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1.  Evidence summaries (decision boxes) to prepare clinicians for shared decision-making with patients: a mixed methods implementation study 
Decision boxes (Dboxes) provide clinicians with research evidence about management options for medical questions that have no single best answer. Dboxes fulfil a need for rapid clinical training tools to prepare clinicians for clinician-patient communication and shared decision-making. We studied the barriers and facilitators to using the Dbox information in clinical practice.
We used a mixed methods study with sequential explanatory design. We recruited family physicians, residents, and nurses from six primary health-care clinics. Participants received eight Dboxes covering various questions by email (one per week). For each Dbox, they completed a web questionnaire to rate clinical relevance and cognitive impact and to assess the determinants of their intention to use what they learned from the Dbox to explain to their patients the advantages and disadvantages of the options, based on the theory of planned behaviour (TPB). Following the 8-week delivery period, we conducted focus groups with clinicians and interviews with clinic administrators to explore contextual factors influencing the use of the Dbox information.
One hundred clinicians completed the web surveys. In 54% of the 496 questionnaires completed, they reported that their practice would be improved after having read the Dboxes, and in 40%, they stated that they would use this information for their patients. Of those who would use the information for their patients, 89% expected it would benefit their patients, especially in that it would allow the patient to make a decision more in keeping with his/her personal circumstances, values, and preferences. They intended to use the Dboxes in practice (mean 5.6 ± 1.2, scale 1–7, with 7 being “high”), and their intention was significantly related to social norm, perceived behavioural control, and attitude according to the TPB (P < 0.0001). In focus groups, clinicians mentioned that co-interventions such as patient decision aids and training in shared decision-making would facilitate the use of the Dbox information. Some participants would have liked a clear “bottom line” statement for each Dbox and access to printed Dboxes in consultation rooms.
Dboxes are valued by clinicians. Tailoring of Dboxes to their needs would facilitate their implementation in practice.
Electronic supplementary material
The online version of this article (doi:10.1186/s13012-014-0144-6) contains supplementary material, which is available to authorized users.
PMCID: PMC4201673  PMID: 25280742
Clinical practice guidelines; Knowledge translation; Decision support; Evidence-based practice; Barriers; Patient-centred care; User experience; Continuing professional development; Communication competency
2.  Decision boxes for clinicians to support evidence-based practice and shared decision making: the user experience 
This project engages patients and physicians in the development of Decision Boxes, short clinical topic summaries covering medical questions that have no single best answer. Decision Boxes aim to prepare the clinician to communicate the risks and benefits of the available options to the patient so they can make an informed decision together.
Seven researchers (including four practicing family physicians) selected 10 clinical topics relevant to primary care practice through a Delphi survey. We then developed two one-page prototypes on two of these topics: prostate cancer screening with the prostate-specific antigen test, and prenatal screening for trisomy 21 with the serum integrated test. We presented the prototypes to purposeful samples of family physicians distributed in two focus groups, and patients distributed in four focus groups. We used the User Experience Honeycomb to explore barriers and facilitators to the communication design used in Decision Boxes. All discussions were transcribed, and three researchers proceeded to thematic content analysis of the transcriptions. The coding scheme was first developed from the Honeycomb’s seven themes (valuable, usable, credible, useful, desirable, accessible, and findable), and included new themes suggested by the data. Prototypes were modified in light of our findings.
Three rounds were necessary for a majority of researchers to select 10 clinical topics. Fifteen physicians and 33 patients participated in the focus groups. Following analyses, three sections were added to the Decision Boxes: introduction, patient counseling, and references. The information was spread to two pages to try to make the Decision Boxes less busy and improve users’ first impression. To try to improve credibility, we gave more visibility to the research institutions involved in development. A statement on the boxes’ purpose and a flow chart representing the shared decision-making process were added with the intent of clarifying the tool’s purpose. Information about the risks and benefits according to risk levels was added to the Decision Boxes, to try to ease the adaptation of the information to individual patients.
Results will guide the development of the eight remaining Decision Boxes. A future study will evaluate the effect of Decision Boxes on the integration of evidence-based and shared decision making principles in clinical practice.
PMCID: PMC3533695  PMID: 22862935
Evidence-based medicine; User experience; Risk communication; Usability; Patient-centered care; Counselling; Clinical topic summary; Decision support; Knowledge translation; Communication design
3.  Developing and user-testing Decision boxes to facilitate shared decision making in primary care - a study protocol 
Applying evidence is one of the most challenging steps of evidence-based clinical practice. Healthcare professionals have difficulty interpreting evidence and translating it to patients. Decision boxes are summaries of the most important benefits and harms of diagnostic, therapeutic, and preventive health interventions provided to healthcare professionals before they meet the patient. Our hypothesis is that Decision boxes will prepare clinicians to help patients make informed value-based decisions. By acting as primers, the boxes will enhance the application of evidence-based practices and increase shared decision making during the clinical encounter. The objectives of this study are to provide a framework for developing Decision boxes and testing their value to users.
We will begin by developing Decision box prototypes for 10 clinical conditions or topics based on a review of the research on risk communication. We will present two prototypes to purposeful samples of 16 family physicians distributed in two focus groups, and 32 patients distributed in four focus groups. We will use the User Experience Model framework to explore users' perceptions of the content and format of each prototype. All discussions will be transcribed, and two researchers will independently perform a hybrid deductive/inductive thematic qualitative analysis of the data. The coding scheme will be developed a priori from the User Experience Model's seven themes (valuable, usable, credible, useful, desirable, accessible and findable), and will include new themes suggested by the data (inductive analysis). Key findings will be triangulated using additional publications on the design of tools to improve risk communication. All 10 Decision boxes will be modified in light of our findings.
This study will produce a robust framework for developing and testing Decision boxes that will serve healthcare professionals and patients alike. It is the first step in the development and implementation of a new tool that should facilitate decision making in clinical practice.
PMCID: PMC3060840  PMID: 21385470
4.  Decision Aid to Technologically Enhance Shared decision making (DATES): study protocol for a randomized controlled trial 
Trials  2013;14:381.
Clinicians face challenges in promoting colorectal cancer screening due to multiple competing demands. A decision aid that clarifies patient preferences and improves decision quality can aid shared decision making and be effective at increasing colorectal cancer screening rates. However, exactly how such an intervention improves shared decision making is unclear. This study, funded by the National Cancer Institute, seeks to provide detailed understanding of how an interactive decision aid that elicits patient’s risks and preferences impacts patient-clinician communication and shared decision making, and ultimately colorectal cancer screening adherence.
This is a two-armed single-blinded randomized controlled trial with the target of 300 patients per arm. The setting is eleven community and three academic primary care practices in Metro Detroit. Patients are men and women aged between 50 and 75 years who are not up to date on colorectal cancer screening. ColoDATES Web (intervention arm), a decision aid that incorporates interactive personal risk assessment and preference clarification tools, is compared to a non-interactive website that matches ColoDATES Web in content but does not contain interactive tools (control arm). Primary outcomes are patient uptake of colorectal cancer screening; patient decision quality (knowledge, preference clarification, intent); clinician’s degree of shared decision making; and patient-clinician concordance in the screening test chosen. Secondary outcome incorporates a Structural Equation Modeling approach to understand the mechanism of the causal pathway and test the validity of the proposed conceptual model based on Theory of Planned Behavior. Clinicians and those performing the analysis are blinded to arms.
