ponderadas, suavizado exponencial simple, utilizando la herramienta de gráfico de líneas de Power BI®, con un intervalo de confianza del 95% y predicciones de tres meses. Resultados: los resultados mostraron que existen diferentes pasos para construir predicciones y se deben cumplir algunos requisitos previos, se encontraron las siguientes predicciones con sus respectivos intervalos de confianza: noviembre 134 (97,172), diciembre 141 (102,180), enero 147 (106,188). Conclusión: el uso de pronósticos puede ser una herramienta útil para la toma de decisiones, predicción de problemas y siempre necesaria en la gestión de un hospital, e incluso puede suprimir gastos en previsión de una variedad de problemas.

Trends in Adverse Event Rates in Hospitalized Patients, 2010-2019.

Importance: Patient safety is a US national priority, yet lacks a comprehensive assessment of progress over the past decade. Objective: To determine the change in the rate of adverse events in hospitalized patients. Design, Setting, and Participants: This serial cross-sectional study used data from the Medicare Patient Safety Monitoring System from 2010 to 2019 to assess in-hospital adverse events in patients. The study included 244 542 adult patients hospitalized in 3156 US acute care hospitals across 4 condition groups from 2010 through 2019: acute myocardial infarction (17%), heart failure (17%), pneumonia (21%), and major surgical procedures (22%); and patients hospitalized from 2012 through 2019 for all other conditions (22%). Exposures: Adults aged 18 years or older hospitalized during each included calendar year. Main Outcomes and Measures: Information on adverse events (abstracted from medical records) included 21 measures across 4 adverse event domains: adverse drug events, hospital-acquired infections, adverse events after a procedure, and general adverse events (hospital-acquired pressure ulcers and falls). The outcomes were the total change over time for the observed and risk-adjusted adverse event rates in the subpopulations. Results: The study sample included 190 286 hospital discharges combined in the 4 condition-based groups of acute myocardial infarction, heart failure, pneumonia, and major surgical procedures (mean age, 68.0 [SD, 15.9] years; 52.6% were female) and 54 256 hospital discharges for the group including all other conditions (mean age, 57.7 [SD, 20.7] years; 59.8% were female) from 3156 acute care hospitals across the US. From 2010 to 2019, the total change was from 218 to 139 adverse events per 1000 discharges for acute myocardial infarction, from 168 to 116 adverse events per 1000 discharges for heart failure, from 195 to 119 adverse events per 1000 discharges for pneumonia, and from 204 to 130 adverse events per 1000 discharges for major surgical procedures. From 2012 to 2019, the rate of adverse events for all other conditions remained unchanged at 70 adverse events per 1000 discharges. After adjustment for patient and hospital characteristics, the annual change represented by relative risk in all adverse events per 1000 discharges was 0.94 (95% CI, 0.93-0.94) for acute myocardial infarction, 0.95 (95% CI, 0.94-0.96) for heart failure, 0.94 (95% CI, 0.93-0.95) for pneumonia, 0.93 (95% CI, 0.92-0.94) for major surgical procedures, and 0.97 (95% CI, 0.96-0.99) for all other conditions. The risk-adjusted adverse event rates declined significantly in all patient groups for adverse drug events, hospital-acquired infections, and general adverse events. For patients in the major surgical procedures group, the risk-adjusted rates of events after a procedure declined significantly. Conclusions and Relevance: In the US between 2010 and 2019, there was a significant decrease in the rates of adverse events abstracted from medical records for patients admitted for acute myocardial infarction, heart failure, pneumonia, and major surgical procedures and there was a significant decrease in the adjusted rates of adverse events between 2012 and 2019 for all other conditions. Further research is needed to understand the extent to which these trends represent a change in patient safety.

General surgeon involvement in the care of patients designated with an American Association for the Surgery of Trauma-endorsed ICD-10-CM emergency general surgery diagnosis code in Wisconsin.

