Medical Practice Case Study Categories

The data ultimately speaks for itself so here at Claimocity we have a team that is dedicated to gathering and presenting the data in case studies, intake surveys, product comparisons, bench-marking, scientific analyses, measurements, time studies, A/R evaluations, and deep dives into impacts on productivity, efficiency, and accuracy.

Our goal comes down to constant improvement around three core key areas: revenue efficiency, time efficiency, and effective decision making. Everything we do from product development to data gathering is to give practices and providers more time, money, and relevant information.

Claimocity Medical Big Data Analytics Testimonials

“In 2017, we were generating 2.3 million in total revenue for our practice. By 2018, we were above 3 million and by 2019 we were a hair over 3.9 million. By the end of 2020 we are now projected to hit over 5 million.”

-Dr. K. Yuen, Internal Medicine, Practice Manager

“Within the first year we saw increases in every notable metric and by the end of the first twelve months, we were setting the best marks for our practice over the last ten years. Clean denials and missed or lost charges went down. Revenue per encounter, clean claims, and total revenue hit our highest benchmarks.”

-Dr. Steven Fritz, Senior Partner and Business Manager

Claimocity Medical Big Data Company Testimonials

“Our executive team approved participation in a voluntary two year time and revenue study in order to evaluate the quantitative and qualitative value compared to the numbers we were generating with the prior software in order to justify the switch. Within 24 months we had a 41.6% net revenue rate increase as well as an average of 38.8 hour savings per month per physician across our practice, which was a remarkable result.”

dr chacinF. Chacin M.D., Hospitalist Practice, Founder and CEO

Revenue Study: Hospitalist Charge Capture Process

Core Question: Does accelerated charge capture save time and make doctors more money?

Summary of Findings: Switching to just the Claimocity accelerated charge capture, a native component of the full-service end-to-end mobile practice management and billing app, resulted in a 9% increase in time efficiency and 11% increase in revenue efficiency for an Internal Medicine hospitalist group in Florida. This equated to an extra half hour per day per provider and an extra 41K for the practice over 2 months.

Full Study

Published 4/14/2020

Impact Study: New Client A/R Audit and Revenue Changes

Core Question: Is there an initial dip in revenue when switching to Claimocity?

Summary of Findings: A common concern among new clients is what level of initial revenue dip to expect when switching from their current billing, A/R, and/or charge capture software to the all-in-one Claimocity solution. This study follows a single practitioner through the process and finds that instead of seeing a dip, the move from a stand alone legacy software to a full-service option generated a 28% increase in monthly revenue. As a powerful secondary benefit, this case study exposes that moving from a one dimensional billing system to an intelligent end-to-end process uncovers and triages any live claims stuck in bottlenecks within the former A/R process, converting them to additional total revenue. In this case study an extra 52k was uncovered and converted.

Full Study
Published 6/11/20

Impact Study: Transitioning from Paper Billing

Core Question: Is there an initial dip in productivity when switching from paper billing?

Summary of Findings: A common misconception about transitioning from a paper-billing system to the Claimocity full service software with mobile charge capture is an expected initial loss of productivity and time during the implementation and learning process. A pulmonology practice in California was expecting and preparing for between a quarter and a third loss of encounters to account for the transition but the actual end result was an increase in workflow productivity as measured by total number of encounters on a practice level. In spite of the change over, total encounters rose by 7% within the first 14 days and by 13% within the first 90 days. The time efficiency of the app and charge capture more than offset the learning curve, additional support needs, and transition issues.

Full Study
Published 2/8/20

Value Study: Stand Alone Charge Captures

Core Question: Do stand alone charge capture options create the same value as end-to-end billing?

Summary of Findings: Stand-alone charge capture software options such as pMD, MDCoder, Ingenious Med, PatientKeeper, SwiftPay MD, NueMD, Medaptus, DrRounds, and others saturate the mobile medical app market. Often referred to as one dimensional or flat software options because of their singular and specialized focus on the charge capture segment of the RCM process, these software options perform very specific services efficiently (measured by time efficiency) but the associated cost comes in the form of lower revenue efficiency. As a stand-alone service they are missing the end to end revenue cycle intelligence necessary to drive higher efficiency models and larger bottom line revenue totals. The piecemeal approach to billing generates gray area sticky points and A/R bottlenecks that slip under the radar for busy doctors and practices who do not even realize there is an issue. Stand-alone charge capture software users lose an average of 10-16% of revenue to expired claims that needed a higher level of end to end billing expertise to finesse or push these charges through to the payout.

Full Study
Published 6/6/20

Revenue Study: Coding Efficiency on Total Revenue

Core Question: What is the level of impact of coding efficiency on total revenue?

Summary of Findings: The stakes are high when it comes to coding efficiency. Even a 1-2% improvement can have up to a 20% impact on revenue. Unfortunately, this works both ways and a negative efficiency shift can leave hundreds of thousands of dollars on the table. The exact amount of variance and impact depends on the specialty, geographic region, patient demographics, insurance types, practice size, and other variables, but in every case study we found two results. Once that higher coding efficiency created higher total revenue and lower risk levels, and two, that the majority of coding inefficiencies stemmed from patterns created by a central set of encounters with unclear coding guideposts that cause physicians to either play it safe and under code (losing earned revenue) or over estimate the value of that encounter and over code (setting up audit risks and repercussions).

Full Study
Published 5/6/20

Time Study: Code Assist

Core Question: What is the time savings value of using Code Assist?

Summary of Findings: Using code assist during complex coding encounters reduces the time cost of coding to 2-3 seconds (from an average of 1-3 minutes) per encounter used, reducing workload stress levels and enabling a seamless workflow transition into the next encounter. Additionally, since the majority of under and over coding efficiency issues occur during complicated or unclear encounters, by reducing the risk of under or over coding in the keystone gray area encounters (with unclear coding situations) a physician’s overall coding efficiency and benchmarks significantly increase over time, helping to eliminate the revenue losses associated with consistent under coding and legal/financial audit risks associated with consistently over coding.

Full Study
Published 5/26/20

Time Study: Mobile Charge Capture by Encounter Type

Core Question: Do mobile charge capture claims hold up under a closer look?

Summary of Findings: Though the aggregate data oversimplifies the time stamps of the accelerated charge capture feature to an average of 9 seconds per encounter, there is an important distinction between initial and follow up encounters. The results show that charge capture on initial encounters averages 15 seconds while that of follow up encounters averages less than 2 seconds. Meanwhile, stand alone charge capture alternatives advertise charge capture times as low as 2-7 seconds but a breakdown analysis shows that as a group they average 32 seconds per initial encounter and 18 seconds for follow up encounters, significantly higher than stated. In fact, the 2-7 second average was only applicable in 12% of encounters, with the other 88% requiring a much heftier time commitment than expected.

Full Study
Published 5/22/20

Value Study: ICD-10 Smart Directory

Core Question: Does a streamlined ICD-10 directory help streamline the coding process?

Summary of Findings: Using a set of intake and exit surveys, new clients were asked their comfort levels, familiarity, and time expenditures when it comes to coding. At the end of the survey, having used the ICD-10 directory the entire time, they were asked to rate the value and the results show that it was positively received and the providers felt that it streamlined the coding phase of billing by 5-10%.

Full Study
Published 3/18/20