Patient satisfaction with oncology clinical decision support in South Korea.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18329-e18329
Author(s):  
Kyounga Lee ◽  
Seon Heui Lee ◽  
Anita Preininger ◽  
JungHo Shim ◽  
Gretchen Jackson
Keyword(s):  
Decision Making ◽  
Medical Center ◽  
Treatment Decision ◽  
Clinical Decision ◽  
Treatment Decisions ◽  
Tumor Board ◽  
Fully Integrated ◽  
Treatment Decision Making ◽  
Level Of Satisfaction ◽  
Significant Difference

e18329 Background: Watson For Oncology (WFO) is an artificial intelligence (AI) tool that presents therapeutic options to oncologists and patients at 9 hospitals in Korea. The earliest user is Gachon University Gil Medical Center (GMC), where the tumor board (MDT) is fully integrated with WfO (MDT-WfO). GMC patients and oncologists may select one of the treatment choices presented by MDT-WfO or choose to follow recommendations of one or more oncologists at GMC augmented by WfO (non-MDT-WfO). This study is aimed at determining the satisfaction of patients who pursue shared decision-making through the MDT-WfO approach. Methods: Cancer patients enrolled in this IRB-approved study and treated at GMC between March and September of 2018 were surveyed. All patients rated satisfaction levels from 1-10 after treatment decision-making was completed, with 1 indicating the lowest level of satisfaction and 10 the highest. For each question, the average satisfaction score for patients in the MDT-WfO group was compared to the mean for patients in the non-MDT-WfO group, with a t-test for significance. Results: There were 9 cancer types treated at GMC from March through September of 2018. Of the of 290 patients enrolled in this study, 130 (44.8%) selected MDT-WfO and 160 (55.2%) did not. Overall, patients that interacted with MDT-WfO viewed GMT more positively (86.9%) after treatment decisions had been made than patients in the non-MDT-WfO group (71.3%).Although patients did not report significantly differing levels of satisfaction for most survey questions, there was a significant difference in terms of satisfaction with the explanation they received from the medical staff. Satisfaction level for this item was 9.52 with MDT-WfO and 9.22 points without ( p = 0.029). Conclusions: Patients reported greater satisfaction in the explanations they received in the MDT-WfO group, consistent with their more positive impression of GMT after treatment decisions were made. More studies are needed to determine if the increase in the level of satisfaction for this item is due to explanations from MDT unrelated or related to WfO. More studies on how WfO is used differently by the tumor board and individual oncologists may provide a unique perspective on how WfO is integrated into the MDT.

Physicians' views on the influence of patient participation on treatment decisions - an explorative study

2007 ◽  
Vol 20 (3) ◽  
pp. 174-182 ◽  
Author(s):  
Elina Jaakkola
Keyword(s):  
Decision Making ◽  
Patient Participation ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Role Expectations ◽  
Customer Participation ◽  
Health Care Managers ◽  
Treatment Decision Making ◽  
Explorative Study ◽  
Significant Difference

While patient participation in treatment decisions is increasingly advocated in medical literature, patient demand has been considered to cause unnecessary prescribing. Using the concept of customer participation as discussed in services marketing and management literature as a theoretical base, the paper analyses the influence of patient participation on the medical service process and treatment decision-making. A qualitative, explorative study was conducted to investigate American and British physicians' views on patient participation in the treatment of osteoporosis and schizophrenia. It became evident that in the cases of both osteoporosis and schizophrenia, patients influence prescribing decisions despite the significant difference in their willingness and ability to participate. The manifestations of patient participation were divided into three groups: (1) resources, such as the patient's condition and information about it, and his/her preconceived notions and preferences, (2) actions, such as preparing for the service, negotiating decisions and implementing the treatment, and (3) the patient's role expectations and inclination to participate. The influence of such manifestations on prescribing decision-making is discussed in detail, and differences between the studied illnesses are explained. Implications to health-care managers and practitioners are discussed.

