Reading tea leaves worldwide: Decoupled drivers of initial litter decomposition mass-loss rate and stabilization.

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models.

General reversal of N-decomposition relationship during long-term decomposition in boreal and temperate forests.

Decomposition of dead organic matter is fundamental to carbon (C) and nutrient cycling in terrestrial ecosystems, influencing C fluxes from the biosphere to the atmosphere. Theory predicts and evidence strongly supports that the availability of nitrogen (N) limits litter decomposition. Positive relationships between substrate N concentrations and decomposition have been embedded into ecosystem models. This decomposition paradigm, however, relies on data mostly from short-term studies analyzing controls on early-stage decomposition. We present evidence from three independent long-term decomposition investigations demonstrating that the positive N-decomposition relationship is reversed and becomes negative during later stages of decomposition. First, in a 10-y decomposition experiment across 62 woody species in a temperate forest, leaf litter with higher N concentrations exhibited faster initial decomposition rates but ended up a larger recalcitrant fraction decomposing at a near-zero rate. Second, in a 5-y N-enrichment experiment of two tree species, leaves with experimentally enriched N concentrations had faster decomposition initial rates but ultimately accumulated large slowly decomposing fractions. Measures of amino sugars on harvested litter in two experiments indicated that greater accumulation of microbial residues in N-rich substrates likely contributed to larger slowly decomposing fractions. Finally, a database of 437 measurements from 120 species in 45 boreal and temperate forest sites confirmed that higher N concentrations were associated with a larger slowly decomposing fraction. These results challenge the current treatment of interactions between N and decomposition in many ecosystems and Earth system models and suggest that even the best-supported short-term controls of biogeochemical processes might not predict long-term controls.

Exchangeable manganese regulates carbon storage in the humus layer of the boreal forest.

The huge carbon stock in humus layers of the boreal forest plays a critical role in the global carbon cycle. However, there remains uncertainty about the factors that regulate below-ground carbon sequestration in this region. Notably, based on evidence from two independent but complementary methods, we identified that exchangeable manganese is a critical factor regulating carbon accumulation in boreal forests across both regional scales and the entire boreal latitudinal range. Moreover, in a novel fertilization experiment, manganese addition reduced soil carbon stocks, but only after 4 y of additions. Our results highlight an underappreciated mechanism influencing the humus carbon pool of boreal forests.

Impact of Set-Day Clinic on Physician Continuity in a Family Medicine Residency Clinic.

BACKGROUND AND OBJECTIVES: Continuity of care between patients and their primary care providers is associated with improved patient outcomes and experience, decreased health care costs, and improved provider well-being. Strategies to enhance continuity of care in residency programs involve electronic health record, scheduling, and panel management methods. Our study compared physician-patient continuity rates (pre and post) for one family medicine residency's implementation of a set-day clinic (SDC) scheduling model. METHODS: In July 2019, Bethesda Clinic switched from a rotation-driven scheduling (RDS) model to SDC. Physicians were divided into two scheduling groups: Monday, Thursday, or Friday; or Tuesday, Wednesday, or Friday. We used visit data from two 6-month periods, October 2018 to March 2019 (RDS) and October 2021 to March 2022 (SDC), to calculate continuity using the continuity for physician formula. We used t tests to compare mean continuity rates between the RDS and SDC periods. In June 2022, faculty and residents were emailed a nine-question survey about SDC. RESULTS: Adherence to the SDC model ranged from 65% to 76%. Postgraduate year (PGY) 3 residents' continuity increased significantly (P<.001) from 44% (RDS) to 56% (SDC), while PGY2 residents' continuity increased, nonsignificantly, from 38% to 43%. Among those that completed the survey, 94% of residents and 78% of faculty were in favor of SDC. CONCLUSIONS: We demonstrated that SDC is feasible and well received by residents and faculty alike. Continuity was highest for PGY2 and PGY3 residents during the SDC period. Predictable clinic schedules have the potential to improve continuity in family medicine residency clinics and may improve physician well-being.

Predominant contributions through lichen and fine litter to litterfall mercury deposition in a subalpine forest.

