Analytics and Value Based Care

In order to evolve further towards value-based care, it is necessary that organizations make more use of data analysis. To improve outcomes for patients at a lower cost with higher patient satisfaction, it is necessary to collect and analyze data. There are many ways to do this and I will list a few, including some I use.

Healthcare is packed with data. There is billing information, including diagnostic and procedure codes. There are claims-based payer data. There is much more detailed information in EPDs, such as test results. These data are clinical data. Financial data is also important. Much of this data can be found in financial software such as QuickBooks and patient management software.

In order to use this data effectively, it is necessary to organize, map and investigate for significant changes. Each of these requires the use of statistics, either at an elementary level to spot trends, or at an advanced level to see if there are any real and significant changes that indicate the health care provider is moving towards better care at a lower cost. Examining and analyzing data collected from patients and grouped by patient characteristics is called population-level health management.

One approach to using analytics to improve patient health is to investigate and monitor key indicators for patients with chronic diseases, usually those who incur the greatest costs in a practice. For example, a practice can collect and analyze the A1c values ​​of all patients diagnosed with diabetes. This data can be collected monthly and an average and standard deviation determined. A chart from month to month using an Excel spreadsheet helps visualize any trends. If there is an upward trend over a period of several months, action can be taken to disrupt the trend. A nurse coordinator can be used to help patients better manage their diabetes. Control charts from technical statistics could be used to better analyze whether trends are real or due to random fluctuations that are normal when collecting data over a period of time. Statistical t-tests could also be used to determine whether the changes are really significant or not.

It can be very useful to plot collected data such as A1c levels, plot the resources over time as indicated above, and present them in a Dashboard with short descriptions and analysis. These dashboards can be shared in practice to encourage improvement. This can be very effective when making improvements with a healthcare team. I recently listened to an NPR podcast from ‘The Hidden Brain’ that described how a Pittsburgh hospital improved hand washing by health care providers before entering patient rooms. Despite repeated training of health care providers, the rate has fluctuated around 10% for a long time. Then, the hospital started showing monthly hand wash statistics in a dashboard that everyone could see and view. Management-oriented caregivers draw attention to the dashboards. The hand wash rates quickly improved to 90% and stayed there. The visuals had a major impact on suppliers’ awareness of hand washing.

Analytics can also be used to improve patient satisfaction scores. The Medical Group Management Association (MGMA) provides a very good patient satisfaction survey for its members. I have adapted it to different providers depending on their requirements. The survey contains 36 basic questions and ends with “Would you recommend the provider to others?”, A very good closing question. I also add demographic questions. Providers can use the patient survey and track performance in five areas: the appointment, the quality of front office personnel and billing, ease of communication, visit to clinicians, and the condition of the facilities. The aim is to obtain the highest possible composite score for each of these areas. With advanced analysis, more can be discovered to improve satisfaction. It is possible to identify which of the questions have the most impact on the last question. Patients most likely to refer to practice with friends and family have been found to be most satisfied. Finding out which of the many questions have the most impact on this can help identify areas for improvement. It is necessary to analyze regularly which questions have the greatest impact, since the questions with the greatest impact may change over time.

Of course, a dashboard needs to be created to report survey results to staff every month or so. This will encourage staff to perform even better. If management likes it, results can be broken down by staff area or by provider to help determine where individuals can improve. Individual coaching can then be used to help employees make improvements. However, the dashboards should never be used to blame staff. Whether individual dashboards are shared with other employees depends on how well the employees function as a team, how mutually supportive they are.

The MGMA collects a lot of data from its members through surveys. It then provides its members with data for benchmarking, some for free and some for costs. Providers who participate in their surveys often get the results for free. In a recent article in his monthly publication Link it provided a dashboard with data on the most profitable independent practices. Contrary to common sense, it turned out that the organizations with the highest median costs per FTE doctor were also the most profitable. Some information in the dashboard follows:

Median total medical revenue per FTE physician = $ 1,169,542

Median total operating costs per FTE physician = $ 630,680

Median total physician reimbursement and benefit = $ 462,722

Median total support staff per FTE physician = 5.12

The article, Designing the practice of the future, found in the March issue of the magazine, also provided the benchmark data for all multi-specialty practices. This data, along with other data in the article and the article analysis, can help providers develop long-term strategies to improve the profitability of their practice.

As you can see, there are many ways to use data and data analysis to improve outcomes at your healthcare location. It is important to identify which data should be collected and analyzed to have the greatest impact. As I said, healthcare providers are flooded with data and it would be a waste of time and energy to analyze everything. Those just starting to use advanced analytics should start with a few data projects and expand as time goes on. Intelligent use of data and analysis can have a significant impact on the care you provide and your business results.

Source by Donald Bryant