Interventions to support shared decision making for medication therapy in long term conditions: A systematic review

G Model PEC 6381 No. of Pages 12

Patient Education and Counseling xxx (2019) xxx–xxx

Contents lists available at ScienceDirect

Patient Education and Counseling journal homepage: www.elsevier.com/locate/pateducou

Review Article

Interventions to support shared decision making for medication therapy in long term conditions: A systematic review Elke G.E. Mathijssena,* , Bart J.F. van den Bemtb,c , Frank H.J. van den Hoogena,d , Calin D. Popaa,d, Johanna E. Vriezekolka a

Department of Rheumatology, Sint Maartenskliniek, Nijmegen, the Netherlands Department of Pharmacy, Sint Maartenskliniek, Nijmegen, the Netherlands Department of Pharmacy, Radboud University Medical Center, Nijmegen, the Netherlands d Department of Rheumatology, Radboud University Medical Center, Nijmegen, the Netherlands b c

A R T I C L E I N F O

A B S T R A C T

Article history: Received 12 April 2019 Received in revised form 21 August 2019 Accepted 24 August 2019

Objective: 1) To examine the effectiveness of interventions to support shared decision making (SDM) for medication therapy in long term conditions on patient outcomes; 2) to identify characteristics of SDM interventions that are associated with positive patient outcomes. Methods: A systematic search for randomized controlled trials up to February 2019. A best evidence synthesis was performed. Intervention characteristics that are likely to be associated with positive patient outcomes were identified using descriptive statistics. Results: Twenty-five articles reporting 23 studies were included. Seventeen patient outcomes were assessed using a variety of measurement instruments. There was evidence for a positive effect of SDM interventions on risk estimation and involvement in decision making. Evidence for no effect was found on four outcomes (e.g. medication adherence) and conflicting evidence on ten outcomes (e.g. decisional conflict). Electronically delivered SDM interventions and those comprising value clarification exercises were likely to be associated with positive patient outcomes. Conclusion: There is a lack of evidence for a positive effect of SDM interventions on the majority of patient outcomes. The mode and content of SDM interventions seem to affect patient outcomes. Practice implications: There is a need for standardization of patient outcomes and measurement instruments to evaluate SDM interventions. © 2019 Elsevier B.V. All rights reserved.

Keywords: Patient centered care Shared decision making Medication therapy Long term conditions Patient outcomes Intervention characteristics Systematic review

Contents 1. 2.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . Search strategy . . . . . . . . . . . . . . . . . 2.1. Inclusion criteria . . . . . . . . . . . . . . . . 2.2. Risk of bias assessment . . . . . . . . . . 2.3. Data extraction . . . . . . . . . . . . . . . . . 2.4. Data analysis . . . . . . . . . . . . . . . . . . . 2.5. Best evidence synthesis . . . 2.5.1. Intervention characteristics 2.5.2. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Search results . . . . . . . . . . . . . . . . . . 3.1. Risk of bias assessment . . . . . . . . . . 3.2. Description of studies . . . . . . . . . . . . 3.3. Participants . . . . . . . . . . . . . 3.3.1.

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* Corresponding author at: Department of Rheumatology, Sint Maartenskliniek, PO box 9011, 6500 GM, Nijmegen, the Netherlands. E-mail address: [email protected] (E.G.E. Mathijssen). https://doi.org/10.1016/j.pec.2019.08.034 0738-3991/© 2019 Elsevier B.V. All rights reserved.

Please cite this article in press as: E.G.E. Mathijssen, et al., Interventions to support shared decision making for medication therapy in long term conditions: A systematic review, Patient Educ Couns (2019), https://doi.org/10.1016/j.pec.2019.08.034

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3.3.2. SDM interventions . . . . . . . . . Control conditions . . . . . . . . . 3.3.3. Follow-up intervals, outcomes, 3.3.4. Best evidence synthesis . . . . . . . . . . . . 3.4. Intervention characteristics . . . . . . . . . 3.5. Discussion and conclusion . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . 4.1. Conclusion . . . . . . . . . . . . . . . . . . . . . . . 4.2. 4.3. Practice implications . . . . . . . . . . . . . . Role of funding . . . . . . . . . . . . . . . . . . . . . . . . . Author contributions . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.......................... .......................... and measurement instruments .......................... .......................... .......................... .......................... .......................... .......................... .......................... .......................... ..........................

