Reducing Cost Through Standardization

Validation of a Costing Algorithm and Cost Drivers for Neonates Admitted to the Neonatal Intensive Care Unit

OBJECTIVE

 Neonatal intensive care units (NICUs) account for over 35% of pediatric in-hospital costs. A better understanding of NICU expenditures may help identify areas of improvements. This study aimed to validate the Canadian Neonatal Network (CNN) costing algorithm for seven case-mix groups with actual costs incurred in a tertiary NICU and explore drivers of cost.

STUDY DESIGN

 A retrospective cohort study of infants admitted within 24 hours of birth to a Level-3 NICU from 2016 to 2019. Patient data and predicted costs were obtained from the CNN database and were compared to actual obtained from the hospital accounting system (Coût par Parcours de Soins et de Services). Cost estimates (adjusted to 2017 Canadian Dollars) were compared using Spearman correlation coefficient (rho).

RESULTS

 Among 1,795 infants included, 169 (9%) had major congenital anomalies, 164 (9%) with <29 weeks' gestational age (GA), 189 (11%) with 29 to 32 weeks' GA, and 452 (25%) with 33 to 36 weeks' GA. The rest were term infants: 86 (5%) with hypoxic-ischemic encephalopathy treated with therapeutic hypothermia, 194 (11%) requiring respiratory support, and 541 (30%) admitted for other reasons. Median total NICU costs varied from $6,267 (term infants admitted for other reasons) to $211,103 (infants born with <29 weeks' GA). Median daily costs ranged from $1,613 to $2,238. Predicted costs correlated with actual costs across all case-mix groups (rho range 0.78-0.98, p < 0.01) with physician and nursing representing the largest proportion of total costs (65-82%).

CONCLUSION

 The CNN algorithm accurately predicts NICU total costs for seven case-mix groups. Personnel costs account for three-fourths of in-hospital total costs of all infants in the NICU.

KEY POINTS

· Very preterm infants born below 33 weeks of gestation account for most of NICU resource use.. · Human resources providing direct patient care represented the largest portion of costs.. · The algorithm strongly predicted total costs for all case-mix groups..

Variations in the Evaluation and Management of Vascular Rings: A Survey of American Clinicians

Vascular rings are arterial malformations that lead to the compression of the trachea and/or esophagus. While "tight" rings often produce symptoms and require surgery, "loose" rings rarely produce symptoms. Given advances in fetal echocardiography, this diagnosis is now more often made prenatally. This poses a new conundrum in the management of asymptomatic patients, leading to practice variation and creating a target for clinical system improvement. Hence, we conducted this survey aiming to demonstrate the practice variation existing in current evaluation and management of these patients. An anonymous web-based survey was distributed to several listservs for pediatric cardiologists and pediatric cardiothoracic surgeons. Survey questions targeted respondent practice characteristics, testing obtained, and indications for testing or surgical referral. In total 61 responses were received, predominantly from pediatric cardiologists (95%) in the United States (97%). About 60% of clinicians reported frequently diagnosing patients with vascular rings by fetal echocardiogram, with only about 20% diagnosing them frequently on evaluation of symptoms. Computed tomography angiography and echocardiogram were the most common imaging modalities employed. Most clinicians obtained cross-sectional imaging at the time of diagnosis and referred to surgery once patients had at least occasional symptoms. Respondents demonstrated a low degree of agreement (Krippendorf's alpha 0.48). Few statistically significant patterns were identified between respondents based on their practice characteristics. This study identified significant variation between clinicians regarding the evaluation and management of vascular rings. Further research or expert opinions may help to standardize practice, saving costs and improving the quality of care for affected patients.

Role of practice standardization in outcome optimization for CDH

Standardization of care seeks to improve patient outcomes and healthcare delivery by reducing unwanted variations in care as well as promoting the efficient and effective use of healthcare resources. There are many types of standardization, with clinical practice guidelines (CPGs), based on a stringent assessment of evidence and expert consensus, being the hallmark of high-quality care. This article outlines the history of CPGs, their benefits and shortcomings, with a specific focus on standardization efforts as it relates to congenital diaphragmatic hernia management.

Effect of an algorithm for automatic placing of standardised test order sets on low-value appointments and attendance rates at four Spanish teaching hospitals: an interrupted time series analysis

OBJECTIVE

Reducing backlogs for elective care is a priority for healthcare systems. We conducted an interrupted time series analysis demonstrating the effect of an algorithm for placing automatic test order sets prior to first specialist appointment on avoidable follow-up appointments and attendance rates.

DESIGN

Interrupted time series analysis.

SETTING

4 academic hospitals from Madrid, Spain.

PARTICIPANTS

Patients referred from primary care attending 10 033 470 outpatient appointments from 16 clinical specialties during a 6-year period (1 January 2018 to 30 June 2023).

INTERVENTION

An algorithm using natural language processing was launched in May 2021. Test order sets developed for 257 presenting complaints from 16 clinical specialties were placed automatically before first specialist appointments to increase rates of diagnosis and initiation of treatment with discharge back to primary care.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcomes included rate of diagnosis and discharge to primary care and follow-up to first appointment index. The secondary outcome was trend in 'did not attend' rates.

RESULTS

Since May 2021, a total of 1 175 814 automatic test orders have been placed. Significant changes in trend of diagnosis and discharge to primary care at first appointment (p=0.005, 95% CI 0.5 to 2.9) and 'did not attend' rates (p=0.006, 95% CI -0.1 to -0.8) and an estimated attributable reduction of 11 306 avoidable follow-up appointments per month were observed.

