Darius Stiels

Kathrin Schidelko

Jan O Engler

Renate Van Den Elzen

Dennis Rödder

Predicting the potential distribution of the invasive Common Waxbill Estrilda astrild (Passeriformes: Estrildidae)

Keywords: ecological niche modelling, species distribution model, niche overlap, MAXENT, climate change, invasive species Zusammenfassung Vorhersagen zur möglichen zukünftigen Verbreitung des invasiven Wellenastrilds Estrilda astrild (Passeriformes: Estrildidae) Weltweiter Handel und Mobilität haben zu einer zunehmenden Ausbreitung nichtheimischer Arten geführt. Invasive Arten können großen Einfluss auf zahlreiche Aspekte ökosystemarer Zusammenhänge haben. Deshalb ist die Fähigkeit, Regionen vorherzusagen, die für solche Arten potentiell geeignet und daher möglicherweise bedroht sind, eine Kernaufgabe erfolgreichen Managements Algorithmus, der auf maschinellem Lernen basiert, haben wir seine gegenwärtige, potentielle Verbreitung basierend auf Fundpunkten aus verschiedenen Quellen, die klimatisch gut geeignet erscheinen, in denen der Wellenastrild aber noch nicht nachgewiesen wurde. Unter zukünftigen Bedingungen legen die Modelle eine polwärts gerichtete Verschiebung der Verbreitungsgebiete nahe, obwohl die potentielle Verbreitung innerhalb der Übereinstimmung zwischen beiden Analysen wurden einige Unterschiede auffällig vorsichtig zu dem Modell basierend auf der natürlichen Verbreitung, unterstreichen

Human transport and commerce have led to an increased spread of non-indigenous species. Alien invasive species can have major impacts on many aspects of ecological systems. Therefore, the ability to predict regions potentially suitable for alien species, which are hence at high risk, has become a core task for successful management. The common waxbill Estrilda astrild is a widespread African species, which has been successfully introduced to many parts of the world. Herein, we used MAXENT software, a machine learning algorithm, to assess its current potential distribution based on species records compiled from various sources. Models were trained separately with records from the species" native range and from both invaded and native ranges. Subsequently, the models were projected onto different future climate change scenarios. They successfully identified the species known range as well as some regions that seem climatically well suited, where the common waxbill is not recorded yet. Assuming future conditions, the models suggest pole ward range shifts. However, its potential distribution within its tropical native and invasive ranges appears to be more complex. Although the results of both separate analyses showed general similarities, many differences have become obvious. Niche overlap analysis shows that the invasive range includes only a small fraction of the ecological space that can be found in the native range. Thus, we tentatively prefer the model based on 2 native locations only, but in particular we highlight the importance of the selection process of species records for modelling invasive species.

Introduction

Human transport and commerce has led to an increased spread of non-indigenous species [START_REF] Mack | Biotic Invasions: Causes, Epidemiology, Global Consequences, and Control[END_REF], which can have major impacts on ecological systems by altering mutualistic and competitive interactions among species, ecosystem functions, and resource distributions [START_REF] Mooney | The evolutionary impact of invasive species[END_REF]. Among exotic species, birds are particularly ubiquitous. Although in general, impacts on native species are suggested to be rather weak, also substantial impacts are observed at times including competition, predation, disease transmission but also mutualisms (Blackburn et al. 2009, chapter 7.5 and references therein). Herein, we aim to predict the recent and future potential distribution of the granivorous common waxbill, one of the most successful invaders among estrildid finches and a species that might even belong to the most successful among all tropical birds (see [START_REF] Lever | Naturalised birds of the world[END_REF]. Although studies on interactions with native species are largely lacking, granivorous passerines ("finches") can be substantial predators on plant seeds [START_REF] Clement | Seed preferences in sparrow species of the Monte desert, Argentina: implications for seed-granivore interactions[END_REF] and are thus likely to influence ecosystems extensively. Food seems to be one of the most important factors determining finch densities and thus making food competition among these birds very likely [START_REF] Schluter | Worldwide limitation of finch densities by food and other factors[END_REF]. Competition largely affects assemblages of invasive avian finch communities [START_REF] Lockwood | Ecomorphological pattern in Bermuda birds: the influence of competition and implications for nature preserves[END_REF]. Thus, identification of potential risk areas for a finch like the common waxbill is especially appealing.

Estrilda astrild is a widespread African species [START_REF] Clement | Seed preferences in sparrow species of the Monte desert, Argentina: implications for seed-granivore interactions[END_REF], originally endemic to mainland areas south of the Sahara and some islands (Fig. 1), including Bioko and Mafia. Distributional gaps exist in the rainforest areas of the Congo basin, and more arid parts of Western Africa and the northern Sahel zone, where it seems to be partly replaced by Estrilda troglodytes, with which it may form a superspecies (together with Estrilda nigriloris and Estrilda rufibarba; [START_REF] Fry | Estrilda astrild[END_REF]. It is a polytypic species with currently 15 [START_REF] Fry | Estrilda astrild[END_REF]) to 17 [START_REF] Dickinson | The Howard & Moore complete checklist of the birds of the world[END_REF] recognized subspecies, although these taxa intergrade and most are only slightly differentiated in colour and size (e.g. [START_REF] Goodwin | Estrildid finches of the world[END_REF]. Estrilda astrild favours open habitats such as savannas as well as areas characterized by tall grasses, and it can be common around human settlements [START_REF] Fry | Estrilda astrild[END_REF][START_REF] Goodwin | Estrildid finches of the world[END_REF]. Like most estrildid finches, common waxbills depend on at least some small puddles for drinking and bathing [START_REF] Goodwin | Estrildid finches of the world[END_REF].

Experiences from birds in captivity show that common waxbills are sensitive to low temperatures (below 15° C) and seem to suffer from cold-wet weather conditions in particular (Steinbacher andWolters 1965, Nicolai andSteinbacher 2002). They sometimes roost in nests [START_REF] Fry | Estrilda astrild[END_REF], which might maintain a favourable microclimate under harsher weather conditions (compare [START_REF] Ricklefs | Energetics of reproduction in birds. In: Paynter R (ed) Avian Energetics[END_REF]. Otherwise, common waxbills are highly gregarious and, although in most parts of their range are resident birds, local movements and nomadism seems to be not uncommon [START_REF] Fry | Estrilda astrild[END_REF]).

Common waxbills have been introduced, with and without intent, as a result of the pet trade to many parts of the world (Fig. 1). These introductions often date back to the 19 th century, and for some cases the introduction event is well known [START_REF] Lever | Naturalised birds of the world[END_REF]. Although not all introductions have resulted in successfully established populations, some occur e.g. in the Iberian Peninsula, where it was introduced in 1964 (Reino and Silva 1998 and references therein), in South America and on several tropical islands around the globe. The latter include Oahu (Hawaii), Society Islands (Tahiti), New Caledonia, Amirantes, parts of the Seychelles archipelago, Mauritius, Réunion, Rodrigues, Ascension, St Helena, São Tomé and Príncipe, Bermuda, Trinidad, Cape Verde and Canary Islands (e.g. [START_REF] Fry | Estrilda astrild[END_REF][START_REF] Lever | Naturalised birds of the world[END_REF].

Other parts of the world might offer also environmentally suitable conditions for the species, and further spreads are likely. During the last decades the species increased its invaded range at least within the Iberian Peninsula (Silva et al 2002).

Based on data presented by [START_REF] Reino | Using survival regression to study patterns of expansion of invasive species: will the common waxbill expand with global warming?[END_REF], the species might further expand its invaded range in south-western Europe making future predictions on a global scale especially appealing.

Species distribution models (SDMs) are tools to assess the potential distribution of species (Guisan and Thuiller 2005[START_REF] Jeschke | Usefulness of bioclimatic models for studying climate change and invasive species[END_REF], but see Elith and Leathwick 2009 for discussion on terminology) including birds [START_REF] Peterson | Predicting species" geographic distributions based on ecological niche modeling[END_REF][START_REF] Martinez-Meyer | Evolution of seasonal ecological niches in the Passerina buntings (Aves: Cardinalidae)[END_REF][START_REF] Walther | Known and predicted African Winter distributions and habitat use of the endangered Basra reed warbler (Acrocephalus griseldis) and the near-threatened cinereous bunting (Emberiza cineracea)[END_REF][START_REF] Strubbe | Establishment success of invasive ring-necked and monk parakeets in Europe[END_REF][START_REF] Echarri | Predicting the distribution of the crested tinamous, Eudromia spp. (Aves, Tinamiformes)[END_REF]. A special case of SDMs are climate envelope models, which rely on the climatic niche of the organism only (Guisan andThuiler 2005, Elith et al. 2006). SDMs are widely used to predict possible further spreads of invasive species [START_REF] Menke | Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder[END_REF][START_REF] Peterson | Predicting species invasions using ecological niche modeling: new approaches from bioinformatics attack a pressing problem[END_REF][START_REF] Rödder | Potential distribution of the alien invasive Brown tree snake, Boiga irregularis (Reptilia: Colubridae)[END_REF]. In particular, SDMs offer the possibility to project models derived from current conditions into the past or the future using palaeo climate layers or climate change scenarios of forthcoming decades [START_REF] Peterson | Future projections for Mexican faunas under global climate change scenarios[END_REF], Peterson and Nyári 2007[START_REF] Rödder | Bioclimatic models as predictive GIS tools for the identification of potential refuges and possible migration pathways[END_REF][START_REF] Waltari | Locating pleistocene refugia: comparing phylogeographic and ecological niche model predictions[END_REF].

Commonly, SDMs are derived from information of the spatial distribution of the target species and environmental, often climatic, variables at these locations.

