Rebuilding the Standing Prescription Renewal Orders.

BACKGROUND: Managing prescription renewal requests is a labor-intensive challenge in ambulatory care. In 2009, Vanderbilt University Medical Center developed clinic-specific standing prescription renewal orders that allowed nurses, under specific conditions, to authorize renewal requests. Formulary and authorization changes made maintaining these documents very challenging. OBJECTIVE: This article aims to review, standardize, and restructure legacy standing prescription renewal orders into a modular, scalable, and easier to manage format for conversion and use in a new electronic health record (EHR). METHODS: We created an enterprise-wide renewal domain model using modular subgroups within the main institutional standing renewal order policy by extracting metadata, medication group names, medication ingredient names, and renewal criteria from approved legacy standing renewal orders. Instance-based matching compared medication groups in a pairwise manner to calculate a similarity score between medication groups. We grouped and standardized medication groups with high similarity by mapping them to medication classes from a medication terminology vendor and filtering them by intended route (e.g., oral, subcutaneous, inhalation). After standardizing the renewal criteria to a short list of reusable criteria, the Pharmacy and Therapeutics (P&T) committee reviewed and approved candidate medication groups and corresponding renewal criteria. RESULTS: Seventy-eight legacy standing prescription renewal orders covered 135 clinics (some applied to multiple clinics). Several standing orders were perfectly congruent, listing identical medications for renewal. We consolidated 870 distinct medication classes to 164 subgroups and assigned renewal criteria. We consolidated 379 distinct legacy renewal criteria to 21 criteria. After approval by the P&T committee, we built subgroups in a structured and consistent format in the new EHR, where they facilitated chart review and standing order adherence by nurses. Additionally, clinicians could search an autogenerated document of the standing order content from the EHR data warehouse. CONCLUSION: We describe a methodology for standardizing and scaling standing prescription renewal orders at an enterprise level while transitioning to a new EHR.

Increasing body fat mass reverses bone loss in osteopenia as detected by dual-energy X-ray absorptiometry scans.

OBJECTIVE: Low body mass index (BMI) is a known risk factor for osteoporosis and is part of the FRAX™ 10-year fracture risk stratification tool for predicting fragility fractures. Little is known regarding the effects of changing body composition on bone mineral density (BMD). However, increasing fat mass (FM) improves BMD in young women with anorexia nervosa. This study aimed to assess whether changes in FM over time affected BMD in the general population. MATERIAL AND METHODS: Data was collected from patients who underwent dual-energy X-ray absorptiometry (DEXA) assessment between 2004 and 2011. Patients were included if they had multiple scans, including FM measurements. Our scanners limited these to scans of the lumbar spine. Linear regression analysis was performed to identify the relationship between changes in FM and BMD. Backwards stepwise linear regression analysis was performed to identify confounding factors, including sex, risk factors, previous fractures, and baseline BMI. RESULTS: In this study, 23,239 patients were included, of which 702 met the inclusion criteria. There were 609 (86%) females and 93 (13%) males with a mean age of 64.5 (SD 11.2) years at first scan. We identified a strong positive correlation between increasing FM and BMD between scans (coefficient 28.4; p<0.01; 95% CI, 26.6-30.1). Previous pelvic and femur fractures and a history of inflammatory diseases were also associated with increasing FM (p<0.05). This relationship was true regardless of patients BMI at their first scan. CONCLUSION: These findings suggest that patients at high risk of fragility fractures should be encouraged to increase their FM as long as they are at a low risk for disease states related to high FM.

What is the relation between number of sessions worked and productivity of radiologists-a pilot study?

Increasing workloads and the current austerity measures are putting UK radiology departments under considerable stress. We need to look at the most efficient ways to manage radiology departments in order to cope with increasing demand. Consequently, a system is needed that can compare productivity between radiologists with different jobs. We measured workload in a UK radiology department and compared the productivities of consultants working different numbers of sessions, which are called programmed activities (PAs), to identify the optimal job plan structure for reporting productivity. Reporting data was gathered from electronic records for 14 consultants working different numbers of PA during the period April 2010-March 2011. These were converted into relative value unit (RVU) scores using a modified RCSI RVU system. Crude and net workloads were calculated for each consultant by dividing their total RVU score by the number of PAs they were contracted for and how many they spent reporting. The consultants reported 118,001 imaging studies. There was statistically significant variation in productivity between consultants working different numbers of PAs on χ (2) analysis (p < 0.05). Consultants working 12 PAs were more productive than consultants working 11 PAs, with net workloads of 7636 RVU/PA/year versus net 6146 RVU/PA/year, p < 0.05. Although UK consultants working 12 PAs per week are more productive than their colleagues, the reasons why are unclear. We have identified a method that can be developed further to identify efficient working practices in UK radiology departments. However, a UK-specific RVU system would make this productivity analysis more accurate.