Medical Information Delivering Improved Customer Experience: A Guide.

Customer experience (CX) is essential in any business. In the pharmaceutical industry, the Medical Information Contact Center is a customer-facing unit that provides evidence-based, scientifically balanced information to healthcare professionals and patients in response to unsolicited inquiries. The purpose of this paper is to provide analysis and guidance for designing and measuring interactions in the Medical Information Contact Center to facilitate the delivery of a superior and continuously improving CX. Surveys were conducted to establish current trends in CX among a diverse group of CX professionals and members of phactMI, a non-profit collaboration of Medical Information leaders from the pharmaceutical industry. The top three observations from the CX professionals survey centered on establishing a clear CX strategy, use of technology, and frequency of sharing results. Three potential areas for improvement focus on CX strategy, measurements of CX, and sharing of results. An analysis of quality monitoring results of customer interactions in the pharmaceutical industry from Centerfirst, a contact center quality monitoring service provider, was also reviewed. This analysis found a positive correlation between CX and three agent skills: taking the lead, empathy, and strong compliance skills. Based on these results, a CX guide was developed and specifically tailored for the pharmaceutical industry. This tool may be used to help identify, assess, and possibly improve CX.

The Medical Information Scientific Process: Define, Research, Evaluate, Synthesize, and Share (DRESS).

Medical information (MI) professionals are primarily responsible for researching and responding to unsolicited requests for information on their company's product(s). In an effort to set a standard for quality, the Pharma Collaboration for Transparent Medical Information (phactMI) created a code of practice for the provision of medical information to healthcare professionals. This code introduced the term "MI science skills" to describe the expertise required to perform the duties of an MI professional. These skills can be summarized by the acronym DRESS. In order to effectively and efficiently respond to an unsolicited request for information, the MI professional essentially follows five steps: define the question, research the topic, evaluate the evidence, synthesize a response, and share the answer. As this approach mirrors the scientific process for data generation, MI scientist may be a more apt description for this role. This paper explains the rationale behind the term MI scientist and the skills associated with each component of the DRESS approach.

Comparison of linezolid and daptomycin for the treatment of vancomycin-resistant enterococcal bacteremia.

Vancomycin-resistant enterococcal bacteremia (VRE-B) is a common nosocomial infection associated with significant morbidity and mortality. Daptomycin and linezolid are primary treatment options although definitive clinical data to assess comparative therapeutic effectiveness are lacking. This study assessed the outcomes of patients with VRE-B treated with linezolid or daptomycin. This was a single-center, retrospective cohort study evaluating adult patients with VRE-B treated with either daptomycin or linezolid admitted between January 2012 and August 2016 at a tertiary care, academic medical center. The primary outcome was clinical failure, a composite outcome defined as 14-day in-hospital mortality, microbiologic failure, or relapse of VRE-B. Secondary outcomes included 14-day in-hospital mortality, microbiologic failure, relapse of VRE-B, duration of VRE-B, and antibiotic failure. A multivariate logistic regression model was performed to adjust for potential confounding variables. A total of 93 patients were included (n = 62 for linezolid and n = 31 for daptomycin). All blood isolates were Enterococcus faecium. Overall clinical failure was 55.9% and 14-day in-hospital mortality was 21.5%. There was a significantly higher rate of clinical failure in the daptomycin group as compared with the linezolid-treated patients (74.2% versus 46.8%; p = 0.01; respectively). In multivariate logistic regression analysis, there was a significantly higher odds of clinical failure for patients treated with daptomycin as compared with linezolid (adjusted odds ratio 2.89; 95% confidence interval 1.08-7.75) after adjusting for confounders. Secondary outcomes were not statistically significantly different between study groups. Standard-dose (6 mg/kg) daptomycin treatment was associated with a higher rate of clinical failure as compared with linezolid treatment.