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At least 487 records · Page 27Linked to original sources
PubMed1989

The box plot: a simple visual method to interpret data.

Exploratory data analysis involves the use of statistical techniques to identify patterns that may be hidden in a group of numbers. One of these techniques is the "box plot," which is used to visually summarize and compare groups of data. The box plot uses the median, the approximate quartiles, and the lowest and highest data points to convey the level, spread, and symmetry of a distribution of data values. It can also be easily refined to identify outlier data values and can be easily constructed by hand. We apply box plots to tabular data from two recently published articles to show how readers can use box plots to improve the interpretation of data in complex tables. The box plot, like other visual methods, is more than a substitute for a table: It is a tool that can improve our reasoning about quantitative information. We recommend that the box plot be used more frequently.

Alcohol Drinking↗
PubMed1999

3-dimensional volume rendered computerized tomography for preoperative evaluation and intraoperative treatment of patients undergoing nephron sparing surgery.

PURPOSE: Computerized tomography (CT) is the diagnostic and staging modality of choice for renal neoplasms. Existing imaging modalities are limited by a 2-dimensional (D) format. Recent advances in computer technology now allow the production of high quality 3-D images from helical CT. Nephron sparing surgery requires a detailed understanding of renal anatomy. Preoperative evaluation must delineate the relationship of the tumor to adjacent normal structures and demonstrate the vascular supply to the tumor for the surgeon to conserve as much normal parenchyma as possible. We propose that helical CT combined with 3-D volume rendering provides all of the information required for preoperative evaluation and intraoperative management of nephron sparing surgery cases. We prospectively evaluated the role of 3-D volume rendering CT in 60 patients undergoing nephron sparing surgery for renal cell carcinoma at the Cleveland Clinic Foundation. MATERIALS AND METHODS: Triphasic spiral CT was performed preoperatively in 60 consecutive patients undergoing nephron sparing surgery for renal neoplasms. A 3 to 5-minute videotape was prepared using volume rendering software which demonstrated the position of the kidney, location and depth of extension of the tumor(s), renal artery(ies) and vein(s), and relationship of the tumor to the collecting system. These videotapes were viewed by a radiologist and urologist in the operating room at surgery, and immediately correlated with surgical findings. Corresponding renal arteriograms of 19 patients were retrospectively compared to 3-D volume rendering CT and operative findings. RESULTS: A total of 97 renal masses were identified in 60 cases evaluated with 3-D volume rendering CT before nephron sparing surgery. There were no complications related to the 3-D protocol and 3-D rendering was successful in all patients. The number and location of lesions identified by 3-D volume rendering CT were accurate in all cases, while enhancement and diagnostic characteristics were consistent with pathological findings in 95 of 97 tumors (98%). Of 77 renal arteries identified at surgery 74 were detected by 3-D volume rendering CT (96%). Helical CT missed 3 small accessory arteries, including 1 in a cross fused ectopic kidney. All major venous branches and anomalies were identified, including 3 circumaortic left renal veins. Of 69 renal veins identified at surgery 64 were detected by 3-D volume rendering CT (93%). All 5 renal veins missed by CT were small, short, duplicated right branches of the main renal vein. Renal fusion and malrotation anomalies were correctly identified in all 4 patients. CONCLUSIONS: The 3-D volume rendering CT accurately depicts the renal parenchymal and vascular anatomy in a format familiar to most surgeons. The data integrate essential information from angiography, venography, excretory urography and conventional 2-D CT into a single imaging modality, and can obviate the need for more invasive imaging. Additionally, the use of videotape in an intraoperative setting provides concise, accurate and immediate 3-D information to the surgeon, and it has become the preferred means of data display for these procedures at our center.

Adult↗
PubMed1990

Distributive and clinical activity measurement using spreadsheet software.

Documentation of distributive and clinical activities is an important factor in maintaining and expanding pharmacy services. In order to illustrate the impact of pharmacists' efforts on risk management and the reduction of drug costs, the pharmacy must effectively monitor workload. This report describes a method to identify and estimate time required for both distributive and clinical functions. Tabulation of the distributive work units is automated through the hospital billing system. Clinical monitors are dependent on manual documentation by decentralized clinical pharmacists. The clinical coordinator and the pharmacy director review the documented clinical monitors to insure compliance and standardization. Productivity and workload calculations are performed automatically via the spreadsheet software once all the distributive and clinical units are entered. Identifying clinical functions and measuring the associated workload has aided in justifying new positions. Future considerations include calculating the impact of clinical services on revenues, expenses, and staffing.

Connecticut↗
PubMed1993

Some computer-based decision support tools for the rehabilitation manager.

The recent introduction of the Management Information System (MIS) guidelines has sparked much interest among health care institutions across Canada regarding proper approaches to the recording and interpretation of various financial and workload indicators. While the benefits of the MIS guidelines are widely acknowledged, much less attention has been directed to how departmental managers can analyze and make use of the vast amount of information generated. In this paper we attempt to review some of the computer-based decision-support tools that may be useful to the manager of the rehabilitation services department in analyzing the various MIS data that are collected. The data are assumed to be available through a computerized rehabilitation information system which includes workload measures. The quantitative models reviewed in this paper include basic descriptive statistics, deviation, trend and what-if-analysis and graph-plotting. Although the use of such tools can assist the rehabilitation manager in the routine decision-making process, it is very important that we ask the right questions and employ the proper model to make the most rational and best decision. In this respect, ongoing training in general problem-solving skills, decision-making processes, and use of computer-based decision-support tools may be very beneficial.

