Evaluation of operating room inefficiencies and their impact on operating room duration using a surgical app

BACKGROUND

Efficient utilization of the operating room (OR) is essential. Inefficiencies are thought to cause preventable delays. Our goal was to identify OR incidents causing delays and estimate their impact on the duration of various general surgery procedures.

MATERIALS

Three trained observers prospectively collected intraoperative data using the ExplORer Surgical app, a tool that helped capture incidents causing delays. The impact of each incident on case duration was assessed using multivariable analysis.

RESULTS

151 general surgery procedures were observed. The mean number of incidents was 2.7 per each case that averaged 109min. On average, each incident caused a 2.8 ​min delay (p ​< ​0.001), however, some incidents were associated with longer delays. The procedural step of each procedure most susceptible to incidents was also defined.

CONCLUSION

The identification of the type of incidents and the procedural step during which they occur may allow targeted interventions to optimize OR efficiency and decrease operative time.

Inefficiency of two-stage designs in phase II oncology clinical trials with high proportion of inevaluable patients

BACKGROUND

Two-stage designs are commonly used for oncology Phase II clinical trials with a binary response endpoint. An issue that has not gained sufficient attention is the potential inefficiency in the usage of two-stage designs due to multiple enrollment suspensions when the proportion of patients inevaluable for response is high.

METHODS

Simulation studies were used to assess the performance of Simon's two-stage designs, two-stage designs with a proposed modification, and a single-stage design in the context of Phase II clinical trials with a high proportion of patients inevaluable for response.

RESULTS

Two-stage designs can require multiple enrollment disruptions when the inevaluable proportion is high, which can result in unacceptable inefficiency. The proposed modification provides a practical solution to this issue by enrolling an extra number of patients towards the end of the 1st stage, anticipating that a proportion of the patients pending response evaluation could be inevaluable. Single-stage designs with interim monitoring of futility that require no interim accrual suspension can be more efficient than two-stage designs, especially when the accrual and inevaluable rates are high.

CONCLUSIONS

Planning of Phase II trials should consider the issue of inefficiency of the two-stage designs, especially for trials with a high inevaluable proportion. Designs with monitoring rules that do not require accrual suspensions may be given more considerations, especially in trials of agents that have already had some evidence for safety and efficacy in other populations.

Insights from the (in)efficiency of Chinese sectoral indices during COVID-19

This article evaluates the effects of the crisis caused by the new Coronavirus (COVID-19) on the Chinese sectoral indices. Using the complexity-entropy plane methodology, we find that the COVID-19 crisis caused increased inefficiency in most of China's equity sectors. We also find heterogeneous effects depending on the economic sector. Our results are useful for a better understanding the effect of global shocks on the stock markets and how their effects are distributed across economic sectors.

Perceived 'optimal efficiency': theorization and conceptualization for development and implementation

We recently advanced the study of positive psychology by introducing the theory of optimization, which explains the underlying process of optimal best. Our continuing research interest has led us to a newly developed concept, termed as ‘optimal efficiency’. Optimal efficiency, we contend, focuses on the utilization of resources as well as the amount of time and effort that a person would have to expend during the course of his/her learning. How much time and effort, for example, should a student expend before it is perceived as being ‘inefficient’? Optimal efficiency, in this analysis, is concerned with an important relationship – namely: the minimization of expenditure of time, effort, resources, etc. versus the maximization in productivity.

Perceived efficiency is related to the teaching and training of judgment, decision making, autonomy, and self-determination – for example, in terms of successful schooling, a student has to decide whether it is worthwhile to expend so much time and effort on a given task when he/she may not necessarily pass. In our conceptual analysis and proposition of optimal efficiency, we consider the impact of cognitive load theory, which places emphasis on calculated investment and subsequent use of cognitive resources to process information for the purpose of achieving effective learning in a subject matter. Using cognitive load theory as a basis, we attempt to validate the concept of optimal efficiency by taking into account three main types of cognitive load imposition: extraneous, intrinsic, and germane. For example, we consider the possibility that a reduction in extraneous cognitive load imposition could instill a perception of efficiency, resulting in a person's achievement of optimal best. Emphasis on encouragement of germane cognitive load, in contrast, could be perceived as being more efficient, likewise yielding exceptional outcomes in a subject matter.

