The FSISs Public Health Information System - Essay Example

The FSIS’s Public Health Information System Introduction There are many instances in which human and animal worlds interact leading to economical, agricultural, medical, social, and psychological benefits. Conversely, there are numerous limitations connected to this interaction such as the transmission of infectious diseases from animals to human beings which are commonly referred to as zoonoses (Ossebaard, 2013). Over the past years, pathogenic micro-organisms shared between human beings and animals have caused significant disease outbreaks such as H1NI flu, HIV, Ebola, avian flu, and MERS-CoV. According to Ossebaard (2013), these diseases have had a serious negative impact on global public health. To prevent the outbreaks and spread of such illnesses, this area has been a focus of scientific research. Public health organizations have to establish ell-designed information systems to make maximum use of the collected data. Today, information systems are a critical public health tools because they provide real-time data which is used by concerned parties to guide public health decisions. At the beginning of this century, the World Health Organization (WHO) strongly recommended the idea of PHIS as a basic principle for collection and analysis of public health data (WHO, 2000). Also, there is need to utilize a more informed and systematic approach to the application of IT to take full advantage of IT’s ability to facilitate and enhance public health activities (Yasnoff, Carroll, Koo, Linkins & Kilbourne, 2000). In 2006, a report by the National Advisory Committee on Microbiology Criteria for Foods indicated that there is inadequate data regarding foodborne illnesses (NACMCF, 2007). The recommendations that were put forward by the committee included that FSIS partner with the Centers for Disease Control and Prevention (CDC) to establish a system that will help in addressing the gaps in data. The committee further recommended that FSIS collect extensive information regarding meat and poultry labeling and consumer protection. As stated by the Institute for Homeland Security Solutions (2009), the national security of the United States depends on a safe and secure food supply; food that is free of contamination. In 2006, the Pandemic and All-Hazards Preparedness Act was passed by both the White House and Congress. The Act established a goal of near-real-time information to enhance rapid response to public health threats to minimize their impact (Institute for Homeland Security Solutions, 2009). To meet such a challenge, public health and safety organizations need to enhance their ability to collect, analyze, and disseminate health information across the organization. Liu & Wein (2008) and Zink (2004) have raised concerns that it is only a matter of time before the United States begins experiencing instances of major food terrorism. Earlier in this century, Sobel, Griffith, Slutsker, Swerdlow & Tauxe (2002) observed that the information environment and informatics tools that were used then tended to follow jurisdiction boundaries. They further observed that these boundaries worked against efforts to reduce inherent latencies. One good example of the effects of these boundaries is the 2008 peanut butter contamination. In November 2008, the Center for Disease Control confirmed clusters of Salmonella Typhimurium (IHSS, 2009). Two months later, investigations associated Salmonella Typhimurium with peanut butter contamination. In April 2009, 691 cases of Salmonella Typhimurium poisoning due to peanut butter were reported in nearly all states. This prompted Peanut butter products and brands recall making it one of the largest food recalls in the history of the United States (IHSS, 2009). The contamination source was identified as the Peanut Corporation of America (PCA), and the recall made PCA file for bankruptcy in March 2009. Such cases prompted public health organizations to consider improving their information systems. The ‘human element’ in public health organizations at the time shared information on an informal basis because the available systems were not adequately responsive to their need for information promptly. Prior to the adoption of new public health information system, FSIS encountered several challenges due to issues related to fragmented data stores. For example, where the FSIS personnel was required to inspect import establishments across the U.S., there were problems related to latency with which information about safety violations or border refusals were availed to be surveillance teams was too great to be useful in containing an outbreak. There was poor or lack of effective communication or cooperation between the Organization and other agencies involved making the confirmation and response too slow. This was one of the major challenges that were encountered by the FSIS. United States Department of Agriculture (USDA) This report will explore the public health information system that is applied to the United States Department of Agriculture (USDA). USDA is also referred to as the