Subsequently, the model is projected into geographic space using a geographic information system (GIS). Preferably, predictor variables should be proximal factors limiting the niche of the species (e.g. [START_REF] Austin | Spatial prediction of species distribution: an interface between ecological theory and statistical modelling[END_REF], Elith and Leathwick 2009, Rödder et al. 2009a). Models base upon the ecological niche concept, which assumes that the ecological niche of a species is the range of biotic and abiotic conditions in a multidimensional space, which allows the species to persist without immigration [START_REF] Hutchinson | Concluding remarks[END_REF][START_REF] Soberón | Grinnellian and Eltonian niches and geographic distributions of species[END_REF][START_REF] Soberón | Interpretation of models of fundamental ecological niches and species' distributional areas[END_REF]. One needs to keep in mind that SDMs postulate three key assumptions that are mostly not strictly met in nature [START_REF] Jeschke | Usefulness of bioclimatic models for studying climate change and invasive species[END_REF]. First, climatic tolerances of the species should be the main determinants of their distribution, neglecting dispersal limitations and biotic factors (e.g. competition, predation), which can only seldomly be incorporated in SDMs (e.g. Rödder et al. 2008a,b). Therefore the realized niche, i.e. environmental conditions present within the geographical space occupied by the species, is under natural circumstances only a subset of the fundamental niche (Hutchinson 1957, Soberón and[START_REF] Soberón | Interpretation of models of fundamental ecological niches and species' distributional areas[END_REF]. In addition, SDMs assume that the range of the species under study is in equilibrium with environmental parameters (Pearson andDawson 2003, Araújo andPearson 2005) and the niche is conservative over time and space (Peterson et al 1999, Wiens and[START_REF] Wiens | Niche conservatism: integrating evolution, ecology and conservation biology[END_REF]. Finally, SDMs cannot easily cope with dispersal limitations and thus claim that species occur at all locations where environmental conditions are favourable and nowhere else [START_REF] Jeschke | Usefulness of bioclimatic models for studying climate change and invasive species[END_REF]. Note that these assumptions are not undisputed (e.g. [START_REF] Beale | Opening the climate envelope reveals no macroscale associations with climate in European birds[END_REF][START_REF] Losos | Phylogenetic niche conservatisms, phylogenetic signal and the relationship bewteen phylogenetic relatedness and ecological similarity among species[END_REF], Rödder and Lötters 2009[START_REF] Warren | Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution[END_REF]).

When modelling the potential distribution of an exotic species, the question arises how to treat observations from the native and the invaded range, respectively.

Upon recently, SDMs were commonly derived from either species records obtained from the native range (e.g. [START_REF] Peterson | Predicting species" geographic distributions based on ecological niche modeling[END_REF]Viglais 2001, Thuiller et al. 2005) or the invaded range (e.g. [START_REF] Mau-Crimmins | Can the invaded range of a species be predicted using only native-range data? Lehmann lovegrass (Eragrostis lehmanniana) in the southwestern United States[END_REF]. As recent findings highlighted a failure of models trained with native records to predict invasive ones [START_REF] Fitzpatrick | The biogeography of prediction error: why does the introduced range of the fire ant over-predict its native range?[END_REF], Rödder and Lötters 2009[START_REF] Beaumont | Different climatic envelopes among invasive populations may lead to underestimations of current and future biological invasions[END_REF][START_REF] Broennimann | Predicting current and future biological invasions: both native and invaded ranges matter[END_REF] recommend using occurrence data from the whole range of the species.

Herein, we approach this issue using a split dataset from the (1) native as well as (2) from the native and invaded range of Estrilda astrild and describe its consequences for (a) current and (b) future predictions of the potential range of this species.

Methods

Common waxbill records

Species records were obtained from the "Global Biodiversity Information Facility" (GBIF, http://www.gbif.org), from the "Invasives Information Network" (I3N, http://i3n.institutohorus.org.br/filt_especies.asp) of the Inter-American Biodiversity Information Network, from labels of museum specimens held in the Zoological Research Museum Alexander Koenig, and from additional literature references [START_REF] Fry | Estrilda astrild[END_REF][START_REF] Gatter | Birds of Liberia[END_REF][START_REF] Leonard | Important Bird Areas in Zambia[END_REF]. All records were mapped using DIVA-GIS 5.4 [START_REF] Hijmans | DIVA-GIS, version 1.4. A geographic information system for the management and analysis of genetic resources data[END_REF], available through http://www.diva-gis.org) for visual inspection, and coordinates were checked to spot possible errors, i.e. if coordinates were not sufficiently accurate (possible spatial error decisively larger than selected spatial solution of grid size of environmental data, see below) or otherwise unreasonable (e.g. coordinates of the museum instead of the location of the bird), locations were excluded from the analysis. Localities without coordinates were georeferenced by consulting online gazetteers, i.e. the Biogeomancer (http://bg.berkely.edu/latest, last access 18.05.2009) and Falling Rain (http://www.fallingrain.com/world, last access 18.05.2009). Furthermore, specimens collected before 1950 were not included in this study to be in concordance with the temporal resolution of the environmental predictors (see below). For each grid cell only one record was permitted in any analysis, resulting in 135 species records from the native and 341 species records from the introduced part of the range.

Spatially unbalanced sampling designs may cause artificial regional clusters of species records [START_REF] Dormann | Methods to account for spatial autocorrelation in the analysis of species distributional data: a review[END_REF]. To minimize such effects, a cluster analysis based on Euclidean distances in feature space was conducted with XLSTAT 2009 (Addinsoft, http://www.xlstat.com). The resulting dendrogram was blunted leaving each 118 native and invasive classes, and only one randomly chosen record per class was used for further processing. This method has been used to reduce effects of spatial autocorrelation (e.g. Rödder et al. 2009b), and simulations suggest a superior performance compared to simple distance buffers (Schmidtlein, Rödder and Feilhauer, unpubl. data). As AUC scores are affected by prevalence, and although native and invasive data did not contribute equally within the NAT+INV model, this procedure allows a better comparability between the NAT and the NAT+INV models.

Environmental data

We used climate data taken from WorldClim, v. 1.4 (Hijmans et al. 2005, http://www.worldclim.org), which cover the period from 1950-2000. Data from a global network of weather stations were interpolated for the whole land surface of the globe with latitude, longitude and elevation as independent variables [START_REF] Hijmans | Very high resolution interpolated climate surfaces for global land areas[END_REF].

Monthly temperature and precipitation data were summarized into 19 so called Bioclim variables [START_REF] Busby | BIOCLIM -A bioclimatic analysis and predictive system[END_REF]. We used only eight of them as predictor variables in our ecological niche models to reduce effects of overfitting and multi-collinearity of predictors (Heikkinnen et al. 2006). Given the changing seasonal aspect of grasslands and the need for open water for the species, we selected variables covering annual parameters (BIO1, annual mean temperature; BIO12, annual precipitation), quaternary aspects (BIO10, mean temperature of warmest quarter; BIO11, mean temperature of coldest quarter; BIO16, precipitation of wettest quarter; BIO17, precipitation of driest quarter) and seasonal characteristics (BIO4, temperature seasonality; BIO15 precipitation seasonality) of the climate as a biological meaningful combination of predictors. We used a rather coarse resolution of 2.5 arc-minutes (about 4.63 km at the equator) meeting the accuracy of most available occurrence data (see [START_REF] Graham | The influence of spatial errors in species occurrence data used in distribution models[END_REF] for a discussion on spatial errors) and at least slightly compensating for the nomadic biology of the species.

For future projections, we obtained climate data of six climate scenarios describing projected conditions for the year 2080 under two different emission scenarios (A2a, B2a) and two different climate models, respectively.

Comparison of climate niches

In order to illustrate the relative positions of native vs. invasive ranges in ecological space (E-Space) as well as the potential niche available for each of them, we computed principal component analyses (PCA) depending on the environmental variables used for modelling. Only those principal components were selected which had eigenvalues ≥1 because these PCs explain more variance than the original data does (here, two PCs were extracted). To assess the niche overlaps in E-space, we subsequently performed linear discriminant analysis (LDA) following Rödder and Engler (in press). This method has the advantage of comparing niche-overlap directly in ecological space instead of geographical space. Hence, it is independent from SDM predictions. In LDA native and invasive ranges were a priori defined as groups, each with equal prior probabilities and compared through a set of explanatory variables, representing the E-space spanned by principal components. The discriminant model was constructed with a randomly selected subset of 70% of the dataset and validated with the rest of the data. Total overlaps in E-space were derived by summing all falsely classified values and dividing them by the total of all values resulting in a metric ranged between 0 (no overlap) to 1 (total overlap).

Accounting for possible variations caused by data splits, this procedure was repeated 1000 times. Computations were conducted using R 2.11.1 (R Development Core

Team, 2010).

Results

Model Performance

We received similar AUC values in both model approaches, i.e. for NAT based on the native range (AUC Test = 0.8211) and NAT+INV including data points from the native and the introduced range (AUC Test = 0.7567) (Fig. 2). AUC values can be considered at least as "useful" (>0.75) or even good (>0.8) although classification schemes might differ according to the aim of the study [START_REF] Swets | Measuring the accuracy of diagnostic systems[END_REF]. Analysis of variable contributions revealed high values for mean temperature of the warmest and coldest quarters as well as precipitation variables (Figs. 3a,b). In general, variable contributions were similar in both models, although we detected pronounced differences in the contributions of "temperature seasonality". Response curves for each predictor variable are provided in the online supplementary material. The minimum training logistic threshold was 0.0822 for NAT and 0.0883 for NAT+INV.

Values of the more relaxed 10% training presence logistic threshold were also similar in both models (0.2483 for NAT, 0.2820 for NAT+INV, Fig. 4). The spatial extent of the potential distributions derived from the more restrictive 10% training presence logistic threshold was generally smaller (Table 1).

