The relationship between health literacy and medication adherence is statistically significant but weak. It is plausible that health literacy has a mediator relationship with other adherence determinants. Future research should explore such relationships.

As the world's most populous country with the largest aging population and a rapidly growing economy, China is receiving increased attention from both the Chinese government and the governments of other countries that face low fertility and aging problems. This unprecedented shift of demographic structure has repercussions for many aspects of development including economic growth, social welfare, elder care, and other public welfare issues in China. Balancing population aging and economic growth requires innovative strategies and represents both challenges and opportunities for China.

No abstract

Research Objective. To assess the impact of recent Medicare prospective payment system (PPS) changes on efficiency in skilled nursing homes. Data Source/Study Setting. Medicare Cost Reports (MCR), On-line Survey Certification and Reporting System (OSCAR), Area Resource Files (ARF), a Centers for Medicare and Medicaid Services (CMS) hospital wage index website, a Consumer Price Index (CPI) database, and a survey of state Medicaid reimbursement rates. The sample was 8,361 nursing homes in the Medicare Cost Report databases from the years 1997 to 2003. Study Design. Data-envelopment analyses (DEA) calculated efficiency scores for three separate DEA models: unadjusted, acuity-adjusted, and acuity-and-qualityadjusted efficiency. The efficiency scores from these models were regressed on the Medicare PPS changes (the Balanced Budget Act [BBA], the Balanced Budget Refinement Act [BBRA] and the Benefits Improvement and Protection Act) and other organizational and market explanatory variables using a panel-data truncated regression. Principal Findings. Mean values for all efficiency measures decreased over time, the acuity-quality-adjusted efficiency measures decreasing the most. All policy variables were significantly negatively related to all efficiency measures. Higher nurse staffing was negatively related to efficiency in all but the acuity-quality-adjusted model. Other explanatory variables varied in their relationships to the efficiency variables. Conclusions. The results suggest that the reimbursement policy changes had a significantly negative impact on efficiency. Higher nurse staffing contributed to lower efficiency only when efficiency was not adjusted for quality. Various organizational and market factors also played significant roles in all efficiency models.Key Words. Nursing home efficiency, SNF PPS, BBA, nurse staffing and nursing home efficiency, DEA analysis of efficiency in nursing homesThe Medicare prospective payment system (PPS) for skilled nursing facility (SNF) reimbursement was implemented with the Balanced Budget Act (BBA) of 1997 in order to reduce nursing home costs and align reimbursement with r Health Research and Educational Trust

This analysis investigates what patients and practitioners can do to improve their interactive communications to achieve optimal patient-centric (PC) care. One goal of this clinical practice approach is to improve patient satisfaction, compliance, and outcomes. The mutual responsibilities required of both the patients and practitioners to attain PC care are discussed. Innovative, information technology techniques in the healthcare environment in general and in care delivery in particular are explored. Practitioner-to-patient encouragement vis-a-vis self education on their conditions is also provided.

A positive relationship has been demonstrated between the quality of care delivered in nursing homes and the quality of nursing staff providing the care. The general perception, however, is that there is a decline in registered nurses' staff hours in nursing homes. The primary objective of this study is to investigate whether the levels of registered nurses (RNs), licensed practical nurses (LPNs), and nursing assistants (NAs) as well as skill mix has changed in nursing homes between the years 1997 and 2007. A descriptive research design was employed on data derived from Online Survey Certification and Reporting System database. After accounting for facility size and ownership, it was found that more nursing homes have increased-rather than decreased-LPN and NA hours per resident day between 1997 and 2007. On the other hand, more nursing homes have decreased-rather than increased-RN hours per resident day and skill mix during the same time period.

BackgroundThe large number of uninsured individuals in the United States creates negative consequences for those who are uninsured and for those who are covered by health insurance plans. Young adults between the ages of 18 and 24 are the largest uninsured population subgroup. This subgroup warrants analysis. The major aim of this study is to determine why young adults between the ages of 18 and 24 are the largest uninsured population subgroup.MethodsThe present study seeks to determine why young adults between the ages of 18 and 24 are the largest population subgroup that is not covered by private health insurance. Data on perceived health status, perceived need, perceived value, socioeconomic status, gender, and race was obtained from a national sample of 1,340 young adults from the 2005 Medical Expenditure Panel Survey and examined for possible explanatory variables, as well as data on the same variables from a national sample of 1,463 from the 2008 Medical Expenditure Panel Survey.ResultsResults of the structural equation model analysis indicate that insurance coverage in the 2005 sample was largely a function of higher socioeconomic status and being a non-minority. Perceived health status, perceived need, perceived value, and gender were not significant predictors of private health insurance coverage in the 2005 sample. However, in the 2008 sample, these indicators changed. Socioeconomic status, minority status, perceived health, perceived need, and perceived value were significant predictors of private health insurance coverage.ConclusionsThe results of this study show that coverage by a private health insurance plan in the 2005 sample was largely a matter of having a higher socioeconomic status and having a non-minority status.In 2008 each of the attitudinal variables (perceived health, perceived value, and perceived need) predicted whether subjects carried private insurance. Our findings suggest that among those sampled, the young adult subgroup between the ages of 18 and 24 does not necessarily represent a unique segment of the population, with behaviors differing from the rest of the sample.

Previous studies show that the healthcare industry lags behind many other economic sectors in the adoption of information technology. The purpose of this study is to understand differences in structural characteristics between providers that do and that do not adopt Health Information Technology (HIT) applications. Publicly available secondary data were used from three sources: American Hospital Association (AHA) annual survey, Healthcare Information and Management Systems Society (HIMSS) analytics annual survey, and Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) databases. Fifty-two information technologies were grouped into three clusters: clinical, administrative, and strategic decision making ITs. Negative binomial regression was applied with adoption of technology as the dependent variables and eight organizational and contextual factors as the independent variables. Hospitals adopt a relatively larger proportion of administrative information technology as compared to clinical and strategic IT. Large size, urban location and HMO penetration were found to be the most influential hospital characteristics that positively affect information technology adoption. There are still considerable variations in the adoption of information technology across hospitals and in the type of technology adopted. Organizational factors appear to be more influential than market factors when it comes to information technology adoption. The future research may examine whether the Electronic Health Record (EHR) Incentive Program in 2011 would increase the information technology uses in hospitals as it provides financial incentives for HER adoptions and uses among providers.