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Patient perspectives. Alison Bowes University of Stirling . In this domain. Outcomes = patient’s (and relatives’) perceptions and satisfaction Not easy to define, as includes many aspects such as: Feelings, comfort Interaction with professionals Convenience, timeliness
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Patient perspectives Alison Bowes University of Stirling Berlin
In this domain • Outcomes = patient’s (and relatives’) perceptions and satisfaction • Not easy to define, as includes many aspects such as: • Feelings, comfort • Interaction with professionals • Convenience, timeliness • Overall satisfaction • Preference as compared with face to face interaction • Privacy and confidentiality • Professionals’ competence and/or personal manner • Views about the technology itself • Informativeness of professionals • Usefulness/potential for future use • Self efficacy and empowerment • An evaluation has to specify which aspects are important and therefore which will be investigated. Berlin
Choosing outcome measures • Standard or bespoke instruments? • Need to be specific and reportable • Need to use standard instruments where these are appropriate • Criterion: what do we need to know, given the nature of the intervention? Key aspects from MAST are • Satisfaction or acceptance • Understanding of information • Confidence • Ease of use • Access • Empowerment and self-efficacy Berlin
Examples from literature • Qualitative methods: • Interviews (semi structured) • Diary keeping • Patients record and self report their symptoms • Quantitative methods • Questionnaires to patients • Standard satisfaction survey (e.g. Group Health Association of America Consumer Satisfaction Survey) • Standard health measures (e.g. SF36 – a generic health and well-being scale) • Condition related standard measures (e.g. DQOL [Diabetes], DemQOL [Dementia] and others) • Mixed methods • Selection of qualitative and quantitative tools Berlin
Collecting data on patient perceptions • Consider what criteria need to be considered • Design a systematic approach to data collection • Integrate the collection of satisfaction data within the system • Ensure that data can be analysed readily • No need to re-invent the wheel (see Appendix to MAST, which includes many suggestions) Berlin
Examples from literature • Surveys which combine standard and bespoke measures (e.g. standard satisfaction measures with specific questions about access to services, when intervention was delivered in rural areas) • Mixed methods data collection (e.g. in teleoncology services, some quantitative questionnaire work, but more open-ended interview data which is helpful where patients and their families are in varied circumstances and locations) • Patients keep a record of their symptoms (e.g. this was frequently used in telepsychiatry) Berlin
Handy hints • Focus on key aspects (less may be more…..) • Remember the key criteria • Satisfaction or acceptance • Understanding of information • Confidence • Ease of use • Access • Empowerment and self-efficacy • Integrate data collection with other procedures • Allow for the unexpected (e.g. differences between patients, unintended results) • Make sure that the data are used to inform the intervention • See patients as partners in care, who contribute to successful outcomes Berlin
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