Boken presenterer en helhetlig strategi for hvordan myndigheter, helsepersonell, industri og forbrukere kan redusere medisinske feil.

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To Err Is Human Building a Safer Health System

The Task Force for the management of atrial fibrillation of the European Society of Cardiology (ESC)  

Developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC  

Endorsed by the European Stroke Organisation (ESO)

/pdf/2016-esc-guidelines-for-the-management-of-atrial-ba0601yb9m.pdf

2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS

Background
Decision aids are intended to help people participate in decisions that involve weighing the benefits and harms of treatment options often with scientific uncertainty.

Objectives
To assess the effects of decision aids for people facing treatment or screening decisions.

Search methods
For this update, we searched from 2009 to June 2012 in MEDLINE; CENTRAL; EMBASE; PsycINFO; and grey literature. Cumulatively, we have searched each database since its start date including CINAHL (to September 2008).

Selection criteria
We included published randomized controlled trials of decision aids, which are interventions designed to support patients' decision making by making explicit the decision, providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies of participants making hypothetical decisions.

Data collection and analysis
Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were:

A) 'choice made' attributes;

B) 'decision-making process' attributes.

Secondary outcomes were behavioral, health, and health-system effects. We pooled results using mean differences (MD) and relative risks (RR), applying a random-effects model.

Main results
This update includes 33 new studies for a total of 115 studies involving 34,444 participants. For risk of bias, selective outcome reporting and blinding of participants and personnel were mostly rated as unclear due to inadequate reporting. Based on 7 items, 8 of 115 studies had high risk of bias for 1 or 2 items each.

Of 115 included studies, 88 (76.5%) used at least one of the IPDAS effectiveness criteria: A) 'choice made' attributes criteria: knowledge scores (76 studies); accurate risk perceptions (25 studies); and informed value-based choice (20 studies); and B) 'decision-making process' attributes criteria: feeling informed (34 studies) and feeling clear about values (29 studies).

A) Criteria involving 'choice made' attributes:

Compared to usual care, decision aids increased knowledge (MD 13.34 out of 100; 95% confidence interval (CI) 11.17 to 15.51; n = 42). When more detailed decision aids were compared to simple decision aids, the relative improvement in knowledge was significant (MD 5.52 out of 100; 95% CI 3.90 to 7.15; n = 19). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.82; 95% CI 1.52 to 2.16; n = 19). Exposure to a decision aid with explicit values clarification resulted in a higher proportion of patients choosing an option congruent with their values (RR 1.51; 95% CI 1.17 to 1.96; n = 13).

B) Criteria involving 'decision-making process' attributes:

Decision aids compared to usual care interventions resulted in:

a) lower decisional conflict related to feeling uninformed (MD -7.26 of 100; 95% CI -9.73 to -4.78; n = 22) and feeling unclear about personal values (MD -6.09; 95% CI -8.50 to -3.67; n = 18);

b) reduced proportions of people who were passive in decision making (RR 0.66; 95% CI 0.53 to 0.81; n = 14); and

c) reduced proportions of people who remained undecided post-intervention (RR 0.59; 95% CI 0.47 to 0.72; n = 18).

Decision aids appeared to have a positive effect on patient-practitioner communication in all nine studies that measured this outcome. For satisfaction with the decision (n = 20), decision-making process (n = 17), and/or preparation for decision making (n = 3), those exposed to a decision aid were either more satisfied, or there was no difference between the decision aid versus comparison interventions. No studies evaluated decision-making process attributes for helping patients to recognize that a decision needs to be made, or understanding that values affect the choice.

C) Secondary outcomes

Exposure to decision aids compared to usual care reduced the number of people of choosing major elective invasive surgery in favour of more conservative options (RR 0.79; 95% CI 0.68 to 0.93; n = 15). Exposure to decision aids compared to usual care reduced the number of people choosing to have prostate-specific antigen screening (RR 0.87; 95% CI 0.77 to 0.98; n = 9). When detailed compared to simple decision aids were used, fewer people chose menopausal hormone therapy (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable.

