Impact of educational and patient decision aids on decisional conflict associated with total knee arthroplasty

University of Texas MD Anderson Cancer Center, Houston, USA.
Arthritis care & research 02/2012; 64(2):229-37. DOI: 10.1002/acr.20646
Source: PubMed

ABSTRACT To examine the impact of a videobooklet patient decision aid supplemented by an interactive values clarification exercise on decisional conflict in patients with knee osteoarthritis (OA) considering total knee arthroplasty.
A total of 208 patients participated in the study (mean age 63 years, 68% female, and 66% white). Participants were randomized to 1 of 3 groups: 1) educational booklet on OA management (control), 2) patient decision aid (videobooklet) on OA management, and 3) patient decision aid (videobooklet) + adaptive conjoint analysis (ACA) tool. The ACA tool enables patients to consider competing attributes (i.e., specific risks/benefits) by asking them to rate a series of paired comparisons. The primary outcome was the decisional conflict scale ranging from 0-100. Differences between groups were analyzed using analysis of variance and Tukey's honestly significant difference tests.
Overall, decisional conflict decreased significantly in all groups (P < 0.05). The largest reduction in decisional conflict was observed for participants in the videobooklet decision aid group (21 points). Statistically significant differences in pre- versus postintervention total scores favored the videobooklet group compared to the control group (21 versus 10) and to the videobooklet plus ACA group (21 versus 14; P < 0.001). Changes in the decisional conflict score for the control group compared to the videobooklet decision aid + ACA group were not significantly different.
In our study, an audiovisual patient decision aid decreased decisional conflict more than printed material alone or the addition of a more complex computer-based ACA tool requiring more intense cognitive involvement and explicit value choices.

Download full-text


Available from: Maria E Suarez-Almazor, Aug 25, 2014
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Choosing the correct ventilator settings for the treatment of patients with respiratory tract disease is quite an important issue. Since the task of specifying the parameters of ventilation equipment is entirely carried out by a physician, physician's knowledge and experience in the selection of these settings has a direct effect on the accuracy of his/her decisions. Nowadays, decision support systems have been used for these kinds of operations to eliminate errors. Our goal is to minimize errors in ventilation therapy and prevent deaths caused by incorrect configuration of ventilation devices. The proposed system is designed to assist less experienced physicians working in the facilities without having lung mechanics like cottage hospitals. This article describes a decision support system proposing the ventilator settings required to be applied in the treatment according to the patients' physiological information. The proposed model has been designed to minimize the possibility of making a mistake and to encourage more efficient use of time in support of the decision making process while the physicians make critical decisions about the patient. Artificial Neural Network (ANN) is implemented in order to calculate frequency, tidal volume, FiO2 outputs, and this classification model has been used for estimation of pressure support / volume support outputs. For the obtainment of the highest performance in both models, different configurations have been tried. Various tests have been realized for training methods, and a number of hidden layers mostly affect factors regarding the performance of ANNs. The physiological information of 158 respiratory patients over the age of 60 and were treated in three different hospitals between the years 2010 and 2012 has been used in the training and testing of the system. The diagnosed disease, core body temperature, pulse, arterial systolic pressure , diastolic blood pressure, PEEP, PSO2, pH, pCO2, bicarbonate data as well as the frequency, tidal volume, FiO2, and pressure support / volume support values suitable for use in the ventilator device have been recommended to the physicians with an accuracy of 98,44 %. Performed experiments show that sequential order weight/bias training was found to be the most ideal ANN learning algorithm for regression model and Bayesian regulation backpropagation was found to be the most ideal ANN learning algorithm for classification models. This article aims at making independent of the choice of parameters from physicians in the ventilator treatment of respiratory tract patients with proposed decision support system. The rate of accuracy in prediction of systems increases with the use of data of more patients in training. Therefore, non-physician operators can use systems in determination of ventilator settings in case of emergencies.
    BMC Medical Informatics and Decision Making 01/2014; 14(1):3. DOI:10.1186/1472-6947-14-3 · 1.50 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Purpose: To create and validate educational material for patients undergoing orthognathic surgery. Methods: The design included five phases: (a) a review of the literature regarding surgical complications; (b) gathering information on the needs of patients through blogs and virtual communities; (c) evaluating patient perceptions of the post-operative period through a focus group; (d) obtaining information through specialists using the Delphi technique and validation by judges; and (e) validation by patients in terms of understanding the exhibited material. Results: The first three phases of the study and the first round of the Delphi technique assisted in generating the perioperative patient booklet. The following rounds of the Delphi technique introduced modifications to improve the material, with the judges agreeing on the final material to be validated by patients. Conclusion: Creating a booklet involves more than simply writing summarized ideas on a paper and handing it to the patient. One must understand the population, involve the relevant professionals, and obtain high-quality graphic aids for this type of educational material.
    Asian Nursing Research 12/2012; 6:166-172. DOI:10.1016/j.anr.2012.10.006 · 0.42 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Despite evidence that shared decision-making tools for treatment decisions improve decision quality and patient engagement, they are not commonly employed in orthopaedic practice. The purpose of this study was to evaluate the impact of decision and communication aids on patient knowledge, efficiency of decision making, treatment choice, and patient and surgeon experience in patients with osteoarthritis of the hip or knee. One hundred and twenty-three patients who were considered medically appropriate for hip or knee replacement were randomized to either a shared decision-making intervention or usual care. Patients in the intervention group received a digital video disc and booklet describing the natural history and treatment alternatives for hip and knee osteoarthritis and developed a structured list of questions for their surgeon in consultation with a health coach. Patients in the control group received information about the surgeon's practice. Both groups reported their knowledge and stage in decision making and their treatment choice, satisfaction, and communication with their surgeon. Surgeons reported the appropriateness of patient questions and their satisfaction with the visit. The primary outcome measure tracked whether patients reached an informed decision during their first visit. Statistical analyses were performed to evaluate differences between groups. Significantly more patients in the intervention group (58%) reached an informed decision during the first visit compared with the control group (33%) (p = 0.005). The intervention group reported higher confidence in knowing what questions to ask their doctor (p = 0.0034). After the appointment, there was no significant difference between groups in the percentage of patients choosing surgery (p = 0.48). Surgeons rated the number and appropriateness of patient questions higher in the intervention group (p < 0.0001), reported higher satisfaction with the efficiency of the intervention group visits (p < 0.0001), and were more satisfied overall with the intervention group visits (p < 0.0001). Decision and communication aids used in orthopaedic practice had benefits for both patients and surgeons. These findings could be important in facilitating adoption of shared decision-making tools into routine orthopaedic practice. Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
    The Journal of Bone and Joint Surgery 09/2013; 95(18):1633-9. DOI:10.2106/JBJS.M.00004 · 4.31 Impact Factor