Use of electronic medical records for clinical research in the management of type 2 diabetes

Dose-response associations between metabolic indexes and the risk of comorbid type 2 diabetes mellitus among rheumatoid arthritis patients from Northern China: a case-control study

OBJECTIVE

To investigate whether there were any differences in the patterns of metabolic abnormalities between patients with rheumatoid arthritis (RA) with comorbid type 2 diabetes mellitus (T2DM) and other populations, and to plot the dose-response relationships between metabolic indexes and the risk of comorbid T2DM among patients with RA.

DESIGN AND SETTING

This is a retrospective case-control study using electronic medical records (EMRs). Patients with RA and/or T2DM or controls who were admitted to the First Affiliated Hospital of China Medical University between April 2008 and December 2016 were retrospectively recruited through the EMR system. After age-matching and sex-matching, 261 controls, 274 patients with T2DM, 276 patients with RA and 151 patients with RA+T2DM were eventually recruited.

RESULTS

Patients with RA+T2DM exhibited higher levels of systolic blood pressure (SBP), fasting plasma glucose (FPG) and triglyceride (TG) than the RA only patients. Moreover, the proportions of impaired fasting glucose (IFG), and total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) dyslipidaemia in the RA+T2DM group were higher than those in the RA alone group (for IFG: 28.48% vs 18.84%, p=0.02; for TC: 25.17% vs 15.22%, p=0.01; for LDL-C: 25.83% vs 17.03%; p=0.03). Rheumatoid factor (RF) positivity and IFG were independent risk indicators for comorbid T2DM among patients with RA (for RF positivity: OR=0.45; 95% CI: 0.29 to 0.69; p<0.001; for IFG: OR=1.70; 95% CI: 1.04 to 2.76; p=0.03).

CONCLUSION

Linear dose-response associations between SBP, TC, TG and the risk of comorbid T2DM among patients with RA were observed, whereas a non-linear dose-response association between FPG and the risk of comorbid T2DM was found. Patients with RA+T2DM were more likely to exhibit metabolic abnormalities than RA only patients. Patients with RA+T2DM with metabolic abnormalities deserve more attention from rheumatologists and endocrinologists.

Validation of electronic medical data: Identifying diabetes prevalence in general practice

BACKGROUND:

Electronic medical records are increasingly used for research with limited external validation of their data.

OBJECTIVE:

This study investigates the validity of electronic medical data (EMD) for estimating diabetes prevalence in general practitioner (GP) patients by comparing EMD with national Bettering the Evaluation and Care of Health (BEACH) data.

METHOD:

A "decision tree" was created using inclusion/exclusion of pre-agreed variables to determine the probability of diabetes in absence of diagnostic label, including diagnoses (coded/free-text diabetes, polycystic ovarian syndrome, impaired glucose tolerance, impaired fasting glucose), diabetic annual cycle of care (DACC), glycated haemoglobin (HbA1c) > 6.5%, and prescription (metformin, other diabetes medications). Via SQL query, cases were identified in EMD of five Illawarra and Southern Practice Network practices (30,007 active patients; from 2 years to January 2015). Patient-based Supplementary Analysis of Nominated Data (SAND) sub-studies from BEACH investigating diabetes prevalence (1172 GPs; 35,162 patients; November 2012 to February 2015) were comparison data. SAND results were adjusted for number of GP encounters per year, per patient, and then age-sex standardised to match age-sex distribution of EMD patients. Cluster-adjusted 95% confidence intervals (CIs) were calculated for both datasets.

RESULTS:

EMD diabetes prevalence (T1 and/or T2) was 6.5% (95% CI: 4.1-8.9). Following age-sex standardisation, SAND prevalence, not significantly different, was 6.7% (95% CI: 6.3-7.1). Extracting only coded diagnosis missed 13.0% of probable cases, subsequently identified through the presence of metformin/other diabetes medications (*without other indicator variables) (6.1%), free-text diabetes label (3.8%), HbA1c result* (1.6%), DACC* (1.3%), and diabetes medications* (0.2%).

DISCUSSION:

While complex, proxy variables can improve usefulness of EMD for research. Without their consideration, EMD results should be interpreted with caution.

