Summary
Background: Clinical pathways are evidence-based recommendations for treating a diagnosis. Although
implementations of clinical pathways have reduced medical errors, lowered costs, and
improved patient outcomes, monitoring whether a patient is following the intended
pathway is problematic. Implementing a variance reporting program is impeded by the
lack of a reliable source of electronic data and automatic retrieval methods.
Objectives: Our objective is to develop an automated method of measuring and reporting patient
variance from a clinical pathway.
Methods: We identify a viable and ubiquitous data source for establishing the realized patient’s
path- Health Level Seven (HL7) formatted message exchanges between Hospital Information
Systems. This is in contrast to current practices in most hospitals where data for
clinical pathway variance reporting is obtained from multiple data sources, often
retrospectively. This paper develops a method to use message exchanges to automatically
establish and compare a patient’s path against a clinical pathway. Our method not
only considers pathway activities as is common practice, but also extracts patient
outcomes from HL7 messages and reports this in addition to the variance.
Results: Using data from our partner hospital, we illustrate our clinical pathway variance
analysis tool using major joint replacement patients. We validate our method by comparing
audit results for a random sample of HL7 constructed pathways with data extracted
from patient charts. We report several variances such as omitted laboratory tests
or additional activities such as blood transfusions. Our method successfully identifies
variances and reports them in a quantified way to support decisions related to quality
control.
Conclusions: Our approach differs from previous studies in that a quantitative measure is established
over three dimensions: (1) omissions from the pathway, (2) additions to the pathway,
and (3) patient outcomes. By examining variances providers can evaluate clinical decisions,
and support quality feedback and training mechanisms.
Citation: Konrad R, Tulu B, Lawley M. Monitoring adherence to evidence based practices – a
method to utilize HL7 messages from hospital information systems. Appl Clin Inf 2013;
4: 126–143
http://dx.doi.org/10.4338/ACI-2012-06-RA-0026
Keywords
HL7 - inpatient care - workflow - monitoring - surveillance - clinical decision support
