- Email: [email protected]
A computer-based information system for epilepsy and electroencephalography
International Journal of Medical Informatics 55 (1999) 127 – 134
www.elsevier.com/locate/ijmedinf
Technical communication
A computer-based information system for epilepsy and electroencephalography N.B. Finnerup, A. Fuglsang-Frederiksen *, P. Røssel, P. Jennum Department of Clinical Neurophysiology, Gentofte Hospital, Uni6ersity of Copenhagen, DK-2900 Hellerup, Denmark Received 4 June 1998; received in revised form 3 December 1998; accepted 15 December 1998
Abstract This paper describes a standardised computer-based information system for electroencephalography (EEG) focusing on epilepsy. The system was developed using a prototyping approach. It is based on international recommendations for EEG examination, interpretation and terminology, international guidelines for epidemiological studies on epilepsy and classification of epileptic seizures and syndromes and international classification of diseases. It is divided into: (1) clinical information and epilepsy relevant data; and (2) EEG data, which is hierarchically structured including description and interpretation of EEG. Data is coded but is supplemented with unrestricted text. The resulting patient database can be integrated with other clinical databases and with the patient record system and may facilitate clinical and epidemiological research and development of standards and guidelines for EEG description and interpretation. The system is currently used for teleconsultation between Gentofte and Lisbon. © 1999 Elsevier Science Ireland Ltd. All rights reserved. Keywords: EEG; Epilepsy; Information system; Database; Standardisation; Telecommunication
1. Introduction Clinical information databases offer several advantages in clinical research because of accurate and timely data and clinical details. They can be used to investigate clinical epi* Corresponding author. Tel.: +45-39-773429; fax: + 4539-777636. E-mail address: [email protected] (A. FuglsangFrederiksen)
demiology, risk assessment, post-marketing surveillance of drugs, practice variation, resource use, quality assurance and decision analysis. In addition they can be used to identify subjects for prospective studies [1,2]. Furthermore databases might be useful in daily routine because of standardised methods for data acquisition and time saved due to avoidance of duplication of information [2,3]. They can also be useful when data has
1386-5056/99/$ - see front matter © 1999 Elsevier Science Ireland Ltd. All rights reserved. PII: S 1 3 8 6 - 5 0 5 6 ( 9 9 ) 0 0 0 0 2 - 7
128
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
to be transferred between different centres. Several large clinical information databases have been established [1,4]. Within electromyography there is a European database for neuromuscular diseases [5]. A comprehensive EEG information system including a database and user interface does not exits. The purpose of this project was to develop a standardised computer-based system with a common structure for qualitative visual electroencephalogram (EEG) description and interpretation and for collection of epilepsy data. 2. About Prestige The epilepsy and EEG information system was developed as part of an European multicentre project PRESTIGE, Guidelines in Healthcare, which is a project in the European Commissions’ Telematics Applications Programme, DG XIII.C4–Telematics Applications for Health, Project HC 1040. The aim of PRESTIGE is to deploy healthcare telematics technology to assist in the generation, dissemination and routine application of research-based and consensus-based guidelines, and thus bridge the gap between research and everyday clinical practice. As part of the Neurology subproject —Information technology support of guidelines for the management of epilepsy—a teleconsultation in EEG between Lisbon and Gentofte was needed where clinical EEG cases could be discussed. The purpose was to specify a database structure for the representation of EEG data and to develop a tool for EEG teleconsultation.
ratories a general database structure was specified. During a pre-study the description of user needs were described by means of scenarios. These scenarios were developed by review of the literature and from answers to questionnaires about examination techniques, EEG evaluation, and epilepsy data from mainly Danish neurologists and neurophysiologists but also from neurophysiologists in Portugal, Italy and UK. In this way an attempt was made to cover various user requirements. The structure and terminology were based on international guidelines. The structure and terminology for EEG examination and evaluation follows the recommendations from the American Electroencephalographic Society (AEGGS), the International Federation of Societies for Electroencephalography and Clinical Neurophysiology (IFSECN) and the American Society for Testing and Materials [6–9]. The epilepsy data is based on guidelines from the International League Against Epilepsy (ILAE) for epidemiological studies on epilepsy [10], classification of epileptic seizures [11] and classification of epileptic syndromes [12]. Diagnoses are classified according to the International Classification of Diseases and Health Related Problems (ICD 10). The system was developed in Microsoft Access 97 for Windows 95 as a run-time module using a prototyping approach. Several prototypes were designed during the initial phase. In this way development and evaluation was interactive between computer scientists and physicians and feedback was sought throughout the development process.
