- Email: [email protected]
Protocols and guides, tools1
International Journal of Medical Informatics 52 (1998) 117 – 122
Protocols and guides, tools1 Attila Naszlady 2 National Institute of Pulmonlogy, H-1529, Budapest, Hungary
Abstract The author describes in the first part of the review the definitions and relations of the occurring concepts. In the second part a short history of the topic is overviewed. The third part is dealing with the electronic patient record based development of guidelines in addition what are the relations among guidelines, protocols, tools, knowledgebased systems, diagnosis supporting systems, expert systems, outcome analysis and artificial intelligence. A short review of what was presented in the MIE ’97 in this area is finally described and the Session Chairman’s conclusion. © 1998 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Clinical guidelines; Protocols; Patient record; DSS
1. Introduction The industrial society era of mankind has been followed by the so called post-industrial one the characteristic feature of which is automation and computerisation. Medicine in its theory and practice has also been involved into this tendency of our age. ‘Towards the Information Society [1] the technological progress now enables us to collect, store, process, retrieve and communicate
1 Chairman’s introduction on Session 2 of MIE ’97 - edited version. 2 President of the European Federation for Medical Informatics.
information in whatever form it may take— oral, written or visual—unconstrained by distance, time and volume’. Health, however, is not so unequivocal product as an industrial one. In patient care the diagnostic procedure is describable as a decision tree but the branchings have rather probabilistic than deterministic feature. That is the reason why the probability theorem of Bayes has been introduced in medicine, for supporting the differential diagnostics of the congenital heart diseases in Homer Warner’s fundamental work first time in 1961 [2]. It seems to be the starting point for automation and computerisation of standardised medical diagnostics.
1386-5056/98/$ - see front matter © 1998 Elsevier Science Ireland Ltd. All rights reserved. PII S1386-5056(98)00130-0
118
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
2. Relations of concepts Expert systems (XS) often referred to as decision support systems (DSS), nevertheless the guidelines, protocols have also the same roles i.e. supporting decisions for optimising the sequence of steps in clinical practice. Clinical practice guidelines are ‘systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances’ [3]. For sharing and disseminating this knowledge guidelines, protocols can be regarded as appropriate and effective tools. Medical knowledge sharing [4] aiming good clinical practice can be realised by specification of care which proved to be effective in practice combined with knowledge, based on experts’ opinion and /or scientific evidence The path, however, is very long from theory to practice and from clinical practice to descriptive guidelines or prescriptive protocols. In addition the vertical loss of information along this pathway may be remarkable [5]. Medical guideline is a device as a scheme for directing a doctor in his/her conduct of operation and to support decision in clinical environment especially at emergency situation [6,7]. Protocols are essentially conceptual models of medical diagnostic and/or therapeutic interventions. DSS should improve health outcomes by enabling real time access to care guidelines.
opinions are generally used in present medical practice but in its ancient form related rather to the behaviour of the physician, than to single diseases. The guidelines start from situations encountered by the health professionals. An Act of (US) Congress established the Agency for Health Care Policy and Research (AHCPR) in 1989 to develop and promote practice guidelines [8]. A quality related overview of this topic was published as early as 1990 [9]. A comprehensive review of literature of scientific trials of the use of clinical guidelines including examples of computerised guideline implementation appeared in 1993 [10]. For developers of guidelines in primary care Guideline Skill Course was created by the UK Royal College of General Practitioners in 1994. The number of guidelines increased exponentially e.g. only in Cardiology 54 guidelines were edited within the two years of 1994–95 [11]. A state-of-the-art publication was in the Proceedings of the 1994 AIM COM Conference [12]. Also a wide range overview is in the series of Technology and Informatics in 1995 [13]. On MIE ’96 Congress among other papers the DILEMMA project of the EC AIM and the PRESTIGE project of the EC Fourth Framework Telematics Applications programmes were presented [14], focusing on the efficiency, quality and outcome of using guidelines, protocols as knowledge representation. The interest is directing more and more towards telecommunication of guidelines recently.