Agriculture Department. It is one of the departments of the federal government. USDA executes policies on agriculture, food, farming, and forestry. Its main objective is to ensure food safety, promote agricultural trade and production, promote farmers and ranchers, and eradicate hunger in the United States and also beyond U.S. borders. USDA is headquartered in Washington D.C. Due to its extensive area of operations; USDA requires a well-designed information system to ensure food safety in U.S. and beyond. Its public health information system (PHIS) is dynamic and comprehensive (USDA, 2015). USDA launched this comprehensive system to enable it to collect, consolidate and analyze data towards its objective of improving public health among the citizens. The system collects importers and brokers’ data of agricultural products such as poultry, meat, egg products, and other agricultural products. USDA took advantage of new digital technologies to improve its information processing. The new system provided a new information-rich distributed environment that is characterized by increased sharing of near-real-time data electronically across the organization. According to Enache, Bontos & Vaireanu (2014), the new information system should be based on modern technologies for acquiring and processing data in the food industry. USDA’S Food Safety and Inspection Service (FSIS) FSIS is a health regulatory agency in USDA (USDA, 2012). According to Temel & Kinlay (2012), FSIS is a soft system with an organizational domain that is shaped by policy issue, participating organizations, and the qualification of policy makers. From a policymaking standpoint, FSIS’s goal is to provide critical food security policy information in a convenient manner. Therefore, defining the operations of FSIS requires one to have a clear-cut distinction between formal and informal information. FSIS’s Public Health Information System (PHIS) An information system with the capacity to generate the desired information is one of the two elements that are required for information to be used effectively. Many organizations today are adopting a two-tier strategy to support informed policy making process. On one side, they are promoting the emergence of information systems and on the other hand they are investing in the improvement of human resource capacities. FSIS is one of the organizations that have adopted this strategy because it has adopted a public health information system on one hand and invested in training personnel who are tasked with running the system. The Public Health Information System is considered to be the cornerstone of FSIS because it is the information system that has facilitated the connection of public health and food safety agencies across the United States. It has changed the way FSIS operated before its adoption. The Public Health Information System (PHIS) was launched on May 29, 2012, by the Food Safety and Inspection Service (FSIS) which is a health regulatory agency in USDA (USDA, 2012). PHIS is administrative in nature. The FSIS Public Health Information System (PHIS) was established in response to a 2007 recommendation from the Office of the Inspector General in order to improve the inspection system and develop an integrated data infrastructure across the country (FSIS, 2010). This system was designed so that: i. It can serve as a repository for data gathered from all domestic inspections and import and export inspections. ii. It can enable FSIS to have a consistent, data-driven inspection, auditing, and scheduling system. iii. It can support predictive analytics through its ability to facilitate timely data analysis from multiple sources. This facilitation enhances the organization’s ability to determine patterns, trends, and anomalies to identify emerging food-safety problems. iv. It can facilitate effective coordination within the organization, between the organization and other federal agencies, and between the organization and the entire industry in order to improve investigations and contaminant trace-back activities (Committee on a Study of Food Safety, 2014). The general public does not have access to the PHIS. However, it is accessible to the FSIS personnel. Other federal agencies only have restricted access, and this happens only after authorization through a memorandum of understanding. The above information was supported by Jones Barnett, who is one of the FSIS analysts. Jones was interviewed on July 27, 2015, and he shed light into the topic at hand. The interviewer based his interview on five questions: 1. Can you say that the implementation of the public health information system at FSIS has been successful? 2. What are the major challenges that FSIS has encountered in the implementation of HSIS? 3. What are some of the major achievements has FSIS achieved by upgrading its old versioned information systems to new information system? 4. Which strategies does FSIS use to ensure that the PHIS is running well and contributing towards accomplishing the Agency’s mission and objectives? 