Causal inference for clinicians

2019 ◽  
Vol 24 (3) ◽  
pp. 109-112 ◽  
Author(s):  
Steven D Stovitz ◽  
Ian Shrier
Keyword(s):  
Decision Making ◽  
Causal Inference ◽  
Clinical Decision Making ◽  
Causal Effect ◽  
Treatment Decision ◽  
Clinical Decision ◽  
Directed Acyclic Graphs ◽  
Causal Effects ◽  
Treatment Decision Making ◽  
Inference Methods

Evidence-based medicine (EBM) calls on clinicians to incorporate the ‘best available evidence’ into clinical decision-making. For decisions regarding treatment, the best evidence is that which determines the causal effect of treatments on the clinical outcomes of interest. Unfortunately, research often provides evidence where associations are not due to cause-and-effect, but rather due to non-causal reasons. These non-causal associations may provide valid evidence for diagnosis or prognosis, but biased evidence for treatment effects. Causal inference aims to determine when we can infer that associations are or are not due to causal effects. Since recommending treatments that do not have beneficial causal effects will not improve health, causal inference can advance the practice of EBM. The purpose of this article is to familiarise clinicians with some of the concepts and terminology that are being used in the field of causal inference, including graphical diagrams known as ‘causal directed acyclic graphs’. In order to demonstrate some of the links between causal inference methods and clinical treatment decision-making, we use a clinical vignette of assessing treatments to lower cardiovascular risk. As the field of causal inference advances, clinicians familiar with the methods and terminology will be able to improve their adherence to the principles of EBM by distinguishing causal effects of treatment from results due to non-causal associations that may be a source of bias.

HSR19-089: Misperceptions Regarding Palliative and Hospice Care Among Cancer Patients: What Can We Learn from Patient-Reported Treatment Decision Making

2019 ◽  
Vol 17 (3.5) ◽  
pp. HSR19-089
Author(s):  
Sara Hayes ◽  
Brian M. Green ◽  
Shayna Yeates ◽  
Amrita Bhowmick ◽  
Kaitlyn McNamara ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Decision Making ◽  
Palliative Care ◽  
Cancer Care ◽  
Hospice Care ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Treatment Decision Making ◽  
Diagnosis Of Cancer

Background: Despite NCCN Guidelines and clear definition of palliative care, patients often carry misperceptions about palliative care and how it can be beneficially integrated into a patient’s care plan. In order to better understand the misinformation about palliative and hospice care, this study aims to assess patient-healthcare provider (HCP) communication regarding treatment decisions. Methods: An online survey was conducted with individuals who have had a diagnosis of cancer (n=1,517) to better understand their healthcare experiences as well as the impact their cancer diagnosis had on their quality of life. Measures included agreement scale questions assessing patient information needs surrounding treatment decision making. Open-ended questions where respondents were prompted to provide a written response allowed researchers to further assess patients’ understanding of palliative and hospice care. Responses to agreement-scale questions were evaluated using descriptive statistics. Openended question responses were analyzed using Dedoose qualitative data analysis software. Results: Among patients with a diagnosis of cancer, there were a broad range of patient misperceptions regarding palliative care, hospice care, and how they are used in cancer care. The majority of respondents (81%) stated that their HCP played a role when deciding on their treatment plan. Despite this, only 46% were confident they knew about the treatment’s impact on their daily life, 56% were confident they knew about the potential side effects of treatment, and 57% felt they had all of the information they needed. Themes identified through qualitative analysis include: patient conflation of palliative and hospice care, belief that palliative and hospice care are only relevant to end-of-life decision-making, and uncertainty about whether quality of life can actually be improved. Conclusions: Institutions and HCPs are recommended to integrate palliative care into cancer care. However, as this research shows, oncology patients are often misinformed about the benefits of palliative care. This follows a parallel concern of patients making treatment decisions without optimal information. A potential factor behind this unmet need may be lack of effective communication between patient and HCP. Palliative care may be mentioned by the HCP, but not discussed with enough empathy or depth, leading to patient misunderstanding and lack of inclusion in treatment plans.

