Archives for October 3, 2018

The link between data quality and provider satisfaction

Study after study has confirmed it: American physicians are suffering from extreme dissatisfaction with their work – to the point many say they are considering leaving the medical profession altogether.

As noted in the 2018 Medscape National Physician Burnout and Depression Survey, 42 percent of more than 15,000 respondents reported feeling “burned out.”1 But this is an issue that affects more than a healthcare organization’s provider retention rates. A recent JAMA study found a strong correlation between burnout and patient safety issues, with weary providers two times more likely to act unprofessionally and make less than optimal decisions regarding patient care.2

While there are several reasons why today’s providers may be experiencing fatigue and discontent, there is one factor that keeps showing up in related surveys – frustrations using electronic health records (EHRs).

Alexia Gillen, DO, a family medicine provider and ambulatory medical information officer at Regional Health in Rapid City, South Dakota, said one EHR-related aggravation for providers is a lack of consistent, accurate data within the EHR system. “If a provider doesn’t have accurate data in a patient’s chart, they really have to struggle to be able to give accurate and appropriate care,” she explained. “It slows us down. It sets us up where we are more likely to repeat tests. And it increases the risk for error.”

A data disconnect

As healthcare organizations adopt and replace EHRs across the country, they are relying on electronic migration methods to pull and push data to where it’s needed. But it’s critical to ensure that the data is captured in such a way that providers can not only access it – but use it to make smart clinical decisions. Jonathan French, Senior Director of Health Information Systems for Quality and Patient Safety Initiatives at HIMSS, said that, too often, data simply isn’t ported to where it needs to be.

“If the EHR is not properly configured or if the provider does not leverage structured data fields during the patient encounter, data accuracy is impacted,” he said. “Inaccurate data can lead to redundant testing and potential threats to patient safety.”

Gillen added that it also leads to a lack of trust in the EHR system. When the system is populated with inaccurate data – or accurate data shows up in unexpected places – it makes it that much harder for providers to do their jobs, contributing to burnout.

“If providers have to spend their time data mining, looking through different records, trying to find what should have been extracted and put in the right place beforehand, it increases the time of visit with the patient,” she said. “But it’s not just more work during the patient encounter. When data isn’t migrated over correctly, it also increases the work providers need to do outside business hours. Providers end up staying late cleaning up charts to prepare for appointments the next business day.”

That lack of quality data also influences how patients view their encounters with doctors.

“Patients don’t want to sit there while you are searching for something in the EHR,” she said. “And if a provider misses something because the data isn’t accurate, it could lead to a repeated test or the wrong treatment.”

Getting data to where it needs to be

French said that poor data quality damages a provider’s faith and confidence in the EHR system. But having a trusted partner with specialized expertise to help with discrete data migration and mining can help to improve data accuracy.

“Third-party clinical abstractors can play an important role in improving data quality for healthcare organizations,” he said. “When working with information technology and clinical teams on EHR implementation and workflow improvement, a clinical abstraction service can provide insight into the most effective way to design interfaces and workflow so critical data elements are captured to ensure data accuracy. After implementation, they can also help alleviate the time and human capital burden associated with internal staff being overwhelmed by manual chart abstraction and review.”

By doing the work upfront to ensure the right data is getting to the right place, clinical abstraction can help providers do their jobs without undue stress and aggravation and, consequently, improve patient outcomes in the process.

“By helping to set the guardrails for data migration from the beginning, manual abstractors can help bring data over cleanly and accurately,” Gillen said. “That helps providers do a better job, increasing their own satisfaction as well as that of their patients.”


