Problem
The Problem Addressed:
The study seeks to evaluate the use of computer-aided dispatch (CAD) systems to improve the implementation of hot spot policing by addressing challenges in resource allocation, officer compliance, and accurate measurement of intervention dosages.
General Impact:
Ineffective resource allocation in policing can lead to suboptimal crime reduction and strained police-community relations. By optimizing CAD for proactive policing, this study highlights an innovative method for improving law enforcement's efficiency in targeting high-crime areas while potentially enhancing community trust.
Research Questions:
- Can CAD effectively deliver planned frequencies, doses, and dosages of supplemental patrols to high-crime areas?
- Do supplemental patrols via CAD align with peak periods of criminal activity?
- Does the use of CAD introduce randomness in patrol timing to maximize deterrent effects?
- Does directed patrol reduce officers' self-initiated activities in targeted areas?
Method and Analysis
Program Evaluated or Gaps Addressed:
The study evaluated a directed patrol initiative using CAD in Portland, Oregon, which programmed 16,200 supplemental community engagement patrols to be communicated as routine calls. The initiative aimed to overcome limitations in hot spot policing such as officer discretion and inconsistent patrol deployment.
Data and Sample Size:
- Data Sources: CAD records, historical crime data, 911 dispatch logs, and officer self-initiated call logs.
- Sample Size: 90 high-crime locations divided into three groups: no patrols (control), two supplemental patrols per day, and four patrols per day.
Analysis Used:
The study employed randomized block assignment and statistical analyses (e.g., correlation studies and variance analyses) to evaluate patrol frequency, dose delivery, temporal alignment with crime patterns, and randomness in patrol timing.
Outcome
Key Findings:
- Delivery of Patrols: CAD achieved 78% and 81% completion rates for two and four patrols per day groups, respectively. Planned dosage ratios were maintained.
- Patrol Effectiveness: Patrols coincided with 72.4% of peak crime periods, showing strong temporal alignment with criminal activity.
- Randomness: Scheduling randomness was achieved through pre-programming and call delays, potentially maximizing deterrence.
- Officer Activity: Directed patrols did not negatively affect self-initiated officer activities in treatment areas.
Implications or Recommendations:
- Strategic Benefits: CAD enhances control over proactive policing efforts, ensuring consistent patrol dosages and optimizing crime deterrence in high-risk areas.
- Operational Integration: Using CAD for directed patrol aligns with existing law enforcement protocols, facilitating adoption and scalability.
- Future Research: Investigating long-term impacts on crime rates and community relations could validate CAD's efficacy further. Additionally, exploring automation and integration with other technologies like GPS could refine resource allocation strategies.
This study underscores the potential of leveraging technology to improve law enforcement practices, setting a precedent for proactive and data-driven policing strategies.