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QualOptima v1.2

QualOptima Professional Practice Application Version 1.2

Electronic Triggers

q_iconThe use of “triggers” as words or phrases in quality and risk management operational processes is well recognized and implemented in hundreds of hospitals in multiple countries. Traditionally, triggers were called “clinical indicators” of sub-optimal care to identify cases for peer review, not only for quality improvement but for patient safety processes. The “global trigger tool” of the Institute for Healthcare Improvement is now implemented in hundreds of hospitals in multiple countries as clues to identify adverse events (AE’s), widely accepted as an effective method for measuring the overall level of harm in a healthcare organization. The Joint Commission adopted the use of triggers to be developed from performance criteria for Ongoing Professional Practice Evaluation, which convert to Focused evaluation using trigger methodology. With less than 15% of electronic medical record data in structured data fields (such as drop-down lists), machine reading narrative text in discharge summaries, history & physical examinations, operative reports, radiology and pathology reports, QualOptima technology is an essential tool to read and learn from triggers.

QualOptima electronically machine reads both structured and unstructured narrative text using defined triggers, both from Q’s lexicon of triggers and from the healthcare organization’s performance criteria. The burden of manually reading medical records and electronic databases for triggers is illogical and financially unfeasible if FTE’s are required for manual processes. The learning functionality of the technology then continuously develops organization-specific triggers from their own experience with performance metrics. Triggers have their own inherent value to identify adverse events for patient safety, but identify patterns and trends and specific cases for drill-down using the peer review functionality of QualOptima. The combination of QualOptima trigger technology is far more robust and valuable when integrated into the other QualOptima v1.7 applications.

Triggers in Ongoing Professional Practice Evaluation (OPPE)

Triggers, as required in Joint Commission Standards (see Elements of Performance 5) for healthcare organizations to be accredited, are used to identify sub-optimal outcomes or events as part of Ongoing Professional Practice Evaluation (OPPE). OPPE should convert to FPPE based on triggers that indicate the need for performance monitoring and can be clearly defined single incidents or evidence of a clinical practice trend. The performance criteria offer opportunities to read and learn from patient records and hospital documents and data to refine performance criteria into these triggers.

The Standards contemplate when the OPPE process converts to the FPPE process. Elements of Performance 2 requires that organized medical staffs develop performance criteria to evaluate the performance of practitioners when issues affecting the provision of safe, high quality patient care are identified. Examples of such performance criteria might include but not be limited to:

  • Small number of admissions or procedures over an extended period of time that raise the concern of continued competence (zero data is in fact data)
  • Growing number of longer lengths of stay than other practitioners
  • Returns to surgery
  • Frequent or repeat readmission suggesting possibly poor or inadequate initial management/treatment
  • Patterns of unnecessary diagnostic testing/treatments
  • Failure to follow approved clinical practice guidelines (may or may not indicate care problems, but why the variance should be evaluated)

So healthcare organization must evaluate and correlate the relationship between performance criteria and triggers; reading for triggers logically includes reading for performance criteria. QualOptima v1.2 electronically reads both structured and unstructured existing data from disparate data sources for both triggers and performance criteria.

Focused Evaluation When there is Zero Data

Zero data is, in fact, data. It may be evidence of good performance, e.g. no returns to surgery, no complications, no complaints, no infections, etc. However, it is also important to recognize when a practitioner is not performing certain privileges over a given period of time. TJC states that it would not be acceptable to find at the 2-year reappointment that a privilege has not been performed for this timeframe. Zero performance of a privilege should be evaluated to determine possible reasons, such as the practitioner is no longer performing the privilege (now doing laproscopically, for example), taking patients needing the procedure to another facility, or a typically rare or infrequent privilege).

When OPPE Converts to Focused Professional Practice Evaluation (FPPE)

OPPE should convert to Focused Professional Practice Evaluation (FPPE) based on triggers that indicate the need for performance monitoring and can be clearly defined single incidents or evidence of a clinical practice trend. Triggers and performance metrics in a focused review process should logically be expanded to customize triggers to read for identification of root causes of data generated from the global triggers of the OPPE processes. For example, in the zero data discussion above, reading for specific triggers that would explain evaluation of a practitioner no longer performing a clinical privilege could readily be determined and analyzed with trigger methodology.

