Efficacy and cost-effectiveness of an automated screening algorithm in an inpatient clinical trial

Clinical Trials

Volumn 9, Issue 2, 2012, Pages 198-203

  Beauharnais, Catherine C ^a   Larkin, Mary E ^a,b   Zai, Adrian H ^a,b   Boykin, Emily C ^a   Luttrell, Jennifer ^a   Wexler, Deborah J ^a,b  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GLUCOSE; INSULIN;

ALGORITHM; ARTICLE; AUTOMATED PRESCREENING ALGORITHM; CLINICAL EFFECTIVENESS; CLINICAL TRIAL (TOPIC); COST EFFECTIVENESS ANALYSIS; GLUCOSE BLOOD LEVEL; HOSPITAL ADMISSION; HOSPITAL PATIENT; HOSPITALIZATION; HUMAN; HYPOTHESIS; LENGTH OF STAY; MEDICAL RECORD REVIEW; NON INSULIN DEPENDENT DIABETES MELLITUS; PRIORITY JOURNAL; SAMPLE SIZE; SCREENING;

ALGORITHMS; AUTOMATION; CLINICAL TRIALS AS TOPIC; COST-BENEFIT ANALYSIS; EFFICIENCY, ORGANIZATIONAL; HOSPITALS, GENERAL; HUMANS; INPATIENTS; MASSACHUSETTS; PATIENT SELECTION;

EID: 84861801136     PISSN: 17407745     EISSN: 17407753     Source Type: Journal    
DOI: 10.1177/1740774511434844     Document Type: Article

References (23)

1. CanavanCGrossmanSKushRWalkerJ. Integrating recruitment into eHealth patient records. Appl Clin Trials Online. Available at http:// appliedclinicaltrialsonline.findpharma.com/appliedclinicaltrials/article/ articleDetail.jsp?id=334569 (accessed October 2011).
2. Sanders KM, Stuart AL, Merriman EN, et al. Trials and tribulations of recruiting 2,000 older women onto a clinical trial investigating falls and fractures: Vital D study. BMC Med Res Methodol. 2009 ; 9: 78
3. Rengerink KO, Opmeer BC, Logtenberg SL, et al. IMproving PArticipation of patients in Clinical Trials-Rationale and design of IMPACT. BMC Med Res Methodol. 2010 ; 10: 85
4. Dugas M, Lange M, Müller-Tidow C, Kirchhof P, Prokosch H-U. Routine data from hospital information systems can support patient recruitment for clinical studies. Clin Trials. 2010 ; 7: 183-89
5. Dugas M, Amler S, Lange M, et al. Estimation of patient accrual rates in clinical trials based on routine data from hospital information systems. Methods Inf Med. 2009 ; 48: 263-66
6. Cohen HJ, Feussner JR, Weinberger M, et al. A controlled trial of inpatient and outpatient geriatric evaluation and management. N Engl J Med. 2002 ; 346: 905-12
7. Rigotti NA, Thorndike AN, Regan S, et al. Bupropion for smokers hospitalized with acute cardiovascular disease. Am J Med. 2006 ; 119: 1080-87
8. Butte AJ, Weinstein DA, Kohane IS. Enrolling patients into clinical trials faster using RealTime Recruiting. Proc AMIA Symp. 2000 ;: 111-15
9. Cuggia M, Besana P, Glasspool D. Comparing semi-automatic systems for recruitment of patients to clinical trials. Int J Med Inform. 2011 ; 80: 371-88
10. Bergin PS, Ip T, Sheehan R, et al. Using the Internet to recruit patients for epilepsy trials: Results of a New Zealand pilot study. Epilepsia. 2010 ; 51: 868-73
11. Page MJ, French SD, McKenzie JE, O'Connor DA, Green SE. Recruitment difficulties in a primary care cluster randomised trial: Investigating factors contributing to general practitioners' recruitment of patients. BMC Med Res Methodol. 2011 ; 11: 35
12. Dyas JV, Apekey T, Tilling M, Siriwardena AN. Strategies for improving patient recruitment to focus groups in primary care: A case study reflective paper using an analytical framework. BMC Med Res Methodol. 2009 ; 9: 65
13. de Lusignan S, van Weel C. The use of routinely collected computer data for research in primary care: Opportunities and challenges. Fam Pract. 2006 ; 23: 253-63
14. McGregor J, Brooks C, Chalasani P, et al. The Health Informatics Trial Enhancement Project (HITE): Using routinely collected primary care data to identify potential participants for a depression trial. Trials. 2010 ; 11: 39
15. 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
16. Heinemann S, Thüring S, Wedeken S, et al. A clinical trial alert tool to recruit large patient samples and assess selection bias in general practice research. BMC Med Res Methodol. 2011 ; 11: 16
17. 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 ;: 231-35
18. Lee Y, Dinakarpandian D, Katakam N, Owens D. MindTrial: An intelligent system for clinical trials. AMIA Annu Symp Proc. 2010 ; 2010: 442-46
19. Embi PJ, Jain A, Clark J, et al. Effect of a clinical trial alert system on physician participation in trial recruitment. Arch Intern Med. 2005 ; 165: 2272-77
20. Weiner DL, Butte AJ, Hibberd PL, Fleisher GR. Computerized recruiting for clinical trials in real time. Ann Emerg Med. 2003 ; 41 (2). 242-46
21. Nkoy FL, Wolfe D, Hales JW, et al. Enhancing an existing clinical information system to improve study recruitment and census gathering efficiency. AMIA Annu Symp Proc. 2009 ;: 476-80
22. Street A, Strong J, Karp S. Improving patient recruitment to multicentre clinical trials: The case for employing a data manager in a district general hospital-based oncology centre. Clin Oncol. 2001 ; 13: 38-43
23. Campbell MK, Snowdon C, Francis D, et al. Recruitment to randomised trials: Strategies for trial enrollment and participation study. The STEPS study. Health Technol Assess. 2007 ; 11: iii ix - 105