Improving the Timing of Laboratory Studies in Hospitalized Children: A Quality Improvement Study

The QI study was conducted from November 2017 to February 2020 at a single-site medium-sized urban children’s hospital in the northeastern United States with ∼150 hospital beds. At the time of the study, the PHM service consisted of 2 clinical teams on 4 inpatient units and cared for >2000 admissions per year. Each clinical team was composed of 2 to 3 resident physicians, an attending physician, and occasionally an advanced practice provider (APP). During the study, there were ∼75 residents, 14 attending physicians, and 3 APPs on the PHM teams on a rotating basis over 1- to 2-week rotations. Bedside nurses obtained morning laboratory studies according to orders entered into the electronic health record (EHR) by providers (resident physicians, APPs, and occasionally attending physicians). Daily laboratory studies defaulted to 6 am in the EHR, requiring providers to manually adjust this if a different time was desired.

An interdisciplinary QI team with key stakeholders, including 14 PHM attending physicians, 2 resident physicians, 3 nurse practitioners, 2 registered nurses, 1 QI coach, 1 administrative assistant, and 1 family advisor, was formed. The family advisor was the mother of a patient who previously received care from the children’s hospital. A core team from the larger interdisciplinary group included 3 PHM attending physicians, 1 family advisor, 1 QI coach, and 1 resident physician. The core team consistently attended monthly meetings, led the implementation of plan-do-study-act (PDSA) cycles, and was critically involved in evaluating the QI effort.¹² 

With the personal insight and guidance from our family advisor that overnight and early-morning laboratory study collection occurred frequently and caused significant psychosocial stress for families, changing the timing of laboratory studies to later in the morning became the key focus for improvement.¹²  The occurrence of early-morning laboratory study collection had previously been substantiated by work done by our group revealing that most laboratory studies for pediatric inpatients at our children’s hospital occurred between 4 and 6 am.¹³ 

The main intervention was the design and use of a rounding checklist that the inpatient PHM teams reviewed daily. Frontline providers (resident physicians and APPs) presented the checklist at the end of each patient’s presentation on family-centered rounds, and teams shared in the responsibility of its review. To promote the discussion and review of laboratory study timing, in addition to other quality and safety aspects of medical care, the checklist addressed each patient’s intravenous lines, expiring orders, antimicrobial therapy, and diagnostic testing (LEAD), with emphasis on the diagnostic testing domain. The LEAD mnemonic and rounding checklist were developed by coauthor MSL, with input from other QI team members.¹²  Discussions within the diagnostic domain were intended to include both the specific tests ordered and the date and time they were ordered to be collected. This allowed the clinical teams and families to collaboratively discuss and plan the timing of laboratory studies. In their daily notes, attending physicians documented use of the LEAD checklist during rounds.

The primary outcome measure was the percentage of routine morning laboratory studies ordered for collection after 7 am, designated family-centered timing. Discussion with the family advisor informed our decision to designate 7 am or later as family-centered timing. Routine morning laboratory studies were defined as laboratory tests that included a complete blood cell count, basic or complete metabolic profile, C-reactive protein measurement, and/or erythrocyte sedimentation rate ordered to be drawn between the hours of 12 am and 12 pm. Multiple laboratory studies ordered for and collected at the same time were considered 1 laboratory draw. A secondary outcome measure was the percentage of routine morning laboratory studies collected after 7 am.

The process measure was use of the LEAD checklist on daily rounds, as documented by PHM attending physicians in their admission and progress notes. The balancing measure was the percentage of morning laboratory studies collected after 11 am because this could delay patient care and discharges.

Members of the QI team retrospectively collected data through monthly chart review of PHM patients. Team members abstracted 15 randomly selected patient charts each month and reviewed the first 3 days of each patient’s admission. We abstracted the following variables and entered them into Research Electronic Data Capture¹⁴ : (1) the time that routine morning laboratory studies were ordered for collection, (2) the time that morning laboratory studies were collected, and (3) evidence that the rounding checklist was reviewed on rounds and documented in the PHM attending’s daily note.

