Bridget C. Booske

Job and organizational determinants of nursing home employee commitment, job satisfaction and intent to turnover

The purpose of this study was to examine whether job characteristics, the work environment, participation in quality improvement activities and facility quality improvement environment predicted employee commitment and job satisfaction in nursing homes, and whether those same predictors and commitment and satisfaction predicted turnover intention. A total of 6584 nursing home employees from 76 nursing homes in a midwestern state participated. A self-administered questionnaire was used to collect the data. The results supported the hypotheses that job and organizational factors predicted commitment and satisfaction while commitment and satisfaction predicted turnover intentions. The implications for retaining nursing home employees are discussed.

A population health framework for setting national and state health goals.

WITH THE APPOINTMENT OF THE US DEPARTment of Health and Human Services Advisory Committee on National Health Promotion and Disease Prevention for 2020, the process for setting national health goals in 2009 for the coming decade is under way. The Healthy People 2010 goals and objectives have served as the framework for establishing outcomes for virtually every public health planning process in the United States from National Institutes of Health grants to federal health programs and to state and local health plans. Although an initial process produced a Draft Model with 4 guiding principles and a proposal for a smaller number of objectives for Healthy People 2020, a specific framework has not yet been decided and will be established after a series of public hearings. This Commentary proposes a population health guiding framework for national and state planning processes, including both broad overall goals as well as a prioritized set of policies and interventions aligned with the multiple determinants of health. The ultimate purpose of population health policy is to improve the health of individuals and populations by investments in the determinants of health through policies and interventions that influence these determinants. Without careful attention to the outcomes, attention to determinants and policies could proceed without reference to the ultimate goals and become ends instead of means to an end. A shortcoming of this step of broader goal setting is that it is often framed in general terms without quantification, so it is not likely that the impact of making progress on some objectives can be assessed. Healthy People 2010 devoted significant attention to the 467 objectives in 28 focus areas, but the 2 broad goals of “increasing quality and years of healthy life” and “eliminating disparities” did not have specified quantitative targets. Although the “Healthy People in Healthy Communities” model in Healthy People 2010 contains health determinant categories, the focus areas are presented alphabetically rather than by determinant. The FIGURE is a model that could be a starting point for a framework more precisely aligned to a population health perspective. The right side represents a way of conceptualizing broad population health outcomes. Previous health improvement frameworks have identified both increasing the overall population mean, as well as reducing and eliminating disparities within the population. Within disparities, multiple domains could be policy targets such as race/ ethnicity, socioeconomic status, sex, and geographic location. In addition, such outcomes should include both length of life (mortality) and health-related quality of life. Although it is possible to combine all 4 quadrants into a single summary measure, considering them separately is important because different patterns of determinants will probably produce different changes in each of them. Each quadrant in the Figure is arbitrarily sized equally, and similarly the domain bars within the disparity quadrants are depicted as equal. It is probably not the case that each quadrant or domain should receive equal weight. This is not an empirical issuebut ratheroneof social valuation fordifferentnations, states, or other population groups to decide. The point of presenting them this way is to encourage such consideration as a component of goal setting, which has been done occasionally. For example, the World Health Report 2000 weighted the mean and disparity equally based on a survey of about 1000 respondents. Similarly in a State Health Report Card for Wisconsin, equal weighting was primarily used, although the method used for summarizing disparities across domains resulted in slight variation from equality. The Figure’s left-hand side represents the determinants of the population health outcomes represented on the Figure’s left side. Based on the Evans-Stoddart model, these determinants are divided into 5 categories. For example, medical care includes prevention, treatment, and management of disease. Examples of individual behaviors are smoking, exercise, and eating habits. The social environment includes socioeconomic factors, most often measured by income, educational level, and occupation, while the physical environment consists of air and water quality as well as the built environment, ie, the constructed structures such as buildings, roads, parks, and other physical infrastructure that make up communities. Genetics refers to inher-

US opinions on health determinants and social policy as health policy.

To examine what factors the public thinks are important determinants of health and whether social policy is viewed as health policy, we conducted a national telephone survey of 2791 US adults from November 2008 through February 2009. Respondents said that health behaviors and access to health care have very strong effects on health; they were less likely to report a very strong role for other social and economic factors. Respondents who recognized a stronger role for social determinants of health and who saw social policy as health policy were more likely to be older, women, non-White, and liberal, and to have less education, lower income, and fair/poor health. Increasing public knowledge about social determinants of health and mobilizing less advantaged groups may be useful in addressing broad determinants of health.

Applying Quality Improvement Principles to Achieve Healthy Work Organizations

BACKGROUND Health care has used total quality management (TQM)/quality improvement (QI) methods to improve quality of care and patient safety. Research on healthy work organizations (HWOs) shows that some of the same work organization factors that affect employee outcomes such as quality of life and safety can also affect organizational outcomes such as profits and performance. An HWO is an organization that has both financial success and a healthy workforce. For a health care organization to have financial success it must provide high-quality care with efficient use of scarce resources. To have a healthy workforce, the workplace must be safe, provide good ergonomic design, and provide working conditions that help to mitigate the stress of health care work. INTEGRATING TQM/QI INTO THE HWO PARADIGM If properly implemented and institutionalized, TQM/QI can serve as the mechanism by which to transform a health care organization into an HWO. To guide future research, a framework is proposed that links research on QI with research on HWOs in the belief that QI methods and interventions might be an effective means by which to create an HWO. Specific areas of research should focus on identifying the work organization, cultural, technological, and environmental factors that affect care processes; affect patient health, safety, and satisfaction; and indirectly affect patient health, safety, and satisfaction through their effects on staff and care process variables. SUMMARY Integrating QI techniques within the paradigm of the HWO paradigm will make it possible to achieve greater improvements in the health of health care organizations and the populations they serve.