1. Introduction Shared decision making (SDM) is considered the cornerstone of patient centered care [1]. The approach aims to engage clinicians and patients in a partnership to reach a mutual treatment decision, based on the best available evidence and patients’ informed preferences [2]. Although SDM is increasingly promoted, the approach is not widely implemented in clinical practice [3]. Clinicians and patients report various implementation barriers. Frequently reported barriers are time constraints, a lack of applicability due to patient characteristics and/or the clinical context, and the power imbalance in the clinician-patient relationship [4,5]. In recent years, a range of interventions have been developed to overcome these barriers and to support SDM [6]. These SDM interventions come in various types, such as decisions aids, educational meetings, question prompt lists, coaching sessions, and communication skills training programs. However, studies examining the effectiveness of SDM interventions show inconsistent results [7–9]. Two possible explanations for these inconsistencies are the various clinical contexts in which SDM interventions are implemented and the heterogeneity of intervention characteristics. Some clinical contexts may be more suitable for SDM than others [7]. Long term care, relative to acute care, naturally provides more scope for involvement of patients in the decision making process. Long term care decisions are usually made over an extended period of time and are more likely to require an active patient role in carrying out the treatment (e.g. medication adherence) [10]. In addition, SDM is particularly suitable for preference-sensitive decisions where two or more equivalent treatment options exist [11,12]. Relevant examples in the long term care context are decisions about treatment with medication. These treatment decisions involve trade-offs between potential benefits and risks [13]. Individual values and preferences are then key to determining the best treatment option. In contrast to previous systematic reviews that included studies in various clinical contexts, this systematic review specifically focused on interventions to support SDM for medication therapy in long term conditions, excluding cancer and mental illness. Intervention characteristics (e.g. target, format, mode, content, and frequency) may also moderate an intervention’s effect [14]. SDM interventions are quite heterogeneous in terms of their characteristics. Consequently, a crucial question is which intervention characteristics constitute the effective ingredients. For example, studies suggest that SDM interventions targeting both clinicians and patients are more likely to be effective than the ones that solely focus on one of the parties [6]. Furthermore, SDM interventions may be differentially effective according to their frequency of delivery [7]. To date, insight into whether and how different intervention characteristics contribute to the desired outcomes is lacking. This knowledge is valuable for the implementation and future development of SDM interventions.

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Therefore, the aim of this systematic review was: 1) to examine the effectiveness of interventions to support SDM for medication therapy in long term conditions on patient outcomes; and 2) to identify characteristics of SDM interventions that are associated with positive patient outcomes. 2. Methods This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [15]. 2.1. Search strategy The databases of PubMed, EMBASE, PsycINFO, Web of Science, CINAHL, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched from inception to February 2019. A similar search strategy was built for each database using subject headings and text words (Supplementary file 1). The search strategy was limited to peer-reviewed articles written in English or Dutch. Titles and abstracts were independently screened by two researchers (EM and BvdB or JV). The full texts of potentially relevant articles were independently assessed for inclusion by two researchers (EM and JV). Discrepancies between the researchers were resolved through discussion and consensus. If no consensus was reached, a third researcher (BvdB) was consulted. The reference lists of the included articles were hand searched to identify additional articles. Different articles reporting the same study were all included, provided that they reported complementary data. 2.2. Inclusion criteria Studies had to meet the following inclusion criteria: 1) the design was a randomized controlled trial; 2) the study population consisted of patients aged 18 years or older with a long term condition, defined as a condition that lasts a year or more and requires ongoing medical attention and/or limits activities of daily living [16]; 3) patients faced a decision about treatment with medication (i.e. different types of medication, treatment with medication versus another non-pharmacological treatment option, or treatment with medication versus no treatment); 4) the SDM intervention targeted clinicians, patients, or both and was developed to facilitate involvement of patients in the decision making process; 5) the control group received usual care or an alternative intervention (i.e. passive or active control condition); and 6) at least one patient outcome was assessed within six months post-intervention. In this systematic review, patient outcomes were defined as all subjective and objective outcomes, reported by patients or directly related to patients’ health or behavior. Studies in patients with cancer or mental illness were excluded. Studies in mixed patient populations were also excluded, unless results were reported separately for each population.

Please cite this article in press as: E.G.E. Mathijssen, et al., Interventions to support shared decision making for medication therapy in long term conditions: A systematic review, Patient Educ Couns (2019), https://doi.org/10.1016/j.pec.2019.08.034

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2.3. Risk of bias assessment Two researchers (EM and BvdB) independently assessed the internal validity of each study according to the Cochrane Collaboration’s tool for assessing risk of bias [17]. Seven domains were scored low risk of bias/positive (+), high risk of bias/negative (-), or unclear risk of bias (?). Five of seven domains were considered key domains. Because blinding of participants and personnel and blinding of outcome assessment is hardly feasible in studies evaluating SDM interventions, these two domains were not considered key domains. Studies with a positive score on all five key domains were considered high quality studies. If relevant information was not reported, the corresponding author was contacted to request the information. Discrepancies between the researchers’ assessments were resolved in a consensus meeting with a third researcher (JV).

