Nicklas Højgaard Rasmussen1, Reimar Wernich Thomsen2, Henrik Højgaard Rasmussen3, Mette Søgaard2. 1. Faculty of Health Sciences, Aarhus University, Denmark. Electronic address: nicklas_r@hotmail.com. 2. Department of Clinical Epidemiology, Institute of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark. 3. Centre for Nutrition and Bowel Diseases, Department of Medical Gastroenterology, Aalborg University Hospital, Aalborg, Denmark; Department of Clinical Medicine, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Abstract
BACKGROUND & AIMS: We examined the accuracy of ICD-10 diagnostic coding for undernutrition in Danish Hospitals, including the use of Nutritional Risk Screening 2002 guidelines. METHODS: We investigated a random sample of hospitalized patients registered in the Danish National Registry of Patients with a discharge diagnosis of undernutrition between 2002 and 2011 in the North Denmark Region. Based on medical record review we estimated the positive predictive value (PPV) of the undernutrition diagnosis. Stratification was made by calendar period, hospital type (local vs. university), gender, age, speciality and type of diagnosis code. Subsequently, we evaluated the use of Nutritional Risk Screening 2002 as recommended by the European Society of Clinical Nutrition and Metabolism and the Danish National Board of Health. RESULTS: We could retrieve the medical records of 172/200 sampled patients with undernutrition (86%). Nineteen patients were classified as being definite (screening-confirmed) cases and another 103 patients as probable (clinically-confirmed) cases of undernutrition, yielding a PPV of 11.0% (95% confidence interval [CI]: 6.8-16.7) for definite undernutrition and 70.9% (95% CI: 63.5-77.6) for any confirmed undernutrition. Only 26.2% of patients coded with undernutrition had been screened according to the Nutritional Risk Screening 2002. CONCLUSIONS: This population-based study found modest agreement between ICD-10 codes for undernutrition compared to a standard method (Nutritional Risk Screening 2002) as documented in medical doctors' records in Danish hospitals. Diagnoses of undernutrition contained in hospital discharge registries should be used with caution.
BACKGROUND & AIMS: We examined the accuracy of ICD-10 diagnostic coding for undernutrition in Danish Hospitals, including the use of Nutritional Risk Screening 2002 guidelines. METHODS: We investigated a random sample of hospitalized patients registered in the Danish National Registry of Patients with a discharge diagnosis of undernutrition between 2002 and 2011 in the North Denmark Region. Based on medical record review we estimated the positive predictive value (PPV) of the undernutrition diagnosis. Stratification was made by calendar period, hospital type (local vs. university), gender, age, speciality and type of diagnosis code. Subsequently, we evaluated the use of Nutritional Risk Screening 2002 as recommended by the European Society of Clinical Nutrition and Metabolism and the Danish National Board of Health. RESULTS: We could retrieve the medical records of 172/200 sampled patients with undernutrition (86%). Nineteen patients were classified as being definite (screening-confirmed) cases and another 103 patients as probable (clinically-confirmed) cases of undernutrition, yielding a PPV of 11.0% (95% confidence interval [CI]: 6.8-16.7) for definite undernutrition and 70.9% (95% CI: 63.5-77.6) for any confirmed undernutrition. Only 26.2% of patients coded with undernutrition had been screened according to the Nutritional Risk Screening 2002. CONCLUSIONS: This population-based study found modest agreement between ICD-10 codes for undernutrition compared to a standard method (Nutritional Risk Screening 2002) as documented in medical doctors' records in Danish hospitals. Diagnoses of undernutrition contained in hospital discharge registries should be used with caution.
Authors: Emelie Curovic Rotbain; Dennis Lund Hansen; Ove Schaffalitzky de Muckadell; Flemming Wibrand; Allan Meldgaard Lund; Henrik Frederiksen Journal: PLoS One Date: 2017-11-14 Impact factor: 3.240
Authors: Morten Schmidt; Sigrun Alba Johannesdottir Schmidt; Jakob Lynge Sandegaard; Vera Ehrenstein; Lars Pedersen; Henrik Toft Sørensen Journal: Clin Epidemiol Date: 2015-11-17 Impact factor: 4.790