The central hypothesis is that ColoDATES Web will improve colorectal cancer screening adherence through improvement in patient behavioral factors, shared decision making between the patient and the clinician, and concordance between the patient’s and clinician’s preferred colorectal cancer screening test. The results of this study will be among the first to examine the effect of a real-time preference assessment exercise on colorectal cancer screening and mediators, and, in doing so, will shed light on the patient-clinician communication and shared decision making ‘black box’ that currently exists between the delivery of decision aids to patients and subsequent patient behavior.
Trial Registration ID NCT01514786
PMCID: PMC3842677  PMID: 24216139
Colorectal neoplasms; Early detection of cancer; Cancer screening; Decision aids; Decision support techniques; Decision making; Shared; Health communication
5.  Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC) 
Implementing shared decision making into routine practice is proving difficult, despite considerable interest from policy-makers, and is far more complex than merely making decision support interventions available to patients. Few have reported successful implementation beyond research studies. MAking Good Decisions In Collaboration (MAGIC) is a multi-faceted implementation program, commissioned by The Health Foundation (UK), to examine how best to put shared decision making into routine practice. In this paper, we investigate healthcare professionals’ perspectives on implementing shared decision making during the MAGIC program, to examine the work required to implement shared decision making and to inform future efforts.
The MAGIC program approached implementation of shared decision making by initiating a range of interventions including: providing workshops; facilitating development of brief decision support tools (Option Grids); initiating a patient activation campaign (‘Ask 3 Questions’); gathering feedback using Decision Quality Measures; providing clinical leads meetings, learning events, and feedback sessions; and obtaining executive board level support. At 9 and 15 months (May and November 2011), two rounds of semi-structured interviews were conducted with healthcare professionals in three secondary care teams to explore views on the impact of these interventions. Interview data were coded by two reviewers using a framework derived from the Normalization Process Theory.
A total of 54 interviews were completed with 31 healthcare professionals. Partial implementation of shared decision making could be explained using the four components of the Normalization Process Theory: ‘coherence,’ ‘cognitive participation,’ ‘collective action,’ and ‘reflexive monitoring.’ Shared decision making was integrated into routine practice when clinical teams shared coherent views of role and purpose (‘coherence’). Shared decision making was facilitated when teams engaged in developing and delivering interventions (‘cognitive participation’), and when those interventions fit with existing skill sets and organizational priorities (‘collective action’) resulting in demonstrable improvements to practice (‘reflexive monitoring’). The implementation process uncovered diverse and conflicting attitudes toward shared decision making; ‘coherence’ was often missing.
The study showed that implementation of shared decision making is more complex than the delivery of patient decision support interventions to patients, a portrayal that often goes unquestioned. Normalizing shared decision making requires intensive work to ensure teams have a shared understanding of the purpose of involving patients in decisions, and undergo the attitudinal shifts that many health professionals feel are required when comprehension goes beyond initial interpretations. Divergent views on the value of engaging patients in decisions remain a significant barrier to implementation.
PMCID: PMC3848565  PMID: 24006959
Shared decision making; Implementation; Patient-centered care; Normalization Process Theory
6.  Why do clinicians not refer patients to online decision support tools? Interviews with front line clinics in the NHS 
BMJ Open  2012;2(6):e001530.
To assess whether clinical teams would direct patients to use web-based patient decision support interventions (DESIs) and whether patients would use them.
Retrospective semistructured interviews and web server log analysis.
Participants and settings
57 NHS professionals (nurses, doctors and others) in orthopaedic, antenatal, breast, urology clinics and in primary care practices across 22 NHS sites given access to DESIs hosted on the NHS Direct website.
Fewer than expected patients were directed to use the web tools. The most significant obstacles to referral to the tools were the attitudes of clinicians and clinical teams. Technical problems contributed to the problems but the low uptake was mainly explained by clinicians’ limited understanding of how patient DESIs could be helpful in clinical pathways, their perception that ‘shared decision-making’ was already commonplace and that, in their view, some patients are resistant to being involved in treatment decisions. External factors, such as efficiency targets and ‘best practice’ recommendations were also cited being significant barriers. Clinicians did not feel the need to refer patients to use decision support tools, web-based or not, and, as a result, felt no requirement to change existing practice routines. Uptake is highest when clinicians set expectations that these tools are integral to practice and embed their use into clinical pathways.
Existing evidence of patient benefit and the free availability of patient DESIs via the web are not sufficient drivers to achieve routine use. Health professionals were not motivated to refer patients to these interventions. Clinicians will not use these interventions simply because they are made available, despite good evidence of benefit to patients. These attitudes are deep seated and will not be modified by solely developing web-based interventions: a broader strategy will be required to embed DESIs into routine practice.
PMCID: PMC3532981  PMID: 23204075
Qualitative Research; Health Service Research; Shared Decision Making; Decision Support Interventions; Patient Decision Aids
7.  Development and pilot testing of an online case-based approach to shared decision making skills training for clinicians 
Although research suggests that patients prefer a shared decision making (SDM) experience when making healthcare decisions, clinicians do not routinely implement SDM into their practice and training programs are needed. Using a novel case-based strategy, we developed and pilot tested an online educational program to promote shared decision making (SDM) by primary care clinicians.
A three-phased approach was used: 1) development of a conceptual model of the SDM process; 2) development of an online teaching case utilizing the Design A Case (DAC) authoring template, a well-tested process used to create peer-reviewed web-based clinical cases across all levels of healthcare training; and 3) pilot testing of the case. Participants were clinician members affiliated with several primary care research networks across the United States who answered an invitation email. The case used prostate cancer screening as the clinical context and was delivered online. Post-intervention ratings of clinicians’ general knowledge of SDM, knowledge of specific SDM steps, confidence in and intention to perform SDM steps were also collected online.
Seventy-nine clinicians initially volunteered to participate in the study, of which 49 completed the case and provided evaluations. Forty-three clinicians (87.8%) reported the case met all the learning objectives, and 47 (95.9%) indicated the case was relevant for other equipoise decisions. Thirty-one clinicians (63.3%) accessed supplementary information via links provided in the case. After viewing the case, knowledge of SDM was high (over 90% correctly identified the steps in a SDM process). Determining a patient’s preferred role in making the decision (62.5% very confident) and exploring a patient’s values (65.3% very confident) about the decisions were areas where clinician confidence was lowest. More than 70% of the clinicians intended to perform SDM in the future.
A comprehensive model of the SDM process was used to design a case-based approach to teaching SDM skills to primary care clinicians. The case was favorably rated in this pilot study. Clinician skills training for helping patients clarify their values and for assessing patients’ desire for involvement in decision making remain significant challenges and should be a focus of future comparative studies.
Electronic supplementary material
The online version of this article (doi:10.1186/1472-6947-14-95) contains supplementary material, which is available to authorized users.
PMCID: PMC4283132  PMID: 25361614
Decision making; Medical education; Primary health care
8.  Interactions between Non-Physician Clinicians and Industry: A Systematic Review 
PLoS Medicine  2013;10(11):e1001561.
In a systematic review of studies of interactions between non-physician clinicians and industry, Quinn Grundy and colleagues found that many of the issues identified for physicians' industry interactions exist for non-physician clinicians.
