Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

Filip Velickovski, Luigi Ceccaroni, Josep Roca, Felip Burgos, Juan B Galdiz, Nuria Marina, Magí Lluch-Ariet, Filip Velickovski, Luigi Ceccaroni, Josep Roca, Felip Burgos, Juan B Galdiz, Nuria Marina, Magí Lluch-Ariet

Abstract

Background: The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway.

Objectives: The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow.

Methods: The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team.

Results: A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms.

Conclusions: Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.

Figures

Figure 1
Figure 1
CDSS architecture depicting internal modules, external user HIS, and external supporting Synergy-COPD systems.
Figure 2
Figure 2
Reasoning paradigm.
Figure 3
Figure 3
Adapted incremental software development model for the CDSS.
Figure 4
Figure 4
System interaction during confirmation of a COPD diagnosis in a primary care setting.

References

    1. Lodewijckx C, Sermeus W, Vanhaecht K, Panella M, Deneckere S, Leigheb F, Decramer M. Inhospital management of copd exacerbations: a systematic review of the literature with regard to adherence to international guidelines. J Eval Clin Pract. 2009;15(6):1101–1110. doi: 10.1111/j.1365-2753.2009.01305.x.
    1. Schoen C, Osborn R, How SKH, Doty MM, Peugh J. In chronic condition: experiences of patients with complex health care needs, in eight countries, 2008. Health Aff (Millwood) 2009;28(1):1–16. doi: 10.1377/hlthaff.28.1.w1.
    1. Sim I, Gorman P, Greenes RA, Haynes RB, Kaplan B, Lehmann H, Tang PC. Clinical decision support systems for the practice of evidence-based medicine. J Am Med Inform Assoc. 2001;8(6):527–534. doi: 10.1136/jamia.2001.0080527.
    1. Burgos F, Disdier C, de Santamaria EL, Galdiz B, Roger N, Rivera ML, Hervàs R, Durán-Tauleria E, Garcia-Aymerich J, Roca J. Telemedicine enhances quality of forced spirometry in primary care. Eur Respir J. 2012;39(6):1313–1318. doi: 10.1183/09031936.00168010.
    1. Castillo D, Guayta R, Giner J, Burgos F, Capdevila C, Soriano J, Barau M, Casan P. Copd case finding by spirometry in high-risk customers of urban community pharmacies: a pilot study. Respir Med. 2009;103(6):839–845. doi: 10.1016/j.rmed.2008.12.022.
    1. Vestbo J, Hurd SS, Agusti AG, Jones PW, Vogelmeier C, Anzueto A, Barnes PJ, Fabbri LM, Martinez FJ, Nishimura M. et al.Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: Gold executive summary. American journal of respiratory and critical care medicine. 2013;187(4):347–365. doi: 10.1164/rccm.201204-0596PP.
    1. Sittig DF, Wright A, Osheroff JA, Middleton B, Teich JM, Ash JS, Campbell E, Bates DW. Grand challenges in clinical decision support. Journal of biomedical informatics. 2008;41(2):387–392. doi: 10.1016/j.jbi.2007.09.003.
    1. Fox J, Glasspool D, Patkar V, Austin M, Black L, South M, Robertson D, Vincent C. Delivering clinical decision support services: there is nothing as practical as a good theory. Journal of biomedical informatics. 2010;43(5):831–843. doi: 10.1016/j.jbi.2010.06.002.
    1. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. Bmj. 2005;330(7494):765. doi: 10.1136/bmj.38398.500764.8F.
    1. Roshanov PS, Misra S, Gerstein HC, Garg AX, Sebaldt RJ, Mackay JA, Weise-Kelly L, Navarro T, Wilczynski NL, Haynes RB. C.C.D.S.S.S.R.T. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review. Implement Sci. 2011;6:92. doi: 10.1186/1748-5908-6-92.
