Perspectives for Medical Informatics

 

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Summary

Objectives: Even though today most university hospitals have already implemented commercial hospital information systems and started to build up comprehensive electronic medical records, reuse of such data for data warehousing and research purposes is still very rare. Given this situation, the focus of this paper is to present an overview on exemplary projects, which have already tackled this challenge, reflect on current initiatives within the United States of America and the European Union to establish IT infrastructures for clinical and translational research, and draw attention to new challenges in this area.

Methods: This paper does not intend to provide a fully comprehensive review on all the issues of clinical routine data reuse. It is based, however, on a presentation of a large variety of historical, but also most recent activities in data warehousing, data retrieval and linking medical informatics with translational research.

Results: The article presents an overview of the various international approaches to this issue and illustrates concepts and solutions which have been published, thus giving an impression of activities pursued in this field of medical informatics. Further, problems and open questions, which have also been named in the literature, are presented and three challenges (to establish comprehensive clinical data warehouses, to establish professional IT infrastructure applications supporting clinical trial data capture and to integrate medical record systems and clinical trial databases) related to this area of medical informatics are identified and presented.

Conclusions: Translational biomedical research with the aim “to integrate bedside and biology” and to bridge the gap between clinical care and medical research today and in the years to come, provides a large and interesting field for medical informatics researchers. Especially the need for integrating clinical research projects with data repositories built up during documentation of routine clinical care, today still leaves many open questions and research challenges. Consideration of regulatory requirements, data privacy issues, data standards as well as people/organizational issues are prerequisites in order to vanquish existing obstacles.

• References

• 1 Ebidia A, Mulder C, Tripp B, Morgan MW. Getting data out of the electronic patient record: critical steps in building a data warehouse for decision support. Proc AMIA Symp 1999 pp 745-749.
  PubMedGoogle Scholar
• 2 Haug PJ, Gardner RM, Tate KE, Evans RS, East TD, Kuperman G, Pryor TA, Huff SM, Warner HR. Decision support in medicine: examples from the HELP system. Comput Biomed Res 1994; 27 (05) 396-418.
  CrossrefPubMedGoogle Scholar
• 3 Safran C, Rind DM, Sands DZ, Davis RB, Wald J, Slack WV. Development of a knowledge-based electronic patient record. MD Comput 1996; 13 (01) 46-54 63.
  PubMedGoogle Scholar
• 4 Müller ML, Ganslandt T, Eich HP, Lang K, Ohmann C, Prokosch HU. Integrating knowledge based functionality in commercial hospital information systems. Stud Health Technol Inform 2000; 77: 817-821.
  PubMedGoogle Scholar
• 5 Dexter PR, Perkins S, Overhage JM, Maharry K, Kohler RB, McDonald CJ. A computerized reminder system to increase the use of preventive care for hospitalized patients. N Engl J Med 2001; 345 (13) 965-970.
  CrossrefPubMedGoogle Scholar
• 6 Altman M. The clinical data repository: a challenge to medical student education. J Am Med Inform Assoc 2007; 14 (06) 697-699.
  CrossrefPubMedGoogle Scholar
• 7 Siegel E, Reiner B. Electronic teaching files: sevenyear experience using a commercial picture archiving and communication system. J Digit Imaging 2001; 14 2 Suppl 1 125-127.
  CrossrefPubMedGoogle Scholar
• 8 Scheese R. Data warehousing as a healthcare business solution. Healthc Financ Manage 1998; 52 (02) 56-59.
  PubMedGoogle Scholar
• 9 Gray GW. Challenges of building clinical data analysis solutions. J Crit Care 2004; 19 (04) 264-270.
  CrossrefPubMedGoogle Scholar
• 10 Lang M, Kirpekar N, Bürkle T, Laumann S, Prokosch HU. Results from data mining in a radiology department: the relevance of data quality. Medinfo 2007; 12 Pt (01) 576-580.
  PubMedGoogle Scholar
• 11 Lyman JA, Scully K, Harrison Jr JH. The development of health care data warehouses to support data mining. Clin Lab Med 2008; 28 (01) 55-71 vi.
