Fischer A J, O'Halloran P, Littlejohns P, Kennedy A, Butson G
Public Health Sciences Department, St George's Hospital Medical School, London.
J Public Health Med. 2000 Sep;22(3):413-21. doi: 10.1093/pubmed/22.3.413.
Ambulance services produce a large quantity of data, which can yield valuable summary statistics. For strategic planning purposes, an economic framework is proposed, and the following four resource allocation questions are answered, using data from the Surrey Ambulance Service: (1) To satisfy government response time targets, how many additional ambulances will be required, ceteris paribus? (2) To minimize average response time (r*) with given resources, how should ambulances be rostered temporally? (3) Which innovations are worth undertaking? (4) How would an increase in demand affect r*?
The 'Ambulance Response Curve' --the relation between response time and the number of available but not-in-use ambulances--is used to estimate how much r* will be reduced by deploying an additional ambulance. Estimating the marginal cost of an ambulance allows us to estimate the opportunity cost of each second of response time, and to compare the cost of three 'innovations' with that of increasing resources. The time savings of adding an extra ambulance at each of the 168 h of the week are examined.
In 1997-1998, r* was 8 min 52 s. An additional ambulance reduces r* by 8.9 s. Each reduction of 1 s in r* costs 28,000 pounds per year. Fourteen additional ambulances are required to meet response time targets if the 8.9 s reduction per ambulance is maintained. r* reduces by 4.6 s when ambulances are shifted from early mornings to Saturday evenings. Activation time reduces by 38 s when crews sit in their ambulances. A 1 min decrease in overall call time decreases r* by 1.1 s. Answering only 10 per cent of all calls reduces r* by 63 s. An increase of demand of 10 per cent increases r* by 7.8 s.
Ambulance services will be better able to determine which innovations are worth undertaking. Policy makers will be better placed to determine funding levels to achieve response time targets.
救护车服务产生大量数据,这些数据可得出有价值的汇总统计信息。出于战略规划目的,提出了一个经济框架,并利用萨里郡救护车服务的数据回答了以下四个资源分配问题:(1)在其他条件不变的情况下,为满足政府的响应时间目标,需要增加多少辆救护车?(2)在给定资源的情况下,为使平均响应时间(r*)最小化,救护车应如何进行时间排班?(3)哪些创新举措值得实施?(4)需求增加将如何影响r*?
“救护车响应曲线”(即响应时间与可用但未投入使用的救护车数量之间的关系)用于估计增加一辆救护车可使r*降低多少。估算救护车的边际成本使我们能够估计每一秒响应时间的机会成本,并将三种“创新举措”的成本与增加资源的成本进行比较。研究了在一周的168个小时内每个时段增加一辆额外救护车所节省的时间。
在1997 - 1998年,r为8分52秒。增加一辆救护车可使r降低8.9秒。r每降低1秒每年成本为28,000英镑。如果每辆救护车保持降低8.9秒的效果,需要额外增加14辆救护车才能达到响应时间目标。当救护车从清晨时段转移到周六晚上时,r降低4.6秒。当急救人员坐在救护车内时,启动时间减少38秒。总呼叫时间减少1分钟可使r降低1.1秒。仅接听所有呼叫的10%可使r降低63秒。需求增加10%会使r*增加7.8秒。
救护车服务机构将能更好地确定哪些创新举措值得实施。政策制定者将更有能力确定为实现响应时间目标所需的资金水平。