3. History of decision support Transportation of experiences is as old as human community. Consultation may also be regarded as a kind of decision support and is commonly used for hundreds of years, typically in verbal form. Diagnostic and/or therapeutic advises in written form as second
4. Construction of guidelines Principally there are two possibilities for standardisation of clinical thinking: an authoritative one and a data-analytic one. The former resulted in many attempts to con-
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
struct expert systems by collecting opinions from outstanding professionals of the problem in question. The data-analytic systems contain collected experiences, then tried to formulate into rules and finally resulted in guidelines, protocols [14]. Guideline constructors prefer to use randomised clinical trials and their analyses. ‘Large randomised, controlled trials are generally considered the gold standard in evaluation of clinical interventions. However, since such trials are not always available, clinicians increasingly rely on meata-analysis to support their choice of clinical strategies. Critics have emphasised the intrinsic weakness of meata-analysis’ [15]. (A special field of guides is the trial guide i.e. a guide for guidelines [16]). To develop a knowledge structuring tool and its appropriate application needs close co-operation between clinicians and knowledge engineers. Data acquisition and collection require reliable patient documentation system possibly well defined electronic health care record (EHCR). An EHCR the most fundamental document in health care should be in close relation to the individual practical, clinical activities controlled by protocols or directed by guides and as a tool it should serve a basis for risk/benefit estimation (scientific aspect) as well as for cost/effectiveness calculation (economic aspect). Ideally an EHCR is as complex as the patient’s problem is. Since a protocol is the result of a general abstraction from optimum clinical practices—which is not equal to the best one, because this latter is not always available—therefore in an actual patient’s care it should be individually tailored. Protocols, guides and tools should be based on both experience and logic. Logic may be equally used, however, ‘cloning solution’ means less adaptivity for unexpected requirements. Phalanxter reasoning can be a
119
real danger. On the other side experience is provider dependent too. It might only harmonise, interface but not completely integrate or homogenise doctor’s opinion based on their own experience. An additional problem is the management of a protocol updating from the appropriate knowledge based system according to speciality. In such a personal care management data and derived informations should be maximally reliable and might contain as few as possible ambiguities. Information carriers in medicine are texts, signs, images. Text may be free and/or structured, representing mainly the patient history and actual physical findings in his/her status. Signal curves as amplitude/time functions recorded during rest and stress tests are used to assess adaptivity of the patient similar to a system. Images, pictures as X-ray, ultrasound, nuclear, magnetic resonance, thermographic, near infrared etc. represent structural alterations and depending on their reversibility or irreversibility help to define expectable outcome i.e. the prognosis. Consequently EHCR must be a standardised multimedia object [17], which is communicable, hence available in shared care, therefore guidelines, protocols should also refer to multimedia methodologies. Multimedia presentations require standardisation’s of the other two information carriers: signs and images. Out of EEG and EKG standardised description according to ICD10, in the EC AIM program out of five DDS projects four projects were dealing with signal processing, including interpretation too [18]. For images there is an on-going harmonisation between the American standard the ACR-NEMA and the European one named DICOM resulted in DICOM III. Both for diagnosis and teaching a software has been developed which can incorporate time-related signals and the spatial location of their sources in 2D or 3D images [19].
120
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
A further requirement is commonly usable terminology. Medical terms cannot be arranged in a perfectly unequivocal hierarchy, so it is impossible to fit them to an up-todown architecture of medical concepts. Another way of saying their architecture itself does not form a concept-graph expandable in a single well defined plane. Arguing for this statement let us consider only the word of diagnosis. It has at least three different meanings. It may be (1) an expression of the essentials of a disease (theoretical point); (2) the doctor’s opinion on the essentials of a disease which is not necessarily the most appropriate (practical point); and (3) purely an operational category characterised by an ‘if -then’ implication-according to the Boolean algebra-expressing only: if I find A then I have to do B (e.g. hypertension treatment).
5. The usability of guidelines, protocols When a practitioner is looking for an appropriate guideline or protocol he/she should prejudice a working-diagnosis in order to find the adequate guide just that one which could be achieved only at the end of executing a diagnostic protocol. For these cases much better to use symptom-driven guidelines instead of diagnosis directed ones. Several studies have documented previously the limited impact of clinical guidelines on concrete clinical problem-solvings [20,21]. A useful applications of guidelines are when laboratory tests are requested [22]. Not only for rationalisation of ordering, but being a knowledge based system it is also effective in improving laboratory efficiency as well as helps to regulate laboratory work flow and to calculate management capacity [23]; in addition LUMPS system ‘provides feedback of laboratory usage facilitating refinements of guidelines’ themselves [24].
Another advantage of existing protocols and guidelines is that they may serve the medical education and inversely there are guidelines for curricula in health informatics [25].