Current potential distribution

Based on both models (Figs. 5a,b) the common waxbill has a huge potential distribution throughout the tropics, subtropics and some temperate regions. The spatial extent of the potential distributions suggested by the models is not consistent over both thresholds (Table 1). Both models show general similarities, although differences in some tropical areas are obvious (e.g. within Australia and Southeast Asia). Unsurprisingly, within Africa the NAT model better reflects the actual distribution when compared with the expert map. The NAT+INV model seems to overpredict some sub-Saharan areas like the Congo basin. According to the NAT+INV model (Fig. 5b) the potential distribution of E. astrild is slightly more concentrated in the tropics, and less so in the subtropics. Both models predict suitable areas in some temperate regions including parts of Europe and North America. Although the NAT+INV model includes data points from South America, the NAT (Fig. 5a) model projects larger areas of highly suitable conditions within this continent. However, the native as well as the introduced range of the common waxbill is well covered by both models. Note that large areas that host suitable climatic conditions for the species, e.g. in Australia, South East Asia and the Andes, are currently not populated by the species.

Future potential distribution

Under projected climate conditions for the end of the 21 st century, both models predict a general reduction of climatically suitable areas (Table 1). Furthermore, a slight pole ward shift of current northern and southern distribution limits is suggested (Figs. 6a-d). This is mainly a shift of the northern potential distribution limit as even under current climate conditions the southernmost parts of Africa, Australia, and South America show suitable climatic conditions. In western North America, the NAT+INV model predicts only a slightly higher probability of occurrence (Fig. 6c-d)

while under the NAT model this change is more obvious (Fig. 6a-b). In Europe, the NAT+INV model predicts a decline of suitable areas in parts of the Mediterranean region while these changes are less clear assuming the NAT model. The situation in the tropics is even more complex. In most parts of the native African range of the common waxbill, the NAT model predicts a strong reduction of occurrence probabilities. However, this pattern is reversed in Southern Africa, where higher suitability values are predicted for the future (Fig. 6a-b). Suitability also decreases according to NAT in parts of its invaded range such as in the Caatinga region of north-eastern Brazil and in areas not populated by common waxbills such as in India and in the south-western part of the Arabian Peninsula. The NAT+INV model also predicts lower likelihoods of occurrence in parts of South America and India (Fig. 6cd). Inside Africa, these results contradict the outputs of the NAT model as declines in suitability are much less pronounced and are only obvious in central Southern Africa, where the likelihood of occurrence might drop below the chosen thresholds.

Decreases in suitability might also occur within the southern Congo basin and along the current northern natural border of the common waxbill"s range.

In direct comparison, both emission scenarios closely resemble each other although there are differences in some smaller areas. Assuming the A2a scenario, the NAT model predicts a stronger decrease in suitability than the B2a scenario within parts of tropical Africa and South America (Fig. 6a vs. 6b). This regional trend becomes also evident on a global extent. Here, decreases for the A2a scenario are more severe than for the B2a scenario.

Comparison of climate niches

PCA-LDA resulted in an overlap value of 0.32 (sd ± 0.057) of climate niches between the records from the native and records from the invasive distribution of the common waxbill. This low overlap is largely due to the fact that invasive locations occupy a smaller climate space than the native ones and are nested within the native E-space (Fig. 7). This indicates that the NAT+INV model does not incorporate any additional climate space in comparison to the NAT model.

Discussion

Model performance and current potential distribution

Based on our SDMs we were able to predict the current and future global potential distribution of the common waxbill. Compared to the expert map, our prediction reflects current distribution fairly well applying the minimum training presence threshold. This is especially true for the native afrotropical range, which has its northern limit south of the Sahel zone, well reflecting the gap in the Congo Basin applying the NAT model. The high occurrence probabilities in the invaded range of the Iberian Peninsula or in parts of eastern coastal Brazil are in concordance with the realized distribution of the species [START_REF] Reino | Variation partitioning for range expansion of an introduced species: the common waxbill Estrilda astrild in Portugal[END_REF]Silva 1998, Ridgely and[START_REF] Ridgely | Field Guide to the Songbirds of South America: The Passerines (Mildred Wyatt-Wold Series in Ornithology)[END_REF].

However, the current potential distribution limited by the 10% training presence threshold seems to underestimate its realized distribution, at least within the native African range. Hence, given the threshold dependencies, our global quantifications based on estimated areas should be interpreted with care.

Variable contributions and response curves are well in concordance with the known climatic demands of the species (see introduction). However, seasonality parameters -with the noteworthy exception of temperature seasonality in the NAT+INV model -did not highly contribute to the model. This is possibly due to a high variability in parameters in the overall range, which is quite large.

When interpreting the potential distribution of a species derived from a SDM, it is necessary to consider possible discrepancies between the fundamental climatic niche and the realized niche of the species (Hutchinson 1957, Soberón and[START_REF] Soberón | Interpretation of models of fundamental ecological niches and species' distributional areas[END_REF]. Besides climatic demands, biological interactions, accessibility of regions and non-climatic habitat parameters need to be considered [START_REF] Heikkinen | Methods and uncertainties in bioclimatic envelope modelling under climate change[END_REF][START_REF] Davis | Making mistakes when predicting shifts in specues range in response to global warming[END_REF]). Thus, unsurprisingly our models predict a potential distribution notably larger than the one actually inhabited by the species (Gioia and Pigot 2000). Huge parts of Central America, Australia as well as South and Southeast Asia harbour climatic conditions well suitable for the common waxbill. High occurrence probabilities are also found in mountainous areas of the Andes and the Himalaya. These areas might have not been colonized yet, maybe due to dispersal limitations, i.e. the species has not been released there or did not make its way on its own from colonized areas. In any case, finding suitable conditions for a species on a rather coarse scale in climatically diverse areas such as the Andes does not surprise. Competition may play a role and theoretically could explain the absence of the common waxbill on mainland Asia and Australia as these areas are home to a variety of other estrildid finches [START_REF] Clement | Seed preferences in sparrow species of the Monte desert, Argentina: implications for seed-granivore interactions[END_REF][START_REF] Restall | Munias and Mannikins[END_REF]. [START_REF] Reino | Variation partitioning for range expansion of an introduced species: the common waxbill Estrilda astrild in Portugal[END_REF] related an expansion of the invaded range of the common waxbill in Portugal mainly to spatial-temporal variables, but in a recent publication, temperature and relative humidity were identified as important predictor variables [START_REF] Reino | Using survival regression to study patterns of expansion of invasive species: will the common waxbill expand with global warming?[END_REF]). This ongoing range extension might indicate that at least some northern invasive populations are not in environmental equilibrium. Modelling of species with ongoing range extensions is a special challenge (Elith et al. 2010).

However, we rest our results upon a large sample of locations from a huge part of the known distribution of the species and hence at least mitigate possible effects. In any case, interpretations of the common waxbill"s potential distribution should be done cautiously as the species, although well studied for an estrildid finch, is still little known from the field. Exact temperature requirements rely on experience with pet birds only rather than from scientific experiments. Furthermore, variation in the climatic niche among populations and subspecies is hardly investigated although Nicolai and Steinbacher (2007) suppose considerable geographic differences, again mainly derived from temperature sensitivity of birds kept in captivity [START_REF] Mau | Weltbürger Wellenastrild[END_REF]. This would potentially violate one of the basic assumptions for niche models. However, for most areas of the introduced range, subspecific status of the populations is unknown although mainly the subspecies jagoensis (e.g. on Cape Verde), astrild and angolensis (Príncipe, São Tomé) might be involved [START_REF] Fry | Estrilda astrild[END_REF]).

The large distribution of suitable climate around the globe shown in this study underlines the invasive potential of the species. While many other estrildid finches are invasive on islands only, the common waxbill already has noteworthy populations on continents making these areas also relevant for considerations of invasive species management. Our models predict a larger potential distribution range than actually occupied within South America, where competitive [START_REF] Peterson | Using ecological-niche modeling to predict Barred Owl invasions with implications for Spotted Owl conservation[END_REF] or mutualistic interactions with ecomorphologically similar species of the genus Sporophila (Emberizidae) and other syntopically granivorous species [START_REF] Manhães | Spatial Distribution and Diversity of Bird Community in an Urban Area of Southeast Brazil[END_REF] are likely. This is of particular concern as many seedeaters of the genus Sporophila are under severe threat, partially due to bird trapping, but also due to habitat destructions [START_REF] Silva | Seasonal movements and conservation of seedeaters of the genus Sporophila in South America[END_REF]. So these potential interactions are a rewarding field for future research. As long as detailed studies on the impact of common waxbills on native species are lacking, we can only recommend an enhanced monitoring of the species where it is already established. Our potential distribution maps may also indicate areas where pet trade of Estrilda astrild should be under particular control.

Future Predictions

Our models predict less climatically suitable area for the common waxbill on a global scale. This trend is consistent over thresholds and models. However, note that we did not extrapolate onto climate conditions exceeding the calibration range of the models.

Hence, any novel climate conditions occurring in the future are assumed to be unsuitable for the species. Furthermore, we do not take any evolutionary or behavioural adaptations into account. Besides this global trend, a more regional view is warranted. The suggest pole ward shift in northern temperate areas is a common phenomenon predicted under climate change [START_REF] Thomas | Birds extend their ranges northward[END_REF]Lennon 1999, Parmesan 2006 and references therein). However, predicted shifts suggest a reduction of habitat suitability in some areas (e.g. North Africa) and range extensions in others (e.g. Northern Central Europe). Our current models confirm detected and predicted range extensions in the Iberian Peninsula [START_REF] Reino | Using survival regression to study patterns of expansion of invasive species: will the common waxbill expand with global warming?[END_REF]. However, for central Spain our future projections rather suggested less suitable future conditions underlining the complexity of observed patterns. Interpretation of distributional change in the tropics seems to be even more difficult. While our models predict an increased climate suitability in parts of South Africa, the distributional gap in the Congo Basin may also grow. Suitability inside today"s tropical rain forest areas might be reduced in the invaded range (e.g. Amazonia), but results for both models are not without contradiction (see below). Predictions of range changes due to microhabitat availability were not part of this analysis. Dealing with a species living in open areas, ongoing deforestation in tropical areas also needs to be considered explaining range shifts on a smaller scale [START_REF] Pearson | Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?[END_REF].

