Johan Gustav Bellika

Propagation of program control: A tool for distributed disease surveillance

Abstract Purpose The purpose of the study was (1) to identify the requirements for syndromic, disease surveillance and epidemiology systems arising from events such as the SARS outbreak in March 2003, and the deliberate spread of Bacillus anthracis, or anthrax, in the US in 2001; and (2) to use these specifications as input to the construction of a system intended to meet these requirements. An important goal was to provide information about the diffusion of a communicable disease without being dependent on centralised storage of information about individual patients or revealing patient-identifiable information. Methods The method applied is rooted in the engineering paradigm involving phases of analysis, system specification, design, implementation, and testing. The requirements were established from earlier projects’ conclusions and analysis of disease outbreaks. The requirements were validated by a literature study of syndromic and disease surveillance systems. The system was tested on simulated EHR databases generated from microbiology laboratory data. Results A requirements list that a syndromic and disease surveillance system should meet, and an open source system, “The Snow Agent system”, has been developed. The Snow Agent system is a distributed system for monitoring the status of a populations health by distributing processes to, and extracting epidemiological data directly from, the electronic health records (EHR) system in a geographic area. Conclusions Syndromic and disease surveillance tools should be able to operate at all levels in the health systems and across national borders. Such systems should avoid transferring patient identifiable data, support two-way communications and be able to define and incorporate new and unknown diseases and syndrome definitions that should be reported by the system. The initial tests of the Snow Agent system shows that it will easily scale to national level in Norway.

Surgical Telementoring in Knowledge Translation—Clinical Outcomes and Educational Benefits A Comprehensive Review

Background. Surgical telementoring has been reported for decades. However, there exists limited evidence of clinical outcome and educational benefits. Objective. To perform a comprehensive review of surgical telementoring surveys published in the past 2 decades. Results. Of 624 primary identified articles, 34 articles were reviewed. A total of 433 surgical procedures were performed by 180 surgeons. Most common telementored procedures were laparoscopic cholecystectomy (57 cases, 13%), endovascular treatment of aortic aneurysm (48 cases, 11%), laparoscopic colectomy (32 cases, 7%), and nefrectomies (41 cases, 9%). In all, 167 (38%) cases had a laparoscopic approach, and 8 cases (5%) were converted to open surgery. Overall, 20 complications (5%) were reported (liver bleeding, trocar port bleeding, bile collection, postoperative ileus, wound infection, serosa tears, iliac artery rupture, conversion open surgery). Eight surveys (23%) have structured assessment of educational outcomes. Telementoring was combined with simulators (n = 2) and robotics (n = 3). Twelve surveys (35%) were intercontinental. Technology satisfaction was high among 83% of surgeons. Conclusion. Few surveys have a structured assessment of educational outcome. Telementoring has improved impact on surgical education. Reported complication rate was 5%.

Properties of a federated epidemiology query system

PURPOSE The purpose of the study was to establish knowledge about how online access to epidemiological data from general practitioners (GPs) electronic health record (EHR) system should be provided. Before such systems are developed and deployed a decision about the appropriate system architecture must be made. Such a decision should ideally be based on knowledge about the properties of different system architectures. This choice is important because the system architecture may affect the willingness of GPs to participate in providing epidemiological data from their EHR system. METHOD Verifying the performance and properties of an architectural approach by implementing and deploying a system on a trans-institutional level and performing evaluations studies is a very resource demanding method to establish a foundation for the decision of appropriate system architecture. Instead, we have tried to create this foundation by constructing a prototype system, establish knowledge about the properties of the system using experiments, and finally compare the properties of the federated approach to the properties of the centralised approach. By using this methodological approach we provide the best available knowledge, on this stage, for the appropriate system architecture to use for providing access to epidemiological data from the local population. RESULTS Our experimental results show that it is possible to improve the timeliness and the temporal and spatial resolution of epidemiological data, compared to traditional centralised disease surveillance systems. Up-to-date epidemiological data from the local population may be provided directly from the source EHR system within 4s. The responsiveness of the system is minimally affected (0.1s) as the number of participating data providers grows from 1 to 49 data providers. The comparison of the federated approach to the centralised approach indicates that federated approaches avoid the privacy issues involved, as intended; it offers better scalability when computing speed is compared, and it provides better specificity because more data about the patient may be used. CONCLUSION The conclusion from our study is that the federated approach to providing epidemiological data about the local population has many benefits over the traditional centralised approach. A federated approach to an epidemiology system may raise the GPs awareness of local disease outbreak because it is possible to share information about incidence rates of communicable diseases and use of laboratory requests in a geographical area that predates laboratory-based disease surveillance. The effects of the federated approach could be improved data quality in the EHR systems and improved representativeness of the epidemiological data for the areas covered by such systems.

