Nosocomial infections, also known as healthcare-associated infections (HAIs), pose a significant problem in healthcare facilities. Exchanging patient data between clinicians and public health agencies could help address the spread of HAIs. Empirical data mapping patient movement networks and monitoring HAI spread could improve understanding and response. Standardized HAI surveillance data collected annually from healthcare facilities is considered open access and can be used by researchers and health organizations without ethical restrictions to advance public health goals like HAI prevention.

1. Dr, Obumneke Amadi -Onuoha
Principles/Medical Informatics
Discussion: Public Health Informatics
An Example of a Public Health Problem that Could be Addressed by Patients, Clinicians or
Other Clinical Data Holders Exchanging that Data with Public Health Agencies
Nosocomial infection, also called Health care-associated infections (HAIs) are infections
that people acquire while under treatment or care for another illness, they are significant source
of mobility and mortality, that have imposed great financial cost to the US health care syster
(Fernández-Gracia, Onnela, Barnett, Eguíluz, & Christakis,2017). Incidence may be prevalent
in any health care facility, that include hospitals, ambulatory surgical centers, end-stage renal
disease facilities, and long-term care facilities. The organisms responsible for HAIs occurrence
are bacteria, fungi, viruses, or other, less common pathogens (Office of Disease Prevention and
Health Promotion, 2018). Transferring of patient between facilities are linked to the spread of
HAIs, clinicians have helped to address this problem using genetic data to ascertain if the
bacterial strains coincide or use a scalable sensor network-based method for monitoring the
hospital system against the spread of these infections.
Improving Health Care Delivery or Patient Outcomes using empirical data and Types of
Biomedical Data that Would Need to be Shared
“Empirical data could be of great advantage used either periodically, or in real time, to
map networks of patient movement in the US health care system, and that can also monitor the

2. spread of nosocomial and other infections in the network” (Fernández-Gracia, Onnela, Barnett,
Eguíluz, & Christakis,2017, p.6). Through standardized surveillance and annual data collection
reports of the trends in HAIs infections, composed with targeted programmatic indicators such as
diagnostic, treatment enrolment, care delivery and treatment outcome will be made
understandable. Empirical data has the capability to support patients, clinicians and health care
provers to have information’s that would aid them obtain or provide immediate access to
effective treatment and suitable care; prevent transmission through proper infection control;
increase political obligation and provide satisfactory HAIs solution financing (Weyer, et al.,
2017). Other types of biomedical data that can be shared to help improve public health include:
diagnostic platforms, logistics and digital technology data can be used to link HAIs programs at
the local and state level (Weyer, et al., 2017).
The Ethical or Legal Considerations -Empirical/Surveillance data
Such data are open access data, that are achieved by health organization agencies linked
to the hospitals that subscribe to reporting their hospital HAIs Infection incidence and rates,
through which health researchers, providers, patients, population and health promoters use to
support their endeavors towards a HAIs safe and free community, and are not obliged to any
ethical and legal consideration order than to use the information from them appropriately to
advance better public health e.g. the Centers for Disease Control and Prevention, collaborated
with health care and public health partners to provide great attention using the “HAI Data and
Statistics” at a glance in the centers website (Centers for Disease Control and Prevention, 2018).
Explored to understand the various aspects of hospital environmental hygiene and Infection
prevention control program and recommended” a nationwide reliable HAI surveillance system

3. and a robust infection prevention and control program in each health-care institution” (Joshi et
al., 2018).
Reference
Centers for Disease Control and Prevention (2018). HAI Data and Statistics. Retrieved from
https://www.cdc.gov/hai/surveillance/index.html
Fernández-Gracia, J., Onnela, J. P., Barnett, M. L., Eguíluz, V. M., & Christakis, N. A. (2017).
Influence of a patient transfer network of US inpatient facilities on the incidence of
nosocomial infections. Scientific reports, 7(1), 2930.
Joshi, S., Diwan, V., Joshi, R., Sharma, M., Pathak, A., Shah, H., & Stålsby Lundborg, C.
(2018). “How Can the Patients Remain Safe, If We Are Not Safe and Protected from the
Infections”? A Qualitative Exploration among Health-Care Workers about Challenges of
Maintaining Hospital Cleanliness in a Resource Limited Tertiary Setting in Rural
India. International journal of environmental research and public health, 15(9), 1942.
Office of Disease Prevention and Health Promotion (2018). Overview: Health Care-Associated
Infections. Retrieved from https://health.gov/hcq/prevent-hai.asp
Weyer, K., Dennis Falzon, D., Jaramillo, E., Zignol, M., Mirzayev, F., & Raviglione, M. (2017).
Drug-resistant tuberculosis: what is the situation, what are the needs to roll it
back. AMR control.