When predicting the future, many uncertainties arise in addition to the well known biological uncertainties and those related to the SDMs. Climatic incertitudes include the unknown development of greenhouse gas emission, all issues related to the climate models and the downscaling of data and the resulting future climatic scenario [START_REF] Beaumont | Predicting species distributions: use of climatic parameters in BIOCLIM and its impact on predictions of species" current and future distributions[END_REF]. We dealt with this problem by using two different kinds of climate models and two different emission scenarios. However, given the current state of knowledge, our predictions are necessarily preliminary, and we agree with [START_REF] Beaumont | Predicting species distributions: use of climatic parameters in BIOCLIM and its impact on predictions of species" current and future distributions[END_REF] that repeated analysis with most recent data is warranted.

Comparison of modelling approaches

Both models NAT and NAT+INV were able to predict the current distribution of the common waxbill quite well. However, differences also became evident. AUC values were higher for the NAT model, but balancing up on this statistical measurement alone is certainly unsatisfying as stated above. Additionally, the native range shows fewer commission errors and is thus better reflected by the NAT model. However, this could be caused by a reduced number of records located in the native range used for the NAT+INV model as we use equal total sample sizes in both models. Furthermore, higher commission errors in the NAT+INV model are not unexpected because the species may not have reached all suitable habitat yet making an increased rate of false positives likely. In the South American part of the invasive range the NAT+INV model shows fewer commission errors compared to the expert map. Therefore, rating of both models is not straight forward. Interestingly, differences between both models become more obvious considering the future potential native range (e.g. Fig. 6a and 6c / A2a conditions) further underlining the influence of location selection.

When applying SDMs on invasive species, the fundamental niche is possibly not sufficiently represented within the native range so that the true dimensions of the climatic niche could be hidden due to e.g. dispersal limitations and/or climatic interactions (e.g. [START_REF] Pearson | Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?[END_REF]. Another possibility within the "realized niche dilemma" [START_REF] Gallien | Predicting potential distributions of invasive species: where to go from here?[END_REF] is the occurrence of a true evolutionary niche shift of an invasive population (Broennimann et al. 2007, Rödder andLötters 2009).

Evolutionary niche shift in invasive populations compared to native ones have been recently shown between populations of some species [START_REF] Fitzpatrick | The biogeography of prediction error: why does the introduced range of the fire ant over-predict its native range?[END_REF][START_REF] Broennimann | Evidence of climatic niche shift during biological invasion[END_REF]). Yet, our PCA-LDA does not suggest any niche shift between native and invasive populations. Instead of that, within the invasive range only a rather small fraction of the climate space present in the native range is represented. This could be caused by the fact that the species is still under expansion and thus has not covered the whole range yet [START_REF] Gallien | Predicting potential distributions of invasive species: where to go from here?[END_REF].

Alternatively, invasive populations truly have a smaller climate niche than the native ones, possibly based on founder effects or subspecific differences (see above). Both explanations are not mutually exclusive.

In conclusion, even in the absence of niche shifts between invasive and native ranges of a species the choice of occurrences from one or both areas influences the potential present and future distribution. Tentatively, our results indicate that for the common waxbill the SDM developed with data from the native range only provides more reliable predictions than by omitting the potential bias due to incomplete niche filling. Hence, we call for care when selecting species records from native and invaded ranges for modelling purposes of an invasive species and underline the importance of niche positions in ecological space.

Fig. 1 Fig. 3 aFig. 4 Fig. 5 Fig. 6

 13456 Fig. 1 Expert map of the current distribution of Estrilda astrild based on published references (e.g. Fry 2004, Lever 2005). Grey areas show the native range, crosshatched areas and arrows mark invasive occurrences

Fig. 7

 7 Fig. 7 Positions of native (squares) and invasive (triangles) presence locations of Estrilda astrild in ecological space represented by two Principal components (PC1 & PC2). Background samples are shown behind the presence locations as semi transparent point cloud for invasive and native ranges respectively (see electronic appendix for a coloured plate).

  The scenarios are described in detail in the "Special Report on Emissions Scenarios" by the Hijmans and can be obtained from http://www.worldclim.org (last access 10.08.2010). MAXENT ASCII-outputs were imported into DIVA-GIS, and species presence is presented for two different thresholds: the 10 percentile training presence logistic threshold and the minimum training presence logistic threshold. Both are nonfixed thresholds, as recommended by[START_REF] Liu | Selecting thresholds of occurrence in the prediction of species distributions[END_REF], which provide minimum requirements for the species climate preferences. Variable response was estimated using the implemented jackknife approach of MAXENT (e.g.Yost et al. 2009). Area

	Climate envelope modelling
	We chose MAXENT v.3.3.3a (Phillips et al. 2004, Phillips et al. 2006, available
	through http://www.cs.princeton.edu/~schapire/maxent/), a machine learning program
	which uses environmental variables as predictors, for species distribution modelling calculations of global potential distribution were performed with ArcMap 9.1 (ESRI,
	(SDM). MAXENT has frequently outperformed other competing algorithms (Elith Redlands, California).
	2006, Heikkinnen 2006), in particular, when the number of data points was limited
	(Hernandez 2006, Wisz et al. 2008). For model evaluation we use the area under the
	receiver operation characteristic curve (AUC), which is generated by MAXENT for
	Ideally, random background points, which are automatically selected by
	MAXENT, should reflect an area potentially colonisable by the target species (Phillips
	et al. 2009). Therefore, we restricted the spatial extent of the background records to
	Intergovernmental an area encompassing largely the African continent and thus the complete native Panel on Climate Change (IPCC,
	http://www.grida.no/publications/other/ipcc_sr/, last access 10.08.2010). In general, range in model (1), and to the transatlantic range including Africa, the Atlantic islands
	scenarios belonging to the A2 family assume higher CO 2 concentrations as well as and huge parts of South America east of the Andes in model (2). Subsequently,
	higher surface temperatures for the end of the century than assumed under B2 averages of both models were projected on a global scale onto current climatic
	scenarios. In order to deal with uncertainties that are prone to every single climate conditions and the future climate change scenarios. In order to reduce model

model, we use two currently available climate model outputs (CSIRO, CCCMA). Final distribution maps are based on average values of both models respectively representing one family of emission scenario. Original data were downscaled by R. J. each run derived from ten random splits of the species records (70% / 30% test). The results were summarized as average of the ten models. We are aware that AUC values have been criticized recently (e.g. by

[START_REF] Lobo | AUC: a misleading measure of the performance of predictive distribution models[END_REF]

), but given the general problems with different model evaluation approaches (see examples in Baldwin

2009

) and the ongoing wide use of AUC values in ecological studies, we only call for caution if relying on them alone. For common waxbills, descriptions of the current range are broadly available from the literature, and visual inspection of the maps might help interpreting model outputs.

We followed two different modelling approaches: (1) models trained with species records from the native range only (termed NAT in the following), or (2) with records from both native and invaded ranges (termed NAT+INV). All runs were conducted using the default settings of the program. uncertainty, we did not extrapolate into climates exceeding those conditions in the background regions. We chose the logistic output format, resulting in values between 0 and 1 for each grid cell, where higher values indicate more suitable climatic conditions.

Table 1

 1 Spatial extend of the potential distribution (in Million km 2 ) of Estrilda astrild derived from two different modelling approaches (NAT, NAT+INV, see running text for explanation) and applying two different thresholds (MIN = minimum training presence logistic threshold; 10% = 10% training presence logistic threshold, see running text for details) under current and predicted climate for the end of the 21 st century (A2a and B2a climate change scenarios, differing in green house gas emission).

		NAT		NAT+INV
		MIN	10%	MIN	10%
	Current Climate	47.73	23.04	51.92	16.70
	A2a 2080	34.36	14.47	37.66	08.21
	B2a 2080	39.62	16.96	43.38	10.12

Acknowledgements

We thank two anonymous referees for their comments on the manuscript. DR is grateful to the research initiative of the Ministry of Education, Science, Youth and Culture of the Rhineland-Palatinate state of Germany for financial support.


Lina Marie Hellström
email: lina.hellstrom@lnu.se

Åsa Bondesson

Peter Höglund

Patrik Midlöv

Lydia Holmdahl

Eva Rickhag

Tommy L M Eriksson

Hellström

Impact of the Lund Integrated Medicines Management (LIMM) model on medication appropriateness and drug-related hospital revisits

Keywords:

Purpose

To examine the impact of systematic medication reconciliations when admitted to hospital, and medication review while in hospital, on the number of inappropriate medications and unscheduled drug-related hospital revisits in elderly patients.

Methods

A prospective, controlled study in 210 patients, aged 65 years or older, who were admitted to one of three internal medicine wards at a University Hospital in Sweden. Patients received either standard care or care according to the Lund Integrated Medicines Management (LIMM) model. A multi-professional team, including a clinical pharmacist, provided medication reconciliations on admission and medication reviews during the hospital stay for the LIMM group. Blinded reviewers evaluated the appropriateness of the prescribing (using the Medication Appropriateness Index) on admission and discharge, and assessed the probability that a drug-related problem was the reason for any patient readmitted to hospital or visiting the emergency department within three months of discharge (using WHO causality criteria).

Results

There was a greater decrease in the number of inappropriate drugs in the intervention group than in the control group for both the intention-to-treat population (51% [95% CI 43-58%] versus 39% [95% CI 30-48%], p=0.0446) and the per-protocol population (60% [95% CI 51-67%] versus 44% [95% CI 34-52 %], p=0.0106). There were 6 revisits to hospital in the intervention group which were judged as "possibly, probably or certainly drug-related", compared with 12 in the control group (p=0.0469).

Conclusions

In this study, medication reconciliation and reviews provided by a clinical pharmacist in a multiprofessional team significantly reduced the number of inappropriate drugs and unscheduled drugrelated hospital revisits for elderly patients.