Please see later in the article for the Editors' Summary
With increasing restrictions placed on physician–industry interactions, industry marketing may target other health professionals. Recent health policy developments confer even greater importance on the decision making of non-physician clinicians. The purpose of this systematic review is to examine the types and implications of non-physician clinician–industry interactions in clinical practice.
Methods and Findings
We searched MEDLINE and Web of Science from January 1, 1946, through June 24, 2013, according to PRISMA guidelines. Non-physician clinicians eligible for inclusion were: Registered Nurses, nurse prescribers, Physician Assistants, pharmacists, dieticians, and physical or occupational therapists; trainee samples were excluded. Fifteen studies met inclusion criteria. Data were synthesized qualitatively into eight outcome domains: nature and frequency of industry interactions; attitudes toward industry; perceived ethical acceptability of interactions; perceived marketing influence; perceived reliability of industry information; preparation for industry interactions; reactions to industry relations policy; and management of industry interactions. Non-physician clinicians reported interacting with the pharmaceutical and infant formula industries. Clinicians across disciplines met with pharmaceutical representatives regularly and relied on them for practice information. Clinicians frequently received industry “information,” attended sponsored “education,” and acted as distributors for similar materials targeted at patients. Clinicians generally regarded this as an ethical use of industry resources, and felt they could detect “promotion” while benefiting from industry “information.” Free samples were among the most approved and common ways that clinicians interacted with industry. Included studies were observational and of varying methodological rigor; thus, these findings may not be generalizable. This review is, however, the first to our knowledge to provide a descriptive analysis of this literature.
Non-physician clinicians' generally positive attitudes toward industry interactions, despite their recognition of issues related to bias, suggest that industry interactions are normalized in clinical practice across non-physician disciplines. Industry relations policy should address all disciplines and be implemented consistently in order to mitigate conflicts of interest and address such interactions' potential to affect patient care.
Please see later in the article for the Editors' Summary
Editors' Summary
Making and selling health care goods (including drugs and devices) and services is big business. To maximize the profits they make for their shareholders, companies involved in health care build relationships with physicians by providing information on new drugs, organizing educational meetings, providing samples of their products, giving gifts, and holding sponsored events. These relationships help to keep physicians informed about new developments in health care but also create the potential for causing harm to patients and health care systems. These relationships may, for example, result in increased prescription rates of new, heavily marketed medications, which are often more expensive than their generic counterparts (similar unbranded drugs) and that are more likely to be recalled for safety reasons than long-established drugs. They may also affect the provision of health care services. Industry is providing an increasingly large proportion of routine health care services in many countries, so relationships built up with physicians have the potential to influence the commissioning of the services that are central to the treatment and well-being of patients.
Why Was This Study Done?
As a result of concerns about the tension between industry's need to make profits and the ethics underlying professional practice, restrictions are increasingly being placed on physician–industry interactions. In the US, for example, the Physician Payments Sunshine Act now requires US manufacturers of drugs, devices, and medical supplies that participate in federal health care programs to disclose all payments and gifts made to physicians and teaching hospitals. However, other health professionals, including those with authority to prescribe drugs such as pharmacists, Physician Assistants, and nurse practitioners are not covered by this legislation or by similar legislation in other settings, even though the restructuring of health care to prioritize primary care and multidisciplinary care models means that “non-physician clinicians” are becoming more numerous and more involved in decision-making and medication management. In this systematic review (a study that uses predefined criteria to identify all the research on a given topic), the researchers examine the nature and implications of the interactions between non-physician clinicians and industry.
What Did the Researchers Do and Find?
The researchers identified 15 published studies that examined interactions between non-physician clinicians (Registered Nurses, nurse prescribers, midwives, pharmacists, Physician Assistants, and dieticians) and industry (corporations that produce health care goods and services). They extracted the data from 16 publications (representing 15 different studies) and synthesized them qualitatively (combined the data and reached word-based, rather than numerical, conclusions) into eight outcome domains, including the nature and frequency of interactions, non-physician clinicians' attitudes toward industry, and the perceived ethical acceptability of interactions. In the research the authors identified, non-physician clinicians reported frequent interactions with the pharmaceutical and infant formula industries. Most non-physician clinicians met industry representatives regularly, received gifts and samples, and attended educational events or received educational materials (some of which they distributed to patients). In these studies, non-physician clinicians generally regarded these interactions positively and felt they were an ethical and appropriate use of industry resources. Only a minority of non-physician clinicians felt that marketing influenced their own practice, although a larger percentage felt that their colleagues would be influenced. A sizeable proportion of non-physician clinicians questioned the reliability of industry information, but most were confident that they could detect biased information and therefore rated this information as reliable, valuable, or useful.
What Do These Findings Mean?
These and other findings suggest that non-physician clinicians generally have positive attitudes toward industry interactions but recognize issues related to bias and conflict of interest. Because these findings are based on a small number of studies, most of which were undertaken in the US, they may not be generalizable to other countries. Moreover, they provide no quantitative assessment of the interaction between non-physician clinicians and industry and no information about whether industry interactions affect patient care outcomes. Nevertheless, these findings suggest that industry interactions are normalized (seen as standard) in clinical practice across non-physician disciplines. This normalization creates the potential for serious risks to patients and health care systems. The researchers suggest that it may be unrealistic to expect that non-physician clinicians can be taught individually how to interact with industry ethically or how to detect and avert bias, particularly given the ubiquitous nature of marketing and promotional materials. Instead, they suggest, the environment in which non-physician clinicians practice should be structured to mitigate the potentially harmful effects of interactions with industry.
Additional Information
Please access these websites via the online version of this summary at
This study is further discussed in a PLOS Medicine Perspective by James S. Yeh and Aaron S. Kesselheim
The American Medical Association provides guidance for physicians on interactions with pharmaceutical industry representatives, information about the Physician Payments Sunshine Act, and a toolkit for preparing Physician Payments Sunshine Act reports
The International Council of Nurses provides some guidance on industry interactions in its position statement on nurse-industry relations
The UK General Medical Council provides guidance on financial and commercial arrangements and conflicts of interest as part of its good medical practice website, which describes what is required of all registered doctors in the UK
Understanding and Responding to Pharmaceutical Promotion: A Practical Guide is a manual prepared by Health Action International and the World Health Organization that schools of medicine and pharmacy can use to train students how to recognize and respond to pharmaceutical promotion.
The Institute of Medicine's Report on Conflict of Interest in Medical Research, Education, and Practice recommends steps to identify, limit, and manage conflicts of interest
The University of California, San Francisco, Office of Continuing Medical Education offers a course called Marketing of Medicines
PMCID: PMC3841103  PMID: 24302892
9.  Understanding treatment decision making in juvenile idiopathic arthritis: a qualitative assessment 
The increase in therapeutic options for juvenile idiopathic arthritis (JIA) has added complexity to treatment decisions. Shared decision making has the potential to help providers and families work together to choose the best possible option for each patient from the array of choices. As part of a needs assessment, prior to design and implementation of shared decision making interventions, we conducted a qualitative assessment of clinicians’ current approaches to treatment decision making in JIA.