4. The structure of the system 3. Development As to collect and exchange the heterogeneous EEG patient cases from different labo-
The system is divided into three main groups of data: (1) introduction; (2) clinical information; and (3) EEG. The latter is fur-
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
ther subdivided into three subgroups (3a) EEG description, (3b) EEG interpretation and (3c) final diagnosis. Each group is divided into modules (Fig. 1). The system includes the description and interpretation of the EEG and the epilepsy data; the viewing of EEGs is not part of the system. (1) Introduction: Main options: the user has to select whether to evaluate an examination or to create/edit an examination. General information: this includes information about the patient such as name, date of birth and sex and test information such as EEG identification number and date, EEG type, electrode sites and electroencephalographer. (2) Clinical information: this includes the epilepsy part of the system, which can be used separately. Referral information: includes referring department, date of referral, and referral diagnosis. Clinical data is classified into medical history, medication, physical examination and ancillary tests. Epilepsy-data: further epilepsy relevant data such as possible aetiology and precipitating factors. Epilepsy-classification: a classification of the epilepsy or epileptic syndrome and a classification of epileptic seizures, seizure frequency and date of first and last seizure. (3) EEG: the EEG data is hierarchically structured. The EEG description and EEG interpretation are based on the EEG, whereas the final diagnosis also should take ‘the clinical information’ as described above into account. (3a) The EEG description: this is the lowest level in the diagnostic hierarchy and should include all the characteristics of the record presented in an objective way, avoiding as much as possible judgement about their significance. It includes: General clinical obser6ations: clinical observations made at the beginning of recording e.g. a description of the level of consciousness,
129
respiration and vital signs. EEG acti6ity and seizure description: First an EEG activity is selected from a list, e.g. spike, alpha rhythm or 14 and 6 Hz positive burst. By selecting an activity (e.g. 14 and 6 Hz positive burst) some judgement about its significance is already made, but this possibility was chosen to keep the system relatively simple. Next step is a description of the activities, which includes, e.g. frequency, amplitude, symmetry, location, rhytmicity, synchronicity, amount, relation to activations, reactivity and occurrence (intermittent, periodic, continuous) (Fig. 2). Any seizure (the term includes nonepileptic seizures) observed during recording are described by selecting symptoms and signs from a list, e.g. blank stare or hyperventilation, pallor and sweating. The seizure is then described by, e.g. location, duration or postictal changes. It is also possible to relate EEG activities and seizures. (3b) The EEG interpretation: includes: Acti6ity and seizure conclusion: this is the second level in the hierarchy. It will show a summary of the findings. The summary leads to a pathophysiological interpretation for each activity such as normal or focal or epileptogenic abnormal. Any seizure is interpreted e.g. as absence seizure with impairment of consciousness only or hyperventilation syndrome. EEG conclusion: This third level in the hierarchy is an impression regarding the normality or grade of abnormality of the record. It includes diagnoses that the EEG might be suggestive or diagnostic of, e.g. absence epilepsy or alpha coma. It includes recommendations for new examinations and comparisons with previous EEGs. (3c) Final diagnosis: this is the fourth and highest level in the diagnostic hierarchy and is a correlation of the EEG findings with ‘the clinical information’ suggesting a final diag-
130 N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
Fig. 1. Schematic representation of the menu hierarchy with the major pathways of the electroencephalography (EEG) and epilepsy information system.
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
nosis, e.g. G40.3 Childhood absence epilepsy, and for epilepsies it includes a syndrome classification. Most of the data is entered as coded data, but since this is in many instances too limited to express nuances, unrestricted text is added in a comment field on most of the screens. When possible some data are automatically deduced, e.g. age of the patient and the system has automatically cross-checking, e.g. for blood pressure the systolic must be higher than the diastolic blood pressure etc. Some data is hidden and appear only when relevant, e.g. occurrence, selection and description of a seizure will be shown only when a related seizure is selected in the activity de-
131
scription (Fig. 2). When a given patient is registered more than once the examinations are treated as separate entities since this version of the system is designed primarily for exchange of patients for consultation.
5. Functions of the system The reasons for the development of the computer-based epilepsy and EEG information system were to support 1. Teleconsultation: supplying a database structure for the representation of EEG data facilitating inter-laboratory exchange
Fig. 2. Description of an electroencephalography (EEG) activity, is this case delta activity. An interface of the epilepsy and EEG information system.
