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Electronic Health Records (EHRs) and other Health Information Technologies (HITs) pose significant challenges for clinicians, administrators and managers in the field of primary care. While there is an abundance of literature on the challenges of HIT systems in primary care, there are also practices where HITs are well-integrated and useful for care delivery. This study aims to (1) understand how exemplary primary care practices conceptualized data and HIT system use in their care delivery and (2) describe components that support and promote data and HIT system use in care delivery.

This paper is a sub-analysis of a larger qualitative data set on exemplary primary care in which data was collected using in-depth interviews, observations, field notes and primary source documents from week-long site visits at each organization. Using a combination of qualitative analysis methods including elements of thematic analysis, discourse analysis, and qualitative comparison analysis, we examined HIT-related data across six exemplary primary care organizations.

Three key components were identified that underlie engagement with data and HIT systems: data audience identification, defined data purpose and structures for participation in both data design and maintenance.

Within the context of primary care, these findings have implications for effective integration of HIT systems into primary care delivery.

Using a meta-regression analysis, we quantitatively review the empirical literature on the relation between effective tax rate (ETR) and firm size. Accounting literature offers two competing theories on this relation: The political cost theory, suggesting a positive size-ETR relation, and the political power theory, suggesting a negative size-ETR relation. Using a unique data set of 56 studies that do not show a clear tendency towards either of the two theories, we contribute to the discussion on the size-ETR relation in three ways: First, applying meta-regression analysis on a US meta-data set, we provide evidence supporting the political cost theory. Second, our analysis reveals factors that are possible sources of variation and bias in previous empirical studies; these findings can improve future empirical and analytical models. Third, we extend our analysis to a cross-country meta-data set; this extension enables us to investigate explanations for the two competing theories in more detail. We find that Hofstede’s cultural dimensions theory, a transparency index and a corruption index explain variation in the size-ETR relation. Independent of the two theories, we also find that tax planning aspects potentially affect the size-ETR relation. To our knowledge, these explanations have not yet been investigated in our research context.

Process mining is a research area used to discover, monitor and improve real business processes by extracting knowledge from event logs available in process-aware information systems. The purpose of this paper is to evaluate the application of artificial neural networks (ANNs) and support vector machines (SVMs) in data mining tasks in the process mining context. The goal was to understand how these computational intelligence techniques are currently being applied in process mining.

The authors conducted a systematic literature review with three research questions formulated to evaluate the use of ANNs and SVMs in process mining.

The authors identified 11 papers as primary studies according to the criteria established in the review protocol. Most of them deal with process mining enhancement, mainly using ANNs. Regarding the data mining task, the authors identified three types of tasks used: categorical prediction (or classification); numeric prediction, considering the “regression” type, and clustering analysis.

Although there is scientific interest in process mining, little attention has been specifically given to ANNs and SVM. This scenario does not reflect the general context of data mining, where these two techniques are widely used. This low use may be possibly due to a relative lack of knowledge about their potential for this type of problem, which the authors seek to reverse with the completion of this study.

This paper aims to examine the existence of a transparency gap between voluntary external sustainability reporting and internal sustainability performance of an organisation arising from the operationalisation of transparency as an instrumental tool.

This study combined an analysis of a firm’s sustainability report (secondary data) with a qualitative case study data (primary data comprising interviews, meetings and internal documents) to understand how the Global Reporting Initiative (GRI) sustainability reporting guidelines are applied in practice.

By comparing what is reported with a range of primary case study data, this study finds evidence of transparency gaps, particularly in terms of the quality of measurement of sustainability performance, the materiality of issues covered and the completeness of the report. This study posits that voluntary disclosures following the GRI guidelines (transparency technique) shape the external expression of acceptable corporate behaviour (transparency norm) that is nevertheless at odds with actual behaviour or performance.

The findings indicate the importance of mandatory sustainability reporting requirements that facilitate accountability to all key stakeholders and that are externally assured and enforced. Such requirements might take the form of standards that put boundaries on judgement and address material sustainable development impacts and that are accompanied by implementation guidance. Non-financial assurance practices must be developed to cover adherence to reporting principles and processes.

Transparency gaps that result from voluntary disclosure guidelines or standards being used to imply a transparency norm may undermine accountability for the impacts of the organisation and hinder alignment of business models and corporate strategies with sustainable development.