The effect of decision aids on length of consultation varied from 8 minutes shorter to 23 minutes longer (median 2.55 minutes longer) with 2 studies indicating statistically-significantly longer, 1 study shorter, and 6 studies reporting no difference in consultation length. Groups of patients receiving decision aids do not appear to differ from comparison groups in terms of anxiety (n = 30), general health outcomes (n = 11), and condition-specific health outcomes (n = 11). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive.

Authors' conclusions
There is high-quality evidence that decision aids compared to usual care improve people's knowledge regarding options, and reduce their decisional conflict related to feeling uninformed and unclear about their personal values. There is moderate-quality evidence that decision aids compared to usual care stimulate people to take a more active role in decision making, and improve accurate risk perceptions when probabilities are included in decision aids, compared to not being included. There is low-quality evidence that decision aids improve congruence between the chosen option and the patient's values.

New for this updated review is further evidence indicating more informed, values-based choices, and improved patient-practitioner communication. There is a variable effect of decision aids on length of consultation. Consistent with findings from the previous review, decision aids have a variable effect on choices. They reduce the number of people choosing discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, cost-effectiveness, use with lower literacy populations, and level of detail needed in decision aids need further evaluation. Little is known about the degree of detail that decision aids need in order to have a positive effect on attributes of the choice made, or the decision-making process.

/pdf/decision-aids-for-people-facing-health-treatment-or-1j1706q17l.pdf

Decision aids for people facing health treatment or screening decisions

/pdf/2016-esc-guidelines-for-the-management-of-atrial-36b2cidm1x.pdf

2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS: The Task Force for the management of atrial fibrillation of the European Society of Cardiology (ESC). Developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC. Endorsed by the European Stroke Organisation (ESO)

The author systematically examines one of the important issues of information — establishing the market price. He introduces the concept of «search» — where a buyer wanting to get a better price, is forced to question sellers. The article deals with various aspects of finding the necessary information.

Economics of Information

Two significant emerging policy directions put patients and consumers in a key role for influencing health care quality and costs. First, consumer-directed health plans rely on informed consumer choices to contain costs and improve the quality of care. This approach assumes that consumers will make more prudent health and health care choices when they are given financial incentives along with access to comparative cost and quality information. This approach also assumes that the combination of financial incentives and relevant information will increase their “activation” (Gabel, Lo Sasso, and Rice 2002). Second, the Chronic Illness Care Model (Bodenheimer et al. 2002) emphasizes patient-oriented care, with patients and their families integrated as members of the care team. A critical element in the model is activated patients, with the skills, knowledge, and motivation to participate as effective members of the care team (Von Korff et al. 1997).

A key health policy question is, what would it take for consumers to become effective and informed managers of their health and health care? What skills, knowledge, beliefs, and motivations do they need to become “activated” or more effectual health care actors? These are essential questions if we hope to improve the health care process, the outcomes of care, and control costs. This is true especially with regard to the 99 million Americans with a chronic disease. Because those with chronic illness need ongoing care, account for a large portion of health care costs, and must play an important role in maintaining their own functioning, encouraging their activation should be a priority.

Even though patient activation is a central concept in both the consumer driven health care approach and the chronic illness care models, it remains conceptually and empirically underdeveloped. There has been a lack of conceptual clarity regarding “activation,” and thus a lack of adequate measurement. There are a number of existing methods for assessing different aspects of activation, such as health locus of control (Wallston, Stein, and Smith), self-efficacy in self-managing behaviors (Lorig et al. 1996), and readiness to change health-related behaviors (DiClemente et al. 1991; Prochaska, Redding, and Evers 1997), but these measures tend to focus on the prediction of a single behavior. Moreover, there is no existing measure that includes the broad range of elements involved in activation, including the knowledge, skills, beliefs, and behaviors that a patient needs to manage a chronic illness.

In this paper we describe the development of the Patient Activation Measure (PAM), a measure of activation that is grounded in rigorous conceptualization and appropriate psychometric methods. The PAM was developed in four stages:


Stage 1.Conceptually defining activation involved a literature review, systematic consultation with experts using a “consensus method,” and consultation with individuals with chronic disease using focus groups.