6. Perspectives Application of KBS to the use of clinical guidelines seems to remain a worthwhile objective for research in medical informatics. Following the failure of promoting the widespread use of the paper-based guidelines, attempts have been carried out to yield expert system shells as e.g. MILORD and EQUANT are [26,27] and ‘from GALEN (1992–95) to GALEN-IN-USE creating an environment for the development of methodologies, skills, formalisms, software and awareness about conceptual modelling in health care’ [28]. The attention is directed more and more towards telecommunication for accessing diagnosis supporting tools in the future. The interest of developers in this field is turning to integration of guidelines, into the Hospital Information Systems [29] and intranet/internet usability [30], modelling [31,32], usability of mark-up languages [33,34] as well as organisational problems of knowledge sharing [35,36]. In his keynote speech on MIE ’97 Ilias Iakovidis emphasised that one of the main goal of Telematics in medicine is the support for shared care. We should not forget, however, that the applicability of any type of decision support system in clinical circumstances depends on the following seven criteria: One may provide a care on a patient only if it is scientifically (theoretically) possible clinically (practically) applicable actually (in that disease or combination of diseases) indicated
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
ethically (and also legally) allowable organisationally (institutionally) accessible financially (by resource management) available in agreement of the patient’s informed consent It seems reasonable to conclude that the time may now have come when emphasis should be put on the integration of all the tools which can improve patient shared care [37]. References [1] J. Kubosch, Towards the information society, in: M.F. Laires, M.J. Ladeira, J.P. Christensen (Eds.), Health in the New Communication Age, IOS Press 1995, pp. 23–26. [2] H. Warner, J. Am. Med. Assoc. 177 (1961) 177. [3] G. Collins, M. Veloso, The PRESTIGE project: implementing guidelines in health-care, in: J. Brender, J.P. Christensen, J.-R. Scherrer, P. McNair (Eds.), Medical Informatics Europe ’96, IOS Press 1996, pp. 887–891. [4] P.D. Clayton, T.A. Pryor, O. Wigertz, G. Hripcsak, Issues and structure for sharing medical knowledge among decision-making systems: the 1989 Arden Homestead Retreat, in: L.C. Kingsland (Ed.), Symposium on Computer Applications in Medical Care, Washington IEEE Comp. Soc. 1989. [5] E.A. Balas, D. Gardner, O. Hamdy, Z.R. Li, J.A. Mitchell, Multipurpose practice guideline modules for clinical decision analysis and quality improvement, in: R.A. Greenes, H. Peterson, D. Protti (Eds.), Proceedings of Medinfo ’95 1995, pp. 1001–1004. [6] R.A. Hollingworth, B. Richards, B. Doran, A CAL system for training and treatment in an ITU, in: J. Brender, J.O. Christensen, J.-R. Scherrer, P. McNair (Eds.), Medical Informatics Europe ’96, IOS Press Technology and Informatics Series No 34 1996, pp. 813–817. [7] P.H. Thoreux, P. LeBeux, J. Bouget, A microcomputer decision-support system for emergency medicine residents using hypermedia and artificial intelligence tools, in: P. Barahona, M. Veloso, J. Bryant (Eds.), Proceedings of MIE ’94 1994, pp. 180–185.
121
[8] M.J. Field, K.N. Lohr, Clinical Practice Guidelines, Edited by the National Academy Press, NY, Washington DC, 1992. [9] L.L. Leape, Practice guidelines and standards: An overview, Q. R. B. 2 (1990) 42 – 49. [10] E.A. Balas, S.M. Austin, G.D. Brown, J.A. Mitchell, Quality evaluation of controlled clinical information service trials, in: C. Safran (Ed.), Proceedings of the Symposium on Computer Application in Medical Care, McGraw-Hill, New York, 1993, pp. 586 – 590. [11] CARDIOSCAN, 1 (1996) 36 – 37. [12] C. Gordon, J.P. Christensen (Eds.), Proceedings of the AIM COM Conference Health Telematics for Clinical Guidelines and Protocols, 1994. [13] P. Nicklin, B. Frandji, Act management and clinical guidelines, in: C. Gordon, J.P. Christensen (Eds.), Studies in Health Telematics and Informatics 16 (1995) 117 – 124. [14] P. Barahona, Resource management constraints in guideline-based care, in: J. Brender, J.P. Christensen, J.-R. Scherrer, P. McNair (Eds.), MIE ’96 T and I Series No. 46 (1996) 920 – 924. [15] J. LeLorier, G. Gregoire, A. Benhaddad, J. Lapierre, F. Derderian, Discrepancies between meata-analyses and subsequent large randomised, controlled trials, New Engl. J. Med. 337 (1997) 536 – 542. [16] What is what. A cardiovascular guide. Edited by The Medicine Group (UK) Ltd. Published by Astra Ha¨ssle AB 1992. [17] Electronic healthcare record architecture, European standard, CEN/TC251, 1997. [18] P. Barahona, Introduction to project line 3 decision support, primary care and resource management, in: M.F. Laires, M.J. Ladeira, J.P. Christensen (Eds.), Health in the New Communication Age 1995, pp. 199 – 207. [19] J. Newell, F. Schuier, M. Staemmler, U. Hu¨bner, SAMMIE software applied to multimodal images and education, in: M.F. Laires, M.J. Ladeira, J.P. Christensen (Eds.), Health in the New Communication Age 1995, pp. 174 – 178 [20] J. Lomas, G.M. Anderson, K. Domnick-Pierre, E. Vayda, M.W. Enkin, W.J. Hanna, Do practice guidelines guide practice? The effect of a consensus statement on the practice of physicians, New Engl. J. Med. 321 (1989) 1306 – 1311. [21] T. Delamothe, Wanted: guidelines that doctors will follow, Br. Med. J. (1993) 218. [22] M. Peters, P.M.G. Broughton, The role of expert systems in improving the test requesting pattern of clinicians, Ann. Clin. Biochem. 30 (1993) 52 –59.