5. Which changes would you recommend on FSIS’s PHIS? Jones observed that FSIS had realized great improvements since it upgraded its information system. Jones has been working at FSIS since 2005, and he has used both the old and new information systems. He argues that information collection, analysis, and dissemination have been speeded up by the new information system. According to Jones, this process used to take five days to 4 weeks depending on the nature of the task. However, under the new system, the time spent searching and reviewing information has been greatly reduced. He also cited training of personnel as the cornerstone of PHIS. Jones also observed that the descriptions of an algorithm and the description and analysis of data are not clearly defined in the FSIS Technical report. He recommended that the management should address this issue. During its launch, the USDA under secretary for food safety, Dr. Elisabeth Hagen said that the system was aimed at arming food inspectors with a powerful tool to carry out food safety mission more effectively (USDA, 2012). FSIS is tasked with the responsibility of ensuring the safety of both imported and domestic meat, poultry, and egg products. It also ensures that these products are wholesome, correctly packaged and labeled. FSIS replaced most of its systems such as Automated Import Information System (AIIS) and Performance Based Inspection System (PBIS) (USDA, 2012). This initiative was taken because paper-based business processes were found to be inefficient, limiting, and time-consuming. All the FSIS information systems were consolidated into one automated data-driven inspection system. This was a complete change of the IT system and an adoption of a new inspection infrastructure. What prompted FSIS to change the previous outdated inspection system used to burden the inspectors with scheduled tasks to accomplish each day. This is contrary to the current system which provides inspectors with daily calendars with suggestions. Lack of timely response causes acute illnesses and deaths. For instance, it is estimated that foodborne infections cause approximately 76 million acute illnesses and 5,000 deaths in a year in the United States (NACMCF, 2010). These infections are as a result of food contamination from disease-causing bacteria and viruses. Prior to the adoption of PHIS, the USDA’s Economic Research Service (ERS) estimated that diseases caused by E. coli account for $6.9 billion in medical costs in the U.S. (NACMCF, 2010). In 2010, FSIS established an incorporated and vigorous data compilation and analysis system to validate the efficiency of its programs. Such data analysis systems helped FSIS to enhance its public health information system. Since it as established, FSIS has been conducting assessments of public health data to ensure that it meets its information and communications goals. Such assessments provide it with evidence that shows whether their approach to information sharing and dissemination is working. According to the FSIS (2010), it has put in place a Strategic Data Analysis Plan that supports its strategic goals and provides the necessary data to effectively measure performance and allocate resources. Such a measurement effort and feedback promotes continuous improvement. The feedback includes input from all the internal and external stakeholders. These inputs facilitated the adoption of the PHIS. FSIS pledges its commitment to making its planning as transparent as possible by seeking input from all relevant stakeholders. According to FSIS (2012), input from its stakeholders provided valuable information that helped it in designing its Public Health Information System. To refine this system further, FSIS is committed to seeking more input from outside stakeholders. Other inputs were sought from third parties including the National Academy of Sciences (NAS). NAS highly influenced the changes made in FSIS’s PHIS because of its comments 2.1, 2.3, and 2.7 regarding the need for transparency in the system’s intended use. This prompted FSIS to make an adjustment to address these comments. Also, the Office of the Inspector General also made some recommendations in 2007 while reviewing the issues impacting the development of the system (FSIS, 2012). The FSIS business objectives for adopting the PHIS were to enhance its use of technology in the collection, analysis, and prediction of likely outcomes to effectively protect public health. Secondly, to assist it in the modernization of its technology and move from client-server to web-based systems that can collect and analyze near real-time data. Thirdly, provide it with a predictive analytic capability for detecting and responding to events of public health concerns. Finally, assist it to deliver a framework for future expansion plans (FSIS, 2012). The current system significantly improved FSIS detection and response to foodborne hazards (Wethington & Barlett, 2006). There are four components in PHIS, and these are domestic inspection, export activities, import activities, and predictive analytics. The PHIS has an empowering effect because it enables FSIS to protect public health more effectively and