The paper contributes to a theoretical understanding of transparency as a form of self-regulation and has implications for the further development of sustainability reporting standards.

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.

Devolution of fiscal and administrative autonomy to public schools is a global phenomenon now. Various models of school autonomy have been adopted both in developing and developed countries. The purpose of this paper is to explore the impact of devolution of fiscal autonomy to public primary schools through Parent–Teacher Councils (PTCs) on retention of primary school children in the Khyber Pakhtunkhwa (KP) province, Pakistan.

Two sources of data were used to analyze the research question: Education Management Information System for the years 2006–2011 and 2007–2012, and a specially designed survey questionnaire used to compile information about PTCs from 222 public primary schools in the KP Province. Multiple linear regressions were conducted to examine whether PTC reforms are related to retention rates. An education production function approach was used to examine the effect of “inputs” (PTC reform) on “outputs” (retention).

The regression results indicate that reforms in procedural mechanisms to spend PTC budget and schools with separate classrooms for each grade level are significant in improving retention to the last grade of primary. The results also indicate that retention in all-girls’ schools tend to be significantly lower compared to all-boys’ schools.

First, the integration of data sets resulted in a small sample size, 361 schools, out of which the researcher could visit only 222 schools (10 schools per district) due to time and financial constraints. There may be a probability that with a larger sample size the author findings may look slightly different. However, this is the only current data set collected by the researcher in KP, Pakistan. Second, an ideal way of calculating retention is to track each and every child enrolled in a school over a period of five years and to calculate retention at the end of Grade 5 called true cohort model. However, due to unavailability of such kind of data, a more commonly used method, called reconstructed cohort method, is employed. In this method, data on enrollment by grade are used for six consecutive years, with an assumption that the student flow rates will remain unchanged over time and across grades.

The findings of this study provide vital policy input to the Government of Pakistan in particular and other developing countries in general. The study reveals that PTCs have critical impacts on educational outcomes, school productivity and return on public sector educational investment thus providing an impetus for further strengthening of PTC and community participation. Besides, this study offers significant implications as to how school-based management programs will lead to outcomes under resource scarcity in developing countries.

The paper has implications for the role of school leadership and community participation and for how to engender community involvement in marginalized areas where communities often do not have the time, resources or confidence to participate in their schools. Besides, community participation in parent–teacher meetings means that the school budget is spent transparently and with consensus. Hence, the chances of misuse of funds are minimized to a considerable extent, a dilemma faced by many developing countries. Finally, the collection of PTC-related data regularly especially details about budget allocated, spent and, the unutilized budget may result in better record keeping, which was found lacking during the visit.

The uniqueness and originality of this paper can be gauged from the fact that no systematic study exists with regards to the impact of school autonomy on students’ retention to the last grade of primary in KP province – a poor and conflict-ridden region in a low-income country (Pakistan). Also, the data collection from primary and secondary sources was not an easy task. However, the researcher as a civil servant has to use personal contacts to collect primary and secondary data. Hence, this study is unique and first of its kind in nature. No such research has been conducted so far by any researcher, especially in KP.

The Ethiopian educational system has witnessed considerable structural and curricular changes aimed to address access, equity and relevance. At the same time, there are serious concerns about educational quality as a consequence of these changes. Data use can be an important approach for changing the planning, execution, monitoring and evaluation of activities having the purpose of improving teaching and learning. The purpose of this paper is, therefore, to investigate data use in primary education in Ethiopia.

Using a mixed methods approach, surveys and semi-structured interviews were conducted to collect data from a cluster random sample of eight primary schools representing four different levels of effectiveness in implementing a mandated school improvement program in Ethiopia.

The availability of wider ranges of input, process, outcome and context data per se does not ensure actual use. A complex combination of data, user and organizational factors influences data use in schools, with organizational factors appearing to be most influential. Unrealistic accountability pressures and lack of targeted supervision support seemed to cause unintended data use, such as abuse of data.

Schools need more systematic professional development in data use, with explicit attention to school leadership. Moreover, it is important to make educational inspection processes more responsive to the demands of the school improvement process by adding aspects of the school improvement tradition, such as data-based decision making.

This study contributes to understanding of the nature, characteristics and processes of data use in a developing country context, in which competing accountability mandates often shape policy and practice.