Public Health Data

PublicHealth Data

Nameof author

PublicHealth Data

Discussionquestion 1

Thetask of locating data sources at the federal level and the efficientuse of the statistics has vitality among the public healthprofessionals (Curtis,Brown &amp Platt, 2014).One source of statistical data at the federal level is the healthinstitution registers that contains some crucial information such asthe frequency of attendance at the hospital and the diseases treated(Hoffman&amp Podgurski, 2013).The research firms may be interested in this data source as it wouldassist in the identification of the common health issues and thefrequency of their occurrence (Curtis,Brown &amp Platt, 2014).

Secondarysources such as web site information are a crucial source of data atthe federal level. The internet is a suitable location where one canfind a lot of essential information about the public health that issystematically recorded. The web contains some updated and currentdata about the conditions prevalent in a population (Curtis,Brown &amp Platt, 2014).It assists in identifying some occurrence of diseases such as theoutbreak of illnesses and the frequency of their occurrence.Therefore, the policy makers can locate the health problems quicklyand influence the direction of the funding. The NGOs may beinterested in these sites as they would assist in the identificationof the needy population and their priority needs.

Anothersource of data at the federal level is the umbrella websites whichhighlight the areas one can locate the statistical data (Hoffman&amp Podgurski, 2013).The umbrella sites are also known as the portal and search engines,for instance, Google. Through these locations, the researcher canconduct health surveillance on the study population and identify someof the priority health issues among the residents. These sitescontain information about the specific community priorities thatinform the funding and the prioritization of activities, to make thehealth surveillance and provision of capital towards health servicesas efficient as possible. The food industry may have an interest inthese sites as they would assist in the location of the relevantpopulation data and thus the supply of the products will be informedof the health status of the population.

Anotherimportant source of data at the federal level is the Healthcare Costand Utilization Project (HCUP) databases. HCUP is a collection ofmedical records, software tools, and the federal-state-partnershipproducts (Taylor,Davies, Kristensen, &amp Csavina, 2014).These data sources enable the researchers to study a variety ofhealth program issues such as the quality, cost, patterns, access andoutcomes of the healthcare programs from the federal to the locallevels. By observing the various aspects of the study population, theHCUP assists the health researchers to identify the priority areasfor funding through the health surveillance (Curtis,Brown &amp Platt, 2014).The medicine industries may be interested in this data source as itwould inform them about the demand for particular drugs. The othersource of data at the federal level is the National Survey on DrugUse and Health. It provides data concerning the patterns and the rateof usage of the drugs. This source also explores the effects ofusage of narcotics among the juniors aged seventeen years to twelveyears (Hoffman&amp Podgurski, 2013).It is a crucial source of data at the federal level as it assists inconducting a surveillance of the rate of usage of the drugs.Therefore, the policy makers can determine the amount of funding toallocate the health institutions for curbing the issues of drug use(Curtis,Brown &amp Platt, 2014).One of the industries that may find this data source compelling isthe security firms as it would imply the rate of drug use may be areflection of the rate of criminal activities.

Discussionquestion 2

Thepublic health information systems may be classified intoservice-based and population-based applications. The service-basedapplications tend to emphasize the importance of the services offeredto the patients above the particular patients’ needs (Sagiroglu&amp Sinanc, 2013).This approach views service delivery to the patients as beinginfluenced by the nature and the availability of services (Hoffman&amp Podgurski, 2013).On the other hand, the population-based applications focus on theparticular needs of the study group and the provision of healthservices is influenced by the needs of the population. It is a betterapproach as it enables the health providers to deal with the mostprominent needs of the society (Sallowayet al., 2016).It, therefore, ensures high levels of patient satisfaction andefficient resource use. An example of the population basedapplications is the immunization registers while service-basedapplications are the disease and funding records.

Accordingto Curtis,Brown &amp Platt (2014), thepublic health providers have designed information systems that storevarious forms of data. The use of healthcare information providesdata concerning the immunization programs, preventable diseases, andnature of care services (Taylor,Davies, Kristensen, &amp Csavina, 2014).The population-based data may be derived from service-based datathrough the interpretation of the aggregated information (Hoffman&amp Podgurski, 2013).

