Establishing lasting quality through a hybrid model:

Top health care system's stroke department's rise in divisional rankings

Introduction

Formed in response to the growing need for easier access to health care, this Q-Centrix partner is one of the nation’s first hospital companies. With over 2,000 sites of care, it is today among the country’s largest health care systems.

The system is comprised of unique divisions sharing a common goal – excellent quality patient care. One of its divisions was struggling to uphold this goal. The division’s neuroscience leadership knew a change was necessary to improve its stroke care ranking among its peers. With more than 25 years of experience in executive leadership for several leading health care systems, the leader’s expertise in quality helped her identify staffing, data management, and technology as areas of growth. This executive and the division’s health care team took the next step needed—partnership with Q-Centrix to provide clinical data management expertise and market-leading technology.

Challenges

Meaningful care insights require more training and resources than ever before. The division faced a series of staff, training and clinical data management challenges which contributed to higher than desired investment and a low internal benchmark among its peer divisions.

Staffing inefficiencies

  • Two hospitals within the system had no onsite stroke experts for nearly nine months
  • Stroke coordinator duties were inconsistent and varied between sites
  • 70% of stroke coordinators had competing assignments
  • Stroke coordinators routinely served dual roles as abstractors and had no consistent reporting structure

Lack of training and tools

  • The division’s guideline manual was outdated and did not account for site variability
  • Inconsistent training for data abstraction led to data variations
  • Staff’s lack of familiarity with data abstraction and technology presented a challenge to establishing consistent data integrity
  • Staff was hesitant to engage data because they lacked confidence in its quality
  • Many employees lacked training in IQVIA registry technology
  • Misaligned resources and tools between hospital sites were common

Inconsistent data management

  • How data was reported was inconsistent between sites
    • Some data reported was not for stroke patients, leading to fallouts because of incorrect coding and data input
    • Data abstraction was not completed in real time
    • Several hospital sites lagged in reporting data by several months or were behind in comparison to other divisions
  • Higher than desired investment
    • From beginning to end, cases took up to 50 minutes
    • One person was charged with 400-500 hundred charts per year, plus daily rounds, and emergency medical services
  • Additionally, the COVID-19 pandemic put a temporary pause on opportunities for improvement due to competing priorities

Goals

  • Improve internal ranking among the system’s divisions
  • Establish data integrity and improve data management
    • Improve data abstraction from the registry
    • Modernize data collection and use
  • Enhance technology competency among staff
    • Encourage dashboard use and engagement by staff
  • Streamline and modernize stroke guidelines
    • Establish “Get with the Guidelines” as a foundational learning tool
  • Reduce case times
  • Diminish case fallout and resource constraints

There are multiple opportunities to measure data and identify/correct fallouts while the patient is still in house. This includes getting the appropriate documentation into the EMR at the right time, and after the case goes into IQVIA, looking at time intervals to see if case trends are tracking positively.

The solution

Together with Q-Centrix, this partner set benchmarks and outlined a strategy to best suit their needs. A holistic approach proved most effective, working with Q-Centrix and a clinical data expert to view and enter clinical data daily for stroke departments across the division. This was a departure from the traditional offerings of concurrent and/or retrospective models of clinical data entry. The Q-Centrix hybrid model developed for the partnership also allowed each department access to the data integrity process process, exception reporting tools, all information in their applications, and their IQVIA dashboard in real-time. In addition, the hybrid model had the same clinical data expert handling both the concurrent and retrospective reviews to ensure consistency throughout the case’s lifecycle. The result? Faster, more consistently monitored registry cases and data abstraction. The former retrospective model case finished in about two months. The new hybrid model cases were completed in 15 days – four times faster.

The leader met with the head of each site’s stroke division to review their unique benchmarks, needs and goals, ensuring the hybrid solution proposed by Q-Centrix would make an immediate and lasting impact.

  • Centralized staffing and workload structure
    • Coordinator duties made consistent across the division
    • Coordinators no longer abstract data along with other duties
    • Staffing on registries handled by experienced external partner
  • Centralized data management across the division leading to expert data abstraction
  • Technology training and education
  • Staff technology training for dashboards was provided by Q-Centrix

Outcomes

  • Cases finish in 15 days, down from two months in the retrospective model
  • Case times have reduced from 41 minutes to 36 minutes on average across the entire division
    • Some sites post even shorter average case times
  • Centralized staffing and workload structure enable qualified staff to handle data abstraction with reduced turnover rates
    • Other staff dedicate time and expertise to other duties
  • Achieved and continuing data integrity
    • Data is regularly input without coding errors, reducing fallout
  • Staff has increased confidence in data integrity
    • Staff are more willing to engage with data and pull reports as necessary
    • Using data to pinpoint root causes
  • Staff registry and technology competence
    • Staff is more extensively using dashboards
    • Staff can now view month over month data improvements
  • Division’s rank positively reflects changes
    • Division climbed several spots

Conclusion

This South Texas health care division improved their data integrity, increased staff competence, and impacted patient quality care through the adaptation of a Q-Centrix hybrid model. Staff was provided tools to optimize work projects, and with data integrity assured, engage the data output of their registry. This data integrity, staffing structure, and newfound technology competency helped the division to significantly reduce case times and fallouts from improper coding. This resulted in higher patient quality care reflected in their rapidly rising rankings. The division continues to hit their goals and benchmarks and is hoping to achieve top ranking in the coming year.