Perioperative Health Interventions in Children With Chronic Neuromuscular Conditions Undergoing Major Musculoskeletal Surgery: A Scoping Review.

BACKGROUND AND OBJECTIVES: Children with chronic neuromuscular conditions (CCNMC) have many coexisting conditions and often require musculoskeletal surgery for progressive neuromuscular scoliosis or hip dysplasia. Adequate perioperative optimization may decrease adverse perioperative outcomes. The purpose of this scoping review was to allow us to assess associations of perioperative health interventions (POHI) with perioperative outcomes in CCNMC. METHODS: Eligible articles included those published from January 1, 2000 through March 1, 2022 in which the authors evaluated the impact of POHI on perioperative outcomes in CCNMC undergoing major musculoskeletal surgery. Multiple databases, including PubMed, Embase, Cumulative Index of Nursing and Allied Health Literature, Web of Science, the Cochrane Library, Google Scholar, and ClinicalTrials.gov, were searched by using controlled vocabulary terms and relevant natural language keywords. Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines were used to perform the review. A risk of bias assessment for included studies was performed by using the Risk of Bias in Non-randomized Studies of Interventions tool. RESULTS: A total of 7013 unique articles were initially identified, of which 6286 (89.6%) were excluded after abstract review. The remaining 727 articles' full texts were then reviewed for eligibility, resulting in the exclusion of 709 (97.5%) articles. Ultimately, 18 articles were retained for final analysis. The authors of these studies reported various impacts of POHI on perioperative outcomes, including postoperative complications, hospital length of stay, and hospitalization costs. Because of the heterogeneity of interventions and outcome measures, meta-analyses with pooled data were not feasible. CONCLUSIONS: The findings reveal various impacts of POHI in CCNMC undergoing major musculoskeletal surgery. Multicenter prospective studies are needed to better address the overall impact of specific interventions on perioperative outcomes in CCNMC.

Hospital Variation and Resource Use for Infants with Craniosynostosis Undergoing Open, Endoscopic, and Distraction Osteogenesis Surgical Techniques.

BACKGROUND: Craniosynostosis is treated with endoscopic, open, and/or distraction surgical techniques. We assessed institutional variation in the use these techniques for craniosynostosis and compared hospital resource use. METHODS: Retrospective analysis of 5249 infants age <18 months old undergoing surgical procedures for all types of craniosynostosis in 2016-2020 in 39 freestanding children's hospitals in the Pediatric Health Information System (PHIS) database. Endoscopic vs. open cranial vault surgery (with and without distraction osteogenesis) was identified using ICD-10-CM codes. Inpatient cost and length of stay (LOS) were compared by surgery type with Wilcoxon Rank Sum. RESULTS: There was significant (p < .001) variation in the percentage of infants who underwent endoscopic repair across hospitals [median 23.6% (interquartile range (IQR): 7.6%-37.5%), range: 0% to 80.4%] and across regions [range: 22.1% (southeast) to 42.5% (northeast)]. For endoscopic procedures, median LOS and inpatient cost were lower (p < .001) without vs. with distraction [1 day (IQR 1-1) vs. 2 days (IQR 2-2); $14,617 (IQR 11,823-22178) vs. $33,599 (IQR 22,800-38,619)]. For open interventions, median LOS and inpatient cost were also lower (p < .001) without vs. with distraction [3 days (IQR 2-4) vs. 5 days (IQR 4-6) and $37,251 (IQR 27,114-50.320) vs. $62,247 (IQR 42,124-91,620)]. CONCLUSIONS: Substantial variation in the surgical approach for craniosynostosis exists across hospitals and regions. Endoscopic repair without distraction had the lowest hospital resource use, while open repair with distraction had the highest hospital resource. Subsequent analysis of short- and long-term outcomes as well as patient-and-family costs is necessary to assess the true cost-effectiveness of each approach.

Assessing the Utility of a Machine-Learning Model to Assist With the Assignment of the American Society of Anesthesiology Physical Status Classification in Pediatric Patients.

