Safe Opioid Prescripting: A SMART on FHIR Approach to Clinical Decision Support

Authors

  • Shyamashree Sinha NIH T32 Fellow in Bioinformatics Public Health Informatics Research with UB Biomedical Informatics department
  • Mark Jensen Student Department of Biomedical Informatics and Department of Philisophy University at Buffalo SUNY
  • Sarah Mullin Student Department of Biomedical Informatics University at Buffalo SUNY
  • Peter L Elkin Professor and Chair, Department of Biomedical Informatics & Professor of Internal Medicine at University at Buffalo, SUNY

DOI:

https://doi.org/10.5210/ojphi.v9i2.8034

Abstract

Prescription opioid pain medication overuse, misuse and abuse has been a significant contributing factor in the opioid epidemic. The rising death rates from opioid overdose has caused healthcare practitioners and researchers to work on optimizing pain therapy and limiting the prescriptions for pain medications. The state of New York has implemented a prescription drug monitoring program(PDMP), amended public health law to limit the prescription of opioids for acute pain and utilized the resources of the state and county health departments to help in curbing this epidemic. The recent publication of guidelines for prescription opioids from CDC [2] and ASIPP (American Society of Interventional pain practitioners) [4] have independently reviewed literature and found good evidence of limiting opioid prescription for acute and chronic non cancer pain.

Method

Clinical Decision Support Systems (CDSS) have been developed over the last decade to help in the work flow of healthcare providers since advanced technology is increasing the complexity of electronic health records systems. There are several systematics reviews on the effectivity and utility of CDSSs. The common consensus seems to be that commercially and locally developed CDSS are effective in improving patient measures while actual workload improvement and efficient cost cutting measure are not significantly improved by CDSS. Patient provider involvement in developing CDSS is a determinant of its success and utilization rates. In this light, a plug and play form of CDSS which is independent of the vendors of Electronic Health Records and can be implemented from an external platform through secure channels would be more effective.

The Health Level Seven’s (HL7) open licensed interoperability standard called Fast Health Interoperability Resources (FHIR) has a platform, Substitutable Medical Applications and Reusable Technologies (SMART) for CDSS app development by a third party. (Mandl and Kohane) [13] We adopted these open source standard to develop an app for proper implementation of the recently published guidelines for management of pain with opioid pain medications.

The goal for this CDSS tool would be to achieve proper monitoring of prescription drugs, patients’ medication list and potential interactive medications, surveillance for abuse/ misuse, patient involvement in alternative therapy, reporting problems and obtaining adequate pain control.

Author Biography

Shyamashree Sinha, NIH T32 Fellow in Bioinformatics Public Health Informatics Research with UB Biomedical Informatics department

Fellow

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Published

2017-09-08

How to Cite

Sinha, S., Jensen, M., Mullin, S., & Elkin, P. L. (2017). Safe Opioid Prescripting: A SMART on FHIR Approach to Clinical Decision Support. Online Journal of Public Health Informatics, 9(2). https://doi.org/10.5210/ojphi.v9i2.8034

Issue

Section

Capstones and Working Papers