Standards for reporting randomized controlled trials in medical informatics: a systematic review of CONSORT adherence in RCTs on clinical decision support

Introduction The Consolidated Standards for Reporting Trials (CONSORT) were published to standardize reporting and improve the quality of clinical trials. The objective of this study is to assess CONSORT adherence in randomized clinical trials (RCT) of disease specific clinical decision support (CDS). Methods A systematic search was conducted of the Medline, EMBASE, and Cochrane databases. RCTs on CDS were assessed against CONSORT guidelines and the Jadad score. Result 32 of 3784 papers identified in the primary search were included in the final review. 181 702 patients and 7315 physicians participated in the selected trials. Most trials were performed in primary care (22), including 897 general practitioner offices. RCTs assessing CDS for asthma (4), diabetes (4), and hyperlipidemia (3) were the most common. Thirteen CDS systems (40%) were implemented in electronic medical records, and 14 (43%) provided automatic alerts. CONSORT and Jadad scores were generally low; the mean CONSORT score was 30.75 (95% CI 27.0 to 34.5), median score 32, range 21–38. Fourteen trials (43%) did not clearly define the study objective, and 11 studies (34%) did not include a sample size calculation. Outcome measures were adequately identified and defined in 23 (71%) trials; adverse events or side effects were not reported in 20 trials (62%). Thirteen trials (40%) were of superior quality according to the Jadad score (≥3 points). Six trials (18%) reported on long-term implementation of CDS. Conclusion The overall quality of reporting RCTs was low. There is a need to develop standards for reporting RCTs in medical informatics.

Archetype-based data warehouse environment to enable the reuse of electronic health record data

BACKGROUND The reuse of data captured during health care delivery is essential to satisfy the demands of clinical research and clinical decision support systems. A main barrier for the reuse is the existence of legacy formats of data and the high granularity of it when stored in an electronic health record (EHR) system. Thus, we need mechanisms to standardize, aggregate, and query data concealed in the EHRs, to allow their reuse whenever they are needed. OBJECTIVE To create a data warehouse infrastructure using archetype-based technologies, standards and query languages to enable the interoperability needed for data reuse. MATERIALS AND METHODS The work presented makes use of best of breed archetype-based data transformation and storage technologies to create a workflow for the modeling, extraction, transformation and load of EHR proprietary data into standardized data repositories. We converted legacy data and performed patient-centered aggregations via archetype-based transformations. Later, specific purpose aggregations were performed at a query level for particular use cases. RESULTS Laboratory test results of a population of 230,000 patients belonging to Troms and Finnmark counties in Norway requested between January 2013 and November 2014 have been standardized. Test records normalization has been performed by defining transformation and aggregation functions between the laboratory records and an archetype. These mappings were used to automatically generate open EHR compliant data. These data were loaded into an archetype-based data warehouse. Once loaded, we defined indicators linked to the data in the warehouse to monitor test activity of Salmonella and Pertussis using the archetype query language. DISCUSSION Archetype-based standards and technologies can be used to create a data warehouse environment that enables data from EHR systems to be reused in clinical research and decision support systems. With this approach, existing EHR data becomes available in a standardized and interoperable format, thus opening a world of possibilities toward semantic or concept-based reuse, query and communication of clinical data.