Using the Wisconsin County Health Rankings to catalyze community health improvement.

BACKGROUND Assessment is a core function of public health; however, standard community health assessments often remain within the boundaries of the traditional public health system and rarely elicit public discussion and community-wide action. The University of Wisconsin Population Health Institute developed the annual Wisconsin County Health Rankings (Rankings) report in 2003 with three primary goals: (1) to increase media attention to local health outcomes and determinants; (2) to highlight the broad range of factors that influence health; and (3) to catalyze community health improvement efforts. METHODS We assessed how well the Rankings met these goals through an examination of media coverage and a survey of the local public health community following the 2006 report. FINDINGS Newspaper, television, and radio media across the state covered the Rankings, highlighting local results for outcomes and a broad range of determinants. Local public health officials used the Rankings for educating policy makers and community partners, performing needs assessments, and identifying program targets. CONCLUSIONS The Rankings report is an approach to community health assessment that has received media attention and been found to be useful by local public health officials in their community health improvement efforts.

Measuring the health of communities--how and why?

Improving the health of individuals is inextricably linked to improving the health of the communities where they live, work, and play. It is widely recognized that achieving the goal of Healthy People 2020— to increase length and quality of life for all—will not be accomplished by simply providing more health care to Americans. Broad and sustainable investments are needed to improve the health of entire communities, such as by implementing health promoting policies, supporting early childhood education and job training, and designing neighborhoods that promote healthy living. These efforts to improve the health of communities fundamentally distinguish public health from health care approaches, by “assuring conditions” so that people can be healthy. Public health surveillance plays a vital role in community health improvement efforts. Although the Institute of Medicine first defined assessment as one of the core functions of public health in 1988—its vital role in public health dates almost 200 years ago, when William Farr first published the Bills of Mortality. Public health surveillance now goes beyond the simple collection, analysis, and dissemination of date, to include the application of surveillance findings to population health improvement.4 Although few question the central role that public health surveillance plays in community health improvement, there is less consensus about the ways to measure the health of communities, and about strategies to apply this information to accelerate the translation of evidence-based programs and policies into practice.

How healthy could a state be

Objective. We predicted the amount of health outcome improvement any state might achieve if it could reach the highest level of key health determinants any individual state has already achieved. Methods. Using secondary county-level data on modifiable and nonmodifiable health determinants from 1994 to 2003, we used regression analysis to predict state age-adjusted mortality rates in 2000 for those younger than age 75, under the scenario of each states “ideal” predicted mortality if that state had the best observed level among all states of modifiable determinants. Results. We found considerable variation in predicted improvement across the states. The state with the lowest baseline mortality, New Hampshire, was predicted to improve by 23% to a mortality rate of 250 per 100,000 population if New Hampshire had the most favorable profile of modifiable health determinants. However, West Virginia, with a much higher baseline, would be predicted to improve the most—by 46% to 254 per 100,000 population. Individual states varied in the pattern of specific modifiable variables associated with their predicted improvement. Conclusions. The results support the contention that health improvement requires investment in three major categories: health care, behavioral change, and socioeconomic factors. Different states will require different investment portfolios depending on their pattern of modifiable and nonmodifiable determinants.

Job and Work Environment Predictors of Turnover Intention in Long-Term Care Facilities

The purpose of this study was to examine whether job characteristics, the work environment, participation in quality improvement (QI) activities, and facility quality improvement environment predicted turnover intention in nursing homes. 6584 nursing home employees from seventy-six nursing homes in a midwestern state participated. A self-administered survey was used to collect the data. The results suggest that specific work organization factors, such as workload and work scheduling, can be manipulated to affect turnover intentions. The implications for retaining nursing home employees are discussed.

A Case-Control Study of Medication use and Acute Occupational Injury

The purpose of this study was to test the hypothesis that workers who use medications that cause drowsiness are at increased risk of having an acute occupational injury. To test the hypothesis, a case-control study (n=1223 cases, n=1202 controls) was conducted where the sampling frame was composed of employees who had Workers Compensation claims in one Midwestern state between March and October of 1997. Cases were employees whose cause of injury was acute (i.e. caught in, struck by, or fall). Controls, on the other hand, were employees whose cause of injury was not acute (i.e. strain injuries). The results of the study supported the hypothesis by showing that the use of drowsing medications significantly increased the risk of having an acute occupational injury (odds ratio=2.45, 95% CI = 1.00–6.01), after adjusting for 12 other risk factors. Age modified the effect such that only younger workers who took drowsing medication were at increased risk of acute occupational injuries.