Protocol for a multicentre, multistage, prospective study in China using system-based approaches for consistent improvement in surgical safety

Development and validation of an interpretable Markov-embedded multilabel model for predicting risks of multiple postoperative complications among surgical inpatients: a multicenter prospective cohort study

BACKGROUND

When they encounter various highly related postoperative complications, existing risk evaluation tools that focus on single or any complications are inadequate in clinical practice. This seriously hinders complication management because of the lack of a quantitative basis. An interpretable multilabel model framework that predicts multiple complications simultaneously is urgently needed.

MATERIALS AND METHODS

The authors included 50 325 inpatients from a large multicenter cohort (2014-2017). The authors separated patients from one hospital for external validation and randomly split the remaining patients into training and internal validation sets. A MARKov-EmbeDded (MARKED) multilabel model was proposed, and three models were trained for comparison: binary relevance, a fully connected network (FULLNET), and a deep neural network. Performance was mainly evaluated using the area under the receiver operating characteristic curve (AUC). The authors interpreted the model using Shapley Additive Explanations. Complication-specific risk and risk source inference were provided at the individual level.

RESULTS

There were 26 292, 6574, and 17 459 inpatients in the training, internal validation, and external validation sets, respectively. For the external validation set, MARKED achieved the highest average AUC (0.818, 95% CI: 0.771-0.864) across eight outcomes [compared with binary relevance, 0.799 (0.748-0.849), FULLNET, 0.806 (0.756-0.856), and deep neural network, 0.815 (0.765-0.866)]. Specifically, the AUCs of MARKED were above 0.9 for cardiac complications [0.927 (0.894-0.960)], neurological complications [0.905 (0.870-0.941)], and mortality [0.902 (0.867-0.937)]. Serum albumin, surgical specialties, emergency case, American Society of Anesthesiologists score, age, and sex were the six most important preoperative variables. The interaction between complications contributed more than the preoperative variables, and formed a hierarchical chain of risk factors, mild complications, and severe complications.

CONCLUSION

The authors demonstrated the advantage of MARKED in terms of performance and interpretability. The authors expect that the identification of high-risk patients and the inference of the risk source for specific complications will be valuable for clinical decision-making.

Prediction of complications associated with general surgery using a Bayesian network

BACKGROUND

Numerous attempts have been made to identify risk factors for surgery complications, but few studies have identified accurate methods of predicting complex outcomes involving multiple complications.

METHODS

We performed a prospective cohort study of general surgical inpatients who attended 4 regionally representative hospitals in China from January to June 2015 and January to June 2016. The risk factors were identified using logistic regression. A Bayesian network model, consisting of directed arcs and nodes, was used to analyze the relationships between risk factors and complications. Probability ratios for complications for a given node state relative to the baseline probability were calculated to quantify the potential effects of risk factors on complications or of complications on other complications.

RESULTS

We recruited 19,223 participants and identified 21 nodes, representing 9 risk factors and 12 complications, and 55 direct relationships between these. Respiratory failure was at the center of the network, directly affected by 5 risk factors, and directly affected 7 complications. Cardiopulmonary resuscitation and sepsis or septic shock also directly affected death. The area under the receiver operating characteristic curve for the ability of the network to predict complications was >0.7. Notably, the probability of other severe complications or death significantly increased when a severe complication occurred. Most importantly, there was a 141-fold higher risk of death when cardiopulmonary resuscitation was required.

CONCLUSION

We have created a Bayesian network that displays how risk factors affect complications and their interrelationships and permits the accurate prediction of complications and the creation of appropriate preventive guidelines.

Construction and evaluation of networks among multiple postoperative complications

BACKGROUND AND OBJECTIVE

Postoperative complications confer an increased risk of reoperation, prolonged length of hospital stay, and increased mortality. Many studies have attempted to identify the complex associations among complications to preemptively interrupt their progression, but few studies have looked at complications as a whole to reveal and quantify their possible trajectories of progression. The main objective of this study was to construct and quantify the association network among multiple postoperative complications from a comprehensive perspective to elucidate the possible evolution trajectories.