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significant. Statistical significance was set at p < 0.05. If p-values or confidence intervals were not reported, these measures were calculated using means and standard deviations or proportions. If multiple measurement instruments or subscales were used to assess a single outcome within a study, the outcome was scored in concordance with the direction (i.e. positive, negative, or unclear) of the majority (>50%) of the results. In the absence of a majority, the outcome was scored mixed. Based on a previous systematic review, outcomes were categorized into three different outcome categories: 1) cognitive-affective outcomes; 2) behavioral outcomes; and 3) health outcomes [8]. Details of the SDM interventions were extracted using the Template for Intervention Description and Replication (TIDieR) checklist and guide [18]. Data were extracted by one researcher (EM) and checked for accuracy by a second researcher (BvdB or JV). 2.5. Data analysis

2.4. Data extraction A standardized template was used to extract data on participants, SDM interventions, control conditions, follow-up intervals, outcomes, and measurement instruments. This systematic review only focused on outcomes that were assessed within six months post-intervention. To avoid redundancy, only the first assessment of an outcome was extracted in studies with multiple follow-ups within six months post-intervention. Also, results of subscales were extracted only if no total score was reported. Outcomes were scored positive (+) if there was a statistically significant effect favoring the intervention group, negative (-) if there was a statistically significant effect favoring the control group, and not significant (NS) if the effect was not statistically

2.5.1. Best evidence synthesis Statistical data pooling was not feasible due to heterogeneity between studies. Therefore, a best evidence synthesis was performed to examine the effectiveness of SDM interventions on patient outcomes [19]. Four levels of evidence were defined according to the Cochrane Back Review Group [20]. Strong evidence reflects consistent results among two or more high quality studies. Moderate evidence reflects the result of one high quality study and/or consistent results among two or more lower quality studies. Limited evidence reflects the result of one lower quality study. Conflicting evidence reflects inconsistent results among two or more studies. Results were considered consistent if more than 75 percent of the studies reported results in

Fig. 1. Flow diagram of the inclusion procedure. Abbreviations: RCT = randomized controlled trial, SDM = shared decision making.

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the same direction. If there were two or more high quality studies, the lower quality studies were disregarded in the best evidence synthesis. Two post-hoc sensitivity analyses assessed the robustness of the best evidence synthesis’ results. The first analysis was stratified for studies with a passive and active control condition. The second analysis used a less stringent cut-off point for study quality. Studies with a positive score on at least four key domains, instead of all five key domains in the initial analysis, of the Cochrane Collaboration’s tool for assessing risk of bias were considered high quality studies. 2.5.2. Intervention characteristics A template, based on the TIDieR checklist and guide, was created to extract data on intervention characteristics in a standardized manner [18]. The following intervention characteristics were included: 1) theory-based (yes, no); 2) multifaceted (yes, no); 3) target (patients, clinicians and patients); 4) setting (home-based, healthcare setting); 5) format (individual, group); 6) mode (face-to-face, on paper, electronic, audio, video, telephone); 7) content (education, value clarification exercises, communication skills training for clinicians, communication skills training for patients); 8) timing (before the consultation, during the consultation); and 9) frequency (once, more than once). Two researchers (EM and JV) independently determined the presence of all characteristics in each SDM intervention. Also, the percentage of SDM interventions with a particular characteristic was calculated. Discrepancies between the researchers were resolved through discussion until consensus was reached. Furthermore, success rates were calculated to identify intervention characteristics that are likely to be associated with positive patient outcomes [21]. Outcomes that were assessed in more than five studies were selected. Success rates of intervention characteristics were calculated per outcome. To calculate a success rate, the number of studies evaluating a SDM intervention with a particular characteristic and a positive outcome was divided by all studies evaluating a SDM intervention with that characteristic regardless of outcome. Outcomes were considered positive if there was a statistically significant effect (p < 0.05) favoring the intervention group. Success rates were expressed as percentages. A success rate was calculated only if the intervention characteristic was present in five or more studies. 3. Results 3.1. Search results Fig. 1 shows a flow diagram of the inclusion procedure. Twentysix articles reporting 23 studies met the inclusion criteria [22–47]. One study was reported in two articles [22,24]. Both articles were included. Another study was reported in three articles [30,39,44]. One of these articles did not report complementary data and was excluded from this systematic review [30]. This reduced the number of included articles to 25. 3.2. Risk of bias assessment

Fig. 2. Summary of the risk of bias assessment. $Articles reporting the same study. #Articles reporting the same study.

