Development and preliminary validation of a dynamic, patient-tailored method to detect abnormal laboratory test results.
Laboratory test results in primary care are flagged as 'abnormal' when they fall outside a population-based Reference Interval (RI), typically generating many alerts with a low specificity. In order to decrease alert frequency while retaining clinical relevance, we developed a method to assess dynamic, patient-tailored RIs based on mixed-effects linear regression models. Potassium test results from primary care were used as proof-of-concept test bed. Clinical relevance was assessed via a survey administered to general practitioners (GPs). Overall, the dynamic, patient-tailored method and the combination of both methods flagged 20% and 36% fewer values as abnormal than the population-based method. Nineteen out of 43 invited GPs (44%) completed the survey. The population-based method yielded a better sensitivity than the patient-tailored and the combined methods (0.51 vs 0.41 and 0.38, respectively) but a lower PPV (0.66 vs 0.67 and 0.76, respectively). We conclude that a combination of population-based and patient-tailored RIs can improve the detection of abnormal laboratory results. We suggest that lab values outside both RIs be flagged with high priority in clinical practice.
NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, Institute of Population Health, University of Manchester, Manchester, UK.
Paolo
P
Fraccaro
NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, Institute of Population Health, University of Manchester, Manchester, UK.
Benjamin
B
Brown
Health eResearch Centre, Farr Institute for Health Informatics Research, UK.
Mattia
M
Prosperi
Health eResearch Centre, Farr Institute for Health Informatics Research, UK.
Matthew
M
Sperrin
NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, Institute of Population Health, University of Manchester, Manchester, UK.
Iain
I
Buchan
NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, Institute of Population Health, University of Manchester, Manchester, UK.
Niels
N
Peek
D002984:Clinical Laboratory Information Systems / Q000458:organization & administration*; D019411:Clinical Laboratory Techniques / Q000379:methods*; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D057286:Electronic Health Records / Q000458:organization & administration*; D006801:Humans; D000069550:Machine Learning; D018802:Patient-Centered Care / Q000458:organization & administration*; D010865:Pilot Projects; D015203:Reproducibility of Results; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D006113:United Kingdom