Dataset Information

Using Discrete Choice Methodology to Explore the Impact of Patient Room Window Design on Hospital Choice.

ABSTRACT: Evidence-based design has been fundamental to designing healthcare environments for patient outcomes and experience, yet few studies have studied how design factors drive patient choice. 652 patients who recently received care at hospitals across the United States were administered an online discrete choice survey to investigate the factors playing into their choice between hypothetical hospitals. Discrete choice models are widely used to model patient preferences among treatment alternatives, but few studies have utilized this approach to investigate healthcare design alternatives. In the current study, respondents were asked to choose between hypothetical hospitals that differed in patient room design, window features of the room, appointment availability, distance from home, insurance coverage, and HCAHPS ratings. The results demonstrate that patient room design that allowed unobscured access to daylight and views through windows, in-network insurance coverage, closer distance from home, and one-star higher patient experience rating increased the likelihood of a patient's hospital choice. The study broadly explores discrete choice model's applicability to healthcare design and its ability to quantify patient perceptions with a metric meaningful for hospital administrators.

SUBMITTER: Woo M

PROVIDER: S-EPMC9208038 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Using Discrete Choice Methodology to Explore the Impact of Patient Room Window Design on Hospital Choice.

Woo May M Jafarifiroozabadi Roxana R MacNaughton Piers P Mihandoust Sahar S Kennedy Sara S Joseph Anjali A

Journal of patient experience 20220615

Evidence-based design has been fundamental to designing healthcare environments for patient outcomes and experience, yet few studies have studied how design factors drive patient choice. 652 patients who recently received care at hospitals across the United States were administered an online discrete choice survey to investigate the factors playing into their choice between hypothetical hospitals. Discrete choice models are widely used to model patient preferences among treatment alternatives, b ...[more]

PMID: 35734469

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Project description:ImportanceSurgical options for weight loss vary considerably in risks and benefits, but the relative importance of procedure-associated characteristics in patient decision making is largely unknown.ObjectiveTo identify patient preferences for risks, benefits, and other attributes of treatment options available to individuals who are candidates for bariatric surgery.Design, setting, and participantsThis discrete choice experiment of weight loss procedures was performed as an internet-based survey administered to patients recruited from bariatric surgery information sessions in the State of Michigan. Each procedure was described by the following set of attributes: (1) treatment method, (2) recovery and reversibility, (3) time that treatment has been available, (4) expected weight loss, (5) effect on other medical conditions, (6) risk of complication, (7) adverse effects, (8) changes to diet, and (9) out-of-pocket costs. Participants chose between surgical profiles by comparing attributes. Survey data were collected from May 1, 2015, through January 30, 2016, and analyzed from February 1 to June 30, 2016.Main outcomes and measuresEstimated relative value of risks and benefits for leading weight-loss surgical options and marginal willingness to pay for procedure attributes. A latent class analysis identified respondent subgroups.ResultsAmong the 815 respondents (79.9% women; mean [SD] age, 44.5 [12.0] years), profiles of hypothetical procedures that included resolution of medical conditions (coefficient for full resolution, 0.229 [95% CI, 0.177 to 0.280; P < .001]; coefficient for no resolution, -0.207 [95% CI, -0.254 to -0.159; P < .001]), higher total weight loss (coefficient for each additional 20% loss, 0.185 [95% CI, 0.166 to 0.205; P < .001]), and lower out-of-pocket costs (coefficient for each additional $1000, -0.034 [95% CI, -0.042 to -0.025; P < .001]) were most likely to be selected. Younger respondents were more likely than older respondents to choose treatments with higher weight loss (coefficient for loss of 80% excess weight 0.543 [95% CI, 0.435-0.651] vs 0.397 [95% CI, 0.315-0.482]) and were more sensitive to out-of-pocket costs (coefficient for $100 out-of-pocket costs, 0.346 [95% CI, 0.221-0.470] vs 0.262 [95% CI, 0.174 to 0.350]; coefficient for $15 000 in out-of-pocket costs, -0.768 [95% CI, -0.938 to -0.598] vs -0.384 [95% CI, -0.500 to -0.268]). Marginal willingness to pay indicated respondents would pay $5470 for losing each additional 20% of excess body weight and $12 843 for resolution of existing medical conditions, the most desired procedure attributes. Latent class analysis identified the following 3 unobserved subgroups: cost-sensitive (most concerned with costs); benefit-focused (most concerned with excess weight loss and resolution of medical conditions); and procedure-focused (most concerned with how the treatment itself worked, including recovery and reversibility).Conclusions and relevanceCandidates for bariatric surgery identified costs, expected weight loss, and resolution of medical conditions as the most important characteristics of weight loss surgery decisions. Other information, such as risk of complications and adverse effects, were important to patients but less so.

