Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
The Impact of Technology Failure on Electronic Prescribing Behavior in Primary Care: A Case Study Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

3. Understanding Lifestyle Decisions Based on Patient Historical Data: A Latent Growth Modeling Approach

verfasst von : Ronald Freeze, T. S. Raghu, Ajay Vinze

Erschienen in: Advances in Healthcare Informatics and Analytics

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Healthcare issues related to chronic disease conditions and management does not have easy or immediate solutions. Evidence based decision making in such contexts requires long-term tracking and analysis of patient data in order to provide patient choices that produce extended quality of life. Using Latent Growth Modeling (LGM), we present a planning perspective to analyze underlying patterns of long-term chronic data related to the progression of Multiple Sclerosis (MS). Using the North American Research Committee on Multiple Sclerosis (NARCOMS) patient driven initiative that collects survey data on a biannual basis for the purpose of clinical trial recruitment and epidemiological research, this study analyzes three temporal data points spanning 3 years. Two LGM models are presented that identify patient traits correlating with disease progression. The traits analyzed are both patient and physician controlled.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Individuals’ Attitudes Towards Electronic Health Records: A Privacy Calculus Perspective
Nächstes Kapitel Designing an Integrated Surgical Care Delivery System Using Axiomatic Design and Petri Net Modeling
Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
A prior version of this paper was presented at the Hawaiian International Conference of System Sciences in January, 2009.
 
2
See Appendix for the questions used to construct the Overall Health and Emotional Health latent Variables.
 
3
Only the Slope and Intercept changes, along with their significance, have been provided due to length considerations. Fit statistics for the Age Effect models and the remainder of the models outlined can be requested from the authors.
 
4
The fit statistics for the models of these Life Style effects can be requested from the authors.
 
5
See Table 3.1 for PDDS Question.
 
Literatur
Achiron A, Barak Y, Rotstein Z (2003) Longitudinal disability curves for predicting the course of relapsing—remitting multiple sclerosis. Mult Scler 9:486–491CrossRef
Berndt DJ, Hevner AR, Studnicki J (2003) The Catch data warehouse: support for community health care decision-making. Decis Support Syst 35:367–384CrossRef
Bryk A, Raudenbush S (1992) Hierarchical linear models in social and behavioral research: applications and data analysis methods. Sage, Newbury Park
Burchinal M, Appelbaum MI (1991) Estimating individual developmental functions: methods and their assumptions. Child Dev 62:23–43CrossRef
Cohen J, Cohen P, West S, Aiken L (2003) Applied multiple regression/correlation analysis for the behavioral sciences, 3rd edn. Lawrence Erlbaum, Mahwah
Duncan TE, Duncan SC (2004) An introduction to latent growth curve modeling. Behav Ther 35:333–363CrossRef
Freeman JA (1999) Rehabilitation in multiple sclerosis: outcome selection in clinical trials. Int J MS Care 2:20–26
Hamalainen P, Seinela A, Ruutiainen J (1999) Adaptational approach to cognitive rehabilitation in multiple sclerosis: description of three models of care. Int J MS Care 2:7–12
Kelley H, Chiasson M, Downey A, Pacaud D (2011) The clinical impact of eHealth on the self-management of diabetes: a double adoption perspective. J Assoc Inform Syst 12(Special Issue):208–234
Liang H, Xue Y, Berger BA (2006) Web-based intervention support system for health promotion. Decis Support Syst 42:435–449CrossRef
Longabaugh R, Wirtz PW, Beattie MC, Noel N, Stout R (1995) Matching treatment focus to patient social investment and support: 18-month follow-up results. J Consult Clin Psychol 63:296–307CrossRef
Marrie RA, Cutter G, Tyry T, Hadjimichael O, Vollmer T (2005) Validation of the NARCOMS registry: pain assessment. Mult Scler 11:338–342CrossRef
Nesselroade JR, Baltes PB (1979) Longitudinal research in the study of behavior and development. Academic, New York
Palmer RF, Blanchard S, Jean CR, Mandell DS (2005) School district resources and identification of children with autistic disorder. Am J Public Health 95:125–130CrossRef
Pedersen MK, Larsen MH (2001) Distributed knowledge management based on product state models—the case of decision support in health care administration. Decis Support Syst 31:139–158CrossRef
Patterson GR (1993) Orderly change in a stable world: the antisocial trait as a chimera. J Consult Clin Psychol 61:911–919CrossRef
Porter ME, Teisberg EO (2006) Redefining health care: creating value-based competition on results. Harvard Business School, Boston
Serva M, Kher H, Laurenceau J-P (2011) Using latent growth modeling to understand longitudinal effects in MIS theory: a primer. Commun Assoc Inform Syst 28(Article 14):213–232
Song J, Zahedi FM (2007) Trust in health infomediaries. Decis Support Syst 43:390–407CrossRef
Tabachnick BG, Fidell LS (2001) Using multivariate statistics, 4th edn. Allyn & Bacon, Needham Heights
Tisak J, Meredith W (1990) Descriptive and associative developmental models. In: von Eye A (ed) Statistical methods in developmental research, vol 2. Academic, San Diego, pp 387–406
Vollmer T, Ni W, Stanton S, Hadjimichael O (1999) The NARCOMS patient registry: a resource for investigators. Int J MS Care 1:12–15CrossRef
Wills TA, Sandy JM, Yaeger AM, Cleary SD, Shinar O (2001) Coping dimensions, life stress, and adolescent substance use: a latent growth analysis. J Abnormal Psychol 110:309–323CrossRef
Metadaten
Titel
Understanding Lifestyle Decisions Based on Patient Historical Data: A Latent Growth Modeling Approach
verfasst von
Ronald Freeze
T. S. Raghu
Ajay Vinze
Copyright-Jahr
2016
Buch
Advances in Healthcare Informatics and Analytics

Print ISBN: 978-3-319-23293-5

Electronic ISBN: 978-3-319-23294-2

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-23294-2_3