Enhancing Patient Care with Clinical Documentation Improvement

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Clinical documentation improvement (CDI) ensures that health services are accurately documented and helps healthcare coders and physicians work toward improved patient care while also streamlining productivity.

When meaningful clinical data is captured, organizations can ensure improved quality reporting, clinician productivity, and even better clinical information delivered at the point of care.

Phoenix Children’s Hospital recently opted for CDI at its outpatient clinics with Medicomp Systems.

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With about 400 licensed inpatient beds, Phoenix Children’s Hospital is one of the five largest children’s hospitals in the country, explained Chief Medical Information Officer and VP Vinay Vaidya.

For the last 10 years, Vaidya has focused on implementing electronic systems at Phoenix Children’s. More recently, that focus has altered to include reaping the benefits of those past implementations. It’s important to help physicians make patient care faster, safer, and more efficient.

Phoenix Children’s had been using Allscripts for many years as its EMR vendor across all locations, including inpatient, ambulatory, and emergency, Vaidya told EHRIntelligence.com.

“What happened in the first almost 10 to 12 years, we had fully developed our electronic EMR and other electronic system capabilities on the inpatient side,” he explained. “We have been fully electronic for many years on the hospital side, but our ambulatory side was still completely on paper.”

That was the driving force behind changing the hospital’s clinical documentation process. Starting about four years ago, Phoenix Children’s decided to convert the full ambulatory outpatient clinic to an electronic system.

“Our inpatient documentation was going well with Allscripts, but we are always looking towards new, innovative solutions,” Vaidya said. “That is the period of time about four years ago we came across Medicomp.”

“Every single symptom, sign, medication, surgery, drug, operation procedure, almost a repository of more than 360,000 terms, they have structured and coded with every possible common coding schema, such as ICD-10,” he continued.

Having 360,000 terms can be overwhelming, but they were built along disease patterns, Vaidya stated. If a physician entered that a patient had asthma, or tried to research asthma in the database, it went out to all related items that were related to asthma and it brought them together in a manner of an automatic template that was a quick, rapid initial draft.

“What we got from Quippe, from the documentation solution, was a way to almost have not the final form of the template, but an initial rough draft with the heavy lifting quickly, rapidly across our 30 divisions,” he explained.

There are lots of prompts to simplify the process for how physicians use the EHR for notes, Vaidya said.

“We did a rolling go live about three or four divisions, each three to four months, so that we could focus on them and then move onto the next one,” he stated. “It took about two and a half years.”

“At the end of last year when we finished our implementation, we then focused on getting this data back from their notes and creating real-time dashboards that impacted care,” Vaidya added.

Having more specific dashboards for CDI has exceeded expectations as well.

“We often say that we have to convert paper to electronic, but unless you see the benefit of electronic, what next?” Vaidya posited. “Just stopping at electronic actually increases the burden of all this without really seeing the benefit.”

Walking through the process of using the EHR, Vaidya noted that the colorful, busy, complex looking dashboard is very easy to understand once an individual has become accustomed to it. He then described what a physician would see on the dashboard, explaining how to read the data.

“You can very easily see that from the EHR data without any other additional entry by any research nurse,” he said. “For example, what our physicians are seeing is a complete profile of 558 juvenile idiopathic arthritis patients in the last two years with almost 3,000 visits.”

“Then they do what is known as a two-week, three visit planning,” Vaidya continued. “This is PDP. Instead of just rushing into the patient’s room in a 30-minute visit and trying to understand what is going on, every Friday they plan for patients who are going to come two weeks from now. You can see these other patients who are going to come.”

From there, it can also be narrowed down by physician. If there are three physicians, the system can narrow the patients down to nine who are seen by a specific physician.

A physician could also narrow down her view to see that a patient has been seen eight times. Different colors in the system depict how the patient has responded to different treatments.

“This is how the physicians go around, and you can see how each patient looks so different from the other based on what is the pattern of that particular disease,” Vaidya explained.

“This is real-time data and this is where you saw that the disease had to be documented in the note, because without that documentation of clinically inactive disease we cannot measure it.”
Challenges with improving clinical documentation efficiency

There is no magic formula with clinical documentation and finding an applicable system for an organization, Vaidya maintained.

“You cannot take shortcuts. You cannot not capture things that are critical and essential,” he stressed. “Some of the key things that help us is really working very closely with our providers. We often consider that we just don’t take the material from physicians and light contractors, or just build something and expect that it would work.”

Every stage, from fact-finding to rapid trials to quick proof of concepts, Phoenix Children’s works to understand the physicians, the disease, and the challenges, Vaidya said.

“We try to make things simple and easy,” he noted. “One single thing was in rheumatology, where they deal with 70 joints. Now can you imagine the EMR template that is having 70 joints and clutter? So we tried to remove the clutter by just having one button and asking them to focus on which joint they need.”

“When [physicians] focus on the elbow, [the system] will just show the right elbow, whether there was swelling, whether there was pain, there was tenderness,” Vaidya continued. “All these things, minute and careful attention to detail, understanding the disease, understanding the physicians and reiterative cycles of correction, improvement, enhancing and teamwork are important.”

There is no secret recipe to finding guaranteed success with clinical documentation, he added. But spending a lot of time with the recipe, and focusing on finding the right ingredients can help lead to success.

A system can include every single measure of every single disease, and physicians are faced with more quality metrics and more things to document, to do, and to check, Vaidya said. Overburdening physicians is a very real concern.

“A template could look good, but how visible is it?” he asked. “Is it practical? Are [physicians] using it and is it increasing the documentation burden?”

“We use data at every single stage,” Vaidya added. “To build templates. To do disease management. To do population management. And we use the same approach to measure our burden of documentation.”

The CMIO explained that Phoenix Children’s tries to regularly see the timeline of when the physicians complete documentation.

“Are they taking the work home on Saturday or Sunday? You can see small slivers, two people and three people, and are they completing the documentation by 5 p.m. on the date of service,” Vaidya said, discussing an example of the Quipp program. “Almost 56 percent of them are completing that.”

Using the rheumatology example again, Vaidya noted that half a million rheumatologists have done about 10,000 documents. Nearly all of the documents – 97 percent – were done within 24 hours. Additionally, almost 86 percent are completed by 5 p.m. of the date of service, including billing, coding, structure, documentation, and ICD disease classification.

“We were very encouraged seeing results like this,” Vaidya said. “We are not creating a lopsided data collection clerk out of a physician. It was nice to have validation through data.”

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Photo courtesy of: EHR Intelligence

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