Patient Outcomes in a Pediatric Hospital Medicine Service Staffed With Physicians and Advanced Practice Providers

Short stay unit led by pediatric hospital medicine advanced practice providers

BACKGROUND

In response to a critical pediatric bed shortage in 2022, an urgent process change was required to provide safe and timely medical care. We proposed a pilot for an advanced practice provider (APP)-run short stay unit (SSU) for select pediatric hospital medicine (PHM) patients.

OBJECTIVE

To compare length of stay (LOS) and cost before and after implementation of a PHM APP-led SSU pilot at a tertiary pediatric hospital.

DESIGNS, SETTINGS, AND PARTICIPANTS

Single-center prospective pilot observational cohort study with historical control. Observation encounters for patients with asthma, bronchiolitis, croup, and dehydration were included.

INTERVENTION

An independent-practice model SSU staffed by APPs on the PHM service.

MAIN OUTCOME AND MEASURES

SSU encounters (September 1, 2022-December 1, 2022) were compared against pre-SSU encounters (September 1, 2021-August 31, 2022). Cohorts were described with summary statistics. SSU encounters were matched against pre-SSU encounters based on demographics and diagnosis, and the average effect of treatment was calculated. LOS was abstracted from the enterprise data warehouse and standardized unit cost from the Pediatric Health Information Systems database.

RESULTS

There were 1110 encounters included, 155 in the SSU cohort and 955 in the pre-SSU cohort: 24.2% asthma, 30.8% bronchiolitis, 8.3% croup, and 36.7% dehydration. Median (interquartile range) unit LOS decreased from 21 (16-26) to 18 (10-22) h, p < .001. Cost decreased from $3593 ($3031-$4560) to $2958 ($2278-$3856), p < .001. After matching, the average treatment effect was reduction of 3.88 h (95% confidence interval [CI] 1.91-5.85) and $593 (95% CI $348-$839). There were no significant differences in 7-day ED revisit rates.

Engaging nurse practitioners and physician assistants to improve patient care and drive productivity in a radiology consult practice at a comprehensive cancer center

BACKGROUND

The demand for health care in the United States is increasing because of an aging population and an increase in the number of individuals insured. This has led to requests to revamp the primary care infrastructure fundamentally.

LOCAL PROBLEM

The optimal use of nurse practitioners (NPs) and physician assistants (PAs) is still a subject of debate, but recently, it was reported that for many medical conditions, NP and PA-managed care outcomes are consistent with physician-managed care outcomes.

METHODS

Radiologists' productivity was measured according to relative value units (RVUs)/shift and professional billing changes. Patient care metrics measured were prescribed protocol to patient appointment lead time and number of same-day prescribed imaging protocol changes.

INTERVENTIONS

The focus was on radiologists' productivity and patient care for three months before and three months after integrating NP and PA into our abdominal radiology consult service.

RESULTS

We observed significant increases in the mean RVUs/shift (15.2 ± 0.9 vs. 6.2 ± 1.8; p = .02), studies read per shift (10.1 ± 0.5 vs. 4.4 ± 1.5; p = .003), revenue per shift hour ($756.20 ± 55.40 vs. $335.40 ± 32.60; p = .007), and protocol prescription to patient appointment lead time (39.3 ± 6.7 days vs. 16.3 ± 2.9 days; p = .005) and saw significant decreases in the mean prescribed CT (19.3 ± 0.6 vs. 3.3 ± 0.6; p = .001) and MRI (11.7 ± 0.6 vs. 8.30 ± 0.12; p = .011) same day protocol changes in NP and PA integrated workflow.

CONCLUSIONS

These findings suggest that NP and PA can be effectively integrated into the abdominal radiology consult service, increasing radiologists' productivity and enhancing clinical care.

PAs and NPs improve patient care and productivity in a radiology consult practice

OBJECTIVE

To evaluate the effects on efficiency and patient care of the addition of physician assistants (PAs) and NPs to the abdominal radiology consult service.

METHODS

We obtained radiologist productivity and patient care metrics for 3 months before and 3 months after the integration of PAs and NPs into our consult service.

RESULTS

Integrating PAs and NPs into the workflow led to a significant increase in mean RVUs/shift (15.2 ± 0.9 versus 6.2 ± 1.8; P = .02), number of studies read per shift (10.1 ± 0.5 versus 4.4 ± 1.5; P = .003), revenue per shift hour ($756.20 ± $55.40 versus $335.40 ± $132.60; P = .007), protocol prescription to patient appointment lead time (39.3 ± 6.7 versus 16.3 ± 2.9 days; P = .005), and significant decreases in mean CT (19.3% ± 0.6 versus 3.3% ± 0.6; P = .001) and MRI (11.7% ± 0.6 versus 8.3% ± 0.12; P = .011) same-day protocol changes as patient appointments.

CONCLUSIONS

PAs and NPs can be effectively integrated into abdominal radiology consult service, increasing the productivity of radiologists, and enhancing clinical care.

Risk Factors for Pediatric Asthma Readmissions: A Systematic Review

OBJECTIVE

To systematically review the literature on pediatric asthma readmission risk factors.

STUDY DESIGN

We searched PubMed/MEDLINE, CINAHL, Scopus, PsycINFO, and Cochrane Central Register of Controlled Trials for published articles (through November 2019) on pediatric asthma readmission risk factors. Two authors independently screened titles and abstracts and consensus was reached on disagreements. Full-text articles were reviewed and inclusion criteria applied. For articles meeting inclusion criteria, authors abstracted data on study design, patient characteristics, and outcomes, and 4 authors assessed bias risk.

RESULTS

Of 5749 abstracts, 74 met inclusion criteria. Study designs, patient populations, and outcome measures were highly heterogeneous. Risk factors consistently associated with early readmissions (≤30 days) included prolonged length of stay (OR range, 1.1-1.6) and chronic comorbidities (1.7-3.2). Risk factors associated with late readmissions (>30 days) included female sex (1.1-1.6), chronic comorbidities (1.5-2), summer discharge (1.5-1.8), and prolonged length of stay (1.04-1.7). Across both readmission intervals, prior asthma admission was the most consistent readmission predictor (1.3-5.4).

CONCLUSIONS

Pediatric asthma readmission risk factors depend on the readmission interval chosen. Prior hospitalization, length of stay, sex, and chronic comorbidities were consistently associated with both early and late readmissions.

TRIAL REGISTRATION

CRD42018107601.

Ramping Up a Pediatric Hospital Medicine Advanced Practice Provider Team Rapidly

Pediatric Hospital Medicine (PHM) is a growing subspecialty with a broad scope. The Covid-19 pandemic demands flexible staffing models. Advanced practice providers (APPs) can be a valuable addition to hospital medicine teams, although there is no established training program for APPs within PHM. The authors' purpose is to describe how one institution rapidly established a PHM APP team by collaborating with experienced APPs working in other areas of the hospital. This APP team cared for 16% of the average daily census during the pilot period with no significant difference in length of stay compared to traditional teams.