132
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
of data between EEG laboratories in Europe as part of the PRESTIGE program. 2. Research: patient data stored in the system (collected for research purposes or in daily routine) will be easily accessible and usable for research purposes within the domain of epilepsy and EEG. 3. Daily routine: supporting the daily routine of the neurologist and neurophysiologist as part of a medical record. In the future it is planned to use the system to produce EEG reports and integrate it with a common patient record system. 4. Standardisation: presenting a tool for facilitation development and discussion of guidelines and standards for EEG examinations and evaluations.
5.1. Teleconsultation Two separate elements are telecommunicated. (1) An examination from the information system consisting of patient data, EEG description and EEG conclusion. In the system there is a function called ‘export examination’. This function is used to generate an ASCII file containing a given examination. (2) An EEG curve from a pre-agreed digital EEG machine. For almost every digital EEG machine a limited reader station can be supplied for the specific format and thus be used by others. All information leaving the local area network (LAN) can be hacked. Therefore all information is sent anonymous without patient ID in order to secure the patient and encryption becomes unnecessary. There are then two files. One in ASCII format and one in a pre-agreed EEG format. The only connection between the two files is a list number that is assigned by the user. The most obvious method for transportation of the files is the e-mail system provided by the Internet. It will clearly be an advantage to pack the digital EEG file of 20-40 Mb. data.
The consultant views the EEG on a reader station and inputs his evaluation on his local version of the information system. After evaluation the consultant either exports the data containing his/her evaluation into ASCII and returns it by Internet (offline consultancy) or gives his/hers advice by the telephone (online consultancy). Currently the teleconsultation possibilities of the system between Gentofte Hospital and Hospital Egas Moniz, Lisbon are being evaluated.
5.2. Research purposes The program can be used for clinical and epidemiological research. All data collected using the EEG case collection tool are stored in a database. All coded data can be easily retrieved for use to investigate clinical epidemiology, practice variation, quality assurance, etc. Such data includes for example referral diagnosis, specific epileptic syndromes, seizure frequency, medication, other epilepsy relevant data such as aetiology and previous operation for epilepsy, EEG activities, EEG conclusions and final diagnoses. A pilot study of inter-observer variability in the interpretation of EEG recordings is used as a preliminary evaluation of the system. A random sample of EEG recordings obtained from the Department of Neurophysiology at Gentofte hospital are presented to three specialists in neurophysiology from two departments, Department of Neurophysiology at Gentofte hospital and at Filadelfia hospital in Dianalund, Denmark. The neurophysiologists describe and interpret the records as if they were making a routine EEG report (except that it only includes the description and interpretation of the EEG and not the clinical correlation). Agreement on several factors used in the interpretation of EEGs are studied such as overall assessment of the EEG, exact pattern expression, pres-
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
ence of epileptiform or ictal changes or presence of a focus.
5.3. Supporting daily routine The program can be integrated with clinical databases and with the patient record system. An interface needs to be programmed to interact with the database. The easiest solution in most cases is to use Open Database Connection (ODBC). The referral information part including all clinically relevant epilepsy data can be used separately. When used in the department of neurophysiology, the technician initially fills out the general and referral information forms using information from the referring physician. If the system is part of a common database the referral information will already be available from the neurology department in electronic form. Then the patient’s state of consciousness at the onset of the record and description of any seizure during recording is filled in. As usual the technician also makes a description an interpretation of the EEG. The physician then makes a description, interpretation and final diagnosis. If the system is not part of a common medical record, then selected items might be printed serving as the EEG report. The use of the program in everyday practice is evaluated by an inquiry, which covers the functionality and usability of the system, the fastness, the user interface, the structure and the options available. It is planned to extend the evaluation to include physicians from different laboratories in Europe in order to meet various user requirements in the future.
5.4. Standardisation The use of guidelines for medical practice has high priority in many countries, as it is
133
believed to improve the quality of examinations by standardisation. Several international guidelines exist within the domains of epilepsy and EEG [6–12]. Nonetheless questionnaires to neurophysiologists in Europe and review of the literature reveal differences in EEG practice and definition of terms, and studies have shown variation in EEG interpretation [13–18]. Also epidemiological research on epilepsy often lacks agreement regarding the most basic concepts, and definitions of epilepsy, seizures and independent variables often are not elaborated [10]. It seems that marked variations in practice patterns still exist which leads to concerns about differences in the quality of patient care. Studies on variation in interpretation of EEGs are a prerequisite for standardisation. Databases can help in the identification of differences in clinical care and in patient outcome and may contain data that possibly explains the causes for these differences. They can be used to quantify what portion of the variation is attributable to patient differences and what is due to differences in physician practice pattern [1]. The international guidelines on EEG practice and terminology implemented in the information system will force the physicians to consider using these. Confrontation of clinicians with standards encourages discussion and evaluation of the usability of these and may lead to recommendations for changes or further studies.