Litterfall, typically referring to needles/leaves, may stand for >50% of the total mercury (Hg) deposition in forest ecosystems. By detailed categorisation, we reveal for the first time that the contributions through lichens and fine litter, together 9.98 µg Hg m-2 yr-1, could be as high as that in needle litter (9.96 µg m-2 yr-1) to the annual total Hg deposition (44.6 µg m-2 yr-1) in a subalpine forest in Switzerland. Noticeably, needle litter had the highest contribution (53%) to total Hg in the autumn litterfall but lichens and fine litter together predominated in other seasons (47-59%). Such a seasonal pattern is caused by the high ability of lichens and fine litter to accumulate Hg and the high needle litterfall in autumn, which is related to a good rainfall in summer followed by a dry period in autumn. The constantly higher Hg levels in lichens and fine litter than in needle litter together with similar seasonal patterns of litterfall during 2009-2019 and rainfall during 1980-2019 suggest that our finding can be generally valid. Here, we highlight not only the considerable role of non-needle litterfall in Hg deposition but also the association with weather for seasonal Hg dynamics in different litterfall components.

Modeling Family Medicine Provider Care Team Design to Improve Patient Care Continuity.

BACKGROUND AND OBJECTIVES: Continuity of care is an integral aspect of high-quality patient care in primary care settings. In the Department of Family Medicine at Mayo Clinic, providers have multiple responsibilities in addition to clinical duties or panel management time (PMT). These competing time demands limit providers' clinical availability. One way to mitigate the impact on patient access and care continuity is to create provider care teams to collectively share the responsibility of meeting patients' needs. METHODS: This study presents a descriptive characterization of patient care continuity based on provider types and PMT. Care continuity was measured by the percentage of patient a ppointments s een by a provider in their o wn c are t eam (ASOCT) with the aim of reducing the variability of provider care team continuity. The prediction method is iteratively developed to illustrate the importance of the individual independent components. An optimization model is then used to determine optimal provider mix in a team. RESULTS: The ASOCT percentage in current practice among care teams ranges from 46% to 68% and the per team number of MDs varies from 1 to 5 while the number of nurse practitioners and physician assistants (NP/PAs) ranges from 0 to 6. The proposed methods result in the optimal provider assignment, which has an ASOCT percentage consistently at 62% for all care teams and 3 or 4 physicians (MDs) and NP/PAs in each care team. CONCLUSIONS: The predictive model combined with assignment optimization generates a more consistent ASOCT percentage, provider mix, and provider count for each care team.

Balancing Clinician Workload Through Strategic Patient Panel Designs.

BACKGROUND AND OBJECTIVES: Clinician workload is a key contributor to burnout and well-being as well as overtime and staff shortages, particularly in the primary care setting. Appointment volume is primarily driven by the size of patient panels assigned to clinicians. Thus, finding the most appropriate panel size for each clinician is essential to optimization of patient care. METHODS: One year of appointment and panel data from the Department of Family Medicine were used to model the optimal panel size. The data consisted of 82 881 patients and 105 clinicians. This optimization-based modeling approach determines the panel size that maximizes clinician capacity while distributing heterogeneous appointment types among clinician groups with respect to their panel management time (PMT), which is the percent of clinic work. RESULTS: The differences between consecutive PMT physician groups in total annual appointment volumes per clinician for the current practice range from 176 to 348. The optimization-based approach for the same PMT physician group results in having a range from 211 to 232 appointments, a relative reduction in variability of 88%. Similar workload balance gains are also observed for advanced practice clinicians and resident groups. These results show that the proposed approach significantly improves both patient and appointment workloads distributed among clinician groups. CONCLUSION: Appropriate panel size has valuable implications for clinician well-being, patients' timely access to care, clinic and health system productivity, and the quality of care delivered. Results demonstrate substantial improvements with respect to balancing appointment workload across clinician types through strategic use of an optimization-based approach.

Coordination of Intraoperative Neurophysiologic Monitoring Technologist and Surgery Schedules.

