[A retrospective referral analysis in nuclear medicine].
OBJECTIVE
Written reports are the basis of collaboration between clinician and radiologist or nuclear medicine specialist. For clinicians it is important to receive useful and accurate reports that answer their questions. A thorough referral note is needed in order to choose an appropriate examination method and to write a good report.


METHODS
In this retrospective study we analyzed 1330 referral notes which were addressed to the Department of Nuclear Medicine at the University Clinic of Nuclear Medicine in Vienna between 2008 and 2011. Examinations were divided into 7 groups (heart, lung, bones, central nervous system, PET or PET-CT and other). The following aspects were studied: diagnosis, clinical question, overall legibility, handwritten/typed, contact information, legibility of the referring doctor's name, internal/external referral, additional information and region to be examined.


RESULTS
18% of the referrals per year were analyzed. A diagnosis was given in 95%, a clinical question in 73%. Additional information was found in 41%. Only 4% were typed. In nearly all of these aspects there were major differences when compared in the seven different groups.


CONCLUSIONS
To generate a good report and to provide optimal conditions for examination the data in the referral note should be given as exact as possible. Our retrospective analysis demonstrated the lack of referral note related information concerning the clinical question. In order to achieve good results, intelligent computer-assisted referrals might lead to better referral notes.
Abteilung für Nuklearmedizin, Medizinische Universität Wien, Österreich. philipp.ubl@meduniwien.ac.at
P
P
Ubl
L
L
Ringhofer
P
P
Dolliner
A
A
Staudenherz
D001317:Austria; D003952:Diagnostic Imaging / Q000706:statistics & numerical data*; D055991:Health Records, Personal; D011361:Professional Competence / Q000706:statistics & numerical data*; D011871:Radiology / Q000706:statistics & numerical data*; D012017:Referral and Consultation / Q000706:statistics & numerical data*