Size and influence of the decision support networks of women newly diagnosed with breast cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18012-e18012
Author(s):  
Lauren P. Wallner ◽  
Yun Li ◽  
Chandler McLeod ◽  
Ann S Hamilton ◽  
Kevin C. Ward ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Decision Support ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Breast Cancer Treatment ◽  
Network Size ◽  
Support Networks ◽  
Newly Diagnosed ◽  
Treatment Decision Making

e18012 Background: Little is known about the size and characteristics of informal decision support networks of women diagnosed with breast cancer and whether involvement of informal decision supporters (DSP) influences breast cancer treatment decisions. Methods: A population-based sample of newly diagnosed breast cancer patients reported to the Georgia and Los Angeles SEER registries in 2014-15 were surveyed approximately 6 months after diagnosis (N = 2,502, 68% response rate). Network size was estimated by asking women to list up to 3 of the most important DSPs who helped them with locoregional therapy decisions. For each individual DSP listed, respondents reported how important each DSP’s opinion was in treatment decision making, and how satisfied they were with their involvement (5 pt. scales, “not at all” to “very”). Decision deliberation was measured using 5-items assessing degree patients thought through the decision, with higher scores reflecting more deliberative treatment decisions. We compared network size (0-3 or more) across patient-level characteristics and estimated the association between network size and deliberation using multivariable linear regression. Results: Of the 2,502 women in this analysis, 51% reported having 3 or more DSPs, 20% reported 2, 18% reported 1, and 11% reported not having any DSPs. Married/partnered women, those younger than 45 years old, and black women were all more likely to report larger networks (all p < 0.001). Partnered women most often reported their partner as their main DSP (37.9%), whereas not partnered/unmarried women most often reported children (38.4%). The majority of women were highly satisfied with their DSP being involved in their decisions (76.5%) and 68.6% felt their DSP was very important in their decision making. Larger support networks were associated with more deliberative surgical treatment decision-making (p < 0.001). Conclusions: Most women engaged multiple DSPs in their treatment decision making, including spouses, children, and friends. Involving more DSPs was associated with more deliberative treatment decisions. Future initiatives to improve breast cancer treatment decision making should acknowledge and engage informal DSPs.

“It’s important to me”: A qualitative analysis of shared decision-making and patient preferences in early-stage breast cancer patients.

2019 ◽  
Vol 37 (27_suppl) ◽  
pp. 227-227
Author(s):  
Valerie Lawhon ◽  
Rebecca England ◽  
Audrey S. Wallace ◽  
Courtney Williams ◽  
Stacey A. Ingram ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Shared Decision Making ◽  
Patient Preferences ◽  
Early Stage ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Early Stage Breast Cancer ◽  
Shared Decision ◽  
Treatment Decision Making

227 Background: Shared decision-making (SDM) occurs when both patient and provider are involved in the treatment decision-making process. SDM allows patients to understand the pros and cons of different treatments while also helping them select the one that aligns with their care goals when multiple options are available. This qualitative study sought to understand different factors that influence early-stage breast cancer (EBC) patients’ approach in selecting treatment. Methods: This cross-sectional study included women with stage I-III EBC receiving treatment at the University of Alabama at Birmingham from 2017-2018. To understand SDM preferences, patients completed the Control Preferences Scale and a short demographic questionnaire. To understand patient’s values when choosing treatment, semi-structured interviews were conducted to capture patient preferences for making treatment decisions, including surgery, radiation, or systemic treatments. Interviews were audio-recorded, transcribed, and analyzed using NVivo. Two coders analyzed transcripts using a constant comparative method to identify major themes related to decision-making preferences. Results: Amongst the 33 women, the majority of patients (52%) desired shared responsibility in treatment decisions. 52% of patients were age 75+ and 48% of patients were age 65-74, with an average age of 74 (4.2 SD). 21% of patients were African American and 79% were Caucasian. Interviews revealed 19 recurrent treatment decision-making themes, including effectiveness, disease prognosis, physician and others’ opinions, side effects, logistics, personal responsibilites, ability to accomplish daily activities or larger goals, and spirituality. EBC patient preferences varied widely in regards to treatment decision-making. Conclusions: The variety of themes identified in the analysis indicate that there is a large amount of variability to what preferences are most crucial to patients. Providers should consider individual patient needs and desires rather than using a “one size fits all” approach when making treatment decisions. Findings from this study could aid in future SDM implementations.

