Effect of integrated community neurology on utilization, diagnostic testing, and access
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Muhamad Y Elrashidi1, Lindsey M Philpot1, Nathan P Young1
1Division of Primary Care Internal Medicine, Department of Medicine (MYE, SJC, JOE), Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery (LMP, PR, KMS, JOE), Department of Neurology (NPY), and Department of Cardiovascular Diseases (PMM), Mayo Clinic, Rochester, MN.
Background:
The primary care medical home (PCMH) aims to promote delivery of high-value health care. However, growing demand for specialists due to increasingly older adults with complicated and chronic disease necessitates development of novel care models that efficiently incorporate specialty expertise while maintaining coordination and continuity with the PCMH. We describe the effect of a model of integrated community neurology (ICN) on health care utilization, diagnostic testing, and access.
Methods:
This is a retrospective, matched case-control comparison of patients referred to ICN for a face-to-face consultation over a 12-month period. The control group consisted of propensity score-matched patients referred to a non-colocated neurology practice during the study period. Administrative data were used to assess for diagnostic testing, visit utilization, and patient time to appointment.
Results:
From October 1, 2014, to September 30, 2015, we identified 459 patients evaluated by ICN for a face-to-face visit and 459 matched controls evaluated by the non-colocated neurology practice. The majority of patients were Caucasian and female. ICN patients had lower odds of EMGs ordered (adjusted odds ratio [OR] 0.64; 95% confidence interval [CI] 0.46-0.89; p = 0.009), MRI brain (adjusted OR 0.60; 95% CI 0.45-0.79; p = 0.0004), or subsequent referral to outpatient neurology (adjusted OR 0.62; 95% CI 0.47-0.83; p = 0.001). ICN was not associated with an increase in emergency department visits, hospitalizations, or appointment wait time.
Conclusions:
The ICN model in a PCMH has the potential to reduce diagnostic testing and utilization.
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