A classification of diabetic foot infections using ICD-9-CM codes: application to a large computerized medical database

<p>Abstract</p> <p>Background</p> <p>Diabetic foot infections are common, serious, and varied. Diagnostic and treatment strategies are correspondingly diverse. It is unclear how patients are managed in actual practice and how outcomes might be improved. Clarification will require study of large numbers of patients, such as are available in medical databases. We have developed and evaluated a system for identifying and classifying diabetic foot infections that can be used for this purpose.</p> <p>Methods</p> <p>We used the (VA) Diabetes Epidemiology Cohorts (DEpiC) database to conduct a retrospective observational study of patients with diabetic foot infections. DEpiC contains computerized VA and Medicare patient-level data for patients with diabetes since 1998. We determined which ICD-9-CM codes served to identify patients with different types of diabetic foot infections and ranked them in declining order of severity: Gangrene, Osteomyelitis, Ulcer, Foot cellulitis/abscess, Toe cellulitis/abscess, Paronychia. We evaluated our classification by examining its relationship to patient characteristics, diagnostic procedures, treatments given, and medical outcomes.</p> <p>Results</p> <p>There were 61,007 patients with foot infections, of which 42,063 were classifiable into one of our predefined groups. The different types of infection were related to expected patient characteristics, diagnostic procedures, treatments, and outcomes. Our severity ranking showed a monotonic relationship to hospital length of stay, amputation rate, transition to long-term care, and mortality.</p> <p>Conclusions</p> <p>We have developed a classification system for patients with diabetic foot infections that is expressly designed for use with large, computerized, ICD-9-CM coded administrative medical databases. It provides a framework that can be used to conduct observational studies of large numbers of patients in order to examine treatment variation and patient outcomes, including the effect of new management strategies, implementation of practice guidelines, and quality improvement initiatives.</p

Evaluation of a Theory-Informed Implementation Intervention for the Management of Acute Low Back Pain in General Medical Practice: The IMPLEMENT Cluster Randomised Trial

Introduction: This cluster randomised trial evaluated an intervention to decrease x-ray referrals and increase giving advice to stay active for people with acute low back pain (LBP) in general practice. Methods: General practices were randomised to either access to a guideline for acute LBP (control) or facilitated interactive workshops (intervention). We measured behavioural predictors (e.g. knowledge, attitudes and intentions) and fear avoidance beliefs. We were unable to recruit sufficient patients to measure our original primary outcomes so we introduced other outcomes measured at the general practitioner (GP) level: behavioural simulation (clinical decision about vignettes) and rates of x-ray and CT-scan (medical administrative data). All those not involved in the delivery of the intervention were blinded to allocation. Results: 47 practices (53 GPs) were randomised to the control and 45 practices (59 GPs) to the intervention. The number of GPs available for analysis at 12 months varied by outcome due to missing confounder information; a minimum of 38 GPs were available from the intervention group, and a minimum of 40 GPs from the control group. For the behavioural constructs, although effect estimates were small, the intervention group GPs had greater intention of practising consistent with the guideline for the clinical behaviour of x-ray referral. For behavioural simulation, intervention group GPs were more likely to adhere to guideline recommendations about x-ray (OR 1.76, 95%CI 1.01, 3.05) and more likely to give advice to stay active (OR 4.49, 95%CI 1.90 to 10.60). Imaging referral was not statistically significantly different between groups and the potential importance of effects was unclear; rate ratio 0.87 (95%CI 0.68, 1.10) for x-ray or CT-scan. Conclusions: The intervention led to small changes in GP intention to practice in a manner that is consistent with an evidence-based guideline, but it did not result in statistically significant changes in actual behaviour. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN01260600009853

Acquisition and Evolution of Plant Pathogenesis–Associated Gene Clusters and Candidate Determinants of Tissue-Specificity in Xanthomonas

is a large genus of plant-associated and plant-pathogenic bacteria. Collectively, members cause diseases on over 392 plant species. Individually, they exhibit marked host- and tissue-specificity. The determinants of this specificity are unknown. lineage. genome and indicate that differentiation with respect to host- and tissue-specificity involved not major modifications or wholesale exchange of clusters, but subtle changes in a small number of genes or in non-coding sequences, and/or differences outside the clusters, potentially among regulatory targets or secretory substrates

Differences between hospitals in attainment of parathyroid hormone treatment targets in chronic kidney disease do not reflect differences in quality of care

Contains fulltext : 110897.pdf (publisher's version ) (Open Access)ABSTRACT: BACKGROUND: Transparency in quality of care (QoC) is stimulated and hospitals are compared and judged on the basis of indicators of performance on specific treatment targets. In patients with chronic kidney disease, QoC differed significantly between hospitals. In this analysis we explored additional parameters to explain differences between centers in attainment of parathyroid hormone (PTH) treatment targets. METHODS: Using MASTERPLAN baseline data, we selected one of the worst (center A) and one of the best (center B) performing hospitals. Differences between the two centers were analyzed from the year prior to start of the MASTERPLAN study until the baseline evaluation. Determinants of PTH were assessed. RESULTS: 101 patients from center A (median PTH 9.9 pmol/l, in 67 patients exceeding recommended levels) and 100 patients from center B (median PTH 6.5 pmol/l, in 34 patients exceeding recommended levels), were included. Analysis of clinical practice did not reveal differences in PTH management between the centers. Notably, hyperparathyroidism resulted in a change in therapy in less than 25% of patients. In multivariate analysis kidney transplant status, MDRD-4, and treatment center were independent predictors of PTH. However, when MDRD-6 (which accounts for serum urea and albumin) was used instead of MDRD-4, the center effect was reduced. Moreover, after calibration of the serum creatinine assays treatment center no longer influenced PTH. CONCLUSIONS: We show that differences in PTH control between centers are not explained by differences in treatment, but depend on incomparable patient populations and laboratory techniques. Therefore, results of hospital performance comparisons should be interpreted with great caution