The impact of integrated care on health care utilization and costs in a socially deprived urban area in Germany: A difference-in-differences approach within an event-study framework.

We investigated the impact of an integrated care initiative in a socially deprived urban area in Germany. Using administrative data, we empirically assessed the causal effect of its two sub-interventions, which differed by the extent to which their instruments targeted the supply and demand side of healthcare provision. We addressed confounding using propensity score matching via the Super Learner machine learning algorithm. For our baseline model, we used a two-way fixed-effects difference-in-differences approach to identify causal effects. We then employed difference-in-differences analyses within an event-study framework to explore the heterogeneity of treatment effects over time, allowing us to disentangle the effects of the sub-interventions and improve causal interpretation and generalizability. The initiative led to a significant increase in hospital and emergency admissions and non-hospital outpatient visits, as well as inpatient, non-hospital outpatient, and total costs. Increased utilization may indicate that the intervention improved access to care or identified unmet need.

Complex community health and social care interventions - Which features lead to reductions in hospitalizations for ambulatory care sensitive conditions? A systematic literature review.

Preventing hospitalizations due to ambulatory care sensitive conditions (ACSCs) is traditionally the responsibility of primary care. The determinants of ACSC hospitalizations, however, are not purely medical, but also influenced by other factors like patients' social and personal circumstances. Interventions that include or consist entirely of community health services and social care could potentially reduce the ACSC hospitalization rate. Comparisons of the features of successful interventions of this nature, however, are still lacking. We therefore conducted a systematic review of the literature to identify out-of-hospital interventions that (a) included aspects or consisted entirely of community health services and social care and (b) analyzed the ACSC hospitalization rate as an outcome measure. We identified papers reporting the results of 32 interventions and extracted structural and behavioral features to determine which of these were shared by most or all of the successful interventions. We found that all of the successful interventions included a primary care physician and provided care management. Moreover, most of the successful interventions were characterized by a high degree of interconnectedness between professional groups and provided care within so-called health care homes. We also identified a set of care coordination activities that were implemented in most of the successful interventions. Policy makers may wish to consider adopting these features when designing interventions that aim to reduce the ACSC hospitalization rate.

What is the impact of introducing a non-clinical community health advice and navigation service on the demand for primary care in socially deprived areas? Evidence from an observational panel study with difference-in-differences design.

OBJECTIVES: To examine the effect of introducing a non-clinical community health advice and navigation service on the demand for primary care in a socially deprived area. DESIGN: Observational panel study with difference-in-differences design. We conducted fixed-effects negative binomial regressions to compare changes in the number of visits to general practitioners (GPs) in individuals who visited the health advice and navigation service and a matched control group of individuals who did not visit the service. In addition, we analysed the effects of visiting the service multiple times. SETTING AND PARTICIPANTS: Our empirical setting is a socially deprived urban area in Germany with a multicultural population of about 110 000 people. Our analyses are based on patient data (N=1044) from a non-clinical community health advice and navigation service and from two statutory health insurers. OUTCOME MEASURES: Patient demand for primary care measured as the number of visits to GPs before and after the first visit to the health advice and navigation service. RESULTS: Visiting the service for the first time significantly decreased the number of GP visits compared with the control group (ß=-0.113, p<0.1). Each additional visit to the service, however, significantly decreased the effect of the first visit (ß=0.037, p<0.05). CONCLUSIONS: Our findings suggest that non-clinical community health advice and navigation services can serve as a low-threshold first point of contact. As first point contact, such services might possibly reduce the burden of primary care physicians in socially deprived areas. At the same time, such services might function as a gateway to accessing the health system, reducing unmet care needs and stimulate demand. Ongoing counselling in the service can identify medical needs that require a physician visit. Our findings may be useful for policymakers and healthcare leaders seeking to reduce the demand on the primary care workforce and can stimulate further research in this area.

Eco-evolutionary dynamics of clonal multicellular life cycles.

The evolution of multicellular life cycles is a central process in the course of the emergence of multicellularity. The simplest multicellular life cycle is comprised of the growth of the propagule into a colony and its fragmentation to give rise to new propagules. The majority of theoretical models assume selection among life cycles to be driven by internal properties of multicellular groups, resulting in growth competition. At the same time, the influence of interactions between groups on the evolution of life cycles is rarely even considered. Here, we present a model of colonial life cycle evolution taking into account group interactions. Our work shows that the outcome of evolution could be coexistence between multiple life cycles or that the outcome may depend on the initial state of the population - scenarios impossible without group interactions. At the same time, we found that some results of these simpler models remain relevant: evolutionary stable strategies in our model are restricted to binary fragmentation - the same class of life cycles that contains all evolutionarily optimal life cycles in the model without interactions. Our results demonstrate that while models neglecting interactions can capture short-term dynamics, they fall short in predicting the population-scale picture of evolution.