Resource coordination in surgical scheduling remains challenging in health care delivery systems. This is especially the case in highly-specialized settings such as coordinating Intraoperative Neurophysiologic Monitoring (IONM) resources. Inefficient coordination yields higher costs, limited access to care, and creates constraints to surgical quality and outcomes. To maximize utilization of IONM resources, optimization-based algorithms are proposed to effectively schedule IONM surgical cases and technologists and evaluate staffing needs. Data with 10 days of case volumes, their surgery durations, and technologist staffing was used to demonstrate method effectiveness. An iterative optimization-based model that determines both optimal surgery and technologist start time (operational scenario 4) was built in an Excel spreadsheet along with Excel's Solver settings. It was compared with current practice (operational scenario 1) and optimization solution on only surgery start time (operational scenario 2) or technologist start time (operational scenario 3). Comparisons are made with respect to technologist overtime and under-utilization time. The results conclude that scenario 4 significantly reduces overtime by 74% and under-utilization time by 86% as well as technologist needs by 10%. For practices that do not have flexibility to alter surgeon preference on surgery start time or IONM technologist staffing levels, both scenarios 2 and 3 also result in substantial reductions in technologist overtime and under-utilization. Moreover, IONM technologist staffing options are discussed to accommodate technologist preferences and set constraints for surgical case scheduling. All optimization-based approaches presented in this paper are able to improve utilization of IONM resources and ultimately improve the coordination and efficiency of highly-specialized resources.

Mitigating Nonattendance Using Clinic-Resourced Incentives Can Be Mutually Beneficial: A Contingency Management-Inspired Partially Observable Markov Decision Process Model.

OBJECTIVES: Nonattendance of appointments in outpatient clinics results in many adverse effects including inefficient use of valuable resources, wasted capacity, increased delays, and gaps in patient care. This research presents a modeling framework for designing positive incentives aimed at decreasing patient nonattendance. METHODS: We develop a partially observable Markov decision process (POMDP) model to identify optimal adaptive reinforcement schedules with which financial incentives are disbursed. The POMDP model is conceptually motivated based on contingency management evidence and practices. We compare the expected net profit and trade-offs for a clinic using data from the literature for a base case and the optimal positive incentive design resulting from the POMDP model. To accommodate a less technical audience, we summarize guidelines for reinforcement schedules from a simplified Markov decision process model. RESULTS: The results of the POMDP model show that a clinic can increase its net profit per recurrent patient while simultaneously increasing patient attendance. An increase in net profit of 6.10% was observed compared with a policy with no positive incentive implemented. Underlying this net profit increase is a favorable trade-off for a clinic in investing in a targeted contingency management-based positive incentive structure and an increase in patient attendance rates. CONCLUSIONS: Through a strategic positive incentive design, the POMDP model results show that principles from contingency management can support decreasing nonattendance rates and improving outpatient clinic efficiency of its appointment capacity, and improved clinic efficiency can offset the costs of contingency management.

Return to work after deceased donor kidney transplant under the kidney allocation system.

BACKGROUND: The Kidney Allocation System (KAS) includes a scoring system to match transplant candidate life expectancy with expected longevity of the donor kidney, and a backdating policy that gives waitlist time credit to patients waitlisted after starting dialysis treatment (post-dialysis). We estimated the effect of the KAS on employment among patient subgroups targeted by the policy. METHODS: We used a sample selection model to compare employment after transplant before and after KAS implementation among patients on the kidney-only transplant waitlist between December 4, 2011 and December 31, 2017. RESULTS: Post-dialysis transplant recipients aged 18-49 were significantly more likely to be employed 1-year post transplant in the post-KAS era compared to the pre-KAS era. Transplant recipients aged 35-64 with no dialysis treatment were significantly less likely to be employed 1 year after transplant in the post-KAS era compared to the pre-KAS era. CONCLUSIONS: This study provides the first assessment of employment after DDKT under the KAS and provides important information about both the methods used to measure employment after transplant and the outcome under the KAS. Changes in employment after DDKT among various patient subgroups have important implications for assessing long-term patient and societal effects of the KAS and organ allocation policy.

An Algorithm for Pairing Interventionalists and Surgeons for the TAVR Procedure.

The Transcatheter Aortic Valve Replacement (TAVR) procedure requires an initial consultation and a subsequent procedure by an interventionalist (IC) and surgeon. The IC-surgeon pair coordination is extremely challenging, especially at Mayo Clinic due to provider time commitments distributed across practice, research, and education activities. Current practice aims to establish the coordination manually, resulting in a scheduling process that is cumbersome and time consuming for the schedulers. We develop an algorithm for pairing ICs and surgeons that minimizes the lead time (days elapsed between the clinic consult and procedure). As compared to current practice, this algorithm is able to reduce average lead time by 59% and increase possible IC-surgeon pairs by 7%. The proposed algorithm is shown to be flexible enough to incorporate practice variations such as lead time upper bound and two procedure days for a single consult day. Algorithm alternatives are also presented for practices who may find the proposed algorithm infeasible for their practice.

