Маркетинг отношений в сфере услуг

Цель данной статьи – обосновать необходимость и важность персонифицированного подхода, построение доверительных отношений с клиентами на рынке услуг

Udlicitering af Odense Bytrafik

Det kommunale bybusselskab i Odense sammenlignes med Aalborg Omnibus Selskab, der blev omdannet til aktieselskab i 1995. Sammenligningerne foretages dels med hensyn til økonomi og dels med hensyn til service. Der er gennemført spørgekortanalyser af såvel passagerer, som chauffører og inter-views af personale og ledelse ved de to selskaber. Serviceniveauet for den kollektive trafik i de to byer sammenlignes. Formålet med projektet var at skabe et beslutningsgrundlag for Odense Byråds overvejelser om eventuel udlicitering af bybusdriften. Paperet præsenterer hovedresultaterne af undersøgelserne, der gennemførtes i efteråret 1999

Active safety monitoring of newly marketed medications in a distributed data network: application of a semi-automated monitoring system

We developed a semi-automated active monitoring system that uses sequential matched-cohort analyses to assess drug safety across a distributed network of longitudinal electronic healthcare data. In a retrospective analysis, we showed that the system would have identified cerivastatin-induced rhabdomyolysis. In this study, we evaluated whether the system would generate alerts for three drug-outcome pairs: rosuvastatin and rhabdomyolysis (known null association), rosuvastatin and diabetes mellitus, and telithromycin and hepatotoxicity (two examples for which alerting would be questionable). During >5 years of monitoring, rate differences (RDs) comparing rosuvastatin to atorvastatin were -0.1 cases of rhabdomyolysis per 1,000 person-years (95% CI, -0.4, 0.1) and -2.2 diabetes cases per 1,000 person-years (95% CI, -6.0, 1.6). The RD for hepatotoxicity comparing telithromycin to azithromycin was 0.3 cases per 1,000 person-years (95% CI, -0.5, 1.0). In a setting in which false positivity is a major concern, the system did not generate alerts for three drug-outcome pairs

Instrumental variable methods in comparative safety and effectiveness research

Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial

Nuances of Completion: Improving Student Outcomes by Unpacking the Numbers

“Accountability” is one of most loaded terms in education today. State governments, students, parents and taxpayers are demanding to know whether public education institutions are spending their money wisely and producing results. In response, colleges are investing enormous amounts of time, energy and resources in trying to increase the number of certificates and degrees awarded and transfers achieved. Increasingly, “completion” numbers often become the litmus test for the success or failure of an entire institution. Amidst this frenzy of activity to improve student completion rates, few colleges have had time to “unpack” the numbers and examine the student experiences being represented by these figures. No matter how big or small, each and every community college serves a diverse group of students with a broad range of backgrounds, talents and goals. These students have not only widely varied starting points and end goals, but also varied pathways to completion. How can colleges better understand the factors that affect diverse students’ ability to achieve completion

Principles of Redesign: Promising Approaches to Transforming Student Outcomes

Community colleges across the country are working hard to help their students succeed. With increasing demands for accountability from the public and state governments, many colleges are feeling the pressure to make changes—now. Even more importantly, practitioners want their students to be successful so they can reap the benefits of their educational achievements: associate’s degree holders earn 33% more than those with a high school diploma and bachelor’s degree holders earn 70% more. Many colleges have been frustrated with the limited results stemming from past efforts to promote student success. With new approaches to improvement emerging and waning every few years, and expanding expectations contrasting with shrinking college budgets, many leaders and practitioners have become rightfully skeptical of the very idea of “change.” Too often, community colleges have begun to feel like enormous battle ships— no matter who is in charge and what changes are made, the ship is too big to move more than a degree or two from its original course. In the face of these challenges, this guide offers a distillation of eight core principles of redesign that any community college leader or practitioner can use to begin thinking about change through a different lens. Based on research and practice conducted and observed by organizations such as Community College Research Center (CCRC), Jobs for the Future (JFF), WestEd, Public Agenda, the Research and Planning Group for California Community Colleges and the Bill and Melinda Gates Foundation, these principles reflect a fresh approach to thinking about student outcomes: one that looks at the institution from the students’ perspective and asks colleges to align structures, systems, programs and services in a coherent way

Measuring prevalence and incidence of chronic conditions in claims and electronic health record databases