Pediatric rheumatology clinicians were recruited from 2 academic children’s hospitals affiliated with a quality improvement learning network, using purposive and snowball sampling. Semi-structured interviews elicited how clinicians with prescribing authority (n = 10) interact with families to make treatment decisions. Interviews were audio-recorded and transcribed verbatim. A multi-disciplinary research team used content analysis to analyze the interview data.
To validate data from individual interviews and enrich our understanding, we presented the interview results to pediatric rheumatology clinicians attending a learning network meeting (n = 24 from 12 children’s hospitals). We then asked the clinicians questions to further identify and discuss areas of variation in the decision-making processes.
Clinicians described a decision-making process in which they, rather than the family or other care team members, consistently initiated treatment decisions. Initial treatment options presented to families generally reflected the clinician’s preferred treatment approaches, which differed across clinicians. Clinicians used various methods to inform families about treatment options and tailor information according to perceptions of a family’s information needs, level of comprehension or mood (e.g. anxiety). The attributes of medication presented to families fell into 4 categories: benefits, risks, logistics and family preferences. Clinicians typically included family members in the decision to initiate JIA treatment after limiting the options to fit the clinical situation and the clinician’s own preferences. Family members’ preferences were seen as more integral in the decision to stop treatment after symptom remission.
Decision making about initial JIA treatment appears to be largely driven by clinician preferences. Family preferences are more likely to be considered for treatment discontinuation. Opportunities exist to develop, test, and implement tools to facilitate shared decision making in pediatric rheumatology.
PMCID: PMC3849714  PMID: 24079577
Juvenile idiopathic arthritis; Decision making; Biologics
10.  Identifying design considerations for a shared decision aid for use at the point of outpatient clinical care: An ethnographic study at an inner city clinic 
Background and Objective
Computerized decision aids could facilitate shared decision-making at the point of outpatient clinical care. The objective of this study was to investigate whether a computerized shared decision aid would be feasible to implement in an inner-city clinic by evaluating the current practices in shared decision-making, clinicians’ use of computers, patient and clinicians’ attitudes and beliefs toward computerized decision aids, and the influence of time on shared decision-making.
Qualitative data analysis of observations and semi-structured interviews with patients and clinicians at an inner-city outpatient clinic.
The findings provided an exploratory look at the prevalence of shared decision-making and attitudes about health information technology and decision aids. A prominent barrier to clinicians engaging in shared decision-making was a lack of perceived patient understanding of medical information. Some patients preferred their clinicians make recommendations for them rather than engage in formal shared decision-making. Health information technology was an integral part of the clinic visit and welcomed by most clinicians and patients. Some patients expressed the desire to engage with health information technology such as viewing their medical information on the computer screen with their clinicians. All participants were receptive to the idea of a decision aid integrated within the clinic visit although some clinicians were concerned about the accuracy of prognostic estimates for complex medical problems.
We identified several important considerations for the design and implementation of a computerized decision aid including opportunities to: bridge clinician-patient communication about medical information while taking into account individual patients’ decision-making preferences, complement expert clinician judgment with prognostic estimates, take advantage of patient waiting times, and make tasks involved during the clinic visit more efficient. These findings should be incorporated into the design and implementation of a computerized shared decision aid at an inner-city hospital.
PMCID: PMC3991432  PMID: 24748995
Computerized decision aids; shared decision-making; health information technology; patient attitudes
11.  A Web-Based Tool to Support Shared Decision Making for People With a Psychotic Disorder: Randomized Controlled Trial and Process Evaluation 
Mental health policy makers encourage the development of electronic decision aids to increase patient participation in medical decision making. Evidence is needed to determine whether these decision aids are helpful in clinical practice and whether they lead to increased patient involvement and better outcomes.
This study reports the outcome of a randomized controlled trial and process evaluation of a Web-based intervention to facilitate shared decision making for people with psychotic disorders.
The study was carried out in a Dutch mental health institution. Patients were recruited from 2 outpatient teams for patients with psychosis (N=250). Patients in the intervention condition (n=124) were provided an account to access a Web-based information and decision tool aimed to support patients in acquiring an overview of their needs and appropriate treatment options provided by their mental health care organization. Patients were given the opportunity to use the Web-based tool either on their own (at their home computer or at a computer of the service) or with the support of an assistant. Patients in the control group received care as usual (n=126). Half of the patients in the sample were patients experiencing a first episode of psychosis; the other half were patients with a chronic psychosis. Primary outcome was patient-perceived involvement in medical decision making, measured with the Combined Outcome Measure for Risk Communication and Treatment Decision-making Effectiveness (COMRADE). Process evaluation consisted of questionnaire-based surveys, open interviews, and researcher observation.
In all, 73 patients completed the follow-up measurement and were included in the final analysis (response rate 29.2%). More than one-third (48/124, 38.7%) of the patients who were provided access to the Web-based decision aid used it, and most used its full functionality. No differences were found between the intervention and control conditions on perceived involvement in medical decision making (COMRADE satisfaction with communication: F1,68=0.422, P=.52; COMRADE confidence in decision: F1,67=0.086, P=.77). In addition, results of the process evaluation suggest that the intervention did not optimally fit in with routine practice of the participating teams.
The development of electronic decision aids to facilitate shared medical decision making is encouraged and many people with a psychotic disorder can work with them. This holds for both first-episode patients and long-term care patients, although the latter group might need more assistance. However, results of this paper could not support the assumption that the use of electronic decision aids increases patient involvement in medical decision making. This may be because of weak implementation of the study protocol and a low response rate.
Trial Registration
Dutch Trial Register (NTR) trial number: 10340; (Archived by WebCite at
PMCID: PMC3806550  PMID: 24100091
psychotic disorders, schizophrenia; computers; computer-assisted decision making; shared decision making; feasibility studies, randomized clinical trial
12.  Option Grids to facilitate shared decision making for patients with Osteoarthritis of the knee: protocol for a single site, efficacy trial 
Despite policy interest, an ethical imperative, and evidence of the benefits of patient decision support tools, the adoption of shared decision making (SDM) in day-to-day clinical practice remains slow and is inhibited by barriers that include culture and attitudes; resources and time pressures. Patient decision support tools often require high levels of health and computer literacy. Option Grids are one-page evidence-based summaries of the available condition-specific treatment options, listing patients’ frequently asked questions. They are designed to be sufficiently brief and accessible enough to support a better dialogue between patients and clinicians during routine consultations. This paper describes a study to assess whether an Option Grid for osteoarthritis of the knee (OA of the knee) facilitates SDM, and explores the use of Option Grids by patients disadvantaged by language or poor health literacy.
This will be a stepped wedge exploratory trial involving 72 patients with OA of the knee referred from primary medical care to a specialist musculoskeletal service in Oldham. Six physiotherapists will sequentially join the trial and consult with six patients using usual care procedures. After a period of brief training in using the Option Grid, the same six physiotherapists will consult with six further patients using an Option Grid in the consultation. The primary outcome will be efficacy of the Option Grid in facilitating SDM as measured by observational scores using the OPTION scale. Comparisons will be made between patients who have received the Option Grid and those who received usual care. A Decision Quality Measure (DQM) will assess quality of decision making. The health literacy of patients will be measured using the REALM-R instrument. Consultations will be observed and audio-recorded. Interviews will be conducted with the physiotherapists, patients and any interpreters present to explore their views of using the Option Grid.
