Socioeconomic inequalities in cardiometabolic control in patients with type 2 diabetes.

BACKGROUND: The aim of this study was to determine if the achievement of control targets in patients with type 2 diabetes was associated with personal socioeconomic factors and if these associations were sex-dependent. METHODS: This cross-sectional, population-based study was conducted in Spain. Glycated haemoglobin (HbA1c) level and other clinical parameters were obtained from electronic primary care records (n = 32,638 cases). Socioeconomic status was determined using education level and yearly income. Among patients, having their HbA1c level checked during the previous year was considered as an indirect measure of the process of care, whereas tobacco use and clinical parameters such as HbA1c, low-density lipoprotein cholesterol (LDL-c) and blood pressure (BP) were considered intermediate control outcomes. General linear mixed effect models were used to assess associations. RESULTS: The achievement of metabolic and cardiovascular control targets in patients with type 2 diabetes was associated with educational level and income, and socioeconomic gradients differed by sex. The probability of having had an HbA1c test performed in the previous year was higher in patients with lower education levels. Patients in the lowest income and education level categories were less likely to have reached the recommended HbA1c level. Males in the lowest education level categories were less likely to be non-smokers or to have achieved the blood pressure targets. In contrast, patients within the low income categories had a higher probability of reaching the recommended LDL-c level. CONCLUSIONS: Our results suggest the presence of socioeconomic inequalities in the achievement of cardiovascular and metabolic control that differed in direction and magnitude depending on the measured outcome and sex of the patient. These findings may help health professionals focus on high-risk individuals to decrease health inequalities.

Quality of life assessment by applying EORTC questionnaires to rectal cancer patients after surgery and neoadjuvant and adjuvant treatment.

BACKGROUND: Quality of Life (QoL) is a key element in rectal cancer (RC) patients. AIMS: this study assesses QoL in a sample of RC patients in their treatment follow-up period, and compares surgery modalities. PATIENTS AND METHODS: eighty four locally advanced RC patients who had received surgery and neoadjuvant chemoradiotherapy were included in the study. Of these, 70 had adjuvant chemotherapy. All patients completed the EORTC QLQ-C30 and the QLQ-CR29 once at least one year after completion of their treatment. Low anterior resection (LAR) patients also completed a Functional Evaluation questionnaire. RESULTS: QoL scores in the EORTC questionnaires for the sample as a whole were high in most dimensions, in line with the general population´s QoL values, although moderate limitations (> 30 points)were observed in urinary frequency, flatulence, impotence and sexual function. The scores for the Functional Evaluation were adequate (mean combined bowel function score of 18.2). LAR patients had a higher stool frequency than those with abdominoperineal resection (APR; p < 0.001). No differences in body image were found amongst LAR and APR patients. LAR patients with a lower anastomosis had higher faecal incontinence (p = 0.02), whereas those with a reservoir had better emotional functioning (p = 0.04) and higher faecal incontinence (p = 0.03). CONCLUSIONS: QoL scores and functional evaluation indicated patients had adapted to their disease and treatment. The few differences in QoL found between surgery modalities are in line with other recent studies and in contrast with earlier ones that suggested a lower QoL in APR patients.

Variability in the detection and monitoring of chronic patients in primary care according to what is registered in the electronic health record.

BACKGROUND: The electronic health record (EHR) allows a detailed study of the primary care consultations and assessment of variability among physicians regarding the implementation of practices for prevention, detection and monitoring of chronic diseases. OBJECTIVES: To describe the variability in the detection and surveillance of chronic conditions in primary care. METHODS: Review of the medical records maintained by 1685 primary care physicians in the Basque Health Service. Estimation of age and sex standardized rates of compliance with evidence-based recommendations and the systematic component of variation (SCV). RESULTS: Compliance with screening recommendations varied from 14.2% for chronic obstructive pulmonary disease (COPD) to 37.2% for hypercholesterolaemia of the at-risk populations. Variability between Primary Care Units (PCUs) was low (SCV(5) (-95) < 0.10) for high blood pressure, hypercholesterolaemia and diabetes and high (SCV(5) (-95) ≥ 0.20) for COPD. Based on the EHR registries, recommendations were followed to in at least 50% of relevant patients according to only 10 of the 44 good care practice (GCP) criteria. For 16 of the GCP criteria, the EHR data indicated compliance to the recommendations in <25% of patients diagnosed. CONCLUSIONS: EHR data indicate that some of the preventative care practices recommended to detect chronic problems in primary care are unevenly implemented across PCUs. Notably, there is less variation in the case of conditions for which evidence-based clinical practice guidelines have been published. The level of monitoring is inadequate for all the conditions studied; particularly in those in which it is less evident that primary care is the right level of the health service to provide this care.