Acknowledgements This project was supported by Prestige. We wish to thank Søren Vingtoft, DSI, Institute for Public Health Service, Copenhagen, Denmark, Mario Veloso, Department of Neurology, Hospital Egas Moniz, Lisbon, Portugal and Lars Gottlieb, Hillerød Hospital, Den-
134
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
mark for helpful suggestions during the development. We also wish to thank I.S. Schofield and P.R.W. Fawcett, Department of Clinical Neurophysiology, Newcastle General Hospital, Newcastle upon Tyne, UK and R. Liguori, Institute of Neurology, University of Bologna, Bologna, Italy for sending examples of their EEG reports.
References [1] W.M. Tierney, C.J. McDonald, Practice databases and their uses in clinical research, Stat. Med. 10 (1991) 541–557. [2] P. Griep, N. Van den Berg, J. Doelman, R. Starrenburg, An epilepsy information system to support routine and research, Int. J. Biomed. Comput. 42 (1996) 135–141. [3] M.D. Bej, R.C. Burgess, An extensive epilepsy monitoring database, J. Clin. Neurophysiol. 14 (5) (1997) 449. [4] C. Confavreux, D.A.S. Compston, O.R. Hommes, W.I. McDonald, A.J. Thomson, EDMUS, a European database for multiple sclerosis, J. Neurol. Neurosurg. Psychiatr. 55 (1992) 671–676. [5] B. Johnsen, A. Fuglsang-Frederiksen, S. Vingtoft, P. Fawcett, I. Schofield, R. Liguori, W. Nix, G. Otte, G. Sieben, M. Veloso, A. Vila, An European database for neuro-muscular diseases (Abstract), Electroenceph. Clin. Neurophysiol. 2 (1993) S100. [6] AEEGS: American Electroencephalographic Society. Guidelines in EEG, evoked potentials and polysomnography. J. Clin. Neurophysiol. 1 (1994) 1–147. [7] IFSECN. Recommendations for the Practice of Clinical Neurophysiology, Elsevier, Amsterdam, 1983.
.
[8] G.E. Chatrian, L. Bergamini, M. Dondey, et al., A glossary of terms most commonly used by clinical electroencephalographers, Electroencephalogr. Clin. Neurophysiol. 37 (1974) 538 – 548. [9] ASTM E1467-92: American Society for Testing and Materials. Standard specification for transferring digital neurophysiological data between independent computer systems. In: Annual Book of ASTM Standards, 1992, pp. 1 – 109. [10] ILAE. Guidelines for epidemiologic studies on epilepsy. Epilepsia 34(4) (1993) 592 – 596. [11] ILAE. Proposal for revised clinical and electroencephalographic classification of epileptic seizures. From the Commission on Classification and Terminology of the International League Against Epilepsy. Epilepsia 22 (1981) 489 – 501. [12] ILAE. Proposal for revised classification of epilepsies and epileptic syndromes. Commission on Classification and Terminology of the International League Against Epilepsy, Epilepsia 30 (1989) 389– 399. [13] R.H. Woody, Inter-judge reliability in clinical electroencephalography, J. Clin. Psychol. 24 (1968) 251 – 256. [14] J. Volavka, M. Matousek, S. Feldstein, et al., The reliability of EEG assessment, EEG EMG 4 (1973) 123 – 130. [15] J. Volavka, M. Matousek, J. Roubicek, et al., The reliability of visual EEG assessment, Electroenceph. Clin. Neurophysiol. 31 (1975) 294. [16] S.C. Little, S.L. Raffel, Intra-rater reliability of EEG interpretation, J. Nerv. Ment. Dis. 135 (1962) 77 – 81. [17] R.H. Blum, A note on the reliability of electroencephalographic judgements, Neurology 4 (1954) 143 – 146. [18] E.E. Houfek, R.J. Ellingson, On the reliability of clinical EEG interpretation, J. Nerv. Ment. Dis. 128 (1959) 425 – 437.