    1. Kattan M, Crain EF, Steinbach S, Visness CM, Walter M, Stout JW, Evans R, Smartt E, Gruchalla RS, Morgan WJ. et al.A randomized clinical trial of clinician feedback to improve quality of care for inner-city children with asthma. Pediatrics. 2006;117(6):1095–1103. doi: 10.1542/peds.2005-2160.
    1. Plaza V, Cobos A, Ignacio-Garcia J, Molina J, Bergonon S, Garcia-Alonso F, Espinosa C. Cost-effectiveness of an intervention based on the global initiative for asthma (gina) recommendations using a computerized clinical decision support system: a physicians randomized trial. Medicina clínica. 2005;124(6):201–206.
    1. McCowan. I.R.F.W.G.H.G.T.C. Neville RG. Lessons from a randomized controlled trial designed to evaluate computer decision support software to improve the management of asthma. Informatics for Health and Social Care. 2001;26(3):191–201. doi: 10.1080/14639230110067890.
    1. Hoeksema LJ, Bazzy-Asaad A, Lomotan EA, Edmonds DE, Ramírez-Garnica G, Shiffman RN, Horwitz LI. Accuracy of a computerized clinical decision-support system for asthma assessment and management. Journal of the American Medical Informatics Association. 2011;18(3):243–250. doi: 10.1136/amiajnl-2010-000063.
    1. National Asthma Education and Prevention Program: Expert panel report 3 (epr-3): Guidelines for the diagnosis and management of asthma-summary report 2007. J Allergy Clin Immunol. 2007;120(5 Suppl):94.
    1. Wright A, Sittig DF. A framework and model for evaluating clinical decision support architectures. J Biomed Inform. 2008;41(6):982–990. doi: 10.1016/j.jbi.2008.03.009.
    1. Fox J, Thomson R. Decision support and disease management: a logic engineering approach. 1998. pp. 217–228.
    1. Peleg M, Tu S, Bury J, Ciccarese P, Fox J, Greenes RA, Hall R, Johnson PD, Jones N, Kumar A, Miksch S, Quaglini S, Seyfang A, Shortliffe EH, Stefanelli M. Comparing computer-interpretable guideline models: a case-study approach. J Am Med Inform Assoc. 2003;10(1):52–68. doi: 10.1197/jamia.M1135.
    1. Boxwala AA, Peleg M, Tu S, Ogunyemi O, Zeng QT, Wang D, Patel VL, Greenes RA, Shortliffe EH. Glif3: a representation format for sharable computer-interpretable clinical practice guidelines. J Biomed Inform. 2004;37(3):147–161. doi: 10.1016/j.jbi.2004.04.002.
    1. Isern D, Moreno A. Computer-based execution of clinical guidelines: a review. Int J Med Inform. 2008;77(12):787–808. doi: 10.1016/j.ijmedinf.2008.05.010.
    1. Tu SW, Hrabak KM, Campbell JR, Glasgow J, Nyman MA, McClure R, McClay J, Abarbanel R, Mansfield JG, Martins SM, Goldstein MK, Musen MA. Use of Declarative Statements in Creating and Maintaining Computer-interpretable Knowledge Bases for Guideline-based Care. 2006. pp. 784–788.
    1. Kawamoto K, Lobach DF. AMIA Annual Symposium Proceedings. Vol. 2005. American Medical Informatics Association; 2005. Design, implementation, use, and preliminary evaluation of sebastian, a standards-based web service for clinical decision support; p. 380.
    1. Fox J, Patkar V, Chronakis I, Begent R. From practice guidelines to clinical decision support: closing the loop. Journal of the Royal Society of Medicine. 2009;102(11):464–473. doi: 10.1258/jrsm.2009.090010.
    1. Fox J, Glasspool D, Modgil S. A canonical agent model for healthcare applications. Intelligent Systems, IEEE. 2006;21(6):21–28.
    1. Forgy CL. Rete: A fast algorithm for the many pattern/many object pattern match problem. Artificial intelligence. 1982;19(1):17–37. doi: 10.1016/0004-3702(82)90020-0.
    1. Bali M. Drools JBoss Rules 5.0: Developer's Guide. Packt Publishing, Birmingham, United Kingdom; 2009.
    1. CLIPS Website. 2013. [accessed August 24, 2014]
    1. JESS Website. 2013. [accessed August 24, 2014]
