Karel Kostev1, Wolfgang Rathmann2. 1. 1 Epidemiology, IMS Health, Frankfurt am Main, Germany. 2. 2 German Diabetes Center, Institute for Biometrics and Epidemiology, Düsseldorf, Germany.
Abstract
BACKGROUND: The aim was to compare the prescribed and calculated daily insulin dosages based on prescription data in type 2 diabetes patients in a general practice database. METHODS: A total of 17 782 type 2 diabetes patients (age: 70.0 ± 11.5 years; 52% males; 16% diabetologist care) with ≥2 insulin prescriptions from 834 practices were analyzed (Disease Analyser: 01/2011-12/2015). Prescribed daily dosage (PDD) (physician documentation) and calculated daily dose (CDD) (pack size × strength × volume / days between 2 prescriptions) were calculated for short-acting, long-acting, and premixed insulins. PDD and CDD were compared using paired t-tests. Linear regression models assessed the associations of insulin dosage difference (CDD-PDD) with age, sex, diabetologist care, private health insurance, obesity, HbA1c, hypertension, hyperlipidemia, macro- and microvascular complications. RESULTS: Mean [SD] CDDs were higher than PDDs for short-acting (52 [28] vs 48 [26] units/day), long-acting (30 [20] vs 24 [15] units/day), and premixed (46 [26] vs 40 [21] units/day) insulins (all P < .05). In regression models, age (per year) was associated with higher CDD-PDD differences (+0.11, +0.04, +0.10; P < .01) for short-, long-acting, and premixed insulins, respectively. Diabetologist care was related to lower differences (-2.92, -1.02, -3.65; all P < .05). HbA1c was associated with higher differences in long-acting and premixed insulins, but was related to a lower difference in short-acting insulins (all P < .05). CONCLUSIONS: CDD in primary care database studies substantially overestimate the PDD (8-25%). Age, diabetologist care, and glycemic control were related to CDD-PDD differences. Priming and safety shots with pens, dosing errors, or the accumulation of insulin reserves by patients may be underlying reasons.
BACKGROUND: The aim was to compare the prescribed and calculated daily insulin dosages based on prescription data in type 2 diabetes patients in a general practice database. METHODS: A total of 17 782 type 2 diabetes patients (age: 70.0 ± 11.5 years; 52% males; 16% diabetologist care) with ≥2 insulin prescriptions from 834 practices were analyzed (Disease Analyser: 01/2011-12/2015). Prescribed daily dosage (PDD) (physician documentation) and calculated daily dose (CDD) (pack size × strength × volume / days between 2 prescriptions) were calculated for short-acting, long-acting, and premixed insulins. PDD and CDD were compared using paired t-tests. Linear regression models assessed the associations of insulin dosage difference (CDD-PDD) with age, sex, diabetologist care, private health insurance, obesity, HbA1c, hypertension, hyperlipidemia, macro- and microvascular complications. RESULTS: Mean [SD] CDDs were higher than PDDs for short-acting (52 [28] vs 48 [26] units/day), long-acting (30 [20] vs 24 [15] units/day), and premixed (46 [26] vs 40 [21] units/day) insulins (all P < .05). In regression models, age (per year) was associated with higher CDD-PDD differences (+0.11, +0.04, +0.10; P < .01) for short-, long-acting, and premixed insulins, respectively. Diabetologist care was related to lower differences (-2.92, -1.02, -3.65; all P < .05). HbA1c was associated with higher differences in long-acting and premixed insulins, but was related to a lower difference in short-acting insulins (all P < .05). CONCLUSIONS: CDD in primary care database studies substantially overestimate the PDD (8-25%). Age, diabetologist care, and glycemic control were related to CDD-PDD differences. Priming and safety shots with pens, dosing errors, or the accumulation of insulin reserves by patients may be underlying reasons.
Entities:
Keywords:
adherence; daily dose; diabetes; insulin; primary care
Authors: R M Stoekenbroek; K L Rensing; S J Bernelot Moens; M Nieuwdorp; J H DeVries; A H Zwinderman; E S Stroes; C J Currie; B A Hutten Journal: Atherosclerosis Date: 2015-03-30 Impact factor: 5.162
Authors: Elias S Siraj; Daniel J Rubin; Matthew C Riddle; Michael E Miller; Fang-Chi Hsu; Faramarz Ismail-Beigi; Shyh-Huei Chen; Walter T Ambrosius; Abraham Thomas; William Bestermann; John B Buse; Saul Genuth; Carol Joyce; Christopher S Kovacs; Patrick J O'Connor; Ronald J Sigal; Sol Solomon Journal: Diabetes Care Date: 2015-10-13 Impact factor: 19.112