BACKGROUND: The current national burden of emergency general surgery (EGS) illnesses and the extent of surgeon involvement in the care of these patients remain largely unknown. To inform needs assessments, research, and education, we sought to: (1) translate previously developed International Classification of Diseases (ICD), 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes representing EGS conditions to ICD 10th Revision, CM (ICD-10-CM) codes and (2) determine the national burden of and assess surgeon involvement across EGS conditions. METHODS: We converted ICD-9-CM codes to candidate ICD-10-CM codes using General Equivalence Mappings then iteratively refined the code list. We used National Inpatient Sample 2016 to 2017 data to develop a national estimate of the burden of EGS disease. To evaluate surgeon involvement, using Wisconsin Hospital Association discharge data (January 1, 2016 to June 30, 2018), we selected adult urgent/emergent encounters with an EGS condition as the principal diagnosis. Surgeon involvement was defined as a surgeon being either the attending provider or procedural physician. RESULTS: Four hundred and eighty-five ICD-9-CM codes mapped to 1,696 ICD-10-CM codes. The final list contained 985 ICD-10-CM codes. Nationally, there were 2,977,843 adult patient encounters with an ICD-10-CM EGS diagnosis. Of 94,903 EGS patients in the Wisconsin Hospital Association data set, most encounters were inpatient as compared with observation (75,878 [80.0%] vs. 19,025 [20.0%]). There were 57,780 patients (60.9%) that underwent any procedure. Among all Wisconsin EGS patients, most had no surgeon involvement (64.9% [n = 61,616]). Of the seven most common EGS diagnoses, surgeon involvement was highest for appendicitis (96.0%) and biliary tract disease (77.1%). For the other five most common conditions (skin/soft tissue infections, gastrointestinal hemorrhage, intestinal obstruction/ileus, pancreatitis, diverticular disease), surgeons were involved in roughly 20% of patient care episodes. CONCLUSION: Surgeon involvement for EGS conditions ranges from highly likely (appendicitis) to relatively unlikely (skin/soft tissue infections). The wide range in surgeon involvement underscores the importance of multidisciplinary collaboration in the care of EGS patients. LEVEL OF EVIDENCE: Prognostic/epidemiological, Level III.

Effect of COVID-19 Pandemic Restructuring on Surgical Volume and Outcomes of Non-COVID Patients Undergoing Surgery.

OBJECTIVES: COVID-19 has caused significant surgical delays as institutions minimize patient exposure to hospital settings and utilization of health care resources. We aimed to assess changes in surgical case mix and outcomes due to restructuring during the pandemic. METHODS: Patients undergoing surgery at a single tertiary care institution in the Deep South were identified using institutional ACS-NSQIP data. Primary outcome was case mix. Secondary outcomes were post-operative complications. Chi-square, ANOVA, logistic regression, and linear regression were used to compare the control (pre-COVID, Mar 2018-Mar 2020) and case (during COVID, Mar 2020-Mar 2021) groups. RESULTS: Overall, there were 6912 patients (control: 4,800 and case: 2112). Patients were 70% white, 29% black, 60% female, and 39% privately insured. Mean BMI was 30.2 (SD = 7.7) with mean age of 58.3 years (SD = 14.8). Most surgeries were with general surgery (48%), inpatient (68%), and elective (83%). On multivariable logistic regression, patients undergoing surgery during the pandemic were more likely to be male (OR: 1.14) and in SIRS (OR: 2.07) or sepsis (OR: 2.28) at the time of surgery. Patients were less likely to have dyspnea with moderate exertion (OR: .75) and were less dependent on others (partially dependent OR: .49 and totally dependent OR: .15). Surgeries were more likely to be outpatient (OR: 1.15) and with neurosurgery (OR: 1.19). On bivariate analysis, there were no differences in post-operative outcomes. CONCLUSION: Surgeries during the COVID-19 pandemic were more often outpatient without differences in post-operative outcomes. Additional analysis is needed to determine the impact of duration of operative delay on surgical outcomes with restructuring focusing more on outpatient surgeries.

