BACKGROUND: Data quality in health information systems has a complex structure and consists of several dimensions. This research conducted for identify Common data quality elements for health information systems.
METHODS: A literature review was conducted and search strategies run in Web of Knowledge, Science Direct, Emerald, PubMed, Scopus and Google Scholar search engine as an additional source for tracing references. We found 760 papers, excluded 314 duplicates, 339 on abstract review and 167 on full-text review; leaving 58 papers for critical appraisal.
RESULTS: Current review shown that 14 criteria are categorized as the main dimensions for data quality for health information system include: Accuracy, Consistency, Security, Timeliness, Completeness, Reliability, Accessibility, Objectivity, Relevancy, Understandability, Navigation, Reputation, Efficiency and Value- added. Accuracy, Completeness, and Timeliness, were the three most-used dimensions in literature.
CONCLUSIONS: At present, there is a lack of uniformity and potential applicability in the dimensions employed to evaluate the data quality of health information system. Typically, different approaches (qualitative, quantitative and mixed methods) were utilized to evaluate data quality for health information system in the publications that were reviewed. Consequently, due to the inconsistency in defining dimensions and assessing methods, it became imperative to categorize the dimensions of data quality into a limited set of primary dimensions.

BACKGROUND: Burnout among health care professionals is a significant concern, with detrimental effects on health care service quality and patient outcomes. The use of the electronic health record (EHR) system has been identified as a significant contributor to burnout among health care professionals.
OBJECTIVE: This systematic review and meta-analysis aims to assess the prevalence of burnout among health care professionals associated with the use of the EHR system, thereby providing evidence to improve health information systems and develop strategies to measure and mitigate burnout.
METHODS: We conducted a comprehensive search of the PubMed, Embase, and Web of Science databases for English-language peer-reviewed articles published between January 1, 2009, and December 31, 2022. Two independent reviewers applied inclusion and exclusion criteria, and study quality was assessed using the Joanna Briggs Institute checklist and the Newcastle-Ottawa Scale. Meta-analyses were performed using R (version 4.1.3; R Foundation for Statistical Computing), with EndNote X7 (Clarivate) for reference management.
RESULTS: The review included 32 cross-sectional studies and 5 case-control studies with a total of 66,556 participants, mainly physicians and registered nurses. The pooled prevalence of burnout among health care professionals in cross-sectional studies was 40.4% (95% CI 37.5%-43.2%). Case-control studies indicated a higher likelihood of burnout among health care professionals who spent more time on EHR-related tasks outside work (odds ratio 2.43, 95% CI 2.31-2.57).
CONCLUSIONS: The findings highlight the association between the increased use of the EHR system and burnout among health care professionals. Potential solutions include optimizing EHR systems, implementing automated dictation or note-taking, employing scribes to reduce documentation burden, and leveraging artificial intelligence to enhance EHR system efficiency and reduce the risk of burnout.
BACKGROUND: PROSPERO International Prospective Register of Systematic Reviews CRD42021281173; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021281173.

Data and indicator estimates are considered vital to document persisting challenges in maternal and newborn health and track progress towards global goals. However, prioritization of standardised, comparable quantitative data can preclude the collection of locally relevant information and pose overwhelming burdens in low-resource settings, with negative effects on the provision of quality of care. A growing body of qualitative studies aims to provide a place-based understanding of the complex processes and human experiences behind the generation and use of maternal and neonatal health data. We conducted a qualitative systematic review exploring how national or international requirements to collect and report data on maternal and neonatal health indicators are perceived and experienced at the sub-national and country level in low-income and lower-middle income countries. We systematically searched six electronic databases for qualitative and mixed-methods studies published between January 2000 and March 2023. Following screening of 4084 records by four reviewers, 47 publications were included in the review. Data were analysed thematically and synthesised from a Complex Adaptive Systems (CAS) theoretical perspective. Our findings show maternal and neonatal health data and indicators are not fixed, neutral entities, but rather outcomes of complex processes. Their collection and uptake is influenced by a multitude of system hardware elements (human resources, relevancy and adequacy of tools, infrastructure, and interoperability) and software elements (incentive systems, supervision and feedback, power and social relations, and accountability). When these components are aligned and sufficiently supportive, data and indicators can be used for positive system adaptivity through performance evaluation, prioritization, learning, and advocacy. Yet shortcomings and broken loops between system components can lead to unforeseen emergent behaviors such as blame, fear, and data manipulation. This review highlights the importance of measurement approaches that prioritize local relevance and feasibility, necessitating participatory approaches to define context-specific measurement objectives and strategies.

