ArticleHealth care management science2016
The effect of information technology on hospital performance.
Article in Health care management science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Implementation of Computerized Prescriber Order Entry Systems: A Review of Impacts, Barriers, and Facilitators.The Journal of pharmacy technology : jPT : official publication of the Association of Pharmacy Technicians · 2024Review
- Patient and Health Care Provider Perspectives on Patient Access to Test Results via Web Portals: Scoping Review.Journal of medical Internet research · 2023Article
- Automatic Identification and Segmentation of Orbital Blowout Fractures Based on Artificial Intelligence.Translational vision science & technology · 2023Article
- Article
- The Core of Healthcare Efficiency: A Comprehensive Bibliometric Review on Frontier Analysis of Hospitals.Healthcare (Basel, Switzerland) · 2022Review
- Factors that Determine Comprehensive Categorical Classification of EHR Implementation Levels.Health services insights · 2021Article
- Health information technology and hospital performance the role of health information quality in teaching hospitals.Heliyon · 2020Article
- Differentiate cavernous hemangioma from schwannoma with artificial intelligence (AI).Annals of translational medicine · 2020Article
- Unscheduled Radiologic Examination Orders in the Electronic Health Record: A Novel Resource for Targeting Ambulatory Diagnostic Errors in Radiology.Journal of the American College of Radiology : JACR · 2020Article
- Ensuring electronic medical record simulation through better training, modeling, and evaluation.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals.Health care management science · 2019Review
- Physician Use of Electronic Health Records: Survey Study Assessing Factors Associated With Provider Reported Satisfaction and Perceived Patient Impact.JMIR medical informatics · 2019Article
- Does participation in health information exchange improve hospital efficiency?Health care management science · 2018Article
- Psychometric evaluation of the Smartphone for Clinical Work Scale to measure nurses' use of smartphones for work purposes.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Religious Hospitals and Poorer Health Outcomes: A Case Study Using Hospital Performance Ratings.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While healthcare entities have integrated various forms of health information technology (HIT) into their systems due to claims of increased quality and decreased costs, as well as various incentives, there is little available information about which applications of HIT are actually the most beneficial and efficient. In this study, we aim to assist administrators in understanding the characteristics of top performing hospitals. We utilized data from the Health Information and Management Systems Society and the Center for Medicare and Medicaid to assess 1039 hospitals. Inputs considered were full time equivalents, hospital size, and technology inputs. Technology inputs included personal health records (PHR), electronic medical records (EMRs), computerized physician order entry systems (CPOEs), and electronic access to diagnostic results. Output variables were measures of quality, hospital readmission and mortality rate. The analysis was conducted in a two-stage methodology: Data Envelopment Analysis (DEA) and Automatic Interaction Detector Analysis (AID), decision tree regression (DTreg). Overall, we found that electronic access to diagnostic results systems was the most influential technological characteristics; however organizational characteristics were more important than technological inputs. Hospitals that had the highest levels of quality indicated no excess in the use of technology input, averaging one use of a technology component. This study indicates that prudent consideration of organizational characteristics and technology is needed before investing in innovative programs.
Indexed as
Identifiers
26018176What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.