To assess the impact of the intervention, we used time series analyses with run charts and probability-based standard rules for determining special cause variation. For each run chart, we reviewed the number of runs or series of data points on 1 side of the baseline median to identify if the measured process revealed nonrandom improvement according to standard criteria.¹⁵  Given that our run charts had 28 data points, <10 runs would indicate a nonrandom process, suggesting that the intervention impacted the process. To assess improvement and calculate a new median after the identified break point, a shift was defined as ≥6 consecutive points above the established median.¹⁵  The baseline period was defined as 10 data points (or 10 months) before the start of the intervention,¹⁶  which was from November 2017 to August 2018. The intervention period consisted of 8 months from September 2018 to April 2019. Data were collected for 10 months after the intervention period to evaluate the effort’s sustainability until February 2020.

We employed the model for improvement framework, a standard method for conceptualizing and designing QI efforts and analyzing their results.¹⁷  Five PDSA cycles were conducted to assess the intervention of the rounding checklist, modify its usage, and add additional interventions as needed. PDSA cycles were designed to implement small changes in a series to measure their effect on outcome measures. The study was deemed exempt by our institutional review board committee, and the article follows Standards for Quality Improvement Reporting Excellence guidelines.¹⁸ 

A total of 420 pediatric patient charts were abstracted during the 28-month study period. The study consisted of 55.0% (n = 231) male and 45.0% female (n = 189) patients. The median age was 2.9 years, and the most frequent principal diagnoses were bronchiolitis, asthma, upper respiratory infections, sepsis, and pneumonia.

In Table 1, we describe how the intervention was modified in each of the 5 PDSA cycles. The cycles included the following: (1) implementing the rounding checklist; (2) posting visual prompts as reminders to discuss the LEAD rounding checklist domains, including diagnostics; (3) educating nurses and providers on the importance of timing laboratory study collection later in the day; (4) having a family advisor present to providers on the stress and anxiety related to early-morning laboratory study collection; and (5) using EHR prompts built into note templates to remind providers to discuss family-centered laboratory study timing.

Figure 1 reveals the run chart of our primary outcome: the percentage of laboratory studies ordered for collection after 7 am each month. The baseline preintervention median was 25.8%. With implementation of the rounding checklist (PDSA cycle 1, September 2018), the percentage of laboratory studies ordered to be collected after 7 am increased to 100% within 2 months. The lowest level during the intervention was in January 2019 (33.0%), although it remained above the baseline median. This decrease led to the implementation of PDSA cycle 3 (distribution of resident, nursing, and attending guides to re-emphasize the goals of the QI study). Subsequently, there was an increase in the percentage of laboratory studies ordered to be collected at family-centered times.

Given that we found 3 runs, which is fewer than the 10 runs expected to occur in a random process, the intervention likely impacted the laboratory study order process.¹⁵  We identified a shift, with 6 consecutive data points (September 2018 to February 2019) above the baseline median of 25.8%, revealing special cause variation. After the break point, the calculated new median was 75.0%.¹⁶  The postintervention median remained above our goal of >50%. Sustainability data over the course of 10 months (May 2019 to February 2020) revealed that the postintervention median did not change.

For the secondary outcome, the percentage of routine laboratory studies collected after 7 am, results were similar (Fig 2). Given that we found 9 runs, which is fewer than the expected 10 runs in a random process, the intervention likely impacted the laboratory study collection process.¹⁵  A shift in the median was noted, with 6 consecutive data points (February 2019 to July 2019) above the baseline median of 37.1%, revealing special cause variation. The calculated new median was 76.4% after the break point.¹⁶ 

Figure 3 demonstrates the run chart of our process measure: the percentage of daily notes documenting the review of the LEAD rounding checklist on rounds. Given a baseline median of 0%, we could not evaluate for runs. With 6 consecutive data points (September 2018 to March 2019, disregarding December 2018) above the baseline median of 0%, special cause variation was observed. The calculated new median was 46.4% after the break point.¹⁶ 

Our balancing measure, the percentage of laboratory studies collected after 11 am, was designed to assess if changes in workflow led to delays in patient care or resulted in unintended afternoon laboratory study collection. The balancing measure was 5.9% at baseline and did not reveal special cause variation or change during the intervention period (data not shown).