Integrating touchscreen-based geriatric assessment and frailty screening for adults with acute myelogenous leukemia to drive personalized treatment decisions.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e24030-e24030
Author(s):  
Debra Wujcik ◽  
Nikolaos Papadantonakis ◽  
Sarah Allison Wall ◽  
Margaret T. Kasner ◽  
OMER HASSAN JAMY ◽  
...  
Keyword(s):  
Decision Making ◽  
Frailty Index ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Self Report ◽  
Myelogenous Leukemia ◽  
Valuable Insight ◽  
Nccn Guidelines ◽  
Treatment Decision Making ◽  
Patient Reported

e24030 Background: AML is a disease of older adults, with median age of 68 years at presentation. NCCN guidelines suggest comprehensive geriatric assessments (GA) be included in clinical practice to guide treatment decisions. Utility of GA in older AML patients in a real-world environment is not yet established. We tested the feasibility of using a modified GA (mGA), administered by patient self-report on a touchscreen computer, real-time use and utility by clinicians and the correlation of mGA results on treatment decision-making. Methods: Sixty-two patients were recruited from three sites to complete a tablet-based mGA screening at a treatment decision-making time point. The mGA consists of the Frailty Index (FI) that includes four domains: age, activities of daily living, instrumental ADLs, and comorbidities. Falls within the past 6 months and patient reported health interference with function are also assessed. Results are displayed for the clinician to inform the treatment discussion. Results: Participants were mean age 73 years (range 61-88), 63% male, and 90% white. Frailty Index result was 32% fit, 40% intermediate, and 28% frail. Providers were asked the fit/frailty status prior to seeing the results of the mGA. Of 53 provider responses, there was 57% (n=30) provider concordance with the mGA result; 9% (n=5) said fit when mGA said intermediate and 17% (n=9) said intermediate when mGA said frail. When asked their goals of care, nearly all (n=60, 97%) patients agreed with the statement “my cancer is curable”, yet 30% (n=19) disagreed the treatment goal was to get rid of all the cancer. Nearly half (n=30) indicated they want to make treatment decisions together with the provider rather than provider or patient making decision alone. 73% (45/62) of patients were satisfied with the ease of using the survey and took an average 16.3 minutes to complete. Patient self-reported presence/severity of eight symptoms at baseline (see Table). Conclusions: A simple electronic tool may provide valuable insight into patient understanding of disease to better tailor patient-provider discussion and treatment decision-making. Providers overestimated fitness 26% of the time. Final results will be presented to include the outcome at 3 months by Frailty Index. [Table: see text]

scholarly journals Qualitative Study of Factors That Influence Treatment Decision-Making Among Community Oncologists and Older Patients with Acute Myeloid Leukemia

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2246-2246 ◽  
Author(s):  
Kah Poh Loh ◽  
Sindhuja Kadambi ◽  
Supriya G. Mohile ◽  
Jason H. Mendler ◽  
Jane L. Liesveld ◽  
...  
Keyword(s):  
Decision Making ◽  
Qualitative Study ◽  
Older Patients ◽  
Clinical Decision Making ◽  
Real Life ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Cell Transplant ◽  
Hematopoietic Stem ◽  
Treatment Decision Making