122
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
[23] M. Peters, J.R. Clark, J. Parekh, Automatic application of rule-based decision support; a specialist unit investigation manager, in: B. Richards (Ed.), Current Perspectives in Healthcare Computing. Surrey, UK. Br. J. Healthcare Comput. 1991, pp. 129–136. [24] D. Multimer, B.A. McCauley, P.G. Nightingale, M.F. Ryan, M. Peters, J.M. Neuberger, Computerised protocols for laboratory investigation and their effect on use of medical time and resources, J. Clin. Pathol. 45 (1992) 572–574. [25] A. Hasman, EDUCTRA Education and Training in Health Informatics B http:// www.mi.rulimburg.nl\ [26] P. Grifoni, C. Lalle, D. Luzi, D.M. Pisanelli, F.L. Ricci, L.D. Serbanati, Modeling the Management of Protocols as the kernel of a Healthcare Information System. In: R.A. Greenes, et al. (Eds.), Medinfo ’95 Proceedings IMIA (1995), pp. 502 – 505. [27] B. Richards, P. Hajek, J. Zvarova, R. Jirousek, J. Esteva, M. Lubicz, MUM managing uncertainty in medicine, in: M.F. Laires, M.J. Ladeira, J.P. Christensen (Eds.), Health in the New Telecommunication Age 1995, pp. 247–250. [28] E. Galeazzi, A. Rossi mori, F. Consorti, A. Errera, P. Merialdo, A cooperative methodology to build conceptual models in medicine, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 280–284. [29] M. Veloso, N. Estavao, P. Ferreira, R. Rodrigues, C. Telmo Costa, P. Barahona, From hospital information system components to the medical record and clinical guidelines and protocols, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 300 – 304. [30] A. Errera, P. Merialdo, G. Sindoni, G. Rumolo, Clinical protocol development using Inter/IntraNet technology: the FENERATE system, in: C. Pap-
.
[31]
[32]
[33]
[34]
[35]
[36]
[37]
pas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 305 – 308. S. Quaglini, L. Dazzi, R. Saracco, M. Stefanelli, F. Locatelli, An ontology-based framework for guideline-driven medical practice, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 309 – 313. C. Gordon, I. Herbert, P. Johnson, P. Nicklin, D. Pitty, P. Reeves, Telematics for clinical guidelines: a conceptual modelling approach, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 314 – 318. D. Pitty, C. Gordon, P. Reeves, A. Capey, P. Vieyra, T. Rickards, The place of SGML and HTML in building electronic patient records, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 329– 333. P. Hurlen, K. Skifjeld, Design and functional specification of the Synapses Federated Healthcare Record Server, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 334 – 338. D.M. Pisanelli, F. Consorti, P. Merialdo, SMART: a system supporting medical activities in real-time, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 343 – 348. V. Maojo, C. Herrero, F. Valenzuela, H. Crespo, P. Lazaro, A. Pazos, A JAVA-based multimedia tool for clinical practice guidelines, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 348 – 352. A. Naszlady, L. Kiss, E. Be´kefi, J. Rodek, G.G. Nagy, I. Szabo, G. Re´tai, Computerised Informatics from Population Mass Screening to Clinical Care Cardiologia Hungarica 18 (1989) 233 – 242 in Hungarian; in English cit. A. Naszlady, L. Horva´th, in Medinfo ’95 Proceedings 1995, pp. 521– 523.
