Knowledge Management – What Is Its Role in Healthcare Research?

This week, we are diving into knowledge management, another new concept we can both learn together.

The driving question is…

How can knowledge management improve access to healthcare research?

To answer the question above, we were tasked to pick a local public health problem and answer the driving question in relation to the public health problem.

Let me break it down and introduce a few concepts first.

Knowledge management (KM) is a concept that was first introduced roughly around the 1990s (Koenig, 2012). According to the Association of State and Territorial Health Officials or ASTHO (2005), is defined as “a process used by organizations and communities to improve how business is conducted by leveraging data and information that are gathered, organized, managed, and shared.” The Gartner Group (2016) defined it as “business process that formalizes the management and use of an enterprise’s intellectual assets. [Knowledge Management] promotes a collaborative and integrative approach to the creation, capture, organization, access and use of information assets, including the tacit, uncaptured knowledge of people.” Its goal is to move from “not knowing what you know” and using that knowledge to improve organizational effectiveness and efficiency (ASTHO, 2005). The building blocks of KM are data, information and knowledge, which are represented by the figure below:

screen-shot-2016-11-28-at-12-12-25-am

Data is defined as “unprocessed representations of raw facts, concepts or instructions that can be communicated, interpreted, or processed by humans or automatic means (ASTHO, 2005).” An example of data is the number of dengue cases in a region. When meaning is assigned to data or when data is categorized, filtered or indexed, it now becomes information. In the dengue scenario, an example of information would be the number of dengue cases per district or barangay in the region. Finally, when processes like critical thinking, evaluation, structure or organization are applied to support decisions or understand concepts, information becomes knowledge. Knowledge is dynamic and evolving. It also has two types, namely: explicit and tacit. The former is also known as ‘book knowledge’ and refers to the “ordering of data and information according to well-defined, formalized procedures or rules.” On the other hand, the later refers to knowledge that is informal and that which is gained through experience and training. An example of knowledge in the dengue scenario is understanding the patterns of illness well enough to adjust preventative measures in a particular area.

When pieces of information are linked in meaningful ways, the information’s relevance to the problem at hand is established, and the information at hand is understood in larger context, there is translation of information to knowledge. This can then lead to knowledge translation which occurs when knowledge is put into action. (Straus et. al, 2011). The concept of knowledge translation is especially important because despite the abundance of evidence-based data, it has been found that there is still large gap between what is known and what is used in practice. In addition, there is a failure to use health research evidence in making informed decision related to healthcare.

For an organization to adapt the KM approach, the following components must be examined: culture, content, processes and technology (ASTHO, 2005). Culture is the organization’s shared set of beliefs, values, and understandings, and therefore varies from one organization to another. It is reflected by how and organization envisions, measures, and carries out its mission and responsibilities. Content refers to resources of the organization, which can range from data to information to skills to expertise. Meanwhile, processes are methods by which an organization manages data and information. They can be formal or informal. The processes are in place to ensure that content is created, assessed, management and disseminated effectively. Finally, technology has to be assessed in the context of why and how effectively it is used in an organization.

The role of knowledge management in public health is critical. To do their jobs, public health practitioners require accurate data and the ability to access data quickly from different sources and transform said data into useful information and knowledge. The officials, in particular, need up-to-date information for them to conduct analyses, report and generate vital information, and to collaborate with other agencies. In addition, the knowledge generated will guide decision-making in addressing public health concerns. Through KM, there can be an efficient way of developing and disseminating best practices and of continually assessing said practices for improvement.

In order to illustrate KM further, let us use dengue as a public health concern as an example. The dengue epidemic has plagued the Philippines since 1953 and continues to be a significant public health concern (Interhealth Worldwide, 2016) despite the many efforts of the Department of Health.

There was a recent article published, however, that featured the elimination of dengue cases through the combined efforts of a data analyst, professor, and local agency director. The story was a feature piece in Manila Bulletin and the subheadline mentioned that the answer to the dengue problem was not medicine but big data. It recounted how Wilson Chua, a big data analyst, was able to analyze the raw data on the dengue cases in Pangasinan provided to him by the Department of Health. He noted that the district of Bonuan had the highest number of cases in Pangasinan for 3 consecutive years, and that most of those infected were children aged 5-15. In doing his research, he found out that there were two public schools in the area (specifically Barangay Bonuan Boquig) with large pools of stagnant water in between, which were assumed as the source of the dengue vector.  Once he was able to identify the problem, he crowdsourced through social media (Facebook in particular) and got in touch with Professor Nicanor Melecio, the project director of the e-Smart Operation Center of Dagupan City Government, and Wesley Rosario, director at the Bureau of Fisheries and Aquatic Resources. Their solution to the problem was two-pronged, which was release of mosquito dunks and mosquito fish. They were able to implement this through the help of the local government. Thirty days after intervention, there was still no report of dengue cases in the area (you can read the full story here).