METHODS

In this study, a Bayesian network model was proposed to analyze the associations among 15 complications. Prior evidence and score-based hill-climbing algorithms were used to build the structure. The severity of complications was graded according to their connection to death, with the association between them quantified using conditional probabilities. The data of surgical inpatients used in this study were collected from four regionally representative academic/teaching hospitals in a prospective cohort study in China.

RESULTS

In the network obtained, 15 nodes represented complications or death, and 35 arcs with arrows represented the directly dependent relationship between them. With three grades classified on that basis, the correlation coefficients of complications within grades increased with increased grade, ranging from -0.11 to -0.06, 0.16, and 0.21 to 0.4 in grade 1 to grade 3, respectively. Moreover, the probability of each complication in the network increased with the occurrence of any other complication, even mild complications. Most seriously, once cardiac arrest requiring cardiopulmonary resuscitation occurs, the probability of death will be up to 88.1%.

CONCLUSIONS

The present evolving network can facilitate the identification of strong associations among specific complications and provides a basis for the development of targeted measures to prevent further deterioration in high-risk patients.

Network prediction of surgical complication clusters: a prospective multicenter cohort study

Complicated relationships exist in both occurrence and progression of surgical complications, which are difficult to account for using a separate quantitative method such as prediction or grading. Data of 51,030 surgical inpatients were collected from four academic/teaching hospitals in a prospective cohort study in China. The relationship between preoperative factors, 22 common complications, and death was analyzed. With input from 54 senior clinicians and following a Bayesian network approach, a complication grading, cluster-visualization, and prediction (GCP) system was designed to model pathways between grades of complication and preoperative risk factor clusters. In the GCP system, there were 11 nodes representing six grades of complication and five preoperative risk factor clusters, and 32 arcs representing a direct association. Several critical targets were pinpointed on the pathway. Malnourished status was a fundamental cause widely associated (7/32 arcs) with other risk factor clusters and complications. American Society of Anesthesiologists (ASA) score ⩾3 was directly dependent on all other risk factor clusters and influenced all severe complications. Grade III complications (mainly pneumonia) were directly dependent on 4/5 risk factor clusters and affected all other grades of complication. Irrespective of grade, complication occurrence was more likely to increase the risk of other grades of complication than risk factor clusters.

Generating real-world evidence compatible with evidence from randomized controlled trials: a novel observational study design applicable to surgical transfusion research

BACKGROUND

Numerous observational studies have revealed an increased risk of death and complications with transfusion, but this observation has not been confirmed in randomized controlled trials (RCTs). The "transfusion kills patients" paradox persists in real-world observational studies despite application of analytic methods such as propensity-score matching. We propose a new design to address this long-term existing issue, which if left unresolved, will be deleterious to the healthy generation of evidence that supports optimized transfusion practice.

METHODS

In the new design, we stress three aspects for reconciling observational studies and RCTs on transfusion safety: (1) re-definition of the study population according to a stable hemoglobin range (gray zone of transfusion decision; 7.5-9.5 g/dL in this study); (2) selection of comparison groups according to a trigger value (last hemoglobin measurement before transfusion; nadir during hospital stay for control); (3) dealing with patient heterogeneity according to standardized mean difference (SMD) values. We applied the new design to hospitalized older patients (aged ≥60 years) undergoing general surgery at four academic/teaching hospitals. Four datasets were analyzed: a base population before (Base Match-) and after (Base Match+) propensity-score matching to simulate previous observational studies; a study population before (Study Match-) and after (Study Match+) propensity-score matching to demonstrate effects of our design.

