Interpretation of EQA results and EQA-based trouble shooting.

Important objectives of External Quality Assessment (EQA) is to detect analytical errors and make corrective actions. The aim of this paper is to describe knowledge required to interpret EQA results and present a structured approach on how to handle deviating EQA results. The value of EQA and how the EQA result should be interpreted depends on five key points: the control material, the target value, the number of replicates, the acceptance limits and between lot variations in reagents used in measurement procedures. This will also affect the process of finding the sources of errors when they appear. The ideal EQA sample has two important properties: it behaves as a native patient sample in all methods (is commutable) and has a target value established with a reference method. If either of these two criteria is not entirely fulfilled, results not related to the performance of the laboratory may arise. To help and guide the laboratories in handling a deviating EQA result, the Norwegian Clinical Chemistry EQA Program (NKK) has developed a flowchart with additional comments that could be used by the laboratories e.g. in their quality system, to document action against deviations in EQA. This EQA-based trouble-shooting tool has been developed further in cooperation with the External quality Control for Assays and Tests (ECAT) Foundation. This flowchart will become available in a public domain, i.e. the website of the European organisation for External Quality Assurance Providers in Laboratory Medicine (EQALM).

Nursing home patients with diabetes: prevalence, drug treatment and glycemic control.

AIMS: Determine prevalence of diabetes, and describe use of blood glucose lowering (BGL) drugs and glycemic control in Norwegian nursing homes. METHODS: In this cross-sectional study we collected details of BGL drugs, capillary blood glucose measurements (CBGM) in the last four weeks and HbA1c measurements in the last 12 months from the medical records of patients with diabetes, within a population of 742 long-term care patients from 19 randomly selected nursing homes in Western Norway. Descriptive statistics were applied, and Pearson's chi-squared (P≤0.05) or non-overlapping 95% confidence intervals were interpreted as significant effects. RESULTS: 116 patients (16%) had diabetes, 100 of these gave informed consent and medical data were available. BGL treatment was as follows: (1) insulin only (32%), (2) insulin and oral antidiabetics (OADs) (15%), (3) OADs only (27%) and (4) no drugs (26%). Patients with cognitive impairment were less likely to receive medical treatment (P=0.04). CBGM and HbA1c measurements were performed for 73% and 77% of patients, respectively. Mean HbA1c was 7.3% (57 mmol/mol), 46% of patients had an HbA1c <7.0% (53 mmol/mol), and CBGM consistent with risk of hypoglycemia was found for 60% of these patients. CONCLUSIONS: Prevalence of diabetes and BGL treatment in Norwegian nursing homes is comparable to other European countries. Although special care seems to be taken when choosing treatment for patients with cognitive impairment, there are signs of overtreatment in the population as a whole. The strict glycemic control unveiled may negatively affect these frail patients' quality of life and increase the risk of early death.