BACKGROUND: The American Society of Anesthesiologists Physical Status Classification System (ASA-PS) is used to classify patients' health before delivering an anesthetic. Assigning an ASA-PS Classification score to pediatric patients can be challenging due to the vast array of chronic conditions present in the pediatric population. The specific aims of this study were to (1) suggest an ASA-PS score for pediatric patients undergoing elective surgical procedures using machine-learning (ML) methods; and (2) assess the impact of presenting the suggested ASA-PS score to clinicians when making their final ASA-PS assignment. The intent was not to create a new ASA-PS score but to use ML methods to generate a suggested score, along with information on how the score was generated (ie, historical information on patient comorbidities) to assist clinicians when assigning their final ASA-PS score. METHODS: A retrospective analysis of 146,784 pediatric surgical encounters from January 1, 2016, to December 31, 2019, using eXtreme Gradient Boosting (XGBoost) methods to predict ASA-PS scores using patients' age, weight, and chronic conditions. SHapley Additive exPlanations (SHAP) were used to assess patient characteristics that contributed most to the predicted ASA-PS scores. The predicted ASA-PS model was presented to a prospective cohort study of 28,677 surgical encounters from December 1, 2021, to October 31, 2022. The predicted ASA-PS score was presented to the anesthesiology provider for review before entering the final ASA-PS score. The study focused on summarizing the available information for the anesthesiologist by using ML methods. The goal was to explore the potential for ML to provide assistance to anesthesiologists by highlighting potential areas of discordance between the variables that generated a given ML prediction and the physician's mental model of the patient's medical comorbidities. RESULTS: For the retrospective analysis, the distribution of predicted ASA-PS scores was 22.7% ASA-PS I, 48.5% II, 23.6% III, 5.1% IV, and 0.04% V. The distribution of clinician-assigned ASA-PS scores was 24.3% for ASA-PS I, 44.5% for ASA-PS II, 24.9% for ASA III, 6.1% for ASA-PS IV, and 0.2% for ASA-V. In the prospective analysis, the final ASA-PS score matched the initial ASA-PS 90.7% of the time and 9.3% were revised after viewing the predicted ASA-PS score. When the initial ASA-PS score and the ML ASA-PS score were discrepant, 19.5% of the cases have a final ASA-PS score which is different from the initial clinician ASA-PS score. The prevalence of multiple chronic conditions increased with ASA-PS score: 34.9% ASA-PS I, 73.2% II, 92.3% III, and 94.4% IV. CONCLUSIONS: ML derivation of predicted pediatric ASA-PS scores was successful, with a strong agreement between predicted and clinician-entered ASA-PS scores. Presentation of predicted ASA-PS scores was associated with revision in final scoring for 1-in-10 pediatric patients.

Categorization of a Universal Coding System to Distinguish Use of Durable Medical Equipment and Supplies in Pediatric Patients.

Importance: Although durable medical equipment and supplies (DMES) are commonly used to optimize the health and function in pediatric patients, little is known about the prevalence of use and spending on DMES. Objective: To categorize the Healthcare Common Procedure Coding System (HCPCS) for distinguishing DMES types, and to measure the prevalence and related spending of DMES in pediatric patients using Medicaid. Design, Setting, and Participants: This study is a cross-sectional analysis of the 2018 Merative Medicaid Database and included 4 569 473 pediatric patients aged 0 to 21 years enrolled in Medicaid in 12 US states from January 1 to December 31, 2018. Data were analyzed from February 2019 to April 2023. Exposure: DMES exposure was identified with the Centers for Medicare & Medicaid Services HCPCS codes. Three pediatricians categorized HCPCS DMES codes submitted by vendors for reimbursement of dispensed DMES into DMES types and end-organ systems; 15 expert reviewers refined the categorization (2576 DMES codes, 164 DMES types, 14 organ systems). Main Outcomes and Measures: The main outcome was DMES prevalence & Medicaid spending. The χ2 test was used to compare DMES prevalence and Wilcoxon rank sum tests were used to compare per-member-per-year (PMPY) spending by complex chronic conditions (CCC). Results: Of the 4 569 473 patients in the study cohort, 49.3% were female and 56.1% were aged 5 to 15 years. Patients used 133 of 164 (81.1%) DMES types. The DMES prevalence was 17.1% (95% CI, 17.0%-17.2%) ranging from 10.1% (95% CI, 10.0%-10.2%) in patients with no chronic condition to 60.9% (95% CI, 60.8%-61.0%) for patients with 2 or more CCCs. The PMPY DMES spending was $593, ranging from $349 for no chronic condition to $4253 for 2 or more CCCs. Lens (7.9%), vision frames (6.2%), and orthotics for orthopedic injury (0.8%) were the most common DME in patients with no chronic condition. Enteral tube / feeding supplies (19.8%), diapers (19.2%), lower extremity orthotics (12.3%), wheelchair (9.6%), oxygen (9.0%), and urinary catheter equipment (4.2%) were among the most common DMES in children with 2 or more CCCs. Conclusions and Relevance: In this cross-sectional study, HCPCS distinguished a variety of DME types and use across pediatric populations. Further investigation should assess the utility of the HCPCS DMES categorization with efforts to optimize the quality and safety of DMES use.

