Patient Experience: The Science Behind Successful Value-based Ecosystem

Abhinav Shashank
Tue 04 September 2018

Remember the last time you found some amazing headphones on Amazon and you decided to buy them. You look for your favorite model number on the website, go through the user reviews, check for its availability in your region, and finally, you make a purchase and then wait for the delivery guy to knock at your door. Once your headphones arrive you check for its authenticity and by the time you actually start using them, a message arrives in your inbox to rate your experience of the purchase.

This one click on a smiley, whether it be a happy one or a sad one, makes all the difference. From the moment you logged into the Amazon’s website to the moment you tore open the delivery-box, every activity is judged based on that one single click.

Healthcare also follows the same pattern. From the patients visiting the care facility to the test they have to go through and to the medicines prescribed— everything affects the network performance and the quality of the care delivered. With each step, the chances of getting better customer feedback, i.e. patient satisfaction, can either increase or decrease. It all depends upon how a network is built and how its members traverse across multiple turns and rounds of the maze.

The looming barriers along the way to efficiency

The introduction of Electronic Health Records (EHRs) was to mark the dawn of a new technical age in the healthcare space but they grew out to be complicated mysteries of patient’s data scattered across multiple columns and rows. As a result, identifying performance trends across the network through EHRs is now a very difficult task. Since EHRs do not provide a holistic picture of the network, healthcare organizations cannot identify the actual health condition of patients and cannot compute on the measures crucial for both providers and patients.

Additionally, with the existing fragmentation in the workflows of multiple elements in the network, consolidating data and inputting measure data into reporting web interface is a very difficult task. This prevents the healthcare organization from building a proper communication channel with each provider and managing their reporting status.

Most people would agree that quality measurements serve a critical purpose, helping patients to make informed decisions and encouraging providers to work on quality. However, the entire process of assessing and assigning risk scores can be two-fold— it can either drive patients towards or away from the network, and can also put an additional burden on the shoulder of physicians.

A brief history of network performance and quality reporting

I have seen thick binders overflowing with hand-written papers describing various quality measures. A room full of data entry personnel reading patient charts, EHR screens flooded with data fields for a provider who has turned on every outpatient quality measure.

“Let’s capture them at first, then we will figure out later which ones to submit to CMS,” would always be the statement from one or many of those data entry personnel.

The sentence in itself is sufficient to describe the complications in understanding the network, building up a perfect quality reporting framework, and in convincing the physicians to go into that complex EHR screen.

How to unlock the mysteries of a health network

Despite its drawbacks and complications, participating in quality programs is good for a practice and yields better clinical and financial outcomes. However, creating and validating quality reports require an understanding of the specifications and health IT functionality to support calculation and improve reporting efficiency.

A network’s performance can be attributed in multiple ways. Healthcare organizations can follow a simple six-step procedure to unlock the hidden mysteries of their network:

  • Identify the key elements in the network: The first and the foremost thing that the organizations need to do is to identify their own network. Once they are aware of their providers, patients, gaps in performance, and other related activities, they can make further interventions. While gaining a better understanding of the network, organizational leaders need to understand the areas where they are lacking and then start working on them.
  • Stratify the high-utilizers and segregate the processes: Stratification is not just about identifying the high-risk patients in the network, but also about segregating each and every process. Healthcare organizations need to stratify their activities based on the high-utilizers and low-utilizers. At this stage, it is necessary for organizations to get a detailed understanding of their providers, patients, activities, and other major factors affecting the network.
  • Collaborate with every member in the network: Once everyone is aware of the looming discrepancies in the network, they can work together to bridge those gaps. Collaboration is a very important factor. Every member needs to take care of their quality measures in order to reduce the chances of any discrepancy in the final reporting procedure. Here, automation and machine learning can play a vital role in easing the process of creating, picking, and validating the measures.
  • Review the individual and overall performance: Along with individual efforts, a uniform review procedure is to be established to ensure the integrity and accuracy of the reporting measure. Providers should be capable enough to track their performance on every measure and cut through the noise to learn about the performance of every measure over time. EHRs do not provide a holistic picture. Therefore, other datasets such as claims data, ADT data, and others can turn out to be crucial in offering an unprecedented visibility into the network.
  • Manage the workflows to streamline the processes: The reporting procedure is iterative in nature and hence manual intervention is not only time-taking but often ineffective and not always error-free. Establishing manageable workflows is extremely critical to streamlining the procedure of extracting, sharing, and managing patient attribution data along with other important data elements. Providers should be well-aware in time on how they are performing in comparison with their network to track their efficiency and take remedial actions to stay on the right course of action.
  • Report to get the best out of your network: Final and the most crucial step is reporting on the quality measures. Reporting process should be automated to reduce the chances of discrepancy between the data points reported and the ones submitted for review. From the initial to the final stage, the entire process should be kept under review of the quality metrics on which the organization is reporting on.

The road ahead

The constant push towards linking traditional fee-for-service models to value-based reimbursement models has made the entire process of reporting on various metrics quite time-taking. Such time-consuming processes reduce the efficiency and sometimes become a hindrance to the ultimate goal of providers— delivering patient-centric care. However, it is a necessary task which they need to do and technology is the only answer to all these inefficiencies. Once healthcare organizations master the process of managing their quality they can look into the hidden aspects of their network and can unlock the doors to 100% efficiency.


To know more on how you can improve your process of quality reporting with a unified healthcare data platform, get a demo.

For more updates, subscribe.

Join Team Innovaccer at PCMH Congress 2018 at booth #103 in San Diego Convention Center, San Diego, CA on 14 – 16 September, and know how we can assist you in understanding the hidden success opportunities for your network.

Please enter valid .
Please enter valid .
Please enter valid comment.