The role of quality metrics as being the primary drivers of value-based outcomes cannot be challenged. Clinical Quality Measures help healthcare providers and payers understand, compare, and track the quality of care. However, keeping track of hundreds of measures, collecting and reporting the data can be daunting.  Clinical Quality Measures (CQMs) are important indicators, but place an additional burden on the already-stressed provider.

Perhaps, these have contributed to the ever-widening care gaps and physician burnout that have become the bane of the healthcare industry today.

Thus, providers are now exploring the possibilities that technology offers to achieve higher compliance on clinical quality measures through automation.

The manual roadblock

Most healthcare IT systems today, such as the EHRs and PHMs, are well equipped to track the measures and determine the care gaps. However, it ends there. The providers are expected to take action based on the tracking data to close the care gaps.

Let’s consider a scenario based on one of the Clinical Quality Measures for 2021 Performance Period, CMS125v9, around Breast Cancer Screening. In this case, providers get the data about the women in the 50-74 age group who need to be screened for breast cancer before the end of the Measurement Period. However, this information will then need to be used by clinical staff to decide on the course of action. Let’s consider the below workflow involving manual intervention:

  • Identify the list of patients in 50-74 age group, who are due for screening
  • Schedule a screening camp for them
  • Call up the patients and manually record who will and will not attend the screening camp
  • Book the appointments for those who can make it to the screening camp
  • Call up the patient to remind a day before the appointment
  • Repeat this until all patients in the age group are screened
  • Close care gap after the eligible population is screened

Sounds tedious, right? Now, imagine the effort needed for a practice that has over 1000 patients qualifying the above criteria and multiply that with the number of measures to be complied with. Simple math tells us that this effort will need multiple FTEs. If the above workflow could be automated, these same FTEs can be used more productively on essential tasks related to patient care.

Enter the world of automation

With appropriate tools, the above problem can be solved with an automated workflow that is quicker, more responsive, and can eliminate staff burden.

With little tweaks here and there, the entire flow can be fully automated to achieve up to 85% of total targeted goals.

Apart from helping providers achieve quality metrics and close care gaps, automated outreach and communication can improve patient satisfaction thanks to timely detection and treatment.

Measurable impact

With increasing rates of chronic disease in the United States and COVID19, providers have more burden than ever before. The data to facilitate the closing of care gaps are already available to providers. Taking that data and making it actionable through the power of technology can close care gaps faster without placing an undue burden on staff. In addition, these are some of the other advantages of using automation:

  • Reduction in manual workflow lead to quick turnarounds
  • Streamlined provider workflow management
  • Quick closure of care gaps
  • Cost reduction for payers

Having said that, it’s essential to work with a technology partner who understands the needs of your customers and their patients. We recently developed a tailored automated outreach solution for one of our customers, ensuring seamless integration across diverse touchpoints, ultimately helping close care gaps.

Do write to us at itservices@healthasyst.com if you want to know more about how automation can help close care gaps.

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  • HealthAsyst Blogging Community

    The HealthAsyst Blogging Community comprises key thought leaders with decades of experience in the Healthcare IT Services industry. Their expertise ranges from product engineering, implementation, healthcare regulation, managed services to applications of data science and analytics in healthcare.

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