Major, trace and rare earth elements dynamics in decomposing litters on successional sites in a cool temperate region of South Korea.

Evaluating the decomposition-based change dynamics of various elements in plant litter is important for improving our understanding about their biogeochemical cycling in ecosystems. We have studied the concentrations of major, trace, and rare earth elements (REEs) (34 elements) in green tissue litter, and soil and their dynamics in the decomposing litters of successional annual fleabane (Erigeron annuus) and silvergrass (Miscanthus sinensis). Concentrations of major and trace elements in the litter of annual fleabane were 1.02-2.71 times higher compared to silvergrass. For REEs the difference between the two litter types for elements studied was in the range of 1.02-1.29 times. Both the litters showed a general decrease in the concentrations of elements in the initial stages of decomposition (60-90 days). All the major and trace elements (except for Na) in silvergrass showed a net increase in concentration at the end of the decomposition study (48.9-52.5% accumulated mass loss). Contrastingly, a few trace elements (Mn, Mo, Sr, Zn, Sb, and Cd) in annual fleabane showed a net decrease in their concentrations. For REEs, there was an increase in concentrations as well as in net amounts in both litter types. Similarities observed in the dynamics together with high and significant correlations among them likely suggest their common source. The higher concentrations of REEs in soil likely suggest its role in the net increase in REEs' concentrations and amount in litter during decomposition.

A Method for Balancing Provider Schedules in Outpatient Specialty Clinics.

Background. Variability in outpatient specialty clinic schedules contributes to numerous adverse effects including chaotic clinic settings, provider burnout, increased patient waiting times, and inefficient use of resources. This research measures the benefit of balancing provider schedules in an outpatient specialty clinic. Design. We developed a constrained optimization model to minimize the variability in provider schedules in an outpatient specialty clinic. Schedule variability was defined as the variance in the number of providers scheduled for clinic during each hour the clinic is open. We compared the variance in the number of providers scheduled per hour resulting from the constrained optimization schedule with the actual schedule for three reference scenarios used in practice at M Health Fairview's Clinics and Surgery Center as a case study. Results. Compared to the actual schedules, use of constrained optimization modeling reduced the variance in the number of providers scheduled per hour by 92% (1.70-0.14), 88% (1.98-0.24), and 94% (1.98-0.12). When compared with the reference scenarios, the total, and per provider, assigned clinic hours remained the same. Use of constrained optimization modeling also reduced the maximum number of providers scheduled during each of the actual schedules for each of the reference scenarios. The constrained optimization schedules utilized 100% of the available clinic time compared to the reference scenario schedules where providers were scheduled during 87%, 92%, and 82% of the open clinic time, respectively. Limitations. The scheduling model's use requires a centralized provider scheduling process in the clinic. Conclusions. Constrained optimization can help balance provider schedules in outpatient specialty clinics, thereby reducing the risk of negative effects associated with highly variable clinic settings.

Provider Scheduling to Maximize Patient Access.

INTRODUCTION: We describe and demonstrate an efficient method for assigning clinic days to urology providers in academic and large urology group practices given their numerous scheduling constraints including evaluation and management visits, office or operating room procedures/surgeries, teaching, trainee mentorship, committee work and outreach activities. METHODS: We propose an integer programming model for scheduling providers for clinic shifts in order to maximize patient access to appointments considering the aforementioned scheduling constraints. We present results for a case study with an academic urology clinic and lessons learned from implementing the model generated schedule. RESULTS: The integer programming model produced a feasible schedule that was implemented after pairwise and 3-way switches among attending providers to account for preferences. The optimized schedule had reduced variability in the number of providers scheduled per shift (standard deviation 1.409 vs 0.999, p=0.01). While other confounding factors are possible we noted a significant increase in the number of encounters after implementing changes from the model (1,370 vs 1,196 encounters, p=0.011). CONCLUSIONS: Optimization models offer an efficient and transferable method of generating a clinic template for providers that takes into account other clinical and academic responsibilities, and can increase the number of appointments for patients. Optimization of schedules may be performed periodically to address changes in providers or provider constraints.

