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The purpose of this paper is to discuss a systematic review on waste identification related to health information systems (HIS) in Lean transformation.

A systematic review was conducted on 19 studies to evaluate Lean transformation and tools used to remove waste related to HIS in clinical settings.

Ten waste categories were identified, along with their relationships and applications of Lean tool types related to HIS. Different Lean tools were used at the early and final stages of Lean transformation; the tool selection depended on the waste characteristic. Nine studies reported a positive impact from Lean transformation in improving daily work processes. The selection of Lean tools should be made based on the timing, purpose and characteristics of waste to be removed.

Overview of waste and its category within HIS and its analysis from socio-technical perspectives enabled the identification of its root cause in a holistic and rigorous manner.

Understanding waste types, their root cause and review of Lean tools could subsequently lead to the identification of mitigation approach to prevent future error occurrence.

Specific waste models for HIS settings are yet to be developed. Hence, the identification of the waste categories could guide future implementation of Lean transformations in HIS settings.

The purpose of this paper is to present a review of health information system (HIS)-induced errors and its management. This paper concludes that the occurrence of errors is inevitable but it can be minimised with preventive measures. The review of classifications can be used to evaluate medical errors related to HISs using a socio-technical approach. The evaluation could provide an understanding of errors as a learning process in managing medical errors.

A literature review was performed on issues, sources, management and approaches to HISs-induced errors. A critical review of selected models was performed in order to identify medical error dimensions and elements based on human, process, technology and organisation factors.

Various error classifications have resulted in the difficulty to understand the overall error incidents. Most classifications are based on clinical processes and settings. Medical errors are attributed to human, process, technology and organisation factors that influenced and need to be aligned with each other. Although most medical errors are caused by humans, they also originate from other latent factors such as poor system design and training. Existing evaluation models emphasise different aspects of medical errors and could be combined into a comprehensive evaluation model.

Overview of the issues and discourses in HIS-induced errors could divulge its complexity and enable its causal analysis.

This paper helps in understanding various types of HIS-induced errors and promising prevention and management approaches that call for further studies and improvement leading to good practices that help prevent medical errors.

Classification of HIS-induced errors and its management, which incorporates a socio-technical and multi-disciplinary approach, could guide researchers and practitioners to conduct a holistic and systematic evaluation.

The purpose of this paper is to assess National Medical Care Survey data quality.

Data completeness and representativeness were computed for all observations while other data quality measures were assessed using a 10 per cent sample from the National Medical Care Survey database; i.e., 12,569 primary care records from 189 public and private practices were included in the analysis.

Data field completion ranged from 69 to 100 per cent. Error rates for data transfer from paper to web-based application varied between 0.5 and 6.1 per cent. Error rates arising from diagnosis and clinical process coding were higher than medication coding. Data fields that involved free text entry were more prone to errors than those involving selection from menus. The authors found that completeness, accuracy, coding reliability and representativeness were generally good, while data timeliness needs to be improved.

Only data entered into a web-based application were examined. Data omissions and errors in the original questionnaires were not covered.

Results from this study provided informative and practicable approaches to improve primary health care data completeness and accuracy especially in developing nations where resources are limited.

Primary care data quality studies in developing nations are limited. Understanding errors and missing data enables researchers and health service administrators to prevent quality-related problems in primary care data.

The aim of this study is to offer evidence-based knowledge of the most popular research topics in studies on spiritual leadership (SL) and the research approaches and theories in use. Another aim is to create a comprehensive research framework covering the antecedents and outcomes of SL, as well as the underlying mechanisms and conditional factors. This study also synthesizes future research avenues presented in the literature.

This study used a systematic literature review method. The presented analysis covered both bibliometric studies and in-depth manual content analysis. In total, 274 articles indexed in the Scopus database were analyzed, with a particular focus on 126 empirical papers.

This study shows that most of the research took place in developing countries and focused on the links between SL and workplace spirituality, employee well-being and engagement. It provides a complex research framework which orders previous variables according to their levels. Future research is required that would use a multilevel research approach and determine the impact of SL on society and the leaders themselves, as well as determining the reverse impact of organizational performance on the development of SL.

This study takes advantages of both bibliometric and in-depth content analysis to expand the understanding of the state of the art in SL research. It demonstrates how different factors contribute to SL and how they subsequently influence outcomes. It also offers numerous future research directions which go beyond those identified so far in the literature to further develop the theory of SL.