Efficiency from pharmacy inventory technology: A means to improving quality in non-profit hospitals

Hospitals, like all organizations, have both a mission and a finite supply of resources with which to accomplish that mission. Because the inventory of therapeutic drugs is among the more expensive resources needed by a hospital to achieve its mission, a conceptual model of structure plus process equals outcome posits that adequate emphasis should be placed on optimization of the organization's investment in this important structural resource to provide highest quality outcomes. Therefore emphasis should be placed on the optimization of pharmacy inventory because lowering the financial investment in drug inventory and associated costs increases productive efficiency, a key element of quality. ^ In this study, a post-intervention analysis of a hospital pharmacy inventory management technology implementation at The University of Texas M.D. Anderson Cancer Center was conducted to determine if an intervention which reduced a hospital's financial investment in pharmaceutical inventory provided an opportunity to incrementally optimize the organization's mix of structural resources thereby improving quality of care. The results suggest that hospital pharmacies currently lacking technology to support automated purchasing logistics and perpetual, real-time inventory management for drugs may achieve measurable benefits from the careful implementation of such technology, enabling the hospital to lower its investment in on-hand inventory and, potentially, to reduce overall purchasing expenditures. ^ The importance of these savings to the hospital and potentially to the patient should not be underestimated for their ability to generate funding for previously unfunded public health programs or in their ability to provide financial relief to patients in the form of lower drug costs given the current climate of escalating healthcare costs and tightening reimbursements.^

Left, right and interval bivariate censored data: Evaluating screening mammography in the presence of lead -time bias, length bias and over-detection

Of the large clinical trials evaluating screening mammography efficacy, none included women ages 75 and older. Recommendations on an upper age limit at which to discontinue screening are based on indirect evidence and are not consistent. Screening mammography is evaluated using observational data from the SEER-Medicare linked database. Measuring the benefit of screening mammography is difficult due to the impact of lead-time bias, length bias and over-detection. The underlying conceptual model divides the disease into two stages: pre-clinical (T0) and symptomatic (T1) breast cancer. Treating the time in these phases as a pair of dependent bivariate observations, (t0,t1), estimates are derived to describe the distribution of this random vector. To quantify the effect of screening mammography, statistical inference is made about the mammography parameters that correspond to the marginal distribution of the symptomatic phase duration (T1). This shows the hazard ratio of death from breast cancer comparing women with screen-detected tumors to those detected at their symptom onset is 0.36 (0.30, 0.42), indicating a benefit among the screen-detected cases. ^