Ten Modifiable Health Risk Factors and Employees' Medical Costs-An Update

PURPOSE

To estimate the relationship between employees' health risks and health-care costs to inform health promotion program design.

DESIGN

An observational study of person-level health-care claims and health risk assessment (HRA) data that used regression models to estimate the relationship between 10 modifiable risk factors and subsequent year 1 health-care costs.

SETTING

United States.

PARTICIPANTS

The sample included active, full-time, adult employees continuously enrolled in employer-sponsored health insurance plans contributing to IBM MarketScan Research Databases who completed an HRA. Study criteria were met by 135 219 employees from 11 employers.

MEASURES

Ten modifiable risk factors and individual sociodemographic and health characteristics were included in the models as independent variables. Five settings of health-care costs were outcomes in addition to total expenditures.

ANALYSIS

After building the analytic file, we estimated generalized linear models and conducted postestimation bootstrapping.

RESULTS

Health-care costs were significantly higher for employees at higher risk for blood glucose, obesity, stress, depression, and physical inactivity (all at P < .0001) than for those at lower risk. Similar cost differentials were found when specific health-care services were examined.

CONCLUSION

Employers may achieve cost savings in the short run by implementing comprehensive health promotion programs that focus on decreasing multiple health risks.

An Examination of Hospital Nurse Staffing and Patient Experience with Care: Differences between Cross-Sectional and Longitudinal Estimates

OBJECTIVE

To study the association between hospital nurse staffing and Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores.

DATA SOURCES

State hospital financial and utilization reports, Healthcare Cost and Utilization Project State Inpatient Databases, HCAHPS survey, and American Hospital Association Annual Survey of Hospitals.

STUDY DESIGN

Retrospective study using cross-sectional and longitudinal models to estimate the effect of nurse staffing levels and skill mix on seven HCAHPS measures.

DATA COLLECTION/EXTRACTION METHODS

Hospital-level data measuring nurse staffing, patient experience, and hospital characteristics from 2009 to 2011 for 341 hospitals (977 hospital years) in California, Maryland, and Nevada.

PRINCIPAL FINDINGS

Nurse staffing level (i.e., number of licensed practical nurses and registered nurses per 1,000 inpatient days) was significantly and positively associated with all seven HCAHPS measures in cross-sectional models and three of seven measures in longitudinal models. Nursing skill mix (i.e., percentage of all staff who are registered nurses) was significantly and negatively associated with scores on one measure in cross-sectional models and none in longitudinal models.

CONCLUSIONS

After controlling for unobserved hospital characteristics, the positive influences of increased nurse staffing levels and skill mix were relatively small in size and limited to a few measures of patients' inpatient experience.

The Effects of Telecommuting Intensity on Employee Health

Purpose.

To investigate the influence of the intensity of telecommuting on employee health.

Design.

Study design comprised a longitudinal analysis of employee demographic data, medical claims, health risk assessment data, and remote connectivity hours.

Setting.

Data from Prudential Financial served as the setting.

Subjects.

Active employees ages 18 to 64 years who completed the health risk assessment between 2010 and 2011 were the study subjects.

Measures.

Measures included telecommuting status and intensity, and eight indicators of health risk status (obesity, depression, stress, tobacco use, alcohol abuse, poor nutrition, physical inactivity, and an overall risk measure), with employee age, sex, race-ethnicity, job grade, management status, and work location as control variables.

Analysis.

Health risks were determined for nontelecommuters and telecommuters working remotely ≤8, 9 to 32, 33 to 72, and ≥73 hours per month. Longitudinal models for each health risk were estimated, controlling for demographic and job characteristics.

Results.

Telecommuting health risks varied by telecommuting intensity. Nontelecommuters were at greater risk for obesity, alcohol abuse, physical inactivity, and tobacco use, and were at greater overall risk than at least one of the telecommuting groups. Employees who telecommuted ≤8 hours per month were significantly less likely than nontelecommuters to experience depression. There was no association between telecommuting and stress or nutrition.

Conclusion.

Results suggest that employees may benefit from telecommuting opportunities.