RESULTS

Of 6141 older patients, 662 (10.78%) were transfused and showed high heterogeneity compared with those not receiving transfusion, particularly regarding preoperative hemoglobin (mean: 11.0 vs. 13.5 g/dL) and intraoperative bleeding (≥500 mL: 37.9% vs. 2.1%). Patient heterogeneity was reduced with the new design; SMD of the two variables was reduced from approximately 100% (Base Match-) to 0% (Study Match+). Transfusion was related to a higher risk of death and complications in Base Match- (odds ratio [OR], 95% confidence interval [CI]: 2.68, 1.86-3.86) and Base Match+ (2.24, 1.43-3.49), but not in Study Match- (0.77, 0.32-1.86) or Study Match+ (0.66, 0.23-1.89).

CONCLUSIONS

We show how choice of study population and analysis could affect real-world study findings. Our results following the new design are in accordance with relevant RCTs, highlighting its value in accelerating the pace of transfusion evidence generation and generalization.

Expanding restrictive transfusion evidence in surgical practice: a multicentre, prospective cohort study

BACKGROUND

Findings of observational studies investigating the impact of transfusions are at odds with those of randomised controlled trials, raising concern that observational studies may be inappropriate to inform transfusion decisions. We examined whether observational data could replicate evidence from randomised controlled trials on restrictive transfusion in cardiac and orthopaedic surgery, and be generalised to broader specialties as well as to a lower haemoglobin transfusion threshold (7 g/dL).

MATERIAL AND METHODS

A multicentre, prospective cohort study was performed at three representative regional hospitals in China between 2015 and 2016. Participants were surgical inpatients (≥18 years; hospital stay ≥24 h) in six specialties: cardiac, cerebral, vascular (CCV), and orthopaedic, general, thoracic (non-CCV). Patients with a stable haemoglobin (7-10 g/dL) constituted the primary analytic sample, while patients with ≥500 mL intra-operative bleeding were analysed separately to avoid haemoglobin instability. The association of transfusion with surgical outcomes (death, in-hospital complications) was evaluated.

RESULTS

The transfusion rate was 10.7% in 36,607 patients (mean age, 52.5±14.3 years; 52.3% female). After restriction, stratification, and propensity score matching to reduce patients' heterogeneity, transfusion was unrelated to death (CCV: odds ratio [OR]=0.74, 95% confidence interval [CI]: 0.16-3.39; non-CCV: OR 0.83, 95% CI: 0.36-1.94) and the composite complication (CCV: OR 1.31, 95% CI: 0.63-2.72; non-CCV: OR=1.24, 95% CI: 0.81-1.90). The results were consistent in subgroups (elderly, coronary heart disease, malignant tumour, severe illness) and applicable to patients with significant bleeding after restoration of a stable haemoglobin.

DISCUSSION

Transfusion at a stable haemoglobin concentration of 7-10 g/dL did not alter surgical outcomes. Our results show the feasibility of observational data to expand restrictive transfusion to broader specialties and a lower transfusion threshold in surgical practice.

Digital Construction of Vocal Music Teaching Resource Base Using Data Mining Technology

Vocal music teaching resource databases can support teachers' instruction and students' learning while also enhancing the school's ability to run a school because they are the main components of digital construction for vocal music teaching. Currently, system application is the main area of research for DM (data mining), which was previously focused on method discovery. A vocal music teaching resource base based on DM technology is created by using the theme as the central organising principle, processing, and organising the resources. Incorporate lesson planning, teaching, self-study, and output resource construction into a digital network resource application environment by using thematic resource development. Students' achievement data, personal basic information, and evaluation data are used for DM based on the enhanced Apriori algorithm in order to uncover hidden rules and find correlations between various factors. This information is then used to support decision-making. When the system load is 1, the results demonstrate that the Apriori algorithm's CPU waste rate and task success rate is 0.144 and 0.896, respectively. The study's conclusion demonstrates that integrating DM technology into the field of education is theoretically and practically possible and that there is significant room for future study and application in this area.