Impact of opioid use disorder on resource utilization and readmissions after operative trauma.

BACKGROUND: Although patients with opioid use disorder have been shown to be more susceptible to traumatic injury, the impact of opioid use disorder after trauma-related admission remains poorly characterized. The present nationally representative study evaluated the association of opioid use disorder on clinical outcomes after traumatic injury warranting operative intervention. METHODS: The 2010 to 2018 Nationwide Readmissions Database was used to identify adult trauma victims who underwent major operative procedures. Injury severity was quantified using International Classification of Diseases Trauma Mortality Prediction Model. Entropy balancing was used to adjust for intergroup differences. Multivariable regression models were developed to assess the association of opioid use disorder on in-hospital mortality, perioperative complications, resource utilization, and readmissions. RESULTS: Of an estimated 5,089,003 hospitalizations, 54,097 (1.06%) had a diagnosis of opioid use disorder with increasing prevalence during the study period. Compared with others, opioid use disorder had a lower proportion of extremity injuries and falls but greater predicted mortality measured by Trauma Mortality Prediction Model. After adjustment, opioid use disorder was associated with decreased odds of in-hospital mortality (adjusted odds ratio: 0.61; 95% confidence interval, 0.53-0.70) but had greater likelihood of pneumonia, infectious complications, and acute kidney injury. Additionally, opioid use disorder was associated with longer hospitalization duration as well as greater index costs and risk of readmission within 30 days (adjusted odds ratio: 1.36; 95% confidence interval, 1.25-1.49). CONCLUSION: Opioid use disorder in operative trauma has significantly increased in prevalence and is associated with decreased in-hospital index mortality but greater resource utilization and readmission.

Emergency General Surgery Procedures and Cost of Care for Older Adults in the State of Maryland.

BACKGROUND: Older adults (OAs) ≥ 65 years of age, representing the fastest growing segment in the United States, are anticipated to require a greater percentage of emergency general surgery procedures (EGSPs) with an associated increase in health care costs. The aims of this study were to identify the frequency of EGSP and charges incurred by OA compared to their younger counterparts in the state of Maryland. METHODS: A retrospective review of the Maryland Health Services Cost Review Commission from 2009 to 2018 was undertaken. Patients undergoing urgent or emergent ESGP were divided into 2 groups (18-64 years and ≥65 years). Data collected included demographics, APR-severity of illness (SOI), APR-risk of mortality (ROM), the EGSP (partial colectomy [PC], small bowel resection [SBR], cholecystectomy, operative management of peptic ulcer disease, lysis of adhesions, appendectomy, and laparotomy), length of stay (LOS), and hospital charges. P-values (P < .05) were significant. RESULTS: Of the 181,283 patients included in the study, 55,401 (38.1%) were ≥65 years of age. Older adults presented with greater APR-SOI (major 37.7% vs 21.3%, extreme 5.2% vs 9.3%), greater APR-ROM (major 25.3% vs 8.7%, extreme 22.3% vs 5.3%), underwent PC (24.5% vs 10.9%) and SBR (12.8% vs 7.0%) more frequently, and incurred significantly higher median hospital charges for every EGSP, consistently between 2009 and 2018 due to increased LOS and complications when compared to those ≤65 years of age. CONCLUSION: These findings stress the need for validated frailty indices and quality improvement initiatives focused on the care of OAs in emergency general surgery to maximize outcomes and optimize cost.

Ontario wait times for delayed surgical treatment of traumatic peripheral nerve injury.

