Automated prediction of risk for problem opioid use in a primary care setting

Timothy R Hylan, Michael Von Korff, Kathleen Saunders, Elizabeth Masters, Roy E Palmer, David Carrell, David Cronkite, Jack Mardekian, David Gross
Journal of Pain: Official Journal of the American Pain Society 2015, 16 (4): 380-7

UNLABELLED: Identification of patients at increased risk for problem opioid use is recommended by chronic opioid therapy (COT) guidelines, but clinical assessment of risks often does not occur on a timely basis. This research assessed whether structured electronic health record (EHR) data could accurately predict subsequent problem opioid use. This research was conducted among 2,752 chronic noncancer pain patients initiating COT (≥70 days' supply of an opioid in a calendar quarter) during 2008 to 2010. Patients were followed through the end of 2012 or until disenrollment from the health plan, whichever was earlier. Baseline risk indicators were derived from structured EHR data for a 2-year period prior to COT initiation. Problem opioid use after COT initiation was assessed by reviewing clinician-documented problem opioid use in EHR clinical notes identified using natural language processing techniques followed by computer-assisted manual review of natural language processing-positive clinical notes. Multivariate analyses in learning and validation samples assessed prediction of subsequent problem opioid use. The area under the receiver operating characteristic curve (c-statistic) for problem opioid use was .739 (95% confidence interval = .688, .790) in the validation sample. A measure of problem opioid use derived from a simple weighted count of risk indicators was found to be comparably predictive of the natural language processing measure of problem opioid use, with 60% sensitivity and 72% specificity for a weighted count of ≥4 risk indicators.

PERSPECTIVE: An automated surveillance method utilizing baseline risk indicators from structured EHR data was moderately accurate in identifying COT patients who had subsequent problem opioid use.

Full Text Links

Find Full Text Links for this Article


You are not logged in. Sign Up or Log In to join the discussion.

Related Papers

Remove bar
Read by QxMD icon Read

Save your favorite articles in one place with a free QxMD account.


Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"