Option Grids offer a potential solution to the barriers to implementing traditional decision aids into routine clinical practice. The study will assess whether Option Grids can facilitate SDM in day-to-day clinical practice and explore their use with patients disadvantaged by language or poor health literacy.
Trial registration
Current Controlled Trials ISRCTN94871417
PMCID: PMC3986464  PMID: 24708747
Shared decision making; Decision aids; Osteoarthritis of the knee; Arthritis; Health literacy; Patient communication
13.  ‘They leave at least believing they had a part in the discussion’: Understanding decision aid use and patient–clinician decision-making through qualitative research 
This study explores how patient decision aids (DAs) for antihyperglycemic agents and statins, designed for use during clinical consultations, are embedded into practice, examining how patients and clinicians understand and experience DAs in primary care visits.
We conducted semistructured in-depth interviews with patients (n = 22) and primary care clinicians (n = 19), and videorecorded consultations (n = 44). Two researchers coded all transcripts. Inductive analyses guided by grounded theory led to the identification of themes. Video and interview data were compared and organized by themes.
DAs used during consultations became flexible artifacts, incorporated into existing decision making roles for clinicians (experts, authority figures, persuaders, advisors) and patients (drivers of healthcare, learners, partners). DAs were applied to different decision making steps (deliberation, bargaining, convincing, case assessment), and introduced into an existing knowledge context (participants’ literacy regarding shared decision-making (SDM) and DAs).
DAs’ flexible use during consultations effectively provided space for discussion, even when SDM was not achieved. DAs can be used within any decision-making model.
Practice implications
Clinician training in DA use and SDM practice may be needed to facilitate DA implementation and promote more ideal-type forms of sharing in decision making.
PMCID: PMC3759553  PMID: 23598292
Shared decision making; Decision aids; Provider–patient communication
14.  Shared decision making and the concept of equipoise: the competences of involving patients in healthcare choices. 
BACKGROUND: Involving patients in healthcare decisions makes a potentially significant and enduring difference to healthcare outcomes. One difficulty (among many) is that the 'involvement' of patients in decisions has been left undefined. It is usually conceptualised as 'patient centredness', which is a broad and variably interpreted concept that is difficult to assess using current tools. This paper attempts to gauge general practitioners' (GPs') attitudes to patient involvement in decision making and their views about the contextual factors, competences, and stages required to achieve shared decisions within consultations. AIM: To explore and understand what constitutes the appropriate involvement of patients in decision making within consultations, to consider previous theory in this field, and to propose a set of competences (skills) and steps that would enable clinical practitioners (generalists) to undertake 'shared decision making' in their clinical environment. METHOD: Qualitative study using focus group interviews of key informants. RESULTS: Experienced GPs with educational roles have positive attitudes to the involvement of patients in decisions, provided the process matches the role individuals wish to play. They perceive some clinical problems as being more suited to a cooperative approach to decision making and conceptualised the existence of professional equipoise towards the existence of legitimate treatment options as an important facilitative factor. A sequence of skills was proposed as follows: 1) implicit or explicit involvement of patients in the decision-making process; 2) explore ideas, fears, and expectations of the problem and possible treatments; 3) portrayal of equipoise and options; 4) identify preferred data format and provide tailor-made information; 5) checking process: understanding of information and reactions (e.g. ideas, fears, and expectations of possible options); 6) acceptance of process and decision making role preference; 7) make, discuss or defer decisions; 8) arrange follow-up. CONCLUSIONS: These clinicians viewed involvement as an implicit ethos that should permeate medical practice, provided that clinicians respect and remain alert to patients' individual preferred roles in decision making. The interpersonal skills and the information requirements needed to successfully share decisions are major challenges to the clinical consultation process in medical practice. The benefits of patient involvement and the skills required to achieve this approach need to be given much higher priority at all levels: at policy, education, and within further professional development strategies.
PMCID: PMC1313854  PMID: 11141876
15.  The Impact of eHealth on the Quality and Safety of Health Care: A Systematic Overview 
PLoS Medicine  2011;8(1):e1000387.
Aziz Sheikh and colleagues report the findings of their systematic overview that assessed the impact of eHealth solutions on the quality and safety of health care.
There is considerable international interest in exploiting the potential of digital solutions to enhance the quality and safety of health care. Implementations of transformative eHealth technologies are underway globally, often at very considerable cost. In order to assess the impact of eHealth solutions on the quality and safety of health care, and to inform policy decisions on eHealth deployments, we undertook a systematic review of systematic reviews assessing the effectiveness and consequences of various eHealth technologies on the quality and safety of care.
Methods and Findings
We developed novel search strategies, conceptual maps of health care quality, safety, and eHealth interventions, and then systematically identified, scrutinised, and synthesised the systematic review literature. Major biomedical databases were searched to identify systematic reviews published between 1997 and 2010. Related theoretical, methodological, and technical material was also reviewed. We identified 53 systematic reviews that focused on assessing the impact of eHealth interventions on the quality and/or safety of health care and 55 supplementary systematic reviews providing relevant supportive information. This systematic review literature was found to be generally of substandard quality with regards to methodology, reporting, and utility. We thematically categorised eHealth technologies into three main areas: (1) storing, managing, and transmission of data; (2) clinical decision support; and (3) facilitating care from a distance. We found that despite support from policymakers, there was relatively little empirical evidence to substantiate many of the claims made in relation to these technologies. Whether the success of those relatively few solutions identified to improve quality and safety would continue if these were deployed beyond the contexts in which they were originally developed, has yet to be established. Importantly, best practice guidelines in effective development and deployment strategies are lacking.
There is a large gap between the postulated and empirically demonstrated benefits of eHealth technologies. In addition, there is a lack of robust research on the risks of implementing these technologies and their cost-effectiveness has yet to be demonstrated, despite being frequently promoted by policymakers and “techno-enthusiasts” as if this was a given. In the light of the paucity of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, it is vital that future eHealth technologies are evaluated against a comprehensive set of measures, ideally throughout all stages of the technology's life cycle. Such evaluation should be characterised by careful attention to socio-technical factors to maximise the likelihood of successful implementation and adoption.
Please see later in the article for the Editors' Summary
Editors' Summary
There is considerable international interest in exploiting the potential of digital health care solutions, often referred to as eHealth—the use of information and communication technologies—to enhance the quality and safety of health care. Often accompanied by large costs, any large-scale expenditure on eHealth—such as electronic health records, picture archiving and communication systems, ePrescribing, associated computerized provider order entry systems, and computerized decision support systems—has tended to be justified on the grounds that these are efficient and cost-effective means for improving health care. In 2005, the World Health Assembly passed an eHealth resolution (WHA 58.28) that acknowledged, “eHealth is the cost-effective and secure use of information and communications technologies in support of health and health-related fields, including health-care services, health surveillance, health literature, and health education, knowledge and research,” and urged member states to develop and implement eHealth technologies. Since then, implementing eHealth technologies has become a main priority for many countries. For example, England has invested at least £12.8 billion in a National Programme for Information Technology for the National Health Service, and the Obama administration in the United States has committed to a US$38 billion eHealth investment in health care.
Why Was This Study Done?
