Toward High-Value Care: A Quality Improvement Initiative to Reduce Unnecessary Repeat Complete Blood Counts and Basic Metabolic Panels on a Pediatric Hospitalist Service.

OBJECTIVE: Achieving high-value health care is a goal of health care providers who strive to increase quality and decrease cost. Decreasing laboratory tests is a potential method to increase value. We used quality improvement methodology to decrease the percentage of unnecessary complete blood counts (CBCs) and basic metabolic panels (BMPs) obtained on a pediatric hospital medicine service from 13.5% to <5%. METHODS: A pre- and postintervention design was conducted including all patients admitted to 2 hospital medicine teams between May 2013 and December 2014. Multiple interventions linked to key drivers were tested through rapid plan-do-study-act cycles. Primary and secondary outcome measures, percent reduction of unnecessary CBCs and BMPs, and consecutive day tests were analyzed using statistical process control. Total billed charges, laboratory charges, 7-day readmission rates, and length of stay were compared pre- and postintervention. RESULTS: Primary outcome of unnecessary CBCs and BMPs was reduced from a baseline of 13.5% to 4.5%. Secondary outcome measure of consecutive day testing was reduced from 20.9% to 8.5%. Median laboratory charges decreased significantly ($842 [$256-$1863] vs $800 [$222-$1616], P = .002), with no significant differences in total billed charges, 7-day readmission rates, or length of stay. CONCLUSIONS: Rapid cycle plan-do-study-act methodology, initially focusing on the inclusion of a daily laboratory plan in progress notes, was an effective means to improve laboratory utilization and decrease laboratory charges without adversely affecting other quality measures. Spreading these efforts to different patient populations and laboratory tests could have a demonstrable effect on the value of health care.

Automated adverse event detection collaborative: electronic adverse event identification, classification, and corrective actions across academic pediatric institutions.

BACKGROUND: Historically, the gold standard for detecting medical errors has been the voluntary incident reporting system. Voluntary reporting rates significantly underestimate the number of actual adverse events in any given organization. The electronic health record (EHR) contains clinical and administrative data that may indicate the occurrence of an adverse event and can be used to detect adverse events that may otherwise remain unrecognized. Automated adverse event detection has been shown to be efficient and cost effective in the hospital setting. The Automated Adverse Event Detection Collaborative (AAEDC) is a group of academic pediatric organizations working to identify optimal electronic methods of adverse event detection. The Collaborative seeks to aggregate and analyze data around adverse events as well as identify and share specific intervention strategies to reduce the rate of such events, ultimately to deliver higher quality and safer care. The objective of this study is to describe the process of automated adverse event detection, report early results from the Collaborative, identify commonalities and notable differences between 2 organizations, and suggest future directions for the Collaborative. METHODS: In this retrospective observational study, the implementation and use of an automated adverse event detection system was compared between 2 academic children's hospital participants in the AAEDC, Children's National Medical Center, and Cincinnati Children's Hospital Medical Center. Both organizations use the EHR to identify potential adverse events as designated by specific electronic data triggers. After gathering the electronic data, a clinical investigator at each hospital manually examined the patient record to determine whether an adverse event had occurred, whether the event was preventable, and the level of harm involved. RESULTS: The Automated Adverse Event Detection Collaborative data from the 2 organizations between July 2006 and October 2010 were analyzed. Adverse event triggers associated with opioid and benzodiazepine toxicity and intravenous infiltration had the greatest positive predictive value (range, 47%- 96%). Triggers associated with hypoglycemia, coagulation disturbances, and renal dysfunction also had good positive predictive values (range, 22%-74%). In combination, the 2 organizations detected 3,264 adverse events, and 1,870 (57.3%) of these were preventable. Of these 3,264 events, clinicians submitted only 492 voluntary incident reports (15.1%). CONCLUSIONS: This work demonstrates the value of EHR-derived data aggregation and analysis in the detection and understanding of adverse events. Comparison and selection of optimal electronic trigger methods and recognition of adverse event trends within and between organizations are beneficial. Automated detection of adverse events likely contributes to the discovery of opportunities, expeditious implementation of process redesign, and quality improvement.

