resources from my career
There will inevitably be age grouping and age range requirements for many of your reporting needs, and the know-how to quickly and accurately calculate a patient's age is crucial to developing trust among your customers and colleagues.
Sometimes it is critical to calculate the age in your SQL language before the data even gets exported from the source.
But if you have the source data (and it includes the date of birth!) you can easily create age and age group calculations in Access or Excel. If you will be using Access to join tables and create multiple reports from the same data set, you should consider calculating the age (and establishing any age groups or ranges) within your Access queries. Alternatively, you can add your Age field "on the fly" using a quick formula in Excel, before you begin work on your final reporting.
This article explains how to compute a patient's age using each of these tools.
The purpose of publishing this study is not really to share outcomes, though those might be useful. The reason I want to share this study is to assist other wishing to devise similar ones.
There are several medical treatments for morbid obesity, including medication, surgery, and prescribed diet and exercise plans. The purpose of this study was to evaluate the effectiveness of bariatric surgery as a treatment for morbid obesity, analyze the impact to utilization, and to evaluate other treatment options in comparison to surgery.
It's a common idea that once a patient undergoes weight loss surgery, all is well. They lose the weight and become healthier because of it. However, in 2016 I was introduced to the idea that not only do bariatric surgery patients regain the weight within 10 years, but gain back more weight than they started with. To say this is troubling is an understatement.
Are viscosupplementation injections effective for treating osteoarthritis (OA) of the knee? Do patients who have the injections still elect surgery to treat OA of the knee?
These were the main questions posed by Our Medical Group in 2017.
In order to answer these questions, I designed a retrospective study of Medical Group patients who received the viscosupplementation injections to quantify their history of injections and whether they eventually underwent knee surgery.
Conclusion: Time in Therapeutic Range does not always lead to lower stroke rate
In a group of patients I recently studied, patients with the lowest TTR % (as calculated using the Rosendaal Method in the patient's first year on Warfarin) had the lowest stroke risk.
Also, I found that patients with the most frequent testing had the lowest TTR.
This study consisted of 210 NVAF patients who are managed by our HMO. Fifty-seven of the patients (37.25%) have their INR testing and Warfarin dosing adjustments through our Anticoagulation Clinic while the other 153 patients have this choreographed by their PCP's office.
Click "Read More" below and over to the right...
This is an example of how to calculate a return-on-investment using an economic benefit model.
Creating a Return on Investment model for a Disease Management is complicated because it falls on the concept of actually trying to measure utilization (namely hospitalizations and ER visits) that didn’t happen. Thus, an unconventional approach was called for. Due to my training in Economics and after a month or so of research, I found a risk management model and adapted it for my needs. I also contacted the original author of the model (Ian Duncan, FSA, FIA, FCIA, MAAA) in order to get some insight.