Protocols and guides, tools1 Attila Naszlady 2 National Institute of Pulmonlogy, H-1529, Budapest, Hungary
Abstract The author describes in the first part of the review the definitions and relations of the occurring concepts. In the second part a short history of the topic is overviewed. The third part is dealing with the electronic patient record based development of guidelines in addition what are the relations among guidelines, protocols, tools, knowledgebased systems, diagnosis supporting systems, expert systems, outcome analysis and artificial intelligence. A short review of what was presented in the MIE ’97 in this area is finally described and the Session Chairman’s conclusion. © 1998 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Clinical guidelines; Protocols; Patient record; DSS
1. Introduction The industrial society era of mankind has been followed by the so called post-industrial one the characteristic feature of which is automation and computerisation. Medicine in its theory and practice has also been involved into this tendency of our age. ‘Towards the Information Society [1] the technological progress now enables us to collect, store, process, retrieve and communicate
1 Chairman’s introduction on Session 2 of MIE ’97 - edited version. 2 President of the European Federation for Medical Informatics.
information in whatever form it may take— oral, written or visual—unconstrained by distance, time and volume’. Health, however, is not so unequivocal product as an industrial one. In patient care the diagnostic procedure is describable as a decision tree but the branchings have rather probabilistic than deterministic feature. That is the reason why the probability theorem of Bayes has been introduced in medicine, for supporting the differential diagnostics of the congenital heart diseases in Homer Warner’s fundamental work first time in 1961 [2]. It seems to be the starting point for automation and computerisation of standardised medical diagnostics.
1386-5056/98/$ - see front matter © 1998 Elsevier Science Ireland Ltd. All rights reserved. PII S1386-5056(98)00130-0
118
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
2. Relations of concepts Expert systems (XS) often referred to as decision support systems (DSS), nevertheless the guidelines, protocols have also the same roles i.e. supporting decisions for optimising the sequence of steps in clinical practice. Clinical practice guidelines are ‘systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances’ [3]. For sharing and disseminating this knowledge guidelines, protocols can be regarded as appropriate and effective tools. Medical knowledge sharing [4] aiming good clinical practice can be realised by specification of care which proved to be effective in practice combined with knowledge, based on experts’ opinion and /or scientific evidence The path, however, is very long from theory to practice and from clinical practice to descriptive guidelines or prescriptive protocols. In addition the vertical loss of information along this pathway may be remarkable [5]. Medical guideline is a device as a scheme for directing a doctor in his/her conduct of operation and to support decision in clinical environment especially at emergency situation [6,7]. Protocols are essentially conceptual models of medical diagnostic and/or therapeutic interventions. DSS should improve health outcomes by enabling real time access to care guidelines.
opinions are generally used in present medical practice but in its ancient form related rather to the behaviour of the physician, than to single diseases. The guidelines start from situations encountered by the health professionals. An Act of (US) Congress established the Agency for Health Care Policy and Research (AHCPR) in 1989 to develop and promote practice guidelines [8]. A quality related overview of this topic was published as early as 1990 [9]. A comprehensive review of literature of scientific trials of the use of clinical guidelines including examples of computerised guideline implementation appeared in 1993 [10]. For developers of guidelines in primary care Guideline Skill Course was created by the UK Royal College of General Practitioners in 1994. The number of guidelines increased exponentially e.g. only in Cardiology 54 guidelines were edited within the two years of 1994–95 [11]. A state-of-the-art publication was in the Proceedings of the 1994 AIM COM Conference [12]. Also a wide range overview is in the series of Technology and Informatics in 1995 [13]. On MIE ’96 Congress among other papers the DILEMMA project of the EC AIM and the PRESTIGE project of the EC Fourth Framework Telematics Applications programmes were presented [14], focusing on the efficiency, quality and outcome of using guidelines, protocols as knowledge representation. The interest is directing more and more towards telecommunication of guidelines recently.