InjuryPrevention and Control: Data and Statistics

Theaccessibility of spatial data has increased with the growth oftechnology (Sagiroglu&amp Sinanc, 2013).A set of data focuses on a particular population of individuals whoreceived regular services at a given time and the frequency theyreceived the services. This data is subdivided into the specifichealth departments that attend to the patients. Conducting an inquiryinto the trends and rates of non-fatal injuries among the residentsof the United States provided a variation of data (Chen,Dunn, Chen, &amp Linakis, 2013).The population of interest was randomly chosen and consisted of mixedraces, sexes and age categories in the year 2014. The study assessedthe patterns of unintentional falls among the research population.The statistics indicate an increased trend with the scaling of theage groups. From the data, the falls among the children aged between10-14 years resulting from accidental collisions were 535,500, thefalls of the age category 25-34 were recorded at 764,225 while thoseof the age group 45-54 were a total of 943,379. The total number ofunintentional falls among the whole population stood at 9,163,980(Chen,Dunn, Chen, &amp Linakis, 2013).

Theinvolvement of the public health providers in the prevention of fallsamong the population may have a significant influence on thereduction of the falls across all the population age groups (Chen,Dunn, Chen, &amp Linakis, 2013).The health workers try to ensure that the individuals learn aboutvarious efficient techniques to assist them in reducing thepossibility of the occurrence of a fall. The populations also get tolearn the most efficient ways of avoiding severe injuries in case aperson falls. There are several necessary and legal procedureobserved while providing information about the populations.Epidemiological data may contain some sensitive matters about therespondents (Curtis,Brown &amp Platt, 2014).It is, therefore, crucial to keeping the respondents’ privacy byconcealing the personally identifiable information while using thedata. When collecting epidemiological information, it is advisablethat the researcher uses a generalized format of labeling therespondents in the report than stating the specific names of theinterviewees (Chen,Dunn, Chen, &amp Linakis, 2013).The epidemiological data is sensitive and may lead to the leaking ofcrucial data if the proper usage and storage practices are notobserved. It is, therefore, advisable that this data should besecured in places only accessible by specific health professionalsand other individuals, who participate in public health affairs. TheHealth Insurance Portability and Accountability Act has provisions ondata privacy and security is observed in the epidemiologicalinformation operations (Curtis,Brown &amp Platt, 2014).

Thetask of locating data sources at the federal level and the efficientuse of the statistics has vitality among the public healthprofessionals (Curtis,Brown &amp Platt, 2014). Thepublic health organizations enjoy too much influence in the usage anddissemination of the public medical records. The excess freedomprovided may have some negative implications for the operations ofthe data among the particular department (Chen,Dunn, Chen, &amp Linakis, 2013).The health institutions may subject the data to improper uses leadingto the leaking of crucial information about the study group. Theusage of health information is focused towards the issues of privacyand security of the databases. There should be adequate informationregulations guiding the usage of population data sets among thehealth institutions. Proper reporting and analysis procedures shouldbe implemented among the public health organizations so thatefficient processing and evaluation of information is carried out(Taylor,Davies, Kristensen, &amp Csavina, 2014).

Thetechnological era has enabled increased access to public healthinformation and statistics. The statistics are made up of logicallyrelated data, arranged in a particular manner. The healthsurveillance fund ensures the establishment of quality health systemsby the implementation and control of the major public surveillanceand monitoring priorities. The health registers provide informationon the prevalence of some health problems and how widespread suchdiseases are (Hoffman&amp Podgurski, 2013).It assists in the identification of some the health conditions thatneed prioritization, thus informing the health surveillance andfunding.


Chen,W. S., Dunn, R. Y., Chen, A. J., &amp Linakis, J. G. (2013).Epidemiology of nonfatal bicycle injuries presenting to UnitedStates emergency departments, 2001–2008.&nbspAcademic emergency medicine,&nbsp20(6),570-575.

Curtis,L. H., Brown, J., &amp Platt, R. (2014). Four health data networksillustrate the potential for a shared national multipurpose big-datanetwork.&nbspHealthaffairs,&nbsp33(7),1178-1186.

Hoffman,S., &amp Podgurski, A. (2013). Big bad data: law, public health, andbiomedical databases.&nbspTheJournal of Law, Medicine &amp Ethics,&nbsp41(s1),56-60.

Sagiroglu,S., &amp Sinanc, D. (2013, May). Big data: A review.In&nbspCollaborationTechnologies and Systems (CTS), 2013 International Conferenceon&nbsp(pp.42-47). IEEE.

Salloway,M. K., Deng, X., Ning, Y., Kao, S. L., Chen, Y., Schaefer, G. O., …&amp Tan, C. S. (2016, February). A de-identification tool forusers in medical operations and public health. In&nbsp2016IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)&nbsp(pp.529-532). IEEE.

Taylor,M. P., Davies, P. J., Kristensen, L. J., &amp Csavina, J. L. (2014).Licenced to pollute but not to poison: the ineffectiveness ofregulatory authorities at protecting public health from atmosphericarsenic, lead and other contaminants resulting from mining and smelting operations.&nbspAeolianResearch,&nbsp14,35-52.