Introduction

Drug treatment is an important component of medical care for the elderly and has the potential to decrease morbidity and mortality and to increase quality of life. However, problems associated with drug treatment are frequent among elderly hospitalised patients [START_REF] Blix | The majority of hospitalised patients have drug-related problems: results from a prospective study in general hospitals[END_REF][START_REF] Krahenbuhl-Melcher | Drugrelated problems in hospitals: a review of the recent literature[END_REF] and, for some patients, it can be a drug-related problem that causes the hospital admission [START_REF] Van Der Hooft | Adverse drug reaction-related hospitalisations: a population-based cohort study[END_REF][START_REF] Pirmohamed | Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients[END_REF][START_REF] Mjorndal | Adverse drug reactions as a cause for admissions to a department of internal medicine[END_REF]. Many drug-related problems can be solved or prevented; it has been estimated that more than half of the drug-related admissions to hospital are preventable [START_REF] Howard | Investigation into the reasons for preventable drug related admissions to a medical admissions unit: observational study[END_REF]. A number of different underlying causes of drug-related hospital admissions have been identified; for example, clinically inappropriate drug regimens, lack of sufficient monitoring and follow-up, insufficient quality of information transfer between levels of care, and poor adherence to drug treatment among patients.

Given the complexity of the process leading to a drug-related hospital admission [START_REF] Howard | Investigation into the reasons for preventable drug related admissions to a medical admissions unit: observational study[END_REF][START_REF] Howard | Causes of preventable drug-related hospital admissions: a qualitative study[END_REF], it is likely that interventions for solving and preventing drug-related admissions and other negative consequences from drug therapy need to be multifaceted.

An integrated medicines management approach, involving input by clinical pharmacists at admission, during the hospital stay and at discharge, has been shown to be effective in reducing health care utilisation [START_REF] Scullin | An innovative approach to integrated medicines management[END_REF] and improving medication appropriateness [START_REF] Burnett | Effects of an integrated medicines management program on medication appropriateness in hospitalized patients[END_REF][START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF]. We have developed the Lund Integrated Medicines Management (LIMM) model, which describes a systematic approach to individualising and optimising drug treatment in elderly inpatients. A more detailed description of the LIMM model is presented in Table 1. Medicines management is defined as a concept that seeks to maximise health through the optimum use of medical drugs [START_REF] Simpson | What is medicines management and what is pharmaceutical care?[END_REF] and the term "integrated" indicates that different levels of care are involved, for example hospital and primary care. The model covers several aspects of the use of medications, from appropriate prescribing to the ways in which the drugs are taken or not taken by the patients [START_REF] Simpson | What is medicines management and what is pharmaceutical care?[END_REF]. Appropriate prescribing encompasses a range of values; three of the most important of these are the patient"s wants, the pharmaceutical/pharmacological qualities of the drug and the wellbeing of the general population [START_REF] Cribb | Prescribers, patients and policy: the limits of technique[END_REF]. The Medication Appropriateness Index (MAI) is a validated instrument for measuring the pharmacological and economic aspects of prescribing appropriateness; the criteria used in the MAI can be described as a combination of implicit (judgment-based) and explicit (criterion-based) [START_REF] Hanlon | A method for assessing drug therapy appropriateness[END_REF]. Results from an earlier study of the LIMM model showed positive effects on the appropriateness of drug therapy according to the MAI [START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF], but a larger controlled study was suggested to confirm the results and to study the effect on drug-related hospital admission levels.

The main objective of this study was to examine the impact of medication reconciliations when admitted to hospital and inpatient medication reviews, according to the LIMM model, on the number of inappropriate medications taken by elderly patients at discharge from hospital. The secondary objective was to examine the effect of LIMM-based patient care on the number of unscheduled drug-related hospital readmissions and emergency department visits within three months of hospital discharge.

Methods

Patients and setting

In this prospective controlled study, we compared patients receiving LIMM-based medication reconciliation and reviews (the intervention group) with patients receiving standard care (the control group). 2) had been prescribed at least one drug for regular use. Patients were excluded if they had been staying in the study wards during one of the previous inclusion dates. The regional Ethical Review Board did not consider an ethical approval to be necessary and had no objections to the study.

Multi-professional team intervention according to the LIMM model

During the intervention periods, clinical pharmacists conducted the medication reconciliation on admission of the patient to the ward and reviewed and monitored medication during the hospital stay according to the LIMM model. The admission medication reconciliation was performed on week-days, shortly after the patient had been admitted, using the LIMM Medication Interview Questionnaire parts 1-3 [START_REF] Bondesson | A structured questionnaire to assess patient compliance and beliefs about medicines taking into account the ordered categorical structure of data[END_REF] (Table 1). Firstly, the most accurate patient medication list was identified (part 1 of the medication interview questionnaire). The current medication list in the electronic medical record was compared with lists from other sources, including the patients and their close relations, drug lists from primary or community care, and the national computerised pharmacy dispensing register. On the basis of identified discrepancies, the pharmacist suggested changes to the current drug list in a face-to-face discussion with a ward physician. Secondly, patients who took responsibility for their own drug treatment at home were interviewed about other aspects of their drug use in part 2 of the interview (Table 1). Finally, if the patient was capable and willing to participate, in-depth questions concerning adherence to the drug regimen [START_REF] Morisky | Concurrent and predictive validity of a self-reported measure of medication adherence[END_REF] and beliefs about the medication [START_REF] Horne | The beliefs about medicines questionnaire: The development and evaluation of a new method for assessing the cognitive representation of medication[END_REF] were added to the interview (part 3). Any problems concerning the patient"s drug use emerging during the interview were addressed by the pharmacist by means of counselling and/or written information, including wardspecific drug information leaflets.

On week-days, before morning rounds, the pharmacists identified drug-related problems by conducting structured medication reviews, which addressed the following categories of risk: drugs that required therapeutic drug monitoring, less appropriate drug therapy, interchangeable drugs (according to a regional interchangeable list), problems with drug handling (e.g. swallowing, crushing, inhalation), drug interactions, type of drug or drug dose not adjusted according to liver/renal function, indication for drug treatment not known, natural remedy drugs, untreated indication and drugs causing adverse drug reactions. Information sources included the patient"s medication list, medical record notes, laboratory values and other relevant data. During ward rounds, the drug-related problems which the pharmacist considered to be the most relevant were discussed within the multiprofessional team (physicians, nurses, carers and paramedics). Patients were followed up at least twice a week to enable identification of new drug-related problems and to monitor previously identified problems. All data were documented on the LIMM Medication Review Form (Table 1).

Clinical pharmacists did not work in the wards during the standard care control periods and no formal medication reviews were undertaken. In some cases, informal medication reconciliation at admission was undertaken but there were no tools or instructions for this.

During both control and intervention periods, patients and primary or community care personnel received a Discharge Information Form which included a Medication Report describing changes in drug treatment during the hospital stay and a Medication List (Table 1). This discharge medication reconciliation was not part of the evaluation because control patients received identical information at discharge and the benefit of this procedure has already been demonstrated [START_REF] Midlov | Clinical outcomes from the use of Medication Report when elderly patients are discharged from hospital[END_REF][START_REF] Bergkvist | Improved quality in the hospital discharge summary reduces medication errors--LIMM: Landskrona Integrated Medicines Management[END_REF].

Data collection and outcome measures

The primary outcome measure was the change in the number of drugs with at least one inappropriate score (C) between admission and discharge, according to the MAI (see below). Secondary outcome measures included the number of patients revisiting the hospital because of a drug-related complaint within three months of discharge and MAI scores for each patient and drug at discharge.

Medication appropriateness index (MAI)

The 10 items that comprise the MAI are indication, drug effectiveness, correct dosage, correct directions, practical directions, drug-drug interactions, drug-disease interactions, drug duplication, duration of treatment and expense. Each drug was rated as appropriate (A), marginally appropriate (B) or inappropriate (C) for each of the 10 items [START_REF] Hanlon | A method for assessing drug therapy appropriateness[END_REF]. In the analysis, ratings for individual items were dichotomised as appropriate (A or B) versus inappropriate (C). A drug was categorised as inappropriate if it received a C for at least one of the ten MAI items. According to a weighting scheme, a summed MAI score of between 0 and 18 can be produced for each medication [START_REF] Samsa | A summated score for the medication appropriateness index: development and assessment of clinimetric properties including content validity[END_REF] and a patient MAI score can be calculated by summing the scores of all medications for each patient. The literature indicates that the overall inter-rater reliability of this index is moderate to very good and the overall intra-rater reliability is good to very good [START_REF] Hanlon | A method for assessing drug therapy appropriateness[END_REF][START_REF] Samsa | A summated score for the medication appropriateness index: development and assessment of clinimetric properties including content validity[END_REF][START_REF] Spinewine | Medication appropriateness index: reliability and recommendations for future use[END_REF][START_REF] Stuijt | Reliability of the medication appropriateness index in Dutch residential home[END_REF][START_REF] Kassam | Reliability of a modified medication appropriateness index in community pharmacies[END_REF]. The content validity has also been shown to be good [START_REF] Bergkvist | Improved quality in the hospital discharge summary reduces medication errors--LIMM: Landskrona Integrated Medicines Management[END_REF]. In some cases, however, the reliability of a few specific individual MAI items has been fair to poor [START_REF] Spinewine | Medication appropriateness index: reliability and recommendations for future use[END_REF]. Clinical judgment is needed to assess some items, although the rating process has been standardised by including explicit instructions on how to interpret each of the 10 items [START_REF] Hanlon | A method for assessing drug therapy appropriateness[END_REF].

The MAI assessments were done retrospectively by a research assistant (junior clinical pharmacist, MSc Pharm) who was not involved in the care of the patients and who had been trained in the use of the MAI by an experienced clinical pharmacist and researcher (Figure 2). The MAI was applied to drugs taken regularly; topical drugs, laxatives and drugs taken as needed were excluded. Patient data used in the MAI assessment of drugs at admission included the drug list at admission, laboratory and diagnostic test results, and medical record notes from admission and the first day in hospital. The research assistant was blinded with respect to group allocation.

