Development and Validation of an Attitudinal-Profiling Tool for Patients With Asthma

Aileen David-Wang, David Price, Sang Heon Cho, James Chung-Man Ho, Chong Kin Liam, Glenn Neira, Pei-Li Teh

Research output: Contribution to journalArticle

3 Citations (Scopus)
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Abstract

Purpose: To develop a profiling tool which accurately assigns a patient to the appropriate attitudinal cluster for the management of asthma. Methods: Attitudinal data from an online survey of 2,467 patients with asthma from 8 Asian countries/region, aged 18-50 years, having had ≥2 prescriptions in the previous 2 years and access to social media was used in a discriminant function analysis to identify a minimal set of questions for the Profiling Tool. A split-sample procedure based on 100 sets of randomly selected estimation and validation sub-samples from the original sample was used to cross-validate the Tool and assess the robustness of its predictive accuracy. Results: Our Profiling Tool contained 10 attitudinal questions for the patient and 1 GINA-based level of asthma control question for the physician. It achieved a predictive accuracy of 76.2%. The estimation and validation sub-sample accuracies of 76.7% and 75.3%, respectively, were consistent with the tool’s predictive accuracy at 95% confidence level; and their 1.4 percentage-points difference set upper-bound estimate for the degree of over-fitting. Conclusions: The Profiling Tool is highly predictive (>75%) of the attitudinal clusters that best describe patients with asthma in the Asian population. By identifying the attitudinal profile of the patient, the physician can make the appropriate asthma management decisions in practice. The challenge is to integrate its use into the consultation workflow and apply to areas where Internet resources are not available or patients who are not comfortable with the use of such technology.
Original languageEnglish
Pages (from-to)43-51
Number of pages9
JournalAllergy, Asthma & Immunology Research
Volume9
Issue number1
Early online date29 Aug 2016
DOIs
Publication statusPublished - Jan 2017

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Asthma
Social Media
Physicians
Workflow
Discriminant Analysis
Internet
Referral and Consultation
Population

Keywords

  • asthma
  • discriminant analysis
  • disease management
  • Asia

Cite this

Development and Validation of an Attitudinal-Profiling Tool for Patients With Asthma. / David-Wang, Aileen; Price, David; Cho, Sang Heon; Chung-Man Ho, James; Liam, Chong Kin; Neira, Glenn; Teh, Pei-Li.

In: Allergy, Asthma & Immunology Research, Vol. 9, No. 1, 01.2017, p. 43-51.

Research output: Contribution to journalArticle

David-Wang, Aileen ; Price, David ; Cho, Sang Heon ; Chung-Man Ho, James ; Liam, Chong Kin ; Neira, Glenn ; Teh, Pei-Li. / Development and Validation of an Attitudinal-Profiling Tool for Patients With Asthma. In: Allergy, Asthma & Immunology Research. 2017 ; Vol. 9, No. 1. pp. 43-51.
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abstract = "Purpose: To develop a profiling tool which accurately assigns a patient to the appropriate attitudinal cluster for the management of asthma. Methods: Attitudinal data from an online survey of 2,467 patients with asthma from 8 Asian countries/region, aged 18-50 years, having had ≥2 prescriptions in the previous 2 years and access to social media was used in a discriminant function analysis to identify a minimal set of questions for the Profiling Tool. A split-sample procedure based on 100 sets of randomly selected estimation and validation sub-samples from the original sample was used to cross-validate the Tool and assess the robustness of its predictive accuracy. Results: Our Profiling Tool contained 10 attitudinal questions for the patient and 1 GINA-based level of asthma control question for the physician. It achieved a predictive accuracy of 76.2{\%}. The estimation and validation sub-sample accuracies of 76.7{\%} and 75.3{\%}, respectively, were consistent with the tool’s predictive accuracy at 95{\%} confidence level; and their 1.4 percentage-points difference set upper-bound estimate for the degree of over-fitting. Conclusions: The Profiling Tool is highly predictive (>75{\%}) of the attitudinal clusters that best describe patients with asthma in the Asian population. By identifying the attitudinal profile of the patient, the physician can make the appropriate asthma management decisions in practice. The challenge is to integrate its use into the consultation workflow and apply to areas where Internet resources are not available or patients who are not comfortable with the use of such technology.",
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note = "This study was supported and funded by Mundipharma Pte Ltd. Online survey and statistical analysis were performed by Pei-Li Teh, Rachel Howard, Tsin-Li Chua and Jie Sun of Research Partnership Pte Ltd. Medical writing support was provided by Sen-Kwan Tay of Research2Trials Clinical Solutions Pte Ltd. The authors received honoraria from Mundipharma for their participation in the REALISE Asia Working Group meetings and discussions. Prof Price has Board membership with Mundipharma; and had received consultancy and speaker fees, grants and unrestricted funding support from Mundipharma; and payment for manuscript preparation and travel/accommodations/meeting expenses from Mundipharma. Profs Liam and David-Wang are members of the Asia-Pacific Advisory Board of Mundipharma. Profs Cho and David-Wang had received speaker fees from Mundipharma in the past. Dr Neira was an employee of Mundipharma Pte Ltd, Singapore. Ms Teh is an employee of Research Partnership Pte Ltd which conducted the REALISE Asia survey for Mundipharma. Prof Cho is a member of the Editorial Board of Allergy, Asthma & Immunology.",
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N2 - Purpose: To develop a profiling tool which accurately assigns a patient to the appropriate attitudinal cluster for the management of asthma. Methods: Attitudinal data from an online survey of 2,467 patients with asthma from 8 Asian countries/region, aged 18-50 years, having had ≥2 prescriptions in the previous 2 years and access to social media was used in a discriminant function analysis to identify a minimal set of questions for the Profiling Tool. A split-sample procedure based on 100 sets of randomly selected estimation and validation sub-samples from the original sample was used to cross-validate the Tool and assess the robustness of its predictive accuracy. Results: Our Profiling Tool contained 10 attitudinal questions for the patient and 1 GINA-based level of asthma control question for the physician. It achieved a predictive accuracy of 76.2%. The estimation and validation sub-sample accuracies of 76.7% and 75.3%, respectively, were consistent with the tool’s predictive accuracy at 95% confidence level; and their 1.4 percentage-points difference set upper-bound estimate for the degree of over-fitting. Conclusions: The Profiling Tool is highly predictive (>75%) of the attitudinal clusters that best describe patients with asthma in the Asian population. By identifying the attitudinal profile of the patient, the physician can make the appropriate asthma management decisions in practice. The challenge is to integrate its use into the consultation workflow and apply to areas where Internet resources are not available or patients who are not comfortable with the use of such technology.

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