Fast Track Registration a Way to Increase Efficiency in the Ir Division

Interventional Radiology
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  CLINICAL STUDY Fast-Track Registration: A Way to IncreaseEf  󿬁 ciency in the IR Division David P. Duncan, MD, Bryan E. Wessel, MBA, MSc,Michael A. Schacht, MD, MBA, Lu Anne V. Dinglasan, MD, MHS,George W. Mader, RPA, Melissa H. Potts, MD, Mahmoud Samman, MD,Martin S. Vyleta, MD, and Douglas M. Coldwell, MD, PhD ABSTRACTPurpose:  To evaluate changes in patient registration process at an academic 2-suite IR Division to determine if moving registrationfrom the waiting room to the vascular holding area decreased amount of time patients spent in the Radiology Department and improvedstart times. Materials and Methods:  A data collection sheet was created by evaluating patient-related processes; event timestamps wererecorded on the sheet. The control group consisted of 33 patients who registered using the traditional process. The fast-track groupconsisted of 29 patients who bypassed the traditional registration procedure and were registered by nurses in the vascular holding area. Results:  Total time between control and fast-track groups signi 󿬁 cantly decreased from an average time of 215 minutes to 178 minutes(  P   ¼ .020). The average start time improved signi 󿬁 cantly from an average of 63 minutes after scheduled procedure start time for thecontrol group to 33 minutes after the scheduled procedure start time for the fast-track group (  P  ¼ .009). Start time (  P  ¼ .022), time spent in recovery area (  P   ¼ .006), and total time, after correcting for differences in laboratory test turnaround time, (  P   ¼ .010) decreased invariability after implementation of fast-track registration. Conclusions:  Implementing fast-track registration for outpatient subcutaneous port placement in the IR Division improved start timesand decreased total time patients spent in the hospital, while also reducing variability in the process. With the rapidly changing climate of hospital medicine,focus on the ef  󿬁 cient use of limited resources and on theenhancement of patient satisfaction has increased (1  –  3).Although the future of current health care legislation re-mains uncertain, this shift in philosophy likely will remainunchanged, and the task of eliminating waste will continue.One common technique of eliminating waste is lean pro-cedure, also known as lean production. Lean production isthe philosophy and method of continuous improvement developed by the Toyota Motor Corporation, which focusedon eliminating waste to increase ef  󿬁 ciency and productivity(4). Waste can be considered anything that uses resources but adds no value. Based on the Toyota Production System,waste can be categorized as overproduction, unnecessarytransportation, inventory, motion, defects, overprocessing,or waiting (4  –  6). Ideally, the lean approach leads toimproved productivity, decreased cost, and increasedcustomer satisfaction (7).Today, lean production has extended beyond the auto-mobile industry and has been adopted by other   󿬁 elds,including health care. For example, the University of Michigan Health System implemented lean philosophyimproving their work  󿬂 ow and achieved a 36% decrease inthe average wait time for placement of a peripherallyinserted central catheter and decreased the rate of referrals toInterventional Radiology (IR) for peripherally insertedcentral catheter placement by 50% (8). Bucci and Musitano(9) applied Lean Six Sigma methodologies to magneticresonance imaging scheduling and billing at Akron Chil-dren ’ s Hospital and reduced the wait time from 25 days to1  –  2 days and billing de 󿬁 cit rates from 10% to 1%. Cheunget al (10) used Six Sigma to decrease time of stay for musculoskeletal procedures. Shah et al (7) successfully usedlean principles to identify waste and decrease patient wait time for mammography. Although these examples represent a small fraction of instances where lean philosophy has beenimplemented in health care, they suggest that lean philoso- phy can be implemented in the Radiology Department,resulting in work  󿬂 ow changes that reduce waste. This study From the Department of Radiology, University of Louisville Hospital, 530South Jackson Street, CCB-C07, Louisville, KY 40202. Received May 25, 2017;final revision received August 28, 2017; accepted August 31, 2017.  Addresscorrespondence to  D.P.D.; E-mail: dpduncan@ucsd.eduNone of the authors have identi 󿬁 ed a con 󿬂 ict of interest.