Background Multimorbidity refers to the presence of two or more chronic conditions in a given individual. It is a growing issue posing a major challenge to healthcare systems around the world. Although studies are diverse in methodology and context, the prevalence of multimorbidity is increasing both in the general population and among people aged 40 years or more. Recent reviews reported a pooled prevalence of 42.4% in high-income countries (HICs), 43% in Latin America and Caribbean, and 36.4% in low-and middle-income countries (LMICs). The prevalence of multimorbidity increases substantially with age, socioeconomic deprivation and obesity. Living with multimorbidity is related to disability, lower quality of life, unplanned hospital admission, and premature mortality. On the other hand, management of people with multimorbidity is challenging in many ways. On one hand, patients with multimorbidity are heterogeneous in terms of the number of disease conditions, illness severity, personal priorities, and self-management skills. On the other hand, the current model of care and guidelines which were developed at a time when single-disease frameworks were predominant, tend to focus on diseases in isolation rather than the needs and circumstances of the person with complex care needs as a whole. Thirdly, there is no conclusive evidence on the best model of care to improve the health and well-being of individuals with multimorbidity across different contexts. Therefore, it is likely that patients with multimorbidity remain inadequately managed and suffer adverse consequences, including poor quality of life (QoL), poor disease progression, hospitalization and mortality. Despite the huge challenge multimorbidity brings, the research base on the magnitude of multimorbidity and the factors associated, the way the health system is organized to manage multimorbidity, the lived experience of patients with multimorbidity and important multimorbidity- related health outcomes such as quality of life, functionality, and survival over time is sparse in LMICs, including Ethiopia. Objectives This study aimed to investigate the magnitude, patterns and determinants of multimorbidity and its impacts on health-related quality of life (QoL), explore lived experience of individuals living with multimorbidity and the perspective of health professionals on the management of multimorbidity, and to investigate longitudinal outcomes of patients attending chronic outpatient medical care in Bahir Dar City, Ethiopia. Methods This study employed a mixed methods study design (cross-sectional quantitative survey, qualitative study, and longitudinal follow-up study). A randomly selected patients aged 40+ years having at least one NCD were recruited from a broad range of health facilities rendering chronic NCD care by medical doctors to determine the magnitude, patterns, associated factors, and impacts of multimorbidity on QoL. Two complementary methods (interview and review of medical records) were employed to collect data on socio-demographic, behavioral, and disease-related characteristics. The data were analyzed by STATA V.16 and R Software V.4.1.0. We fitted multivariable binary logistic regression and latent class analyses (LCA) models to identify the factors associated with multimorbidity and determine patterns of disease clustering, respectively. We also ran multinomial logistic regression to identify factors predicting latent class membership. Further, we fitted ordinal partial proportional odds model to assess the impact of multimorbidity on QoL. Statistical significance was considered at P-value <0.05. The QoL data scores were summarized into three ordered and non-overlapping categories as poor QoL (a scaled value <75), moderate QoL (scaled value from 75-89.9) and high QoL (scaled value from 90-100) and analysied by ordinal logistic regression with partial proportional odds (PPO) model. To explore lived experiences and perspectives on service delivery, we conducted a facility-based phenomenological study in three public and three private health facilities. Nineteen patient participants with two or more chronic NCDs and nine healthcare providers (six medical doctors and three nurses) were purposively selected and interviewed using semi-structured interview guides. This study employed a six-step inductive thematic network analysis approach to construct meaning and interpret experiences and perceptions of individual patients and service providers using NVivo V.12. For the 12 months longitudinal study, data at the end of the follow-up period were obtained from 1123 (78.5%) patients that were enrolled at baseline. Data on NCDs, QoL, and activation level (PA) were collected both at baseline and end line. Information on disease progression, the incidence of new NCDs, hospitalization, and mortality were obtained only at the end of the follow- up period. Data were analyzed by STATA V.16. Descriptive statistics and longitudinal panel data analyses were ran to describe the independent variables and identify factors predicting outcomes. Statistical significance was considered at P-value <0.05. Results A total of 1432 patients (98.4%) were enrolled for the quantitative study. The magnitude of individual chronic conditions ranged from 1.4% (cancer) to 37.9% (hypertension), and multimorbidity was identified in 54.8% (95% CI=52.2%-57.4%) of the sample. The likelihood of having multimorbidity was high among participants with advanced age and among those who were overweight or obese. The LCA model produced four patterns of multimorbidity: the cardiovascular, cardio-mental, metabolic, and respiratory groups. Advanced age, being overweight, and obesity predicted latent class membership for the cardiovascular and metabolic groups, adjusting for relevant confounding factors. Looking into the qualitative study, the thematic network analysis produced two main (global) themes, five organizing themes, and 21 sub-themes. Key problems experienced (organizing themes) include dependency, feeling rejected, psychological distress, poor medication adherence, and poor quality of care. Poor quality of life and compromised clinical outcomes were the main (global) themes constructed. Living with multimorbidity poses a huge burden on the physical, psychological, social, and sexual health of patients. In addition, patients with multimorbidity face financial hardship to access optimal multimorbidity care. On the other hand, the health system is not appropriately prepared to provide integrated, person-centered, and coordinated care for people living with multiple chronic conditions. The follow-up study revealed an increasing magnitude of multimorbidity from 54.8% at baseline to 56.8% by the end of the follow-up. About four percent (n=44) of patients were diagnosed with one or more new NCDs and those having multimorbidity at baseline were more likely than those without multimorbidity to develop new NCDs. In addition, 106 (9.4%) and 22 (2%) individuals, respectively were hospitalized and died during the follow-up period. Living with multimorbidity has also contributed to the increased rate of hospitalization and mortality. In the follow ups study, about one-third of the participants had higher quality of life (QoL), and those having a high activation status were more likely to be in the higher versus the combined moderate and QoL and the combined higher and moderate versus the lower level of QoL. Individual with higher activation levels were more likely than the lower activation group to experience better QoL. Conclusion The magnitude of multimorbidity in this study was high, and the most prevalent conditions shaped the patterns of multimorbidity. Advanced age, being overweight, and obesity were the factors correlated with multimorbidity. The risk of developing new NCDs and multimorbidity overtime was high. In addition, living with multimorbidity was associated with poor progress, hospitalization, mortality, and poor QoL. Poor QoL was also associated with lower activation levels. Further, multimorbidity is posing a huge challenge both to patients and the health system in the study area, and patients with multimorbidity have several unmet needs. However, there is a lack of personal, social, and health system readiness to account for the growing burden of multimorbidity. Recommendations There is a great need to furthering the knowledge base on the epidemiology and risk factors associated with multimorbidity and its impact on people with chronic conditions and the health systems in general. It is essential to understand trajectories of multimorbidity longitudinally and identify risk factors to design life-course preventive strategies. The social fabric and health system need to understand the individual capacities and needs of patients with multimorbidity and devise interventions to enhance their self-management skills and respond to their complex care needs. In addition, care of people with chronic multiple conditions has to be oriented to the realities of multimorbidity burden and its implication on QoL, well-being, and survival. Key words: NCDs, multimorbidity, LCA, patterns, qualitative methods, thematic analysis, quality of life, panel data, ordinal regression, PPO model, Ethiopia