Establishment and implementation of safety check project for invasive procedures outside the operating room

Objective

This study aimed to describe the implementation of the surgical safety check policy and the surgical safety checklist for invasive procedures outside the operating room (OR) and evaluate its effectiveness.

Methods

In 2017, to improve the safety of patients who underwent invasive procedures outside of the OR, the hospital quality and safety committee established the surgery safety check committee responsible for developing a new working plan, revise the surgery safety check policy, surgery safety check form, and provide training to the related staff, evaluated their competency, and implemented the updated surgical safety check policy and checklist. The study compared the data of pre-implementation (Apr to Sep 2017) and two post-implementation phases (Apr to Sep 2018, Apr to Sep 2019). It also evaluated the number of completed surgery safety checklist, correct signature, and correct timing of signature.

Results

The results showed an increase in the completion rate of the safety checklist after the program implementation from 41.7% (521/1,249) to 90.4% (3,572/3,950), the correct rates of signature from 41.9% (218/521) to 99.0% (4,423/4,465), and the correct timing rates of signature from 34.4% (179/521) to 98.5% (4,401/4,465), with statistical significance (P < 0.01).

Conclusion

Implementing the updated surgery safety check significantly is a necessary and effective measure to ensure patient safety for those who underwent invasive procedures outside the OR. Implementing surgical safety checks roused up the clinical staff’s compliance in performing safety checks, and enhanced team collaboration and communication.

Developing a toolbox for identifying when to engage senior surgeons in emergency general surgery: A multicenter cohort study

BACKGROUND

Having a senior surgeon present for high-risk patients is an important safety measure in emergency surgery, but 24-h consultant cover is not efficient. We aimed to develop a user-friendly toolbox (risk identification, outcome prediction and patient stratification) to support when to involve a senior surgeon.

MATERIALS AND METHODS

We included 11,901 general surgery patients (10.0% emergencies) in a multicenter prospective cohort in China (2015-2016). Patient information and surgeons' seniority were compared between emergency and elective surgery with the same procedure codes. Risk indicators common in these two surgical timings and specific to emergency surgery were identified, and their clinical importance was evaluated by a working group of 48 experienced surgeons. Predictive models for mortality and morbidity were built using logistic regression models. Stratification rules were created to balance patients' risk and surgeons' caseload with an Acute Call Team (ACT) model.

RESULTS

Emergency patients had significantly higher risks of mortality (3.6% vs 0.6%) and morbidity (7.8% vs 4.3%) than elective patients, but disproportionally fewer senior surgeons (59.9% vs 91.4%) were present. Using three risk indicators (American Society of Anesthesiologists score, age, blood urea nitrogen), C-statistic (95% CI) for prediction of emergency mortality was high [0.90 (0.84-0.96)]. It was less complex but equally accurate as two existing and validated models (0.86 [0.79-0.93] and 0.86 [0.77-0.95]). Using five indicators, C-statistic (95% CI) was moderate for prediction of overall morbidity [0.77 (0.72-0.83)], but high for severe morbidity [0.92 (0.88-0.97)]. Based on stratification rules of the ACT model, patient mortality and morbidity were 0.5% and 5.3% in the low-risk stratum (composing 64.6% of emergency caseload), and 15.9% and 29.0% in the very high-risk stratum (6.9% of caseload).

CONCLUSION

These findings show the practical feasibility of using a risk assessment tool to direct senior surgeons' involvement in emergency general surgery.

Population-based projections of blood supply and demand, China, 2017-2036

Objective

To estimate the long-term effect of the changing demography in China on blood supply and demand.

Methods

We developed a predictive model to estimate blood supply and demand during 2017–2036 in mainland China and in 31 province-level regions. Model parameters were obtained from World Population Prospects, China statistical yearbook 2016, China’s report on blood safety and records from a large tertiary hospital. Our main assumptions were stable age-specific per capita blood supply and demand over time.