  CrossrefPubMedGoogle Scholar
• 12 Tusch G, Müller M, Rohwer-Mensching K, Heiringhoff K, Klempnauer J. Data warehouse and data mining in a surgical clinic. Stud Health Technol Inform 2000; 77: 784-789.
  PubMedGoogle Scholar
• 13 Silver M, Sakata T, Su HC, Herman C, Dolins SB, O’Shea MJ. Case study: how to apply data mining techniques in a healthcare data warehouse. J Healthc Inf Manag 2001; 15 (02) 155-164.
  PubMedGoogle Scholar
• 14 Lang M, Bürkle T, Laumann S, Prokosch HU. Process Mining for Clinical Workflows: Challenges and Current Limitations. Andersen SK, Klein GO, Schulz S, Aarts J, Mazzoleni MC. (eds). eHealth Beyond the Horizon – Get IT There. IOS Press; 2008 pp 229-234.
  PubMedGoogle Scholar
• 15 Ledbetter CS, Morgan MW. Toward best practice: leveraging the electronic patient record as a clinical data warehouse. J Healthc Inf Manag 2001; 15 (02) 119-131.
  PubMedGoogle Scholar
• 16 Myers DL, Burke KC, Burke Jr JD, Culp KS. An integrated data warehouse system: development, implementation, and early outcomes. Manag Care Interface 2000; 13 (03) 68-72.
  PubMedGoogle Scholar
• 17 Breen C, Rodrigues LM. Implementing a data warehouse at Inglis Innovative Services. J Healthc Inf Manag 2001; 15 (02) 87-97.
  PubMedGoogle Scholar
• 18 Johnson SB, Chatziantoniou D. Extended SQL for manipulating clinical warehouse data. Proc AMIA Symp 1999 pp 819-823.
  PubMedGoogle Scholar
• 19 Bito Y, Kero R, Matsuo H, Shintani Y, Silver M. Interactively visualizing data warehouses. J Healthc Inf Manag 2001; 15 (02) 133-142.
  PubMedGoogle Scholar
• 20 Verma R, Harper J. Life cycle of a data warehousing project in healthcare. J Healthc Inf Manag 2001; 15 (02) 107-117.
  PubMedGoogle Scholar
• 21 Grant A, Moshyk A, Diab H, Caron P, de Lorenzi F, Bisson G, Menard L, Lefebvre R, Gauthier P, Grondin R, Desautels M. Integrating feedback from a clinical data warehouse into practice organisation. Int J Med Inform 2006; 75 3–4 232-239.
  CrossrefPubMedGoogle Scholar
• 22 Rubin DL, Desser TS. A data warehouse for integrating radiologic and pathologic data. J Am Coll Radiol 2008; 5 (03) 210-217.
  CrossrefPubMedGoogle Scholar
• 23 Junttila K, Meretoja R, Seppälä A, Tolppanen EM, Ala-Nikkola T, Silvennoinen L. Data warehouse approach to nursing management. J Nurs Manag 2007; 15 (02) 155-161.
  CrossrefPubMedGoogle Scholar
• 24 Ramick DC. Data warehousing in disease management programs. J Healthc Inf Manag. 2001; 15 (02) 99-105.
  PubMedGoogle Scholar
• 25 Muranaga F, Kumamoto I, Uto Y. Development of Hospital Data Warehouse for Cost Analysis of DPC Based on Medical Costs. Methods Inf Med 2007; 46 (06) 679-685.
  Article in Thieme ConnectPubMedGoogle Scholar
• 26 Barrett JS, Koprowski Jr SP. The epiphany of data warehousing technologies in the pharmaceutical industry. Int J Clin Pharmacol Ther 2002; 40 (03) S3-13.
  PubMedGoogle Scholar
• 27 Zhang Q, Matsumura Y, Teratani T, Yoshimoto S, Mineno T, Nakagawa K, Nagahama M, Kuwata S, Takeda H. The application of an institutional clinical data warehouse to the assessment of adverse drug reactions (ADRs). Evaluation of aminoglycoside and cephalosporin associated nephrotoxicity. Methods Inf Med 2007; 46 (05) 516-522.
  Article in Thieme ConnectPubMedGoogle Scholar
• 28 Hardison CD, Schnetzer T. Using information technology to improve the quality and efficiency of clinical trial research in academic medical centers. Qual Manag Health Care 1999; 7 (03) 37-44.