The MAI assessments for drugs at discharge were performed in two steps for the intervention group (Figure 2) and one step for the control group. In step 1, the control and intervention patients were assessed using the drug list at discharge, the medical record notes during the hospital stay, the laboratory and diagnostic test results and the discharge summary. The research assistant performing the assessment was blinded with respect to group allocation. In step 2, the intervention patients were reassessed; patient information documented in the pharmacist"s Medication Review Form was made available to the reviewer and the MAI scores for drugs receiving an inappropriate rating in step 1 were re-evaluated based on this information. As medication review forms were only produced for intervention patients, the research assistant could not remain blinded to group allocation for this step. The step 2 assessment was performed because some information in the Medication Review Forms had not been documented in the patient"s medical record by the physicians, which could potentially have changed the MAI scores. Only the results from the first step of the discharge MAI assessment (the blinded evaluation) were used in the main analysis, as we wanted to avoid bias.

Drug-related hospital revisits

Data collected from the electronic medical records of patients who had an unscheduled readmission or visit to the emergency department at the Skåne University Hospital in Lund within three months of discharge were used as a basis for evaluation of the reason for the revisit to hospital. If a patient had several unscheduled revisits to hospital within three months, only data from the first contact were used.

In the reviewing process, we combined clinical judgment with the use of predetermined triggers, namely combinations of drugs and symptoms or certain "highalert" medications [START_REF] Van Der Hooft | Adverse drug reaction-related hospitalisations: a population-based cohort study[END_REF][START_REF] Pirmohamed | Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients[END_REF][START_REF] Mjorndal | Adverse drug reactions as a cause for admissions to a department of internal medicine[END_REF][START_REF]Indikatorer för utvärdering av kvaliteten i äldres läkemedelsterapi-Socialstyrelsens förslag[END_REF][START_REF]Institute for safe medication practices[END_REF]. As shown in Figure 2, the initial review, which was performed by a research assistant supported by an experienced clinical pharmacist, was followed by a final review by a multi-professional expert group of senior researchers and clinicians (one clinical pharmacist, one clinical pharmacologist, one consultant in internal medicine/geriatrics and one general practitioner). The initial reviewers were as inclusive as possible when choosing cases for further review; cases were classified as "potentially drug-related" and reviewed by the expert group if there was even the smallest suspicion of a drug-related revisit.

The expert group classified the type of drug-related problem as adverse drug reaction, therapeutic failure (including non-compliance, dose reduction/discontinuation, dose too low, drug interaction, inadequate therapeutic drug monitoring) or untreated indication. The cases were further classified by using the WHO criteria for causality [START_REF]The use of the WHO-UMC system for standardised case causality assessment[END_REF]; the causal relationship between the drug treatment and a symptom or diagnosis present at the hospital revisit was classified as "certain", "probable", "possible" or "unlikely". In addition, the contribution of the drug-related problem to the hospital revisit was assessed and classified as "dominant", "partly contributing", "less important" or "not contributing" [START_REF] Hallas | Drug related hospital admissions: the role of definitions and intensity of data collection, and the possibility of prevention[END_REF]. Drug-related problems associated with medications that had been newly initiated in the outpatient setting after discharge from hospital were excluded from the assessment, as we only wanted to evaluate the treatment that was a result of hospital care during the study. All reviewers in the initial and final reviews were blinded with respect to group allocation. In the statistical analysis, the hospital revisits were classified as drug-related only when "possible, "probable" or "certain" drug-related cases were also classified as the "dominant cause" for or "partly contributing" to the revisit.

Statistics

To assess the comparability of study groups at study inclusion, we used Student´s ttest, the Mann-Whitney test and Fisher´s exact test when appropriate. The difference in the number of drugs with inappropriate ratings was analysed by Poisson regression, with an offset equal to the natural logarithm of the number of drugs with an inappropriate rating at admission. Because the natural logarithm for zero does not exist, all zeros in the offset variable were set to 0.3. Our choice was based on comparisons of a number of values between 0.01 and 0.5, which showed that 0.3 gave the best fit of the model to the data. We also judged it to be an appropriate distance from 1. The Mann-Whitney test was used when comparing MAI scores between the intervention and control groups. For the MAI calculations, bootstrap 95% confidence intervals for the means were obtained by using the re-sampling technique [START_REF] Efron | An Introduction to the Bootstrap[END_REF]. The main analyses of the MAI results were performed according to the intention-to-treat principle, using the "baseline observation carried forward" for missing observations. A per-protocol analysis of patients who had received the complete intervention (both medication reconciliation and review) and who did not die in hospital was also carried out. The Chi squared test for trend was used to analyse drug-related revisits to hospital. The significance level in all analyses was set to 0.05. The R language and environment for statistical computing program (www.r-project.org) was used for the statistical analysis.

The power calculation performed for the primary objective was based on the results of a previous study of the LIMM model in 53 patients, which showed that the number of drugs with at least one inappropriate rating decreased by 33% in the intervention group and 7% in the control group [START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF]. We believed that it would be valuable to detect an even smaller difference between the groups and wanted to account for loss to follow-up; after performing a number of simulations, we therefore decided to include at least 100 patients in each group.

Results

Of the 232 patients eligible for inclusion, 210 were enrolled in the study (Figure 3).

Fifteen patients in the intervention group did not receive the complete intervention, due to short length of stay in hospital, no clinical pharmacist working at weekends, or closed wards due to infection outbreak among the patients. In addition, twelve intervention patients (including two who did not receive the complete intervention) and nine control patients died during the initial hospital stay. Eighty-four intervention patients and 92 control patients were therefore included in the per-protocol analysis.

Demographic data at admission to hospital (baseline) are shown in Table 2. Gender, age and number of drugs at admission were similar in both groups. The median (interquartile range) length of stay in hospital was 16 [START_REF] Burnett | Effects of an integrated medicines management program on medication appropriateness in hospitalized patients[END_REF][START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF][START_REF] Simpson | What is medicines management and what is pharmaceutical care?[END_REF][START_REF] Cribb | Prescribers, patients and policy: the limits of technique[END_REF][START_REF] Hanlon | A method for assessing drug therapy appropriateness[END_REF][START_REF] Bondesson | A structured questionnaire to assess patient compliance and beliefs about medicines taking into account the ordered categorical structure of data[END_REF][START_REF] Morisky | Concurrent and predictive validity of a self-reported measure of medication adherence[END_REF][START_REF] Horne | The beliefs about medicines questionnaire: The development and evaluation of a new method for assessing the cognitive representation of medication[END_REF][START_REF] Midlov | Clinical outcomes from the use of Medication Report when elderly patients are discharged from hospital[END_REF][START_REF] Bergkvist | Improved quality in the hospital discharge summary reduces medication errors--LIMM: Landskrona Integrated Medicines Management[END_REF][START_REF] Samsa | A summated score for the medication appropriateness index: development and assessment of clinimetric properties including content validity[END_REF][START_REF] Spinewine | Medication appropriateness index: reliability and recommendations for future use[END_REF][START_REF] Stuijt | Reliability of the medication appropriateness index in Dutch residential home[END_REF][START_REF] Kassam | Reliability of a modified medication appropriateness index in community pharmacies[END_REF][START_REF]Indikatorer för utvärdering av kvaliteten i äldres läkemedelsterapi-Socialstyrelsens förslag[END_REF][START_REF]Institute for safe medication practices[END_REF][START_REF]The use of the WHO-UMC system for standardised case causality assessment[END_REF][START_REF] Hallas | Drug related hospital admissions: the role of definitions and intensity of data collection, and the possibility of prevention[END_REF][START_REF] Efron | An Introduction to the Bootstrap[END_REF][START_REF] Spinewine | Effect of a collaborative approach on the quality of prescribing for geriatric inpatients: a randomized, controlled trial[END_REF] days in the intervention group and 13 [START_REF] Scullin | An innovative approach to integrated medicines management[END_REF][START_REF] Burnett | Effects of an integrated medicines management program on medication appropriateness in hospitalized patients[END_REF][START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF][START_REF] Simpson | What is medicines management and what is pharmaceutical care?[END_REF][START_REF] Cribb | Prescribers, patients and policy: the limits of technique[END_REF][START_REF] Hanlon | A method for assessing drug therapy appropriateness[END_REF][START_REF] Bondesson | A structured questionnaire to assess patient compliance and beliefs about medicines taking into account the ordered categorical structure of data[END_REF][START_REF] Morisky | Concurrent and predictive validity of a self-reported measure of medication adherence[END_REF][START_REF] Horne | The beliefs about medicines questionnaire: The development and evaluation of a new method for assessing the cognitive representation of medication[END_REF][START_REF] Midlov | Clinical outcomes from the use of Medication Report when elderly patients are discharged from hospital[END_REF][START_REF] Bergkvist | Improved quality in the hospital discharge summary reduces medication errors--LIMM: Landskrona Integrated Medicines Management[END_REF][START_REF] Samsa | A summated score for the medication appropriateness index: development and assessment of clinimetric properties including content validity[END_REF][START_REF] Spinewine | Medication appropriateness index: reliability and recommendations for future use[END_REF][START_REF] Stuijt | Reliability of the medication appropriateness index in Dutch residential home[END_REF] days in the control group (p=0.0905). A current medication list was identified for all 97 patients who received medication reconciliation (part 1 of the LIMM Medication Interview Questionnaire). In addition, 23 of these 97 patients were interviewed about knowledge of their medication and adherence to the drug regimen (part 2 of the questionnaire) and 17 of these 23 also completed the questionnaire concerning adherence to the drug regimen [START_REF] Morisky | Concurrent and predictive validity of a self-reported measure of medication adherence[END_REF] and the other on beliefs about medicines [START_REF] Horne | The beliefs about medicines questionnaire: The development and evaluation of a new method for assessing the cognitive representation of medication[END_REF] (part 3).