www.elsevier.com/locate/ijmedinf
Technical communication
A computer-based information system for epilepsy and electroencephalography N.B. Finnerup, A. Fuglsang-Frederiksen *, P. Røssel, P. Jennum Department of Clinical Neurophysiology, Gentofte Hospital, Uni6ersity of Copenhagen, DK-2900 Hellerup, Denmark Received 4 June 1998; received in revised form 3 December 1998; accepted 15 December 1998
Abstract This paper describes a standardised computer-based information system for electroencephalography (EEG) focusing on epilepsy. The system was developed using a prototyping approach. It is based on international recommendations for EEG examination, interpretation and terminology, international guidelines for epidemiological studies on epilepsy and classification of epileptic seizures and syndromes and international classification of diseases. It is divided into: (1) clinical information and epilepsy relevant data; and (2) EEG data, which is hierarchically structured including description and interpretation of EEG. Data is coded but is supplemented with unrestricted text. The resulting patient database can be integrated with other clinical databases and with the patient record system and may facilitate clinical and epidemiological research and development of standards and guidelines for EEG description and interpretation. The system is currently used for teleconsultation between Gentofte and Lisbon. © 1999 Elsevier Science Ireland Ltd. All rights reserved. Keywords: EEG; Epilepsy; Information system; Database; Standardisation; Telecommunication
1. Introduction Clinical information databases offer several advantages in clinical research because of accurate and timely data and clinical details. They can be used to investigate clinical epi* Corresponding author. Tel.: +45-39-773429; fax: + 4539-777636. E-mail address: [email protected] (A. FuglsangFrederiksen)
demiology, risk assessment, post-marketing surveillance of drugs, practice variation, resource use, quality assurance and decision analysis. In addition they can be used to identify subjects for prospective studies [1,2]. Furthermore databases might be useful in daily routine because of standardised methods for data acquisition and time saved due to avoidance of duplication of information [2,3]. They can also be useful when data has
1386-5056/99/$ - see front matter © 1999 Elsevier Science Ireland Ltd. All rights reserved. PII: S 1 3 8 6 - 5 0 5 6 ( 9 9 ) 0 0 0 0 2 - 7
128
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
to be transferred between different centres. Several large clinical information databases have been established [1,4]. Within electromyography there is a European database for neuromuscular diseases [5]. A comprehensive EEG information system including a database and user interface does not exits. The purpose of this project was to develop a standardised computer-based system with a common structure for qualitative visual electroencephalogram (EEG) description and interpretation and for collection of epilepsy data. 2. About Prestige The epilepsy and EEG information system was developed as part of an European multicentre project PRESTIGE, Guidelines in Healthcare, which is a project in the European Commissions’ Telematics Applications Programme, DG XIII.C4–Telematics Applications for Health, Project HC 1040. The aim of PRESTIGE is to deploy healthcare telematics technology to assist in the generation, dissemination and routine application of research-based and consensus-based guidelines, and thus bridge the gap between research and everyday clinical practice. As part of the Neurology subproject —Information technology support of guidelines for the management of epilepsy—a teleconsultation in EEG between Lisbon and Gentofte was needed where clinical EEG cases could be discussed. The purpose was to specify a database structure for the representation of EEG data and to develop a tool for EEG teleconsultation.
ratories a general database structure was specified. During a pre-study the description of user needs were described by means of scenarios. These scenarios were developed by review of the literature and from answers to questionnaires about examination techniques, EEG evaluation, and epilepsy data from mainly Danish neurologists and neurophysiologists but also from neurophysiologists in Portugal, Italy and UK. In this way an attempt was made to cover various user requirements. The structure and terminology were based on international guidelines. The structure and terminology for EEG examination and evaluation follows the recommendations from the American Electroencephalographic Society (AEGGS), the International Federation of Societies for Electroencephalography and Clinical Neurophysiology (IFSECN) and the American Society for Testing and Materials [6–9]. The epilepsy data is based on guidelines from the International League Against Epilepsy (ILAE) for epidemiological studies on epilepsy [10], classification of epileptic seizures [11] and classification of epileptic syndromes [12]. Diagnoses are classified according to the International Classification of Diseases and Health Related Problems (ICD 10). The system was developed in Microsoft Access 97 for Windows 95 as a run-time module using a prototyping approach. Several prototypes were designed during the initial phase. In this way development and evaluation was interactive between computer scientists and physicians and feedback was sought throughout the development process.