    1. Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of the general u.s. population. Am J Respir Crit Care Med. 1999;159(1):179–187. doi: 10.1164/ajrccm.159.1.9712108.
    1. Quanjer PH, Stanojevic S, Cole TJ, Baur X, Hall GL, Culver BH, Enright PL, Hankinson JL, Ip MSM, Zheng J, Stocks J. E.R.S.G.L.F.I. Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations. Eur Respir J. 2012;40(6):1324–1343. doi: 10.1183/09031936.00080312.
    1. Huertas Miguelanez MdlM, Ceccaroni L. A simulation and integration environment for heterogeneous physiology-models. e-Health Networking, Applications Services (Healthcom), 2013 IEEE 15th International Conference On. 2013. pp. 228–232.
    1. Huertas Miguelanez MdlM, Mora D, Cano I, Maier D, Gomez-Cabrero D, Lluch-Ariet M, Miralles F. Simulation Environment and Graphical Visualization Environment: a COPD use-case. BMC Journal of Translational Medicine. 2014;12(S2):S7.
    1. Maier D, Kalus W, Wolff M, Kalko SG, Roca J, Marin de Mas I, Turan N, Cascante M, Falciani F, Hernandez M, Villa-Freixa J, Losko S. Knowledge management for systems biology a general and visually driven framework applied to translational medicine. BMC Syst Biol. 2011;5:38. doi: 10.1186/1752-0509-5-38.
    1. Cano I, Tényi A, Schueller C, Wolff M, Huertas Miguelanez MdlM, Gomez-Cabrero D, Antczak P, Roca J, Cascante M, Falicani F, Maier D. The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research. BMC Journal of Translational Medicine. 2014;12(S2):S6.
    1. Wagner PD. Determinants of maximal oxygen transport and utilization. Annu Rev Physiol. 1996;58:21–50. doi: 10.1146/annurev.ph.58.030196.000321.
    1. Selivanov VA, Votyakova TV, Zeak JA, Trucco M, Roca J, Cascante M. Bistability of mitochondrial respiration underlies paradoxical reactive oxygen species generation induced by anoxia. PLoS Comput Biol. 2009;5(12):1000619. doi: 10.1371/journal.pcbi.1000619.
    1. Selivanov VA, Votyakova TV, Pivtoraiko VN, Zeak J, Sukhomlin T, Trucco M, Roca J, Cascante M. Reactive oxygen species production by forward and reverse electron fluxes in the mitochondrial respiratory chain. PLoS Comput Biol. 2011;7(3):1001115. doi: 10.1371/journal.pcbi.1001115.
    1. Cano I, Mickael M, Gomez-Cabrero D, Tegner J, Roca J, Wagner PD. Importance of mitochondrial in maximal {O2} transport and utilization: A theoretical analysis. Respiratory Physiology & Neurobiology. 2013;189(3):477–483. doi: 10.1016/j.resp.2013.08.020.
    1. Kawamoto K, Del Fiol G, Strasberg HR, Hulse N, Curtis C, Cimino JJ, Rocha BH, Maviglia S, Fry E, Scherpbier HJ, Huser V, Redington PK, Vawdrey DK, Dufour J-C, Price M, Weber JH, White T, Hughes KS, McClay JC, Wood C, Eckert K, Bolte S, Shields D, Tattam PR, Scott P, Liu Z, McIntyre AK. Multi-national, multi-institutional analysis of clinical decision support data needs to inform development of the hl7 virtual medical record standard. AMIA Annu Symp Proc. 2010;2010:377–381.
    1. Gomoi VS, Dragu D, Stoicu-Tivadar V. Virtual medical record implementation for enhancing clinical decision support. Studies in health technology and informatics. 2012;180:118.
    1. Fujii T, Dohi T, Fujiwara T. Proceedings of the 33rd International Conference on Software Engineering. ACM; 2011. Towards quantitative software reliability assessment in incremental development processes; pp. 41–50.
    1. Linkcare: The Integrated Health Care Shared Knowledge Community for Health Care Professionals. Linkcare; 2014. [accessed August 24, 2014]
    1. Infermed: Arezzo Pathways. Infermed; 2014. [accessed August 24, 2014]