A summary of the risk of bias assessment is shown in Fig. 2. Fifteen studies had a positive score on all five key domains and were considered high quality studies [22,24–26,28,29,32,33,36–39,43–47]. 3.3. Description of studies 3.3.1. Participants Table 1 shows an overview of the included studies. Eleven studies included patients with type 1 and/or type 2 diabetes [23,25,26,29,31,35,38–40,44–46]. The other twelve studies

included patients with multiple sclerosis [32,33,41], osteoporosis [34,37], atrial fibrillation [36,42], fibromyalgia [22,24], osteoarthritis [27], trapezio-metacarpal arthritis (i.e. osteoarthritis at the base of the thumb) [47], peptic ulcer disease [28], and asthma [43]. Studies had sample sizes ranging from 45 to 408 patients.

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Table 1 Overview of the included studies. First author (year)

Participants

SDM intervention

Control condition

Follow-up interval

Bailey (2016) Bieber (2006)$

Type 2 diabetes (n = 225) Fibromyalgia (n = 101)

Decision aid

Passive

4-6 weeks

Information tool and SDM training for clinicians

Active

Bieber (2008)$

Branda (2013)

Denig (2014)

Fraenkel (2007) Greenfield (1985)

Greenfield (1988)

Karagiannis (2016)

Fibromyalgia (n = 101)

Type 2 diabetes (n = 104)

Type 2 diabetes (n = 344)

Osteoarthritis (n = 87) Peptic ulcer disease (n = 45)

Diabetes (n = 59)

Type 2 diabetes (n = 204)

Information tool and SDM training for clinicians

Decision aid (2x)

Decision aid

Active

Passive

Passive

Interactive computer tool

Active

Review of patients’ medical records, guided by a treatment algorithm, and a behavior-change strategy

Active

Review of patients’ medical records, guided by a treatment algorithm, and a behavior-change strategy

Decision aid

Active

Passive

Kasper (2008)

Multiple sclerosis (n = 297)

Decision aid

Active

Köpke (2013)

Multiple sclerosis (n = 192)

Patient information program

Active

LeBlanc (2015)

Osteoporosis (n = 77)

Decision aid

Passive

Mann (2010)

Diabetes (n = 150)

Decision aid

Active

Man-SonHing (1999)

Atrial fibrillation (n = 287)

Decision aid

Passive

Outcome

Knowledge Decisional conflict* Directly after the Clinical parameters consultation Health-related quality of life Physical functioning Psychological functioning Directly after the Clinician-patient consultation relationship Satisfaction with decision Decisional conflict Directly after the Knowledgez consultation Risk estimation*z Decisional conflict*z Involvement in decision makingz 3-4 months Attitudes and beliefs* Self-efficacy* Satisfaction with care Health-related quality of life Psychological functioning Directly after the Decisional conflict consultation Self-efficacy During the Involvement in consultation decision making* Directly after the Knowledge consultation Decision making 6-8 weeks preferences Satisfaction with care Clinical parameters Physical functioning* During the Involvement in consultation decision making* Knowledge 12 weeks Satisfaction with care Clinical parameters Health-related quality of life* Physical functioning* Directly after the Knowledge consultation Decisional conflict Satisfaction with decision making process Satisfaction with decision Medication adherence 12 weeks Clinical parameters Directly after the Attitudes and beliefs consultation Involvement in decision making 2 weeks Risk estimation Attitudes and beliefs* Decision making preferences Directly after the Knowledge consultation Risk estimation* Decisional conflict Health-related quality of life Directly after the Knowledge consultation Risk estimation* Attitudes and beliefs* Decisional conflict 3 months Medication adherence 1-4 days Knowledge* Risk estimation*

Score + +, + NS NS NS NS + NS NS +a +b, +b NSa, NSa, NSa, NSb, NSb, NSb +a, +b NS, NS, NS, NS NS, NS, NS NS NS NS + + NS, +, +, +, + – + NS NS +, + NS, +, +, +, + NS NS + NS, +, + NS, +, +, + NS NS NS

NS NS NS + NS + NS, NS, +, +, + NS NS +, + NS NS NS NS, NS NS, NS NS NS NS, +, + +, +, +, + NS, NS, NS, NS, NS, NS

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Table 1 (Continued) First author (year)

Participants

SDM intervention

Control condition

Follow-up interval

Montori (2011)

Osteoporosis (n = 100)

Decision aid

Active

Directly after the consultation

Mullan (2009)

