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According to Strome (2013), “the purpose of an analytics strategy is to guide a healthcare organization (HCO) ability to rapidly respond to the information needs of stakeholders while maintaining a consistent direction in supporting the quality and business goals of the HCO.”
As a healthcare administrator the analytics systems should work to collect, analyze, and provide useful information to managers and other leaders to assist them in making better decisions. In healthcare every decision that is made by administration and managers should be to improve the quality, safety, and efficacy of care patients receive. However, there is an analytic framework that incorporates the key components of an effective analytics system that supports quality. According to Strome (2013) the areas that should be considered in a comprehensive analytics strategy include:
- Business and quality context
- Stakeholders and users
- Processes and data
- Tools and techniques
- Team and training
- Technology and infrastructure
Each one of these areas is used to support one of the main functions in an HCO and can’t do without them. Each one plays a vital role in sustaining the other. Healthcare analytics systems can also be used to solve problems. Specific problems can be address with healthcare analytics. Business and quality context information is used to outline business problems facing HCOs. It also tracks quality, financial, and performance goals (Strome, 2013). It’s easier to address these issues with the right kind of data. Stakeholders and uses includes individuals and organizations that are actively involved in a patients care, a project, or any other interest within the facility can gain access to this information and improve communication, and efficiency. Team and training are important because teams are often formed for QI and proper training is crucial from the start. A strong foundation with good training program is important for new members and for staff that would like to upskill. Healthcare analytics are at times required by administrators, and healthcare leaders to make crucial decisions for their organizations. These decisions are often directly or indirectly linked to the care patients receive. Decisions can be made using analytic indicators rather than gut feelings. Analytics systems can mitigate risk and help administrators and healthcare leaders monitor progress.
The three strategies that I would like to discuss are:
- What data is most required to address key quality, efficiency, and performance issues facing the HCO
- What skill and knowledge are necessary in the HCO’s analytics team;
- What data and integration infrastructure is necessary to support analytics initiatives;
Before all else, it’s crucial to have a good idea of where and what is required of a HCOs analytics system. Without a clear understanding an organization will waste time and resources compiling useless information. Quality, efficiency, and performance are key points to track in any organization, especially healthcare. Data should be used in every department to try and improve their performance, efficiency, and quality of care the patients receive. Collecting data on patient satisfaction and patient outcome during their stay is a good start but it’s not enough. Most of the time patients complain that it takes too long to get help after pressing a call light. This has been an ongoing problem for years in many HCOs.
Data should be shared with every department manager and the manager along with staff should try to find the best solutions for their department. Most of the time staff is working short staffed, making it impossible to get to all the lights within a reasonable time. Data on staffing might be used to notify available staff that there is an available shift via email, or text messages. It would be easier to find staff to work and managers wouldn’t have to call each individual person to see if they want to work. Quality of care, efficiency, and performance would improve if healthcare facilities were staffed better and being able to communicate staffing needs with staff members at all times would improve the chances of finding people to fill open shifts.
A healthcare analytics team should have at least a basic understanding of the data they’re collecting; therefore, an analytics team should include the input of every department manager so that the data that’s being collected is relevant and useful. Data should be used to improve quality, efficiency, and performance every step of the way. A healthcare analytics team that involves those that deal with issues on a daily basis are the best people to ask what kind of data would best serve your department to improve performance, efficiency, and the quality-of-care patients receive.
Data is useless unless its shared with the right people. Some important data that should be shared with clinicians is information on patient infection rates on catheter-associated urinary tract infections (CAUTI), central line-associated bloodstream infections (CLABSI), and ventilator acquired pneumonia (VAP). Managers and clinicians should discuss this information and find ways to reduce or better yet, eliminate them. Data should continuously be collected and shared. Tracking the effectiveness of performance is crucial in determining if the HCO is continuously improving the quality-of-care patients receive.