    1. Jones P, Harding G, Berry P, Wiklund I, Chen W, Leidy NK. Development and first validation of the copd assessment test. European Respiratory Journal. 2009;34(3):648–654. doi: 10.1183/09031936.00102509.
    1. Mahler D, Wells CK. Evaluation of clinical methods for rating dyspnea. CHEST Journal. 1988;93(3):580–586. doi: 10.1378/chest.93.3.580.
    1. Duran-Tauleria E, Forastiere F, Janson C, Roca J, Viegi G, Weinmyer G, Anto J, the IMCA Group. Report on the Respiratory Health of the Elderly Population Living in Catalunya. Centre for Research in Environmental Epidemiology (CREAL), Barcelona; 2013. Centre for Research in Environmental Epidemiology (CREAL)
    1. Holton K, Hill S, Kearney M, Winter R, Moger A. Quality assured diagnostic spirometry (qads)-performance and competence. Am J Respir Crit Care Med. 2013;187:2836.
    1. Soriano JB. The gold rush. Thorax. 2013;68(10):902–903. doi: 10.1136/thoraxjnl-2013-203595.
    1. Burgos F, Melia U, Vallverdú MA, Velickovski F, Lluch-Ariet M, Caminal P, Roca J. Clinical Decision Support System to Enhance Quality Control of Forced Spirometry using Information and Communication Technologies. Journal of Medical Internet Research. 2014.
    1. Kuilboer MM, Van Wijk MA, Mosseveld M, Van Der Does E, Ponsioen BP, De Jongste JC, Overbeek SE, Van Der Lei J. Feasibility of asthmacritic, a decision-support system for asthma and copd which generates patient-specific feedback on routinely recorded data in general practice. Family practice. 2002;19(5):442–447. doi: 10.1093/fampra/19.5.442.
    1. Song B, Wolf K-H, Gietzelt M, Al Scharaa O, Tegtbur U, Haux R, Marschollek M. Pervasive Computing Technologies for Healthcare, 2009. IEEE; 2009. Decision support for teletraining of copd patients; pp. 1–6. PervasiveHealth 2009. 3rd International Conference On.
    1. Rosso R, Munaro G, Salvetti O, Colantonio S, Ciancitto F. Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. IEEE; 2010. Chronious: an open, ubiquitous and adaptive chronic disease management platform for chronic obstructive pulmonary disease (copd), chronic kidney disease (ckd) and renal insufficiency; pp. 6850–6853.
    1. Himes BE, Dai Y, Kohane IS, Weiss ST, Ramoni MF. Prediction of chronic obstructive pulmonary disease (copd) in asthma patients using electronic medical records. Journal of the American Medical Informatics Association. 2009;16(3):371–379. doi: 10.1197/jamia.M2846.
    1. Jafari S, Arabalibeik H, Agin K. Health Informatics and Bioinformatics (HIBIT), 2010 5th International Symposium On. IEEE; 2010. Classification of normal and abnormal respiration patterns using flow volume curve and neural network; pp. 110–113.
    1. Sahin D, Übeyli ED, Ilbay G, Sahin M, Yasar AB. Diagnosis of airway obstruction or restrictive spirometric patterns by multiclass support vector machines. Journal of medical systems. 2010;34(5):967–973. doi: 10.1007/s10916-009-9312-7.
    1. Stearns MQ, Price C, Spackman KA, Wang AY. Proceedings of the AMIA Symposium. American Medical Informatics Association; 2001. Snomed clinical terms: overview of the development process and project status; p. 662.
    1. World Health Organization: International Classification of Diseases (ICD-10) World Health Organization; 2014. [accessed August 24, 2014]
    1. Centres for Disease Control and Prevention: Race and Ethnicity Code Set Version 1.0. Centres for Disease Control and Prevention; 2000. [accessed August 24, 2014]
    1. Library of Congress: Codes for the Representation of Names of Languages. Library of Congress; 2014. [accessed August 24, 2014]

Source: PubMed

Sponsorit ja yhteistyökumppanit

Sairaudet

Huumeiden interventiot

3
Tilaa