BACKGROUND: To better understand the occurrence and operative treatment of peripheral nerve injury (PNI) and the potential need for additional resources, it is essential to define the frequency and distribution of peripheral nerve procedures being performed. The objective of this study was to evaluate Ontario's wait times for delayed surgical treatment of traumatic PNI. METHODS: We retrieved data on wait times for peripheral nerve surgery from the Ontario Ministry of Health and Long-Term Care Wait Time Information System. We reviewed the wait times for delayed surgical treatment of traumatic PNI among adult patients (age ≥ 18 yr) from April 2009 to March 2018. Data collected included total cases, mean and median wait times, and demographic characteristics. RESULTS: Over the study period, 7313 delayed traumatic PNI operations were reported, with variability in the case volume distribution across Local Health Integration Networks (LHINs). The highest volume of procedures (2788) was performed in the Toronto Central LHIN, and the lowest volume (< 6) in the Waterloo Wellington and North Simcoe Muskoka LHINs. The population incidence of traumatic PNI requiring surgery was 5.1/10 000. The mean and median wait times from surgical decision to surgical repair were 45 and 27 days, respectively. Both the longest and shortest wait times occurred in LHINs with low case volumes. The provincial target wait time was met in 93% of cases, but women waited significantly longer than men (p < 0.001). CONCLUSION: The provincial distribution of traumatic PNI surgery was variable, and the highest volumes were in the LHINs with large populations. The provincial wait time strategy for traumatic PNI surgery is effective, but women waited longer than men. Precise reporting from all hospitals is necessary to accurately capture and understand the delivery of care after traumatic PNI.

Assessment of Costs and Care Quality Associated With Major Surgical Procedures After Implementation of Maryland's Capitated Budget Model.

Importance: In 2014, Maryland implemented the all-payer model, a distinct hospital funding policy that applied caps on annual hospital expenditures and mandated reductions in avoidable complications. Expansion of this model to other states is currently being considered; therefore, it is important to evaluate whether Maryland's all-payer model is achieving the desired goals among surgical patients, who are an at-risk population for most potentially preventable complications. Objective: To examine the association between the implementation of Maryland's all-payer model and the incidence of avoidable complications and resource use among adult surgical patients. Design, Setting, and Participants: This comparative effectiveness study used hospital discharge records from the Healthcare Cost and Utilization Project state inpatient databases to conduct a difference-in-differences analysis comparing the incidence of avoidable complications and the intensity of health resource use before and after implementation of the all-payer model in Maryland. The analytical sample included 2 983 411 adult patients who received coronary artery bypass grafting (CABG), carotid endarterectomy (CEA), spinal fusion, hip or knee arthroplasty, hysterectomy, or cesarean delivery between January 1, 2008, and December 31, 2016, at acute care hospitals in Maryland (intervention state) and New York, New Jersey, and Rhode Island (control states). Data analysis was conducted from July 2019 to July 2021. Exposures: All-payer model. Main Outcomes and Measures: Complications (infectious, cardiovascular, respiratory, kidney, coagulation, and wound) and health resource use (ie, hospital charges). Results: Of 2 983 411 total patients in the analytical sample, 525 262 patients were from Maryland and 2 458 149 were from control states. Across Maryland and the control states, there were statistically significant but not clinically relevant differences in the preintervention period with regard to patient age (mean [SD], 49.7 [19.0] years vs 48.9 [19.3] years, respectively; P < .001), sex (22.7% male vs 21.4% male; P < .001), and race (0.3% vs 0.4% American Indian, 2.8% vs 4.5% Asian or Pacific Islander, 25.9% vs 12.7% Black, 4.7% vs 11.9% Hispanic, and 63.5% vs 63.4% White; P < .001). After implementation of the all-payer model in Maryland, significantly lower rates of avoidable complications were found among patients who underwent CABG (-11.3%; 95% CI, -13.8% to -8.7%; P < .001), CEA (-1.6%; 95% CI, -2.9% to -0.3%; P = .02), hip arthroplasty (-0.8%; 95% CI, -1.0% to -0.5%; P < .001), knee arthroplasty (-0.4%; 95% CI, -0.7% to -0.1%; P = .01), and cesarean delivery (-1.0%; 95% CI, -1.3% to -0.7%; P < .001). In addition, there were significantly lower increases in index hospital costs in Maryland among patients who underwent CABG (-$6236; 95% CI, -$7320 to -$5151; P < .001), CEA (-$730; 95% CI, -$1367 to -$94; P = .03), spinal fusion (-$3253; 95% CI, -$3879 to -$2627; P < .001), hip arthroplasty (-$328; 95% CI, -$634 to -$21; P = .04), knee arthroplasty (-$415; 95% CI, -$643 to -$187; P < .001), cesarean delivery (-$300; 95% CI, -$380 to -$220; P < .001), and hysterectomy (-$745; 95% CI, -$974 to -$517; P < .001). Significant changes in patient mix consistent with a younger population (eg, a shift toward private/commercial insurance for orthopedic procedures, such as spinal fusion [4.3%; 95% CI, 3.4%-5.2%; P < .001] and knee arthroplasty [1.6%; 95% CI, 1.0%-2.3%; P < .001]) and a lower comorbidity burden across surgical procedures (eg, CABG: -0.7% [95% CI, -0.1% to -0.5%; P < .001]; hip arthroplasty: -3.0% [95% CI, -3.6% to -2.3%; P < .001]) were also observed. Conclusions and Relevance: In this study, patients who underwent common surgical procedures had significantly fewer avoidable complications and lower hospital costs, as measured against the rate of increase throughout the study, after implementation of the all-payer model in Maryland. These findings may be associated with changes in the patient mix.

