Agreement between self-report and medical records on signs and symptoms of respiratory illness

Background: Information on patient symptoms can be obtained by patient self-report or medical records review. Both methods have limitations. Aims: To assess the agreement between self-report and documentation in the medical records of signs/symptoms of respiratory illness (fever, cough, runny nose, sore throat, headache, sinus problems, muscle aches, fatigue, earache, and chills). Methods: Respondents were 176 research participants in the Hutterite Influenza Prevention Study during the 2008-2009 influenza season with information about the presence or absence of signs/symptoms from both self-report and primary care medical records. Results: Compared with medical records, lower proportions of self-reported fever, sore throat, earache, cough, and sinus problems were found. Total agreements between self-report and medical report of symptoms ranged from 61% (for sore throat) to 88% (for muscle aches and earache), with kappa estimates varying from 0.05 (for chills) to 0.41 (for cough) and 0.51 (for earache). Negative agreement was considerably higher (from 68% for sore throat to 93% for muscle aches and earache) than positive agreement (from 13% for chills to 58% for earache) for each symptom except cough where positive agreement (77%) was higher than negative agreement (64%). Agreements varied by age group. We found better agreement for earache (kappa=0.62) and lower agreements for headache, sinus problems, muscle aches, fatigue, and chills in older children (aged =5 years) and adults. Conclusions: Agreements were variable depending on the specific symptom. Contrary to research in other patient populations which suggests that clinicians report fewer symptoms than patients, we found that the medical record captured more symptoms than selfreport. Symptom agreement and disagreement may be affected by the perspectives of the person experiencing them, the observer, the symptoms themselves, measurement error, the setting in which the symptoms were observed and recorded, and the broader community and cultural context of patients. © 2012 Primary Care Respiratory Society UK. All rights reserved.

Focus group interviews:a guide for palliative care researchers and clinicians

The focus group interview is an increasingly common qualitative research method used by health professionals. General approaches to conducting focus groups have been published. There has, however, been minimal exploration of issues regarding the use of focus groups with palliative care populations and data analysis procedures have been underreported. The aim of this paper is to provide a guide for conducting focus groups drawing on palliative care examples. A succinct outline of why, when and how to use focus groups is offered. Key ethical and practical issues are explored as well as considerations for data analysis. This guide offers researchers and clinicians fundamental strategies for the use of focus groups within the palliative care context.

Guide to Inclined Plate Settlers

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Evaluation of an algorithm to guide patients with type 1 diabetes treated with continuous subcutaneous insulin infusion on how to respond to real-time continuous glucose levels:A randomized controlled trial

OBJECTIVE - To evaluate an algorithm guiding responses of continuous subcutaneous insulin infusion (CSII)-treated type 1 diabetic patients using real-time continuous glucose monitoring (RT-CGM). RESEARCH DESIGN AND METHODS - Sixty CSII-treated type 1 diabetic participants (aged 13-70 years, including adult and adolescent subgroups, with A1C =9.5%) were randomized in age-, sex-, and A1C-matched pairs. Phase 1 was an open 16-week multicenter randomized controlled trial. Group A was treated with CSII/RT-CGM with the algorithm, and group B was treated with CSII/RT-CGM without the algorithm. The primary outcome was the difference in time in target (4-10 mmol/l) glucose range on 6-day masked CGM. Secondary outcomes were differences in A1C, low (=3.9 mmol/l) glucose CGM time, and glycemic variability. Phase 2 was the week 16-32 follow-up. Group A was returned to usual care, and group B was provided with the algorithm. Glycemia parameters were as above. Comparisons were made between baseline and 16 weeks and 32 weeks. RESULTS - In phase 1, after withdrawals 29 of 30 subjects were left in group A and 28 of 30 subjects were left in group B. The change in target glucose time did not differ between groups. A1C fell (mean 7.9% [95% CI 7.7-8.2to 7.6% [7.2-8.0]; P <0.03) in group A but not in group B (7.8% [7.5-8.1] to 7.7 [7.3-8.0]; NS) with no difference between groups. More subjects in group A achieved A1C =7% than those in group B (2 of 29 to 14 of 29 vs. 4 of 28 to 7 of 28; P = 0.015). In phase 2, one participant was lost from each group. In group A, A1C returned to baseline with RT-CGM discontinuation but did not change in group B, who continued RT-CGM with addition of the algorithm. CONCLUSIONS - Early but not late algorithm provision to type 1 diabetic patients using CSII/RT-CGM did not increase the target glucose time but increased achievement of A1C =7%. Upon RT-CGM cessation, A1C returned to baseline. © 2010 by the American Diabetes Association.