High resolution analysis of wait times and factors affecting surgical expediency.

Eric Cole, Wilma Hopman, Jun Kawakami
Author Information
  1. Eric Cole: Urology Resident, Department of Urology, McMaster University Hamilton ON.

Abstract

OBJECTIVES: Wait times in Canada are increasingly being monitored as an indicator of quality health care delivery. We created a higher resolution picture of the wait experienced by urological surgery patients beginning with the initial referral. In doing so, we hoped to (a) identify potential bottlenecks and common delays at our centre, and (b) identify predictors of wait time.
METHODS: The charts of 322 patients undergoing surgery from November 2007 to March 2008 were reviewed and specific dates, patient factors and delays were recorded. The data were used to detail the patient's wait and to determine the patient factors which were predictive of wait time.
RESULTS: The mean time from decision to operate to the day of operation was 75.87 days for all patients. This number accounts for 53% of the wait time, while the time from referral to decision to operate is 47%. Predictors of a decreased wait time include cancer cases, younger age, urgency score, repeat patients and female gender in multivariate analysis. Delays were experienced by 16.8% of patients; most common delays were operating room cancellations/time constraints, patients requiring further optimization and delays in referral (4.7%, 3.4% and 3.1%, respectively).
CONCLUSIONS: The waiting process is complex; the actual waiting time that a patient must endure is much longer than the wait times traditionally recorded and reported by hospitals. As strategies are implemented to decrease wait times, it will become increasingly important to monitor the entire wait time from referral to operation and to ensure that changes are being made that truly decrease wait times and not simply shift where and when the patient waits.

References

  1. CMAJ. 2000 May 2;162(9):1305-10 [PMID: 10813013]
  2. Can J Urol. 2006 Jun;13 Suppl 3:37-47 [PMID: 16818011]
  3. Can J Urol. 2006 Jun;13 Suppl 3:14-5 [PMID: 16818007]
  4. Can J Surg. 2007 Oct;50(5):394-6 [PMID: 18031641]
  5. J Thorac Oncol. 2008 Aug;3(8):865-70 [PMID: 18670304]
  6. J Urol. 2006 Jan;175(1):78-83; discussion 83 [PMID: 16406875]
  7. Br J Cancer. 2003 Aug 4;89(3):492-6 [PMID: 12888818]
  8. CMAJ. 2005 May 10;172(10):1277 [PMID: 15883393]
  9. Can J Urol. 2006 Jun;13 Suppl 3:16-24 [PMID: 16818008]
  10. Can Urol Assoc J. 2008 Dec;2(6):597-603 [PMID: 19066677]
  11. Can J Urol. 2006 Jun;13 Suppl 3:62-4 [PMID: 16818014]
  12. J Urol. 2008 Jun;179(6):2152-7 [PMID: 18423724]
  13. Qual Life Res. 2001;10(6):543-53 [PMID: 11789554]
  14. Br J Cancer. 2007 Jan 15;96(1):162-8 [PMID: 17179986]
  15. Ann R Coll Surg Engl. 2003 Sep;85(5):347-50 [PMID: 14594541]
  16. CMAJ. 2001 Aug 21;165(4):421-5 [PMID: 11531050]

Word Cloud

Created with Highcharts 10.0.0waittimepatientstimesreferraldelayspatientfactorsincreasinglyresolutionexperiencedsurgeryidentifycommonrecordeddecisionoperateoperationanalysis3waitingdecreaseOBJECTIVES:WaitCanadamonitoredindicatorqualityhealthcaredeliverycreatedhigherpictureurologicalbeginninginitialhopedpotentialbottleneckscentrebpredictorsMETHODS:charts322undergoingNovember2007March2008reviewedspecificdatesdatauseddetailpatient'sdeterminepredictiveRESULTS:meanday7587daysnumberaccounts53%47%PredictorsdecreasedincludecancercasesyoungerageurgencyscorerepeatfemalegendermultivariateDelays168%operatingroomcancellations/timeconstraintsrequiringoptimization47%4%1%respectivelyCONCLUSIONS:processcomplexactualmustenduremuchlongertraditionallyreportedhospitalsstrategiesimplementedwillbecomeimportantmonitorentireensurechangesmadetrulysimplyshiftwaitsHighaffectingsurgicalexpediency

Similar Articles

Cited By