Assessment of Hospital Characteristics and Interhospital Transfer Patterns of Adults With Emergency General Surgery Conditions.

Importance: Although patients with emergency general surgery (EGS) conditions frequently undergo interhospital transfers, the transfer patterns and associated factors are not well understood. Objective: To examine whether patients with EGS conditions are consistently directed to hospitals with more resources and better outcomes. Design, Setting, and Participants: This cohort study performed a network analysis of interhospital transfers among adults with EGS conditions from January 1 to December 31, 2016. The analysis used all-payer claims data from the 2016 Healthcare Cost and Utilization Project state inpatient and emergency department databases in 8 states. A total of 728 hospitals involving 85 415 transfers of 80 307 patients were included. Patients were eligible for inclusion if they were 18 years or older and had an acute care hospital encounter with a diagnosis of an EGS condition as defined by the American Association for the Surgery of Trauma. Data were analyzed from January 1, 2020, to June 17, 2021. Exposures: Hospital-level measures of size (total bed capacity), resources (intensive care unit [ICU] bed capacity, teaching status, trauma center designation, and presence of trauma and/or surgical critical care fellowships), EGS volume (annual EGS encounters), and EGS outcomes (risk-adjusted failure to rescue and in-hospital mortality). Main Outcomes and Measures: The main outcome was hospital-level centrality ratio, defined as the normalized number of incoming transfers divided by the number of outgoing transfers. A higher centrality ratio indicated more incoming transfers per outgoing transfer. Multivariable regression analysis was used to test the hypothesis that a higher hospital centrality ratio would be associated with more resources, higher volume, and better outcomes. Results: Among 80 307 total patients, the median age was 63 years (interquartile range [IQR], 50-75 years); 52.1% of patients were male and 78.8% were White. The median number of outgoing and incoming transfers per hospital were 106 (IQR, 61-157) and 36 (IQR, 8-137), respectively. A higher log-transformed centrality ratio was associated with more resources, such as higher ICU capacity (eg, >25 beds vs 0-10 beds: ß = 1.67 [95% CI, 1.16-2.17]; P < .001), and higher EGS volume (eg, quartile 4 [highest] vs quartile 1 [lowest]: ß = 0.78 [95% CI, 0-1.57]; P = .01). However, a higher log-transformed centrality ratio was not associated with better outcomes, such as lower in-hospital mortality (eg, quartile 4 [highest] vs quartile 1 [lowest]: ß = 0.30 [95% CI, -0.09 to 0.68]; P = .83) and lower failure to rescue (eg, quartile 4 [highest] vs quartile 1 [lowest]: ß = -0.50 [95% CI, -1.13 to 0.12]; P = .27). Conclusions and Relevance: In this study, EGS transfers were directed to high-volume hospitals with more resources but were not necessarily directed to hospitals with better clinical outcomes. Optimizing transfer destination in the interhospital transfer network has the potential to improve EGS outcomes.

