Optimizing Laboratory Testing Collaborative

Overview

Annual expenditures on waste in healthcare exceed $900 billion and unnecessary services represent the largest segment of this waste.  Physicians are well positioned to identify unnecessary services and improve the value of care delivery.   

As evidenced by the American Board of Internal Medicine Foundation’s Choosing Wisely® campaign, there is broad clinician consensus around some low-value practices and a shared desire to reduce waste.  However, implementation and dissemination of clinical practice changes to promote high value care has proven challenging.  Busy clinicians and staff often lack resources, skills and time to drive change within organizations and self-protective institutional structures often impede effective collaboration and meaningful comparisons of performance across organizations.  

We developed a collaborative, multi-institutional model to facilitate implementation of specific high-value care practices in hospitalized adults across a state.  We report our experience to date, including a description of the model and early outcomes from the first initiative – the Vermont Optimizing Laboratory Testing project.

CLICK HERE TO READ THE FINAL REPORT

Supported by a Vermont Health Care Innovation Project award, we launched the collaborative model in 2014. The core elements of the model included:

  1. A neutral convener – in this case, the state medical society
  2. Voluntary participation from hospitals
  3. Interdisciplinary teams from each participating hospital that included physician champions
  4. Cooperative identification of a low-value clinical practice as an improvement aim for all hospital teams – coupled with customized goals and implementation at individual hospitals
  5. Standardized electronic data extracts that included administrative, charge, and laboratory data, regularly uploaded to a secure data enclave 
  6. Centralized resources for data analytics, quality consultation, project management and physician leadership
  7. Shared comparative measures of performance

The first project focused on reducing unnecessary laboratory testing in hospitalized adults.  Teams from eight hospitals initially enrolled in the project: two critical access hospitals, four community hospitals and two academic medical centers.  The hospital sizes ranged from 45 to 562 licensed beds.  The data set included patients 18 years or older hospitalized for more than 24 hours.  Patients with maternity-related diagnostic related-group codes and patients admitted to inpatient psychiatry, inpatient rehabilitation, and swing beds were excluded.  The primary measures were utilization rates of commonly overused laboratory studies.  Changes in baseline laboratory testing rates were used to extrapolate estimated changes in the volume of patient blood drawn annually.

Five of the eight hospital teams actively implemented changes to reduce unnecessary laboratory testing (active group).  Two hospital teams submitted data but did not actively introduce interventions at their hospitals (passive group).  One hospital team withdrew due to changes in physician staffing and administrative leadership. 

Compared with baseline performance, the utilization rate of commonly ordered laboratory tests across all participating hospitals with an active improvement team decreased 20 percent and no significant change in the passive group.  Assuming sustained changes in testing rates and phlebotomy practices, 2,917 blood tests will be avoided annually, resulting in 105 liters of averted blood loss (or “blood savings”).  

This scalable model promoted collaborative, clinician-driven changes in care delivery to enhance the value of care across a region.  The model was designed to obviate historical barriers to implementing clinical practice changes across non-affiliated hospitals.  The first initiative resulted in decreased laboratory utilization in hospitalized adults and yielded an estimated annual blood savings equivalent to the average blood volume of 22 adults – outcomes felt to be clinically important by participating teams.  

We encountered a number of challenges, most notably: (a) team participation was often hampered by competing clinical and administrative duties, and (b) the data set required extensive refinement and validation, precluding regular measurement reports to the hospital teams.  

However, the robust data set now allows assessment of the effectiveness of individual interventions and performance comparison on clinically meaningful measures.  We anticipate future evaluation of patient-centered outcomes such laboratory-free (“needle free”) days and the incidence of hospital-acquired anemia.  Planned health economic analyses will help to determine cost-effectiveness.  Moving forward, this model may offer a novel tool in healthcare reform efforts.

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