  CrossrefPubMedGoogle Scholar
• 29 Cuticchia AJ, Cooley PC, Hall RD, Qin Y. NIDDK data repository: a central collection of clinical trial data. BMC Med Inform Decis Mak 2006; 6: 19.
  CrossrefPubMedGoogle Scholar
• 30 Lee TJ, Pouliot Y, Wagner V, Gupta P, Stringer-Calvert DW, Tenenbaum JD, Karp PD. BioWarehouse: a bioinformatics database warehouse toolkit. BMC Bioinformatics 2006; 7: 170.
  CrossrefPubMedGoogle Scholar
• 31 Wang L, Zhang A, Ramanathan M. BioStar models of clinical and genomic data for biomedical data warehouse design. Int J Bioinform Res Appl 2005; 1 (01) 63-80.
  CrossrefPubMedGoogle Scholar
• 32 Côté RG, Jones P, Martens L, Kerrien S, Reisinger F, Lin Q, Leinonen R, Apweiler R, Hermjakob H. The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases. BMC Bioinformatics. 2007; 8: 401.
  CrossrefPubMedGoogle Scholar
• 33 Fischer M, Thai QK, Grieb M, Pleiss J. DWARF – a data warehouse system for analyzing protein families. BMC Bioinformatics 2006; 7: 495.
  CrossrefPubMedGoogle Scholar
• 34 Higgins SB, Jiang K, Plummer Jr WD, Edens TR, Stroud MJ, Swindell BB, Wheeler AP, Bernard GR. Pivot/Remote: a distributed database for remote data entry in multi-center clinical trials. Medinfo 1995; 8 Pt 2: 1097.
  PubMedGoogle Scholar
• 35 Wübbelt P, Fernandez G, Heymer J. Clinical trial management and remote data entry on the Internet based on XML case report forms. Stud Health Technol Inform 2000; 77: 333-337.
  PubMedGoogle Scholar
• 36 Meadows BJ. Eliciting remote data entry system requirements for the collection of cancer clinical trial data. Comput Inform Nurs 2003; 21 (05) 234-240.
  CrossrefPubMedGoogle Scholar
• 37 Brandt CA, Deshpande AM, Lu C, Ananth G, Sun K, Gadagkar R, Morse R, Rodriguez C, Miller PL, Nadkarni PM. Center for Medical Informatics.. TrialDB: A web-based Clinical Study Data Management System. AMIA Annu Symp Proc 2003 . p 794.
  PubMedGoogle Scholar
• 38 Sahoo U, Bhatt A. Electronic data capture (EDC) – a new mantra for clinical trials. Qual Assur 2003; 10 3–4 117-121.
  CrossrefPubMedGoogle Scholar
• 39 Velázquez I, Navarro X, Cobos A. Electronic data capture. Impact on the quality of the clinical research. Med Clin (Barc) 2004; 122 (01) 11-15.
  CrossrefPubMedGoogle Scholar
• 40 Schmier JK, Kane DW, Halpern MT. Practical applications of usability theory to electronic data collection for clinical trials. Contemp Clin Trials 2005; 26 (03) 376-385.
  CrossrefPubMedGoogle Scholar
• 41 Welker JA. Implementation of electronic data capture systems: barriers and solutions. Contemp Clin Trials 2007; 28 (03) 329-336.
  CrossrefPubMedGoogle Scholar
• 42 Kahn MG, Kaplan D, Sokol RJ, DiLaura RP. Configuration challenges: implementing translational research policies in electronic medical records. Acad Med 2007; 82 (07) 661-669.
  CrossrefPubMedGoogle Scholar
• 43 Dorda W, Kogler W. WAMAS – Statistische Auswertung einer patientenorientierten Datenbank. Statistical Software Newsletter 1977; 2: 54-58.
  PubMedGoogle Scholar
• 44 Wolf W, Dorda W, Sachs P, Graber E. WAMAS: On Line Evaluation of a Medical Database Under Consideration of Time-Relations. In: Begon F. (ed). Annals of the World Association for Medical Informatics. 1981 pp 231-235.
  PubMedGoogle Scholar
• 45 Dorda W. WAREL: A System for Retrieval of Clinical Data Considering the Course of Diseases. Methods Inf Med 1989; 28: 133-141.
