Summary
The lean management concept focuses on reducing and eliminating eight kinds of waste. Antony et al. (2018) state that these wastes include defects, overproduction, waiting, non-utilized talent, transportation, inventory, motion, and extra-processing, otherwise abbreviated as DOWNTIME. Thus, lean refers to any tool, measure, or valuable method for identifying and eliminating waste. On the other hand, Six Sigma is a term used to define critical techniques and tools in improving the manufacturing process (Antony et al., 2018). Thus, the Lean Six Sigma strategy helps identify and eliminate the causes of defects and variations in the business and manufacturing process.
This project seeks to define, measure, analyze, improve, and control Point of Service Collections (POS) by the Holistic Health Systems (HHS), which operates 39 hospital facilities and clinics. After reviewing key metrics over the last year, the HHS executive found the need to improve POS. Improving POS is critical since about 60% of patients make payments after discharge (Stahl, n.d.). Increasing POS is imperative for reducing bad debts, lowering expenses, improving cash flow, and enhancing patient satisfaction.
Process Stability
It is simpler to interpret I-MR charts by looking at the charts individually. Consequently, starting with the MR chart, there were two failed test observations of the POS performance at the start of the process and at point 10 for test 2. According to the MR chart, the average POS performance was unstable. Thus, the entire POS performance process variation was out of control (Antony et al., 2018). In contrast, the individual POS data collection showed no failed observation tests. Therefore, the I-MR chart suggests that the average POS performance process was largely unstable and out of control.
Regarding all-patient payments, the MR chart revealed three failed test observations at point 1, point 14, and point 24 for test 2. The MR chart indicates that the overall average performance of all patient payments was unstable. Thus, the All-Patient Payment performance process variation was out of control (Antony et al., 2018). Conversely, the individual payment collection process revealed no failed observation tests. Thus, the I-MR chart generally indicates that the average all-patient payment performance process was unstable and out of control.
The reason leading to the choice of the Individual (I) and Moving Range (MR) Charts, otherwise also known as I-MR Charts, is that these are Control Charts that are critical in examining continuous data, such as that for the project under review. Using the two charts together helps to provide all the necessary information regarding the behavior of the process (Antony et al., 2018).
I-MR Chart is also the perfect choice for examining and measuring individual data, as in the case of the POS. An Individual (I) Chart plots individual data points over a specified period, which was 24 observations for this project. Thus, it is imperative to detect the different trends and shifts present within the process (Antony et al., 2018). It is also important to visualize the causes of variations, whether standard, unusual, or exceptional, whenever present.
Scope Opportunity
Scoping the project’s focus area will consider the absolute individual POS and the percentage POS relative to the All-Patient Payments. The first area of focus will be the absolute POS falling below $1,000,000. Thus, facilities such as CGH, FLO, and SCH will come under the focus of the Lean Six Sigma team of Holistic Health Systems (HHS).
The second area of focus for the Lean Six Sigma team of HHS will be the facilities whose POS percentages relative to the All-Patient Payments are below 30%. The team will take six months to look into these two issues and recommend some of the best approaches to address them. To do so, the team will incorporate and increase Patient Access teams and work closely with the insurance providers, doctors, and other healthcare providers within the focus facilities.
Testing a Theory
The hypotheses for this experiment are as follows:
- H0: Centralized teams have no impact on the POS collections.
- H1: Centralized teams have a positive impact on POS collections.
Table 1: Hypothesis Test Results. t-Test: Two-Sample Assuming Unequal Variances
From the hypothesis test, the t-stat is smaller than the t-critical for the two-tailed test. Consequently, H0 holds. As a result, it can be deduced that centralized teams have no impact on POS collections (Antony et al., 2018).
Solution Categories
Some affinity categories likely to contribute significantly towards low POS collection include sports fans, travel buffs, TV enthusiasts, shoppers, pet lovers, movie lovers, and foodies.
References
Antony, J., Palsuk, P., Gupta, S., Mishra, D., & Barach, P. (2018). Six Sigma in healthcare: A systematic review of the literature. International Journal of Quality & Reliability Management, 35(5), 1075–1092. Web.
Stahl, G. (n.d.). Practicing Point-of-Service Collections Can Improve Your Revenue Cycle. Web.