4. The structure of the system 3. Development As to collect and exchange the heterogeneous EEG patient cases from different labo-
The system is divided into three main groups of data: (1) introduction; (2) clinical information; and (3) EEG. The latter is fur-
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
ther subdivided into three subgroups (3a) EEG description, (3b) EEG interpretation and (3c) final diagnosis. Each group is divided into modules (Fig. 1). The system includes the description and interpretation of the EEG and the epilepsy data; the viewing of EEGs is not part of the system. (1) Introduction: Main options: the user has to select whether to evaluate an examination or to create/edit an examination. General information: this includes information about the patient such as name, date of birth and sex and test information such as EEG identification number and date, EEG type, electrode sites and electroencephalographer. (2) Clinical information: this includes the epilepsy part of the system, which can be used separately. Referral information: includes referring department, date of referral, and referral diagnosis. Clinical data is classified into medical history, medication, physical examination and ancillary tests. Epilepsy-data: further epilepsy relevant data such as possible aetiology and precipitating factors. Epilepsy-classification: a classification of the epilepsy or epileptic syndrome and a classification of epileptic seizures, seizure frequency and date of first and last seizure. (3) EEG: the EEG data is hierarchically structured. The EEG description and EEG interpretation are based on the EEG, whereas the final diagnosis also should take ‘the clinical information’ as described above into account. (3a) The EEG description: this is the lowest level in the diagnostic hierarchy and should include all the characteristics of the record presented in an objective way, avoiding as much as possible judgement about their significance. It includes: General clinical obser6ations: clinical observations made at the beginning of recording e.g. a description of the level of consciousness,
129
respiration and vital signs. EEG acti6ity and seizure description: First an EEG activity is selected from a list, e.g. spike, alpha rhythm or 14 and 6 Hz positive burst. By selecting an activity (e.g. 14 and 6 Hz positive burst) some judgement about its significance is already made, but this possibility was chosen to keep the system relatively simple. Next step is a description of the activities, which includes, e.g. frequency, amplitude, symmetry, location, rhytmicity, synchronicity, amount, relation to activations, reactivity and occurrence (intermittent, periodic, continuous) (Fig. 2). Any seizure (the term includes nonepileptic seizures) observed during recording are described by selecting symptoms and signs from a list, e.g. blank stare or hyperventilation, pallor and sweating. The seizure is then described by, e.g. location, duration or postictal changes. It is also possible to relate EEG activities and seizures. (3b) The EEG interpretation: includes: Acti6ity and seizure conclusion: this is the second level in the hierarchy. It will show a summary of the findings. The summary leads to a pathophysiological interpretation for each activity such as normal or focal or epileptogenic abnormal. Any seizure is interpreted e.g. as absence seizure with impairment of consciousness only or hyperventilation syndrome. EEG conclusion: This third level in the hierarchy is an impression regarding the normality or grade of abnormality of the record. It includes diagnoses that the EEG might be suggestive or diagnostic of, e.g. absence epilepsy or alpha coma. It includes recommendations for new examinations and comparisons with previous EEGs. (3c) Final diagnosis: this is the fourth and highest level in the diagnostic hierarchy and is a correlation of the EEG findings with ‘the clinical information’ suggesting a final diag-
130 N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
Fig. 1. Schematic representation of the menu hierarchy with the major pathways of the electroencephalography (EEG) and epilepsy information system.
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
nosis, e.g. G40.3 Childhood absence epilepsy, and for epilepsies it includes a syndrome classification. Most of the data is entered as coded data, but since this is in many instances too limited to express nuances, unrestricted text is added in a comment field on most of the screens. When possible some data are automatically deduced, e.g. age of the patient and the system has automatically cross-checking, e.g. for blood pressure the systolic must be higher than the diastolic blood pressure etc. Some data is hidden and appear only when relevant, e.g. occurrence, selection and description of a seizure will be shown only when a related seizure is selected in the activity de-
131
scription (Fig. 2). When a given patient is registered more than once the examinations are treated as separate entities since this version of the system is designed primarily for exchange of patients for consultation.
5. Functions of the system The reasons for the development of the computer-based epilepsy and EEG information system were to support 1. Teleconsultation: supplying a database structure for the representation of EEG data facilitating inter-laboratory exchange
Fig. 2. Description of an electroencephalography (EEG) activity, is this case delta activity. An interface of the epilepsy and EEG information system.