Canada↗
PubMed1993

Quality management forces computerization decisions.

It is unlikely the quality management program of the future will be able to effect quality improvements without sophisticated information management tools, one of which is the computer. While computerization is not required by the Joint Commission's Performance Assessment and Improvement Standard nor the Information Management Standard, both standards compel organizations to improve their information system capabilities. If the hospital quality management office attempts to survive without computerization, its ability to manipulate the many data elements required for measurement, assessment and improvement will be severely limited. Begin now to plan your computerization strategy.

Data Display↗
PubMed1995

Techniques for managing quality.

The science of quality management is an eclectic collection of concepts and methods primarily borrowed from other fields. Techniques roughly fall into three categories involving quality improvement, planning, and measurement. Improvement techniques include models to guide team-based efforts, tools for process description, and tools for data analysis. These methods are the most visible artifacts of CQI efforts in health care organizations today. Less widely known, but equally powerful, are the techniques of quality planning. There are models to guide both process design and strategic planning, methods for identifying customer needs, and tools to support these efforts. Finally, while measurement is a traditionally well-developed area in health care, industrial quality management science broadens our outlook about what is important to measure. It also provides the technique of benchmarking, which suggests that we look beyond our own organization when we measure performance.

Data Display↗
PubMedDate not supplied

Benchmarking in healthcare: evaluating data and transforming it into action.

After the benchmarking team has accumulated data for the development of comparisons, it must be validated for completeness and consistency. Various factors can skew the analysis and should be watched: Subjective interpretations of survey questions. Lack of common definitions. Composition of input data. External factors and extraordinary events. After verifying consistency of data gathered from benchmarking partners, calculate appropriate statistics for the performance metric. Typical data tabulations are: mean, median, ratio, minimum and maximum value, normal operating range, standard deviation and correlation coefficient. Statistics derived from the data produce the benchmark against which you will measure your institution's performance. Gap analysis establishes the difference between your internal operation's performance and that of the benchmark. Information developed from properly collected data will help you determine reasons for the gap between your performance and the benchmark and project future trends. The next step is to develop an action plan based on what has been learned from benchmarking and targeted to improving performance in areas that further the strategic goals of the institution. In addition to determining performance goals, you must analyze the decision-making process involved in making changes that will move you toward those goals. Since the goal of benchmarking is to improve the organization, the team must present its analysis to those members of management who can approve an action plan. Changes resulting from benchmarking can range from incremental improvement of existing practices all the way to reenginering. Action plans are designed to effect change at levels that will vary according to the goals that have been set. The more incremental the change, the easier the implementation. The more radical the change, the greater the reward.

Data Display↗
PubMed1997

The data game. Play it right, and you could win more managed care contracts.

If you could see how your organization was performing as easily as you read the gas gauge and speedometer on your car, making decisions in the boardroom would be much easier (and more reliable). See how you can get the information you need in a format that makes sense. The payoff could be more managed care contracts.

Data Collection↗
PubMed1987

Theory and practice for measuring health care quality.

As competition, cost control, and new modes of delivery emerge in health care, there is a need to reexamine both the traditional definitions of health care quality and the methods by which it is measured. Industries other than health care have much to teach regarding the methods for obtaining, analyzing, and displaying data; techniques for problem identification, problem solving, and reassessment; and ideas about organizational factors that produce a high quality product or service. The Quality-of-Care Measurement Department at the Harvard Community Health Plan has built a program that draws from a distinguished health care quality assurance tradition and incorporates techniques that have been successful in other industries.

Consumer Behavior↗
PubMedDate not supplied

Mechanical properties of compomer restorative materials.

The purpose of this study was to measure the compressive strength, flexural strength, microhardness, and surface roughness of three compomers (Compoglass, Dyract, and Hytac) and compare the values to the ones obtained for a resin-modified glass-ionomer cement (Vitremer) and a resin composite (Z100). All materials were handled according to the manufacturers' instructions. There was a significant difference (P < 0.01) among Vitremer, Hytac and Z100 composite with regard to yield strength. Vitremer values were lower than for Hytac, which were lower than for Z100. The yield strength values for Compoglass and Dyract were significantly lower than for Hytac and Z100 composite and significantly higher than for Vitremer (P < 0.01). There was no significant difference in the strain at yield among Vitremer, Hytac, and Z100, but their values were significantly higher than for Compoglass and Dyract (P < 0.01). The flexural strength data displayed a significant difference between Vitremer and Hytac (P < 0.05). Z100 was significantly stronger than the other products tested. The values of strain at break for Vitremer, Hytac, and Z100 were significantly lower than for Compoglass and Dyract (P < 0.01). The compressive strength results showed significantly higher values for Dyract, Compoglass, and Hytac than for Vitremer (P < 0.01). Z100 displayed higher values than the other products tested (P < 0.01). Hytac strength was significantly higher than for Dyract (P < 0.01). The microhardness of Compoglass and Dyract was not significantly different (P < 0.05). Hytac displayed microhardness values higher than for Vitremer, Compoglass, and Dyract (P < 0.01). However, all products tested showed values significantly lower than for Z100 (P < 0.01). The surface roughness values for Compoglass, Dyract, Hytac, and Z100 were not significantly different. Vitremer displayed a significantly higher value than Dyract, Hytac, and Z100 (P < 0.05).

Analysis of Variance↗