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      Texas hospitals with higher health information technology expenditures have higher revenue: A longitudinal data analysis using a generalized estimating equation model

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          Abstract

          Background

          The benefits of health information technology (IT) adoption have been reported in the literature, but whether health IT investment increases revenue generation remains an important research question.

          Methods

          Texas hospital data obtained from the American Hospital Association (AHA) for 2007–2010 were used to investigate the association of health IT expenses and hospital revenue. The generalized estimation equation (GEE) with an independent error component was used to model the data controlling for cluster error within hospitals.

          Results

          We found that health IT expenses were significantly and positively associated with hospital revenue. Our model predicted that a 100 % increase in health IT expenditure would result in an 8 % increase in total revenue. The effect of health IT was more associated with gross outpatient revenue than gross inpatient revenue.

          Conclusion

          Increased health IT expenses were associated with greater hospital revenue. Future research needs to confirm our findings with a national sample of hospitals.

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          Most cited references52

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          Systematic review: impact of health information technology on quality, efficiency, and costs of medical care.

          Experts consider health information technology key to improving efficiency and quality of health care. To systematically review evidence on the effect of health information technology on quality, efficiency, and costs of health care. The authors systematically searched the English-language literature indexed in MEDLINE (1995 to January 2004), the Cochrane Central Register of Controlled Trials, the Cochrane Database of Abstracts of Reviews of Effects, and the Periodical Abstracts Database. We also added studies identified by experts up to April 2005. Descriptive and comparative studies and systematic reviews of health information technology. Two reviewers independently extracted information on system capabilities, design, effects on quality, system acquisition, implementation context, and costs. 257 studies met the inclusion criteria. Most studies addressed decision support systems or electronic health records. Approximately 25% of the studies were from 4 academic institutions that implemented internally developed systems; only 9 studies evaluated multifunctional, commercially developed systems. Three major benefits on quality were demonstrated: increased adherence to guideline-based care, enhanced surveillance and monitoring, and decreased medication errors. The primary domain of improvement was preventive health. The major efficiency benefit shown was decreased utilization of care. Data on another efficiency measure, time utilization, were mixed. Empirical cost data were limited. Available quantitative research was limited and was done by a small number of institutions. Systems were heterogeneous and sometimes incompletely described. Available financial and contextual data were limited. Four benchmark institutions have demonstrated the efficacy of health information technologies in improving quality and efficiency. Whether and how other institutions can achieve similar benefits, and at what costs, are unclear.
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            Can electronic medical record systems transform health care? Potential health benefits, savings, and costs.

            To broadly examine the potential health and financial benefits of health information technology (HIT), this paper compares health care with the use of IT in other industries. It estimates potential savings and costs of widespread adoption of electronic medical record (EMR) systems, models important health and safety benefits, and concludes that effective EMR implementation and networking could eventually save more than $81 billion annually--by improving health care efficiency and safety--and that HIT-enabled prevention and management of chronic disease could eventually double those savings while increasing health and other social benefits. However, this is unlikely to be realized without related changes to the health care system.
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              The effect of electronic prescribing on medication errors and adverse drug events: a systematic review.

              The objective of this systematic review is to analyse the relative risk reduction on medication error and adverse drug events (ADE) by computerized physician order entry systems (CPOE). We included controlled field studies and pretest-posttest studies, evaluating all types of CPOE systems, drugs and clinical settings. We present the results in evidence tables, calculate the risk ratio with 95% confidence interval and perform subgroup analyses for categorical factors, such as the level of care, patient group, type of drug, type of system, functionality of the system, comparison group type, study design, and the method for detecting errors. Of the 25 studies that analysed the effects on the medication error rate, 23 showed a significant relative risk reduction of 13% to 99%. Six of the nine studies that analysed the effects on potential ADEs showed a significant relative risk reduction of 35% to 98%. Four of the seven studies that analysed the effect on ADEs showed a significant relative risk reduction of 30% to 84%. Reporting quality and study quality was often insufficient to exclude major sources of bias. Studies on home-grown systems, studies comparing electronic prescribing to handwriting prescribing, and studies using manual chart review to detect errors seem to show a higher relative risk reduction than other studies. Concluding, it seems that electronic prescribing can reduce the risk for medication errors and ADE. However, studies differ substantially in their setting, design, quality, and results. To further improve the evidence-base of health informatics, more randomized controlled trials (RCTs) are needed, especially to cover a wider range of clinical and geographic settings. In addition, reporting quality of health informatics evaluation studies has to be substantially improved.
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                Author and article information

                Contributors
                leejinh@skku.edu
                jyoungchoi@hallym.ac.kr
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                5 April 2016
                5 April 2016
                2016
                : 16
                : 117
                Affiliations
                [ ]Department of Economics, Sungkyunkwan University College of Economics, Seoul, Republic of Korea
                [ ]Program in Healthcare Management, Hallym University College of Business, Kangwon-do, Chuncheon, 200-702 Republic of Korea
                Article
                1367
                10.1186/s12913-016-1367-9
                4820871
                27048305
                1d016556-83ac-4ca9-aa45-29debde85bbd
                © Lee and Choi. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 10 February 2015
                : 29 March 2016
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Health & Social care
                health it expenses,hospital revenue,generalized estimation equation,clustering error

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