Despite the wide endorsement of and support for eHealth, the scientific basis of its benefits—which are repeatedly made and often uncritically accepted—remains to be firmly established. A robust evidence-based perspective on the advantages on eHealth could help to suggest priority areas that have the greatest potential for benefit to patients and also to inform international eHealth deliberations on costs. Therefore, in order to better inform the international community, the authors systematically reviewed the published systematic review literature on eHealth technologies and evaluated the impact of these technologies on the quality and safety of health care delivery.
What Did the Researchers Do and Find?
The researchers divided eHealth technologies into three main categories: (1) storing, managing, and transmission of data; (2) clinical decision support; and (3) facilitating care from a distance. Then, implementing methods based on those developed by the Cochrane Collaboration and the NHS Service Delivery and Organisation Programme, the researchers used detailed search strategies and maps of health care quality, safety, and eHealth interventions to identify relevant systematic reviews (and related theoretical, methodological, and technical material) published between 1997 and 2010. Using these techniques, the researchers retrieved a total of 46,349 references from which they identified 108 reviews. The 53 reviews that the researchers finally selected (and critically reviewed) provided the main evidence base for assessing the impact of eHealth technologies in the three categories selected.
In their systematic review of systematic reviews, the researchers included electronic health records and picture archiving communications systems in their evaluation of category 1, computerized provider (or physician) order entry and e-prescribing in category 2, and all clinical information systems that, when used in the context of eHealth technologies, integrate clinical and demographic patient information to support clinician decision making in category 3.
The researchers found that many of the clinical claims made about the most commonly used eHealth technologies were not substantiated by empirical evidence. The evidence base in support of eHealth technologies was weak and inconsistent and importantly, there was insubstantial evidence to support the cost-effectiveness of these technologies. For example, the researchers only found limited evidence that some of the many presumed benefits could be realized; importantly, they also found some evidence that introducing these new technologies may on occasions also generate new risks such as prescribers becoming over-reliant on clinical decision support for e-prescribing, or overestimate its functionality, resulting in decreased practitioner performance.
What Do These Findings Mean?
The researchers found that despite the wide support for eHealth technologies and the frequently made claims by policy makers when constructing business cases to raise funds for large-scale eHealth projects, there is as yet relatively little empirical evidence to substantiate many of the claims made about eHealth technologies. In addition, even for the eHealth technology tools that have proven to be successful, there is little evidence to show that such tools would continue to be successful beyond the contexts in which they were originally developed. Therefore, in light of the lack of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, the authors say that future eHealth technologies should be evaluated against a comprehensive set of measures, ideally throughout all stages of the technology's life cycle, and include socio-technical factors to maximize the likelihood of successful implementation and adoption in a given context. Furthermore, it is equally important that eHealth projects that have already been commissioned are subject to rigorous, multidisciplinary, and independent evaluation.
Additional Information
Please access these websites via the online version of this summary at
The authors' broader study is: Car J, Black A, Anandan C, Cresswell K, Pagliari C, McKinstry B, et al. (2008) The Impact of eHealth on the Quality and Safety of Healthcare. Available at:
More information is available on the World Health Assembly eHealth resolution
The World Health Organization provides information at the Global Observatory on eHealth, as well as a global insight into eHealth developments
The European Commission provides Information on eHealth in Europe and some examples of good eHealth practice
More information is provided on NHS Connecting for Health
PMCID: PMC3022523  PMID: 21267058
16.  Shared Decision Making in Oncology Practice: What Do Oncologists Need to Know? 
The Oncologist  2012;17(1):91-100.
A perspective on how to incorporate shared decision making into routine oncology practice to facilitate patient-centered communication and promote effective treatment decisions is presented.
Learning Objectives
After completing this course, the reader will be able to: Outline the five steps that comprise shared decision making.Identify specific tactics that can be used to engage a patient in a shared decision making process.
This article is available for continuing medical education credit at
There is growing interest by patients, policy makers, and clinicians in shared decision making (SDM) as a means to involve patients in health decisions and translate evidence into clinical practice. However, few clinicians feel optimally trained to implement SDM in practice, and many patients report that they are less involved than they desire to be in their cancer care decisions. SDM might help address the wide practice variation reported for many preference-sensitive decisions by incorporating patient preferences into decision discussions.
This paper provides a perspective on how to incorporate SDM into routine oncology practice to facilitate patient-centered communication and promote effective treatment decisions. Oncology practice is uniquely positioned to lead the adoption of SDM because of the vast number of preference-sensitive decisions in which SDM can enhance the clinical encounter.
Clinicians can facilitate cancer decision making by: (a) determining the situations in which SDM is critical; (b) acknowledging the decision to a patient; (c) describing the available options, including the risks, benefits, and uncertainty associated with options; (d) eliciting patients' preferences; and (e) agreeing on a plan for the next steps in the decision-making process.
Given recent policy movements toward incorporating SDM and translating evidence into routine clinical practice, oncologists are likely to continue expanding their use of SDM and will have to confront the challenges of incorporating SDM into their clinical workflow. More research is needed to explore ways to overcome these challenges such that both quality evidence and patient preferences are appropriately translated and incorporated into oncology care decisions.
PMCID: PMC3267829  PMID: 22234632
Decision making; Decision support; Health communication
17.  Perceptions of Shared Decision Making and Decision Aids Among Rural Primary Care Clinicians 
Shared Decision Making (SDM) and Decision Aids (DAs) increase patients’ involvement in healthcare decisions and enhance satisfaction with their choices. Studies of SDM and DAs have primarily occurred in academic centers and large health systems, but most primary care is delivered in smaller practices and over 20% of Americans live in rural areas where poverty, disease prevalence and limited access to care may increase the need for SDM and DAs.
To explore perceptions and practices of rural primary care clinicians regarding SDM and DAs.
Cross sectional survey.
Setting and Participants
Primary care clinicians affiliated with the Oregon Rural Practice-based Research Network (ORPRN).
Surveys were returned by 181 of 231 eligible participants (78%), 174 could be analyzed. Two-thirds of participants were physicians, 84% practiced family medicine, and 55% were male. Sixty five percent of respondents were unfamiliar with the term “SDM”, but following definition, 97% reported they found the approach useful for conditions with multiple treatment options. Over 90% of clinicians perceived helping patients make decisions regarding chronic pain and health behavior change as moderate/hard in difficulty. Although 69% of respondents preferred that patients play an equal role in making decisions, they estimate this happens only 35% of the time. Time was reported as the largest barrier to engaging in SDM (63%). Respondents were receptive to using DAs to facilitate SDM in printed (95%) or web-based formats (72%) and topic preference varied by clinician specialty and decision difficulty.
Rural clinicians recognized the value of SDM and were receptive to using DAs in multiple formats. Integration of DAs to facilitate SDM in routine patient care may require addressing practice operation and reimbursement.
PMCID: PMC3665512  PMID: 22247423
Primary Care; Translating Research Into Practice; Shared Decision Making – Decision Aid Tools; Decision Aids – Decision Aid Tools; Survey Methods – Statistical Methods
18.  The impact of decision aids to enhance shared decision making for diabetes (the DAD study): protocol of a cluster randomized trial 
Shared decision making contributes to high quality healthcare by promoting a patient-centered approach. Patient involvement in selecting the components of a diabetes medication program that best match the patient’s values and preferences may also enhance medication adherence and improve outcomes. Decision aids are tools designed to involve patients in shared decision making, but their adoption in practice has been limited. In this study, we propose to obtain a preliminary estimate of the impact of patient decision aids vs. usual care on measures of patient involvement in decision making, diabetes care processes, medication adherence, glycemic and cardiovascular risk factor control, and resource utilization. In addition, we propose to identify, describe, and explain factors that promote or inhibit the routine embedding of decision aids in practice.