Type 2 diabetes (n = 85)

Decision aid

Active

Directly after the consultation

Nannenga (2009)# PeresteloPérez (2016)

Type 2 diabetes (n = 98) Type 2 diabetes (n = 168)

Decision aid

Active

Decision aid

Passive

Directly after the consultation Directly after the consultation

Rahn (2018)

Multiple sclerosis (n = 73)

Clinician training course and patient coaching intervention

Active

3 months During the consultation 2 weeks

Thomson (2007)

Atrial fibrillation (n = 136)

Decision aid

Active

Directly after the consultation

Wilson (2010) Weymiller (2007)#

Asthma (n = 408)

Treatment protocol based on SDM

Active

Type 2 diabetes (n = 98)

Decision aid

Active

Directly after the consultation Directly after the consultation

Mathers (2012)

Type 2 diabetes (n = 175)

Decision aid

Passive

Buhse (2018) Wilkens (2018)

Type 2 diabetes (n = 279) Trapeziometacarpal arthritis (n = 90)

Informed SDM program for patients

Active

Decision aid

Active

3 months Directly after the consultation

Outcome Satisfaction with decision making process* Decisional conflict Stage of decision making Knowledge Risk estimation* Clinician-patient relationship Decisional conflict Knowledge Clinician-patient relationship Decisional conflict Clinician-patient relationship Knowledge Risk estimation* Satisfaction with decision making process Decisional conflict Psychological functioning Medication adherence* Involvement in decision making Risk estimation Self-efficacy Clinician-patient relationship Decisional conflict Stage of decision making Knowledge* Decisional conflict Psychological functioning Involvement in decision making Knowledge* Risk estimation* Decisional conflict Medication adherence* Knowledge* Risk estimation* Involvement in decision making Decisional conflict Stage of decision making Risk estimation

Directly after the consultation Directly after the Decisional conflict consultation Directly after the Satisfaction with care consultation Satisfaction with 6 weeks decision Clinical parameters 6 weeks

Score

NS + + +, + NS NS + NS NS NS + NS, + +

NS NS NS, NS + NS NS NS + NS NS, NS + NS + NS, + NS, +, + + + NS, + +, +, + + + NS + + NS NS NS

$Articles reporting the same study. #Articles reporting the same study. *Multiple instruments or subscales were used to assess a single outcome within a study. z Results were reported separately for different intervention and control groups within a study, referred to as a and b. Abbreviations: SDM = shared decision making, NS = not significant (i.e. no statistically significant effect), + = positive (i.e. a statistically significant effect favoring the intervention group), - = negative (i.e. a statistically significant effect favoring the control group).

3.3.2. SDM interventions Seventeen different SDM interventions were evaluated. The SDM intervention in 15 studies concerned a decision aid [23,25,26,31,32,34–40,42,44,45,47]. Three decisions aids were evaluated in multiple studies. The Statin Choice decision aid was

evaluated in four studies [25,35,39,40,44], the Diabetes Medication Choice decision aid in three studies [25,31,38], and the Osteoporosis Choice decision aid in two studies [34,37]. The SDM intervention in the other eight studies concerned an information tool and SDM training for clinicians [22,24], a review of patients’

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medical records, guided by a treatment algorithm, and a behaviorchange strategy [28,29], an interactive computer tool [27], a patient information program [33], a clinician training course and a patient coaching intervention [41], a treatment protocol based on SDM [43], and an informed SDM program for patients [46]. Supplementary file 2 includes details of the SDM interventions. 3.3.3. Control conditions In eight studies the control group received usual care [23,25,26,31,34,36,40,45]. In the other 15 studies the control group received an alternative intervention consisting of information [22,24,27,32,35,37–39,41,44,46,47], an extra consultation and information [28,29], a stress management program and information [33], and a treatment protocol based on clinician decision making [42,43].

7

3.4. Best evidence synthesis Table 2 shows the results of the best evidence synthesis. There was strong evidence for a positive effect of SDM interventions on risk estimation and involvement in decision making. Strong evidence for no effect was found on satisfaction with care, clinician-patient relationship, satisfaction with decision, and psychological functioning. Moderate evidence for no effect was found on medication adherence. Conflicting evidence was found on knowledge, attitudes and beliefs, self-efficacy, decision making preferences, satisfaction with decision making process, decisional conflict, stage of decision making, clinical parameters, healthrelated quality of life, and physical functioning. The post-hoc sensitivity analyses did not alter the direction of the results (Supplementary file 4). 3.5. Intervention characteristics

3.3.4. Follow-up intervals, outcomes, and measurement instruments Follow-up intervals varied from during the consultation to 3–4 months post-intervention. Seventeen patient outcomes were assessed, namely knowledge, risk estimation, attitudes and beliefs, self-efficacy, satisfaction with care, decision making preferences, clinician-patient relationship, satisfaction with decision making process, decisional conflict, satisfaction with decision, stage of decision making, involvement in decision making, medication adherence, clinical parameters, health-related quality of life, physical functioning, and psychological functioning. A variety of measurement instruments were used comprising both standardized questionnaires and scales and measurement instruments developed specifically for a particular study. Supplementary file 3 includes the categorization of patient outcomes and measurement instruments. This file also shows which measurement instruments were used in each study.