CONCLUSION:

Enforceable, transparent data linkages in EMRs would resolve many problems with identification of diagnoses. Ongoing data quality improvement remains essential.

Assessing variability in compliance with recommendations given by the International Diabetes Federation (IDF) for patients with type 2 diabetes in primary care using electronic records. The APNA study

OBJECTIVE

Assess compliance with the IDF recommendations for patients with Diabetes Type2 (DM2), and its variability, by groups of doctors and nurses who provide primary care services in Navarre (Spain).

MATERIALS AND METHODOLOGIES

A cross-sectional study of a population of 462,568 inhabitants, aged ≥18 years in 2013, attended by 381 units of doctor/nurse (quota). Clinical data were collected retrospectively through electronic records. Using cluster analysis, we identified two groups of units according to the score for each indicator. We calculated the Odds Ratio, adjusted for age sex, BMI, socioeconomic status and smoking, for complying with each recommendation whether a patient was treated by one of the quota from the highest score to the lowest. 30,312 patients with DM2 were identified: prevalence: 6.39%; coefficient of variation between UDN: 22.8%; biggest cluster 7.7% and smallest 5.3%; OR=1.54 (1.50-1.58). The HbA1c control at ≤8% was 82.8% (82.2-83.3) and >9% was 7.6% (7.3-8.0), with OR 1.79 (1.69-1.89) and 2.62 (2.36-2.91) respectively. Control of BP and LDL-C show significant differences between the clusters.

CONCLUSIONS

An important variability was identified according to the doctor treating patients. The average HbA1c control is acceptable being limited in BP and LDL-C.

Data Mining Approach to Estimate the Duration of Drug Therapy from Longitudinal Electronic Medical Records

Background:

Electronic Medical Records (EMRs) from primary/ ambulatory care systems present a new and promising source of information for conducting clinical and translational research.

Objectives:

To address the methodological and computational challenges in order to extract reliable medication information from raw data which is often complex, incomplete and erroneous. To assess whether the use of specific chaining fields of medication information may additionally improve the data quality.

Methods:

Guided by a range of challenges associated with missing and internally inconsistent data, we introduce two methods for the robust extraction of patient-level medication data. First method relies on chaining fields to estimate duration of treatment (“chaining”), while second disregards chaining fields and relies on the chronology of records (“continuous”). Centricity EMR database was used to estimate treatment duration with both methods for two widely prescribed drugs among type 2 diabetes patients: insulin and glucagon-like peptide-1 receptor agonists.

Results:

At individual patient level the “chaining” approach could identify the treatment alterations longitudinally and produced more robust estimates of treatment duration for individual drugs, while the “continuous” method was unable to capture that dynamics. At population level, both methods produced similar estimates of average treatment duration, however, notable differences were observed at individual-patient level.

Conclusion:

The proposed algorithms explicitly identify and handle longitudinal erroneous or missing entries and estimate treatment duration with specific drug(s) of interest, which makes them a valuable tool for future EMR based clinical and pharmaco-epidemiological studies. To improve accuracy of real-world based studies, implementing chaining fields of medication information is recommended.

Addition of or switch to insulin therapy in people treated with glucagon-like peptide-1 receptor agonists: A real-world study in 66 583 patients

BACKGROUND

Real world outcomes of addition or switch to insulin therapy in type 2 diabetes (T2DM) patients on glucagon-like paptide-1 receptor agonist (GLP-1RA) with inadequately controlled hyperglycaemia, are not known.

MATERIALS AND METHODS

Patients with T2DM (n = 66 583) with a minimum of 6 months of GLP-1RA treatment and without previous insulin treatment were selected. Those who added insulin (n = 39 599) or switched to insulin after GLP-1RA cessation (n = 4706) were identified. Adjusted changes in glycated haemoglobin (HbA1c), weight, systolic blood pressure (SBP), and LDL cholesterol were estimated over 24 months follow-up.

RESULTS

Among those who continued with GLP-1RA treatment without adding or switching to insulin, the highest adjusted mean HbA1c change was achieved within 6 months, with no further glycaemic benefits observed during 24 months of follow-up. Addition of insulin within 6 months of GLP-1RA initiation was associated with 18% higher odds of achieving HbA1c <7% at 24 months, compared with adding insulin later. At 24 months, those who added insulin reduced HbA1c significantly by 0.55%, while no glycaemic benefit was observed in those who switched to insulin. Irrespective of intensification with insulin, weight, SBP and LDL cholesterol were significantly reduced by 3 kg, 3 mm Hg, and 0.2 mmol/L, respectively, over 24 months.

