Classic and spatial shift-share analysis of state-level employment change in Brazil

This paper combines classic and spatial shift-share decompositions of 1981 to 2006 employment change across the 27 states of Brazil. The classic shift-share method shows higher employment growth rates for underdeveloped regions that are due to an advantageous industry-mix and also due to additional job creation, commonly referred to as the competitive effect. Alternative decompositions proposed in the literature do not change this broad conclusion. Further examination employing exploratory spatial data analysis (ESDA) shows spatial correlation of both the industry-mix and the competitive effects. Considering that until the 1960s economic activities were more concentrated in southern regions of Brazil than they are nowadays, these results support beta convergence theories but also find evidence of agglomeration effects. Additionally, a very simple spatial decomposition is proposed that accounts for the spatially-weighted growth of surrounding states. Favourable growth in northern and centre-western states is basically associated with those states’ strengths in potential spatial spillover effect and in spatial competitive effect

Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence

<p>Abstract</p> <p>Background</p> <p>In order to accurately distinguish gaps of varying length in drug treatment for chronic conditions from discontinuation without resuming therapy, short-term observation does not suffice. Thus, the use of inhalation corticosteroids (ICS) in the long-term, during a ten-year period is investigated. To describe medication use as a continuum, taking into account the timeliness and consistency of refilling, a Markov model is proposed.</p> <p>Methods</p> <p>Patients, that filled at least one prescription in 1993, were selected from the PHARMO medical record linkage system (RLS) containing >95% prescription dispensings per patient originating from community pharmacy records of 6 medium-sized cities in the Netherlands.</p> <p>The probabilities of continuous use, the refilling of at least one ICS prescription in each year of follow-up, and medication free periods were assessed by Markov analysis. Stratified analysis according to new use was performed.</p> <p>Results</p> <p>The transition probabilities of the refilling of at least one ICS prescription in the subsequent year of follow-up, were assessed for each year of follow-up and for the total study period.</p> <p>The change of transition probabilities in time was evaluated, e.g. the probability of continuing ICS use of starters in the first two years (51%) of follow-up increased to more than 70% in the following years. The probabilities of different patterns of medication use were assessed: continuous use (7.7%), cumulative medication gaps (1–8 years 69.1%) and discontinuing (23.2%) during ten-year follow-up for new users. New users had lower probability of continuous use (7.7%) and more variability in ICS refill patterns than previous users (56%).</p> <p>Conclusion</p> <p>In addition to well-established methods in epidemiology to ascertain compliance and persistence, a Markov model could be useful to further specify the variety of possible patterns of medication use within the continuum of adherence. This Markov model describes variation in behaviour and patterns of ICS use and could also be useful to investigate continuous use of other drugs applied in chronic diseases.</p

Balance algorithm for cluster randomized trials

<p>Abstract</p> <p>Background</p> <p>Within cluster randomized trials no algorithms exist to generate a full enumeration of a block randomization, balancing for covariates across treatment arms. Furthermore, often for practical reasons multiple blocks are required to fully randomize a study, which may not have been well balanced within blocks.</p> <p>Results</p> <p>We present a convenient and easy to use randomization tool to undertake allocation concealed block randomization. Our algorithm highlights allocations that minimize imbalance between treatment groups across multiple baseline covariates.</p> <p>We demonstrate the algorithm using a cluster randomized trial in primary care (the PRE-EMPT Study) and show that the software incorporates a trade off between independent random allocations that were likely to be imbalanced, and predictable deterministic approaches that would minimise imbalance. We extend the methodology of single block randomization to allocate to multiple blocks conditioning on previous allocations.</p> <p>Conclusion</p> <p>The algorithm is included as Additional file <supplr sid="S1">1</supplr> and we advocate its use for robust randomization within cluster randomized trials.</p> <suppl id="S1"> <title> <p>Additional File 1</p> </title> <text> <p><b>Cluster randomization allocation algorithm version 1.</b> Algorithms scripted in R to provide robust cluster randomization.</p> </text> <file name="1471-2288-8-65-S1.zip"> <p>Click here for file</p> </file> </suppl

A systematic comparison of software dedicated to meta-analysis of causal studies

<p>Abstract</p> <p>Background</p> <p>Our objective was to systematically assess the differences in features, results, and usability of currently available meta-analysis programs.</p> <p>Methods</p> <p>Systematic review of software. We did an extensive search on the internet (Google, Yahoo, Altavista, and MSN) for specialized meta-analysis software. We included six programs in our review: Comprehensive Meta-analysis (CMA), MetAnalysis, MetaWin, MIX, RevMan, and WEasyMA. Two investigators compared the features of the software and their results. Thirty independent researchers evaluated the programs on their usability while analyzing one data set.</p> <p>Results</p> <p>The programs differed substantially in features, ease-of-use, and price. Although most results from the programs were identical, we did find some minor numerical inconsistencies. CMA and MIX scored highest on usability and these programs also have the most complete set of analytical features.</p> <p>Conclusion</p> <p>In consideration of differences in numerical results, we believe the user community would benefit from openly available and systematically updated information about the procedures and results of each program's validation. The most suitable program for a meta-analysis will depend on the user's needs and preferences and this report provides an overview that should be helpful in making a substantiated choice.</p

Is new drug prescribing in primary care specialist induced?