Project description:BackgroundAcross most healthcare systems, patients are the primary focus. Patient involvements enhance their adherence to treatment, which in return, influences their health. The objective of this study was to determine the characteristics (ie, attributes) and associated levels (ie, values of the characteristics) that are the most important for patients regarding telerehabilitation (TR) healthcare to support a future discrete choice experiment (DCE) study design.MethodsA mixed-methods systematic review was conducted from January 2005 to the end of July 2020 and the search strategy was applied to five different databases. The initial selection of articles that met the eligibility criteria was independently made by one researcher, two researchers verified the accuracy of the extracted data, and all researchers discussed about relevant variables to include. Reporting of this systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the Mixed Methods Appraisal Tool (MMAT) was used to assess the quality of the study. A qualitative synthesis was used to summarize findings.ResultsFrom a total of 928 articles, 11 (qualitative [n = 5], quantitative [n = 3] and mixed-methods [n = 3] design) were included, and 25 attributes were identified and grouped into 13 categories: Accessibility, Distance, Interaction, Technology experience, Treatment mode, Treatment location, Physician contact mode, Physician contact frequency, Cost, Confidence, Ease of use, Feeling safer, and Training session. The attributes levels varied from two to five. The DCE studies identified showed the main stages to undertake these types of studies.ConclusionThis study could guide the development of interview grid for individual interviews and focus groups to support a DCE study design in the TR field. By understanding the characteristics that enhance patients' preferences, healthcare providers can create or improve TR programs that provide high-quality and accessible care. Future research via a DCE is needed to determine the relative importance of the attributes.

Project description:ObjectivesThis study reviews simulation studies of discrete choice experiments to determine (i) how survey design features affect statistical efficiency, (ii) and to appraise their reporting quality.OutcomesStatistical efficiency was measured using relative design (D-) efficiency, D-optimality, or D-error.MethodsFor this systematic survey, we searched Journal Storage (JSTOR), Since Direct, PubMed, and OVID which included a search within EMBASE. Searches were conducted up to year 2016 for simulation studies investigating the impact of DCE design features on statistical efficiency. Studies were screened and data were extracted independently and in duplicate. Results for each included study were summarized by design characteristic. Previously developed criteria for reporting quality of simulation studies were also adapted and applied to each included study.ResultsOf 371 potentially relevant studies, 9 were found to be eligible, with several varying in study objectives. Statistical efficiency improved when increasing the number of choice tasks or alternatives; decreasing the number of attributes, attribute levels; using an unrestricted continuous "manipulator" attribute; using model-based approaches with covariates incorporating response behaviour; using sampling approaches that incorporate previous knowledge of response behaviour; incorporating heterogeneity in a model-based design; correctly specifying Bayesian priors; minimizing parameter prior variances; and using an appropriate method to create the DCE design for the research question. The simulation studies performed well in terms of reporting quality. Improvement is needed in regards to clearly specifying study objectives, number of failures, random number generators, starting seeds, and the software used.ConclusionThese results identify the best approaches to structure a DCE. An investigator can manipulate design characteristics to help reduce response burden and increase statistical efficiency. Since studies varied in their objectives, conclusions were made on several design characteristics, however, the validity of each conclusion was limited. Further research should be conducted to explore all conclusions in various design settings and scenarios. Additional reviews to explore other statistical efficiency outcomes and databases can also be performed to enhance the conclusions identified from this review.

Dataset Information

Using Discrete Choice Methodology to Explore the Impact of Patient Room Window Design on Hospital Choice.

Publications

Using Discrete Choice Methodology to Explore the Impact of Patient Room Window Design on Hospital Choice.

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