Our QI study successfully accomplished interprofessional practice change by shifting the timing of routine laboratory study collection to later in the morning. By implementing a rounding checklist to standardize the daily discussion of the timing of routine laboratory studies, our study changed laboratory study ordering practice for pediatric patients admitted to our children’s hospital’s PHM service. The postintervention median for the percentage of laboratory studies ordered for after 7 am increased from 25.8% to 75.0%, and the median for the percentage of laboratory studies collected after 7 am increased from 37.1% to 76.4%. In addition, use of the LEAD rounding checklist increased from 0% to 46.4%. These improvements reveal that our study was both successful and sustainable.

Our QI study is the first, to our knowledge, to shift the timing of laboratory study collection to later in the morning for admitted pediatric patients. Researchers and administrators have recognized that overnight and early-morning laboratory study collection contributes to poor quality of sleep for patients and are neither patient nor family centered.^3,11,19–23  Previous research encouraging sleep-friendly laboratory study collection has occurred primarily in hospitalized adults. Studies on adult general medicine services have been focused on the development of EHR tools to flag non–sleep-friendly laboratory study collection, the adjustment of workflow and staffing to facilitate phlebotomy, and the retiming of laboratory study collection based on patient and staff survey data.^20,22,23  Although these efforts highlight important interventions to implement sleep-friendly laboratory study collection in hospitalized adults, our study offers a novel approach to adjustments in provider ordering practice for pediatric inpatients.

Improvements in our QI study’s outcome measures largely coincided with PDSA cycles, highlighting potential interventions for other institutions to adopt. Particularly impactful initiatives that led to improvement seemed to be those that standardized the discussion of diagnostic testing for patients, enhanced awareness of the need to avoid early-morning laboratory study collection, and reinforced training for providers on how to implement the intervention. PDSA cycle 1 (implementing the checklist) resulted in the largest single increase in both the number of laboratory studies ordered for and collected after 7 am. Run charts appeared to reveal that a shift in laboratory study ordering practice took place before a shift in laboratory study collection practice, suggesting that improvements in workflow take time and that order change may occur before practice change. In addition, use of the checklist seemed to correlate positively with the primary and secondary outcome measures. By standardizing the daily discussion of the timing of routine laboratory studies on inpatient rounds, the LEAD checklist served as a reminder to providers and nurses to discuss and plan the timing of laboratory study collection collaboratively. This reinforces that checklists may be useful to help drive practice change and improve family-centered outcomes, just as they have been shown to improve patient quality and safety in clinical care.^24–27 

Engaging an interprofessional team of resident physicians, attending physicians, a family advisor, and nurses as stakeholders in our QI effort while creating both provider- and nursing-targeted improvement cycles was key to enacting practice change. For resident physicians, practice habits are often set during training; thus, sustainability may depend on establishing early cultural habits for ordering behavior.²⁸  Several studies have adopted similar approaches to educate resident physicians on the impact of laboratory study ordering behavior.^2,29  Vidyarthi et al³⁰  partnered with residents to reduce test overuse and raise awareness of the costs associated with laboratory studies by adopting a multilevel approach that included teaching sessions, social marketing, and financial incentives. Tchou et al²⁸  focused on reducing rates of electrolyte laboratory study collection through e-mails and orientation sessions educating providers on the costs and risks associated with test overuse. To change laboratory study ordering practice, our QI study collaborated with resident physicians to integrate PDSA cycles into interprofessional workflow and provide education on the intervention. This suggests that raising resident awareness on the impact of laboratory study ordering behavior may be an effective strategy to adjust clinician practice and highlights the need to consider education as an important intervention.² 