  Article in Thieme ConnectPubMedGoogle Scholar
• 46 Dorda W. Data-Screening and Retrieval of Medical Data by the System WAREL. Methods Inf Med 1990; 29: 3-11.
  Article in Thieme ConnectPubMedGoogle Scholar
• 47 Grabner G. WAMIS – Wiener Allgemeines Medizinisches Informationssystem. Berlin: Springer; 1986
  Google Scholar
• 48 Dorda W, Gall W, Duftschmid G. Clinical data retrieval: 25 years of temporal query management at the University of Vienna Medical School. Methods Inf Med 2002; 41 (02) 89-97.
  Article in Thieme ConnectPubMedGoogle Scholar
• 49 Cimino C, Barnett GO, Hassan L, Blewett DR, Piggins JL. Interactive Query Workstation: standardizing access to computer-based medical resources. Comput Methods Programs Biome 1991; 35 (04) 293-299.
  PubMedGoogle Scholar
• 50 Murphy SN, Morgan MM, Barnett GO, Chueh HC. Optimizing healthcare research data warehouse design through past COSTAR query analysis. Proc AMIA Symp 1999 pp 892-896.
  PubMedGoogle Scholar
• 51 Safran C, Porter D, Lightfoot J, Rury CD, Underhill LH, Bleich HL, Slack WV. ClinQuery: a system for online searching of data in a teaching hospital. Ann Intern Med 1989; 111 (09) 751-756.
  CrossrefPubMedGoogle Scholar
• 52 Safran C, Porter D, Rury CD, Herrmann FR, Lightfoot J, Underhill LH, Bleich HL, Slack WV. Clin- Query: searching a large clinical database. MD Comput 1990; 7 (03) 144-153.
  PubMedGoogle Scholar
• 53 Herrmann FR, Safran C. Exploring a hospital-wide database: integrating statistical functions with ClinQuery. Proc Annu Symp Comput Appl Med Care 1990 pp 583-587.
  PubMedGoogle Scholar
• 54 Safran C. Using routinely collected data for clinical research. Stat Med 1991; 10 (04) 559-564.
  CrossrefPubMedGoogle Scholar
• 55 Safran C, Chute CG. Exploration and exploitation of clinical databases. Int J Biomed Comput 1995; 39 (01) 151-156.
  CrossrefPubMedGoogle Scholar
• 56 Dorda W, Wrba T, Duftschmid G. et al. ArchiMed – A Medical Information and Retrieval System. Methods Inf Med 1999; 38: 16-24.
  Article in Thieme ConnectPubMedGoogle Scholar
• 57 Duftschmid G, Gall W, Eigenbauer E, Dorda W. Management of data from clinical trials using the ArchiMed system. Med Inform Internet Med 2002; 27 (02) 85-98.
  CrossrefPubMedGoogle Scholar
• 58 Winn RJ. Obstacles to the accrual of patients to clinical trials in the community setting. Semin Oncol 1994; 21 4 Suppl 7 112-117.
  PubMedGoogle Scholar
• 59 Taylor KM, Margolese RG, Soskolne CL. Physicians’ reasons for not entering eligible patients in a randomized clinical trial of surgery for breast cancer. N Engl J Med 1984; 310 (21) 1363-1367.
  CrossrefPubMedGoogle Scholar
• 60 Schain WS: Barriers to clinical trials.. Part II: Knowledge and attitudes of potential participants. Cancer 1994; 74 (09) 2666-2671.
  CrossrefPubMedGoogle Scholar
• 61 Somkin CP, Altschuler A, Ackerson L, Geiger AM, Greene SM, Mouchawar J, Holup J, Fehrenbacher L, Nelson A, Glass A. et al. Organizational barriers to physician participation in cancer clinical trials. Am J Manag Care 2005; 11 (07) 413-421.
  PubMedGoogle Scholar
• 62 Campbell MK, Snowdon C, Francis D, Elbourne D, McDonald AM, Knight R, Entwistle V, Garcia J, Roberts I, Grant A, Grant A. STEPS group.. Recruitment to randomised trials: strategies for trial enrolment and participation study. The STEPS study. Health Technol Assess 2007; 11 (48).