Preventing rather than punishing: An early warning model of malfeasance in public procurement

Is it possible to predict malfeasance in public procurement? With the proliferation of e-procurement systems in the public sector, anti-corruption agencies and watchdog organizations have access to valuable sources of information with which to identify transactions that are likely to become troublesome and why. In this article, we discuss the promises and challenges of using machine learning models to predict inefficiency and corruption in public procurement. We illustrate this approach with a dataset with more than two million public procurement contracts in Colombia. We trained machine learning models to predict which of them will result in corruption investigations, a breach of contract, or implementation inefficiencies. We then discuss how our models can help practitioners better understand the drivers of corruption and inefficiency in public procurement. Our approach will be useful to governments interested in exploiting large administrative datasets to improve the provision of public goods, and it highlights some of the tradeoffs and challenges that they might face throughout this process.

Technical efficiency of provincial public healthcare in South Africa

Background

Forty-nine million people or 83 per cent of the entire population of 59 million rely on the public healthcare system in South Africa. Coupled with a shortage of medical professionals, high migration, inequality and unemployment; healthcare provision is under extreme pressure. Due to negligence by the health professionals, provincial health departments had medical-legal claims estimated at R80 billion in 2017/18. In the same period, provincial health spending accounted for 33 per cent of total provincial expenditure of R570.3 billion or 6 per cent of South Africa’s Gross Domestic Product. Despite this, healthcare outcomes are poor and provinces are inefficient in the use of the allocated funds. This warrants a scientific investigation into the technical efficiency of the public health system.

Methods

The study uses data envelopment analysis (DEA) to assess the technical efficiency of the nine South African provinces in the provision of healthcare. This is achieved by determining, assessing and comparing ways that individual provinces can benchmark their performance against peers to improve efficiency scores. DEA compares firms operating in homogenous conditions in the usage of multiple inputs to produce multiple outputs. Therefore, DEA is ideal for measuring the technical efficiency of provinces in the provision of public healthcare. In DEA methodology, the firms with scores of 100 per cent are technically efficient and those with scores lower than 100 per cent are technically inefficient. This study considers six DEA models using the 2017/18 total health spending and health staff as inputs and the infant mortality rate as an output. The first three models assume the constant returns to scale (CRS) while the last three use the variable return to scale (VRS) both with an input-minimisation objective.

Results

The study found the mean technical efficiency scores ranging from 35.7 to 87.2 per cent between the health models 1 and 6. Therefore, inefficient provinces could improve the use of inputs within a range of 64.3 and 20.8 per cent. The Gauteng province defines the technical efficiency frontiers in all the six models. The second-best performing province is the North West province. Other provinces like KwaZulu-Natal, Limpopo and the Eastern Cape only perform well under the VRS. The other three provinces are inefficient.

Conclusions

Based on the VRS models 4 to 6, the study presents three policy options. Policy option 1 (model 4): the efficiency gains from addressing health expenditure wastage in four inefficient provinces amounts to R17 billion. Policy option 2 (model 5): the potential savings from the same provinces could be obtained from reducing 17,000 health personnel, advisably, in non-core areas. In terms of Policy option 3 (model 6), three inefficient provinces should reduce 6940 health workers while the same provinces, inclusive of KwaZulu-Natal could realise health expenditure savings of R61 million. The potential resource savings from improving the efficiency of the inefficient provinces could be used to refurbish and build more hospitals to alleviate pressure on the public health system. This could also reduce the per capita numbers per public hospital and perhaps their performance as overcrowding is reportedly negatively affecting their performance and health outcomes. The potential savings could also be used to appoint and train medical practitioners, specialists and researchers to reduce the alarming numbers of medical legal claims. Given the existing challenges, South Africa is not ready to implement the National Health Insurance (NHI) Scheme, as it requires additional financial and human resources. Instead, huge improvements in public healthcare provision could be achieved by re-allocating the resources ‘saved’ through efficiency measures by increasing the quality of public healthcare and extending healthcare to more recipients.

Network dysfunction during associative learning in schizophrenia: Increased activation, but decreased connectivity: an fMRI study

Schizophrenia (SCZ) is characterized by disordered activation and disordered connectivity, yet few fMRI studies have convergently investigated both. Here, we compared differences in activation and connectivity between SCZ and controls (HC). Twenty-two subjects (18≤age≤35yrs) participated in a paired-associative learning task, a behavioral domain particularly dependent on fronto-hippocampal connectivity and of relevance to the schizophrenia diathesis. Activation differences were assessed using standard approaches. Seed-based connectivity differences were compared using Psychophysiological Interaction (PPI) with a hippocampus-based seed. SCZ evinced significantly increased activation, but significantly decreased connectivity with the hippocampus across a cortical-striatal learning network. These results assess potentially complementary patterns of network dysfunction in schizophrenia: increased activation suggests inefficient responses relating to functional specialization; decreased connectivity suggests impaired integration of functional signals between regions. Inefficiency and dysconnection appear to collectively characterize functional deficits in schizophrenia.