This article caught my attention for several reasons. One, I found it amazing that they were able to find a solution that could help address the dengue problem in the country. While I am aware that their solution is not applicable to other areas (ex. urban poor areas where large pools of water are not present and mosquito fish release is not feasible), it still impresses me how they were able to collaborate and come up with a solution. Two, the initial efforts were not made by a public health professional but by an analyst who just happened to have a personal interest in the situation. Third, his collaborators were not from the Department of Health. Fourth, DOH gave him raw data. (It was mentioned in the article that he was given an file with 81,000 rows of data. Aren’t there data privacy concerns?) Lastly, it mentioned that ‘big data’ was the solution.

Let me take a quick detour and discuss that last point. Big data, according to Tech Target, is a term that refers to a voluminous amount of structured, semi-structured, or unstructured data that has potential to be mined for information. There is no consensus on what ‘voluminous’ equates to in terms of volume or size, although it often refers to terabytes, petabytes, or exabytes of data captured over time. It is often characterized by extreme volume of data, wide variety of data types, and the velocity with which the data must be processed.

Going back, it now makes me wonder about how DOH has handled the massive amount of data that they have. Have they thought of Mr. Chua and his team’s interventions before? Based on the article by Lomibao (2013) in the Philippine Inquirer, Mr. Rosario mentioned that mosquito fish has been in the country for decades. Mosquito dunks are also not a new concept. But is the two-pronged approach new? If it showed promising results in Pangasinan, are there efforts to disseminate the information and replicate it in regions with similar topography? Is further research being done to address the feasibility of this solution and its long-term effects?

Recalling the 4 components of KM, I’ll now discuss how each of those components would play a role in improving access to healthcare research given the scenario above. Organization in the following paragraph will refer to the Department of Health.

The ideal culture in an organization is one where leadership plays a strong role in establishing the cultural will to support and maintain practices such as data documentation and dissemination of results. Considering the nature of public health, leadership should also be able to effectively communicate and coordinate with other organizations. It will help in understanding how the practices of others might be leveraged. First, recognizing the efforts of Mr. Chua is imperative. Given his and his collaborators’ success, a more wide-scale feasibility study should be done on the intervention that they did. Long-term effects of said intervention should likewise be performed, since the Department of Environment and Natural Resources’ Protected Areas and Wildlife Bureau (PAWB) has already expressed their concern over the potential negative and irreversible impact on our fragile biodiversity (Lomibao, 2013). At least for this particular aspect of dengue vector control and management, the DOH should work with BFAR, PAWB and the local government.

For content, one of the most significant challenges is capturing tacit knowledge, which means making it easy for individuals to share what they know through training, collaborative opportunities, networking, and other personal interactions. Mr. Chua can be considered as a potential content resource of the organization. I assume that there are already people employed by the DOH who do what Mr. Chua does, but he can help by sharing his knowledge on how he analyzed the data that was given to him.

As for processes, the ideal scenario is that the data and information management processes that exist in the organization are driven by the needs identified from the agency’s business activities. Given the nature of the public health sector, the data it collects is usually shared with external organizations aside for its intended personal use. Because of this, data and information management processes should make it possible for the DOH to share their data in a way that is understable and meaningful to other sectors, such as the local government or BFAR.

Lastly, for technology, it is already a reality that the public health sector has been increasingly using electronic technology to collect, store, access, analyze, visualize and communicate data. However, there remains a gap in the availability of personnel who both have an expertise in information technology and in public health, or the so-called hybrids. If the gap in hybrids cannot be addressed for now since it needs specialized training, the DOH could continue its efforts to collaborate with experts in different fields to address the problem.

If the above core components are present in an organization such as the Department of Health, knowledge on dengue and means for vector control would be more accessible. It will also encourage and allow for further research to be done. 

That is it for week number 12 of HI 201. I have a couple of questions for you.

First, do you agree that big data was indeed the answer to the dengue problem (at least for Pangasinan)? Second, do you think your organization (if you belong to one) is ready to adopt knowledge management approach?

Let me know in the comments below.

XO,
Eve

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  1. Pingback: HI 201 Journey – A Look Back | Garden of Eden

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