1. Medscape National Physician Burnout & Depression Report 2018, Medscape, January 17, 2018.

2. Panagioti, M. et al., “Association Between Physician Burnout and Patient Safety, Professionalism, and Patient Satisfaction:  A Systematic Review and Meta-Analysis,” JAMA Internal Medicine, 2018, doi:10.1001/jamainternmed.2018.3713,

Maintaining data integrity during EHR migration

Nearly three years ago, PwC’s Health Research Institute dubbed 2016 the year of “merger mania” in healthcare. With so many shifts occurring across the industry, many health systems have looked to mergers and acquisitions to help them survive – and thrive – in a value-based care world.1 The trend continues to this day. In fact, earlier this year, PwC reported the announcement of more than 250 healthcare M&A deals in the second quarter of 2018 alone.2

But while scaling up in this manner has multiple advantages for health systems, it is not without challenges. One of the biggest is maintaining data integrity as organizations migrate data into a common electronic health record (EHR) platform.

There are many reasons why a given healthcare organization may need to migrate patient data from one EHR system to another – to provide a single system for multiple institutions in an M&A situation, to lower the costs involved with maintaining an outdated legacy system or to eliminate dangerous data siloes that interfere with clinical decision-making, just to start. But Rod Piechowski, Senior Director of Health Information Systems at HIMSS, said that healthcare organizations should not downplay the data integrity risks involved with such a move.

“One of the biggest challenges, which is also one of the most important elements of a successful migration, is developing a plan that properly addresses the scope of data that needs to be migrated, the order in which it should be done, and the amount of time that a quality migration can take,” he said.

The risks of poor planning

Putting the right plan in place requires a lot of forward thinking, as well as cooperation among different stakeholders across the enterprise, said Michelle Holmes, Chief Operation Officer at ECG Management Consultants. Too often, she maintained, those two factors are lacking in the pre-planning stages of the process – and this can significantly increase the risk of data integrity issues later.

“You can’t just assume that there’s going to be a one-to-one relationship between data types and fields and that everything will flow over accurately. You need to understand the implications of a mapping error can be quite significant, to both providers and patients,” she explained. This is why, she said, you can’t rely just on electronic migration processes. There needs to be a manual component, for example, clinical abstraction services, as well.

When critical information is lost or corrupted, it can affect the quality of patient care. Providers won’t have access to the data they need to guarantee patient safety. “You don’t want to lose or incorrectly map drug allergy information, for example. Patient safety issues open up a whole new world of liability,” said Piechowski.

But data integrity affects more than just patient safety, he cautioned. “If you’re migrating more than just clinical data, like scheduling and billing, you run the risk of business interruptions, revenue issues, and, in the long-term, problems with your reputation,” he said.

Taken together, these factors can negatively impact provider trust, patient satisfaction and the strength of the patient-provider relationship.

Strategies for success

Piechowski said that a strong data migration strategy starts with bringing the right people to the table to map out a workable plan of action. “When building a migration team, include a wide variety of people from many different areas within the organization, with a variety of skills,” he said. “You’ll need clinicians as well as technologists, revenue specialists and others.”

And even with the strongest migration strategy, it can be important to leverage external organizations, such as manual abstraction services to ensure the consistency and accuracy of clinical information that is being migrated across the system.

He argued that abstraction plays an important role as the migration team shapes your data migration plan, helping to build and refine the rules that will be used to preserve historical clinical data.

“Abstraction can really benefit a larger migration, especially if there are elements that must be converted that require clinical insight and decision-making in order to do a successful mapping, especially where patient safety is concerned,” he said.

Holmes added that organizations should not underestimate the need for quality assurance testing. “You need to put the time and resources in place to test, test and retest before every partial and full migration,” she said. “It’s also important to make sure you have ongoing quality assurance processes and manual abstraction processes to fill in for any information that may not have been migrated or may have been incorrectly migrated.” This is where an organization like a clinical abstraction service can be especially important to your migration strategy.

As with so many information technology initiatives, it’s better to have the right scaffolding in place from the start to ensure data integrity – and, ultimately, patient safety and satisfaction.

“Consider the impact of incorrect or incomplete information on future decision-making in a clinical encounter. The same is true of business-related data if it is being moved,” said Piechowski. “It’s better to do it correctly than to do it fast.”



1. Top Health Industry Issues of 2016: Thriving in the New Health Economy, PwC Health Research Institute, December 2015.

2. US Health Services Deals Insights:  Q2 2018, PwC Health Research Institute, August 2018.