The impact of health information technology on inpatient medical errors in US hospitals
Description
TitleThe impact of health information technology on inpatient medical errors in US hospitals
Date Created2015
Other Date2015-10 (degree)
Extent1 online resource (xii, 193 p. : ill.)
DescriptionBackground In today’s complex and high risk healthcare environment the race to implement health information technology (health IT) in the care delivery system is becoming more prevalent in United States hospitals but the science to support its safe and effective use is contradictory at best. Since the 1999 Institute of Medicine Report, To Err is Human, Building a Safer Health System; there has been an increasingly intensive focus on the prevention of medical errors and the improvement of hospital safety and quality. In more recent years information technology has been identified as having the potential to reduce and prevent a wide range of issues, including medical errors, thus increasing patient safety, improving the quality of care, and reducing costs. Many hospitals and provides have integrated health IT into the patient care process, usually in the form of decision support systems, electronic health records, provider order entry systems, and the like. However, not all providers, clinicians, and researchers are in agreement on the impact these computerized systems have on safety, quality, and patient outcomes. With contradicting results in the literature and gaps in the evidence of the safe and effective use of health IT there is much to be learned in this area. This research project aims to quantify the impact of health IT on hospitals in the United States by investigating inpatient medical claims data, specifically medical errors and mortality rates and how they are impacted by health IT implementation data. The stage of health IT implementation from year to year will be evaluated for its impact on the number of medical errors and mortality rates. Methods To address the study objectives data from two datasets, the HIMSS Analytics datasets, provided by the Healthcare Information Management and Systems Society (HIMSS) and the Healthcare Cost and Utilization Project’s (HCUP) National Inpatient Sample (NIS) datasets provided by the Agency for Healthcare Research and Quality (AHRQ), were aggregated to form the analysis dataset. To accurately match the hospitals in each dataset the hospital’s Medicare ID code was used. Once the datasets were matched, the study outcomes, number of medical errors and mortality rates, were drawn from the HCUP data and the health IT stages was derived from the HIMSS data. The International Classification of Disease version 9 (ICD-9) codes were used to identify medical errors from the HCUP data. To address the primary and secondary objectives, both SAS and SPSS were utilized for data manipulation, data cleaning, and analysis. As part of the analysis descriptive statistics on hospital characteristics were assessed to determine the characteristics of hospitals at different stages of health IT implementation. Additionally, analysis of variance (ANOVA) was performed to determine the effects of health IT on medical errors and mortality rates. Finally multiple regression analysis was performed to determine if health IT stage is a predictor of medical errors and mortality rates. Results More than 530 hospitals were assessed for each of the four study years (2008, 2009, 2010, and 2011). Overall, US hospitals in three of the four years assessed support a significant difference in the mean number of medical errors between health IT stages within each year and for mortality rates all four years demonstrated the a significant amount of the variation in the model could be explained by health IT stage. Additionally, it was demonstrated that Stage 7 and Stage 0 were significantly different indicating that health IT stage can be a predictor for medical errors and mortality rates in three of the four years assessed. Conclusion This study demonstrates that there is an affect on quality of care, measured by medical errors and mortality rates, as it relates to the implementation of health IT. While the results are able to demonstrate this relationship between stages of health IT, further research is needed to assess health IT’s affects on hospital outcomes in greater detail. Additionally, the hospital characteristics associated with hospitals at various levels of health IT provides insight into the available resources for implementation of technology in the clinical setting.
NotePh.D.
NoteIncludes bibliographical references
Noteby Nadia Ramey
Genretheses, ETD doctoral
Languageeng
CollectionSchool of Health Related Professions ETD Collection
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
Statistical Profile