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. 2013 Nov-Dec;20(6):1137-42.
doi: 10.1136/amiajnl-2012-001608. Epub 2013 May 22.

Effects of health information exchange adoption on ambulatory testing rates

Stephen E Ross  1 , Tiffany A Radcliff, William G Leblanc, L Miriam Dickinson, Anne M Libby, Donald E Nease Jr
Affiliations

Effects of health information exchange adoption on ambulatory testing rates

Stephen E Ross et al. J Am Med Inform Assoc. 2013 Nov-Dec.

Abstract

Objective: To determine the effects of the adoption of ambulatory electronic health information exchange (HIE) on rates of laboratory and radiology testing and allowable charges.

Design: Claims data from the dominant health plan in Mesa County, Colorado, from 1 April 2005 to 31 December 2010 were matched to HIE adoption data on the provider level. Using mixed effects regression models with the quarter as the unit of analysis, the effect of HIE adoption on testing rates and associated charges was assessed.

Results: Claims submitted by 306 providers in 69 practices for 34 818 patients were analyzed. The rate of testing per provider was expressed as tests per 1000 patients per quarter. For primary care providers, the rate of laboratory testing increased over the time span (baseline 1041 tests/1000 patients/quarter, increasing by 13.9 each quarter) and shifted downward with HIE adoption (downward shift of 83, p<0.01). A similar effect was found for specialist providers (baseline 718 tests/1000 patients/quarter, increasing by 19.1 each quarter, with HIE adoption associated with a downward shift of 119, p<0.01). Even so, imputed charges for laboratory tests did not shift downward significantly in either provider group, possibly due to the skewed nature of these data. For radiology testing, HIE adoption was not associated with significant changes in rates or imputed charges in either provider group.

Conclusions: Ambulatory HIE adoption is unlikely to produce significant direct savings through reductions in rates of testing. The economic benefits of HIE may reside instead in other downstream outcomes of better informed, higher quality care.

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Figures

Figure 1
Figure 1
Models chosen and considered for evaluation of the effect of health information exchange adoption on rates of testing.
Figure 2
Figure 2
Adoption of health information exchange in Mesa County, CO, 2005-2010.
See this image and copyright information in PMC

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