Garbage in, garbage out: extracting disease surveillance data from epr systems in primary care

This paper presents an interpretive case study on extraction of disease surveillance data from Electronic Patient Records (EPRs) in primary care. The General Practitioners (GPs) use of the EPR system, and the effect this has on data content, such as symptoms reported by patients and diagnoses reported by GPs, is discussed. The paper contributes to greater understanding of sociotechnical issues related to disease surveillance, and contains illustrative examples of many issues important to CSCW. This includes how data collected in one context may be applied to a different context, and the delicate interplay between organizational and technical design challenges.

An Evaluation Framework for Defining the Contributions of Telestration in Surgical Telementoring

Background An increasing quantity of research in the domain of telemedicine show a growing popularity and acceptance of care over distance systems among both clinicians and patients. We focus on telementoring solutions, developed for providing remote guidance to less experienced surgeons. Telestration is often regarded as an extra functionality of some telementoring systems. However, we advocate that telestration must be viewed as a core feature of telementoring due to its advantages. Objective To analyze and define concepts, parameters, and measurement procedures to evaluate the impact of using telestration while telementoring. Methods A systematic review of research dealing with telestration during remote guidance sessions was performed by querying three major online research databases (MEDLINE, Association of Computing Machinery, and Institute of Electrical and Electronics Engineers) using a predefined set of keywords (“laparoscopy”, “annotate”, “telestrate”, “telestration”, “annotation”, “minimally invasive”, and “MIS”). Results The keyword-based search identified 117 papers. Following the guidelines for performing a systematic review, only 8 publications were considered relevant for the final study. Moreover, a gap in research defining the impacts of telestration during telementoring was identified. To fill this niche, a framework for analyzing, reporting, and measuring the impacts of telestration was proposed. Conclusions The presented framework lays the basics for the structured analysis and reporting of telestration applied to telementoring systems. It is the first step toward building an evidence knowledge base documenting the advantages of live video content annotation and supporting the presented connections between the concepts.

Causality in Scale Space as an Approach to Change Detection

Kernel density estimation and kernel regression are useful ways to visualize and assess the structure of data. Using these techniques we define a temporal scale space as the vector space spanned by bandwidth and a temporal variable. In this space significance regions that reflect a significant derivative in the kernel smooth similar to those of SiZer (Significant Zero-crossings of derivatives) are indicated. Significance regions are established by hypothesis tests for significant gradient at every point in scale space. Causality is imposed onto the space by restricting to kernels with left-bounded or finite support and shifting kernels forward. We show that these adjustments to the methodology enable early detection of changes in time series constituting live surveillance systems of either count data or unevenly sampled measurements. Warning delays are comparable to standard techniques though comparison shows that other techniques may be better suited for single-scale problems. Our method reliably detects change points even with little to no knowledge about the relevant scale of the problem. Hence the technique will be applicable for a large variety of sources without tailoring. Furthermore this technique enables us to obtain a retrospective reliable interval estimate of the time of a change point rather than a point estimate. We apply the technique to disease outbreak detection based on laboratory confirmed cases for pertussis and influenza as well as blood glucose concentration obtained from patients with diabetes type 1.

The virtual library secretary: A user model-based software agent

A user model comprises knowledge of the users past and present tasks, and is the essential element in adaptive user interfaces. Through the propagation of user models, we can take the user models into the world of software agents, and thus construct user model-based software agents. The user model approach reduces the threats of software agents penetrating a local host and the amount of data transferred. This paper presents the Virtual Library Secretary, which is a user model-based software agent system. The Virtual Library Secretary offers information retrieval and information filtering to the user. The system is part of the Virtual Secretary project. The user model is established by a simple neural network. In this way, the agent is able to learn and adapt to the users behaviour. This paper discusses the user model concept, presents the Virtual Secretary system architecture and describes how this architecture works through the Virtual Library Secretary.

Towards privacy-preserving computing on distributed electronic health record data

The paper reports on work in progress towards construction of a peer-to-peer framework for privacy preserving computing on distributed electronic health data. The framework supports three different types of federated queries. For privacy-preserving computing, we proposed distributed secure multi-party computation (SMC), where each peer is only involved in secure computations with some of the peers. We hypothesize distributed SMC could enable to achieve more efficient and scalable computing solutions. The architecture of the framework is also described.