CONCLUSIONS

Significant delay in intensification of treatment by addition of insulin is observed in patients with T2DM inadequately controlled with GLP-1RA. Earlier addition of insulin is associated with better glycaemic control, while switching to insulin is not clinically beneficial during 2 years of treatment. Non-responding patients on GLP-1RA would benefit from adding insulin therapy, rather than switching to insulin.

Weight gain in insulin-treated patients by body mass index category at treatment initiation: new evidence from real-world data in patients with type 2 diabetes

AIMS

To evaluate, in patients with type 2 diabetes (T2DM) treated with insulin, the extent of weight gain over 2 years of insulin treatment, and the dynamics of weight gain in relation to glycaemic achievements over time according to adiposity levels at insulin initiation.

MATERIALS AND METHODS

Patients with T2DM (n = 155 917), who commenced insulin therapy and continued it for at least 6 months, were selected from a large database of electronic medical records in the USA. Longitudinal changes in body weight and glycated haemoglobin (HbA1c) according to body mass index (BMI) category were estimated.

RESULTS

Patients had a mean age of 59 years, a mean HbA1c level of 9.5%, and a mean BMI of 35 kg/m² at insulin initiation. The HbA1c levels at insulin initiation were significantly lower (9.2-9.4%) in the obese patients than in patients with normal body weight (10.0%); however, the proportions of patients with HbA1c >7.5% or >8.0% were similar across the BMI categories. The adjusted weight gain fell progressively with increasing baseline BMI category over 6, 12 and 24 months (p < .01). The adjusted changes in HbA1c were similar across BMI categories. A 1% decrease in HbA1c was associated with progressively less weight gain as pretreatment BMI rose, ranging from a 1.24 kg gain in those with a BMI <25 kg/m² to a 0.32 kg loss in those with a BMI > 40 kg/m² .

CONCLUSIONS

During 24 months of insulin treatment, obese patients gained significantly less body weight than normal-weight and overweight patients, while achieving clinically similar glycaemic benefits. These data provide reassurance with regard to the use of insulin in obese patients.

The association of the treatment with glucagon-like peptide-1 receptor agonist exenatide or insulin with cardiovascular outcomes in patients with type 2 diabetes: a retrospective observational study

BACKGROUND

To evaluate the association of treatment with glucagon-like peptide-1 (GLP-1) receptor agonist exenatide and/or insulin on macrovascular outcomes in patients with type 2 diabetes (T2DM).

METHODS

We conducted a retrospective longitudinal pharmaco-epidemiological study using large ambulatory care data to evaluate the risks of heart failure (HF), myocardial infarction (MI) and stroke in established T2DM patients who received a first prescription of exenatide twice daily (EBID) or insulin between June 2005 and May 2009, with follow-up data available until December 2012. Three treatment groups were: EBID with oral antidiabetes drugs (OADs) (EBID, n = 2804), insulin with OADs (Insulin, n = 28551), and those who changed medications between EBID and insulin or had combination of EBID and insulin during follow-up, along with OADs (EBID + insulin, n = 7870). Multivariate Cox-regression models were used to evaluate the association of treatment groups with the risks of macrovascular events.

RESULTS

During a median 3.5 years of follow-up, cardiovascular event rates per 1000 person-years were significantly lower for the EBID and EBID + insulin groups compared to the insulin group (HF: 4.4 and 6.1 vs. 17.9; MI: 1.1 and 1.2 vs. 2.5; stroke: 2.4 and 1.8 vs. 6.1). Patients in the EBID/EBID + insulin group had significantly reduced risk of HF, MI and stroke by 61/56%, 50/38% and 52/63% respectively, compared to patients in the insulin group (p < 0.01).

CONCLUSIONS

Treatment with exenatide, with or without concomitant insulin was associated with reduced macrovascular risks compared to insulin; although inherent potential bias in epidemiological studies should be considered.