Trends of major, minor and rare earth elements in decomposing litter in a cool temperate ecosystem, South Korea.

The decomposition dynamics of 34 different elements in four different litter types (foliar and woody litter) from Pinus densiflora (Korean red pine) and Castanea crenata (Korean chestnut) was investigated in a cool temperate ecosystem using the litterbag method. Two contrasting trends were observed in the dynamics of elements with accumulated mass loss of litter and carbon. Leaf litter of Korean chestnut, which was richer in elements, showed a general decrease in concentrations of elements with accumulated mass loss of litter and carbon on a dry mass basis during decomposition in the field. Other litter types, with initially lower concentrations of elements, exhibited an increase in concentration on a dry mass basis during field incubation. Highest relative increase in the concentration was noticed for the minor elements, and for the woody litters. Concentrations of major and minor elements increased by factors ranging from 1.07 for antimony (Sb) to 853.7 for vanadium (V). Rare earth elements (REE) concentrations increased by factors ranging from 1.04 for scandium (Sc) to 83.5 for thorium (Th). Our results suggest that litter type plays an important role for nutrient dynamics. Results from principal component analysis for major, minor, and rare earth elements showed grouping of elements and high correlation among them (P < 0.05), which suggests a common source. At both sites, element concentrations were high in the soil, especially for REE. This suggests that increase in element concentrations during field incubation probably was due to transfer of elements from soil to the overlying decomposing litter.

Improving Clinic Operational Efficiency and Utilization with RTLS.

New sources of operational data are leading to novel healthcare delivery system design and opportunities to support operational planning and decision-making. Technologies such as real time locating systems (RTLS) provide a unique view and understanding of how healthcare delivery settings behave and respond to operational design changes. In this paper RTLS data from an outpatient clinical setting is leveraged to identify the appropriate number of scheduled providers in order to improve the utilization of the clinical space while balancing the negative effects of clinic congestion. The approaches presented pair historical utilization rates for the clinical space with scheduled provider and patient volumes to support scheduling decisions in an operationally flexible clinic design. These historical data are augmented with clinic staff observation logs to identify target utilization rates as well as high congestion levels. Results are presented for two approaches: one where utilization of clinical space is a key performance metric and another where the decision-maker may be risk averse toward the use of provider time and use a probabilistic approach to determine provider staffing levels.

Contrasting dynamics and trait controls in first-order root compared with leaf litter decomposition.

Decomposition is a key component of the global carbon (C) cycle, yet current ecosystem C models do not adequately represent the contributions of plant roots and their mycorrhizae to this process. The understanding of decomposition dynamics and their control by traits is particularly limited for the most distal first-order roots. Here we followed decomposition of first-order roots and leaf litter from 35 woody plant species differing in mycorrhizal type over 6 years in a Chinese temperate forest. First-order roots decomposed more slowly (k = 0.11 ± 0.01 years-1) than did leaf litter (0.35 ± 0.02 years-1), losing only 35% of initial mass on average after 6 years of exposure in the field. In contrast to leaf litter, nonlignin root C chemistry (nonstructural carbohydrates, polyphenols) accounted for 82% of the large interspecific variation in first-order root decomposition. Leaf litter from ectomycorrhizal (EM) species decomposed more slowly than that from arbuscular mycorrhizal (AM) species, whereas first-order roots of EM species switched, after 2 years, from having slower to faster decomposition compared with those from AM species. The fundamentally different dynamics and control mechanisms of first-order root decomposition compared with those of leaf litter challenge current ecosystem C models, the recently suggested dichotomy between EM and AM plants, and the idea that common traits can predict decomposition across roots and leaves. Aspects of C chemistry unrelated to lignin or nitrogen, and not presently considered in decomposition models, controlled first-order root decomposition; thus, current paradigms of ecosystem C dynamics and model parameterization require revision.

Early stage litter decomposition across biomes.