We will be conducting a mixed-methods study comprised of a cluster-randomized, practical, multicentered trial enrolling clinicians and their patients (n = 240) with type 2 diabetes from rural and suburban primary care practices (n = 8), with an embedded qualitative study to examine factors that influence the incorporation of decision aids into routine practice. The intervention will consist of the use of a decision aid (Statin Choice and Aspirin Choice, or Diabetes Medication Choice) during the clinical encounter. The qualitative study will include analysis of video recordings of clinical encounters and in-depth, semi-structured interviews with participating patients, clinicians, and clinic support staff, in both trial arms.
Upon completion of this trial, we will have new knowledge about the effectiveness of diabetes decision aids in these practices. We will also better understand the factors that promote or inhibit the successful implementation and normalization of medication choice decision aids in the care of chronic patients in primary care practices.
Trial registration
PMCID: PMC3468357  PMID: 22640439
Diabetes; Shared decision making; Cardiovascular prevention; Implementation
19.  Practice based, longitudinal, qualitative interview study of computerised evidence based guidelines in primary care 
BMJ : British Medical Journal  2003;326(7384):314.
To understand the factors influencing the adoption of a computerised clinical decision support system for two chronic diseases in general practice.
Practice based, longitudinal, qualitative interview study.
Five general practices in north east England.
13 respondents (two practice managers, three nurses, and eight general practitioners) gave a total of 19 semistructured interviews. 40 people in practices included in the randomised controlled trial (34 doctors, three nurses) and interview study (three doctors, one previously interviewed) gave feedback.
Negative comments about the decision support system significantly outweighed the positive or neutral comments. Three main areas of concern among clinicians emerged: timing of the guideline trigger, ease of use of the system, and helpfulness of the content. Respondents did not feel that the system fitted well within the general practice context. Experience of “on-demand” information sources, which were generally more positively viewed, informed the comments about the system. Some general practitioners suggested that nurses might find the guideline content more clinically useful and might be more prepared to use a computerised decision support system, but lack of feedback from nurses who had experienced the system limited the ability to assess this.
Significant barriers exist to the use of complex clinical decision support systems for chronic disease by general practitioners. Key issues include the relevance and accuracy of messages and the flexibility to respond to other factors influencing decision making in primary care.
What is already known on this topicRandomised controlled trials of complex computerised decision support systems have found low rates of use and no effects on process and outcomes of careWhat this study addsClinicians found a computerised decision support system for chronic disease in general practice to be difficult to use and unhelpful clinicallyIt did not fit well into a general practice consultation and compared unfavourably with “on-demand” information“Active” decision support can make clinicians aware of gaps between their own practice and “best” practice, but computer prompts need to be relevant and accurate
PMCID: PMC143528  PMID: 12574046
20.  An integrated strategy of knowledge application for optimal e-health implementation: A multi-method study protocol 
E-health is increasingly valued for supporting: 1) access to quality health care services for all citizens; 2) information flow and exchange; 3) integrated health care services and 4) interprofessional collaboration. Nevertheless, several questions remain on the factors allowing an optimal integration of e-health in health care policies, organisations and practices. An evidence-based integrated strategy would maximise the efficacy and efficiency of e-health implementation. However, decisions regarding e-health applications are usually not evidence-based, which can lead to a sub-optimal use of these technologies. This study aims at understanding factors influencing the application of scientific knowledge for an optimal implementation of e-health in the health care system.
A three-year multi-method study is being conducted in the Province of Quebec (Canada). Decision-making at each decisional level (political, organisational and clinical) are analysed based on specific approaches. At the political level, critical incidents analysis is being used. This method will identify how decisions regarding the implementation of e-health could be influenced or not by scientific knowledge. Then, interviews with key-decision-makers will look at how knowledge was actually used to support their decisions, and what factors influenced its use. At the organisational level, e-health projects are being analysed as case studies in order to explore the use of scientific knowledge to support decision-making during the implementation of the technology. Interviews with promoters, managers and clinicians will be carried out in order to identify factors influencing the production and application of scientific knowledge. At the clinical level, questionnaires are being distributed to clinicians involved in e-health projects in order to analyse factors influencing knowledge application in their decision-making. Finally, a triangulation of the results will be done using mixed methodologies to allow a transversal analysis of the results at each of the decisional levels.
This study will identify factors influencing the use of scientific evidence and other types of knowledge by decision-makers involved in planning, financing, implementing and evaluating e-health projects.
These results will be highly relevant to inform decision-makers who wish to optimise the implementation of e-health in the Quebec health care system. This study is extremely relevant given the context of major transformations in the health care system where e-health becomes a must.
PMCID: PMC2390530  PMID: 18435853
21.  Making decisions about treatment for young people diagnosed with depressive disorders: a qualitative study of clinicians’ experiences 
BMC Psychiatry  2013;13:335.
The imperative to provide effective treatment for young people diagnosed with depressive disorders is complicated by several factors including the unclear effectiveness of treatment options. Within this context, little is known about how treatment decisions are made for this population.
In order to explore the experiences and beliefs of clinicians about treatment decision making for this population, semi-structured, qualitative interviews were conducted with 22 psychiatrists, general practitioners and allied health professionals from health care settings including specialist mental health services and primary health care. Interviews were audio taped, transcribed verbatim and analysed using thematic analysis.
Clinicians largely reported and endorsed a collaborative model of treatment decision making for youth depression, although several exceptions to this approach were also described (e.g. when risk issues were present), highlighting a need to adapt the decision-making style to the characteristics and needs of the client. A differentiation was made between the decision-making processes (e.g. sharing of information) and who makes the decision. Caregiver involvement was seen as optional, especially in situations where no caregivers were involved, but ideal and useful if the caregivers were supportive. Gaps between the type and amount of information clinicians wanted to give their clients and what they actually gave them were reported (e.g. having fact sheets on hand). A broad range of barriers to involving clients and caregivers in decision-making processes were described relating to four levels (client and caregiver, clinician, service and broader levels) and suggestions were given to help overcome these barriers, including up-to-date, accessible and relevant information.
The current data support a collaborative model of treatment decision making for youth depression which: 1) focuses on the decision-making processes rather than who actually makes the decision; 2) is flexible to the individual needs and characteristics of the client; and 3) where caregiver involvement is optional. Shared decision making interventions and the use of decision aids should be considered for this area.
PMCID: PMC4029801  PMID: 24330307
22.  Perceived Barriers and Facilitators of Using a Web-Based Interactive Decision Aid for Colorectal Cancer Screening in Community Practice Settings: Findings From Focus Groups With Primary Care Clinicians and Medical Office Staff 
Information is lacking about the capacity of those working in community practice settings to utilize health information technology for colorectal cancer screening.
To address this gap we asked those working in community practice settings to share their perspectives about how the implementation of a Web-based patient-led decision aid might affect patient-clinician conversations about colorectal cancer screening and the day-to-day clinical workflow.