As a healthcare administrator when Strome writes, “The purpose of an analytics strategy is to guide a healthcare organization’s (HCO) ability to rapidly respond to the information needs of stakeholders while maintaining a consistent direction in supporting the quality and business goals of the HCO”(Strome, p. 29, 2013). I believe that Strome is identifying the direction that an effective analytic strategy can take an HCO. By identifying that the purpose includes meeting the stakeholder’s wants and needs but also keeping in mind that maintaining quality and business goals are just as important, it sets a precedent for the HCO to remain true to their plan. Instead of being swayed by outside factors such as vendors or other distractions it gives the analytic strategy value as a beneficial decision-making process.
- What major analytics development projects to undertake and on what tasks to focus the analytics team? This item is important because it helps define that the analytic strategy must be worthy of your time and effort and therefore you must prioritize as a leader. I relate to this because so often we are faced with decisions of things that we don’t want to do because it isn’t worth the time it takes and by focusing on the most important aspects we are able to get more done. A real-world example of this is prioritizing time to build the foundation of the house so that the rest of the house has something to sit on. By prioritizing time and effort into the base of the project you are allowing the project to be successful. Without a strong structure, the house may fall apart. Just like the house, a strategic analysis needs a strong base, and therefore it is important to prioritize the necessary components before moving on to the next part.
- What skills and knowledge are necessary for the HCO’s analytics team? This item includes defining the team’s strengths and identifying what type of skills are needed for the organization’s analytics team in order to be successful. Without successful identification of what knowledge is needed for the strategic plan, the wrong people may end up contributing to the wrong part. For example, you wouldn’t want a math teacher teaching kids art class when it’s not their specialty. Instead, you would want to identify that teacher’s strength and knowledge of math and have them teach kids that subject instead. By having open and honest conversations strengths (and weaknesses) can be defined to best delegate responsibilities.
- How to maximize return on investment in analytics tools, teams, and training by demonstrating value to the HCO? This item relates to giving the strategic plan value by showing team members that is purpose and worth in what they are doing. By providing substance to actions, leaders can then see employees utilizing the infrastructure such as analytic tools, teams, and training when they understand the importance. If the plan is not given value or purpose it is hard to utilize and understand. This in turn allows the organization to see a return on their benefit because the tools are utilized. A real-world example in healthcare is when patients utilize portals to communicate with providers. Hospitals see a return on their investment when providers are able to provide better care to their patients when there is easier and more open communication through a platform like a portal.
Three main components of the analytic strategy diagram that are vital to the success of an analytical plan are Stakeholders and Users, Tools and Techniques, and Team and Training.
- Stakeholders and users are vital because it is necessary to identify who is directly affected by the plan. By defining the level of participation that individuals have in the plan and by identifying the impact the plan has on people, successful participation in effective execution is more likely to happen. Analytics initiatives are most likely to succeed when stakeholders are involved throughout all phases of a project (Strome, p. 38, 2013).
- Tools and Techniques are important because appropriate software, statistics, or models are necessary to ensure that the correct type of analytics can be performed to address stakeholder needs and the HCO’s business problems. (Strome, p. 42). Without the right type of tools, basic issues can arise that become unavoidable and in turn make it highly difficult to effectively continue with the analytic strategy.
- Team and training are one of the most important components to the plan in my opinion because even if you have all the right tools, infrastructure, and foolproof plan, it takes strong teams with intellectual people who have been trained property to implement a strategy. It is important to recognize what skills are required to develop, implement, and utilize the particular types of analytics your organization requires, what gaps may exist, and what to do to address any gaps (Strome, p. 43, 2013). Without structure or guidance, the plan becomes meaningless and the right team and training give it value.
The three main steps in creating an analytics strategy are first to identify the current state of the strategy and organization to understand where the starting point is, second identify the tools and people necessary to carry out the analytic objectives, and third put together a plan that people can follow to mitigate error, avoid gaps and overall complete the goals of the analytic strategy.
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