Preparing the ground for the 'paperless hospital': a case study of medical records management in a UK outpatient services department

PurposeThe purpose of the study was to understand the preparations for the introduction of electronic patient record systems (EPRs) within the outpatient services department of a large acute hospital based in the UK. In particular, one of the main aims of the study was to examine in detail the likely impact of EPRs on the working practices of healthcare workers, their expectations regarding the impact of EPRs within the department and other sociotechnical aspects of the management of patient information.MethodsTwenty-seven semi-structured interviews were undertaken with staff in a variety of roles that deal with the management of medical records. The interviews focused on the organisation of the medical records department and current problems (e.g., missing records). In addition, the interviews contained questions about the specific role of medical records supervisors in the administration of records, as well as pathways and expectations about EPRs more generally. The data from the interviews was analysed using a mixture of thematic and template analysis and coded using constructs from a sociotechnical model of information system implementation and adoption.ResultsThe findings show that despite severe delays to the nationally led (NPfIT) roll-out of EPRs and associated IT infrastructure within the UK, staff attitudes within the department were broadly positive about the potential of future EPRs to deliver efficiencies (e.g., improved workflow within the department, reduced reliance on paper-based systems). One of the main influences on attitudes towards the type of EPRs that should exist within outpatients was prompted by negative reactions to the way in which NPfIT systems had been managed and attempted to be introduced in the past. A strong commitment to end-user involvement in EPRs design, together with a rejection of NPfIT, appears to have shaped attitudes towards future expectations of the adoption of new EPRs within the department. In addition, staff do not believe that a rapid change to ‘paperless’ working is likely to be possible.ConclusionsOur findings provide further evidence that there is a need to treat the implementation of EPRs not simply as an exercise in technical system delivery, but as a larger process of sociotechnical systems change. We conclude the paper with some guidelines, the aim of which is to provide guidance regarding EPRs implementation and adoption informed by sociotechnical principles and ideas.     

Data security and protection in cross-institutional electronic patient records

This paper aims at identifying the specific legal requirements concerning data security and data protection of patient health data that apply to a cross-institutional electronic patient record (EPR) and describes possible solutions for meeting these requirements. In Germany, the legal framework for such records provide that disclosure of patient health information to physicians of third-party institutions is only allowed in case that it is necessary for the joint treatment of the patient, i.e. in case of a “treatment connection”. As a first step, the functionality of a remote-access architecture was proven allowing a one-way connection between the EPR systems of two health institutions in Germany, which jointly treat tumor patients. Besides, a signature system model for ensuring the integrity and authenticity of medical documents was developed and implemented in the existing information system architecture of the University Medical Center of Heidelberg. Especially in Germany, the legal framework for cross-institutional EPRs is very complex and has a considerable influence on the development and implementation of cross-institutional EPRs. However, its introduction is thought to be valuable, since a cross-institutional EPR will improve communication within shared care processes, and thus improve the quality of patient care.     

An Improved Medical Image Fusion Algorithm for Anatomical and Functional Medical Images

In recent years,many medical image fusion methods had been exploited to derive useful information from multimodality medical image data, but, not an appropriate fusion algorithm for anatomical and functional medical images. In this paper, the traditional method of wavelet fusion is improved and a new fusion algorithm of anatomical and functional medical images,in which high-frequency and low-frequency coefficients are studied respectively. When choosing high-frequency coefficients, the global gradient of each subimage is calculated to realize adaptive fusion,so that the fused image can reserve the functional information;while choosing the low coefficients is based on the analysis of the neighborbood region energy, so that the fused image can reserve the anatomical image＇ s edge and texture feature. Experimental results and the quality evaluation parameters show that the improved fusion algorithm can enhance the edge and texture feature and retain the function information and anatomical information effectively.     

Optimization and evaluation of landmark-based image correlation.

Image correlation methods enable the complementary use of information from different medical images of a patient. These images can be obtained from different imaging devices (CT, MR, PET), or, from one imaging device taken at different times. Unfortunately, there are few cases in which the requirements for later image correlation are taken into account at the time of image acquisition. There is therefore a need for correlation techniques requiring no preparation in advance. We have developed two correlation methods, both based on three or more anatomical or artificial landmarks, to be defined in corresponding image data sets. These methods have been evaluated with phantom data as well as with patient data. We have improved these correlation methods by using more landmarks and special selection criteria. They are applicable to all medical tomograms and to x-ray pictures taken under stereotactical conditions. The results obtained have error ranges in the order of the three-dimensional image resolution.     

