This study describes the incidence of fatal and nonfatal injuries occurring in 87,022 Massachusetts children and adolescents during a one-year period. A surveillance system for injuries at 23 hospitals captured 93 per cent of all discharges for ages 0-19 in the 14 communities under study. Sample data were collected on emergency room visits, hospital admissions, and deaths for all but a few causes of unintentional injuries. The overall incidence was 2,239 per 10,000. The true incidence rates are probably higher than those reported. The ratio of emergency room visits to admissions to deaths was 1,300 to 45 to 1. Injury rates varied considerably by age, sex, cause, and level of severity. Age-specific injury rates were
This study describes the incidence of fatal and nonfatal injuries occurring in 87,022 Massachusetts children and adolescents during a one-year period. A surveillance system for injuries at 23 hospitals captured 93 per cent of all discharges for ages 0-19 in the 14 communities under study. Sample data were collected on emergency room visits, hospital admissions, and deaths for all but a few causes of unintentional injuries. The overall incidence was 2,239 per 10,000. The true incidence rates are probably higher than those reported. The ratio of emergency room visits to admissions to deaths was 1,300 to 45 to 1. Injury rates varied considerably by age, sex, cause, and level of severity. Age-specific injury rates were
The patient-centered medical home (PCMH) model emphasizes comprehensive, coordinated, patient-centered care, with the goals of reducing spending and improving quality. To evaluate the impact of PCMH initiatives on utilization, cost, and quality, we conducted a meta-analysis of methodologically standardized findings from evaluations of eleven major PCMH initiatives. There was significant heterogeneity across individual evaluations in many outcomes. Across evaluations, PCMH initiatives were not associated with changes in the majority of outcomes studied, including primary care, emergency department, and inpatient visits and four quality measures. The initiatives were associated with a 1.5 percent reduction in the use of specialty visits and a 1.2 percent increase in cervical cancer screening among all patients, and a 4.2 percent reduction in total spending (excluding pharmacy spending) and a 1.4 percent increase in breast cancer screening among higher-morbidity patients. These associations were significant. Identification of the components of PCMHs likely to improve outcomes is critical to decisions about investing resources in primary care.
In the face of increasing rates of overdose deaths, escalating health care costs, and the tremendous social costs of opioid addiction, policy makers are asked to address the questions of whether and how to expand access to treatment services. In response to an upward trend in opioid abuse and adverse outcomes, Vermont is investing in statewide expansion of a medication-assisted therapy program delivered in a network of community practices and specialized treatment centers (Hub & Spoke Program). This study was conducted to test the rationale for these investments and to establish a pre-Hub & Spoke baseline for evaluating the additive impact of the program. Using a serial cross-sectional design from 2008 to 2013 to evaluate medical claims for Vermont Medicaid beneficiaries with opioid dependence or addiction (6158 in the intervention group, 2494 in the control group), this study assesses the treatment and medical service expenditures for those receiving medication-assisted treatment compared to those receiving substance abuse treatment without medication. Results suggest that medication-assisted therapy is associated with reduced general health care expenditures and utilization, such as inpatient hospital admissions and outpatient emergency department visits, for Medicaid beneficiaries with opioid addiction. For state Medicaid leaders facing similar decisions on approaches to opioid addiction, these results provide early support for expanding medication-assisted treatment services rather than relying only on psychosocial, abstinence, or detoxification interventions.
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.
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