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Closing the Referral Loop: an Analysis of Primary Care Referrals to Specialists in a Large Health System

Overview of attention for article published in Journal of General Internal Medicine, March 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

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4 news outlets
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13 X users

Citations

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57 Dimensions

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124 Mendeley
Title
Closing the Referral Loop: an Analysis of Primary Care Referrals to Specialists in a Large Health System
Published in
Journal of General Internal Medicine, March 2018
DOI 10.1007/s11606-018-4392-z
Pubmed ID
Authors

Malhar P. Patel, Priscille Schettini, Colin P. O’Leary, Hayden B. Bosworth, John B. Anderson, Kevin P. Shah

Abstract

Ideally, a referral from a primary care physician (PCP) to a specialist results in a completed specialty appointment with results available to the PCP. This is defined as "closing the referral loop." As health systems grow more complex, regulatory bodies increase vigilance, and reimbursement shifts towards value, closing the referral loop becomes a patient safety, regulatory, and financial imperative. To assess the ability of a large health system to close the referral loop, we used electronic medical record (EMR)-generated data to analyze referrals from a large primary care network to 20 high-volume specialties between July 1, 2015 and June 30, 2016. The primary metric was documented specialist appointment completion rate. Explanatory analyses included documented appointment scheduling rate, individual clinic differences, appointment wait times, and geographic distance to appointments. Of the 103,737 analyzed referral scheduling attempts, only 36,072 (34.8%) resulted in documented complete appointments. Low documented appointment scheduling rates (38.9% of scheduling attempts lacked appointment dates), individual clinic differences in closing the referral loop, and significant differences in wait times and distances to specialists between complete and incomplete appointments drove this gap. Other notable findings include high variation in wait times among specialties and correlation between high wait times and low documented appointment completion rates. The rate of closing the referral loop in this health system is low. Low appointment scheduling rates, individual clinic differences, and patient access issues of wait times and geographic proximity explain much of the gap. This problem is likely common among large health systems with complex provider networks and referral scheduling. Strategies that improve scheduling, decrease variation among clinics, and improve patient access will likely improve rates of closing the referral loop. More research is necessary to determine the impact of these changes and other potential driving factors.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 124 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 14%
Student > Bachelor 14 11%
Other 10 8%
Researcher 10 8%
Student > Postgraduate 7 6%
Other 24 19%
Unknown 42 34%
Readers by discipline Count As %
Medicine and Dentistry 30 24%
Nursing and Health Professions 13 10%
Social Sciences 6 5%
Business, Management and Accounting 5 4%
Engineering 5 4%
Other 16 13%
Unknown 49 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 39. 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 30 January 2023.
All research outputs
#1,029,024
of 25,262,379 outputs
Outputs from Journal of General Internal Medicine
#838
of 8,140 outputs
Outputs of similar age
#22,884
of 339,061 outputs
Outputs of similar age from Journal of General Internal Medicine
#31
of 152 outputs
Altmetric has tracked 25,262,379 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,140 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.1. This one has done well, scoring higher than 89% 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 339,061 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 152 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.