The Correlation Between Case Total Work Relative Value Unit, Operative Stress, and Patient Frailty: Retrospective Cohort Study.

OBJECTIVE: Assess the relationships between case total work relative value units (wRVU), patient frailty, and the physiologic stress of surgical interventions. SUMMARY OF BACKGROUND DATA: Surgeon reimbursement is frequently apportioned by wRVU. These subjective, procedure-specific valuations generated by physician survey estimate the intensity and time for typical patient care services. We hypothesized wRVU would not adequately account for patient-specific factors, such as frailty, that modify the required physician work, regardless of procedural complexity. METHODS: Using National and Veterans Affairs Surgical Quality Improvement Programs (2015-2018), we evaluated the correlation between case total wRVU, patient frailty (risk analysis index) and physiologic surgical stress (operative stress score). RESULTS: Of 4,111,371 (86%) cases, the correlation between total wRVU and operative stress was moderate [ρs = 0.587 (95% confidence interval, 0.586-0.587)], but negligible with frailty ρ = 0.177 (95% confidence interval, 0.176-0.178)]. Very high operative stress procedures [n = 34,047 (1%)] generated a mean total wRVU of 55.1 (standard deviation, 12.9), comprising 7%, 2%, and 1% of thoracic, vascular, and general surgical cases, respectively. Very frail patients [n = 152,535 (4%)] accounted for 9% of thoracic, 9% of vascular, 4% of general, 5% of urologic, and 4% of neurologic surgical cases, generating 21.0 (standard deviation, 12.4) mean total wRVU. Some nonfrail patients undergoing low operative stress procedures [n = 60,128 (2%)] nonetheless generated the highest quintile wRVU; these comprised >15% of plastic, gynecologic, and urologic surgical cases. CONCLUSIONS: Surgeon reimbursement correlates with operative stress but not patient frailty. The total wRVU does not adequately reflect patient-specific factors that increase the physician workload required to render optimal care to complex patients.

Medicare Advantage Networks and Access to High-volume Cancer Surgery Hospitals.

OBJECTIVE: To determine how Medicare Advantage (MA) health plan networks impact access to high-volume hospitals for cancer surgery. BACKGROUND: Cancer surgery at high-volume hospitals is associated with better short- and long-term outcomes. In the United States, health insurance is a major detriment to seeking care at high-volume hospitals. A third of older (>65 years) Americans are enrolled in privatized MA health plans. The impact of MA plan networks on access to high-volume surgery hospitals is unknown. METHODS: We analyzed in-network hospitals for MA plans offered in Los Angeles county during open enrollment of 2015. For the purposes of this analysis, MA network data from provider directories were linked to hospital volume data from California Office of Statewide Health Planning and Development. Volume thresholds were based on published literature. RESULTS: A total of 34 MA plans enrolled 554,754 beneficiaries in Los Angeles county during 2014 open enrollment for coverage starting in 2015 (MA penetration ∼43%). The proportion of MA plans that included high-volume cancer surgery hospital varied by the type of cancer surgery. While most plans (>71%) included at least one high-volume hospital for colon, rectum, lung, and stomach; 59% to 82% of MA plans did not include any high-volume hospitals for liver, esophagus, or pancreatic surgery. A significant proportion of beneficiaries in MA plans did not have access to high-volume hospitals for esophagus (93%), stomach (44%), liver (39%), or pancreas (70%) surgery. In contrast, nearly all MA beneficiaries had access to at least one high-volume hospital for lung (93%), colon (100%), or rectal (100%) surgery. Overall, Centers for Medicare & Medicaid Services plan rating or plan popularity were not correlated with access to high-volume hospital (P > 0.05). CONCLUSIONS: The study identifies lack of high-volume hospital coverage in MA health plans as a major detriment in regionalization of cancer surgery impacting at least a third of older Americans.