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Measuring the operational impact of digitized hospital records: a mixed methods study

Overview of attention for article published in BMC Medical Informatics and Decision Making, November 2016
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  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

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Title
Measuring the operational impact of digitized hospital records: a mixed methods study
Published in
BMC Medical Informatics and Decision Making, November 2016
DOI 10.1186/s12911-016-0380-6
Pubmed ID
Authors

Philip J. Scott, Paul J. Curley, Paul B. Williams, Ian P. Linehan, Steven H. Shaha

Abstract

Digitized (scanned) medical records have been seen as a means for hospitals to reduce costs and improve access to records. However, clinical usability of digitized records can potentially have negative effects on productivity. Data were collected during follow-up outpatient consultations in two NHS hospitals by non-clinical observers using a work sampling approach in which pre-defined categories of clinician time usage were specified. Quantitative data was analysed using two-way ANOVA models and the Mann-Whitney U test. A focus group was held with clinicians to qualitatively explore their experiences using digitized medical records. The quantitative and qualitative results were synthesized. Four hundred six consultations were observed. Using paper records, there was a significant difference in consultation times between hospitals (p = 0.016) and a significant difference in consultation times between specialties within hospitals (p = 0.003). Using digitized records there was a significant difference in consultation times between specialties within a hospital (p = 0.001). Excluding outliers, there was no significant difference between consultation times using digitized records compared with consultations using paper records in the same hospital, either at site (p > =0.285) or specialty level (p > =0.122). With digitized records at site A, two out of three specialties showed a significant increase in time spent searching computer records (p < =0.010, Δ = 01:50-07:10) and one specialty had a corresponding reduction in time spent searching paper records (p = 0.015, Δ = -00:28). Site B showed a notable increase in direct patient care (p < 0.001, Δ = 04:20-06:00) and time spent searching computer records (p < =0.043, Δ = 00:10-01:40) and reductions in the other time categories. The focus group confirmed that the most recent clinical letter was a vital document in the patient record, often containing most of the required information. Concerns were expressed about consistency of scanning practice, causing uncertainty about what could be relied upon to exist in the digitized record. Benefits of digitized records included: access from multiple locations, better prepared ward rounds, improved inpatient handovers and an improved timeline of patient events. Limitations of digitized records included: increased complexity of creating a patient summary, display of specialised content such as hand-drawn diagrams, inability to quickly flick through the pages to find relevant content. Digitized medical records can be implemented without detrimental operational impact. Inherent differences between specialties can outweigh the differences between paper and digitized records. Clear and consistent operational processes are vital for the reliability and usability of digitized medical records. Divergent views about usability (such as whether patient summary information is better or worse) may reflect familiarity with features of the digitized record.

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 79 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 16 20%
Researcher 10 13%
Student > Doctoral Student 5 6%
Student > Bachelor 5 6%
Student > Postgraduate 4 5%
Other 14 18%
Unknown 26 33%
Readers by discipline Count As %
Medicine and Dentistry 11 14%
Computer Science 10 13%
Nursing and Health Professions 7 9%
Social Sciences 6 8%
Business, Management and Accounting 4 5%
Other 13 16%
Unknown 29 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2017.
All research outputs
#7,206,788
of 23,510,717 outputs
Outputs from BMC Medical Informatics and Decision Making
#702
of 2,026 outputs
Outputs of similar age
#106,859
of 314,575 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#12
of 24 outputs
Altmetric has tracked 23,510,717 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 2,026 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 64% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 314,575 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.