Originally posted by Tiana Antul:
Recently several people have inquired about analyzing the amount of time their officers spend on calls. I’m personally not aware of any established standards for response times, but having this data, or at least being able to get it quickly, might serve a variety of useful purposes to your agency.
The first thing you’ll need to do is make sure that your date and time fields are combined. Some RMS’s already combine their dates and times while others parse them out. If yours are parsed out, you can combine these fields right in your query by using an expression like the following:
CallRecieved_DateTime: [CallRecieved_Date] & “ “ & [CallRecieved_Time]
Repeat this for any date/time fields you plan to use, for example Dispatch date/time, Arrival date/time, Clear date/time, naming the new fields whatever you would like.
Now, to calculate the difference between any of these date/time fields, simply use the following function which calculates the difference between two dates and times. I like to see the difference in minutes because it makes the most sense for police response time data:
Response Time in Minutes: DateDiff(“n”,[ Dispatch_Datetime],[Arrival_Datetime])
Now the fun begins. For instance, you can calculate the “total time spent on calls” using arrival and clear times. Of course this doesn’t necessarily account for time officers spend writing reports after they clear a call, etc. But it will give you a rough sense of how much time is spent at each call.
Here are some other questions to contemplate…
Do response times get longer when your agency’s compliment is down? Can you use this information to make a public safety case for more officers when your compliment is low?
Which types of calls consume the most time from officers?
How do response times vary by call priority? *You can use a crosstab query to determine this.
Is there any correlation between call priority, response time, and cruiser accidents?
What other uses can you think of for this type of analysis?