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Medinfo ; 8 Pt 2: 1635, 1995.
Article in English | MEDLINE | ID: mdl-8591521

ABSTRACT

The Provincial Advisory Committee on Cardiovascular Services was established in January of 1990 to advise concerning these services. One of the first tasks assigned was to monitor waiting times for cardiac surgery. Referring cardiologists categorized their patients into four priorities: emergency, urgent-inpatient, urgent-outpatient, and planned. Data of the southern Alberta centers for the past three years were analyzed for events while waiting for surgery. (Median time to event in days) M1=Myocardial Infarction EM=Emergency D=Day A hierarchy was used to assign the single most serious event for patients having more than one event: death>MI>readmission or change from urgent-inpatient to emergency. Events were frequent and unpredictable, particularly in outpatients. Categorization of patient suitable to wait at home for cardiac surgery is imperfect. The risk of having an event while on the waiting list is much greater for out-patients than in-patients: 12.8% (169/1323) versus 1.9% (19/1002). All adverse events for the in-patients occurred at four days--one day less than the proposed maximum waiting time. In the out-patient population, the median waiting time to experiencing adverse events ranged between 32 and 54 days. Target waiting times set by PACCS for these two categories is 14 and 56 days respectively. Total adverse events occurred to 8% of the patients on the waiting list. Median waiting time to experiencing an adverse event while on the list occurs much earlier than suspected: four days in urgent in-patients and 36 days for out-patients; well below the intended maximum of 56 days. This database proved invaluable for this important critical data collection. It is hoped it will serve as a model for similar future projects.


Subject(s)
Cardiac Surgical Procedures/statistics & numerical data , Information Systems/organization & administration , Waiting Lists , Alberta/epidemiology , Cardiology Service, Hospital/statistics & numerical data , Health Care Coalitions , Humans
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