Evidence map›Paper›PMID 27919250›Full record

Observational studyBMC medical informatics and decision making2016

The impact of health information technologies on quality improvement methodologies' efficiency, throughput and financial outcomes: a retrospective observational study.

Raed H AlHazme, Syed S Haque, Hal Wiggin, Arif M Rana

Abstract readObservational Study
In one paragraph

Observational study in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Raed H AlHazmeDepartment of Health Informatics, Rutgers University, School of Health Related Professions, Newark, NJ, 07107, USA. raed.alhazme@rutgers.edu.
Syed S HaqueDepartment of Health Informatics, Rutgers University, School of Health Related Professions, Newark, NJ, 07107, USA.
Hal WigginCollege of Osteopathic Medicine, Biomedical Informatics Program, Nova Southeastern University, Ft Lauderdale, FL, 33314, USA.
Arif M RanaCollege of Osteopathic Medicine, Biomedical Informatics Program, Nova Southeastern University, Ft Lauderdale, FL, 33314, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo evaluate whether or not the utilization of Health Information Technologies (HITs) in Quality Improvement Methodologies (QIMs) has impacts on QIMs' efficiency, throughput and financial outcomes at healthcare organizations and physician practices in the United States.

methodsThis is a retrospective observational study that was conducted between the years of 2014 and 2015 and relied on two data sources: the Dorenfest Institute dataset and the Healthcare Information and Management Systems Society (HIMSS) Analytics data source. In addition, questionnaires were submitted to collect data about how healthcare settings in the United States had been utilizing QIMs in the last 10 years. The submitted questionnaire invitations yielded 144 responses from 134 hospitals and 10 physician practices. Descriptive statistics were used to assess the condition of the data. This involved the utilization of Box-Whisker plots to visualize the data shape, outliers and variation. The Gamma correlation analysis method was used to evaluate the statistical relationships between the QIM outcomes, efficiency, throughput and financial outcomes, and the employment of HIT systems in QIMs.

resultsThe study found that 99.3% of the healthcare organizations and physician practices had implemented at least one QIM over the last 10 years. In the QIM implementations, the total numbers of reported utilization instances of manual data collection, electronic health records, lab information systems, pharmacy information systems, computerized provider order entry and radiology information systems were 387, 352, 205, 185, 180 and 158, respectively. Based on a 95% confidence limit, the Gamma statistical test has shown an inverse correlation between the exclusive utilization of manual data collection and the overall QIM efficiency (p = 0.047, Gamma = -0.388) and throughput (p = 0.012, Gamma = -0.593) outcomes. However, the overall QIM financial outcomes were found to have a statistically insignificant correlation (p = 0.159).

conclusionsThe study has revealed statistically significant negative impacts on QIMs' efficiency and throughput outcomes when the manual data collection is the sole method used in QIM implementations. This also indicates a positive correlation between the QIMs' efficiency and throughput outcomes and the HIT utilization in QIMs.

Indexed as

HumansMedical InformaticsQuality ImprovementRetrospective StudiesUnited StatesClinical and business intelligenceData analyticsHealthcare challengesQuality controlQuality improvement

Identifiers

PMID27919250
PMCPMC5139044

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.