Background: Digital Health Interventions (DHIs) such as electronic health (eHealth) and mobilernhealth (mHealth) are emerging as promising technologies to advance clinical care and treatment.rnHowever, many of these breakthroughs have not reached the people most in need to tackle thernrising burden of diseases such as Tuberculosis (TB) and Human Immunodeficiency Virus (HIV).rnPeople living in low-income countries are at high risk of many health conditions than those livingrnin other regions while having the least access to such technologies. There is a high level of concernrnthat low-income countries lack the infrastructure and human resource capacity needed torneffectively adopt, implement, and scale up DHIs. Being one of the top 30 high TB and HIV burdenrncountries globally, Ethiopia exerts efforts to meet the global targets to End TB by 2035 and EndrnHIV/AIDS by 2030. DHIs could transform TB and HIV clinical care and treatment services inrnEthiopia. However, the country needs an in-depth assessment of the healthcare systemâ€™s capacityrnand readiness to absorb and implement DHIs. rnObjective: This study aimed to assess the capacity and readiness of healthcare facilities to adoptrnand implement DHIs for TB and HIV care and treatment. rnMethod: This study was a multi-center, facility-based, mixed-method, cross-sectional study. Thernstudy included 14 government healthcare facilities: 10 health centers and four hospitals with highrnTB/HIV clients load in Addis Ababa, Ethiopia. The participants were healthcare providers whornprovide TB and HIV clinical care and treatment services in the study facilities. With a purposivernsampling method, two healthcare providers have participated from each included site. Using arnquestionnaire framed by the Technology Readiness and Acceptance Model, data were collectedrnfrom the participants that assessed their experience using digital health technologies and thernpotential readiness of their healthcare facilities to implement DHIs. Using a tool framed by thernunified theory of acceptance and use of technology (UTAUT) model, data were collected fromrnparticipants who hold a solid prior experience of using DHIs to understand further the level ofrnacceptability of such digital health technologies. A multiple linear regression model to determinernthe relationship between dependent and independent variables. Cronbachâ€™s alpha test wasrnperformed to evaluate the internal consistency and reliability. Using an adapted checklist, thernhealthcare facilities were assessed to investigate their infrastructure and human resource capacityrnto adopt and implement DHIs.rnResult: There were 76 healthcare providers actively engaged in HIV/TB clinical care services inrnthe selected 14 study sites, of whom 60 met the inclusion criteria and participated in this study. rnsixty-two percent of the participants were working in HIV clinics, 37% of them had more than 10rnyears of working experience, 65% of them held a minimum of BSc degree, 60% were female, andrn42% were aged between 31-40 years. rnAccording to the responses, 80% of the healthcare providers had the experience of using DHIs tornfacilitate their healthcare delivery. Most of them had internet access and computers in theirrnfacilities. Seventy-five percent of the participants found the technologies advantageous than therntraditional system and the majority preferred to use the DHIs in their healthcare facility. The majorrnfactors that influence healthcare providersâ€™ willingness to use different technologies wererneducational level (Î²= .097, t= 3.784, p= .006), age (Î²= -.227, t= -1.757, p= .027), work experiencern(Î²= -.366, t= -2.855, p= .016). rnRespondents who had experience using digital adherence technology for TB felt that remoternmonitoring of medication adherence benefits both patients and providers. Similarly, respondentsrnwho had experience using smart care technology for HIV felt that the technology helps to retrievernpatientsâ€™ data easily and simplify their work. The strongest facilitator of their acceptance and thernuse of the digital adherence technology were perceptions of positive performance expectancy (i.e.,rnperceived usefulness). rnAccording to Cronbachâ€™s alpha test, all factors were greater than 0.7, and such values suggest arnhigh level of internal consistency and reliability of related items. The majority of respondentsrnreported the absence of regulatory policy and guidelines as the major gap to adopt and use DHTsrnin their facilities. The correlation between technological readiness and organizational culturalrnreadiness was considered to being significant (r = 0.8). rnThirty-one percent of the healthcare facilities had prior needs assessments made to make their sitesrnready for new DHIs. The data showed that 57.1% of facilities had skilled staff on payroll forrnmaintaining computers and other dysfunctions related to technologies. The average number ofrncomputers in each facility was about 20. most of the healthcare providers used Wi-Fi while 42.9%rnof them used both Wi-Fi and broadband internet. Of the 14 facilities, 35.7% had the plan tornestablish a functional Local Area Network for interconnectivity to give better services. rnConclusion: The present data confirm that many public healthcare facilities in Addis Ababa havernalready begun implementing various DHIs/e-Health systems for TB/HIV services and the level ofrnacceptability of these technologies by healthcare providers was noticeably good. Thus, there is anrnexcellent opportunity for DHIs to be integrated into the healthcare system in tertiary healthrnfacilities in Ethiopia with appropriate training and education. However, most of the availablerndigital health technologies in the facilities were utilized without reliable DHIs/eHealth regulatoryrnpolicy in place. Thus, there is a critical need for DHIs/e-Health regulatory policies and somernimprovement is needed in DHIs/e-Health strategic planning (core readiness). There should be arnprior need assessment and proper training given to healthcare providers to properly adopt andrnimplement new DHIs in healthcare facilities.