Table 3 shows the presence of all characteristics in each SDM intervention and the percentage of SDM interventions with a particular characteristic. Four outcomes were assessed in more than five studies, namely knowledge (n = 14), risk estimation (n = 11), decisional conflict (n = 17), and involvement in decision making (n = 8). Success rates of intervention characteristics were calculated for these outcomes (Table 4). Success rates indicated that SDM interventions with an electronic mode of delivery were likely to be associated with less decisional conflict. Those comprising value clarification exercises seemed to be associated with better risk estimation and less decisional conflict. Success rates also indicated that SDM interventions delivered during the consultation were likely to be associated with better knowledge and more involvement in decision making. In contrast, intervention delivery before the consultation seemed to be associated with

Table 2 Results of the best evidence synthesis. Outcome categories

Outcome

Studies

Effect

Level of evidence

Cognitive-affective outcomes

Knowledge

8 6 7 4 3 1 1 2 4 2 4 1 1 2 9 8 2 1 2 1 5 3 1 3 4 1 3 1 3 2 2

NS, +, +, +, +, mixed, mixed, NS, NS, NS, NS, +, + +, +, +, +, +, +, + NS, NS, +, mixed NS, +, + NS NS NS, + NS, NS, NS, NS NS, + NS, NS, NS, + NS NS NS, + NS, NS, NS, NS, NS, NS, +, +, + NS, NS, NS, NS, +, +, +, + NS, NS NS NS, + NS NS, +, +, +, + +, +, + + NS, NS, NS NS, NS, NS, + NS NS, NS, + NS NS, +, + NS, NS NS, NS

Conflicting evidence

Risk estimation Attitudes and beliefs Self-efficacy Satisfaction with care Decision making preferences Clinician-patient relationship Satisfaction with decision making process Decisional conflict Satisfaction with decision Behavioral outcomes

Stage of decision making Involvement in decision making Medication adherence

Health outcomes

Clinical parameters Health-related quality of life Physical functioning Psychological functioning

HQ studies LQ studies HQ studies LQ studies HQ study LQ studies HQ study LQ studies HQ study HQ studies HQ studies LQ study HQ study LQ studies HQ studies LQ studies HQ studies LQ study HQ studies LQ studies HQ studies LQ studies HQ studies LQ studies HQ studies LQ study HQ study LQ study HQ studies HQ study LQ study

Strong evidence for a positive effect Conflicting evidence Conflicting evidence Strong evidence for no effect Conflicting evidence Strong evidence for no effect Conflicting evidence Conflicting evidence Strong evidence for no effect Conflicting evidence Strong evidence for a positive effect Moderate evidence for no effect Conflicting evidence Conflicting evidence Conflicting evidence Strong evidence for no effect

Abbreviations: HQ = high quality, LQ = lower quality, NS = not significant (i.e. no statistically significant effect), + = positive (i.e. a statistically significant effect favoring the intervention group), - = negative (i.e. a statistically significant effect favoring the control group).

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SDM

training for

clinicians

[22,24]

Decision

Aid for

type 2

diabetes

exercises

More than once

Once

Frequency

consultation

During the

consultation

Before the

Timing

for clinicians

skills training

Communication

for patients

skills training

Communication

X

X

X

Value

clarification

X

Education

Content

Telephone

Video

X

X

X

X

X

X

X

X

X

X

X

X

X

Audio

X

X

X

X

X

X

Electronic

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

behavior-

diab) [26]

X

and a

X

X

X

X

X

X

X

X

X

X

X

[28,29]

strategy

change

algorithm,

treatment

a

guided by

records,

medical

patients’

A review of

(PORTDA-

On paper

Face-to-face

Mode

Group

Individual

Format

setting

Healthcare

Home-based

Setting

patients

Clinicians and

Patients

Target

No

Yes

Multifaceted

X

tool [27]

computer

interactive

An

diabetes

goals in

treatment

prioritizing

aid for

decision

oriented

A patient

X

X

X

X

X

X

X

X

X

X

[25,31,38]

decision aid

Choice

Medication

Diabetes

The

X

X

X

X

X

X

X

X

X

X

decision aid [32]

