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AHRQ Research Studies Date
Topics
- Ambulatory Care and Surgery (1)
- (-) Care Management (3)
- Chronic Conditions (2)
- Clinical Decision Support (CDS) (1)
- Clinician-Patient Communication (1)
- Decision Making (1)
- Depression (1)
- Healthcare Delivery (1)
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- Opioids (2)
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 3 of 3 Research Studies DisplayedIke B, Baldwin LM, Sutton S
Staff and clinician work-life perceptions after implementing systems-based improvements to opioid management.
The authors assessed the impact of implementing the Six Building Blocks on the work-life of primary care providers and staff. Six rural and rural-serving primary care organizations implemented the Six Building Blocks, with assistance from practice facilitators, clinical experts, and informatics specialists. The authors found that clinicians and staff reported improvement in their work-life after implementing the Six Building Blocks Program to improve opioid medication management and recommended further research on patient experiences specific to practice redesign programs.
AHRQ-funded; HS023750.
Citation: Ike B, Baldwin LM, Sutton S .
Staff and clinician work-life perceptions after implementing systems-based improvements to opioid management.
J Am Board Fam Med 2019 Sep-Oct;32(5):715-23. doi: 10.3122/jabfm.2019.05.190027.
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Keywords: Opioids, Pain, Chronic Conditions, Primary Care: Models of Care, Primary Care, Care Management, Ambulatory Care and Surgery, Quality Improvement, Medication, Provider, Clinician-Patient Communication
Harle CA, DiIulio J, Downs SM
Decision-centered design of patient information visualizations to support chronic pain care.
The objective of this study was to describe a decision-centered design process, and resultant interactive patient information displays, to support key clinical decision requirements in chronic noncancer pain care. Through critical decision method interviews and a half-day multidisciplinary design workshop, researchers designed an interactive prototype, the Chronic Pain Treatment Tracker. This prototype summarizes the current treatment plan, past treatment history, potential future treatments, and treatment options that require caution. The researchers concluded that the Chronic Pain Treatment Tracker presents clinicians with the information they need in a structure that promotes quick uptake, understanding, and action.
AHRQ-funded; HS023306.
Citation: Harle CA, DiIulio J, Downs SM .
Decision-centered design of patient information visualizations to support chronic pain care.
Appl Clin Inform 2019 Aug;10(4):719-28. doi: 10.1055/s-0039-1696668..
Keywords: Pain, Chronic Conditions, Decision Making, Health Information Technology (HIT), Clinical Decision Support (CDS), Care Management, Healthcare Delivery
Parthipan A, Banerjee I, Humphreys K
Predicting inadequate postoperative pain management in depressed patients: a machine learning approach.
Researchers employed a machine-learning approach to identify patients who were prescribed a combination of selective serotonin reuptake inhibitors (SSRIs) and prodrug opioids in order to examine the effect of this combination on postoperative pain control. They identified patients who received surgery over a 9-year period by using EHR data from an academic medical center, then developed and validated natural language processing (NLP) algorithms to extract depression-related information from both structured and unstructured data elements. The machine-learning algorithm accurately predicted the increase or decrease of the discharge, 3-week, and 8-week follow-up pain scores when compared to the pre-operative pain score; pre-operative pain, surgery type, and opioid tolerance were the strongest predictors of postoperative pain control. The researchers conclude that their study results provide the first direct clinical evidence that the known ability of SSRIs to inhibit prodrug opioid effectiveness is associated with worse pain control among depressed patients. They suggest that prescribers might choose direct acting opioids such as oxycodone or morphine for depressed patients on SSRIs instead of prodrug opioids.
AHRQ-funded; HS024096.
Citation: Parthipan A, Banerjee I, Humphreys K .
Predicting inadequate postoperative pain management in depressed patients: a machine learning approach.
PLoS One 2019 Feb 6;14(2):e0210575. doi: 10.1371/journal.pone.0210575..
Keywords: Care Management, Depression, Medication, Opioids, Pain, Surgery