© SIR, 2017 J Vasc Interv Radiol 2018; 29:125  –  131  aimed to evaluate changes in the patient check-in process at an academic 2-suite IR Division to determine if movingregistration from the waiting room to the vascular holdingarea decreased the amount of time that patients spent in theRadiology Department and improved start times. MATERIALS AND METHODS This prospective single-institution study was exempted bythe institutional review board, and informed consent waswaived. A list of common procedures performed in the IR Division was created. Variability, a measurement of the predictability and consistency of a process, in each pro-cedure was estimated by creating outlines of the stepsinvolved in each. Lean procedure assumes a larger number of steps correlates with increased complexity and increasedvariability. The subcutaneous port placement procedurehad the lowest expected variability of the procedures on thelist and was the most suitable target for evaluation.Selecting the most consistent procedure increased thechances that any difference between cases was likely dueto differences in periprocedural events rather than the procedure itself.The process of patient throughput was assessed byfollowing a single patient and recording all patient-staff interactions. Using this log, a value-stream map ( Fig1a ) and a data collection sheet ( Fig 2 ) were created.The process map was evaluated for actionable waste.The results were sorted by ease of intervention and potential waste eliminated. Moving registration fromthe waiting room to the vascular holding area ( Fig 1b )ranked highest in both ease of intervention andexpected reduction of waste and was selected as thewaste target.An a priori statistical power analysis was performed usingG*Power 3.1 software (Heinrich-Heine-Universit  € at, Düs-seldorf, Germany) for sample size estimation (11,12). Data published by Cheung et al (10) demonstrated a decrease of approximately 25% of total time following multiple in-terventions. With only a single process change made, theexpected results would be less dramatic. The clinicallyrelevant reduction in time was set to be 20  –  30 minutes,approximately 10%  –  15% of expected total time. The power analysis was performed twice using both 20 minutes and 30minutes as the difference in means. With the pooled SD for the calculation set to 30 minutes, the effect size equaled 0.66and 0.99. With  a  ¼  0.03 and power   ¼  0.80, the projectedsample size needed was approximately 28  –  60, assumingequal distribution of enrollees between the control and test groups. Thus, a sample size of 60 was selected to allow for expected attrition.During a 6-month period between September 1, 2014, andMarch 1, 2015, 62 patients were evaluated. All patients wereassigned a data sheet at time of sign-in, and nurses recordedclock time at each staff-patient interaction event delineated by the process map on the data sheet. The bottom of the page was left blank for comments regarding potential causesof delay.The control group consisted of 33 patients who registeredusing the same process as all Radiology Department imag-ing examinations and procedures. Registration for this groupoccurred in the waiting room with registration priorityassigned in the order of arrival. No priority was given to patients undergoing outpatient interventional procedures.The patient checked in, received a  “ restaurant-style ”  coaster  pager, and then sat in the waiting room until the pager  buzzed. After being paged, the patient came to the secondstation of registration where the patient  ’ s identity, insurance, Figure 1.  Value-stream maps.  (a)  Original value-stream map created following a single patient through the Radiology Department fromarrival to discharge.  (b)  Value-stream map following implementation of fast-track registration with registration occurring in parallel withother preprocedural tasks in the vascular holding area.126  ▪  Fast-Track Registration in IR Duncan et al  ▪  JVIR  and payment method were con 󿬁 rmed, and then patient wasescorted by the IR nurse to the holding area.The test group consisted of 29 patients who were assignedto the fast-track registration group. The patient signed in tothe Radiology Department waiting room and was directed tothe IR division holding area to complete registration, bypassing the pager system. No other changes were made.Data collected included the time of arrival at each loca-tion, beginning and end times of informed consent, time of  peripheral intravenous line placement, laboratory test drawand return times, and laboratory test type and result. Patient laboratory tests, if required, consisted