Correction: Medication Adherence Reminder System for Virtual Home Assistants: Mixed Methods Evaluation Study.

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Medication Adherence Reminder System for Virtual Home Assistants: Mixed Methods Evaluation Study.

BACKGROUND: Medication nonadherence is a global public health challenge that results in suboptimal health outcomes and increases health care costs. Forgetting to take medicines is one of the most common reasons for unintentional medication nonadherence. Research findings indicate that voice-activated virtual home assistants, such as Amazon Echo and Google Home devices, may be useful in promoting medication adherence. OBJECTIVE: This study aims to create a medication adherence app (skill), MedBuddy, for Amazon Echo devices and measure the use, usability, and usefulness of this medication-taking reminder skill. METHODS: A single-group, mixed methods, cohort feasibility study was conducted with women who took oral contraceptives (N=25). Participants were undergraduate students (age: mean 21.8 years, SD 6.2) at an urban university in the Southeast United States. Participants were given an Amazon Echo Dot with MedBuddy-a new medication reminder skill for Echo devices created by our team-attached to their study account, which they used for 60 days. Participants self-reported their baseline and poststudy medication adherence. MedBuddy use was objectively evaluated by tracking participants' interactions with MedBuddy through Amazon Alexa. The usability and usefulness of MedBuddy were evaluated through a poststudy interview in which participants responded to both quantitative and qualitative questions. RESULTS: Participants' interactions with MedBuddy, as tracked through Amazon Alexa, only occurred on half of the study days (mean 50.97, SD 29.5). At study end, participants reported missing their medication less in the past 1 and 6 months compared with baseline (χ21=0.9 and χ21=0.4, respectively; McNemar test: P<.001 for both). However, there was no significant difference in participants' reported adherence to consistently taking medication within the same 2-hour time frame every day in the past 1 or 6 months at the end of the study compared with baseline (χ21=3.5 and χ21=0.4, respectively; McNemar test: P=.63 and P=.07, respectively). Overall feedback about usability was positive, and participants provided constructive feedback about the skill's features that could be improved. Participants' evaluation of MedBuddy's usefulness was overwhelmingly positive-most (15/23, 65%) said that they would continue using MedBuddy as a medication reminder if provided with the opportunity and that they would recommend it to others. MedBuddy features that participants enjoyed were an external prompt separate from their phone, the ability to hear the reminder prompt from a separate room, multiple reminders, and verbal responses to prompts. CONCLUSIONS: The findings of this feasibility study indicate that the MedBuddy medication reminder skill may be useful in promoting medication adherence. However, the skill could benefit from further usability enhancements.

Virtual Home Assistant Use and Perceptions of Usefulness by Older Adults and Support Person Dyads.

AIM: Describe virtual home assistant use and usefulness from the perspective of older adults and their support persons. METHODS: This was a mixed-methods study with older adults and their support persons (n = 10 dyads). Virtual home assistant (VHA) equipment was installed in participants' homes, and its use was documented for 60 days. Participants received protocol-guided telephone calls to address their VHA questions or problems. The type and frequency of VHA use were summarized with descriptive statistics. End-of-study interviews about VHA use were conducted with dyad participants. Qualitative content analyses were used to describe the interview findings about the dyad's perceptions of using the VHA, how it was used, any difficulties experienced, and suggestions for future VHA uses. RESULTS: Participant dyads reported positive VHA perceptions, including the potential for VHAs to promote aging in place. Participants discussed the challenges learning the technology and replacing old habits with new ones. Participants offered recommendations for future VHA skills and for more education and training about using the VHA. CONCLUSIONS: The study findings suggest that VHAs may be useful for older adults as they age in place and offer reassurance for support persons.