A plea for consistent reliability in ambulatory blood pressure monitoring: an unusual case of software error in Spacelabs Report Management System 92506

Blood Press Monit. 2013 Feb;18(1):27-31. doi: 10.1097/MBP.0b013e32835a375f.

Abstract

Objective: Ambulatory blood pressure monitors are subject to extensive validation protocols, but no international guidelines on the software processing the collected raw data exist. Hence, there seems to be little or no control of ambulatory blood pressure monitoring (ABPM) software with respect to errors. In this paper, we wish to point out an important error in Spacelabs Report Management System 92506 software.

Methods: By chance, we noticed discrepancies in the Spacelabs Report Management System 92506 hourly average tabular as shown on-screen and on printout. To exclude the possibility of a random error, 97 ABPM reports were evaluated. In a random patient, we calculated the hourly averages by the arithmetic mean from all measurements. Similarly, the summary average of 24 h, daytime and night-time blood pressure was calculated both by the arithmetic mean of all measurements and by the mean of hourly averages in the respective periods.

Results: Evaluation of ABPM reports showed errors in 89 out of 97 (92%). In a random patient, the numerical difference between printout and on-screen hourly averages was considerable, ranging from -37 to 18 mmHg systolic and from -16 to 10 mmHg diastolic. Calculation on the basis of raw data established that on-screen hourly average tabular was correct, whereas printout values were erroneous. The erroneous values were also found in the exported hourly average tabular.

Conclusion: If researchers base calculations on the use of erroneous data from printout or exported hourly average tabular, the results and hence the conclusions may be wrong. Focus on ABPM software is warranted.

Publication types

  • Clinical Trial
  • Multicenter Study
  • Randomized Controlled Trial

MeSH terms

  • Blood Pressure Monitoring, Ambulatory / instrumentation*
  • Diabetes Mellitus, Type 2 / physiopathology*
  • Equipment Failure Analysis*
  • Equipment Failure*
  • Female
  • Humans
  • Male
  • Software*