(ISDIMS)

sclerosis

multiple

for patients with

immunotherapy

making about

shared decision

The informed

X

X

X

X

X

X

X

X

X

X

X

X

X

[33]

program

information

A patient

X

X

X

X

X

X

X

X

X

X

[34,37]

decision aid

Choice

Osteoporosis

The

X

X

X

X

X

X

X

X

X

X

X

[25,35,39,40,44]

aid

Choice decision

The Statin

Multiple Sclerosis (DECIMS) [41]

prevention in atrial fibrillation [36]

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

[46]

with

stroke

X

diabetes

In people

X

X

X

X

X

X

X

X

X

X

[42]

fibrillation

atrial

patients with

X

X

X

X

X

X

X

X

X

X

X

X

SDM [43]

based on

X

X

X

X

X

X

X

X

X

X

X

X

X

aid [45]

decision

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

2

with type

patients

for

(ISDM-P)

program

SDM

informed

therapy for

An

Coaching

protocol

PANDAs

DEcision

The

antithrombotic

decision aid in

treatment

regarding

A

eatment

decision aid

computerized

immunotr-

booklet

A

Nurse-led

An audio

X

X

X

X

X

X

X

X

X

X

[47]

arthritis

etacarpal

trapeziom-

aid for

A decision

23.5

76.5

58.8

76.5

5.9

23.5

70.6

94.1

5.9

5.9

5.9

47.1

70.6

70.6

23.5

100

82.4

29.4

58.8

41.2

41.2

58.8

17.6

82.4

(%)

Percentage

8

No

Yes

X

tool and

Diabetes

Theory-based

information

interactive

characteristics

[23]

An

The

Intervention

Table 3 Presence of all characteristics in each SDM intervention and percentage of SDM interventions with a particular intervention characteristic.

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Table 4 Success rates of intervention characteristics. Intervention characteristics

Theory-based Yes No Multifaceted Yes No Target Patients Patients and clinicians Setting Home-based Healthcare setting Format Individual Group Mode Face-to-face On paper Electronic Audio Video Telephone Content Education Value clarification exercises Communication skills training for clinicians Communication skills training for patients Timing Before the consultation During the consultation Frequency Once More than once

Success rates (%) Knowledge (n = 14)

Risk estimation (n = 11)

Decisional conflict (n = 17)

Involvement in decision making (n = 8)

5/11 (45.5)

7/10 (70)

6/15 (40)

5/6 (83.3)

5/10 (50)

4/5 (80) 4/6 (66.7)

5/13 (38.5)

4/10 (40)

6/9 (66.7)

4/13 (30.8)

5/5 (100)

4/12 (33.3)

7/10 (70)

6/15 (40)

7/7 (100)

6/14 (42.9)

8/11 (72.7)

7/17 (41.2)

7/8 (87.5)

4/12 (33.3) 5/12 (41.7)

7/10 (70) 8/10 (80)

4/13 (30.8) 3/12 (25) 5/6 (83.3)

7/7 (100) 6/7 (85.7)

6/14 (42.9)

8/11 (72.7) 4/5 (80)

6/16 (37.5) 5/7 (71.4)

7/8 (87.5)

2/6 (33.3) 5/10 (50)

4/6 (66.7) 6/9 (66.7)

6/8 (75) 4/13 (30.8)

4/5 (80) 5/5 (100)

6/14 (42.9)

7/9 (77.8)

6/15 (40)

5/6 (83.3)

5/6 (83.3)

Empty cells indicate that the intervention characteristic was present in less than five studies.

less decisional conflict. The timing of SDM interventions did not seem to affect risk estimation. 4. Discussion and conclusion 4.1. Discussion This systematic review examined the effectiveness of interventions to support SDM for medication therapy in long term conditions on patient outcomes. There was strong evidence for a positive effect of SDM interventions on risk estimation and involvement in decision making. Strong evidence for no effect was found on four outcomes, namely satisfaction with care, clinicianpatient relationship, satisfaction with decision, and psychological functioning. Moderate evidence for no effect was found on medication adherence. Conflicting evidence was found on ten outcomes (e.g. decisional conflict). Electronically delivered SDM interventions and those comprising value clarification exercises were likely to be associated with positive patient outcomes. We found that risk estimation improved after a SDM intervention. In eight studies, patients in the intervention group significantly better estimated their risk of complications with and without medication than control patients. Six of these studies evaluated a decision aid, suggesting that implementing SDM interventions of this type may be sufficient to improve risk estimation. Involvement in decision making also improved after a SDM intervention. In contrast, other decisional outcomes (e.g. decisional conflict, satisfaction with decision, and stage of decision making) did not improve or showed inconsistent results. Three lower quality studies showed no effect of SDM interventions on medication adherence. However, one high quality study that

