Search

Nursing homes are considered lagging behind in adopting health information technology (HIT). Many studies have highlighted the use of HIT as a means of improving health care quality. However, these studies overwhelmingly do not provide empirical information proving that HIT can actually achieve these improvements. The main research goal of this dissertation is to review the current development of HIT in nursing homes, to determine the nursing homes use of HIT features in MDS software, and to examine whether these uses result in better quality of care as measured by Nursing Home Compare (NHC) quality measures. This dissertation includes three parts and each part has its own emphasis and methodology centered on the main topic of the use of HIT in nursing homes. The first paper reviews the background and definitions of HIT as well as the most important applications and several standards that are currently used or under development. The second paper examines the use of commercial Minimum Data Set (MDS) software in nursing homes and identifies the HIT features that are available in the most commonly used software package. The frequency of use of each HIT feature in MDS software is also reported. The third paper evaluated whether the use of such HIT features is associated with better quality of care as measured by NHC. This dissertation reviews the HIT, summarizes a list of top 12 advanced HIT features in commercial MDS software used by the surveyed nursing homes. The study also evaluates the frequency of use of each feature. It concluded that although nursing homes were often viewed as technologically impaired, many of them had used quite advanced HIT in commercial MDS software. The findings are helpful in prioritizing the importance of future HIT development in nursing homes. Understanding the highlighted issues and the evidence of HIT use for promoting quality of care in nursing homes is a top research and public health concern. Future research should extend the list of HIT features in the current commercial MDS software and interconnect such features with available EHR systems in the continuum of health care. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Mediation analyses are common in the field of psychology or social science research. Mediators are variables that explain the mechanism of action forming the observed relationships between independent and dependent variables. The advantage of testing models is that it helps the researcher to construct the conceptual framework regarding the intercorrelation of variables of interest because pure relationships between independent and dependent variables are usually unlikely.This thesis was conducted to clarify whether the use of IT in MDS software would possibly influence the relationship between nurse staffing levels and quality of care in nursing homes. Literatures on the concepts of mediation and moderation effects were reviewed and analyses using STATA Sobel-Goodman tests were performed. Variables from three resources were used, including the use of IT in MDS software, three nurse staffing levels (RN, LPN, NA), and nursing home compare quality measures.Results of the Sobel-Goodman test indicated the indirect path for the use of IT was statistically significant in all cases of nurse staffing levels, and the tests of moderation effects showed the use of IT was a statistically significant moderator.Studies in this area can be further enhanced by taking into account more associated variables and by using extensive statistical mediation analysis. The public health importance for the present study is that it provides researchers with more information not only about the scientific evidences for exploring possible mediating variable effect from previous literatures but also about the statistical procedures for examining the statistical significance of an mediating effect.