Can Big Data Solve Small Problems? Paper Use in a Paperless Hospital

Area of Science:

• Health Informatics
• Data Science
• Hospital Administration

Background:

• Hospitals are increasingly adopting digital systems to reduce paper consumption.
• Assessing the actual extent and sources of remaining paper use is crucial for effective waste reduction.

Purpose of the Study:

• To evaluate the utility of a "Big Data" approach in analyzing paper printing in a nearly paperless hospital.
• To quantify monthly paper usage within a 700-bed healthcare facility.

Main Methods:

• A "Big Data" methodology was employed to analyze paper printing logs.
• Monthly printing volumes were quantified and compared to general population benchmarks.

Main Results:

• The hospital printed 1.2 to 1.5 million pages monthly, approximately 10% of an average citizen's monthly paper use.
• Identified paper printing volumes were not exceptionally high compared to other organizations.
• The "Big Data" approach was limited by the lack of log data from source programs, hindering detailed analysis.

Conclusions:

• While "Big Data" can quantify paper usage, it was insufficient to identify specific printing sources for reduction.
• Further data integration, including source program logs, is necessary for actionable insights into reducing hospital paper consumption.