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- Determine if an HLA genetic test occurred and view available results
- Order HLA test from the EHR
- Store HLA test results in the EHR
- Order medications through “order set forms”
- See everything on a single order entry screen
The SunriseTM platform is unique because we designed it to be a central nervous system of health care organizations. It constantly gathers, aggregates, evaluates and acts on information for optimal clinical decision support.
Our clients are using these capabilities to integrate evidence-based information at the point of care. For example, a team at the U.S. National Institutes of Health Clinical Center (NIH CC) recently developed a program for Sunrise using pharmacogenetics, which evaluates genetic information to predict a patient’s response to medication.
The goal was to provide newly available information at the point of care to help clinicians reduce the risk of adverse drug events. The Journal of American Medical Information Association (JAMIA)* featured this patient safety project in a recent article.
Starting with safety checks for three drugs
The NIH CC team wanted a tool to help clinicians as they place orders for three medications: abacavir, carbamazepine, and allopurinol. They treat different conditions, but the same genetic variant (HLA) can predict severe reactions for all three drugs.
NIH CC developed algorithms, which it integrated directly into the EHR with a Medical Logic Module (MLM) program. As soon as a clinician orders one of these drugs, the MLM checks to see if HLA genetic test results are in the patient’s record.
The clinician can see on the order form if lab results are present, absent, pending, or not ordered. Then the MLM determines if the prescriber can place the order, place it but require an over-ride reason, or be blocked from placing the order.
Now NIH CC clinicians can:
Since implementation, 154 different prescribers have placed more than 725 medication orders for over 230 patients for these drugs. NIH CC is beginning work to apply algorithms to other medications.
Because Sunrise draws from all of the information available in the EHR and can evaluate it, NIH CC can use MLMs to continually improve this powerful decision support tool. The organization’s pharmacogenetic MLMs provide consistent, automatic checks for potential warning signs. These processes reduce the risk of adverse drug events and keep patients safer.
* Source: “Integrating pharmacogenetic information and clinical decision support into the electronic health record” Barry R Goldspiel, Willy A Flegel, Gary DiPatrizio, et al. J Am Med Inform Assoc 2014; 21:522-528. Originally published online December 3, 2013. doi: 10.1136/amiajnl-2013-001873
You can’t have a separate electronic health record (EHR) for every specialty in medicine. On the other hand, if you have a general EHR, it won’t have the “brains” to support specific workflows. Fortunately, we can customize SunriseTM EHRs with Medical Logic Modules (MLMs).
3 of my favorite MLMs
MLMs are packages of computer code that are the building blocks of electronic clinical decision support. Their potential to improve patient safety is unlimited. Here are three of my favorites:
1) Insulin dose adjustment
When caring for diabetics in a critical situation, clinicians must have fine control of blood sugar levels. A nurse under pressure has to rapidly gather information, calculate dosage and document the chart. One of our clients developed an MLM algorithm using 100 data points to assist in these situations.
Now the nurse simply enters the current blood sugar level. The MLM uses that information, combines it with other data (i.e., previous blood sugar levels and insulin doses) and the patient’s current insulin dose. It then reads the algorithm to acquire the algorithm recommendation for the next dose and documents the chart automatically.
2) Automated discharge summaries
When patients are discharged from Springhill Medical Center (Mobile, Ala., U.S.A.), an MLM pulls data from the entire hospital visit including lab results, radiology, diagnostics, problem lists, discharge medications and more. With just one click, physicians can now pull all of this information into the discharge summary automatically saving time and improving care coordination.
Now that the process takes five minutes, instead of 15-20 minutes, physicians are much more likely to finish their discharge summaries. The utilization rate of this automated discharge summary process increased from 6% in January 2013 to about 70% just five months later. (Read more in a recent blog post, How Springhill Medical Center simplified discharge summaries)
3) Oncology treatment calculators
As an oncologist, I am particularly fond of MLMs that improve treatment for cancer patients. My favorite MLMs in this space read the chart and display the patient’s history – whether in an order set, note or summary. This information is critical when determining a course of treatment. Some medications have a lifetime maximum dose. An MLM can calculate the delivered amount of any medication.
For example, a pediatric patient who has had 3-4 years of treatment could have 18 charts. MLMs can save clinicians the effort and error-prone method of opening each encounter to calculate a lifetime dose of medication. Instead, the MLM can quickly query the charts and provide a total.
We developed the Sunrise platform around the core concept of continuous patient evaluation, and it embraces MLMs. We believe clients must have this capability to deliver the best quality health care possible.
Clearly our clients agree. To date, we estimate there are about 20,000 MLMs embedded within Sunrise platforms. While some are likely similar in concept, each one is customized to the client site.
MLMs give control back to healthcare organizations
Most software and computer code is completely locked down by the developers. Software typically offers only one set of instruction code, so the organization has to adapt to the way that software works.
In Sunrise, the healthcare organization can change the behavior of the software with MLMs. Now the software must adapt to the enterprise, instead of the other way around.
Systems without MLMs have to build everything out specifically. You’d have to wait a year or two for the development process to provide what you need. But clients who can write their own MLMs don’t have to wait for production.