efficiently. It facilitates data sharing FSIS headquarter, the managers, and the inspection personnel. Such a facilitated work relationship enables the decision makers to have a clear picture of what is happening in all areas of the country promptly. As a result, there is the elimination of time lag that as associated with the previous systems where such communication used to take days or weeks. FSIS’s PHIS is a web-based application that is user-friendly. This application has gone a long way to facilitate better identification of food safety risks before the result in recalls or disease outbreaks. The PHIS has a component known as ‘the predictive analytics’ which supports a data-driven approach to sample and inspection. This is enabled by an automatic search of data which happens to identify trends and notify FSIS data personnel about potential public health threats. According to Miller (2013), successful organizations compete and in based on analytics. Predictive Analytics can bring together all concepts, techniques, and R code that an organization needs to excel in all the roles involving analytics. The PHIS personnel access real-time data to recognize any deficiency and trend in food safety system. The collected data is used in initiating a quick response to prevent product adulteration, outbreaks and recalls such as the one that was witnessed when peanut butter was contaminated in 2008. However, the quality of the analysis is dependent on the quality of data present in the system. Therefore, the data entered in the system has to be accurate and complete for reliable results to be achieved. Training is provided to the personnel that is assigned the roles in PHIS. According to FSIS (2012), training is the foundation of public health protection. Training provides information system personnel with the ability to make effective and sound decisions based on appropriate public health principles. Training is, therefore, one of FSIS top priorities, and it aggressively trains and educates its workforce. The Office of Outreach and Employee Education and Training is tasked with the role of providing the workforce with PHIS training modules. The training is classroom-based, and it is offered by FSIS instructor. According to FSIS (2012), training is provided in areas such as NR documentation, new directives, Hazard Analysis Verification, and interpretation of establishment test results. IP and supervisors are trained together. Training will also be provided to all analysts. Predictive analytics facilitates the integration of data from sources such as PulseNet, the National Antimicrobial Resistance Monitoring System, CDC, and the Agricultural Research Service VetNet (FSIS, 2012). After integrating this data, predictive analytics stores the collected data in the FSIS Data Warehouse. After this, real time data analysis is performed, and if algorithms identify any anomaly, the system sends alerts to the appropriate user’s homepage. Users then subscribe to alerts that they are interested in. Algorithms are used by the system to automate scheduling to respond to certain events. PHIS responds to sampling results and inspection findings by generating appropriate follow-up tasks (FSIS, 2012). The predictive analysis facilitates identification of instances when an establishment should reassess their Hazard Analysis. Data analysts also conduct spontaneous data analyzes from the data sources in the system to identify anomalies and trends. One of the most important characteristics of predictive analytics is its data reporting and visualization tools which enable it to flag unusual events in the reports thus bringing them to FSIS’s personnel attention. The data-reporting function of Predictive Analytics enables users to delve into the underlying data, populate the report and flag anomalies. The visualization function is comprised of trend lines, box plots, and maps, standard tables among others (FSIS, 2012). The FSIS personnel who are assigned the task of overseeing the PHIS include the managers, inspectors, analysts, and policy developers among others, and each one of these personnel is assigned a role different from the other. However, all these personnel have the access to inspection and sampling data. The main functional areas within the PHIS are domestic inspection, exports certification, imports, and predictive analytics. Different roles are assigned by the system in accordance to the duties, job description and job series with each user having a unique navigation menu. Most of the PHIS’s important functions are driven by establishment profile data. Therefore, the Inspection Program Personnel (IPP) is assigned the task of routinely updating and ensuring that the profile data is accurate (FSIS, 2012). The profile comprises of critical information about the types of products, the operations of establishments, the HACCP system, and product volumes. Through this information, FSIS can tailor sampling, inspection, and other activities based on establishment factors. The routing of sample requests to inspectors is electronically done and is specifically based on the profile