Exemplar pediatric collaborative improvement networks: achieving results.

A number of pediatric collaborative improvement networks have demonstrated improved care and outcomes for children. Regionally, Cincinnati Children's Hospital Medical Center Physician Hospital Organization has sustained key asthma processes, substantially increased the percentage of their asthma population receiving "perfect care," and implemented an innovative pay-for-performance program with a large commercial payor based on asthma performance measures. The California Perinatal Quality Care Collaborative uses its outcomes database to improve care for infants in California NICUs. It has achieved reductions in central line-associated blood stream infections (CLABSI), increased breast-milk feeding rates at hospital discharge, and is now working to improve delivery room management. Solutions for Patient Safety (SPS) has achieved significant improvements in adverse drug events and surgical site infections across all 8 Ohio children's hospitals, with 7700 fewer children harmed and >$11.8 million in avoided costs. SPS is now expanding nationally, aiming to eliminate all events of serious harm at children's hospitals. National collaborative networks include ImproveCareNow, which aims to improve care and outcomes for children with inflammatory bowel disease. Reliable adherence to Model Care Guidelines has produced improved remission rates without using new medications and a significant increase in the proportion of Crohn disease patients not taking prednisone. Data-driven collaboratives of the Children's Hospital Association Quality Transformation Network initially focused on CLABSI in PICUs. By September 2011, they had prevented an estimated 2964 CLABSI, saving 355 lives and $103,722,423. Subsequent improvement efforts include CLABSI reductions in additional settings and populations.

Transforming safety and effectiveness in pediatric hospital care locally and nationally.

Achieving dramatic, sustainable improvements in the safety and effectiveness of care for children requires a transformational approach to how hospitals individually focus on improvement and learn from each other to achieve national goals. The authors describe a theoretic framework for transformation that includes setting system-level priorities, aligning measures with each priority, identifying breakthrough targets, testing interventions to get results, and spreading successful interventions throughout the organization. Essential key drivers of transformation include leadership, building will, transparency, a business case for quality, patient and family engagement, improvement infrastructure, improvement capability, and reliability and standardization. Improving national system-level measures requires each hospital to pursue its own transformation journey while collaborating with hospitals and other organizations.

Clinical microsystems, part 1. The building blocks of health systems.

BACKGROUND: Wherever, however, and whenever health care is delivered-no matter the setting or population of patients-the body of knowledge on clinical microsystems can guide and support innovation and peak performance. Many health care leaders and staff at all levels of their organizations in many countries have adapted microsystem knowledge to their local settings. CLINICAL MICROSYSTEMS: A PANORAMIC VIEW: HOW DO CLINICAL MICROSYSTEMS FIT TOGETHER? As the patient's journey of care seeking and care delivery takes place over time, he or she will move into and out of an assortment of clinical microsystems, such as a family practitioner's office, an emergency department, and an intensive care unit. This assortment of clinical microsystems-combined with the patient's own actions to improve or maintain health--can be viewed as the patient's unique health system. This patient-centric view of a health system is the foundation of second-generation development for clinical microsystems. LESSONS FROM THE FIELD: These lessons, which are not comprehensive, can be organized under the familiar commands that are used to start a race: On Your Mark, Get Set, Go! ... with a fourth category added-Reflect: Reviewing the Race. These insights are intended as guidance to organizations ready to strategically transform themselves. CONCLUSION: Beginning to master and make use of microsystem principles and methods to attain macrosystem peak performance can help us knit together care in a fragmented health system, eschew archipelago building in favor of nation-building strategies, achieve safe and efficient care with reliable handoffs, and provide the best possible care and attain the best possible health outcomes.