PIH66 – A Systematic Review To Identify the Use of Preference Elicitation Methods in Health Care Decision Making

Objectives: Preference elicitation methods (PEMs) offer the potential to increase patient-centered medical decision-making (MDM), by offering a measure of benefit along with a measure of value. Preferences can be applied in decisions on: reimbursement, including health technology assessment (HTA); market access, including benefit-risk assessment (BRA), and clinical care. The three decision contexts have different requirements for use and elicitation of preferences. The aim of this systematic review was to identify studies that used PEMs to represent the patient view and identify the types of health care decisions addressed by PEMs. Additionally, PEMs were described by methodological and practical characteristics within the three contexts’ requirements. Methods: Search terms included those related to MDM and patient preferences. Only articles with original data from quantitative PEMs were included. Results: Articles (n=322) selected included 379 PEMs, comprising matching methods (MM) (n=71,18.7%), discrete choice experiments (DCE) (n=96,25.3%), multi-criteria decision analysis (n=12,3. 2%), and other methods (i. e. rating scales), which provide estimates inconsistent with utility theory (n=200,52.8%). Most publications of PEMs had an intended use for clinical decisions (n=134,40%), HTA (n=68,20%), or BRA (n=12,4%). However, many did not specify an intended use (n=156,41.1%). In clinical decisions, rating, ranking, visual analogue scales and direct choice are used most often. In HTA, DCEs and MM are both used frequently, and the elicitation of preferences in BRA was limited to DCEs. Conclusions: Relatively simple preference methods are often adequate in clinical decisions, because they are easy to administer, give fast results, place low cognitive burden on the patient, and low analytical burden on the provider. MM and DCE fulfill the requirements of HTA and BRA but are more complex for the respondents. There were no PEMs that had low cognitive burden, and strong methodological underpinnings which could deliver adequate information to inform HTA and BRA decisions

Patient participation in the development and application of eHealth:Willingness and preferences of people with diabetes mellitus type 2

AIM: The aim was to gain insight in the preferences of people with type 2 diabetes mellitus regarding the moments and methods of patient participation in the development and application of eHealth, and which factors influence this. METHODS: A digital questionnaire with both closed and open questions was distributed via various online platforms and the newsletter of the Diabetes Association in the Netherlands. Information was collected on: 1) willingness to participate; 2) preferences about the method of participation; 3) influencing factors on participation, including motivation, competence, resources, social influences, and outcome expectations; 4) background characteristics. RESULTS: 160 questionnaires were analysed. More than three quarter of the respondents intend to be involved in patient participation. Most respondents prefer solo participation methods over group participation, respectively 93% and 46%. Half of the respondents feel that they have sufficient knowledge to participate, and 40% feels that they can provide valuable input. As compensation for participation, participants prefer to use new technologies for free. CONCLUSION: As people with diabetes type 2 differ in their preferences for moments and methods of participation, it is recommended to offer different methods of participation and types of compensation in the process from development to application of eHealth

Indicatoren voor de zorgtoewijzing bij persoonlijkheidsstoornissen: resultaten van een concept map analyse

Using the concept map method, this study revealed patient characteristics that are important for treatment selection decisions in patients with personality disorders. Concept mapping is a specific type of structured conceptualization process and describes the underlying structure of specific phenomena. The method uses qualitative and quantitative methods. In this study, we integrated a literature investigation with the opinions of 29 experts in the field of treatment allocation and/or personality disorders. Our goal was to reduce and describe the number of patient characteristics that are important for treatment allocation in personality disorders. The concept map procedure resulted in eight patient characteristics: (1) severity of symptoms, (2) severity of personality pathology, (3) ego-adaptive capacity, (4) motivation and capacity for a therapeutic alliance, (5) patient’s social system, (6) social demographic variables, (7) traumata, (8) treatment history and physical examination. This report describes in detail the concept mapping procedure and the outcomes are discussed

Added value of co-morbidity in predicting health-related quality of life in COPD patients

AbstractThe extent to which a chronic obstructive pulmonary disease (COPD) patient is impaired in health-related quality of life (HRQoL) is only to a small extent reflected in clinical and demographical measures. As the influence of co-morbidity on HRQoL is less clear, we investigated the added value of 23 common diseases in predicting HRQoL in COPD patients with mild to severe airways obstruction.COPD patients from general practice who appeared to have an forced expiratory volume in 1 sec/inspiratory vital capacity (FEV1/IVC) < predicted −1·64 SD, FEV1<80% predicted, FEV1reversibility <12% and a smoking history, were included (n=163). HRQoL was assessed with the short-form-36 (SF-36) and the presence of co-morbidity was determined by a questionnaire, which asked for 23 common diseases.All domains of the SF-36 were best predicted by the presence of three or more co-morbid diseases. FEV1% predicted, dyspnoea and the presence of one or two diseases were second-best predictors. Co-morbidity explained an additional part of the variance in HRQoL, particularly for emotional functioning (ΔR2=0·11). When individual diseases were investigated, only insomnia appeared to be related to HRQoL.As HRQoL is still only partly explained, co-morbidity and other patient characteristics do not clearly distinguish between COPD patients with severe impairments in HRQoL and COPD patients with minor or no impairments in HRQoL. Therefore, it remains important to ask for problems in daily functioning and well-being, rather than to rely on patient characteristics alone