  PubMedGoogle Scholar
• 63 Carlson RW, Tu SW, Lane NM, Lai TL, Kemper CA, Musen MA. Shortliffe EH. Computer-based screening of patients with HIV/AIDS for clinical-trial eligibility. Online J Curr Clin Trials 1995 ; Doc No 179.
  PubMedGoogle Scholar
• 64 Ohno-Machado L, Wang SJ, Mar P, Boxwala AA. Decision support for clinical trial eligibility determination in breast cancer. Proc AMIA Symp 1999. pp 340-344.
  PubMedGoogle Scholar
• 65 Papaconstantinou C, Theocharous G, Mahadevan S. An expert system for assigning patients into clinical trials based on Bayesian networks. J Med Syst 1998; 22 (03) 189-202.
  CrossrefPubMedGoogle Scholar
• 66 Thompson DS, Oberteuffer R, Dorman T. Sepsis alert and diagnostic system: integrating clinical systems to enhance study coordinator efficiency. Comput Inform Nurs 2003; 21 (01) 22-26. quiz 27-28.
  CrossrefPubMedGoogle Scholar
• 67 Séroussi B, Bouaud J. Using OncoDoc as a computer- based eligibility screening system to improve accrual onto breast cancer clinical trials. Artif Intell Med 2003; 29 (1–2): 153-167.
  CrossrefPubMedGoogle Scholar
• 68 Moore TD, Hotz K, Christensen R, Litwak D, Meyer J, Baxter T, Thompson M, Ashbury F. Integration of clinical trial decision rules in an electronic medical record (EMR) enhances patient accrual and facilitates data management, quality control and analysis. In: Proc Am Soc Clin Onc 22: 2003. 2003. p 557.
  Google Scholar
• 69 Kamal J, Pasuparthi K, Rogers P, Buskirk J, Mekhjian H. Using an information warehouse to screen patients for clinical trials: a prototype. AMIA Annu Symp Proc 2005. p 1004
  PubMedGoogle Scholar
• 70 Embi PJ, Jain A, Clark J, Harris CM. Development of an electronic health record-based Clinical Trial Alert system to enhance recruitment at the point of care. AMIA Annu Symp Proc 2005. pp 231-235.
  PubMedGoogle Scholar
• 71 Embi PJ, Jain A, Clark J, Bizjack S, Hornung R, Harris CM. Effect of a clinical trial alert system on physician participation in trial recruitment. Arch Intern Med 2005; 165 (19) 2272-2277.
  CrossrefPubMedGoogle Scholar
• 72 Embi PJ, Jain A, Martin Harris C. Physicians’ perceptions of an electronic health record-based clinical trial alert approach to subject recruitment: a survey. BMC Medical Informatics and Decision Making 2008; 8: 13 doi: 10.1186/1472-6947-8-13.
  CrossrefPubMedGoogle Scholar
• 73 Dugas M, Lange M, Berdel WE, Müller-Tidow C. Workflow to improve patient recruitment for clinical trials within hospital information systems – a case-study. Trials 2008; 9: 2.
  CrossrefPubMedGoogle Scholar
• 74 Miller JL. The EHR solution to clinical trial recruitment in physician groups. Health Manag Technol 2006; 27 (12) 22-25.
  PubMedGoogle Scholar
• 75 Weiner DL, Butte AJ, Hibberd PL, Fleisher GR. Computerized recruiting for clinical trials in real time. Ann Emerg Med 2003; 41 (02) 242-246.
  CrossrefPubMedGoogle Scholar
• 76 Afrin LB, Oates JC, Boyd CK, Daniels MS. Leveraging of Open EMR Architecture for Clinical Trial Accrual. AMIA Proceedings 2003 pp 16-20.
  PubMedGoogle Scholar
• 77 Powell J, Buchan I. Electronic health records should support clinical research. J Med Internet Res 2005; 7 (01) e4-00.
  CrossrefPubMedGoogle Scholar
• 78 Ohmann C, Kuchinke W. Meeting the Challenges of Patient Recruitment – A Role for Electronic Health Records. Int J Pharmaceutical Medicine 2007; 21 (04) 263-270.
  PubMedGoogle Scholar
• 79 Nadkarni PM, Brandt CA. The common data elements for cancer research: Remarks on Functions and Structure. Methods Inf Med 2006; 45: 594-601.