Findings

We estimated that the change in demographic structure between 2016 (baseline year) and 2036 would result in a 16.0% decrease in blood supply (from 43.2 million units of 200 mL to 36.3 million units) and a 33.1% increase in demand (from 43.2 million units to 57.5 million units). In 2036, there would be an estimated shortage of 21.2 million units. An annual increase in supply between 0.9% and 1.8% is required to maintain a balance in blood supply and demand. This increase is not enough for every region as regional differences will increase, e.g. a blood demand/supply ratio ≥ 1.45 by 2036 is predicted in regions with large populations older than 65 years. Sensitivity analyses showed that increasing donations by 4.0% annually by people aged 18–34 years or decreasing the overall blood discard rate from 5.0% to 2.0% would not offset but help reduce the blood shortage.

Conclusion

Multidimensional strategies and tailored, coordinated actions are needed to deal with growing pressures on blood services because of China’s ageing population.

Cost-effectiveness comparison of routine transfusion with restrictive and liberal transfusion strategies for surgical patients in China

BACKGROUND AND OBJECTIVES

A health industry standard recommending restrictive transfusion is to be in effect in China in April 2019. We aim to explore its potential economic and clinical impacts among surgical patients.

MATERIALS AND METHODS

A decision tree model was applied to compare cost-effectiveness of current routine transfusion in China, a restrictive (transfusion at Hb < 8 g/dl or ischaemic symptoms) and a liberal (transfusion at Hb < 10 g/dl) strategy. Parameters were estimated from empirical data of 25 227 surgical inpatients aged ≥30 years in a multicenter study and supplemented by meta-analysis when necessary. Results are shown for cardio-cerebral-vascular (CCV) surgery and non-CCV (orthopaedics, general, thoracic) surgery separately.

RESULTS

Per 10 000 patients in routine, restrictive, liberal transfusion scenarios, total spending (transfusion and length of stay related) was 7·67, 7·58 and 9·39 million CNY (1 CNY × 0.157 = 1 US dollar) for CCV surgery and 6·35, 6·70 and 8·09 million CNY for non-CCV surgery; infectious and severe complications numbered 354, 290, and 290 (CCV) and 315, 286, and 330 (non-CCV), respectively. Acceptability curves showed high probabilities for restrictive strategy to be cost-effective across a wide range of willingness-to-pay values. Such findings were mostly consistent in sensitivity and subgroup analyses except for patients with cardiac problems.

CONCLUSION

We showed strong rationale, succeeding previous findings only in cardiac or joint procedures, to comply with the new standard as restrictive transfusion has high potential to save blood, secure safety, and is cost-effective for a wide spectrum of surgical patients. Experiences should be further summarized to pave the way towards individualized transfusion.

Key Issues in the Development of an Evidence-Based Stratified Surgical Patient Safety Improvement Information System: Experience From a Multicenter Surgical Safety Program

Surgery is still far from being completely safe and reliable. Surgical safety has, therefore, been the focus of considerable attention over the last few decades, and there are a growing number of national drives to improve it. There are also a number of large surgical complication reporting systems and system-based interventions, both of which have made remarkable progress in the past two decades. These systems, however, have either mainly focused on reporting complications and played a limited role in guiding practice or have provided nonselective interventions to all patients, perhaps imposing unnecessary burdens on frontline medical staff. We have, therefore, developed an evidence-based stratified surgical safety information system based on a multicenter surgical safety improvement program. This study discusses some critical issues in the process of developing this information system, including (1) decisions about data gathering, (2) establishing and sharing knowledge, (3) developing functions for the system, (4) system implementation, and (5) evaluation and continuous improvement. Using examples drawn from the surgical safety improvement program, we have shown how this type of system can be fitted into day-to-day clinical practice and how it can guide medical practice by incorporating inherent patient-related risk and providing tailored interventions for patients with different levels of risk. We concluded that multidisciplinary collaboration, involving experts in health care (including senior staff in surgery, nursing, and anesthesia), data science, health care management, and health information technology, can help build an evidence-based stratified surgical patient safety improvement system. This can provide an information-intensified surgical safety learning platform and, therefore, benefit surgical patients by delivering tailored interventions and an integrated workflow.