The mantra of modeling and the forgotten powers of paper: A sociotechnical view on the development of process-oriented ICT in health care

The recognition that restructuring care processes is central to effective and efficient health care will result in the emergence of process-oriented electronic patient records (EPRs). How will these technologies come into being? Within informatics, it is often stated that to informate something, we should first model it. This paper queries whether a detailed modeling of work processes and data flows is the primary step that needs to be completed before such EPRs can be developed or tailored. Building upon a sociotechnical understanding of ICT development, we argue for a reinterpretation of 'models' in such development processes. We do so through a reverse engineering of parts of the paper-based medical record, which has received little attention in medical informatics. In process-oriented EPR design, we argue, modeling should not be conceived as the crucial first step in this design, but rather as an intervention in the organizational change-processes that constitute proper ICT development.     

Technical Report on Semiautomatic Segmentation Using the Adobe Photoshop

The purpose of this research is to enable users to semiautomatically segment the anatomical structures in magnetic resonance images (MRIs), computerized tomographs (CTs), and other medical images on a personal computer. The segmented images are used for making 3D images, which are helpful to medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was scanned to make 557 MRIs. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL and manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a similar manner, 13 anatomical structures in 8,590 anatomical images were segmented. Proper segmentation was verified by making 3D images from the segmented images. Semiautomatic segmentation using Adobe Photoshop is expected to be widely used for segmentation of anatomical structures in various medical images. The authors obtained consent for this research from concerned parties (a female subject and relatives of the deceased subject) after a full explanation about the nature of this procedure. In addition, we followed the cadaver management laws of South Korea.     

Effectiveness of using cross-sections in the recognition of anatomical structures in radiological images

This study measured the effect of using anatomical cross-sections to enhance the interpretation of radiological images. It examined the effectiveness of using magnetic resonance (MR or MRI) images presented side-by-side with their corresponding cross-sectional images, as compared to using only the MR images. Student aptitude to identify anatomical structures in the radiological images was measured. The study also assessed student preferences toward the two presentation formats. Thirty-four freshmen medical students (17 females and 17 males) and a female graduate student enrolled in a clinical anatomy, embryology, and imaging course volunteered to participate in the study. A posttest-only control group design was used and the collected data were analyzed by a t-test. A survey was developed to collect student perceptions of the two presentation formats. There was no significant difference between using MR images with cross-section images and using MR images alone in the students' immediate recall of anatomical information presented in radiological images. However, the students showed strong preferences for the presentation of MR images with cross-section images and indicated that it would help them interpret radiological information.     

PET image reconstruction with anatomical edge guided level set prior

Acquiring both anatomical and functional images during one scan, PET/CT systems improve the ability to detect and localize abnormal uptakes. In addition, CT images provide anatomical boundary information that can be used to regularize positron emission tomography (PET) images. Here we propose a new approach to maximum a posteriori reconstruction of PET images with a level set prior guided by anatomical edges. The image prior models both the smoothness of PET images and the similarity between functional boundaries in PET and anatomical boundaries in CT. Level set functions (LSFs) are used to represent smooth and closed functional boundaries. The proposed method does not assume an exact match between PET and CT boundaries. Instead, it encourages similarity between the two boundaries, while allowing different region definition in PET images to accommodate possible signal and position mismatch between functional and anatomical images. While the functional boundaries are guaranteed to be closed by the LSFs, the proposed method does not require closed anatomical boundaries and can utilize incomplete edges obtained from an automatic edge detection algorithm. We conducted computer simulations to evaluate the performance of the proposed method. Two digital phantoms were constructed based on the Digimouse data and a human CT image, respectively. Anatomical edges were extracted automatically from the CT images. Tumors were simulated in the PET phantoms with different mismatched anatomical boundaries. Compared with existing methods, the new method achieved better bias-variance performance. The proposed method was also applied to real mouse data and achieved higher contrast than other methods.     

Synchronous acquisition of hyperpolarised 3He and 1H MR images of the lungs – maximising mutual anatomical and functional information

The development of hybrid medical imaging scanners has allowed imaging with different detection modalities at the same time, providing different anatomical and functional information within the same physiological time course with the patient in the same position. Until now, the acquisition of proton MRI of lung anatomy and hyperpolarised gas MRI of lung function required separate breath‐hold examinations, meaning that the images were not spatially registered or temporally synchronised. We demonstrate the spatially registered concurrent acquisition of lung images from two different nuclei in vivo. The temporal and spatial registration of these images is demonstrated by a high degree of mutual consistency that is impossible to achieve in separate scans and breath holds. Copyright © 2010 John Wiley & Sons, Ltd.     

