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PACIC Instrument: disentangling dimensions using published validation models.

K Iglesias1, B Burnand1, I Peytremann-Bridevaux1

  • 1Institute of Social and Preventive Medicine, Lausanne University Hospital, Route de la Corniche 10, Lausanne CH-1010, Switzerland.

International Journal for Quality in Health Care : Journal of the International Society for Quality in Health Care
|April 17, 2014
PubMed
Summary
This summary is machine-generated.

This study found that an 11-item, single-dimension model best fits the Patient Assessment of Chronic Illness Care (PACIC) instrument data. A single PACIC score may be more suitable than its traditional five dimensions for assessing chronic illness care.

Keywords:
chronic care modelconfirmatory factorial analysisdiabetesvalidation analyses

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Area of Science:

  • Health Services Research
  • Psychometrics
  • Chronic Illness Management

Background:

  • The Patient Assessment of Chronic Illness Care (PACIC) instrument is widely used to evaluate chronic illness care.
  • Existing validation models for the PACIC instrument require further investigation to determine the most appropriate structural representation.
  • Understanding the PACIC's structure is crucial for accurate interpretation of patient-reported experiences.

Purpose of the Study:

  • To rigorously test all published validation models of the Patient Assessment of Chronic Illness Care (PACIC) instrument.
  • To identify the most suitable structural model for the PACIC using a single dataset and advanced statistical techniques.
  • To inform the optimal use and interpretation of the PACIC in research and clinical practice.

Main Methods:

  • A cross-sectional survey of a population-based sample of adults with diabetes in Switzerland.
  • Confirmatory Factor Analysis (CFA) was employed to test multiple PACIC structural models.
  • Three distinct CFA approaches were utilized, varying in estimator types and distribution assumptions for manifest variables.

Main Results:

  • The study analyzed data from 406 adult patients with diabetes.
  • While item loadings were generally high, only an 11-item, single-dimension model demonstrated acceptable fit.
  • Significant floor and ceiling effects were observed in the item responses.

Conclusions:

  • The 11-item, single-dimension model provides the best fit for the PACIC instrument data in this population.
  • A single summary score derived from the 11-item model may be a more appropriate measure than the traditional five dimensions.
  • These findings suggest a potential revision in how the PACIC is scored and interpreted to enhance its utility.