Patient-centeredness in Integrated healthcare delivery systems: Needs, expectations & priorities for organized healt

1. Patient-centeredness in Integrated healthcare delivery systems:Needs, expectations & priorities for organized healthcare systems 13th International Conference on Integrated Care 1.2 Patient-centred care Christin Juhnke, M.A.Prof. Dr. Axel C. Mühlbacher IGM Institute Health Economics andHealthcare Management, Hochschule Neubrandenburg, Germany

2. BackgroundDesigning Healthcare Delivery • Organized healthcare delivery systems intend to structure the care for a defined population or the care process for a defined indication. • Integrated care, coordinated care, disease management • The Institute of Medicine report “Crossing the Quality Chasm” emphasizes that healthcare should be customized based on patients’ needs and values. • Patient-centred care, in which health services are customized on the basis of patients’ needs and values, is seen as a critical factor in a high-performance healthcare system. “Healthcare systems are challenged to effectively meet the wants and needs of patients by tailoring interventions based on each person’s […] preferences as well as personal and social context”. [Sevin et al. 2009] Hochschule Neubrandenburg

3. Research Question • Contemporary and application-oriented analysis and documentation of what patients need and expect from organized healthcare services. • Aim: structure the patient-relevant need dimensions of healthcare programs: • Identification of needs, expectations and priorities of patients in organized healthcare delivery networks. • Identification of characteristics of healthcare services which determine utility, motivation and quality of care from the patients’ point of view. • Identification of characteristics from the perspective of healthcare providers, payers and other experts within the framework of integrated and coordinated services. Hochschule Neubrandenburg

4. Methods and Study DesignChronology of Methods Project-definition Literature research(Sept.2010; N=167) • Definition of research question • Multilevel methodological approach • Structuring and Analysis of data using factor analyses Aim: • Comprehensive data collection and documentation of all potentially relevant characteristics of integrated care programs • Analysis of needs and expectations on the psychometric structures and dimensions of the needs Qualitative Study Phase Interviews using Design-Thinking Method (N=22) • Generation of relevant characteristics • Designing of questionnaire Quantitative Study Phase Rating Experts & Patients • Conducting of survey in medical offices and on congresses Data analysis/ Reporting Explorative Data analyses: Factor analyses • Data Analysis • Development of factor model Hochschule Neubrandenburg

5. Methods and Study DesignRating & Factor Analysis • Results of qualitative study phase were transferred to 84 care- related items • Five-point Likert-Scale • Very important • Important • So- so • Less important • Not important • Factor-Analysis using SPSS® 18 Hochschule Neubrandenburg

6. Results Sample Characteristics • Rating of 84 care delivery-related items • Paper-and pencil-based surveys • Patients: 12 surgeries/ medical offices in 3 German federal states • June - October 2010 • N=670 • Healthcare experts: three international health conventions • April - June 2010 • N=254 Hochschule Neubrandenburg

7. Methods and Study DesignFactor Analysis • Method of multivariate data analysis • Aim: Descriptions of variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. • Basis: • Factor Theory of Spearman (1904) • methodological development especially Thurstone (1931; 1947) • Principal components analysis based on Pearson (1901) & Hotelling (1933) Hochschule Neubrandenburg

8. Results Factor Analysis: Experts • Exploratory factor analysis: • 24 factors with Eigenvalue > 1 • KMO of 0,730 • 71,357% of total variance • Screeplot: 4-7 factors • 7-Factor solution • Total variance: 38,427% • KMO: 0,797 • Cronbach alpha: 0,836 -0,715. Hochschule Neubrandenburg

9. ResultsFactor Analysis: Patients • Exploratory factor analysis: • 20 factors with Eigenvalue > 1 • KMO of 0,914 • 63,462 % of total variance • Screeplot: 4-8 factors • List-wise deletion: N= 453 • 7-Factor solution • Total variance: 42,963 % • KMO: 0,914 • Cronbach alpha: 0,899 – 0,756 Hochschule Neubrandenburg

10. ResultsModel of need dimensions in organized healthcare Hochschule Neubrandenburg

11. Limitations • Patient sample does not fulfil the criterion of representativityin terms of age • Study represents cross-sectional data from 670 respondents from three German regions • Statement on the deviation from a representative norm sample is not possible • Rating was based on 5-point Likertscale • individual items are not weighted against each other • items did not show a Gaussian distribution, but a left shift Hochschule Neubrandenburg

12. Conclusion • Systematic approach of qualitative and quantitative measures as preparation of a preference study • Aim of structuring of needs using psychometric analyses • Identification and structuring of patient-relevant characteristics was successful • Based on the results a Discrete-Choice Experiment was conducted  If providers and payers can incorporate patient needs and expectations into organized care programs, greater concordance regarding treatment goals, adherence and better clinical outcomes might be achieved Hochschule Neubrandenburg

13. THANK YOU • Prof. Dr. rer. oec. Axel C. Mühlbacher • Christin Juhnke, M.A. • IGM InstitutGesundheitsökonomie und Medizinmanagement • Hochschule Neubrandenburg • BrodaerStraße2 • 17033 Neubrandenburg • juhnke@hs-nb.de • Phone (+49) 0395 5693 3308 Hochschule Neubrandenburg