Medication Appropriateness Index

Drugs with at least one inappropriate rating

There was a greater decrease in the number of drugs with at least one inappropriate rating in the intervention group than in the control group (51% [95% CI 43-58%] versus 39% [95% CI 30-48%], p=0.0446), according to the intention-to-treat analysis of the MAI assessment, step 1. At discharge, 18.4% of the drugs for intervention patients and 21.9% of the drugs for controls were rated as inappropriate.

In the per-protocol analysis, the number of drugs with at least one inappropriate rating decreased by 60% (95% CI 51-67%) in the intervention group, compared with 44% (95% CI 34-52 %) in the control group (p=0.0106). At discharge, 15.1% of the drugs for the intervention group and 20.2% of the drugs for the control group were rated as inappropriate. The mean number of drugs with at least one inappropriate rating per patient, at admission and discharge, is shown in Table 3.

The mean number of inappropriate drugs changed between admission and discharge as a result of discontinuing inappropriate drugs, initiating inappropriate drugs, adjusting existing therapy to more appropriate therapy (for example, by changing the dose), or improving documentation (for example, stating the indication for a specific drug in the medical record). The number of inappropriate drugs that were discontinued, initiated or adjusted is shown in Table 4.

In the MAI assessment, step 2 (performed in the intervention group at discharge), 117 drugs for 62 patients (all drugs with at least one C rating, according to the MAI assessment, step 1) were assessed. The MAI rating was changed from a C to an A or B for 27 drugs in 19 patients. The average decrease per patient between step 1 and 2 in number of drugs with at least one C was 0.44 (95% CI 0.26-0.63).

MAI items

Table 5 shows that the MAI item "expense" received the most inappropriate ratings in both control and intervention patients, followed by "indication" and "duration". When the indication was rated as inappropriate, both expense and duration also received an inappropriate rating, according to the MAI instructions. In the intervention group, there were improvements in all MAI criteria except "effectiveness" and "correct directions" (Table 5). In the control group, there was an improvement for six of the ten criteria.

MAI scores

The average MAI scores per patient and per drug, at admission and discharge, are shown in Table 3. No significant differences between the control and intervention groups at discharge were found in the patient MAI score (intention-to-treat p = 0.553; per-protocol p = 0.421), or the MAI score per drug (intention-to-treat p = 0.543; perprotocol p = 0.329).

Drug-related revisits to the hospital

Within three months of discharge, 71 patients were readmitted (unscheduled admissions) to hospital and 15 visited the emergency department. Two patients (one intervention and one control) were excluded from the analysis, due to insufficient medical record data. There were 6 revisits to hospital with a causality assessment of possible, probable or certain in the intervention group compared with 12 in the control group (p=0.0469) (Table 6). Among the drug-related cases, 3 patients visited the emergency department without being admitted to hospital and 15 patients were admitted to a hospital ward.

In 5.6% of intervention patients (6 of 108) and 12.0% of control patients (12 of 100), the revisit to hospital was at least possibly drug related (p=0.138, Fisher"s exact test).

The absolute risk reduction for possibly drug-related revisits was 6.4% (95% CI: -1.2% to 14.1%). The cases where a drug-related problem was assessed as having a certain or probable relationship with the revisit to hospital are described in more detail in Table 7.

Discussion

The results of this study showed that medication reviews and medication reconciliation on admission to hospital, carried out according to the LIMM model, were associated with a significant decrease in the number of inappropriate drugs taken by elderly hospitalised patients. In agreement with these results, a previous study showed a reduction in the number of drugs with at least one inappropriate rating after implementation of the LIMM model [START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF]. A number of earlier controlled studies on pharmaceutical care, integrated medicines management or other collaborative approaches in hospitalised patients have also shown improvements in the appropriateness of medications (decrease in the MAI scores) [START_REF] Burnett | Effects of an integrated medicines management program on medication appropriateness in hospitalized patients[END_REF][START_REF] Spinewine | Effect of a collaborative approach on the quality of prescribing for geriatric inpatients: a randomized, controlled trial[END_REF][START_REF] Schmader | Effects of geriatric evaluation and management on adverse drug reactions and suboptimal prescribing in the frail elderly[END_REF].

In accordance with the previous study of the LIMM model [START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF], we regarded "the number of drugs with at least one inappropriate rating", to be the most suitable main outcome measure. This measure has also previously been used by others [START_REF] Spinewine | Medication appropriateness index: reliability and recommendations for future use[END_REF][START_REF] Spinewine | Effect of a collaborative approach on the quality of prescribing for geriatric inpatients: a randomized, controlled trial[END_REF]. By using that measure we could avoid summing or subtracting scores, which is generally not recommended when dealing with ordered categorical data (i.e. the MAI scores A, B and C) [START_REF] Altman | Practical statistics for medical research[END_REF]. Nonetheless, we have presented the MAI scores in this study in order to facilitate comparison with previous studies. In our study, the average patient MAI score in the intervention group at discharge was lower than that in most other studies (indicating more appropriate prescribing) [START_REF] Burnett | Effects of an integrated medicines management program on medication appropriateness in hospitalized patients[END_REF][START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF][START_REF] Spinewine | Effect of a collaborative approach on the quality of prescribing for geriatric inpatients: a randomized, controlled trial[END_REF][START_REF] Schmader | Effects of geriatric evaluation and management on adverse drug reactions and suboptimal prescribing in the frail elderly[END_REF]. However, because the control group also had a very low patient MAI score, there were no apparent differences between the groups. In two previous interventions with a similar lack of improvement in the MAI scores [START_REF] Schmader | Effects of geriatric evaluation and management on adverse drug reactions and suboptimal prescribing in the frail elderly[END_REF]31] neither the intervention nor the control group improved.

In our main analysis we used the most conservative parameters possible, i.e. MAI scores from the blinded assessment (step 1), results from the intention-to-treat population, and "baseline observation carried forward" for missing data. Despite this, the results still indicated a difference between the groups. When the per-protocol population and the nonblinded MAI assessment were analysed, the difference between the groups was larger, suggesting that the effect of the intervention may have been underestimated in the main analysis. The use of a blinded outcome assessment, as in our study and two other hospital-based MAI studies [START_REF] Schmader | Effects of geriatric evaluation and management on adverse drug reactions and suboptimal prescribing in the frail elderly[END_REF]31], strengthens the validity of the MAI ratings in comparison with those from other studies, which used reviewers who were not blind to group allocation [START_REF] Burnett | Effects of an integrated medicines management program on medication appropriateness in hospitalized patients[END_REF][START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF][START_REF] Spinewine | Effect of a collaborative approach on the quality of prescribing for geriatric inpatients: a randomized, controlled trial[END_REF].

The clinical consequences of a reduction in the number of inappropriate drugs are difficult to estimate, since the evidence for an association between inappropriate prescribing and adverse patient outcomes is mixed and contradictory [START_REF] Spinewine | Appropriate prescribing in elderly people: how well can it be measured and optimised?[END_REF]. However, the two published studies on the predictive validity of the MAI both indicate that this tool can reliably predict clinical patient outcomes [START_REF] Lund | Inappropriate prescribing predicts adverse drug events in older adults[END_REF][START_REF] Schmader | Inappropriate prescribing and health outcomes in elderly veteran outpatients[END_REF]. Lund et al. showed that inappropriate prescribing, according to a modified MAI score [START_REF] Lund | Inappropriate prescribing predicts adverse drug events in older adults[END_REF], is associated with adverse drug events in older men, and Schmader et al. demonstrated an association between worse MAI scores and poorer blood pressure control and use of more health services [START_REF] Schmader | Inappropriate prescribing and health outcomes in elderly veteran outpatients[END_REF].

Our study has some potential limitations. Firstly, the nonrandomised design could have introduced selection bias. Secondly, the study was undertaken solely in wards of internal medicine, limiting the generalisability of the results. With this in mind and to improve the generalisability, we developed a structured process for performing medication review and reconciliation, and used structured forms (i.e. checklists and questionnaires). Finally, instead of performing two or more independent outcome assessments for each patient, a single rater or a single group of raters assessed the patient data. We decided to use only one rater for the MAI assessments, as previous studies of MAI have shown a good or very good agreement within raters [START_REF] Hanlon | A method for assessing drug therapy appropriateness[END_REF][START_REF] Samsa | A summated score for the medication appropriateness index: development and assessment of clinimetric properties including content validity[END_REF][START_REF] Spinewine | Medication appropriateness index: reliability and recommendations for future use[END_REF][START_REF] Stuijt | Reliability of the medication appropriateness index in Dutch residential home[END_REF][START_REF] Kassam | Reliability of a modified medication appropriateness index in community pharmacies[END_REF] and the main purpose of this study was to quantify changes in MAI (where intra-rater agreement was more important [START_REF] Stuijt | Reliability of the medication appropriateness index in Dutch residential home[END_REF]). The group of reviewers evaluating the drugrelated revisits to hospital was chosen to provide varied backgrounds and expert knowledge in order to minimize the risk of misclassifying the revisits. In addition, they used checklists for detecting drug-related problems and two different explicit criteria to classify the cases.

In a number of cases, the comprehensiveness and quality of the documentation in the medical records affected the appropriateness of the medication. Adding information from the medication review forms led to a change in the MAI rating from "inappropriate" to "appropriate" for 23% of the drugs at discharge. We have already showed that communicating changes in the medication list, together with the reasons for these changes, to the patient and the next level of care decreases medication errors and the number of health care contacts [START_REF] Midlov | Clinical outcomes from the use of Medication Report when elderly patients are discharged from hospital[END_REF][START_REF] Bergkvist | Improved quality in the hospital discharge summary reduces medication errors--LIMM: Landskrona Integrated Medicines Management[END_REF]. We suggest that there is potential to improve the quality of prescribing even more if a broader range of issues concerning medication appropriateness and drug-related problems is documented and communicated to the next level of care in a structured way.