Effect of a risk-stratified intervention strategy on surgical complications: experience from a multicentre prospective study in China

OBJECTIVES

To develop a risk-stratified intervention strategy and evaluate its effect on reducing surgical complications.

DESIGN

A multicentre prospective study with preintervention and postintervention stages: period I (January to June 2015) to develop the intervention strategy and period II (January to June 2016) to evaluate its effectiveness.

SETTING

Four academic/teaching hospitals representing major Chinese administrative and economic regions.

PARTICIPANTS

All surgical (elective and emergent) inpatients aged ≥14 years with a minimum hospital stay of 24 hours, who underwent a surgical procedure requiring an anesthesiologist.

INTERVENTIONS

Targeted complications were grouped into three categories (common, specific, serious) according to their incidence pattern, severity and preventability. The corresponding expert consensus-generated interventions, which focused on both regulating medical practices and managing inherent patient-related risks, were implemented in a patient-tailored way via an electronic checklist system.

PRIMARY AND SECONDARY OUTCOMES

Primary outcomes were (1) in-hospital death/confirmed death within 30 days after discharge and (2) complications during hospitalisation. Secondary outcome was length of stay (LOS).

RESULTS

We included 51 030 patients in this analysis (eligibility rate 87.7%): 23 413 during period I, 27 617 during period II. Patients' characteristics were comparable during the two periods. After adjustment, the mean number of overall complications per 100 patients decreased from 8.84 to 7.56 (relative change 14.5%; P<0.0001). Specifically, complication rates decreased from 3.96 to 3.65 (7.8%) for common complications (P=0.0677), from 0.50 to 0.36 (28.0%) for specific complications (P=0.0153) and from 3.64 to 2.88 (20.9%) for serious complications (P<0.0001). From period I to period II, there was a decreasing trend for mortality (from 0.64 to 0.53; P=0.1031) and median LOS (by 1 day; P=0.8293), without statistical significance.

CONCLUSIONS

Implementing a risk-stratified intervention strategy may be a target-sensitive, convenient means to improve surgical outcomes.

Health Information Technology in Healthcare Quality and Patient Safety: Literature Review

Background

The area of healthcare quality and patient safety is starting to use health information technology to prevent reportable events, identify them before they become issues, and act on events that are thought to be unavoidable. As healthcare organizations begin to explore the use of health information technology in this realm, it is often unclear where fiscal and human efforts should be focused.

Objective

The purpose of this study was to provide a foundation for understanding where to focus health information technology fiscal and human resources as well as expectations for the use of health information technology in healthcare quality and patient safety.

Methods

A literature review was conducted to identify peer-reviewed publications reporting on the actual use of health information technology in healthcare quality and patient safety. Inductive thematic analysis with open coding was used to categorize a total of 41 studies. Three pre-set categories were used: prevention, identification, and action. Three additional categories were formed through coding: challenges, outcomes, and location.

Results

This study identifies five main categories across seven study settings. A majority of the studies used health IT for identification and prevention of healthcare quality and patient safety issues. In this realm, alerts, clinical decision support, and customized health IT solutions were most often implemented. Implementation, interface design, and culture were most often noted as challenges.

Conclusions

This study provides valuable information as organizations determine where they stand to get the most “bang for their buck” relative to health IT for quality and patient safety. Knowing what implementations are being effectivity used by other organizations helps with fiscal and human resource planning as well as managing expectations relative to cost, scope, and outcomes. The findings from this scan of the literature suggest that having organizational champion leaders that can shepherd implementation, impact culture, and bridge knowledge with developers would be a valuable resource allocation to consider.