3. History of decision support Transportation of experiences is as old as human community. Consultation may also be regarded as a kind of decision support and is commonly used for hundreds of years, typically in verbal form. Diagnostic and/or therapeutic advises in written form as second
4. Construction of guidelines Principally there are two possibilities for standardisation of clinical thinking: an authoritative one and a data-analytic one. The former resulted in many attempts to con-
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
struct expert systems by collecting opinions from outstanding professionals of the problem in question. The data-analytic systems contain collected experiences, then tried to formulate into rules and finally resulted in guidelines, protocols [14]. Guideline constructors prefer to use randomised clinical trials and their analyses. ‘Large randomised, controlled trials are generally considered the gold standard in evaluation of clinical interventions. However, since such trials are not always available, clinicians increasingly rely on meata-analysis to support their choice of clinical strategies. Critics have emphasised the intrinsic weakness of meata-analysis’ [15]. (A special field of guides is the trial guide i.e. a guide for guidelines [16]). To develop a knowledge structuring tool and its appropriate application needs close co-operation between clinicians and knowledge engineers. Data acquisition and collection require reliable patient documentation system possibly well defined electronic health care record (EHCR). An EHCR the most fundamental document in health care should be in close relation to the individual practical, clinical activities controlled by protocols or directed by guides and as a tool it should serve a basis for risk/benefit estimation (scientific aspect) as well as for cost/effectiveness calculation (economic aspect). Ideally an EHCR is as complex as the patient’s problem is. Since a protocol is the result of a general abstraction from optimum clinical practices—which is not equal to the best one, because this latter is not always available—therefore in an actual patient’s care it should be individually tailored. Protocols, guides and tools should be based on both experience and logic. Logic may be equally used, however, ‘cloning solution’ means less adaptivity for unexpected requirements. Phalanxter reasoning can be a
119
real danger. On the other side experience is provider dependent too. It might only harmonise, interface but not completely integrate or homogenise doctor’s opinion based on their own experience. An additional problem is the management of a protocol updating from the appropriate knowledge based system according to speciality. In such a personal care management data and derived informations should be maximally reliable and might contain as few as possible ambiguities. Information carriers in medicine are texts, signs, images. Text may be free and/or structured, representing mainly the patient history and actual physical findings in his/her status. Signal curves as amplitude/time functions recorded during rest and stress tests are used to assess adaptivity of the patient similar to a system. Images, pictures as X-ray, ultrasound, nuclear, magnetic resonance, thermographic, near infrared etc. represent structural alterations and depending on their reversibility or irreversibility help to define expectable outcome i.e. the prognosis. Consequently EHCR must be a standardised multimedia object [17], which is communicable, hence available in shared care, therefore guidelines, protocols should also refer to multimedia methodologies. Multimedia presentations require standardisation’s of the other two information carriers: signs and images. Out of EEG and EKG standardised description according to ICD10, in the EC AIM program out of five DDS projects four projects were dealing with signal processing, including interpretation too [18]. For images there is an on-going harmonisation between the American standard the ACR-NEMA and the European one named DICOM resulted in DICOM III. Both for diagnosis and teaching a software has been developed which can incorporate time-related signals and the spatial location of their sources in 2D or 3D images [19].
120
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
A further requirement is commonly usable terminology. Medical terms cannot be arranged in a perfectly unequivocal hierarchy, so it is impossible to fit them to an up-todown architecture of medical concepts. Another way of saying their architecture itself does not form a concept-graph expandable in a single well defined plane. Arguing for this statement let us consider only the word of diagnosis. It has at least three different meanings. It may be (1) an expression of the essentials of a disease (theoretical point); (2) the doctor’s opinion on the essentials of a disease which is not necessarily the most appropriate (practical point); and (3) purely an operational category characterised by an ‘if -then’ implication-according to the Boolean algebra-expressing only: if I find A then I have to do B (e.g. hypertension treatment).
5. The usability of guidelines, protocols When a practitioner is looking for an appropriate guideline or protocol he/she should prejudice a working-diagnosis in order to find the adequate guide just that one which could be achieved only at the end of executing a diagnostic protocol. For these cases much better to use symptom-driven guidelines instead of diagnosis directed ones. Several studies have documented previously the limited impact of clinical guidelines on concrete clinical problem-solvings [20,21]. A useful applications of guidelines are when laboratory tests are requested [22]. Not only for rationalisation of ordering, but being a knowledge based system it is also effective in improving laboratory efficiency as well as helps to regulate laboratory work flow and to calculate management capacity [23]; in addition LUMPS system ‘provides feedback of laboratory usage facilitating refinements of guidelines’ themselves [24].
Another advantage of existing protocols and guidelines is that they may serve the medical education and inversely there are guidelines for curricula in health informatics [25].
