Appl Clin Inform 2011; 02(01): 1-17
DOI: 10.4338/ACI-2010-08-RA-0047
Research Article
Schattauer GmbH

HIS-based support of follow-up documentation – concept and implementation for clinical studies

S. Herzberg
1   Department of Medical Informatics and Biomathematics, University of Münster, Germany
2   IT Department, University Hospital of Münster, Germany
,
F. Fritz
1   Department of Medical Informatics and Biomathematics, University of Münster, Germany
,
K. Rahbar
3   Department of Nuclear Medicine, University Hospital of Münster, Germany
4   European Institute of Molecular Imaging, University of Münster, Germany
,
L. Stegger
3   Department of Nuclear Medicine, University Hospital of Münster, Germany
,
M. Schäfers
4   European Institute of Molecular Imaging, University of Münster, Germany
,
M. Dugas
1   Department of Medical Informatics and Biomathematics, University of Münster, Germany
2   IT Department, University Hospital of Münster, Germany
› Author Affiliations
Further Information

Publication History

received: 27 August 2010

accepted: 20 January 2010

Publication Date:
16 December 2017 (online)

Summary

Objective: Follow-up data must be collected according to the protocol of each clinical study, i.e. at certain time points. Missing follow-up information is a critical problem and may impede or bias the analysis of study data and result in delays. Moreover, additional patient recruitment may be necessary due to incomplete follow-up data. Current electronic data capture (EDC) systems in clinical studies are usually separated from hospital information systems (HIS) and therefore can provide limited functionality to support clinical workflow. In two case studies, we assessed the feasibility of HIS-based support of follow-up documentation.

Methods: We have developed a data model and a HIS-based workflow to provide follow-up forms according to clinical study protocols. If a follow-up form was due, a database procedure created a follow-up event which was translated by a communication server into an HL7 message and transferred to the import interface of the clinical information system (CIS). This procedure generated the required follow-up form and enqueued a link to it in a work list of the relating study nurses and study physicians, respectively.

Results: A HIS-based follow-up system automatically generated follow-up forms as defined by a clinical study protocol. These forms were scheduled into work lists of study nurses and study physicians. This system was integrated into the clinical workflow of two clinical studies. In a study from nuclear medicine, each scenario from the test concept according to the protocol of the single photon emission computer tomography/computer tomography (SPECT/CT) study was simulated and each scenario passed the test. For a study in psychiatry, 128 follow-up forms were automatically generated within 27 weeks, on average five forms per week (maximum 12, minimum 1 form per week).

Conclusion: HIS-based support of follow-up documentation in clinical studies is technically feasible and can support compliance with study protocols.

