Longitudinal patterns in survival, comorbidity, healthcare utilization and quality of care among older women following breast cancer diagnosis

OBJECTIVES To compare longitudinal patterns of health care utilization and quality of care for other health conditions between breast cancer-surviving older women and a matched cohort without breast cancer. DESIGN Prospective five-year longitudinal comparison of cases and matched controls. SUBJECTS Newly identified breast cancer patients recruited during 1997–1999 from four geographic regions (Los Angeles, CA; Minnesota; North Carolina; and Rhode Island; N = 422) were matched by age, race, baseline comorbidity and zip code location with up to four non-breast-cancer controls (N = 1,656). OUTCOMES Survival; numbers of hospitalized days and physician visits; total inpatient and outpatient Medicare payments; guideline monitoring for patients with cardiovascular disease and diabetes, and bone density testing and colorectal cancer screening. RESULTS Five-year survival was similar for cases and controls (80% and 82%, respectively; p = 0.18). In the first follow-up year, comorbidity burden and health care utilization were higher for cases (p < 0.01), with most differences diminishing over time. However, the number of physician visits was higher for cases (p < 0.01) in every year, driven partly by more cancer and surgical specialist visits. Cases and controls adhered similarly to recommended bone density testing, and monitoring of cardiovascular disease and diabetes; adherence to recommended colorectal cancer screening was better among cases. CONCLUSION Breast cancer survivors’ health care utilization and disease burden return to pre-diagnosis levels after one year, yet their greater use of outpatient care persists at least five years. Quality of care for other chronic health problems is similar for cases and controls.

A Trustability Metric for Code Search based on Developer Karma

The promise of search-driven development is that developers will save time and resources by reusing external code in their local projects. To efficiently integrate this code, users must be able to trust it, thus trustability of code search results is just as important as their relevance. In this paper, we introduce a trustability metric to help users assess the quality of code search results and therefore ease the cost-benefit analysis they undertake trying to find suitable integration candidates. The proposed trustability metric incorporates both user votes and cross-project activity of developers to calculate a "karma" value for each developer. Through the karma value of all its developers a project is ranked on a trustability scale. We present JBENDER, a proof-of-concept code search engine which implements our trustability metric and we discuss preliminary results from an evaluation of the prototype.

Spy: A Flexible Code Profiling Framework

Code profiling is an essential activity to increase software quality. It is commonly employed in a wide variety of tasks, such as supporting program comprehension, determining execution bottlenecks, and assessing code coverage by unit tests. Spy is an innovative framework to easily build profilers and visualize profiling information. The profiling information is obtained by inserting dedicated code before or after method execution. The gathered profiling information is structured in line with the application structure in terms of packages, classes, and methods. Spy has been instantiated on four occasions so far. We created profilers dedicated to test coverage, time execution, type feedback, and profiling evolution across version. We also integrated Spy in the Pharo IDE. Spy has been implemented in the Pharo Smalltalk programming language and is available under the MIT license.

Quality in emergency departments: a study on 3,285,440 admissions

INTRODUCTION: A multi-centre study has been conducted, during 2005, by means of a questionnaire posted on the Italian Society of Emergency Medicine (SIMEU) web page. Our intention was to carry out an organisational and functional analysis of Italian Emergency Departments (ED) in order to pick out some macro-indicators of the activities performed. Participation was good, in that 69 ED (3,285,440 admissions to emergency services) responded to the questionnaire. METHODS: The study was based on 18 questions: 3 regarding the personnel of the ED, 2 regarding organisational and functional aspects, 5 on the activity of the ED, 7 on triage and 1 on the assessment of the quality perceived by the users of the ED. RESULTS AND CONCLUSION: The replies revealed that 91.30% of the ED were equipped with data-processing software, which, in 96.83% of cases, tracked the entire itinerary of the patient. About 48,000 patients/year used the ED: 76.72% were discharged and 18.31% were hospitalised. Observation Units were active in 81.16% of the ED examined. Triage programmes were in place in 92.75% of ED: in 75.81% of these, triage was performed throughout the entire itinerary of the patient; in 16.13% it was performed only symptom-based, and in 8.06% only on-call. Of the patients arriving at the ED, 24.19% were assigned a non-urgent triage code, 60.01% a urgent code, 14.30% a emergent code and 1.49% a life-threatening code. Waiting times were: 52.39 min for non-urgent patients, 40.26 min for urgent, 12.08 for emergent, and 1.19 for life-threatening patients.

BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

Mining frequent bug-fix code changes

Detecting bugs as early as possible plays an important role in ensuring software quality before shipping. We argue that mining previous bug fixes can produce good knowledge about why bugs happen and how they are fixed. In this paper, we mine the change history of 717 open source projects to extract bug-fix patterns. We also manually inspect many of the bugs we found to get insights into the contexts and reasons behind those bugs. For instance, we found out that missing null checks and missing initializations are very recurrent and we believe that they can be automatically detected and fixed.

The CODE MGEX orbit and clock solution

The Center for Orbit Determination in Europe (CODE) is contributing as a global Analysis center to the International GNSS Service (IGS) since many years. The processing of GPS and GLONASS data is well established in CODE’s ultra-rapid, rapid, and final product lines. With the introduction of new signals for the established and new GNSS, new challenges and opportunities are arising for the GNSS data management and processing. The IGS started the Multi-GNSS-EXperiment (MGEX) in 2012 in order to gain first experience with the new data formats and to develop new strategies for making optimal use of these additional measurements. CODE has started to contribute to IGS MGEX with a consistent, rigorously combined triple-system orbit solution (GPS, GLONASS, and Galileo). SLR residuals for the computed Galileo satellite orbits are of the order of 10 cm. Furthermore CODE established a GPS and Galileo clock solution. A quality assessment shows that these experimental orbit and clock products allow even a Galileo-only precise point positioning (PPP) with accuracies on the decimeter- (static PPP) to meter-level (kinematic PPP) for selected stations.

Measuring the quality of life of patients with diabetes: Validating the tool and determining the effects on quality of life

There are several tools for measuring quality of life (QoL) and specifically, health-related quality of life (HRQoL) for persons with diabetes. A commonly-used measure, the Diabetes Quality of Life (DQOL) Survey, developed for the Diabetes Control and Complications Trial (DCCT), has been used in several experimental settings, and its reliability and validity are well-established. However, it is considered too long to be of practical use in clinical settings. Because of this, a shortened version of the tool was used recently in the Community Diabetes Education (CoDE) Project in Dallas, Texas, a clinic-based patient education program that uses a specially-trained community healthcare worker to provide patient education. However, the modified scale has never been tested for reliability and validity. Thus, one goal of this thesis was to measure these psychometric properties of the scale. After establishing the reliability and validity, the results of the scale were analyzed to determine the effects of the intervention on the subjects’ quality of life. The changes in QoL scales were compared with changes in physiologic measures which are most closely allied with diabetes, including blood glucose levels, weight/BMI, co-morbidities and health beliefs in order to determine if there is a relationship between such measures and quality of life. The results of the reliability and validity testing were not conclusive. Measures of reliability and criterion validity were established, but these contrasted with poor measures of repeatability and content validity. The effect of the intervention on quality of life, however, was more significant, particularly regarding the impact of diabetes. Those who received the counseling had significantly higher scores on the Impact scale than those who did not, and the former group had much greater improvement in scores over the twelve month period than the latter group. ^