Results-oriented management though MBO.

Management by Objectives (MBO) as it has been implemented in the Houston Academy of Medicine--Texas Medical Center Library is described. That MBO must be a total management system and not just another library program is emphasized throughout the discussion and definitions of the MBO system parts: (1) mission statement; (2) role functions; (3) role relationships; (4) effectiveness areas; (5) objective; (6) action plans; and (7) performance review and evaluation. Examples from the library's implementation are given within the discussion of each part to give the reader a clearer picture of the library's actual experiences with the MBO process. Tables are included for further clarification. In conclusion some points are made which the author feels are particularly crucial to any library MBO implementation.

Outcomes and cost effectiveness of treating type 2 diabetes with a nurse case manager following treatment algorithms versus primary care physicians

Background. Diabetes places a significant burden on the health care system. Reduction in blood glucose levels (HbA1c) reduces the risk of complications; however, little is known about the impact of disease management programs on medical costs for patients with diabetes. In 2001, economic costs associated with diabetes totaled $100 billion, and indirect costs totaled $54 billion. ^ Objective. To compare outcomes of nurse case management by treatment algorithms with conventional primary care for glycemic control and cardiovascular risk factors in type 2 diabetic patients in a low-income Mexican American community-based setting, and to compare the cost effectiveness of the two programs. Patient compliance was also assessed. ^ Research design and methods. An observational group-comparison to evaluate a treatment intervention for type 2 diabetes management was implemented at three out-patient health facilities in San Antonio, Texas. All eligible type 2 diabetic patients attending the clinics during 1994–1996 became part of the study. Data were obtained from the study database, medical records, hospital accounting, and pharmacy cost lists, and entered into a computerized database. Three groups were compared: a Community Clinic Nurse Case Manager (CC-TA) following treatment algorithms, a University Clinic Nurse Case Manager (UC-TA) following treatment algorithms, and Primary Care Physicians (PCP) following conventional care practices at a Family Practice Clinic. The algorithms provided a disease management model specifically for hyperglycemia, dyslipidemia, hypertension, and microalbuminuria that progressively moved the patient toward ideal goals through adjustments in medication, self-monitoring of blood glucose, meal planning, and reinforcement of diet and exercise. Cost effectiveness of hemoglobin AI, final endpoints was compared. ^ Results. There were 358 patients analyzed: 106 patients in CC-TA, 170 patients in UC-TA, and 82 patients in PCP groups. Change in hemoglobin A1c (HbA1c) was the primary outcome measured. HbA1c results were presented at baseline, 6 and 12 months for CC-TA (10.4%, 7.1%, 7.3%), UC-TA (10.5%, 7.1%, 7.2%), and PCP (10.0%, 8.5%, 8.7%). Mean patient compliance was 81%. Levels of cost effectiveness were significantly different between clinics. ^ Conclusion. Nurse case management with treatment algorithms significantly improved glycemic control in patients with type 2 diabetes, and was more cost effective. ^

Alternative Strategies for Identifying High-Performing Charter Schools in Texas

The Obama administration's recurring policy emphasis on high-performing charter schools begs the obvious question: how do you identify a high-performing charter school? That is a crucially important policy question because any evaluation strategy that incorrectly identifies charter school performance could have negative effects on the economically and/or academically disadvantaged students who frequently attend charter schools. If low-performing schools are mislabeled and allowed to persist or encouraged to expand, then students may be harmed directly. If high-performing schools are driven from the market by misinformation, then students will lose access to programs and services that can make a difference in their lives. Most of the scholarly analysis to date has focused on comparing the performance of students in charter schools to that of similar students in traditional public schools (TPS). By design, that research measures charter school performance only in relative terms. Charter schools that outperform similarly situated, but low performing, TPSs have positive effects, even if the charter schools are mediocre in an absolute sense. This analysis describes strategies for identifying high-performing charter schools by comparing charter schools with one another. We begin by describing salient characteristics of Texas charter schools. We follow that discussion with a look at how other researchers across the country have compared charter school effectiveness with TPS effectiveness. We then present several metrics that can be used to identify high-performing charter schools. Those metrics are not mutually exclusive—one could easily justify using multiple measures to evaluate school effectiveness—but they are also not equally informative. If the goal is to measure the contributions that schools are making to student knowledge and skills, then a value-added approach like the ones highlighted in this report is clearly superior to a levels-based approach like that taken under the current accountability system.

Application of the general linear model to assess the effect of missing data on bone marrow mononuclear cell therapy with infusion timing and follow-up MRI

With most clinical trials, missing data presents a statistical problem in evaluating a treatment's efficacy. There are many methods commonly used to assess missing data; however, these methods leave room for bias to enter the study. This thesis was a secondary analysis on data taken from TIME, a phase 2 randomized clinical trial conducted to evaluate the safety and effect of the administration timing of bone marrow mononuclear cells (BMMNC) for subjects with acute myocardial infarction (AMI).^ We evaluated the effect of missing data by comparing the variance inflation factor (VIF) of the effect of therapy between all subjects and only subjects with complete data. Through the general linear model, an unbiased solution was made for the VIF of the treatment's efficacy using the weighted least squares method to incorporate missing data. Two groups were identified from the TIME data: 1) all subjects and 2) subjects with complete data (baseline and follow-up measurements). After the general solution was found for the VIF, it was migrated Excel 2010 to evaluate data from TIME. The resulting numerical value from the two groups was compared to assess the effect of missing data.^ The VIF values from the TIME study were considerably less in the group with missing data. By design, we varied the correlation factor in order to evaluate the VIFs of both groups. As the correlation factor increased, the VIF values increased at a faster rate in the group with only complete data. Furthermore, while varying the correlation factor, the number of subjects with missing data was also varied to see how missing data affects the VIF. When subjects with only baseline data was increased, we saw a significant rate increase in VIF values in the group with only complete data while the group with missing data saw a steady and consistent increase in the VIF. The same was seen when we varied the group with follow-up only data. This essentially showed that the VIFs steadily increased when missing data is not ignored. When missing data is ignored as with our comparison group, the VIF values sharply increase as correlation increases.^