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The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

The purpose of this paper is to examine the reliability and validity of the Abbreviated Mental Test (AMT) and the agreement with the Mini-Mental State Examination (MMSE).

This cross-sectional study included 446 older adults who were recruited by cluster sampling from 200,481 adults aged more than 60 years. For each participant, the AMT was administered by village health volunteers and, on a separate day, by a trained professional who also administered the MMSE. Descriptive statistics, Bland and Altman levels of agreement, and Receiver Operator Curves (ROCs) were used to analyze data.

Administration of the AMT by village health volunteers during the annual health screening found cognitive impairment in only 1.12% of the sample. When the AMT was given to these same individuals by trained professionals, the rate of cognitive impairment was almost 24 times greater. Two items in the Thai AMT may require modification due to markedly elevated failure rates. At the cut score of 8, the sensitivity and specificity of the AMT relative to the MMSE were moderate (78.83 and 66.67%, respectively). The degree of agreement between AMT and MMSE was 0.49 (p < 0.001) and the correlation between the difference scores and the mean is exceptionally low (0.048).

Reliable and valid cognitive screening assessment requires the administrator to be well trained and the tools to be appropriate for the population. Although AMT is short and easy for a nonprofessional to administer, some items were not suitable due to construct validity and contextual issues.

This study investigated the impact of economic growth on carbon emissions on selected West African countries between 1980 and 2019. Simon-Steinmann's economic growth model provides the relevant theoretical foundation. The main objective of this study was to ascertain whether economic growth will impact carbon emissions.

The study selected six-sample countries in West Africa and used secondary data obtained through the World Bank Group online database covering the period 1980–2019, employing panel econometric methods of statistical analysis.

The outcome indicates that the independent variable showed a positively significant impact on the dependent variable for the pooled samples in the short-run, with significant cointegration.

The study concluded that economic growth significantly impacts the emissions of carbon, and a 1% rise in economic growth will result to 3.11121% unit rise in carbon emissions.

Policy implementation should encourage the use of energy efficient facilities by firms and government and the establishment of carbon trading hubs.

Failure by governments to heed the recommendations of this research will result to serious climate change issues on economic activities with attendant consequences on human health within the region and globally.

This is one of the comprehensive works on subject covering the West African region within the continent.

The purpose of this paper is to examine the effect of support price on wheat production in Pakistan during the period 1971–2016.

To capture the effect of support price on wheat production, the authors estimated the long-run linkage by using the ARDL bounds testing approach to cointegration.

This study confirmed the presence of a positive and long-term effect of area under cultivation, support price and fertilizer consumption on wheat production through ARDL bounds test. The results showed that both in the long run and short run, support price plays an important role in the enhancement of wheat production. The authors also found that the coefficients of the area under cultivation and fertilizer consumption variables were statistically significant and positive both in the long run and short run.

The use of the ARDL approach that examines the long-run and short-run effects of support price on wheat production in Pakistan makes the current study unique. An emerging economic literature suggests that only limited research has been conducted in this area.

The aims of the paper are to investigate IT software and service export function for India. First, cointegration tests have been used to investigate the long-run equilibrium relationship of the given variables. Second, long-run coefficients and associated error correction mechanism are estimated.

Annual time series data on IT software and service exports, human capital, exchange rate, investment in IT, external demand and openness index have been used for the present study during the period 1980–2017. The data are collected from the National Association of Software and Service Companies (NASSCOM), Planning Commission of India, University Grants Commission (UGC) of India, real effective exchange rate (REER) database and World Bank development indicators. Auto regressive distributed lag (ARDL) model is used to analyze both short-run and long-run dynamic behaviour of economic variables with appropriate asymptotic inferences.

Results of the analysis show the stable long-run equilibrium relationship among the given variables. It is found that external demand, exchange rate, human capital and openness index have a substantial long-run impact on the IT software and service exports. We also found that the coefficient of error correction term is negative and significant at 1% of the level of significance, which confirms the existence of stable long-run relationship which means adjustment will take place when there is a short-run deviation to its long-run equilibrium after a shock.

There may be other determinants of software and service exports apart from those considered by the present study. Due to the non-availability of data, the study considers only important determinants that determine the software and service exports in India. The IT exports are an emerging and dynamic field of economic activity and the rate of change is so rapid that the relevance of individual factors may change over time. The study period is also limited to available data.

The paper has implications for achieving sustainability in IT software and service exports growth. It is recommended that policies directed at improving the performance of IT software and service exports should largely consider the long-run behaviour of these variables.

This paper focuses on originality in the analysis of the relationship among the given variables including IT software and service exports, human capital, exchange rate, investment in IT, external demand and openness index in India. All the work has been done in original by the authors, and the work used has been acknowledged properly.

This study aims to examine the influence of internal and external factors on the credit risk (represented by nonperforming financing [NPF]) of Indonesian Sharīʿah rural banks (SRBs) – a type of Islamic bank that provides Islamic financial services especially to small and medium businesses in Indonesia. Internal variables comprise capital adequacy ratio (CAR), financing to deposit ratio (FDR), return on assets (ROA), operating expense ratio (OER), financing to value (FTV) and profit and loss sharing (PLS) financing ratio. External variables comprise inflation, economic growth and interest rate.