Health information system deployment has been driven by the transformation and digitalization currently confronting healthcare. The need and potential of these systems within healthcare have been tremendously driven by the global instability that has affected several interrelated sectors. Accordingly, many research studies have reported on the inadequacies of these systems within the healthcare arena, which have distorted their potential and offerings to revolutionize healthcare. Thus, through a comprehensive review of the extant literature, this study presents a critique of the health information system for healthcare to supplement the gap created as a result of the lack of an in-depth outlook of the current health information system from a holistic slant. From the studies, the health information system was ascertained to be crucial and fundament in the drive of information and knowledge management for healthcare. Additionally, it was asserted to have transformed and shaped healthcare from its conception despite its flaws. Moreover, research has envisioned that the appraisal of the current health information system would influence its adoption and solidify its enactment within the global healthcare space, which is highly demanded.

This study aims to review the literature on antecedent factors of information security related to the protection of health information systems (HISs) in the healthcare organization. We classify those factors into organizational and individual aspects. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Academic articles were sourced from five online databases (Scopus, PubMed, IEEE, ScienceDirect, and SAGE) using keywords related to information security, behavior, and healthcare facilities. The search yielded 35 studies, in which the three most frequent individual factors were self-efficacy, perceived severity, and attitudes, while the three most frequent organizational factors were management support, cues to action, and organizational culture. Individual factors for patients and medical students are still understudied, as are the organizational factors of academic healthcare facilities. More individual factors have been found to significantly influence security behavior. Previous studies have been dominated by the security compliance behavior of clinical and non-clinical hospital staff. These research gaps highlight the theoretical implications of this study. This study provides insight for managers of healthcare facilities and governments to consider individual factors in establishing information security policies and programs for improving security behavior.

Ebola Virus Disease (EVD) epidemics have been extensively documented and have received large scientific and public attention since 1976. Until July 2022, 16 countries worldwide had reported at least one case of EVD, resulting in 43 epidemics. Most of the epidemics occurred in the Democratic Republic of Congo (DRC) but the largest epidemic occurred from 2014-2016 in Guinea, Sierra Leone and Liberia in West Africa. The indirect effects of EVD epidemics on these countries\' health systems, i.e., the consequences beyond infected patients and deaths immediately related to EVD, can be significant. The objective of this review was to map and measure the indirect effects of the EVD epidemics on the health systems of DRC, Guinea, Sierra Leone and Liberia and, from thereon, draw lessons for strengthening their resilience vis-à-vis future EVD outbreaks and other similar health emergencies. A scoping review of published articles from the PubMed database and gray literature was conducted. It was supplemented by interviews with experts. Eighty-six articles were included in this review. The results were structured based on WHO\'s six building blocks of a health system. During the EVD outbreaks, several healthcare services and activities were disrupted. A significant decline in indicators of curative care utilization, immunization levels and disease control activities was noticeable. Shortages of health personnel, poor health data management, insufficient funding and shortages of essential drugs characterized the epidemics that occurred in the above-mentioned countries. The public health authorities had virtually lost their leadership in the management of an EVD response. Governance was characterized by the development of a range of new initiatives to ensure adequate response. The results of this review highlight the need for countries to invest in and strengthen their health systems, through the continuous reinforcement of the building blocks, even if there is no imminent risk of an epidemic.

BACKGROUND: In regard to health service planning and delivery, the use of information at different levels in the health system is vital, ranging from the influencing of policy to the programming of action to the ensuring of evidence-informed practices. However, neither ownership of, nor access to, good quality data guarantees actual use of these data. For information to be used, relevant data need to be collected, processed and analysed in an accessible format. This problem of underused data, and indeed the absence of data use entirely, is widespread and has been evident for decades. The DHIS2 software platform supports routine health management for an estimated 2.4 billion people, in over 70 countries worldwide. It is by far the largest and most widespread software for this purpose and adopts a holistic, socio-technical approach to development and implementation. Given this approach, and the rapid and extensive scaling of DHIS2, we questioned whether or not there has been a parallel increase in the scaling of improved information use. To date, there has been no rigorous review of the documentation on how exactly DHIS2 data is routinely being used for decision-making and subsequent programming of action. This scoping review addresses this review gap.
METHODS: The five-stage approach of Arksey and O\'Malley progressed by Levac et al. and Peters was followed. Three databases (PubMed, Web of Science and Embase) were searched, along with relevant conference proceedings and postgraduate theses. In total, over 500 documents were reviewed and data from 19 documents were extracted.
RESULTS: Overall, DHIS2 data are being used but there are few detailed descriptions of this usage in peer reviewed or grey literature. We find that, commonly, there exists a centralised versus decentralised pattern of use in terms of access to data and the reporting of data \'up\' in the system. We also find that the different conceptualisations of data use and how data use is conceptualised are not made explicit.
CONCLUSIONS: We conclude with some suggestions for a way forward, namely: i) the need to document in more detail and share how data are being used, ii) the need to investigate how data were created and who uses such data, iii) the need to design systems based on work practices, and in tandem develop and promote forums in which \'conversations\' around data can take place.