Abstract Introduction: Despite data supporting the safety and efficacy of treatment for many older adults with AML, <40% of adults aged ≥65 receive any leukemia-directed therapy. The reasons for why the majority of older patients with AML do not receive therapy are unclear. The use of objective fitness measures (e.g. physical function and cognition) has been shown to predict outcomes and may assist with treatment decision-making, but is underutilized. As most patients are initially evaluated in community practices, exploring clinical decision-making and the barriers to performing objective fitness assessments in the community oncology setting is critical to understanding current patterns of care. We conducted a qualitative study: 1) to identify factors that influence treatment decision making from the perspectives of the community oncologists and older patients with AML, and 2) to understand the barriers to performing objective fitness assessments among oncologists. The findings will help to inform the design of a larger study to assess real-life treatment decision-making among community oncologists and patients. Methods: We conducted semi-structured interviews with 13 community oncologists (9 states) and 9 patients aged ≥60 with AML at any stage of treatment to elicit potential factors that influence treatment decisions. Patients were recruited from the outpatient clinics in a single institution and oncologists were recruited via email using purposive samples (patients: based on treatment received and stage of treatment; oncologists: based on practice location). Interviews were audio-recorded and transcribed. We utilized directed content analysis and adapted the decision-making model introduced by Zafar et al. to serve as a framework for categorizing the factors at various levels. A codebook was provisionally developed. Using Atlas.ti, two investigators independently coded the initial transcripts and resolved any discrepancies through an iterative process. The coding scheme was subsequently applied to the rest of the transcripts by one coder. Results: Median age of the oncologists was 37 years (range 34-64); 62% were females, 92% were white, 38% had practiced more than 15 years, and 92% reported seeing <10 older patients with AML annually. Median age of the patients was 70 years (64-80), 33% were females and all were Caucasian. In terms of treatment, 66% received intensive induction therapy, 22% received low-intensity treatment, and 11% received both. Three patients also received allogeneic hematopoietic stem cell transplant. Eighty-nine percent were initially evaluated and 56% were initially treated by a community oncologist. Factors that influenced treatment decision-making are shown in Figure 1. When making treatment decisions, both patients and oncologists considered factors such as patient's overall health, chronological age, comorbidities, insurance coverage, treatment efficacy and tolerability, and distance to treatment center. Nonetheless, there were distinct factors considered by patients (e.g. quality of care and facility, trust in their oncologist/team) and by oncologists (e.g. local practice patterns, availability of transplant/clinical trials, their own clinical expertise and beliefs) when making treatment decisions. The majority of oncologists do not perform an objective assessment of fitness. Most common reasons provided included: 1) Do not add much to routine assessments (N=8), 2) Lack of time, resources, and expertise (N=7), 3) Lack of awareness of the tools or the evidence to support its use (N=4), 4) Specifics are not important (e.g. impairments are clinically apparent and further nuance is not necessarily helpful; N=5), 5) Impairments are usually performed by other team members (N=2), and 6) Do not want to rely on scores (N=2). Conclusions: Treatment decision-making for older patients with AML is complex and influenced by many factors at the patient, disease/treatment, physician, and organizational levels. Despite studies supporting the utility of objective fitness assessments, these were not commonly performed in the community due to several barriers. Our framework will be useful to guide a larger study to assess real-life treatment decision-making in the community settings. We also identified several barriers raised by community oncologists that could be targeted to allow incorporation of objective fitness assessments. Figure 1. Figure 1. Disclosures Liesveld: Onconova: Other: DSMB; Abbvie: Honoraria. Stock:Jazz Pharmaceuticals: Consultancy. Majhail:Anthem, Inc.: Consultancy; Atara: Honoraria; Incyte: Honoraria. Wildes:Janssen: Research Funding. Klepin:Genentech Inc: Consultancy.

scholarly journals Treatment Decision Making and Treatment Satisfaction Among Individuals Living with Chronic Myeloid Leukemia

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4787-4787
Author(s):  
Julie Olson ◽  
Shauna McManus ◽  
Melissa F. Miller ◽  
Thomas W. LeBlanc ◽  
Eva Yuen ◽  
...  
Keyword(s):  
Decision Making ◽  
Treatment Outcomes ◽  
Board Of Directors ◽  
Research Funding ◽  
Treatment Options ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Advisory Committees ◽  
Treatment Decision Making ◽  
Satisfaction With Treatment