132
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
of data between EEG laboratories in Europe as part of the PRESTIGE program. 2. Research: patient data stored in the system (collected for research purposes or in daily routine) will be easily accessible and usable for research purposes within the domain of epilepsy and EEG. 3. Daily routine: supporting the daily routine of the neurologist and neurophysiologist as part of a medical record. In the future it is planned to use the system to produce EEG reports and integrate it with a common patient record system. 4. Standardisation: presenting a tool for facilitation development and discussion of guidelines and standards for EEG examinations and evaluations.
5.1. Teleconsultation Two separate elements are telecommunicated. (1) An examination from the information system consisting of patient data, EEG description and EEG conclusion. In the system there is a function called ‘export examination’. This function is used to generate an ASCII file containing a given examination. (2) An EEG curve from a pre-agreed digital EEG machine. For almost every digital EEG machine a limited reader station can be supplied for the specific format and thus be used by others. All information leaving the local area network (LAN) can be hacked. Therefore all information is sent anonymous without patient ID in order to secure the patient and encryption becomes unnecessary. There are then two files. One in ASCII format and one in a pre-agreed EEG format. The only connection between the two files is a list number that is assigned by the user. The most obvious method for transportation of the files is the e-mail system provided by the Internet. It will clearly be an advantage to pack the digital EEG file of 20-40 Mb. data.
The consultant views the EEG on a reader station and inputs his evaluation on his local version of the information system. After evaluation the consultant either exports the data containing his/her evaluation into ASCII and returns it by Internet (offline consultancy) or gives his/hers advice by the telephone (online consultancy). Currently the teleconsultation possibilities of the system between Gentofte Hospital and Hospital Egas Moniz, Lisbon are being evaluated.
5.2. Research purposes The program can be used for clinical and epidemiological research. All data collected using the EEG case collection tool are stored in a database. All coded data can be easily retrieved for use to investigate clinical epidemiology, practice variation, quality assurance, etc. Such data includes for example referral diagnosis, specific epileptic syndromes, seizure frequency, medication, other epilepsy relevant data such as aetiology and previous operation for epilepsy, EEG activities, EEG conclusions and final diagnoses. A pilot study of inter-observer variability in the interpretation of EEG recordings is used as a preliminary evaluation of the system. A random sample of EEG recordings obtained from the Department of Neurophysiology at Gentofte hospital are presented to three specialists in neurophysiology from two departments, Department of Neurophysiology at Gentofte hospital and at Filadelfia hospital in Dianalund, Denmark. The neurophysiologists describe and interpret the records as if they were making a routine EEG report (except that it only includes the description and interpretation of the EEG and not the clinical correlation). Agreement on several factors used in the interpretation of EEGs are studied such as overall assessment of the EEG, exact pattern expression, pres-
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
ence of epileptiform or ictal changes or presence of a focus.
5.3. Supporting daily routine The program can be integrated with clinical databases and with the patient record system. An interface needs to be programmed to interact with the database. The easiest solution in most cases is to use Open Database Connection (ODBC). The referral information part including all clinically relevant epilepsy data can be used separately. When used in the department of neurophysiology, the technician initially fills out the general and referral information forms using information from the referring physician. If the system is part of a common database the referral information will already be available from the neurology department in electronic form. Then the patient’s state of consciousness at the onset of the record and description of any seizure during recording is filled in. As usual the technician also makes a description an interpretation of the EEG. The physician then makes a description, interpretation and final diagnosis. If the system is not part of a common medical record, then selected items might be printed serving as the EEG report. The use of the program in everyday practice is evaluated by an inquiry, which covers the functionality and usability of the system, the fastness, the user interface, the structure and the options available. It is planned to extend the evaluation to include physicians from different laboratories in Europe in order to meet various user requirements in the future.
5.4. Standardisation The use of guidelines for medical practice has high priority in many countries, as it is
133
believed to improve the quality of examinations by standardisation. Several international guidelines exist within the domains of epilepsy and EEG [6–12]. Nonetheless questionnaires to neurophysiologists in Europe and review of the literature reveal differences in EEG practice and definition of terms, and studies have shown variation in EEG interpretation [13–18]. Also epidemiological research on epilepsy often lacks agreement regarding the most basic concepts, and definitions of epilepsy, seizures and independent variables often are not elaborated [10]. It seems that marked variations in practice patterns still exist which leads to concerns about differences in the quality of patient care. Studies on variation in interpretation of EEGs are a prerequisite for standardisation. Databases can help in the identification of differences in clinical care and in patient outcome and may contain data that possibly explains the causes for these differences. They can be used to quantify what portion of the variation is attributable to patient differences and what is due to differences in physician practice pattern [1]. The international guidelines on EEG practice and terminology implemented in the information system will force the physicians to consider using these. Confrontation of clinicians with standards encourages discussion and evaluation of the usability of these and may lead to recommendations for changes or further studies.