We found a significant reduction in the number of unscheduled drug-related revisits within three months of discharge from hospital. Similarly, a recent randomized controlled study of a comparable intervention, also in Sweden, showed a reduction in all revisits to hospital as well as in drug-related readmissions [START_REF] Gillespie | A comprehensive pharmacist intervention to reduce morbidity in patients 80 years or older: a randomized controlled trial[END_REF], and patients who received an integrated medicines management service in Northern Ireland benefited from a decreased rate of readmission and an increased time to readmission [START_REF] Scullin | An innovative approach to integrated medicines management[END_REF]. It is probable that the effect of the entire LIMM intervention (at admission, during the hospital stay and at discharge) on reduced need for medical care due to drug-related problems will approximate the sum of the effects of the discharge medication reconciliation (Discharge Information including a Medication Report and a Medication List) previously shown [START_REF] Midlov | Clinical outcomes from the use of Medication Report when elderly patients are discharged from hospital[END_REF] and the admission medication reconciliation and medication reviews as demonstrated in this study.

Our findings confirm the effect on medication appropriateness previously shown by Bergkvist et al. in a study of the entire LIMM model [START_REF] Bergkvist | A multi-intervention approach on drug therapy can lead to a more appropriate drug use in the elderly. LIMM-Landskrona Integrated Medicines Management[END_REF]. In contrast to that study, however, our study demonstrated a relatively large improvement in the number of inappropriate drugs from admission to discharge in both the control and intervention groups. The large improvement seen in the control group could be the result of an effect of the discharge medication reconciliation process on medication appropriateness, since this activity was implemented in both groups.

In conclusion, the results of this study indicate that medication reconciliation and reviews, according to the integrated medicines management model demonstrated here, can reduce the number of inappropriate drugs taken by elderly patients during a hospital stay and the number of subsequent unscheduled drug-related hospital visits. b Patients lost to follow-up died during the hospital stay. The total of 12 patients in the intervention group who died in hospital includes two who had also not received the complete intervention.

Figure legends

c One patient from each group was excluded from the analysis, due to insufficient medical record data.

Admission medication reconciliation

Clinical pharmacist LIMM Medication Interview Questionnaire, parts 1-3 [START_REF] Bondesson | A structured questionnaire to assess patient compliance and beliefs about medicines taking into account the ordered categorical structure of data[END_REF], according to medication, disease and patient characteristics: Part 1: identification of the most accurate medication list for the patient Part 2: addition of questions concerning the patient's practical handling and knowledge of the medications and adherence to the medical regimen Part 3: addition of more detailed questions concerning the patient's adherence to the medical regimen [START_REF] Morisky | Concurrent and predictive validity of a self-reported measure of medication adherence[END_REF] and beliefs about the medications [ The patient MAI score is the sum of the scores for all drugs for each patient. 6 Assessment of causality (using WHO criteria [START_REF]The use of the WHO-UMC system for standardised case causality assessment[END_REF]) and contribution (using Hallas' criteria [START_REF] Hallas | Drug related hospital admissions: the role of definitions and intensity of data collection, and the possibility of prevention[END_REF]) of drug-related problems to the hospital visit for all revisits to hospital. The WHO criteria for causality comprised: certain, probable, possible or unlikely. Hallas" criteria comprised: dominant, partly contributing, less important and not contributing.

  The intervention was implemented in three internal medicine wards(A, B and C) at Skåne University Hospital in Lund, Sweden, between January 2007 and March 2008 (Fig 1). The patients in all three wards received standard care until implementation of the LIMM intervention, which was started at different times in the respective wards (see Fig 1). All patients in wards A, B and C received the intervention after it had been implemented but the patients evaluated retrospectively for eligibility for inclusion in the study included only those who were staying in the study wards on November 1, 2006 (before the intervention), and March 1, 2007, November 1, 2007 and April 1, 2008 (about one month after implementation of the intervention in wards A, B and C, respectively). Patients were included if they: (1) were aged 65 years or older, and (

Fig. 1

 1 Fig. 1 The Lund Integrated Medicines Management (LIMM) model was implemented at different times on the three wards during the year 2007 to 2008. A sample of patients was collected retrospectively and assessed for eligibility. Dates for inclusion of study patients were chosen before and about one month after implementation of the intervention. We included 23 control patients and 55 intervention patients from ward A, 28 control and 36 intervention patients from ward B and 50 control and 18 intervention patients from ward C.

Fig. 2

 2 Fig. 2 Interventions during the hospital stay and evaluations made after hospital discharge in the intervention and control groups, respectively. MAI, Medication Appropriateness Index; DRP, Drug-Related Problem.

Fig. 3

 3 Fig. 3 Flow of patients through the study

Table 1

 1 The Lund Integrated Medicines Management (LIMM) model. The table summarises the activities performed in the hospital wards for each patient, the responsible professional groups, and the tools used to perform the activities

	When	How often	Activity	Responsibility	Tool
	At	Once for each
	admission	patient

  The quality control of discharge medication reconciliation was not performed for all patients. It can be done either before discharge, with immediate feedback to the physician, or retrospectively.

					16]
	During	At regular	Medication review and	Clinical	LIMM Medication Review Form
	hospital	intervals for	monitoring	pharmacist
	stay	each patient	Symptom assessment	Nurse (or clinical	LIMM Symptom Assessment Form
				pharmacist)
			Lead the team and organise a	Physician	Documented in the patient health record
			treatment plan based on the
			symptom assessment,
			medication review and
			reconciliation results
	At	Once for each	Discharge medication	Physician	LIMM Discharge Information Form, including a Medication Report and a
	discharge	patient	reconciliation		Medication List (a list of current drugs, doses and indications)
		Occasionally a	Quality control of discharge	Clinical	LIMM Quality Control form for Discharge Medication Reconciliation
			medication reconciliation	pharmacist

a

Table 2

 2 Characteristics of patients in the intervention and control groups at admission (baseline)

	Characteristic	Intervention group	Control group
		(n=109)	(n=101)
	Gender [no. (%)]
	Female	60 (55.0)	51 (50.5)
	Male	49 (45.0)	50 (49.5)
	Age in years [mean (SD)]	83.0 (7.0)	81.8 (7.4)
	No. of drugs in continuous use	8 (5-11)	7 (5-11)
	[median (IQR)]
	No. of drugs for use on demand	1 (1-3)	1 (1-3)
	[median (IQR)]
	IQR = interquartile range; SD = standard deviation.

Table 3

 3 Number of drugs with at least one inappropriate rating per patient according to the Medication Appropriateness Index (MAI), MAI score per patient and MAI score per drug at admission and discharge. Results from both the intention-to-treat (ITT) analysis (n=210) and the per-protocol (PP) analysis (n=176) are presented. Higher MAI scores indicate a higher level of inappropriateness. Figures are means (95% confidence intervals)

	Intervention group (ITT n=109; PP n=84)	Control group (ITT n=101; PP n=92)
	Admission		Discharge	Admission	Discharge
		Step 1 a	Step 2
	Number of drugs with at least one
	inappropriate rating
	ITT 3.0 (2.5-3.5)	1.5 (1.2-1.8)	1.2 (0.9-1.6)	2.8 (2.3-3.3)	1.7 (1.3-2.1)
	PP 2.9 (2.4-3.4)	1.2 (0.9-1.4)	0.8 (0.6-1.1)	2.7 (2.3-3.2)	1.6 (1.2-1.9)
	Patient MAI score b
	ITT 12.5 (10.1-15.0) 4.5 (3.2-6.2)	3.5 (2.3-5.1)	10.8 (8.9-13.1) 4.9 (3.6-6.4)
	PP 12.2 (9.7-14.9)	3.2 (2.3-4.2)	1.9 (1.4-2.6)	10.7 (8.7-13.0) 4.3 (3.1-5.5)
	MAI score per drug c
	ITT 1.5 (1.2-1.8)	0.5 (0.4-0.6)	0.4 (0.3-0.5)	1.3 (1.1-1.5)	0.5 (0.4-0.6)
	PP 1.5 (1.2-1.9)	0.4 (0.3-0.5)	0.2 (0.2-0.3)	1.3 (1.1-1.5)	0.5 (0.3-0.6)
	a In the analysis of the primary outcome (number of inappropriate drugs), the discharge MAI assessment step 1 data for the intervention group were compared with data for the
	control group.

b

Table 4

 4 Number of inappropriate drugs at admission and discharge and number (percent) of inappropriate drugs that were discontinued, adjusted or initiated during the hospital stay (intention-

	to-treat analysis)
		Intervention group	Control group
		(Admission: n=858 drugs	(Admission: n=783 drugs
		Discharge: n=868)	Discharge: n=785)
		Step 1	Step 2
	Number of inappropriate drugs	324	324	279
	at admission
	Discontinued a	69 (21)	69 (21)	48 (17)
	Therapy adjusted or	123 (38)	144 (44)	87 (31)
	documentation
	improved a
	Number of inappropriate drugs	160	133	172
	at discharge
	Initiated in hospital b	28 (18)	22 (17)	28 (16)

a Number (percent of the number of inappropriate drugs at admission) b Number (percent of the number of inappropriate drugs at discharge) Table

Table 7

 7 Types of drug-related problems covered were: adverse drug reaction, therapeutic failure (including non-compliance, dosereduction/discontinuation, too low dose, drug interaction, inadequate therapeutic drug monitoring) and untreated indication. Figures given indicate number of patients Details of patient cases where a drug-related problem was assessed as having a certain or probable relationship with the revisit to hospital

	Classification according to causality and contribution Intervention group	Control group (n=40)
		(n=44)
	Certain and dominant	0	1
	Probable and dominant or partly contributing	2	5
	Possible and dominant or partly contributing	4	6
	Unlikely or less important/not contributing	38	28

c The MAI score per drug is the sum of the scores for all drugs divided by the number of drugs evaluated.

Acknowledgement

We thank the pharmacists Tanja Lehtinen and Lily Esporlas for skilful help with the collection and evaluation of data. We would also like to thank the staff of the study wards and the clinical pharmacists at the Hospital pharmacy, Skåne University Hospital in Lund, Sweden.

The study was funded by Apoteket AB and the County of Skåne, Sweden.

Conflict of interest

The authors declare that they have no conflicts of interest.