Automated Facial Recognition of Computed Tomography-Derived Facial Images: Patient Privacy Implications

The recognizability of facial images extracted from publically available medical scans raises patient privacy concerns. This study examined how accurately facial images extracted from computed tomography (CT) scans are objectively matched with corresponding photographs of the scanned individuals. The test subjects were 128 adult Americans ranging in age from 18 to 60 years, representing both sexes and three self-identified population (ancestral descent) groups (African, European, and Hispanic). Using facial recognition software, the 2D images of the extracted facial models were compared for matches against five differently sized photo galleries. Depending on the scanning protocol and gallery size, in 6–61 % of the cases, a correct life photo match for a CT-derived facial image was the top ranked image in the generated candidate lists, even when blind searching in excess of 100,000 images. In 31–91 % of the cases, a correct match was located within the top 50 images. Few significant differences (p > 0.05) in match rates were observed between the sexes or across the three age cohorts. Highly significant differences (p < 0.01) were, however, observed across the three ancestral cohorts and between the two CT scanning protocols. Results suggest that the probability of a match between a facial image extracted from a medical scan and a photograph of the individual is moderately high. The facial image data inherent in commonly employed medical imaging modalities may need to consider a potentially identifiable form of “comparable” facial imagery and protected as such under patient privacy legislation.     

Developing a standard for de-identifying electronic patient records written in Swedish: Precision, recall and F-measure in a manual and computerized annotation trial

Background

Electronic patient records (EPRs) contain a large amount of information written in free text. This information is considered very valuable for research but is also very sensitive since the free text parts may contain information that could reveal the identity of a patient. Therefore, methods for de-identifying EPRs are needed. The work presented here aims to perform a manual and automatic Protected Health Information (PHI)-annotation trial for EPRs written in Swedish.

Methods

This study consists of two main parts: the initial creation of a manually PHI-annotated gold standard, and the porting and evaluation of an existing de-identification software written for American English to Swedish in a preliminary automatic de-identification trial. Results are measured with precision, recall and F-measure.

Results

This study reports fairly high Inter-Annotator Agreement (IAA) results on the manually created gold standard, especially for specific tags such as names. The average IAA over all tags was 0.65 F-measure (0.84 F-measure highest pairwise agreement). For name tags the average IAA was 0.80 F-measure (0.91 F-measure highest pairwise agreement). Porting a de-identification software written for American English to Swedish directly was unfortunately non-trivial, yielding poor results.

Conclusion

Developing gold standard sets as well as automatic systems for de-identification tasks in Swedish is feasible. However, discussions and definitions on identifiable information is needed, as well as further developments both on the tag sets and the annotation guidelines, in order to get a reliable gold standard. A completely new de-identification software needs to be developed.     

Computer-based anthropometrical system for total body irradiation

For total body irradiation (TBI) dose calculation requirements, anatomical information about the whole body is needed. Despite the fact that video image grabbing techniques are used by some treatment planning systems for standard radiotherapy, there are no such systems designed to generate anatomical parameters for TBI planning. The paper describes an anthropometrical computerised system based on video image grabbing which was purpose-built to provide anatomical data for a PC-based TBI planning system. Using software, the system controls the acquisition and digitalisation of the images (external images of the patient in treatment position) and the measurement procedure itself (on the external images or the digital CT information). An ASCII file, readable by the TBI planning system, is generated to store the required parameters of the dose calculation points, i.e. depth, backscatter tissue thickness, thickness of inhomogeneity, off-axis distance (OAD) and source to skin distance (SSD).     

Transmission and storage of medical images with patient information

Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. The text data is encrypted before interleaving with images to ensure greater security. The graphical signals are interleaved with the image. Two types of error control-coding techniques are proposed to enhance reliability of transmission and storage of medical images interleaved with patient information. Transmission and storage scenarios are simulated with and without error control coding and a qualitative as well as quantitative interpretation of the reliability enhancement resulting from the use of various commonly used error control codes such as repetitive, and (7,4) Hamming code is provided.     

Pathological analysis of cadavers for educational dissection by using postmortem imaging

This study was performed primarily to clarify whether pathological analysis of cadavers for anatomical dissection is possible using postmortem imaging (PMI), and whether this is worthwhile. A total of 33 cadavers that underwent systematic anatomical dissection at our medical school also underwent PMI. Fixative solution was injected into the corpus 3–4 days after death. PMI was then performed using an 8‐slice multi‐detector CT scanner 3 months before dissection. Before dissection, a conference was held to discuss the findings of the PMI. First, two radiologists read the postmortem images without any medical information and deduced the immediate cause of death. Then, the anatomy instructor revealed the medical information available. Based on this information, the radiologist, anatomy instructor, and pathologists suggested candidate sampling sites for pathological examination. On the last day of the dissection period, the pathologists resected the sample tissues and processed them for pathological examination. In 12 of 33 cases, the presumed causes of death could be determined based on PMI alone, and revision of the cause of death described in the death certificate was considered in five (15.2%) cases, based on PMI and pathological analysis. This article presents a novel method of pathological analysis of cadavers for anatomical dissection using PMI without disturbing the anatomy education of medical students.     