 
  • References

  • 1 Chan KS, Fowles J, Weiner JP. Electronic health records and reliability and validity of quality measures. A review of the literature. Medical Care Research and Review. Forthcoming 2010. doi:10.1177/1077558709359007 PMid:20150441
  • 2 Ammenwerth E, Spötl HP. The time needed for clinical documentation versus direct patient care. Methods Inf Med 2009; 48: 84-91. PMid:19151888.
  • 3 Forster M, Bailey C, Brinkhof MW, Graber C, Boulle A, Spohr M. et al. Electronic medical record systems, data quality and loss to follow-up: survey of antiretroviral therapy programmes in resource-limited settings. Bulletin of the World Health Organization 2008; 86: 939-947. doi:10.2471/BLT.07.049908 PMid:19142294 PMCid:2649575.
  • 4 El Emam K, Jonker E, Sampson M, Krleža-Jeri K, Neisa A. The use of electronic data capture tools in clinical trials: Web-survey of 259 Canadian trials. J Med Internet Res 2009; 11 (01) e8. doi:10.2196/jmir.1120 PMid:19275984 PMCid:2762772.
  • 5 Dugas M, Breil B, Thiemann V, Lechtenbörger J, Vossen G. Single source information system to connect patient care and clinical research. Stud Health Technol Inform 2009; 150: 61-65. PMid:19745267.
  • 6 Kush R, Alschuler L, Ruggeri R, Cassells S, Gupta N, Bain L. et al. Implementing single source: the STAR-BRITE proof-of-concept study. J Am Med Inform Assoc 2007; 14 (05) 662-673. doi:10.1197/jamia. M2157 PMid:17600107 PMCid:1975790.
  • 7 Dugas M, Lange M, Berdel BE, Müller-Tidow C. Workflow to improve patient recruitment for clinical trials within hospital informations systems –a case-study. Trials 2008; 9: 2. doi:10.1186/1745-6215-9-2 PMid:18186949 PMCid:2253503.
  • 8 Dambro MR, Weiss BD. Assessing the quality of data entry in a computerized medical records system. J Med Syst 1988; 12: 181-187. doi:10.1007/BF00996640 PMid:3171446.
  • 9 Hogan WR, Wagner MM. Accuracy of data in computer-based patient records. J Am Med Inform Assoc 1997; 5: 342-355.
  • 10 de Lusignan S, van Weel C. The use of routinely collected computer data for research in primary care: opportunities and challenges. Family Practice 2006; 23: 253-263. doi:10.1093/fampra/cmi106 PMid:16368704.
  • 11 Herzberg S, Rahbar K, Stegger L, Schäfers M, Dugas M. Concept and implementation of a single source information system in nuclear medicine for myocardial scintigraphy (SPECT-CT data). Appl Clin Inf 2010; 1: 50-67.
  • 12 AGFA.com [Internet].. Agfa Healthcare; c2010 [updated 2009 Oct 8; cited 2010 Aug 26]. Available from: http://healthcare.agfa.com.
  • 13 ORACLE.com [Internet].. ORACLE [cited 2010 Aug 26]. Available from: http://www.oracle.com.
  • 14 SPSS.com [Internet].. Illinois: SPSS, Inc.; c2010 [cited 2010 Aug 26]. Available from: http://www.spss.com.
  • 15 McDonald AM, Knight RC, Campbell MK, Entwistle VA, Grant AM, Cook JA. et al. What influences recruitment to randomised controlled trials? A review of trials funded by two UK funding agencies. Trials 2006; 7: 9. doi:10.1186/1745-6215-7-9 PMid:16603070 PMCid:1475627.
  • 16 Weiner DL, Butte AJ, Hibberd PL, Fleisher GR. Computerized recruiting for clinical trials in real time. Ann emerg Med 2003; 41: 242-246. doi:10.1067/mem.2003.52 PMid:12548275.
  • 17 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: 2272-2280. doi:10.1001/archinte.165.19.2272 PMid:16246994 PMCid:1343501.
  • 18 Welker JA. Implementation of electronic data capture systems: Barriers and solutions. Contemporary Clinical Trials 2007; 28: 229-236. doi:10.1016/j.cct.2007.01.001 PMid:17287151.
  • 19 Prokosch HU, Ganslandt T. Perspectives for medical informatics: reusing the electronic medical record for clinical research. Methods Inf Med 2009; 48: 38-44. PMid:19151882.
  • 20 Poissant L, Pereira J, Tamblyn R, Kawasumi Y. The impact of electronic health record on time efficiency of physicians and nurses: A systematic review. J Am Med Inform Assoc 2005; 12: 505-516. doi:10.1197/jamia. M1700 PMid:15905487 PMCid:1205599.
  • 21 CDISC.org [Internet].. Clinical Data Interchange Standards Consortium; c2010 [cited 2010 Aug 26]. Available from: http://www.cdisc.org.
  • 22 Gardner RM, Pryor TA, Warner HR. The HELP hospital information system: update 1998. International Journal of Medical Informatics 1999; 54: 169-182. doi:10.1016/S1386-5056(99)00013-1.
  • 23 Mosen D, Elliot CG, Egger MJ, Mundorff M, Hopkins J, Patterson R. et al. The effect of a computerized reminder system on the prevention of postoperative venous thromoembolism. Chest 2004; 125: 1635-1641. doi:10.1378/chest.125.5.1635 PMid:15136370.
  • 24 Barnett GO, Winickoff RN, Morgan MM, Zielstorff RD. A computer-based monitoring system for follow-up of elevated blood pressure?. Medical Care 1983; 21: 400-409. doi:10.1097/00005650-198304000-00003 PMid:6341724.
  • 25 Staes CJ, Evans RS, Rocha BH, Sorensen JB, Huff SM, Arata J. et al. Computerized alerts improve outpatient laboratory monitoring of transplant patients. J Am Med Inform Assoc 2008; 15: 324-332. doi:10.1197/jamia. M2608 PMid:18308982 PMCid:2410008.
  • 26 Jha AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG. et al. Use of electronic health records in U. S. Hospitals. N Engl J Med 2009; 360: 1628-1638. doi:10.1056/NEJMsa0900592 PMid:19321858.