Partnering with a family advisor, the mother of a patient previously cared for at our hospital, was integral to informing our QI study’s design, implementation, and outcomes.³¹  As a member of the interdisciplinary QI team, the family advisor led the team to identify improving the family-centered timing of laboratory study collection as the primary goal of the study. Furthermore, improvement efforts and system changes were enacted on the basis of her insight.¹²  For example, in PDSA cycle 4, the family advisor educated resident physicians about the negative psychosocial impact related to overnight and early-morning laboratory study collection. This PDSA cycle contributed to a sustained increase above the baseline median for the percentage of routine laboratory studies ordered for family-centered times. Partnering with a family advisor and disseminating the parent perspective enhanced the goal and purpose of the QI study and likely contributed to influencing provider ordering practice. Institutions should be encouraged to universally include a family partner on QI initiatives to enhance patient- and family-centered care and optimize outcomes.

Our study had several limitations. The intervention was conducted at a single-site medium-sized university hospital in an urban setting, and findings may not be generalizable. At our institution, bedside nurses collected laboratory studies according to orders placed by providers in the EHR, whereas other institutions may have different staffing for laboratory study collection, thereby impacting the study’s generalizability. The process measure was evaluated by chart review of documentation of the intervention usage by PHM attending physicians, which was subject to recall bias. Attending physician notes that did not document use of the LEAD rounding checklist may have also underestimated its use during rounds. Direct observation may have provided more objective information and an opportunity to evaluate the context of implementation of the checklist. Our outcomes were measured through abstraction of randomly selected patient charts, which may have also impacted results. This was limited by the availability of QI study members. In addition, our study did not elicit qualitative data or ratings of the quality of care to measure the perceived benefits to patients, families, and providers.

Future studies should be focused on obtaining satisfaction and sleep metrics by surveying patients and families to determine if the intervention improved patient and family centeredness, satisfaction, sleep quality, and the overall quality of patient care. Evaluating the impact on child life and music therapy use to support coping and minimize procedure-related distress from shifted laboratory study timing may provide additional insights.³²  Creating an electronic prompt within the EHR to encourage sleep-friendly laboratory study timing and flagging laboratory studies that are not deemed family centered should be considered, as well as adjusting the default time in the EHR to later in the morning.²²  Lastly, further evaluation should include whether the QI effort decreased the overall frequency of laboratory studies obtained.

Implementing a rounding checklist successfully shifted the timing of routine laboratory studies to later in the morning for patients admitted to the PHM service at our children’s hospital. This study was successful because of frequent reminders, re-education, and presentations to providers on the psychosocial impact of overnight and early-morning laboratory specimen collection. Sustainability data preliminarily reveal that implementation of a checklist can result in a persistent change in laboratory study ordering and collection practices. This intervention could be a potential improvement strategy for other institutions seeking to adjust inpatient laboratory study practice to promote patient sleep and improve the delivery of patient- and family-centered care.

Coauthors who are members of the University of Rochester Medicine Golisano Children’s Hospital PHM QI Team include the following: Barbara L. Asselin, MD; Adam Bracken, MD; Keely Dwyer-Matzky, MD, MBA; Anne Fallon, MD; Catherine Krafft, MD, MHPE; Natalia Paciorkowski, MD, PhD; Sherry Philip, MD; Lindsay Rogozinski, MS, PNP; Lauren G. Solan, MD, MEd; Elise van der Jagt, MD, MPH; and Jeffrey P. Yaeger, MD, MPH.

We thank the nurses and resident physicians in the Pediatrics and Medicine-Pediatrics Residency Program at Golisano Children’s Hospital, University of Rochester, Rochester, New York, for collaborating on this initiative; Jenna Wagner, family advisor, for her expertise and effort to improve patient- and family-centered care; and Frances Cartella, study team member, for data collection, analysis, and innovative contributions crucial to this effort’s success.