Analysis of the quality of hospital information systems Audit Trails.

BACKGROUND: Audit Trails (AT) are fundamental to information security in order to guarantee access traceability but can also be used to improve Health information System's (HIS) quality namely to assess how they are used or misused. This paper aims at analysing the existence and quality of AT, describing scenarios in hospitals and making some recommendations to improve the quality of information. METHODS: The responsibles of HIS for eight Portuguese hospitals were contacted in order to arrange an interview about the importance of AT and to collect audit trail data from their HIS. Five institutions agreed to participate in this study; four of them accepted to be interviewed, and four sent AT data. The interviews were performed in 2011 and audit trail data sent in 2011 and 2012. Each AT was evaluated and compared in relation to data quality standards, namely for completeness, comprehensibility, traceability among others. Only one of the AT had enough information for us to apply a consistency evaluation by modelling user behaviour. RESULTS: The interviewees in these hospitals only knew a few AT (average of 1 AT per hospital in an estimate of 21 existing HIS), although they all recognize some advantages of analysing AT. Four hospitals sent a total of 7 AT - 2 from Radiology Information System (RIS), 2 from Picture Archiving and Communication System (PACS), 3 from Patient Records. Three of the AT were understandable and three of the AT were complete. The AT from the patient records are better structured and more complete than the RIS/PACS. CONCLUSIONS: Existing AT do not have enough quality to guarantee traceability or be used in HIS improvement. Its quality reflects the importance given to them by the CIO of healthcare institutions. Existing standards (e.g. ASTM:E2147, ISO/TS 18308:2004, ISO/IEC 27001:2006) are still not broadly used in Portugal.publishersversionpublishe

First Steps Towards Process Mining in Distributed Health Information Systems

Business Intelligence approaches such as process mining can be applied to the healthcare domain in order to gain insight into the complex processes taking place. Disclosing as-is processes helps identify room for improvement and answers questions from medical professionals. Existing approaches are based on proprietary log data as input for mining algorithms. Integrating  the  Healthcare  Enterprise (IHE) defines in its Audit  Trail  and  Node Authentication (ATNA) profile how real-world events must be recorded. Since IHE is used by many healthcare providers throughout the world, an extensive amount of log data is produced. In our research we investigate if audit trails, generated from an IHE test system, carry enough content to successfully apply process mining techniques. Furthermore we assess the quality of the recorded events in accordance with the maturity level scoring system. A simplified simulation of the organizational workflow in a radiological practice is presented. Based on this simulation a process miing task is conducted

a review

Introduction: eHealth and mHealth are technologies that allow services to be extended closer to patients, in pursuit of the objectives of Health 2020: a European policy framework and strategy for the 21st century and of the Global Strategy on Human Resources for Health: workforce 2030. As Europe faces increased demand for health services due to ageing populations, rising patient mobility, and a diminishing supply of health workers caused by retirement rates that surpass recruitment rates, this paper illustrates how eHealth and mHealth can improve the delivery of services by the health workforce in response to increasing demands. Methods: Through a scoping literature review, the impact of eHealth/mHealth on the health workforce was assessed by examining how these technologies affect four dimensions of the performance of health professionals, according to the so-called AAAQ: availability, accessibility, acceptability, and quality. Results: Few high-quality studies were found. Most studies focused on the utilization of text messaging (SMS) for patient behavior change, and some examined the potential of mhealth to strengthen health systems. We also found some limited literature reporting effects on clinical effectiveness, costs, and patient acceptability; we found none reporting on equity and safety issues. Facilitators and barriers to the optimal utilization of eHealth and mHealth were identified and categorized as they relate to individuals, professional groups, provider organizations, and the institutional environment. Discussion: There are ongoing clinical trial protocols of largescale, multidimensional mHealth interventions, suggesting that the current limited evidence base will expand in coming years. The requirement for new digital skills for human resources for health (HRH) was observed as significant. This has implications for the education of health workers, the management of health services, policy-making, and research.publishersversionpublishe

Digital service innovation enabled by the blockchain use in healthcare: the case of the allergic patients ledger

International audienceBy combining the institutional approach and the rational model of digital innovation, there is increasingly a great interest in the implementation of blockchain solutions in healthcare but, until then concrete evidence for this type of project is missing. At the same time the healthcare sector, allergology in particular seems to face security (confidentiality, availability and integrity) issues and information audit trail weaknesses. For these reasons, our study focuses on the co-construction of a distributed ledger for patients allergies with healthcare professionals. The aim is to design and implement a reliable tool to deal with the availability , integrity and confidentiality of information about new allergies and distinguish between validated allergies and declarative allergies for the purpose of mitigating negative effects of unavailability of reliable information about patients allergies. This article defers the first step of our methodological cycle by explaining how collaboration is organized between Pikcio (blockchain technology provider) and allergists. As a result, we have first versions of some deliverables such as formal specifications, risk matrix document and a UML design (class diagram, use case diagram and sequence diagram) as the research project is iterative

Data completeness in healthcare: A literature survey.