Abstract Background: Over the past decade, an increase in treatment options for chronic myeloid leukemia (CML) has dramatically changed the therapeutic landscape and has improved clinical outcomes. This abundance of treatment options may make it difficult for CML patients to feel knowledgeable about what options are available to them, may hinder patients' preparedness for having conversations about treatment, and, similarly, may contribute to patients feeling less involved in treatment decision making (TDM). In light of this changing landscape, we explored whether the TDM experience was linked to satisfaction with treatment outcomes in a national sample of CML patients. Methods: Using data from the Cancer Support Community's Cancer Experience Registry®, our analytic sample included 310 participants who reported CML as their primary diagnosis. The dependent variable in all analyses was a dichotomous, patient-reported indicator of satisfaction with treatment outcomes (satisfied or not satisfied). Our independent variables include three measures that capture the TDM experience: feeling involved in the TDM process; feeling knowledgeable about treatment options prior to making treatment decisions; and, feeling prepared to discuss treatment options with one's doctor. Respondents ranked TDM knowledge, preparedness, and involvement from 0 = "not at all" to 4 = "very much." Responses were dichotomized such that 1 = "quite a bit" or "very much" and 0 = "not at all," "a little bit" or "somewhat." Analytically, we compared patients who reported high satisfaction with treatment outcomes to those who reported low satisfaction, using Student's t-test. Then, we estimated multivariate logistic regression models predicting odds of being satisfied with treatment outcome by TDM knowledge, preparedness, and involvement. Regression models controlled for demographic characteristics including age, gender, and race; clinical factors such as time since diagnosis and symptom burden; treatment-related measures including financial impact of treatment; and the degree to which individuals felt their health care teams prepared them to manage treatment side effects. Results: Descriptively, our sample was 65% female and 87% non-Hispanic White, with an average age of 56.6 years (SD = 12) and mean time since diagnosis of 6 years (SD = 5). Most (74%) reported being "quite a bit" to "very much satisfied" with their treatment outcomes. Experiences with TDM, however, were variable. When making treatment decisions, 52% reported feeling involved, 41% reported feeling knowledgeable, and 21% felt prepared. Importantly, t-test results suggested that individuals with greater involvement, more knowledge, and higher preparedness were significantly more likely to report satisfaction with treatment outcomes. Results of the multivariate models demonstrated a greater likelihood of treatment satisfaction among individuals who felt prepared to discuss treatment options with their health care team, even after controlling for demographic, clinical, and treatment-related characteristics. In fact, prepared individuals were nearly 6 times as likely to be satisfied with their treatment outcomes, as compared to individuals who did not feel prepared to discuss treatment options (p < .05). Conclusion: Most of our patients with CML did not feel prepared to make treatment decisions. However, those who feel more prepared to discuss treatment options with their doctors are also more likely to report satisfaction with treatment outcomes. As new CML treatment options become available, our results highlight the need for an increased focus on shared decision making in clinical practice. This may necessitate providing patients with more resources to help prepare them for treatment-related conversations. Disclosures Birhiray: Takeda: Research Funding, Speakers Bureau; Genomic Health: Patents & Royalties; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Alexion: Consultancy; Puma: Research Funding, Speakers Bureau; Pharmacyclics: Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Bristol Myers Squibb: Speakers Bureau; Norvatis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bayer: Membership on an entity's Board of Directors or advisory committees; Eli-Lilly: Speakers Bureau; Excelis: Speakers Bureau; Clovis Oncology: Speakers Bureau; Sanofi Oncology: Speakers Bureau; Incyte: Speakers Bureau; AstraZeneca: Speakers Bureau; Tessaro: Speakers Bureau; Pfizer: Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees; Helsinn: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees.

scholarly journals ADOLESCENT PATIENTS AND THE CLINICAL DECISION ABOUT THEIR HEALTH

2019 ◽  
Vol 37 (4) ◽  
pp. 503-509
Author(s):  
Marlene Pereira Garanito ◽  
Vera Lucia Zaher-Rutherford
Keyword(s):  
Decision Making ◽  
Latin American ◽  
Clinical Decision Making ◽  
Case Reports ◽  
Treatment Decision ◽  
Clinical Decision ◽  
Electronic Library ◽  
Data Synthesis ◽  
Treatment Decision Making ◽  
The Individual

