Literature DB >> 20703561

Understanding performance and behavior of tightly coupled outpatient systems using RFID: initial experience.

James E Stahl1, Julie K Holt, Nancy J Gagliano.   

Abstract

Understanding how clinical systems actually behave in an era of limited medical resources is critical. The purpose of this study was to determine if a radiofrequency-identification-based indoor positioning system (IPS) could objectively and unobtrusively capture outpatient clinic behavior. Primary outcomes were flowtime, wait time and patient/clinician face time. Two contrasting clinics were evaluated: a primary care clinic (PC) with templated scheduling and an urgent care clinic (UC) with unconstrained visit time and first-in, first-out scheduling. All staff wore transponders throughout the study period. Patients carried transponders from check in to check out. All patients and staff were allowed to opt out. The study was approved by hospital IRB. Standard descriptive and analytic statistical methods were used. Five hundred twenty-six patients (309 patients (PC), 217 patients (UC)) and 38 clinicians (eight (PC) and 30 (UC)) volunteered between April 30 and July 1, 2008. Total FT was not significantly different across clinics. PC wait time was significantly shorter (7.6 min [SD 15.8]) vs. UC (19.7 min [SD 25.3], p < 0.0001), and PC Face time was significantly longer (29.9 min, [SD 19.1] vs. UC (9.8 min [SD 8.5], p < 0.0001). PC Face time distributions reflected template scheduling structure. In contrast, face time distributions in UC had a smooth log normal distribution with a lower mean value. Our study seems to indicate that an IPS can successfully measure important clinic process measures in live clinical outpatient settings and capture behavioral differences across different outpatient organizational structures.

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Year:  2009        PMID: 20703561     DOI: 10.1007/s10916-009-9365-7

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  24 in total

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9.  Tracking the social dimensions of RFID systems in hospitals.

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  7 in total

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Authors:  Samuel Fosso Wamba
Journal:  J Med Syst       Date:  2011-11-23       Impact factor: 4.460

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Authors:  Anne-Katrin Wickboldt; Selwyn Piramuthu
Journal:  J Med Syst       Date:  2010-04-14       Impact factor: 4.460

Review 4.  The adoption and implementation of RFID technologies in healthcare: a literature review.

Authors:  Wen Yao; Chao-Hsien Chu; Zang Li
Journal:  J Med Syst       Date:  2011-10-19       Impact factor: 4.460

5.  ECC-based grouping-proof RFID for inpatient medication safety.

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6.  On the designing of a tamper resistant prescription RFID access control system.

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Journal:  J Med Syst       Date:  2012-08-10       Impact factor: 4.460

Review 7.  Real-time locating systems to improve healthcare delivery: A systematic review.

Authors:  Kevin M Overmann; Danny T Y Wu; Catherine T Xu; Shwetha S Bindhu; Lindsey Barrick
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

  7 in total

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