As the adoption of eHealth has made it easier to access and aggregate healthcare data, there has been growing application for clinical decisions, health services planning, and public health monitoring with daily collected data in clinical care. Reliable data quality is a precursor of the aforementioned tasks. There is a body of research on data quality in healthcare, however, a clear picture of data completeness in this field is missing. This research aims to identify and classify current research themes related to data completeness in healthcare. In addition, the paper presents problems with data completeness in the reviewed literature and identifies methods that have been adopted to address those problems. This study has reviewed 24 papers (January 2011–April 2016) published in information and computing sciences, biomedical engineering, and medicine and health sciences journals. The paper uncovers three main research themes, including design and development, evaluation, and determinants. In conclusion, this paper improves our understanding of the current state of the art of data completeness in healthcare records and indicates future research directions.N

A Delphi Study Analysis of Best Practices for Data Quality and Management in Healthcare Information Systems

Healthcare in the US continues to suffer from the poor data quality practices processes that would ensure accuracy of patient health care records and information. A lack of current scholarly research on best practices in data quality and records management has failed to identify potential flaws within the relatively new electronic health records environment that affect not only patient safety but also cost, reimbursements, services, and most importantly, patient safety. The focus of this study was to current best practices using a panel of 25 health care industry data quality experts. The conceptual lens was developed from the International Monetary Fund\u27s Data Quality Management model. The key research question asked how practices contribute to identifying improvements healthcare data, data quality, and integrity. The study consisted of 3 Delphi rounds. Each round was analyzed to identify consensus on proposed data quality strategies from previous rounds that met or exceeded the acceptance threshold to construct subsequent round questions. The 2 best practices identified to improve data collection were user training and clear processes. One significant and unanticipated finding was that the previous gold standard practices have become outdated with technological advances, leading to a higher potential for flawed or inaccurate patient healthcare data. There is an urgent need for health care leaders to maintain heightened awareness of the need to continually evaluate data collection and management policies, particularly as technology advances such as artificial intelligence matures. Developing national standards to address accurate and timely management of patient care data is critical for appropriate health care delivery decisions by health care providers

Methods to Facilitate the Capture, Use, and Reuse of Structured and Unstructured Clinical Data.

Electronic health records (EHRs) have great potential to improve quality of care and to support clinical and translational research. While EHRs are being increasingly implemented in U.S. hospitals and clinics, their anticipated benefits have been largely unachieved or underachieved. Among many factors, tedious documentation requirements and the lack of effective information retrieval tools to access and reuse data are two key reasons accounting for this deficiency. In this dissertation, I describe my research on developing novel methods to facilitate the capture, use, and reuse of both structured and unstructured clinical data. Specifically, I develop a framework to investigate potential issues in this research topic, with a focus on three significant challenges. The first challenge is structured data entry (SDE), which can be facilitated by four effective strategies based on my systematic review. I further propose a multi-strategy model to guide the development of future SDE applications. In the follow-up study, I focus on workflow integration and evaluate the feasibility of using EHR audit trail logs for clinical workflow analysis. The second challenge is the use of clinical narratives, which can be supported by my innovative information retrieval (IR) technique called “semantically-based query recommendation (SBQR)”. My user experiment shows that SBQR can help improve the perceived performance of a medical IR system, and may work better on search tasks with average difficulty. The third challenge involves reusing EHR data as a reference standard to benchmark the quality of other health-related information. My study assesses the readability of trial descriptions on ClinicalTrials.gov and found that trial descriptions are very hard to read, even harder than clinical notes. My dissertation has several contributions. First, it conducts pioneer studies with innovative methods to improve the capture, use, and reuse of clinical data. Second, my dissertation provides successful examples for investigators who would like to conduct interdisciplinary research in the field of health informatics. Third, the framework of my research can be a great tool to generate future research agenda in clinical documentation and EHRs. I will continue exploring innovative and effective methods to maximize the value of EHRs.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135845/1/tzuyu_1.pd