  Article in Thieme ConnectPubMedGoogle Scholar
• 80 Bürkle T, Ganslandt T, Prokosch HU. Das Krankenhausinformationssystem: Datengrab oder Chance für das Auffinden klinischer Zusammenhänge ?. 50. GMDS Jahrestagung 2005. German Medical Science; 2005. Doc 05gmds072. http://www.egms.de/en/meetings/gmds2005/05gmds472.shtml [last accessed 15.5.2008]
  PubMedGoogle Scholar
• 81 Sinha G. Clinical trials that cost less: Electronic Health Records Help Recruit Trial Participants and Track Drug Safety. JNCI Journal of the National Cancer Institute 2008; 100 (06) 384-385. doi: 10.1093/jnci/djn070:
  CrossrefPubMedGoogle Scholar
• 82 Murphy SN, Mendis ME, Berkowitz DA, Kohane I, Chueh HC. Integration of Clinical and Genetic Data in the i2b2 Architecture. AMIA Annu Symp Proc 2006. p 1040. PMCID: PMC1839291.
  PubMedGoogle Scholar
• 83 Lo Iacono L. Multi-centric universal pseudonymisation for secondary use of the EHR. Stud Health Technol Inform 2007; 126: 239-247.
  PubMedGoogle Scholar
• 84 Ash JS, Anderson NR, Tarczy-Hornoch P. People and Organizational Issues in Research Systems Implementation. J Am Med Inform Assoc 2008; 15: 283-289. PrePrint published February 28, 2008; doi: 10.1197/jamia.M2582.
  CrossrefPubMedGoogle Scholar
• 85 Richesson RL, Krischer J. Data standards in clinical research: gaps, overlaps, challenges and future directions. J Am Med Inform Assoc 2007; 14 (06) 687-696. Epub 2007 Aug 21. Erratum in: J Am Med Inform Asso. 2008; 15 (2): 265.
  CrossrefPubMedGoogle Scholar
• 86 Kush RD, Helton E, Rockhold FW, Hardison CD. Electronic health records, medical research, and the Tower of Babel. N Engl J Med 2008; 358 (16) 1738-1740.
  CrossrefPubMedGoogle Scholar
• 87 Kohane I, Glaser J. i2b2: informatics for integrating biology & bedside. https://www.i2b2.org/about/index.html [last accessed 15.5.2008]
  PubMedGoogle Scholar
• 88 Oster S, Langella S, Hastings S, Ervin D, Madduri R, Phillips J, Kurc T, Siebenlist F, Covitz P, Shanbhag K, Foster I, Saltz J. caGrid 1.0: an enterprise Grid infrastructure for biomedical research. J Am Med Inform Assoc 2008; 15 (02) 138-149.
  CrossrefPubMedGoogle Scholar
• 89 caBIG Strategic Planning Workspace.. The Cancer Biomedical Informatics Grid (caBIG): infrastructure and applications for a worldwide research community. Medinfo 2007; 12 Pt (01) 330-334.
  PubMedGoogle Scholar
• 90 Fridsma DB, Evans J, Hastak S, Mead CN. The BRIDG Project: A Technical Report. J Am Med Inform Assoc 2008; 15 (02) 130-137.
  CrossrefPubMedGoogle Scholar
• 91 Kush R, Alschuler L, Ruggeri R, Cassells S, Gupta N, Bain L, Claise K, Shah M, Nahm M. Implementing Single Source: the STARBRITE proof-of-concept study. J Am Med Inform Assoc 2007; 14 (05) 662-673.
  CrossrefPubMedGoogle Scholar
• 92 Lovis C, Colaert D, Stroetmann VN. DebugIT for Patient Safety – Improving the Treatment with Antibiotics through Multimedia Data Mining of Heterogeneous Clinical Data. Stud Health Technol Inform 2008; 136: 641-646.
  PubMedGoogle Scholar
• 93 Van der Lei J. Early detection of adverse drug events by integrative mining of clinical records and biomedical knowledge. http://www.eurorec.org/ehrworkshop2/research/Day%202%20%20P2%20ALERT%20overview-J%20van%20der%20Lei.ppt [last accessed 21.8.2008].
  PubMedGoogle Scholar