Screening mammography rates by specialty of the usual care physician.

CONTEXT: Although Medicare began paying for screening mammography in 1991, utilization among enrollees has been low. PRACTICE PATTERN EXAMINED: The relation between the specialty of the usual care physician and the proportion of women 65 years of age and older receiving mammography. DATA SOURCE: 100% Medicare Part B claims for 186,526 female enrollees residing in Maine, New Hampshire, and Vermont during 1993 and 1994. RESULTS: Among women of the target screening age (65 to 69 years), 55.4%, received mammography during the 2-year period. The highest rates of mammography were observed in women whose usual care physician was a gynecologist (77.9%; 95% CI, 75.8 to 79.9), followed by those treated by an internist (67.1%; CI, 66.5 to 67.7), family practitioner (58.1%; CI, 57.4 to 58.9), general practitioner (47.4%; CI, 45.4 to 49.5), and other specialists (41.3%; CI, 40.1 to 42.5). The lowest rates were observed in women who had no physician visits during the 2-year period (9.5%; CI, 8.7 to 10.4). Although screening rates were lower in women aged 70 years and older, a similar pattern was observed. CONCLUSIONS: The probability of a Medicare enrollee's receiving screening mammography is strongly influenced by the specialty of her usual care physician. Covering a preventive service does not guarantee its use.

Applying control charts to quality improvement.

This article reviews the definitions and principles that should guide the use of control charts in healthcare quality. Several examples from the literature are used to illustrate significant problems and issues in control chart construction.

Moose-motor vehicle collisions. An increasing hazard in northern New England.

OBJECTIVE: To analyze the epidemiology and epizootiology of moose-motor vehicle collisions (MMVC) and outcomes in severely injured patients to identify variables that might be modified to reduce the impact of this mutually deleterious interspecies interaction. DESIGN: Wildlife and Traffic Safety databases permitted retrospective, population-based assessment of MMVC epidemiology. A case series compiled from hospital trauma registries characterized morbidity and mortality from MMVC. SETTING: New Hampshire and Maine area. PATIENTS: All victims of MMVC (1980 through 1991) were included in population-based analyses. Twenty-three patients hospitalized at three rural trauma centers (January 1990 through June 1994) were included in the case series. MAIN OUTCOME MEASURES: Location, time of day and seasonal occurrence of MMVC were determined. Injury patterns and Injury Severity Scores were analyzed in 23 representative patients. Maine's 1991 traffic and medical data were linked, and factors predictive of injury from MMVC were identified using multivariate logistics. RESULTS: Most MMVC occur from April through October after dark. Of 23 subjects, 70% sustained head and/or face injuries and 26%, cervical spine injuries. Mortality was 9%. Mean Injury Severity Score was 15.7 (SD=9.0). Safety belt use, rear seat location, and light truck occupancy were associated with reduced injury (p<.05). CONCLUSIONS: Moose-motor vehicle collisions are increasing in rural regions. Prevention programs should emphasize defensive driving and seat belt use, especially during high-risk periods. Injury patterns in MMVC suggest a need for automobile design modifications that better protect the passenger compartment form direct impact.

Perspective: comparing two-sample tests and control charts.

For the task of monitoring a process, detecting change, and making correct attributions on a continuous basis, there is no better tool than the control chart, particularly where the data set is large and permits subgrouping. By using this technique, staff will get quicker answers or will have a smaller data requirement, and will arrive at more valid conclusions than with the two-sample method. (The two-sample approach is typically used when the data are not produced or collected in sequence is unknown. This, however, may reflect a weakness in the data collection process.) In addition, we believe that the control chart approach is as simple as the two-sample approach. Once the control limits and zones are established, the plot of points can be maintained by personnel who need to do no more than plot a rate on a weekly (or a daily) basis. The control chart rules properly focus laboratory and QA personnel on change. Control chart procedures are statistical tests of special cause and need no further significance tests. Those using control charts need to be aware of three important points: 1. Control limits are not standards or thresholds and cannot be derived from these concepts. Control limits are a statement about the current natural variation in the process. 2. The type of chart to be used should depend upon the type of data being evaluated. (Finison et al., 1993).(ABSTRACT TRUNCATED AT 250 WORDS)

The use of control charts to improve healthcare quality.

Control charts are a basic tool for understanding variation in all healthcare processes. Control chart limits are not standards; rather, they divided variation into special and common cause, each of which requires a different management response. Each type of data--variables, count defect, or defectives data--requires a different type of chart (e.g., X bar and R, X bar and S; C or U; P or NP). Individual observations where events are infrequent can be charted on an individual's chart with moving range limits or by several alternative methods discussed in this article.

WIC participation and pregnancy outcomes: Massachusetts Statewide Evaluation Project.

The effects of WIC prenatal participation were examined using data from the Massachusetts Birth and Death Registry. The birth outcomes of 4,126 pregnant women who participated in the WIC program and gave birth in 1978 were compared to those of 4,126 women individually matched on maternal age, race, parity, education, and marital status who did not participate in WIC. WIC prenatal participants are at greater demographic risk for poor pregnancy outcomes compare to all women in the same community. WIC participation is associated with improved pregnancy outcomes, including, a decrease in low birthweight (LBW) incidence (6.9 per cent vs 8.7 per cent) and neonatal mortality (12 vs 35 deaths), an increase in gestational age (40.0 vs 39.7 weeks), and a reduction in inadequate prenatal care (3.8 per cent vs 7.0 per cent). Stratification by demographic subpopulations indicates that subpopulations at higher risk (teenage, unmarried, and Hispanic origin women) have more enhanced pregnancy outcomes associated with WIC participation. Stratification by duration of participation indicates that increased participation is associated with enhanced pregnancy outcomes. While these findings suggest that birth outcome differences are a function of WIC participation, other factors which might distinguish between the two groups could also serve as the basis for alternative explanations.