Acknowledgements This project was supported by Prestige. We wish to thank Søren Vingtoft, DSI, Institute for Public Health Service, Copenhagen, Denmark, Mario Veloso, Department of Neurology, Hospital Egas Moniz, Lisbon, Portugal and Lars Gottlieb, Hillerød Hospital, Den-
134
N.B. Finnerup et al. / International Journal of Medical Informatics 55 (1999) 127–134
mark for helpful suggestions during the development. We also wish to thank I.S. Schofield and P.R.W. Fawcett, Department of Clinical Neurophysiology, Newcastle General Hospital, Newcastle upon Tyne, UK and R. Liguori, Institute of Neurology, University of Bologna, Bologna, Italy for sending examples of their EEG reports.
References [1] W.M. Tierney, C.J. McDonald, Practice databases and their uses in clinical research, Stat. Med. 10 (1991) 541–557. [2] P. Griep, N. Van den Berg, J. Doelman, R. Starrenburg, An epilepsy information system to support routine and research, Int. J. Biomed. Comput. 42 (1996) 135–141. [3] M.D. Bej, R.C. Burgess, An extensive epilepsy monitoring database, J. Clin. Neurophysiol. 14 (5) (1997) 449. [4] C. Confavreux, D.A.S. Compston, O.R. Hommes, W.I. McDonald, A.J. Thomson, EDMUS, a European database for multiple sclerosis, J. Neurol. Neurosurg. Psychiatr. 55 (1992) 671–676. [5] B. Johnsen, A. Fuglsang-Frederiksen, S. Vingtoft, P. Fawcett, I. Schofield, R. Liguori, W. Nix, G. Otte, G. Sieben, M. Veloso, A. Vila, An European database for neuro-muscular diseases (Abstract), Electroenceph. Clin. Neurophysiol. 2 (1993) S100. [6] AEEGS: American Electroencephalographic Society. Guidelines in EEG, evoked potentials and polysomnography. J. Clin. Neurophysiol. 1 (1994) 1–147. [7] IFSECN. Recommendations for the Practice of Clinical Neurophysiology, Elsevier, Amsterdam, 1983.
.
[8] G.E. Chatrian, L. Bergamini, M. Dondey, et al., A glossary of terms most commonly used by clinical electroencephalographers, Electroencephalogr. Clin. Neurophysiol. 37 (1974) 538 – 548. [9] ASTM E1467-92: American Society for Testing and Materials. Standard specification for transferring digital neurophysiological data between independent computer systems. In: Annual Book of ASTM Standards, 1992, pp. 1 – 109. [10] ILAE. Guidelines for epidemiologic studies on epilepsy. Epilepsia 34(4) (1993) 592 – 596. [11] ILAE. Proposal for revised clinical and electroencephalographic classification of epileptic seizures. From the Commission on Classification and Terminology of the International League Against Epilepsy. Epilepsia 22 (1981) 489 – 501. [12] ILAE. Proposal for revised classification of epilepsies and epileptic syndromes. Commission on Classification and Terminology of the International League Against Epilepsy, Epilepsia 30 (1989) 389– 399. [13] R.H. Woody, Inter-judge reliability in clinical electroencephalography, J. Clin. Psychol. 24 (1968) 251 – 256. [14] J. Volavka, M. Matousek, S. Feldstein, et al., The reliability of EEG assessment, EEG EMG 4 (1973) 123 – 130. [15] J. Volavka, M. Matousek, J. Roubicek, et al., The reliability of visual EEG assessment, Electroenceph. Clin. Neurophysiol. 31 (1975) 294. [16] S.C. Little, S.L. Raffel, Intra-rater reliability of EEG interpretation, J. Nerv. Ment. Dis. 135 (1962) 77 – 81. [17] R.H. Blum, A note on the reliability of electroencephalographic judgements, Neurology 4 (1954) 143 – 146. [18] E.E. Houfek, R.J. Ellingson, On the reliability of clinical EEG interpretation, J. Nerv. Ment. Dis. 128 (1959) 425 – 437.