Waiting list management: priority criteria or first-in first-out? A case for total joint replacement.

BACKGROUND: Total joint replacements are interventions with large waiting times from indication to the surgery management. These patients can be managed in two ways; first-in first-out or through a priority tool. The aim of this study was to compare real time on waiting list (TWL) with a priority criteria score, developed by our team, in patients awaiting joint replacement due to osteoarthritis. METHODS: Consecutive patients placed on waiting list were eligible. Patients fulfilled a questionnaire which included items of our priority tool and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) specific questionnaire. Other priority items were extracted from the clinical history. The priority tool gives a score from 0 to 100 points, and three categories (urgent, preferent and ordinary). We studied the differences among categories and TWL by means of one-way analysis of variance. Correlational analysis was used to evaluate association among priority score and TWL and WOMAC baseline and gains at 6 months with priority score and TWL. RESULTS: We have studied 684 patients. Women represented 62% of sample. The mean age was 70 years. There were not association between the categories of priority score and TWL (P = 0.12). The rho correlation coefficient between TWL and priority score was -0.11. Among baseline WOMAC scores and priority score, the rho coefficients were 0.79, 0.7 and 0.52 with function, pain and stiffness dimensions, respectively. There were differences in the mean scores of WOMAC dimensions according to the three priority categories (P < 0.001) but no with TWL categories. Data of gains in both health-related quality of life dimensions at 6 months were similar, with differences according to priority categories but no regarding TWL. CONCLUSIONS: The results of the study support the necessity of implementing a prioritization system instead of the actual system if we want to manage the waiting list for joint replacement with clinical equity.

Is there much variation in variation? Revisiting statistics of small area variation in health services research.

BACKGROUND: The importance of Small Area Variation Analysis for policy-making contrasts with the scarcity of work on the validity of the statistics used in these studies. Our study aims at 1) determining whether variation in utilization rates between health areas is higher than would be expected by chance, 2) estimating the statistical power of the variation statistics; and 3) evaluating the ability of different statistics to compare the variability among different procedures regardless of their rates. METHODS: Parametric bootstrap techniques were used to derive the empirical distribution for each statistic under the hypothesis of homogeneity across areas. Non-parametric procedures were used to analyze the empirical distribution for the observed statistics and compare the results in six situations (low/medium/high utilization rates and low/high variability). A small scale simulation study was conducted to assess the capacity of each statistic to discriminate between different scenarios with different degrees of variation. RESULTS: Bootstrap techniques proved to be good at quantifying the difference between the null hypothesis and the variation observed in each situation, and to construct reliable tests and confidence intervals for each of the variation statistics analyzed. Although the good performance of Systematic Component of Variation (SCV), Empirical Bayes (EB) statistic shows better behaviour under the null hypothesis, it is able to detect variability if present, it is not influenced by the procedure rate and it is best able to discriminate between different degrees of heterogeneity. CONCLUSION: The EB statistics seems to be a good alternative to more conventional statistics used in small-area variation analysis in health service research because of its robustness.

A cohort study to estimate occupational mortality risks in Navarra.

BACKGROUND: Few studies on occupational mortality have been conducted in Spain. The objective of this work was to analyse inequalities on global mortality and on mortality due to specific causes according to occupation in a historical cohort of males from the province of Navarra, Spain. METHODS: The base population for this historical cohort comprised all employed men over age 34 from Navarra in the 1986 population register. Age-standardised point estimates and confidence intervals for occupational-specific mortality risks were computed. RESULTS: There exist differences in mortality risks with respect to the overall risk of Navarra in certain occupational activities for several major causes of mortality. Some of the results corroborate previous findings in other works, such as the significant high risk that presents in leather, clothing workers and shoemakers when analysing kidney, bladder and other urinary malignant tumours, while others present a certain degree of novelty. CONCLUSION: This work contributes to filling the gap in the lack of works on occupational mortality in Spain. It also complements the information that other monitoring systems may provide on occupational health.