CONCLUSION

An algorithm for placing automatic standardised test order sets can reduce low-value follow-up appointments by allowing specialists to confirm diagnoses and initiate treatment at first appointment, also leading to early discharge to primary care and a reduction in 'did not attend' rates. This initiative points to an improved process for outpatient diagnosis and treatment, delivering healthcare more effectively and efficiently.

Regional variation in cost of neonatal intensive care for extremely preterm infants

Background

Regional variation in cost of neonatal intensive care for extremely preterm infant is not documented. We sought to evaluate regional variation that may lead to benchmarking and cost saving.

Methods

An analysis of a Canadian national costing data from the payor perspective. We included all liveborn 23–28-week preterm infants in 2011–2015. We calculated variation in costs between provinces using non-parametric tests and a generalized linear model to evaluate cost variation after adjustment for gestational age, survival, and length of stay.

Results

We analysed 6932 infant records. The median total cost for all infants was $66,668 (Inter-Quartile Range (IQR): $4920–$125,551). Medians for the regions varied more than two-fold and ranged from $48,144 in Ontario to $122,526 in Saskatchewan. Median cost for infants who survived the first 3 days of life was $91,000 (IQR: $56,500–$188,757). Median daily cost for all infants was $1940 (IQR: $1518–$2619). Regional variation was significant after adjusting for survival more than 3 days, length of stay, gestational age, and year (pseudo-R² = 0.9, p < 0.01). Applying the model on the second lowest-cost region to the rest of the regions resulted in a total savings of $71,768,361(95%CI: $65,527,634–$81,129,451) over the 5-year period ($14,353,672 annually), or over 11% savings for the total program cost of $643,837,303 over the study period.

Conclusion

Costs of neonatal intensive care are high. There is large regional variation that persists after adjustment for length of stay and survival. Our results can be used for benchmarking and as a target for focused cost optimization, savings, and investment in healthcare.

Standardizing Preoperative Evaluation for Pediatric Central Venous Access: A Care Algorithm to Improve Safety

Central vascular access device (CVAD) placement is a common procedure in children. When selecting a CVAD, available evidence and specified indications should be used to choose the device that best supports the patient's treatment and carries the lowest risks. A multidisciplinary team developed a care algorithm to standardize preoperative screening before pediatric CVAD placement, with 3 major parts: CVAD selection, patient risk stratification, and preoperative evaluation. Using a stepwise approach of provider education and incorporation into the electronic health record, the team achieved 82% stratification among inpatients. The team's algorithm integrates the existing literature and recommendations for safe and effective CVAD placement.

Impactibility Model for Population Health Management in High-Cost Elderly Heart Failure Patients: A Capture Method Using the ACG System

The aim of the present study is to use the ACG (Adjusted Clinical Groups) System to create an impactibility model by identifying homogeneous clinical subgroups of patients with high risk of an adverse health outcome in a population of heart failure patients with complex health care needs (PCHCN). This method will allow policy makers to target and prioritize services for the highest risk PCHCN in the context of limited health care resources, by identifying relatively homogeneous groups of patients with similar comorbidities. Subjects classified in 2012 as PCHCN in a local health unit by the ACG System were linked with hospital discharge records in 2013. The authors applied the Apriori algorithm to identify the most common sets of the most predictive diseases for the following outcomes of interest: at least 1 admission and at least 1 preventable admission in the year. Predictive performance for the former outcome was compared between the impactability model with the available ACG's individual risk score. The Apriori algorithm also was applied to predict the latter outcome as an example of an event that a policy maker would be able to prevent. Evidence showed no statistically significant difference between the 2 methods. The present model also displayed evidence of good calibration. The Apriori algorithm was applied as an impactibility model, built based on the ACG System, that allowed the authors to obtain an "ACG-based group risk score" and use it to identify clinically homogeneous subgroups of PCHCN. This will help policy makers develop "tool kits" for homogeneous groups of patients that improve health outcomes.

Standardising hospitalist practice in sepsis and COPD care

Background

Hospitalist medicine was predicated on the belief that providers dedicated to inpatient care would deliver higher quality and more cost-effective care to acutely hospitalised patients. The literature shows mixed results and has identified care variation as a culprit for suboptimal quality and cost outcomes. Using a scientifically validated engagement and measurement approach such as Clinical Performance and Value (CPV), simulated patient vignettes may provide the impetus to change provider behaviour, improve system cohesion, and improve quality and cost efficiency for hospitalists.

Methods

We engaged 33 hospitalists from four disparate hospitalist groups practising at Penn Medicine Princeton Health. Over 16 months and four engagement rounds, participants cared for two patients per round (with a diagnosis of chronic obstructive pulmonary disease [COPD] and sepsis), then received feedback, followed by a group discussion. At project end, we evaluated both simulated and real-world data to measure changes in clinical practice and patient outcomes.

Results

Participants significantly improved their evidence-based practice (+13.7% points, p<0.001) while simultaneously reducing their variation (−1.4% points, p=0.018), as measured by the overall CPV score. Correct primary diagnosis increased significantly for both sepsis (+19.1% points, p=0.004) and COPD (+22.7% points, p=0.001), as did adherence to the sepsis 3-hour bundle (+33.7% points, p=0.010) and correct admission levels for COPD (+26.0% points, p=0.042). These CPV changes coincided with real-world improvements in length of stay and mortality, along with a calculated $5 million in system-wide savings for both disease conditions.

Conclusion

This study shows that an engagement system—using simulated patients, benchmarking and feedback to drive provider behavioural change and group cohesion, using parallel tracking of hospital data—can lead to significant improvements in patient outcomes and health system savings for hospitalists.