Recherche de cas médicaux multimodaux à l’aide d’arbres de décision

In this article, we present a Case-based Reasoning system for the retrieval of patient files similar to a case placed as query. We focus on patient files made up of several images with contextual information (such as the patient age, sex and medical history). Indeed, medical experts generally need varied sources of information (which might be incomplete) to diagnose a pathology. Consequently, we derive a retrieval framework from decision trees, which are well suited to process heterogeneous and incomplete information. To be integrated in the system, images are indexed by their digital content. The method is evaluated on a classified diabetic retinopathy database. On this database, results are promising: the retrieval sensitivity reaches 79.5% for a window of five cases, which is almost twice as good as the retrieval of single images alone.     

The contextual nature of medical information

Successful design of information systems in health care starts with a thorough understanding of the practices in which the systems are to function. In this paper, we discuss the nature of 'medical information' from a sociological perspective. We focus on the (im)possibilities of the utilization of primary health care data for secondary purposes such as research and administration. In much of the literature on EPRs, this secondary utilization is only seen to depend on the question whether the IT connections are in place. It is then simply a matter of selecting which information to transport and to where. In this article, we argue that this view of medical information is mistaken. Information should be conceptualized as always entangled with the context of its production. The disentangling of information from its production context is possible, but that entails work. We propose the following 'law of medical information': the further information has to be able to circulate (i.e. the more diverse contexts it has to be usable in), the more work is required to disentangle the information from the context of its production. The question that then becomes pertinent is; who has to do this work, and who reaps the benefits?     

Efficient high capacity technique to embed EPR information and to detect tampering in medical images

Abstract

Reversible data hiding (RDH) is one of the well-known and highly recommended method to enhance medical data security or electronic patient record (EPR), privacy and truthfulness. In clinical images, while hiding the data, care must be taken to maintain the confidentiality of the information that is to be hidden within the clinical images because the hidden information should not bring down the original quality of the image. Mostly, the investigations carried out for medical diagnosis are usually constructed on the basis of investigation systems used for diagnosis and are grounded on the images usually used for medical study. Magnetic resonance image (MRI), CR and CT, digital format images which are acquired are related to the patient’s data and information regarding their diagnosis study. In this presented approach, we introduce an RDH scheme that can also be combined with encryption and reversible watermarking techniques. Here, we use the data related to the patient diagnosis as the secret information to embed in medical images. Quality of the marked image after embedding the data is usually measured with metrics that are usually used in image processing such as PSNR and SSIM.     

基于配准方法的颅脑CT图像病变信息自动提取算法

医学图像中病变信息的计算机自动提取是实现计算机智能辅助诊断的关键与难点,本研究的目的就是提出一个解决该难题的算法,称之为PATHOINFER。该算法的基本过程是首先选择一幅具有代表性的模板图像帆和一系列与其相应的正常图像样奉Mi,利用非刚性配准分别建立表示“正常图像”灰度变化的灰度均值图谱,表示正常变异的统计概率图谱和反映其解剖结构空间关系的分割模板。以实现对“正常图像”的计算机描述。再通过M0与目标图像S的配准,达到“正常图像”与S在空间关系上的一致,然后通过S与“正常图像”的比较,利用模糊逻辑推理,自动检出S中的病变区域,并实现对其病变特征信息的自动提取。实验结果表明,PATHOINFER算法可自动地检出并分割病变区域,并能够自动地提取包括病变发生部位在内的特征信息。实现了计算机智能辅助诊断研究中病变信息自动提取的难胚。     

Virtual bronchoscope system

In this article, we describe the features of Virtual Bronchoscope System(VBS) and its practical use. VBS is constructed based on 3-D chest CT images. The bronchus region is automatically extracted from 3-D chest CT images by a three-dimensional region growing method. The surface rendering is employed for construction of virtualized tracheo-bronchial tree. It gives us an environment where we can observe inside the bronchi from an arbitrary viewpoint and a view direction. By mouse operation, the user can control the viewpoint and the view direction to fly through inside the airway in real time. VBS is applicable for a variety of purposes such as diagnosis, surgical planning, informed consent, education and training. One of extension of this system is a teaching tool for medical students. In the module for educational use, we have developed four functions for using the system as a teaching tool as follows: (a) automated display of bronchial anatomical names, (b) presenting questions about the currently observed branch in the endoscopic view, (c) display of the path which the user should follow, and (d) display of a question about the location of the artificially created tumor in the bronchus. These functions use the processed results of automated anatomical labeling. The method proposed here combines the knowledge based processing technique 'automated labeling of bronchial branch' and the novel visualization technique 'virtual bronchoscope'. This is one of new teaching tools of medical images. We conclude that this virtual bronchoscope system might have an important role in the medial students' education.