Through litter decomposition enormous amounts of carbon is emitted to the atmosphere. Numerous large-scale decomposition experiments have been conducted focusing on this fundamental soil process in order to understand the controls on the terrestrial carbon transfer to the atmosphere. However, previous studies were mostly based on site-specific litter and methodologies, adding major uncertainty to syntheses, comparisons and meta-analyses across different experiments and sites. In the TeaComposition initiative, the potential litter decomposition is investigated by using standardized substrates (Rooibos and Green tea) for comparison of litter mass loss at 336 sites (ranging from -9 to +26 °C MAT and from 60 to 3113 mm MAP) across different ecosystems. In this study we tested the effect of climate (temperature and moisture), litter type and land-use on early stage decomposition (3 months) across nine biomes. We show that litter quality was the predominant controlling factor in early stage litter decomposition, which explained about 65% of the variability in litter decomposition at a global scale. The effect of climate, on the other hand, was not litter specific and explained <0.5% of the variation for Green tea and 5% for Rooibos tea, and was of significance only under unfavorable decomposition conditions (i.e. xeric versus mesic environments). When the data were aggregated at the biome scale, climate played a significant role on decomposition of both litter types (explaining 64% of the variation for Green tea and 72% for Rooibos tea). No significant effect of land-use on early stage litter decomposition was noted within the temperate biome. Our results indicate that multiple drivers are affecting early stage litter mass loss with litter quality being dominant. In order to be able to quantify the relative importance of the different drivers over time, long-term studies combined with experimental trials are needed.

Manganese availability is negatively associated with carbon storage in northern coniferous forest humus layers.

Carbon sequestration below ground depends on organic matter input and decomposition, but regulatory bottlenecks remain unclear. The relative importance of plant production, climate and edaphic factors has to be elucidated to better predict carbon storage in forests. In Swedish forest soil inventory data from across the entire boreal latitudinal range (n = 2378), the concentration of exchangeable manganese was singled out as the strongest predictor (R2 = 0.26) of carbon storage in the extensive organic horizon (mor layer), which accounts for one third of the total below ground carbon. In comparison, established ecosystem models applied on the same data have failed to predict carbon stocks (R2 < 0.05), and in our study manganese availability overshadowed both litter production and climatic factors. We also identified exchangeable potassium as an additional strong predictor, however strongly correlated with manganese. The negative correlation between manganese and carbon highlights the importance of Mn-peroxidases in oxidative decomposition of recalcitrant organic matter. The results support the idea that the fungus-driven decomposition could be a critical factor regulating humus carbon accumulation in boreal forests, as Mn-peroxidases are specifically produced by basidiomycetes.

Healthcare Burden and Costs Associated with Urinary Tract Infections in Type 2 Diabetes Mellitus Patients: An Analysis Based on a Large Sample of 456,586 German Patients.

OBJECTIVES: We examined the real-world treatment of urinary tract infections (UTIs) in a type 2 diabetes mellitus (T2DM) population, evaluated UTI-related healthcare resource use and direct treatment costs, and assessed factors that may predict UTI-related costs. METHODS: We analyzed an anonymized dataset from a regional German healthcare fund (2010-2012). UTI-associated resource use was described by the number of UTI-associated outpatient visits, the number and length of UTI-related acute hospital visits, and the number of UTI-related antibiotics prescriptions. UTI-related direct treatment costs were studied both based on these resource use numbers and, additionally, based on a comparison of all-cause annual healthcare costs of T2DM-patients who were or were not affected by a UTI. To identify factors that might predict direct treatment costs related to UTI treatment, we conducted generalized linear regression model analyses (based on gamma distribution) using sociodemographic and clinical characteristics of observed patients as available in the database as independent variables. RESULTS: A total of 456,586 T2DM-patients were included with a mean age of 73.8, a percentage of 56.3 female patients, and a mean Charlson comorbidity index of 7.3. In our database, we observed 48,337 UTI events. The direct mean resource-based costs were €315.90 per UTI event. Older age, higher comorbidity status, at least one previous non-UTI infection, and poorer renal function were associated with higher costs, while female gender and at least one previous UTI event were associated with lower costs. In the all-cause cost analysis, healthcare costs per patient year were €3,916 higher in the UTI group than in the non-UTI group. CONCLUSION: Our study confirms that UTI is a common complication in patients with T2DM. Patients with T2DM who have had previous infections, who are older, and who are male, as well as patients who have more comorbidities or severe renal insufficiency, face above-average UTI treatment costs. These patient groups, therefore, should receive special attention in the real-world treatment of T2DM, which should include a regular screening of UTI risk.