The effectiveness of an automated algorithm as a tool for investigating the cause of anaemia in undiagnosed patients from general practitioners.

Background The Dutch guideline algorithm for the analysis of anaemia in patients of general practitioners (GPs) was programmed in a Clinical Decision Support system (CDS-anaemia) to support the process of diagnosing the cause of anaemia in the laboratory. This study investigates the diagnostic yield of the automated anaemia algorithm compared to that of the manual work up by the general practitioner. Methods This retrospective population-based study consisted of 2697 people ≥18 years. Anaemia was defined according to the Dutch College of General Practitioners (DCGP) guideline. Causes of anaemia were based on the DCGP guidelines with the corresponding blood tests. The number of blood tests and causes of anaemia were measured in two separate periods in both the (CDS-anaemia) pilot group and a control group in which routine care was provided. Results Patients from GPs supported by CDS-anaemia had higher chances of having more anaemia-related blood tests being performed. This resulted in finding significantly more causes of anaemia in the pilot group compared to the control group with respect to iron deficiency (resp. 31.3% vs 14.5%), possible iron deficiency (resp. 11.4% vs 2.8%), iron deficiency in acute phase (2.6% vs 0.5%), chronic disease/infection/inflammation (23.5% vs 1.9%), vitamin B12 deficiency (4.5% vs 1.9%), possible vitamin B12 deficiency (16.8% vs 8.7%), folate deficiency (3.3% vs 0.9%) and possible bone marrow disorder (3.8% vs 0.0%); p < 0.05. Conclusions This study suggests that an automated-algorithm support can effectively aid in the diagnostic work-up of anaemia in primary care to find more causes of anaemia.