ABSTRACT Objective: To carry out a review of the literature on adolescents’ participation in decision making for their own health. Data sources: Review in the Scientific Electronic Library Online (SciELO), Latin American and Caribbean Health Sciences Literature (LILACS) and PubMed databases. We consider scientific articles and books between 1966 and 2017. Keywords: adolescence, autonomy, bioethics and adolescence, autonomy, ethics, in variants in the English, Portuguese and Spanish languages. Inclusion criteria: scientific articles, books and theses on clinical decision making by the adolescent patient. Exclusion criteria: case reports and articles that did not address the issue. Among 1,590 abstracts, 78 were read in full and 32 were used in this manuscript. Data synthesis: The age at which the individual is able to make decisions is a matter of debate in the literature. The development of a cognitive and psychosocial system is a time-consuming process and the integration of psychological, neuropsychological and neurobiological research in adolescence is fundamental. The ability to mature reflection is not determined by chronological age; in theory, a mature child is able to consent or refuse treatment. Decision-making requires careful and reflective analysis of the main associated factors, and the approach of this problem must occur through the recognition of the maturity and autonomy that exists in the adolescents. To do so, it is necessary to “deliberate” with them. Conclusions: International guidelines recommend that adolescents participate in discussions about their illness, treatment and decision-making. However, there is no universally accepted consensus on how to assess the decision-making ability of these patients. Despite this, when possible, the adolescent should be included in a serious, honest, respectful and sincere process of deliberation.

The relationship between cancer patient treatment decision-making roles and quality of life (QOL)

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 6075-6075
Author(s):  
P. J. Atherton ◽  
T. Smith ◽  
J. Huntington ◽  
M. Huschka ◽  
J. A. Sloan
Keyword(s):  
Decision Making ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Patient Expectations ◽  
Patient Treatment ◽  
Satisfaction With Care ◽  
Cancer Society ◽  
Treatment Decision Making ◽  
Role Preference ◽  
Sf 36

6075 Background: Failing to meet patient expectations for participating in treatment decisions impacts satisfaction with care, but it is unknown whether this translates into QOL deficits. As part of a larger survey of cancer survivors conducted by the American Cancer Society (ACS), data were gathered on the role patients in Minnesota preferred and the role actually experienced during the treatment decision-making process. Methods: Patients who were diagnosed with one of the ten most common cancers in 2000 completed a survey containing the Profile of Mood States (POMS), the SF-36, and the Control Preferences Scale (CPS). Fisher’s exact tests compared role preference distributions across demographic categories. Two-sample t-tests compared the POMS and SF-36 scores between patients whose preferred role preference was concordant with the role experienced and those with discordant preferred and actual roles. Results: 33% of the 599 consenting patients preferred an active role in treatment decision-making, 52% preferred a collaborative role, and 13% preferred a passive role. The actual roles experienced were 33% active, 50% collaborative, 17% passive. Over 88% of patients had concordant preferred and actual roles. Patients with concordant roles had higher SF-36 physical scores (45 vs 40, p=0.004), higher vitality (50 vs 42, p=0.005), less fatigue (70.2 vs 60.1, p=0.001), better concentration (84 vs 79, p=0.008) and better overall mood (77 vs 73, p=0.006). Role preference differed across gender (p=0.0002) in that more women preferred a collaborative role than men (57.8% vs 45.5%) and fewer women preferred a passive role (9% vs 17.3%). Patients under age 50 experienced more active roles in treatment decisions than those aged 50+ (p=0.04). Patients reporting an active actual role had higher SF-36 physical scores (p=0.005) and higher POMS vigor subscale scores (p=0.04). There were no differences in QOL scores for preferred roles. Conclusions: Patients who experienced discordance between their preferred role and their experience reported substantial QOL deficits in both physical and emotional domains. Oncologists can improve patient satisfaction with care and QOL by meeting patient expectations with respect to the amount of input they have in making treatment decisions. No significant financial relationships to disclose.

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