The hardest part of developing an MLM is agreeing on the rules. Once an organization agrees on how the architectural set should behave, writing the actual MLM only takes a short time. And you don’t need formal computer education to do it.
Random activity does not drive quality
Computers behave consistently. With the right instruction set, they can efficiently process information to help clinicians make consistent decisions. It’s that consistency that drives quality.
Do you use MLMs? If so, how do they affect the quality of clinical decision support at your organization?
When developing the Sunrise electronic health record (EHR) platform, we had a different vision than our competitors. We modeled Sunrise after one of the most intelligent networks: the central nervous system (CNS).
Evaluation is at the core of Sunrise
The CNS governs most processes in living organisms. It senses information, detects changes, evaluates input and takes action. Constantly monitoring, integrating and evaluating countless transactions, the CNS is the intelligent core of our being.
From the earliest days of development, we envisioned Sunrise as the CNS of the healthcare organization. Our competitors started with a different approach. They designed a data repository to replace paper. Only as an afterthought did they begin to develop rules to do more than just move data electronically from place to place.
In contrast, we designed (and continue to develop) Sunrise around the core concept of evaluation. It not only monitors thousands of data points, but it interprets and acts on them, too.
Keeping constant watch over every detail
Health informatics research consistently finds we can improve outcomes with electronic systems that intelligently monitor patients 24 hours a day, 7 days a week. Similar to the way the CNS processes sensory information for us around the clock, Sunrise is always on duty for patients.
Science has proven that with focused attention to detail, data can help detect potential problems. For example, bilirubin levels in newborns can help identify babies at risk for serious illness, but only if we are carefully watching for that specific indicator.
Automating repetitious work
Even with electronic records, there is a lot of manual labor in medical care, such as creating notes, orders, and prescriptions. It is time-consuming work for clinicians. It is also repetitious and prone to error as clinicians are often interrupted and overloaded.
To take better care of patients at a lower cost, healthcare organizations look for ways to eliminate manual work. They look for more efficient ways to save time and improve quality.
That’s where Sunrise can help. It can replicate clinician decision-making by applying rules instantaneously and create documentation. This type of automation saves time and improves patient safety. Much like the way our CNS automates every heartbeat and breath we take, Sunrise can automate repetitious (but critical) work.
Sunrise can accomplish all of these processes in “blink speed.” You can’t pull a chart out of a rack as quickly as Sunrise can complete complex algorithms to assist in clinical decision-making.
The advantages of awareness and availability
We can alert off of any data that is inherently in Sunrise. All the patient data is already there, and it doesn’t have to manage a separate alerting database.
With some systems, clinicians have to decide to send information to the EHR process. It would be as inefficient as if you had to send sensory data to someone else’s brain to process. “Is the stove hot? Should I pull my hand away?” Clinical decisions are just as time-sensitive and deserve every efficiency we can provide.
With the central nervous system as our model, Sunrise excels at monitoring information reflecting what is happening with a patient. All of these intelligent capabilities help clinicians improve patient safety.
Most people agree that Electronic Health Records (EHRs) have significantly changed the way physicians conduct exams. But there is some debate as to whether or not that change helps physicians and patients communicate better.
Do EHRs live up to their promise of making patient information more accurate and accessible at the point of care? Or do computers (and tablets) create barriers between patients and physicians?
To help improve patient-physician relationships, the American Medical Association (AMA) recently researched the effect of electronic devices on communications in the exam room. It reviewed more than a dozen studies on the topic and revealed plans to encourage EHR adoption in a recent report.
Physician actions shape patient perception of EHRs
Research indicates that EHRs do not negatively affect patient satisfaction. In fact, one study found that exam room computing helped improve communication about medical issues, comprehension about decisions and overall visit satisfaction.
During effective clinical encounters, EHRs are becoming a third participant in communications between patient and physician. Some authors suggest that computers enable better sharing of information – and decision-making power — during the consultation.
Effective communication with an EHR largely depends on the physician’s skill set. According to one researcher, “Physicians with good baseline communication skills tend to integrate exam room computing into their relationship with patients, whereas physicians with poor baseline skills tend to create communication barriers when using computers in the exam room.”
The factor that most consistently influences patient perception of EHRs: physician attitude. If they embrace the technology and the value it brings, then so will patients (click to tweet this idea).
Small steps can help minimize disruption
Physicians who successfully incorporate computers and EHRs take an “inclusive” approach in the exam room. For example, they might install mobile monitors so patients can see the data, too. Or they use devices in a way that they can easily maintain eye contact with patients.
The room needs to be arranged so that the physician is facing the patient during conversation. Physicians should position the computer so the patient is not looking at the physician’s back.
Throughout the visit, it’s important for physicians to explain what they are doing behind the keyboard. If they are ordering lab tests or logging off to protect patient privacy, a little information can help relieve uncertainty.
AMA encourages effective EHR adoption
The report concludes with two action steps regarding exam room computing and EHR use, adopted by the AMA:
1) AMA will share tips and resources with physicians through AMA publications
2) AMA will encourage physicians to seek feedback from patients through satisfaction surveys
These are two important steps in fully integrating EHRs into the exam room. What else do you think needs to happen to integrate them into patient-physician communications?