Research and evidence

Analysing and using PRMs data effectively

The PRMs Program team has developed Analytic principles for patient-reported outcome measures. This document outlines key principles to guide the analysis of patient-reported outcome data, such as those collected by the HOPE system.

The principles provide guidance for local analytic plans and help ensure that what patients tell us about their health and outcomes is interpreted accurately.

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Key analytic principles for patient-reported outcome measures

1. Patient characteristics

How to interpret patient-reported data across different case complexities, cognitive capacities, social circumstances.

Especially important for:

  • populations in integrated care programs
  • patients with impaired cognitive capacity such as hip fracture patients.

2. Time

What represents a meaningful change in patient-reported outcomes.

How to interpret improvement and worsening, of individual and aggregated data.

Especially important for:

  • patients with chronic diseases such as chronic obstructive pulmonary disease, congestive heart failure, rheumatoid arthritis.

3. Data quality

  • Underlying reasons and impact of missing responses and questionnaires
  • Metadata-based insights to assess completion.

Especially important for:

  • older, sicker patients who may be less likely to fill questionnaires, creating a bias.

4. Fair comparisons

How to adjust for differences in case mix, patient resilience, environmental confounders, utilisation patterns.

Especially important for:

  • benchmarking and peer comparisons of clinicians, clinical teams, hospitals.

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