Demographic and Risk-Factor Differences between Users and Non-Users of Unscheduled Healthcare among Pediatric Outpatients with Persistent Asthma

Abstract

This study assesses differences between users and non-users of unscheduled healthcare for persistent childhood asthma, with regard to select demographic and risk factors. The objectives are to provide important healthcare utilization information and a foundation for future research on self-management effectiveness (SME), informed by a recently developed "holistic framework" for measuring SME in childhood asthma. An 18-month retrospective chart review was conducted on 59 pediatric outpatients with persistent asthma-mild, moderate, or severe, to obtain data on various demographic and risk factors, and healthcare use for each child. The study examined five types of "unscheduled" healthcare use. Users had non-zero encounters (at least one) in any of the five types; non-users had zero encounters (not even one) in all five types. Differences between users and non-users were assessed using contingency table and logistic regression analysis. There were 25 users and 34 non-users of unscheduled healthcare. Each severity category contained users and non-users. The only statistically significant finding was that the mild persistent category had fewer users than severe persistent (p < 0.05). There were no significant differences between users and non-users for any other demographic or risk factor examined. After adjusting for asthma severity, there were no other significant differences between users and non-users of unscheduled healthcare. This is a crucial finding which suggests that something else is driving unscheduled healthcare use in these children, given there were users and non-users in each asthma severity category. These results provide impetus for future research on the role of other aspects of the "holistic framework" in explaining differences in uses of unscheduled healthcare in persistent childhood asthma. 12 of 12 21. Zandbelt, L.C.; Smets, E.M.; Oort, F.J.; Godfried, M.H.; Haes, H.C. Medical specialists' patient-centered communication and patient-reported outcomes. Med. Care 2007, 45, 330-339. [CrossRef] [PubMed] 22. Zill, J.M.; Christalle, E.; Müller, E.; Härter, M.; Dirmaier, J.; Scholl, I. Measurement of Physician-Patient Communication-A Systematic Review. PLoS ONE 2014, 9, e112637. [CrossRef] [PubMed] 23. Zolnierek, K.B.H.; DiMatteo, M.R. Physician communication and patient adherence to treatment: A meta-analysis. Med. Care 2009, 47, 826-834. [CrossRef] [PubMed] © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Effect of Disease Severity, Age of Child, and Clinic No-Shows on Unscheduled Healthcare Use for Childhood Asthma at an Academic Medical Center

“…Another methodological limitation that needs to be acknowledged is that this study may not have captured patient visits to other emergency departments or urgent care centers in the community. However, this concern is mitigated by the fact that the study institution is the second largest children’s hospital in the state of Georgia and that past studies at this institution have established that over 95% of the pediatric outpatient population relies on the same health system (academic medical center) for primary, secondary, and tertiary care [ 12 , 13 ]. This concern is also mitigated by the fact that most of the study population was on Medicaid and that past studies have shown that patients on Medicaid are less prone to seek care from a wider network of providers due to insurance limitations [ 41 ].…”

“…(4) Community-level risk factors would include financial hardship, access to asthma care, food, transportation, and housing stability. Lastly, (5) environmental risk factors would include factors such as outdoor temperature, heat, and outdoor and indoor air quality [ 10 , 11 , 12 , 13 ]. According to the “holistic framework” for assessing asthma SME, each of these factors (separately and together) can impact SME in childhood asthma, with SME defined by the primary outcome of unscheduled healthcare use for childhood asthma [ 10 , 11 ].…”

Demographic and Risk Factor Differences between Children with “One-Time” and “Repeat” Visits to the Emergency Department for Asthma

“…Moreover, asthma severity was only found to be significant in explaining the number of users of unscheduled healthcare in the “mild-persistent” category compared to “severe-persistent”. The fact remained that there were users and non-users of unscheduled healthcare in all three persistent asthma severity categories (mild, moderate, and severe) and none of the individual demographic or risk factors examined served to explain differences in the use of unscheduled healthcare across the three severity groups [ 11 ]. A key implication therefore was that something other than the individual factors examined was driving unscheduled healthcare use.…”

“…This earlier study was set in the outpatient clinics at the same institution and took a first step towards assessing SME in 59 children with asthma (8–17 years), informed by the “holistic framework”, by defining SME in terms of the primary outcome of unscheduled healthcare use. In the outpatient study, “users” of unscheduled healthcare served to represent “low SME”, while “non-users” of unscheduled healthcare within the same asthma severity category served to represent “high SME” [ 11 ]. The study examined differences between users and non-users of unscheduled healthcare in persistent childhood asthma, with respect to select individual demographic and risk factors obtained through record review, including asthma severity (defined as mild-persistent, moderate-persistent, and severe-persistent asthma), age, gender, race, insurance , and body-mass index (BMI).…”