The healthcare industry is facing various challenges that can hinder its progress. However, if it is able to overcome these challenges, a lot of opportunities will open up which will be beneficial to all of its stakeholders, healthcare workers and patients alike. The greatest of these challenges is the management of the voluminous and ever-increasing volumes of clinical data.
Healthcare data management is a gargantuan task, considering all the millions of patients, healthcare workers, and facilities involved. For instance, proper analysis and utilization of data in the dental industry will impact marketing for dental clinics tremendously. The right application of artificial intelligence will make it easier for healthcare workers to predict emergencies and assess their risks.
This will result in significant improvements in operational efficiency, management of healthcare staff and reducing costs. If these goals are achieved industry-wide, patient satisfaction will be assured and the ROI of healthcare facilities will be achieved at a much quicker rate. This value-based healthcare system can only be achieved through judicious healthcare data management.
Challenges Facing Healthcare Data Management
1. Reducing Costs While Improving Care
This is something that the healthcare industry will not be able to accomplish without the proper collection and management of clinical data. It is an understatement to say that this is a very huge task to perform. Healthcare could be improved and its costs reduced if the following practice is followed:
- Risk assessment
The Association of American Medical Colleges stated that the identification, classification, and management of high-risk patients should be the focus in the improvement of the quality and cost of healthcare.
- Prediction to help the prevention
With the right assessment of data, healthcare providers will be able to identify high-risk individuals who will develop chronic conditions and poor health early on. This will enable them to prevent expensive and lingering illnesses, thereby reducing costs and suffering. This will benefit consumers because healthcare will then be focused more on prevention rather than the cure.
- Risk score calculation
By the proper use of clinical data, healthcare workers will be able to assign risk scores to individual patients. For instance, dentists will be able to predict when a patient will develop tooth problems if they are armed with properly managed dental data.
2. Improving Operational Efficiency
Operational efficiency is measured by the amount of input against the corresponding outcome. In other words, it is the quantity and quality of the products that one is able to produce with all the efforts and materials that he has spent in producing them. The challenge is to reduce the input while increasing the quality and number of the product. In the healthcare industry, this can be achieved in different ways.
- Reduce supply chain cost
The cost of the supply chain is one of the significant costs of every healthcare facility. Therefore the reduction of this cost is paramount to their goal of achieving improved operational efficiency. Thankfully, there are analytical tools based on healthcare data that can help in monitoring the supply chain costs and thereby make pro-active decisions based on statistical data.
Approximately 17 percent in the healthcare industry is already using such predictive tools in managing their supply chains. These tools are helping them to reduce their variables and enable them to perform calibrated actions in regards to the utilization of their ordering patterns. Optimizing their process of ordering and price negotiations are made possible by using such tools.
- Anticipate the patterns of patient flow
It is very difficult to predict the flow of patients in a healthcare facility. There are times when healthcare workers are stressed out with too many patients to handle. And then there are times when only a few patients are coming in resulting in very little work for healthcare workers.
With proper data management, the utilization rates of healthcare facilities will significantly improve. Predicting the inflow of patients will no longer be left to guesswork. For instance, the cost of marketing for dental clinics will be optimized since the dentists and their assistants will be able to predict the inflow of their patients. These healthcare workers will be able to schedule their advertising costs at times when most patients will more likely require dental health care.
- Control of data access
Sharing patient data among healthcare workers is getting more common these days. However, data sharing, even among peers has its inherent risks. Patient information may fall into the wrong hands and can be used illegally. This underlines the need for data security and protection.
Fortunately, there are analytic tools that can monitor and control the utilization, sharing and access of data. With these analytical tools, evaluating the real-time risks for different transactions is possible. This will enable the system to act correctly based on the result of the risk assessment. If there is no risk, the data system can safely give access. But if the system finds that there are risks involved, it will block the access or ask for additional authentication from the requesting party.
- Minimizing no-shows
No-shows of patients are experienced by most healthcare workers. This unfortunate practice has a significant impact on the bottom line of healthcare facilities. By correctly interpreting big data with the use of analytical tools, it will be easy for health care providers to identify patients who are likely to miss on their appointments.
This fact was already proven by a study conducted by Duke University. By using clinical data, predictive tools were able to capture 4,800 additional no show patients per year. The patient no show patterns were not correctly predicted by previous attempts. This information can be used by healthcare workers by reminding their patients of their upcoming appointments, thus improving their facilities’ ROI.
Opportunities Open to Healthcare Data Management
Data management and analytical tools are the perfect partners that will bring the healthcare industry to new heights. This partnership will bring in more innovations and improved practices that will be beneficial to all the industry’s stakeholders. Healthcare facilities will have better and faster ROI and patients will enjoy better and timely healthcare. How can this partnership bring about the transformation of the healthcare industry?
- Correct patient analysis
Knowing the right patients, their total numbers and the right time to treat them is very important when it comes to the operation of healthcare facilities. This is where data management and predictive tools can be leveraged together by the healthcare facilities and providers. It will bring about the desired results – which is better and faster ROI.
When healthcare providers are able to use the information about the real-time demand of patients, they will be able to match their workers and their equipment to satisfy their patients’ need. If this is achieved, patients will enjoy timely and enhanced healthcare services. No-show patients will be a thing of the past.
- Correct analysis of inventory
Real-time information provided by data management will enable healthcare finance and operations managers to correctly assess the company’s assets versus its projected profits. They will be able to use these two important data to maximize their company profits.
Since big data is involved in this process, many financial analysts believe that storing information in the cloud will be a better option for healthcare providers rather than operating their own big data storage devices. This will also enable them to increase their efficiency since they will use less hardware and consequently enjoy fewer maintenance costs.
- Correct sales analysis
Healthcare facilities are usually saddled by voluminous paperwork. These include patient records, financial records of transactions between healthcare facilities and their patients, records of equipment and their respective maintenance, records of employees and health staff and so forth. A number of these documents are upgraded every day.
Some, if not all of these documents come into play when it is time to evaluate if a healthcare facility is earning or not. A dental clinic, although smaller in size, should have all these documents updated. Marketing for dental clinics is no different. They should know if they are earning or not. How does their profit compare to their goals and their ROIs?
Calculating profit is one of the most important reasons why healthcare facilities and providers should be concerned about healthcare data management. The bottom line is where big data analysis or healthcare data management plays its most important role.
If a healthcare facility is devoted to its practice of data management, it will not fail to see the true picture of the financial health of the organization. It will know how much value a particular patient has to the organization. The facility will also be able to use its available resources judiciously.
As it is, a healthcare facility cannot avoid collecting a vast amount of information each day, especially if it is caring for thousands of patients. The data could include patients, doctors, medicines, cash disbursements, healthcare workers shifting schedules and many more. Health care data management combined with analytical tools will surely make the job easier, faster and more accurate.
About the author
Meggie is a marketing expert and a data junkie with more than six years of experience in the field. Aside from being a marketing nerd, she loves taking her life to the extreme with bungee jumping and skydiving when she feels some freedom.