6. Perspectives Application of KBS to the use of clinical guidelines seems to remain a worthwhile objective for research in medical informatics. Following the failure of promoting the widespread use of the paper-based guidelines, attempts have been carried out to yield expert system shells as e.g. MILORD and EQUANT are [26,27] and ‘from GALEN (1992–95) to GALEN-IN-USE creating an environment for the development of methodologies, skills, formalisms, software and awareness about conceptual modelling in health care’ [28]. The attention is directed more and more towards telecommunication for accessing diagnosis supporting tools in the future. The interest of developers in this field is turning to integration of guidelines, into the Hospital Information Systems [29] and intranet/internet usability [30], modelling [31,32], usability of mark-up languages [33,34] as well as organisational problems of knowledge sharing [35,36]. In his keynote speech on MIE ’97 Ilias Iakovidis emphasised that one of the main goal of Telematics in medicine is the support for shared care. We should not forget, however, that the applicability of any type of decision support system in clinical circumstances depends on the following seven criteria: One may provide a care on a patient only if it is scientifically (theoretically) possible clinically (practically) applicable actually (in that disease or combination of diseases) indicated
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
ethically (and also legally) allowable organisationally (institutionally) accessible financially (by resource management) available in agreement of the patient’s informed consent It seems reasonable to conclude that the time may now have come when emphasis should be put on the integration of all the tools which can improve patient shared care [37]. References [1] J. Kubosch, Towards the information society, in: M.F. Laires, M.J. Ladeira, J.P. Christensen (Eds.), Health in the New Communication Age, IOS Press 1995, pp. 23–26. [2] H. Warner, J. Am. Med. Assoc. 177 (1961) 177. [3] G. Collins, M. Veloso, The PRESTIGE project: implementing guidelines in health-care, in: J. Brender, J.P. Christensen, J.-R. Scherrer, P. McNair (Eds.), Medical Informatics Europe ’96, IOS Press 1996, pp. 887–891. [4] P.D. Clayton, T.A. Pryor, O. Wigertz, G. Hripcsak, Issues and structure for sharing medical knowledge among decision-making systems: the 1989 Arden Homestead Retreat, in: L.C. Kingsland (Ed.), Symposium on Computer Applications in Medical Care, Washington IEEE Comp. Soc. 1989. [5] E.A. Balas, D. Gardner, O. Hamdy, Z.R. Li, J.A. Mitchell, Multipurpose practice guideline modules for clinical decision analysis and quality improvement, in: R.A. Greenes, H. Peterson, D. Protti (Eds.), Proceedings of Medinfo ’95 1995, pp. 1001–1004. [6] R.A. Hollingworth, B. Richards, B. Doran, A CAL system for training and treatment in an ITU, in: J. Brender, J.O. Christensen, J.-R. Scherrer, P. McNair (Eds.), Medical Informatics Europe ’96, IOS Press Technology and Informatics Series No 34 1996, pp. 813–817. [7] P.H. Thoreux, P. LeBeux, J. Bouget, A microcomputer decision-support system for emergency medicine residents using hypermedia and artificial intelligence tools, in: P. Barahona, M. Veloso, J. Bryant (Eds.), Proceedings of MIE ’94 1994, pp. 180–185.
121
[8] M.J. Field, K.N. Lohr, Clinical Practice Guidelines, Edited by the National Academy Press, NY, Washington DC, 1992. [9] L.L. Leape, Practice guidelines and standards: An overview, Q. R. B. 2 (1990) 42 – 49. [10] E.A. Balas, S.M. Austin, G.D. Brown, J.A. Mitchell, Quality evaluation of controlled clinical information service trials, in: C. Safran (Ed.), Proceedings of the Symposium on Computer Application in Medical Care, McGraw-Hill, New York, 1993, pp. 586 – 590. [11] CARDIOSCAN, 1 (1996) 36 – 37. [12] C. Gordon, J.P. Christensen (Eds.), Proceedings of the AIM COM Conference Health Telematics for Clinical Guidelines and Protocols, 1994. [13] P. Nicklin, B. Frandji, Act management and clinical guidelines, in: C. Gordon, J.P. Christensen (Eds.), Studies in Health Telematics and Informatics 16 (1995) 117 – 124. [14] P. Barahona, Resource management constraints in guideline-based care, in: J. Brender, J.P. Christensen, J.-R. Scherrer, P. McNair (Eds.), MIE ’96 T and I Series No. 46 (1996) 920 – 924. [15] J. LeLorier, G. Gregoire, A. Benhaddad, J. Lapierre, F. Derderian, Discrepancies between meata-analyses and subsequent large randomised, controlled trials, New Engl. J. Med. 337 (1997) 536 – 542. [16] What is what. A cardiovascular guide. Edited by The Medicine Group (UK) Ltd. Published by Astra Ha¨ssle AB 1992. [17] Electronic healthcare record architecture, European standard, CEN/TC251, 1997. [18] P. Barahona, Introduction to project line 3 decision support, primary care and resource management, in: M.F. Laires, M.J. Ladeira, J.P. Christensen (Eds.), Health in the New Communication Age 1995, pp. 199 – 207. [19] J. Newell, F. Schuier, M. Staemmler, U. Hu¨bner, SAMMIE software applied to multimodal images and education, in: M.F. Laires, M.J. Ladeira, J.P. Christensen (Eds.), Health in the New Communication Age 1995, pp. 174 – 178 [20] J. Lomas, G.M. Anderson, K. Domnick-Pierre, E. Vayda, M.W. Enkin, W.J. Hanna, Do practice guidelines guide practice? The effect of a consensus statement on the practice of physicians, New Engl. J. Med. 321 (1989) 1306 – 1311. [21] T. Delamothe, Wanted: guidelines that doctors will follow, Br. Med. J. (1993) 218. [22] M. Peters, P.M.G. Broughton, The role of expert systems in improving the test requesting pattern of clinicians, Ann. Clin. Biochem. 30 (1993) 52 –59.
