Long-term care (LTC) facilities have shown remarkable high mortality during the coronavirus disease 2019 (Covid-19) outbreak in many countries. Several risk factors for Covid-19 mortality in LTC facilities have been previously identified. We used multiple variables covering facility characteristics (e.g., size, type of care provided, and preparedness) and socioeconomic factors related to the geographic location (e.g., household income, and incidence of Covid-19 in the surrounding population) to more precisely identify risk factors for Covid-19-related excess mortality (i.e., laboratory-proven, and clinically suspected Covid-19) as well as the overall excess mortality. In addition, we used clustering approaches to detect patterns in data sets and generate hypotheses regarding potential relationships between types of nursing homes and mortality trends. We retrospectively analysed mortality in 167 nursing homes that provide long-term care to 8,716 residents during the Covid-19 outbreak in Catalonia (North-East Spain) using nursing homes as the unit of analyses. Between March 1 and June 1, 2020, 1,629 deaths were reported in the investigated nursing homes, 1,089 (66.9%) of them Covid-19-related. According to the multiple regression analysis, both outcomes, Covid-19 related mortality and overall mortality, at the facility level were significantly associated with a higher percentage of patients with complex diseases, lower scores on pandemic preparedness measures and, higher population incidence of Covid-19 in the surrounding population. Consistently with these findings, when grouping nursing homes into eight clusters of common specific characteristics, we found higher mortality rates in the cluster with higher levels of residents with complex chronic conditions or advanced diseases, the cluster with higher levels of low scores on pandemic preparedness, the cluster of nursing homes located in rural areas, and also in the cluster of nursing homes with larger size. Our results provide policymakers and clinicians caring for residential populations with valuable information for prioritizing interventions in this setting in the advent of a Covid-19 outbreak.