ArticleApplied clinical informatics2014
Optimization of decision support tool using medication regimens to assess rehospitalization risks.
Article in Applied clinical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Analyzing the Iatrogenic Triad: Discovering Strategies for Preventing Harm in the Elderly.Turkish journal of pharmaceutical sciences · 2024Article
- Article
- An Automated Strategy to Calculate Medication Regimen Complexity.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Article
- Medication Regimen Complexity In 8 Australian Residential Aged Care Facilities: Impact Of Age, Length Of Stay, Comorbidity, Frailty, And Dependence In Activities Of Daily Living.Clinical interventions in aging · 2019Article
- Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics.Journal of the American Medical Informatics Association : JAMIA · 2017Review
- Medication Regimen Complexity and Number of Medications as Factors Associated With Unplanned Hospitalizations in Older People: A Population-based Cohort Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2016Article
- Medication regimen complexity in adults and the elderly in a primary healthcare setting: determination of high and low complexities.Pharmacy practiceArticle
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnnecessary hospital readmissions are costly for the U.S. health care system. An automated algorithm was developed to target this problem and proven to predict elderly patients at greater risk of rehospitalization based on their medication regimens.
objectiveImprove the algorithm for predicting elderly patients' risks for readmission by optimizing the sensitivity of its medication criteria.
methodsOutcome and Assessment Information Set (OASIS) and medication data were reused from a study that defined and tested an algorithm for assessing rehospitalization risks of 911 patients from 15 Medicare-certified home health care agencies. Odds Ratio analyses, literature reviews and clinical judgments were used to adjust the scoring of patients' High Risk Medication Regimens (HRMRs). Receiver Operating Characteristic (ROC) analysis evaluated whether these adjustments improved the predictive strength of the algorithm's components.
resultsHRMR scores are composed of polypharmacy (number of drugs), potentially inappropriate medications (PIM) (drugs risky to the elderly), and Medication Regimen Complexity Index (MRCI) (complex dose forms, dose frequency, instructions or administration). Strongest ROC results for the HRMR components were Areas Under the Curve (AUC) of .68 for polypharmacy when excluding supplements; and .60 for PIM and .69 for MRCI using the original HRMR criteria. The "cut point" identifying MRCI scores as indicative of medication-related readmission risk was increased from 20 to 33.
conclusionThe automated algorithm can predict elderly patients at risk of hospital readmissions and its underlying criteria is improved by a modification to its polypharmacy definition and MRCI cut point.
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