The assessment of causation for a potential drug interaction requires thoughtful consideration of the properties of both the object and precipitant drugs, patient-specific factors, and the possible contribution of other drugs that the patient may be taking. The Naranjo nomogram was designed to evaluate single-drug adverse events, not drug-drug interactions. Several of the questions on the Naranjo nomogram do not apply to potential drug-drug interactions, while others do not specify object or precipitant drug. Nevertheless, it has been inappropriately used to evaluate drug-drug interactions. The Drug Interaction Probability Scale (DIPS) was developed to provide a guide to evaluating drug interaction causation in a specific patient. It is intended to be used to assist practitioners in the assessment of drug interaction-induced adverse outcomes. The DIPS uses a series of questions relating to the potential drug interaction to estimate a probability score. An accurate assessment using the DIPS requires knowledge of the pharmacologic properties of both the object and precipitant drugs. Inadequate knowledge of either the drugs involved or the basic mechanisms of interaction will be a limitation for some users. The DIPS can also serve as a guide in the preparation of articles describing case reports of drug interactions, as well as in the evaluation of published case reports.
Introduction There is limited literature comparing the experiences and attitudes of patients with chronic idiopathic constipation (CIC) to those of healthcare professionals (HCPs) treating CIC patients. The BURDEN-CIC study was conducted to better understand the experiences and ongoing needs of CIC patients and to assess their alignment versus disconnection with the perceptions and needs of HCPs who treat CIC patients.MethodsThe BURDEN-CIC study was an author-developed, online questionnaire that used KnowledgePanel® to survey individuals with CIC (n = 1223). HCPs who treat CIC patients were recruited separately and participated in a complementary online questionnaire (n = 331).ResultsMost patients had used (58%) or were using (51%) over-the-counter treatments for their CIC, with only 16% currently on prescription therapy. More than half (59%) of current CIC prescription users were not satisfied/completely satisfied with their current chronic treatment. Many patients (42%) felt frustrated regarding their CIC, and a similar percentage (40%) expressed acceptance that CIC was part of their daily life. The majority of HCPs agreed that CIC patients were frustrated (72%), stressed (50%), or fed up (43%) with current treatment options but were relatively unaware (21%) that patients were accepting of their CIC. HCPs reported the greatest challenges in treating CIC patients as response rates to current therapies (55%), treatment adherence (55%), management of treatment-related diarrhea (34%), and lack of treatment options (34%).ConclusionBURDEN-CIC identified that many patients and HCPs are frustrated and not satisfied with current CIC treatments due to lack of efficacy and side effects, such as diarrhea. The survey identified that many patients are “accepting” of their disease, potentially compromising treatment outcomes. More dialogue is needed between HCPs and CIC patients, especially regarding management of treatment expectations and side effects. Further, additional treatment options would be useful for both patients and HCPs.FundingSynergy Pharmaceuticals Inc.
Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective To provide recommendations for systematic evaluation of evidence from the scientific literature, drug product labeling, and regulatory documents with respect to DDIs for clinical decision support. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 15 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert-consensus answers to three key questions: 1) What is the best approach to evaluate DDI evidence?; 2) What evidence is required for a DDI to be applicable to an entire class of drugs?; and 3) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug information systems that implement these recommendations should be able to provide higher quality information about DDIs in drug compendia and clinical decision support tools.
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