<p>Abstract</p> <p>Background</p> <p>Medical specialists are often seen as the first prescribers of new drugs. However, the extent to which specialists influence new drug prescribing in primary care is largely unknown.</p> <p>Methods</p> <p>This study estimates the influence of medical specialists on new drug prescribing in primary care shortly after market introduction. The influence of medical specialists on prescribing of five new drugs was measured in a cohort of 103 GPs, working in 59 practices, over the period 1999 until 2003. The influence of medical specialists on new drug prescribing in primary care was assessed using three outcome measures. Firstly, the proportion of patients receiving their first prescription for a new or reference drug from a specialist. Secondly, the proportion of GPs prescribing new drugs before any specialist prescribes to their patients. Thirdly, we compared the time until the GP's first own prescribing between GPs who waited for prescriptions from specialists and those who did not.</p> <p>Results</p> <p>The influence of specialists showed considerable differences among the new drugs studied. The proportion of patients receiving their first prescription from a specialist was greatest for the combination salmeterol/fluticasone (60.2%), and lowest for rofecoxib (23.0%). The proportion of GPs prescribing new drugs before waiting for prescriptions from medical specialists ranged from 21.1% in the case of esomeprazole to 32.9% for rofecoxib. Prescribing new drugs by specialists did not shorten the GP's own time to prescribing.</p> <p>Conclusion</p> <p>This study shows that the influence of medical specialists is clearly visible for all new drugs and often greater than for the existing older drugs, but the rapid uptake of new drugs in primary care does not seem specialist induced in all cases. GPs are responsible for a substantial amount of all early prescriptions for new drugs and for a subpopulation specialist endorsement is not a requisite to initiate in new drug prescribing. This contradicts with the idea that the diffusion of newly marketed drugs always follows a two-step model, with medical specialists as the innovators and GPs as the followers.</p

A self-rating scale for patient-perceived side effects of inhaled corticosteroids

BACKGROUND: Patient-reported side effect questionnaires offer a simple method for the systematic measurement of drug-related side effects. In order to measure patients' inhaled corticosteroids (ICS) related side effect perceptions the 14-day retrospective Inhaled Corticosteroid Questionnaire (ICQ) was developed. In this research we aim to assess the construct validity and reliability of the ICQ and test its responsiveness to dose changes in adult asthma patients. METHODS: In a cross-sectional study, current inhaler users with asthma completed the ICQ (27 with non ICS inhaler; 61 BDP equivalent daily ICS low dose ≤400 μg; 62 mid dose 401–800 μg; and 105 with high dose >800 μg). We generated 3 construct validity hypotheses: 1) a hierarchical dose-response pattern for scoring of the individual items on the ICQ, and statistically significant differences in the scores of each of the 15 ICQ domains by ICS dose group 2) an association between ICS dose and ICQ scoring after adjusting for appropriate confounders in multiple regression; 3) greater convergence between local side effect domains than between systemic and local domains of the scale. Test-retest reliability was assessed on a randomly selected subgroup of patients (n = 73) who also completed the ICQ a second time after 7 days. In a separate longitudinal study, 61 patients with asthma completed the ICQ at baseline and after changing their daily ICS dose, at 2- and 6- months, in order to test the ICQ's responsiveness. RESULTS: All three construct validity hypotheses were well supported: 1) a statistically significant difference existed in scores for 14 domains, the high ICS dose group scoring highest; 2) ICS dose independently predicted ICQ scoring after adjusting for confounders; 3) greater convergence existed between local ICQ domains than between local and systemic domains. The ICQ had good reproducibility: test-retest intraclass correlation coefficients were ≥0.69 for all but the 'Facial Oedema' domain. In the longitudinal study, ICQ scores for 'Voice Problems' changed significantly at 2- and 6-months from baseline and other ICQ domains displayed trends in scoring change accordant with dose modulation at 6-months. CONCLUSION: The ICQ has good dose-related discriminative properties, is valid, reliable, and shows potential responsiveness to ICS dose change

Development and validation of MIX: comprehensive free software for meta-analysis of causal research data

BACKGROUND: Meta-analysis has become a well-known method for synthesis of quantitative data from previously conducted research in applied health sciences. So far, meta-analysis has been particularly useful in evaluating and comparing therapies and in assessing causes of disease. Consequently, the number of software packages that can perform meta-analysis has increased over the years. Unfortunately, it can take a substantial amount of time to get acquainted with some of these programs and most contain little or no interactive educational material. We set out to create and validate an easy-to-use and comprehensive meta-analysis package that would be simple enough programming-wise to remain available as a free download. We specifically aimed at students and researchers who are new to meta-analysis, with important parts of the development oriented towards creating internal interactive tutoring tools and designing features that would facilitate usage of the software as a companion to existing books on meta-analysis. RESULTS: We took an unconventional approach and created a program that uses Excel as a calculation and programming platform. The main programming language was Visual Basic, as implemented in Visual Basic 6 and Visual Basic for Applications in Excel 2000 and higher. The development took approximately two years and resulted in the 'MIX' program, which can be downloaded from the program's website free of charge. Next, we set out to validate the MIX output with two major software packages as reference standards, namely STATA (metan, metabias, and metatrim) and Comprehensive Meta-Analysis Version 2. Eight meta-analyses that had been published in major journals were used as data sources. All numerical and graphical results from analyses with MIX were identical to their counterparts in STATA and CMA. The MIX program distinguishes itself from most other programs by the extensive graphical output, the click-and-go (Excel) interface, and the educational features. CONCLUSION: The MIX program is a valid tool for performing meta-analysis and may be particularly useful in educational environments. It can be downloaded free of charge via or