Jeremy A Rassen,1 Dorothee B Bartels,2 Sebastian Schneeweiss,1,3,4 Amanda R Patrick,1 William Murk1,5 1Aetion, Inc, New York, NY, USA; 2BI X GmbH, Ingelheim, Germany; 3Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Boston, MA, USA; 4Harvard Medical School, Boston, MA, USA; 5Jacobs School of Medicine, University at Buffalo, Buffalo, NY, USA Background: Health care databases are natural sources for estimating prevalence and incidence of chronic conditions, but substantial variation in estimates limits their interpretability and utility. We evaluated the effects of design choices when estimating prevalence and incidence in claims and electronic health record databases. Methods: Prevalence and incidence for five chronic diseases at increasing levels of expected frequencies, from cystic fibrosis to COPD, were estimated in the Clinical Practice Research Datalink (CPRD) and MarketScan databases from 2011 to 2014. Estimates were compared using different definitions of lookback time and contributed person-time. Results: Variation in lookback time substantially affected estimates. In 2014, for CPRD, use of an all-time vs a 1-year lookback window resulted in 4.3–8.3 times higher prevalence (depending on disease), reducing incidence by 1.9–3.3 times. All-time lookback resulted in strong temporal trends. COPD prevalence between 2011 and 2014 in MarketScan increased by 25% with an all-time lookback but stayed relatively constant with a 1-year lookback. Varying observability did not substantially affect estimates. Conclusion: This framework draws attention to the underrecognized potential for widely varying incidence and prevalence estimates, with implications for care planning and drug development. Though prevalence and incidence are seemingly straightforward concepts, careful consideration of methodology is required to obtain meaningful estimates from health care databases. Keywords: epidemiology, epidemiologic methods, epidemiological monitoring, sentinel surveillance, pharmacoepidemiology, cross-sectional studies, secondary databases, prevalence, prevalence studies, incidenc

Proton Pump Inhibitors Are Not Associated With Acute Kidney Injury in Critical Illness

Recent epidemiologic data linking proton pump inhibitor (PPI) use to acute and chronic kidney dysfunction is yet to be validated in other populations, and mechanisms have not been explored. Using a large, well phenotyped inception cohort of 15 063 critically ill patients, we examined the risk of acute kidney injury (AKI), as defined by the Kidney Disease Improving Global Outcomes criteria guidelines, according to prior use of a PPI, histamine-2 receptor antagonist (H 2 RA), or neither. A total of 3725 (24.7%) patients reported PPI use prior to admission, while 905 (6.0%) patients reported H 2 RA use. AKI occurred in 747 (20.0%) and 163 (18.0%) of PPI and H 2 RA users respectively, compared to 1712 (16.2%) of those not taking acid suppressive medications. In unadjusted analysis, PPI and H 2 RA users had a 28% (95%CI 1.17-1.41, P  < .001) and 10% (95%CI 0.91-1.30, P =.31) higher risk of AKI compared to those taking neither class of medication. However, in sequential models that included adjustment for demographics, cardiovascular comorbidities, indications for PPI use, and severity of illness, the effect of PPI on the risk of AKI was attenuated, and in the adjusted analysis, PPI was not associated with AKI (OR 1.02; 95%CI 0.91-1.13, P =.73). The presence of sterile pyuria and hypomagnesemia did not modify the association between PPI use and AKI. In summary, after adjustment for demographics, illness severity, and the indication for PPI use, PPI use prior to admission is not associated with critical illness AKI.National Institute of Biomedical Imaging and Bioengineering (U.S.) (Grant 2R01 EB001659

Does Educational Status Impact Adult Mortality in Denmark? A Twin Approach

To disentangle an independent effect of educational status on mortality risk from direct and indirect selection mechanisms, the authors used a discordant twin pair design, which allowed them to isolate the effect of education by means of adjustment for genetic and environmental confounding per design. The study is based on data from the Danish Twin Registry and Statistics Denmark. Using Cox regression, they estimated hazard ratios for mortality according to the highest attained education among 5,260 monozygotic and 11,088 dizygotic same-sex twin pairs born during 1921–1950 and followed during 1980–2008. Both standard cohort and intrapair analyses were conducted separately for zygosity, gender, and birth cohort. Educational differences in mortality were demonstrated in the standard cohort analyses but attenuated in the intrapair analyses in all subgroups but men born during 1921–1935, and no effect modification by zygosity was observed. Hence, the results are most compatible with an effect of early family environment in explaining the educational inequality in mortality. However, large educational differences were still reflected in mortality risk differences within twin pairs, thus supporting some degree of independent effect of education. In addition, the effect of education may be more pronounced in older cohorts of Danish men

Confounding Control in Healthcare Database Research: Challenges and Potential Approaches

Epidemiologic studies are increasingly used to investigate the safety and effectiveness of medical products and interventions. Appropriate adjustment for confounding in such studies is challenging because exposure is determined by a complex interaction of patient, physician, and healthcare system factors. The challenges of confounding control are particularly acute in studies using healthcare utilization databases where information on many potential confounding factors is lacking and the meaning of variables is often unclear. We discuss advantages and disadvantages of different approaches to confounder control in healthcare databases. In settings where considerable uncertainty surrounds the data or the causal mechanisms underlying the treatment assignment and outcome process, we suggest that researchers report a panel of results under various specifications of statistical models. Such reporting allows the reader to assess the sensitivity of the results to model assumptions that are often not supported by strong subject-matter knowledge