of coagulation factors,complete blood count, and basic metabolic panels. Collecteddata were organized on a Microsoft Excel spreadsheet (Microsoft Corp, Redmond, Washington). All clock timeswere converted to intervals in minutes. For example, if a patient arrived in the IR Division holding area at 8:00  AM and later arrived in the procedure suite at 9:00  AM , the in-terval time was recorded as 60. Patients were instructed toarrive 60 minutes before appointment time, so all patient arrival times earlier than 60 minutes before the procedurestart time were adjusted to 60 minutes. Arrival times for any patient signing in  <  60 minutes before the scheduledappointment time were left unchanged.Incomplete data sheets were included where time at in-dividual steps or total time could be calculated. Eventswere separated, and the arithmetic mean, SD, maximum,and minimum were determined. Data analysis was per-formed with Microsoft Excel 2016 version 15.3. Meanswere analyzed using Student   t   test, and variances wereanalyzed using the 2-sample  F   test. Individual events wereanalyzed before evaluating the total time interval. Anyinterval found to be signi 󿬁 cantly different between thecontrol and fast-track groups were normalized to thecontrol group by calculating the ratio of the control andfast-track group means. The ratio was used as thenormalization factor. Total time calculations were per-formed before and after normalization. RESULTS Of the 33 patients in the control group, 3 patients did not have start times recorded, and 1 patient did not havedischarge time recorded. Of the 29 patients in the fast-track group, missing data were more varied. In 10 patients, either sign-in time (n ¼ 9) or start time (n ¼ 1) was not recorded, precluding calculation of time spent in the vascular holdingarea. In 8 patients, either a discharge time was not recorded(n  ¼  6) or events occurred in the IR Division that madeinclusion for data analysis unjusti 󿬁 able (n  ¼  2). Theseevents were a patient fall in the recovery area (n ¼ 1) and aliver biopsy in a patient immediately following placement of the port (n ¼ 1). As a result of missing timestamps and/ or unforeseen events, analysis of total time included 29 patients for the control group and 17 patients for the fast-track group.After implementing fast-track registration, the averagestart time improved signi 󿬁 cantly from an average of 63minutes after the scheduled procedure start time to 33minutes after the scheduled procedure start time (  P  ¼ .009)( Fig 3a ). Average processing time for laboratory tests wassigni 󿬁 cantly different between the control and fast-track groups (38 min vs 53 min,  P   ¼  .007) ( Fig 3e ). After normalizing the laboratory return time intervals, totaltime between control and fast-track groups was signi 󿬁 -cantly decreased from an average time of 215 minutes to178 minutes (  P  ¼ .020) ( Fig 3g ). There were no signi 󿬁 cant differences between control and fast-track groups in timespent in the vascular holding area (67 min vs 73 min,  P  ¼ .64), in the procedure suite (53 min vs 58 min,  P   ¼ .099),or in the recovery area (62 min vs 63 min,  P   ¼  .93)( Fig 3b  –  d ,  f  ).Comparing the control and the fast-track groups, severalcharacteristics decreased in variability ( Fig 4 ), including Figure 2.  Data collection sheet. Times were recorded as clocktimes. For example, if a patient signed in at 9:00  AM  and arrived atthe vascularholding area at 10:30  AM , 9:00 and 10:30 were writtenin their respective corresponding boxes. The times were laterconverted to minutes spent at each step. So, for the above-mentioned example, the time in the waiting room would becalculated as 90 minutes.Volume 29  ▪  Number 1  ▪  January  ▪  2018 127  Figure 3. (a – g)  Box and whisker plots of control and fast-track groups. The box and whisker plots showed decreased median values(horizontal lines inside boxes) for start times  (a)  and total time, after correcting for differences in laboratory test turnaround time  (g) . Thevariability, as represented by the height of the box, also decreased for start times  (a) , time spent in the recovery area  (d) , and total time,after correcting for differences in laboratory test turnaround time  (g) . The changes in the remaining steps were not signi 󿬁 cant for bothmean and variability  (b, c, f) . Average processing time for laboratory tests was signi 󿬁 cantly different between control and fast-trackgroups  (e) .128  ▪  Fast-Track Registration in IR Duncan et al  ▪  JVIR
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