Vol 22, No 5 (2017)
Original research articles
Published online: 2017-09-01

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Assessment of performance indicators of a radiotherapy department using an electronic medical record system

Yasir A. Bahadur1, Camelia Constantinescu2, Ammar Y. Bahadur3, Ruba Y. Bahadur4
DOI: 10.1016/j.rpor.2017.06.002
Rep Pract Oncol Radiother 2017;22(5):360-367.

Abstract

Aim

To retrospectively assess the performance indicators of our radiotherapy department and their temporal trends, using a commercially available electronic-medical-record (EMR) system.

Background

A recent trend in healthcare quality is to define and evaluate performance indicators of the service provided.

Materials and methods

Patient and external-beam-radiotherapy-treatments data were retrieved using the Mosaiq EMR system from 1-January-2012 till 31-December-2015.

Annual performance indicators were evaluated as: productivity (number of new cases/year and diagnosis distribution); complexity (ratio of Volumetric-Modulated-Arc-Therapy (VMAT) courses, average number of imaging procedures/patient); and quality (average, median and 90th percentile waiting times from admission to first treatment).

The temporal trends of all performance indicators were assessed by linear regression.

Results

Productivity: the number of new cases/year increased with an average rate of 4%. Diagnosis distribution showed that breast is the main pathology treated, followed by gastro-intestinal and head-and-neck.

Complexity: the ratio of VMAT courses increased from 13% to 35%, with an average rate of 7% per year. The average number of imaging procedures/patient increased from 8 to 11.

Quality: the waiting times from admission to treatment remained stable over time (R2[[ce:hsp sp="0.25"/]]≤[[ce:hsp sp="0.25"/]]0.1), with average, median and 90th percentile values around 20, 15, and 31 days, respectively.

Conclusions

An EMR system can be used to: monitor the performance indicators of a radiotherapy department, identify workflow processes needing attention and improvement, estimate future demands of resources.

Temporal analysis of our data showed an increasing trend in productivity and complexity paired with constant waiting times.

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