122
A. Naszlady / International Journal of Medical Informatics 52 (1998) 117–122
[23] M. Peters, J.R. Clark, J. Parekh, Automatic application of rule-based decision support; a specialist unit investigation manager, in: B. Richards (Ed.), Current Perspectives in Healthcare Computing. Surrey, UK. Br. J. Healthcare Comput. 1991, pp. 129–136. [24] D. Multimer, B.A. McCauley, P.G. Nightingale, M.F. Ryan, M. Peters, J.M. Neuberger, Computerised protocols for laboratory investigation and their effect on use of medical time and resources, J. Clin. Pathol. 45 (1992) 572–574. [25] A. Hasman, EDUCTRA Education and Training in Health Informatics B http:// www.mi.rulimburg.nl\ [26] P. Grifoni, C. Lalle, D. Luzi, D.M. Pisanelli, F.L. Ricci, L.D. Serbanati, Modeling the Management of Protocols as the kernel of a Healthcare Information System. In: R.A. Greenes, et al. (Eds.), Medinfo ’95 Proceedings IMIA (1995), pp. 502 – 505. [27] B. Richards, P. Hajek, J. Zvarova, R. Jirousek, J. Esteva, M. Lubicz, MUM managing uncertainty in medicine, in: M.F. Laires, M.J. Ladeira, J.P. Christensen (Eds.), Health in the New Telecommunication Age 1995, pp. 247–250. [28] E. Galeazzi, A. Rossi mori, F. Consorti, A. Errera, P. Merialdo, A cooperative methodology to build conceptual models in medicine, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 280–284. [29] M. Veloso, N. Estavao, P. Ferreira, R. Rodrigues, C. Telmo Costa, P. Barahona, From hospital information system components to the medical record and clinical guidelines and protocols, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 300 – 304. [30] A. Errera, P. Merialdo, G. Sindoni, G. Rumolo, Clinical protocol development using Inter/IntraNet technology: the FENERATE system, in: C. Pap-
.
[31]
[32]
[33]
[34]
[35]
[36]
[37]
pas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 305 – 308. S. Quaglini, L. Dazzi, R. Saracco, M. Stefanelli, F. Locatelli, An ontology-based framework for guideline-driven medical practice, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 309 – 313. C. Gordon, I. Herbert, P. Johnson, P. Nicklin, D. Pitty, P. Reeves, Telematics for clinical guidelines: a conceptual modelling approach, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 314 – 318. D. Pitty, C. Gordon, P. Reeves, A. Capey, P. Vieyra, T. Rickards, The place of SGML and HTML in building electronic patient records, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 329– 333. P. Hurlen, K. Skifjeld, Design and functional specification of the Synapses Federated Healthcare Record Server, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 334 – 338. D.M. Pisanelli, F. Consorti, P. Merialdo, SMART: a system supporting medical activities in real-time, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 343 – 348. V. Maojo, C. Herrero, F. Valenzuela, H. Crespo, P. Lazaro, A. Pazos, A JAVA-based multimedia tool for clinical practice guidelines, in: C. Pappas, N. Maglaveras, J.-R. Scherrer (Eds.), Medical Informatics Europe ’97 1997, pp. 348 – 352. A. Naszlady, L. Kiss, E. Be´kefi, J. Rodek, G.G. Nagy, I. Szabo, G. Re´tai, Computerised Informatics from Population Mass Screening to Clinical Care Cardiologia Hungarica 18 (1989) 233 – 242 in Hungarian; in English cit. A. Naszlady, L. Horva´th, in Medinfo ’95 Proceedings 1995, pp. 521– 523.