The study uses the annual reports of SRBs in Indonesia as secondary data for the years 2010–2019. Auto regressive distributed lag (ARDL) is used as the analysis method to examine the short-run and long-run relationships between the variables.

The findings indicate that four variables experienced a lag in the short run, namely, NPF, inflation, CAR and PLS, with different results recorded for each of the variables. Furthermore, the long-run results show that CAR and ROA influence the NPF of SRBs positively, whereas inflation and PLS have a negative influence on NPF. The rest of the variables – notably economic growth, interest rate, FDR, FTV and OER – do not have an influence on NPF in SRBs.

The level of NPF in SRBs exceeds the provision of the Central Bank of Indonesia. The findings are expected to have implications for SRBs and the regulator to consider and to manage the factors related to NPF properly due to the important role of SRBs in small and medium businesses’ development.

This study measures the determinants of NPF using internal and external variables, including the addition of a dummy variable, notably FTV. This study also uses ARDL to analyze the financial policies involving data at the present time and lagged time.

Malaysia is one of the fastest-growing Asian economies with a properly designed and developed Islamic financial system. This unique feature of the Malaysian economy made it an important case study, and the purpose of this study is to assess for the dynamic contribution of Islamic finance to the growth of the real economy.

The study uses a quarterly data set of 20 years analysed via the autoregressive distributive lag bounds test approach to cointegration.

The results in the short-run show a non-significant relationship between Islamic banking indices and the real economy. However, in the long-run, financing and deposits of Islamic banks are favourable and contribute significantly to the growth of the Malaysian economy. There was an accumulation of meaningful and wide-ranging investment over the period of the study and productivity of capital was also extra-efficient. The direction of causality is found to be bidirectional between Islamic banking deposits and Malaysian gross domestic product (GDP), but there is a weak causal effect from Islamic banking financing to GDP.

Malaysia has a dual financial system (conventional and Islamic) and both can affect its real economy. This research is limited to Islamic banking’s effects on Malaysian economic growth. The research also limits the scope and coverage for 20 years, from 1998 to 2017 to cover the years for which data is available for all the variables used in the study.

The results confirm that the Islamic banking sector in Malaysia is performing well in carrying out its major function of financial intermediation, which is the pooling and channelling of funds to productive investment activities. Consequently, the fact that Malaysia excels in Islamic finance is not a fluke. It is because of the effective performance of Islamic financial institutions in the country. Furthermore, Malaysian authorities are doing their level best in promoting Islamic financial activities.

The study fulfills the need to uncover the relationship between the Islamic financial system and the real economy in Malaysia. It differs from other studies as it uses the most recent available data, introduces new variables and identifies the channel by which Islamic banking development transmits growth.

This study aims to examine the short- and long-term equilibrium relationship between All share price index (ASPI), macroeconomic variables and the economic crisis in Sri Lanka.

Monthly time series data for inflation (CPI), industrial production (IP), an exchange rate (EX), an interest rate (TB), short-term interest rate (CD) and economic crisis were used from 2010 to 2021. The ADF test, the bound testing approach, the CUSUM test and the CUSUMQ test were used in this study.

The findings show a long-run stable relationship between stock price, macroeconomic variables and political crisis (i.e., CPI, IP, ER, TB, CD and economic crisis). The results of the Johansen cointegration test suggest that there is at least one cointegrating equation, indicating that there is a long-run equilibrium relationship between macroeconomic variables and stock prices in Sri Lanka.

The vector error correction estimates show that the coefficient of the error correction term is significant with a negative sign, indicating that a long-run dynamic relationship exists between macroeconomic variables and stock prices. In the short term, economic crisis has had a big effect on stock prices suggesting that Sri Lanka’s domestic financial markets are linked to the stability of the country.

This research establishes the links between stock returns, macroeconomic variables and economic crisis. So far, research has been unable to establish the empirical nature of such links. The authors believe that this paper fills that gap.

The purpose of this study is to examine whether external debt procurements during the military and civilian regimes had a correlation with infrastructural developments using available data from Nigeria.

The sample period covering 41 years, was divided into two periods representing the military and civilian regimes with respective secondary data secured from the World Bank Group online database. The study employed robust least square regression, autoregressive distributed lag and the error correction term to test the variables at the 0.05 significance level.

The results affirmed that external debts shows positive and significant relationship with infrastructural developments proxy for capital investments during the short-run for both military and civilian regimes in Nigeria, while the outcome was only significant and negatively signed for the civilian regime in the long-run with 52.28% speed of convergence to long-run. This study concludes that external debt showed significant correlation with infrastructural development during the civilian regime better than the military regime in Nigeria and this conclusion applies globally.

Research period covered only 41 years, between 1979 and 2020 and focused on sub-Saharan African country – Nigeria.

The research encourages civilian administration in governments and urged them to carefully appraise and contract external debts to finance self-liquidating priority projects.

The national economy and the masses suffer during military regime but are better off during civilian regime.

Apart from adding to current literature, the work focused on a coverage period that comprehensively compares two different regimes of government – military and civilian administrations.