information of the establishment. The system creates precise tasks and regulates task frequencies in accordance with public health risk factors. Based on the profile data of each establishment, the system generates a task list. The role of the task list is to identify task frequencies and priorities. There are various factors that IPP considers before scheduling tasks on their task calendar such as time constraints, task priorities, and their knowledge of establishment operations. The scheduling of the task calendar is not limited to routine tasks; rather, there are directed tasks which the IPP may add to the task list. These ‘directed’ tasks are generated by PHIS in response to the findings of the inspection or results of the sampling. Another instance where a directed task is added to the document is when the IPP is documenting a noncompliance found when not performing a routine task. The system has an ability to track the completion of tasks and alert supervisors when tasks are performed. The system also links its users to applicable guidance materials such as notices and directives. These materials are based on specific inspection tasks and the establishment profile. These links help to reduce the time spent searching and reviewing information that may be less or not helpful. The system also helps FSIS to document meeting minutes in a memorandum of the interview (MOI) (FSIS, 2012). The system also provides inspectors with a platform for creating notes that they can use to communicate with other inspectors or that can be used as agenda topics for meetings. About exports, the system facilitates the management of export applications, certificates, and product eligibility. The data generated by the Export Library enables PHIS to populate the entire export certificate. The system contains an Export Library Validation Service, which is used to validate the export certificate. This validation service eliminates the need for inspectors verify the establishment and product eligibility manually. Verification by inspectors is only done on those requirements that have not been passed through the Export Library Validation Service. PHIS is interconnected with United States Customs and Border Protection’s (CBP) Automated Commercial Environment to facilitate these tasks. Other tasks that are conducted manually by inspectors include approval of the export application, re-inspection of the conduct, and permitting establishments to stamp the product. The task of certificate completion is done by the system. The inspector’s signature that appears on these export certificates is done electronically. However, this applies to only those counties that have received electronic certificates. When a replacement of certificate is needed, inspectors only review material changes. FSIS is governed by the Federal Meat Inspection Act (FMIA) and the Poultry Products Inspection Act’s (PPIA) requirements. For FSIS to maximize its task of improving public health, it has been collaborating with other food agencies. This collaboration involves data sharing and collaborative workgroups (FSIS, 2012). Some agencies such as Center for Disease Control (CDC) are close partners of FSIS. For example, FSIS relies on CDC illness data to calculate foodborne illness attribution. To facilitate this, FSIS has to organize regular meetings with CDC. These meetings have been going on since 2010. Another important work collaboration includes FSIS, CDC, and FDA. Staffs from all these agencies have to communicate regularly to develop goals such as High Priority Performance Goals (HPPG) for Salmonella. Earlier in 2012, FSIS had to amend its data sharing agreement with Agricultural Research Service (ARS). These amendments were made to support timely data exchange and to enable it to gain access to the VetNet data on Salmonella serotypes found in poultry meat (Swaminathan, Barrett & Fields, 2006). The MOA also provides access to the National Antibiotic Resistant Monitoring System (NARMS) data on antibiotic resistance. Close work collaboration between FSIS and ARS facilitated this agreement. PHIS must innovate and use the emerging information and communication systems. Innovations can enhance the quality of both information and communication. The descriptions of the algorithm and the description and analysis of data are not clearly articulated in the FSIS Technical report. Therefore, this paper recommends the use of designation decision tool or framework because the term algorithm implies a mathematical model and FSIS has not constructed a mathematical model. References Committee on a Study of Food Safety. (2014). The Potential Consequences of Public Release of Food Safety and Inspection. New York: The National Academic Press. Enache, A., Bontos, M. & Vaireanu, D. (2014). FSIS – An Information System Based on the Modern Technologies of Data Acquisition and Data Processing in Food Industry. U.P.B. Science Bulletin, 76(2), 105-112. FSIS (2010). FSIS Strategic Data Analysis Plan for Domestic Inspection. United States Department of Agriculture. IHSS. (2009). 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