Process Mapping Of a Multi-provider, Multi-department Healthcare Process
This PDF is of a process map of a multi system process for perioperative care. Perioperative care is the care before an operation that is required by the anesthesiologist to perform a safe and successful surgeries. The process can branch multiple departments and levels of expertise including, but not limited to the perioperative care center, cardiology, outpatient testing, surgeon’s department, anesthesiology, and the patient’s primary care physician.
Objective: discover the true process and locate issues with the current process.
Skills demonstrated: this project required clean logical thinking, people skills, and process mapping. This map was later presented to the department head so I had to make the material as clear as possible. For this, I used the tool Blue works live, and process modeling tool.
Challenges: since this project required input from multiple people whom were very busy; I had to carefully navigate and negotiate to acquire the information I needed.
Outcomes: this map was used as justification by the health system to have to Rapid process improvement workshops to solve key issues uncovered and investigate and define other non-standardized parts of the process
Statistical Process Control Analysis of Health & Safety Measures
These charts are part of a larger analysis I conducted for a healthcare system. While at HSyE, I produced many control charts of a hospital’s Health and Safety measures. Discovering when and where Improvements and mistakes were made.
Objective: Create statistical process control charts to analyze data to discover trends, issues, and improvements made to the system.
Skills demonstrated: A strong ability to use Statistical process control methods, data analysis, and excel.
Challenges: a lot of the data required scrubbing and break down data sets to create meaningful analysis.
Outcomes: From this analysis, I created a power point presentation that was presented to the board to show the utility of SPC methods and the true condition of the hospital through the lens of Health and Safety.
Hypothesis Testing is a statistical inference where a hypothesis is tested, as well as its null hypothesis, to determine whether to accept or reject the hypothesis based on a confidence value.
So there are two hypotheses. H1 and H0. We use the nature of a probability distribution to determine the likeliness that the samples we are testing are in the distribution. If the sample is very unlikely to have been drawn, less likely than the our confidence value, we reject the H1 and accept the H0. If the value is likely, more likely than our confidence value, we accept the H1 and reject H0.
In the best case scenario, we calculate the possibility that the probability of drawing using the z distribution, the normal distribution. We use the true mean(u), the sample mean(x), and the true standard deviation(s). (u-x)/s=z value. We next go to a Z table where find the appropriate z value and the probability. If that probability is above our confidence value, we reject. the confidence value is a percentage, which determines the area of the distribution where that percent of values is contained, meaning for a confidence value of 99%, 99% of the values will land within that area. So if our Z value is outside that area. We reject the hypothesis.
Process capability compares the output of an in-control process to the specification limits set by the customer. The comparison is made by forming the ratio of the spread between the process specifications (the specification “width”) to the spread of the process values, as measured by 6 process standard deviation units. National Institute of Standards and Technology
There are several measure to calculate capability. Two important measures are Cp and Cpk. Cp is used when the mean of the specification limits is equal to the true mean while Cpk is used when its not.
Cp = (USL-LSL)/6σ
However, sometimes it may not be possible to get the True mean and True standard deviation. When that happens, we use sample deviation and Xbar
CTQs are the internal critical quality parameters that relate to the wants and needs of the customer. CTQs are what’s important to the quality of the process or service to ensure the things that are important to the customer. – isixsigma
CTQs are not always the problem that customer states. CTQs are the measures that cause the problems. Customer may complain about a broken computer, but there are several reasons of why a computer would be broken. These reasons would be the CTQs.
Definition – In project management, a project charter, project definition, or project statement is a statement of the scope, objectives, and participants in a project. It provides a preliminary delineation of roles and responsibilities, outlines the project objectives, identifies the main stakeholders, and defines the authority of the project manager. It serves as a reference of authority for the future of the project. – Wikipedia
The project charter is a living document, that it may be constantly changing during the life of the project. Typically, it contains several key elements which I will describe in the DMAIIC context.
1. In DMAIIC, the project schedule must be broken down for each step in DMAIIC: Do, Measure, Analyze, Improve, Implement, and Control.
2. The project team should be listed in the project charter, as well as important contacts for project success.
3. Project measures and goals should also be included. Goals should be s et up in measures of improvement from the baseline.
4. Project scope is extremely important. It marks the range and bounds of the project. In any project, there are often many places to expand the project to. While its important to make note of each possible application, its more important maintain the scope of the project rather than risking stretching the project too far.
This is the presentation I made during my technical writing class on the topic of Statistical Process Control in Healthcare. I believe the presentation gave the audience a strong sense of the power such a tool has, but didn’t make them understand the need for a uniform process for deciding on each control chart. However, it does make the audience understand the need for this technique and question why such techniques aren’t prevalent. This might push the need for more analysis of healthcare processes.
I had to deviate from the typical pecha kucha as my topic isn’t a visual like most topics. Specifically, there were more words on many slides. This format was not an effective form of presentation on this topic. I’d have preferred a method such as a video or photographic essay that would better explain and structure the topic.
As this particular niche of healthcare and systems engineering is new, the structure of a guide would alleviate difficulties with data formatting, chart selection, trend examination, and distribution modeling. Authorities in the field like Dr. Benneyan are concerned with the research behind such a structure. His research institute, Healthcare systems Engineering Institute (HSYE), is more concerned with the application and expansion of knowledge of systems engineering in healthcare rather than the weaknesses and faults of those applying such methodology. While they do foster young professionals within their organization, their work is not geared toward the younger professionals who make up most of the field, but rather they are geared toward a more academic and practical audience with higher level degrees. As such, it is the prime candidate for me to publish from within.
This published work would only be valuable as it is picked up by either those in the field or going into the field. Since the HSYE is a research lab at Northeastern University, they are perfectly suited for influencing the weaknesses from within a teaching institution. HSYE’s relation with many of the surrounding hospitals in Boston offer an avenue for this work to be brought to the awareness of industrial engineers in the field. Beth Israel Deaconess and Massachusetts General Hospital would be ideal employer to put such a methodology to use. They are two of the best healthcare providers in the world and are large enough to have incredibly complicated processes that should be measured and improved. The hospitals’ positions and the plentiful possible projects provide a prime testing ground to put the methodology to practice and gather some primary source feedback from healthcare engineers to construct a better process. HSYE’s relation with larger organizations such as the Veterans Engineering Resource Center offer a means to quickly spread the standard.
By working with these institutions and authorities, the methodology will gather the authority needed to make a lasting impact on systems engineering in healthcare. Without this authority, the methodology would struggle because I do not have the authority to make such claims with strong analysis and support.