Five focus groups in five community practice settings were conducted with 8 physicians, 1 physician assistant, and 18 clinic staff. Focus groups were organized using a semistructured discussion guide designed to identify factors that mediate and impede the use of a Web-based decision aid intended to clarify patient preferences for colorectal cancer screening and to trigger shared decision making during the clinical encounter.
All physicians, the physician assistant, and 8 of the 18 clinic staff were active participants in the focus groups. Clinician and staff participants from each setting reported a belief that the Web-based patient-led decision aid could be an informative and educational tool; in all but one setting participants reported a readiness to recommend the tool to patients. The exception related to clinicians from one clinic who described a preference for patients having fewer screening choices, noting that a colonoscopy was the preferred screening modality for patients in their clinic. Perceived barriers to utilizing the Web-based decision aid included patients’ lack of Internet access or low computer literacy, and potential impediments to the clinics’ daily workflow. Expanding patients’ use of an online decision aid that is both easy to access and understand and that is utilized by patients outside of the office visit was described as a potentially efficient means for soliciting patients’ screening preferences. Participants described that a system to link the online decision aid to a computerized reminder system could promote a better understanding of patients’ screening preferences, though some expressed concern that such a system could be difficult to keep up and running.
Community practice clinicians and staff perceived the Web-based decision aid technology as promising but raised questions as to how the technology and resultant information would be integrated into their daily practice workflow. Additional research investigating how to best implement online decision aids should be conducted prior to the widespread adoption of such technology so as to maximize the benefits of the technology while minimizing workflow disruptions.
PMCID: PMC3875904  PMID: 24351420
colon cancer; colonoscopy; cancer screening; early detection of cancer; reminder systems; decision support techniques; focus groups; health information technology
23.  Efficacy of a training intervention on the quality of practitioners' decision support for patients deciding about place of care at the end of life: A randomized control trial: Study protocol 
Most people prefer home palliation but die in an institution. Some experience decisional conflict when weighing options regarding place of care. Clinicians can identify patients' decisional needs and provide decision support, yet generally lack skills and confidence in doing so. This study aims to determine whether the quality of clinicians' decision support can be improved with a brief, theory-based, skills-building intervention.
The Ottawa Decision Support Framework (ODSF) guides an evidence based, practical approach to assist clinicians in providing high-quality decision support. The ODSF proposes that decisional needs [personal uncertainty, knowledge, values clarity, support, personal characteristics] strongly influence the quality of decisions patients make. Clinicians can improve decision quality by providing decision support to address decisional needs [clarify decisional needs, provide facts and probabilities, clarify values, support/guide deliberation, monitor/facilitate progress].
The efficacy of a brief education intervention will be assessed in a two-phase study. In phase one a focused needs assessment will be conducted with key informants. Phase two is a randomized control trial where clinicians will be randomly allocated to an intervention or control group. The intervention, informed by the needs assessment, knowledge transfer best practices and the ODSF, comprises an online tutorial; an interactive skills building workshop; a decision support protocol; performance feedback, and educational outreach. Participants will be assessed: a) at baseline (quality of decision support); b) after the tutorial (knowledge); and c) four weeks after the other interventions (quality of decision support, intention to incorporate decision support into practice and perceived usefulness of intervention components). Between group differences in the primary outcome (quality of decision support scores) will be analyzed using ANOVA.
Few studies have investigated the efficacy of an evidence-based, theory guided intervention aimed at assisting clinicians to strengthen their patient decision support skills. Expanding our understanding of how clinicians can best support palliative patients' decision-making will help to inform best practices in patient-centered palliative care. There is potential transferability of lessons learned to other care situations such as chronic condition management, advance directives and anticipatory care planning. Should the efficacy evaluation reveal clear improvements in the quality of decision support provided by clinicians who received the intervention, a larger scale implementation and effectiveness trial will be considered.
Trial registration
This study is registered as NCT00614003
PMCID: PMC2396601  PMID: 18447916
24.  Consultant psychiatrists’ experiences of and attitudes towards shared decision making in antipsychotic prescribing, a qualitative study 
BMC Psychiatry  2014;14:127.
Shared decision making represents a clinical consultation model where both clinician and service user are conceptualised as experts; information is shared bilaterally and joint treatment decisions are reached. Little previous research has been conducted to assess experience of this model in psychiatric practice. The current project therefore sought to explore the attitudes and experiences of consultant psychiatrists relating to shared decision making in the prescribing of antipsychotic medications.
A qualitative research design allowed the experiences and beliefs of participants in relation to shared decision making to be elicited. Purposive sampling was used to recruit participants from a range of clinical backgrounds and with varying length of clinical experience. A semi-structured interview schedule was utilised and was adapted in subsequent interviews to reflect emergent themes.
Data analysis was completed in parallel with interviews in order to guide interview topics and to inform recruitment. A directed analysis method was utilised for interview analysis with themes identified being fitted to a framework identified from the research literature as applicable to the practice of shared decision making. Examples of themes contradictory to, or not adequately explained by, the framework were sought.
A total of 26 consultant psychiatrists were interviewed. Participants expressed support for the shared decision making model, but also acknowledged that it was necessary to be flexible as the clinical situation dictated. A number of potential barriers to the process were perceived however: The commonest barrier was the clinician’s beliefs regarding the service users’ insight into their mental disorder, presented in some cases as an absolute barrier to shared decision making. In addition factors external to the clinician - service user relationship were identified as impacting on the decision making process, including; environmental factors, financial constraints as well as societal perceptions of mental disorder in general and antipsychotic medication in particular.
This project has allowed identification of potential barriers to shared decision making in psychiatric practice. Further work is necessary to observe the decision making process in clinical practice and also to identify means in which the identified barriers, in particular ‘lack of insight’, may be more effectively managed.
PMCID: PMC4009071  PMID: 24886121
Antipsychotic prescribing; Shared decision making; Patient centred medicine
25.  Investigating active ingredients in a complex intervention: a nested study within the Patient and Decision Aids (PANDAs) randomised controlled trial for people with type 2 diabetes 
BMC Research Notes  2014;7:347.
Randomised trials provide evidence that patient decision aids improve outcomes with respect to patient knowledge, involvement and satisfaction in decision making. It is less clear how these complex interventions are implemented within patient-clinician interactions and which components are active for improving decision processes. To investigate the experiences of using a diabetes treatment decision aid and to explore how components within a complex intervention influenced the decision making process.
A pragmatic mixed methods study nested within the PANDAs cluster randomised trial of a patient decision aid. Themes inductively derived from interviews and observation of consultations with further triangulation with results of decision quality and involvement measurements and case analyses.
The decision aid intervention was employed flexibly within the consultation with both the patient and clinician active in marshalling elements. The decision aid improved processing and organization of information needed for decision making within the consultation interaction. It also improved decision quality by preparing the patient for active involvement within the clinical consultation.
The intervention was acceptable, flexible and readily implemented in primary care consultations. The decision aid was effective in facilitating cognitive processing. The intervention also facilitated rehearsal in preparation for active roles in a shared decision process.
Trial registration
Trials Register Number: ISRCTN14842077. Date registered: 24.06.2010.
PMCID: PMC4062287  PMID: 24908099
Patient decision aid; Process evaluation; Type 2 diabetes; Primary care

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