Currently many healthcare systems are supported by an increasing set of Health Information Sys-tems (HISs), which assist the activities for multiple stakeholders. The literature on HISs is, however, fragmented and a solid overview of the current state of HISs is missing. This impedes the understanding and characterization of the required HISs for the healthcare domain.
In this article, we present the results of a Systematic Literature Review (SLR) that identifies the HISs, their domains, stakeholders, features, and obstacles.
In the SLR, we identified 1340 papers from which we selected 136 studies, on which we performed a full-text analysis. After the synthesis of the data, we were able to report on 33 different domains, 41 stakeholders, 73 features, and 69 obstacles. We discussed how these domains, features, and obstacles interact with each other and presented suggestions to overcome the identified obstacles. We recognized five groups of obstacles: technical problems, operational functionality, maintenance & support, usage problems, and quality problems. Obstacles from all groups require to be solved to pave the way for further research and application of HISs.
This study shows that there is a plentitude of HISs with unique features and that there is no consensus on the requirements and types of HISs in the literature.

BACKGROUND: The workload in health care is high; physicians and nurses report high stress levels due to a demanding environment where they often have to perform multiple tasks simultaneously. As a result, mental health issues among health care professionals (HCPs) are on the rise and the prevalence of errors in their daily tasks could increase. Processes of demographic change are partly responsible for even higher stress levels among HCPs. The digitization of patient care is intended to counteract these processes. However, it remains unclear whether these health information systems (HIS) and digital health technologies (DHT) support the HCPs and relieve stress, or if they represent a further burden. The mental construct that describes this burden of technologies is mental workload (MWL). Work in the clinic can be viewed as working in safety-critical environments. Particularly in this sensitive setting, the measurement methods of MWL are relevant, mainly due to their strongly differing levels of intrusiveness and sensitivity. The method of eye tracking could be a useful way to measure MWL directly in the field.
OBJECTIVE: The systematic review aims to address the following questions: (1) In which manner do DHT contribute to the overall MWL of HCPs? (2) Can we observe a direct or indirect effect of DHT on MWL? (3) Which aspects or factors of DHT contribute to an increase in MWL? (4) Which methods/assessments are applied to measure MWL related to HIS/DHT? (5) What role does eye tracking/pupillometry play in the context of measuring MWL? (6) Which outcomes are being assessed via eye tracking?
METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement, we will conduct a systematic review. Based on the research questions, we define keywords that we then combine in search terms. The review follows the following steps: literature search, article selection, data extraction, risk of bias assessment, data analysis, and data synthesis.
RESULTS: We expect results as well as a finalization of the review in the summer of 2021.
CONCLUSIONS: This review will evaluate the impact of DHT on the MWL of HCPs. In addition, assessment methods of MWL in the context of digital technologies will be systematically analyzed.
BACKGROUND: PROSPERO (International Prospective Register of Systematic Reviews) CRD42021233271; https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42021233271.
UNASSIGNED: DERR1-10.2196/29126.

BACKGROUND: The use of routine immunization data by health care professionals in low- and middle-income countries remains an underutilized resource in decision-making. Despite the significant resources invested in developing national health information systems, systematic reviews of the effectiveness of data use interventions are lacking. Applying a realist review methodology, this study synthesized evidence of effective interventions for improving data use in decision-making.
METHODS: We searched PubMed, POPLINE, Centre for Agriculture and Biosciences International Global Health, and African Journals Online for published literature. Grey literature was obtained from conference, implementer, and technical agency websites and requested from implementing organizations. Articles were included if they reported on an intervention designed to improve routine data use or reported outcomes related to data use, and targeted health care professionals as the principal data users. We developed a theory of change a priori for how we expect data use interventions to influence data use. Evidence was then synthesized according to data use intervention type and level of the health system targeted by the intervention.
RESULTS: The searches yielded 549 articles, of which 102 met our inclusion criteria, including 49 from peer-reviewed journals and 53 from grey literature. A total of 66 articles reported on immunization data use interventions and 36 articles reported on data use interventions for other health sectors. We categorized 68 articles as research evidence and 34 articles as promising strategies. We identified ten primary intervention categories, including electronic immunization registries, which were the most reported intervention type (n = 14). Among the research evidence from the immunization sector, 32 articles reported intermediate outcomes related to data quality and availability, data analysis, synthesis, interpretation, and review. Seventeen articles reported data-informed decision-making as an intervention outcome, which could be explained by the lack of consensus around how to define and measure data use.
CONCLUSIONS: Few immunization data use interventions have been rigorously studied or evaluated. The review highlights gaps in the evidence base, which future research and better measures for assessing data use should attempt to address.