Journal of General Internal Medicine

, Volume 29, Issue 12, pp 1589–1598

Factors Associated with Ordering Laboratory Monitoring of High-Risk Medications

Authors

    • Division of Clinical InformaticsBeth Israel Deaconess Medical Center
    • Meyers Primary Care Institutea Joint Endeavor of University of Massachusetts Medical School, Reliant Medical Group, and Fallon Community Health Plan
  • Jennifer Tjia
    • Meyers Primary Care Institutea Joint Endeavor of University of Massachusetts Medical School, Reliant Medical Group, and Fallon Community Health Plan
  • George Reed
    • University of Massachusetts Medical School
  • Daniel Peterson
    • Meyers Primary Care Institutea Joint Endeavor of University of Massachusetts Medical School, Reliant Medical Group, and Fallon Community Health Plan
  • Jerry H. Gurwitz
    • Meyers Primary Care Institutea Joint Endeavor of University of Massachusetts Medical School, Reliant Medical Group, and Fallon Community Health Plan
  • Terry S. Field
    • Meyers Primary Care Institutea Joint Endeavor of University of Massachusetts Medical School, Reliant Medical Group, and Fallon Community Health Plan
Original Research

DOI: 10.1007/s11606-014-2907-9

Cite this article as:
Fischer, S.H., Tjia, J., Reed, G. et al. J GEN INTERN MED (2014) 29: 1589. doi:10.1007/s11606-014-2907-9

ABSTRACT

BACKGROUND

Knowledge about factors associated with provider ordering of appropriate testing is limited.

OBJECTIVE

To determine physician factors associated with ordering recommended laboratory monitoring tests for high-risk medications.

METHODS

Retrospective cohort study of patients prescribed a high-risk medication requiring laboratory monitoring in a large multispecialty group practice between 1 January 2008 and 31 December 2008. Analyses are based on administrative claims and electronic medical records. The outcome is a physician order for each recommended laboratory test for each prescribed medication. Key predictor variables are physician characteristics, including age, gender, specialty training, years since completing training, and prescribing volume. Additional variables are patient characteristics such as age, gender, comorbidity burden, whether the medication requiring monitoring is new or chronic, and drug-test characteristics such as inclusion in black box warnings. We used multivariable logistic regression, accounting for clustering of drugs within patients and patients within providers.

RESULTS

Physician orders for laboratory testing varied across drug-test pairs and ranged from 9 % (Primidone–Phenobarbital level) to 97 % (Azathioprine–CBC), with half of the drug-test pairs in the 85-91 % ordered range. Test ordering was associated with higher provider prescribing volume for study drugs and specialist status (primary care providers were less likely to order tests than specialists). Patients with higher comorbidity burden and older patients were more likely to have appropriate tests ordered. Drug-test combinations with black box warnings were more likely to have tests ordered.

CONCLUSIONS

Interventions to improve laboratory monitoring should focus on areas with the greatest potential for improvement: providers with lower frequencies of prescribing medications with monitoring recommendations and those prescribing these medications for healthier and younger patients; patients with less interaction with the health care system are at particular risk of not having tests ordered. Black box warnings were associated with higher ordering rates and may be a tool to increase appropriate test ordering.

KEY WORDS

laboratory monitoringhigh-risk medicationsambulatory

Copyright information

© Society of General Internal Medicine 2014