The efficiency and productivity evaluation process commonly employs Data Envelopment Analysis (DEA) as a performance tool in numerous fields, such as the healthcare industry (hospitals). Therefore, this review examined various hospital-based DEA articles involving input and output variable selection approaches and the recent DEA developments. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was utilised to extract 89 English articles containing empirical data between 2014 and 2022 from various databases (Web of Science, Scopus, PubMed, ScienceDirect, Springer Link, and Google Scholar). Furthermore, the DEA model parameters were determined using information from previous studies, while the approaches were identified narratively. This review grouped the approaches into four sections: literature review, data availability, systematic method, and expert judgement. An independent single strategy or a combination with other methods was then applied to these approaches. Consequently, the focus of this review on various methodologies employed in hospitals could limit its findings. Alternative approaches or techniques could be utilised to determine the input and output variables for a DEA analysis in a distinct area or based on different perspectives. The DEA application trend was also significantly similar to that of previous studies. Meanwhile, insufficient data was observed to support the usability of any DEA model in terms of fitting all model parameters. Therefore, several recommendations and methodological principles for DEA were proposed after analysing the existing literature.

The COVID-19 pandemic introduced significant novel risks for healthcare workers and healthcare services. This study aimed to determine the prevalence, trends, characteristics, and sources of COVID-19 infection among healthcare workers during the early COVID-19 pandemic in Malaysian hospitals. A cross-sectional study used secondary data collected from a COVID-19 surveillance system for healthcare workers between January and December 2020. Two surges in COVID-19 cases among healthcare workers in Malaysia were epidemiologically correlated to a similarly intense COVID-19 pattern of transmission in the community. The period prevalence of COVID-19 infection and the mortality rate among healthcare workers in Malaysia were 1.03% and 0.0019%, respectively. The majority of infections originated from the workplace (53.3%); a total of 36.3% occurred among staff; a total of 17.0% occurred between patients and staff; and 43.2% originated from the community. Healthcare workers had a 2.9 times higher incidence risk ratio for the acquisition of COVID-19 infection than the general population. Nursing professionals were the most highly infected occupational group (40.5%), followed by medical doctors and specialists (24.1%), and healthcare assistants (9.7%). The top three departments registering COVID-19 infections were the medical department (23.3%), the emergency department (17.7%), and hospital administration and governance (9.1%). Occupational safety and health units need to be vigilant for the early detection of a disease outbreak to prevent the avoidable spread of disease in high-risk settings. The transformation of some tertiary hospitals to dedicated COVID-19 care, the monitoring of new procedures for the management of COVID-19 patients, and appropriate resource allocation are key to successful risk mitigation strategies.

Data Envelopment Analysis (DEA) has been employed as a performance evaluation tool in the evaluation of efficiency and productivity in numerous fields. This includes hospitals in particular as well as the broad healthcare industry. This review examines 89 papers that discuss the use of DEA in hospitals, paying particular attention to approaches for choosing inputs and outputs as well as the most recent developments in DEA studies. English articles with empirical data from year 2014-2022 (Web of Science, Scopus, PubMed, ScienceDirect, Springer Link, and Google Scholar) were extracted based on PRISMA methodology. DEA Model parameters were specified based on previous studies and approaches were identified narratively. The approaches can be grouped into four: (1) Literature review, (2) Data availability, (3) Systematic method and (4) Expert judgement. The approaches were applied as one strategy either by itself or in combination with others. This review’s emphasis on approaches used in hospital may constrain its conclusions. There might be another strategy or method used to select the input and output for a DEA study in a different area or strategies based on different viewpoints. The trend for DEA application were quite similar to previous studies. There is no evidence that one model fits all DEA model parameters better than another. Based on the reviewed literature, we offer some recommendations and methodological principles for DEA studies.

BACKGROUND Digital contact tracing is a method of tracing contact relying on tracking systems using artificial intelligence (AI) as an epidemic prevention solution for the COVID-19 pandemic. Normally it relies on mobile devices using Bluetooth, Quick Response (QR) code, or Global Positioning System (GPS) technologies OBJECTIVE This review compares the digital contact tracing (DCT) systems that are used in Malaysia, New Zealand and China. METHODS Data sources were from existing electronic articles, newspapers, press releases, government documents, reports, and web pages that are available online RESULTS There are five mobile applications (app) and one Bluetooth device in used by these countries; Malaysia uses MySejahtera app and MyTrace app, New Zealand uses NZ CovidTrace and Bluetooth COVIDCard, China uses a Health Code app that is available in WeChat and Alipay. However, Malaysia has suspended the MyTrace app, while New Zealand is awaiting the government’s decision on more general adoption of the COVIDCard. All apps are available via download through Apple store, Google Play and App Gallery, except for the NZ COVID tracer is not supported by App Gallery that operates Huawei devices. All 3 countries utilises the QR code as the main DCT with additional extra features. However, the number of users could not be determined as certain official platform such as the App Store does not provide such data. But, based on other available databases; MySejahtera has recorded around 74.9% users in Malaysia as at December 2020, NZ CovidTrace logged around 55.1% as at 19th April 2021, and Alipay tracked around 64.3% as at early 2021. CONCLUSIONS Bluetooth component and framework that is added to the NZ COVID Trace could apply to both MySejahtera and Health Code to improve their existing DCT system to assist in identification of close proximity. Conversely, dissimilarities in social, economic, political and cultural aspect could differentiate the outcome of several public health interventions.