Stage 2.Preliminary scale development began by building on the domains identified in stage one and operationalizing them with survey items within each domain. Steps included generating, refining, and testing a large item pool. We used Rasch psychometric methods to develop the scale and test the preliminary measure's psychometric properties.


Stage 3.Stage three involved exploring the possibility of extending the range of the measure, refining the response categories, and testing whether the measure could be used with respondents who had no chronic illnesses.


Stage 4.In the fourth and final stage a national probability sample was used to assess the performance of the measure across different subsamples in the population and to assess the construct validity of the measure.

/pdf/development-of-the-patient-activation-measure-pam-50q63ng0ok.pdf

Development of the Patient Activation Measure (PAM): Conceptualizing and Measuring Activation in Patients and Consumers

Objective The Patient Activation Measure (PAM) is a 22-item measure that assesses patient knowledge, skill, and confidence for self-management. The measure was developed using Rasch analyses and is an interval level, unidimensional, Guttman-like measure. The current analysis is aimed at reducing the number of items in the measure while maintaining adequate precision. Study methods We relied on an iterative use of Rasch analysis to identify items that could be eliminated without loss of significant precision and reliability. With each item deletion, the item scale locations were recalibrated and the person reliability evaluated to check if and how much of a decline in precision of measurement resulted from the deletion of the item. Data sources The data used in the analysis were the same data used in the development of the original 22-item measure. These data were collected in 2003 via a telephone survey of 1,515 randomly selected adults. Principal Findings. The analysis yielded a 13-item measure that has psychometric properties similar to the original 22-item version. The scores for the 13-item measure range in value from 38.6 to 53.0 (on a theoretical 0-100 point scale). The range of values is essentially unchanged from the original 22-item version. Subgroup analysis suggests that there is a slight loss of precision with some subgroups. Conclusions The results of the analysis indicate that the shortened 13-item version is both reliable and valid.

/pdf/development-and-testing-of-a-short-form-of-the-patient-334t2g8n4g.pdf

Development and testing of a short form of the patient activation measure.

Patient engagement is an increasingly important component of strategies to reform health care. In this article we review the available evidence of the contribution that patient activation—the skills and confidence that equip patients to become actively engaged in their health care—makes to health outcomes, costs, and patient experience. There is a growing body of evidence showing that patients who are more activated have better health outcomes and care experiences, but there is limited evidence to date about the impact on costs. Emerging evidence indicates that interventions that tailor support to the individual’s level of activation, and that build skills and confidence, are effective in increasing patient activation. Furthermore, patients who start at the lowest activation levels tend to increase the most. We conclude that policies and interventions aimed at strengthening patients’ role in managing their health care can contribute to improved outcomes and that patient activation can—and should—be measur...

What The Evidence Shows About Patient Activation: Better Health Outcomes And Care Experiences; Fewer Data On Costs

Objective
The purpose of this study is to determine whether patient activation is a changing or changeable characteristic and to assess whether changes in activation also are accompanied by changes in health behavior.

/pdf/do-increases-in-patient-activation-result-in-improved-self-3ccg39kwph.pdf

Do increases in patient activation result in improved self-management behaviors?

Background
There is a growing awareness that patients should be more active and effective managers of their health and health care. Recent studies have found patient activation—or having the knowledge, skills, and confidence to manage one’s health, to be related to health-related outcomes. These studies have often relied on self-reported outcomes and often have used small samples.

/pdf/why-does-patient-activation-matter-an-examination-of-the-1e06nqbugm.pdf

Judith H. Hibbard

Papers

Development of the Patient Activation Measure (PAM): Conceptualizing and Measuring Activation in Patients and Consumers

Development and testing of a short form of the patient activation measure.

What The Evidence Shows About Patient Activation: Better Health Outcomes And Care Experiences; Fewer Data On Costs

Do increases in patient activation result in improved self-management behaviors?

Why Does Patient Activation Matter? An Examination of the Relationships Between Patient Activation and Health-Related Outcomes