An even more basic example of triggers is identifying preventable hospital deaths. The Institute of Medicine published To Err is Human; Building a Safer Health System (2000) estimating that adverse medical events result in 44,000 to 98,000 preventable deaths in US hospitals every year. In an article in Health Affairs in 2011, regarding use of the manual “Global Trigger Tool” of the Institute for Healthcare Improvement (IHI), findings from triggers concluded that adverse events in US hospitals occur to one-third of hospital patients and may be even 10 times greater than previously measured.

For example, Ascension Health has published the results of their quality goal established in 2003 to reduce preventable deaths in their 69 acute care hospitals by 900 each year. By fiscal year 2010 they reduced their preventable deaths by more than 1500 people annually and, by some calculations, by more than 5,000 people annually (average of 22 to 72 preventable deaths/hospital annually). QualOptima trigger technology is the ideal solution to this urgent need for a strategic imperative for zero tolerance for preventable death and patient harm.

QualOptima Trigger Data as Standard Element of Master Data Management

Implementation of the QualOptima trigger technology should be used to simply identify preventable hospital deaths, as well as all adverse events, in a single view as a vital element of the Master Data Management data display. Recommended example for standard data display include at least:

  • Adverse Events per 1,000 Patient Days
  • Adverse Events per 100 Admissions
  • Percent of Admissions with an Adverse Event

Adverse Event Reporting Not Reliable Compared w/ Triggers

Traditional efforts to detect AEs have focused on voluntary reporting and tracking of errors. However, public health researchers have established that only 10 to 20 percent of errors are ever reported and, of those, 90 to 95 percent cause no harm to patients. Hospitals need a more effective way to identify events that do cause harm to patients, in order to select and test changes to reduce harm.

The Institute for Healthcare Improvement (IHI) has demonstrated in reported studies that adverse event (AE) detection methods commonly used by healthcare organizations to track patient safety – voluntary reporting and the Agency for Healthcare Research and Quality’s (AHRQ) Patient Safety Indicators – fared very poorly compared to other methods and missed 90% of adverse events. The IHI manual Global Trigger Tool, for example, found at least 10 times more confirmed, serious events than these other methods. IHI concluded that reliance on voluntary reporting and the AHRQ Patient Safety Indicators could produce misleading conclusions about patient safety and even misdirect efforts to improve patient safety.

The electronic QualOptima Trigger Tool transforms the manual process and provides more rapid and complete actionable insight into both OPPE and FPPE sub-optimal outcomes data. When integrated into the QualOptima analytics tools of QualOptima v1.3 and v1.7, and the more robust analytics of QualOptima v2.0, the clinical variables technology identifies root causes for solutions. QualOptima trigger technology gives meaning to the overused marketing slogan “actionable insight”.

QualOptima Embedded Trigger Technologies

QualOptima v1.2 embeds a combination of technologies in the Qualytx database. Machine reading technologies implement tools commonly designated as natural language processing (NLP) for conventional semantic analysis, as well as unique technology that identifies the important concepts and relationships within unstructured data. QualOptima customers can use both pre-defined dictionaries of important words or phrases, or machine read with technology to find them.

The learning functionality of QualOptima v1.2 technology empowers our customers with technology that so far exceeds manual trigger processes that Q believes it is a vital part of every healthcare related enterprise outcomes analytics for Master Data Management.

QualOptima Common Data Platform for Trigger Analytics

OPPE inherently anticipates coordination of efforts between the Quality/Risk processes and staff, the Medical Staff Office, and the organized medical staff. In most healthcare organizations, the Medical Staff Office will undertake recording clinical information generated by the quality/risk staff and integrating that data into the credentialing/re-credentialing process, while individuals and entities of the organized medical staff will perform the peer evaluation of that information.

The QualOptima common data platform across these traditional functional boundaries is the ideal solution for all healthcare organizations to implement trigger technology with healthcare data science and analytics. Use QualOptima to achieve optimal clinical, operational, and financial outcomes.