evaluated a decision aid in patients with type 2 diabetes showed a significant improvement of medication adherence. More studies of high quality are needed to either confirm or refute this result. Fifteen of 17 patient outcomes did not improve after a SDM intervention. This result is in line with previous systematic reviews that examined the effectiveness of SDM interventions and also showed no effect on the majority of patient outcomes [7–9]. It should be noted that we do not know whether the level of SDM in the intervention and control groups differed sufficiently from one another to detect significant differences. It is possible that elements of SDM were also implemented in the control groups as part of usual care. Furthermore, there is a lack of evidence for a positive effect of SDM interventions on health outcomes, such as health-related quality of life. A follow-up interval less than six months post-intervention is probably too short to assess these outcomes. Also, the question arises whether we should expect these outcomes to improve after a SDM intervention. According to theoretical models, clinician-patient communication (e.g. SDM) may improve health outcomes directly, but usually affects these outcomes via an indirect path [48]. For example, if patients have better knowledge of their disease and its treatment, this may affect medication adherence which, in turn, improves patients’ health. There is a need for mediational studies to examine these assumptions. Our results indicated that SDM interventions with an electronic mode of delivery were likely to be associated with less decisional conflict and those comprising value clarification exercises seemed to be associated with better risk estimation and less decisional conflict. The timing of SDM interventions also seemed to affect patient outcomes. However, this result is inconclusive. SDM interventions delivered during the consultation were likely to be

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associated with better knowledge and more involvement in decision making, whereas intervention delivery before the consultation seemed to be associated with less decisional conflict. A randomized controlled trial of Jones et al. showed supportive results for intervention delivery during the consultation [30]. Stiggelbout et al. also reported that SDM interventions delivered during the consultation are more promising than the ones that have been developed for independent use outside the healthcare setting [49]. The limited number of studies did not allow us to make assumptions about the effect of other intervention characteristics. Moreover, some studies fell short in adequately describing the evaluated SDM interventions. This limited our ability to breakdown the SDM interventions in more detail. There are some shortcomings of the included studies that affected our results. Most notably, patient outcomes were often assessed in only a few studies, precluding quantitative metaanalysis. Also, a variety of measurement instruments were used to assess the same outcomes. Many of these measurement instruments were developed specifically for a particular study and lacked evidence of validity and reliability (Supplementary file 3). This indicates that there is currently no consensus about outcomes with which to examine the effectiveness of SDM interventions and measurement instruments to be used. Standardization of patient outcomes and measurement instruments improves the comparability of studies and may lead to more valid conclusions [50]. To date, some attempts have been made to come to an agreed way of evaluating SDM interventions [51,52]. These initiatives could be taken forward for further consensus-building. This systematic review has several strengths and limitations that need to be acknowledged. A limitation was the highly sensitive search strategy that yielded a large number of articles. Most of these articles turned out to be irrelevant. However, to avoid selection bias, it is important that a systematic review considers all possibly relevant articles [53]. Moreover, our inclusion criteria covered various types of SDM interventions. We consider it a strength that this systematic review went beyond consideration of only decision aids as a means to facilitate involvement of patients in the decision making process. Furthermore, we only assessed the studies’ internal validity according the Cochrane Collaboration’s tool for assessing risk of bias. This tool does not address statistical power [17]. Some studies did not report a sample size calculation or were unable to reach their sample size (data not shown). Therefore, they may not have been sufficiently powered to detect significant differences between the intervention and control group. In the best evidence synthesis, these studies were given the same weight as those with sufficient statistical power. Therefore, effects may have remained hidden. The best evidence synthesis itself was a strength. This transparent method is a generally accepted alternative to quantitative meta-analysis [19,20]. 4.2. Conclusion This systematic review shows that interventions to support SDM for medication therapy in long term conditions improve risk estimation and involvement in decision making. There is a lack of evidence for a positive effect of SDM interventions on the majority of patient outcomes. The mode and content of SDM interventions seem to affect patient outcomes. However, we were not able to draw firm conclusions regarding the association between intervention characteristics and positive patient outcomes. This systematic review emphasizes the need for standardization of patient outcomes and measurement instruments to evaluate SDM interventions. Furthermore, we call for more complete reporting of SDM interventions. This is essential to understand what exactly clinicians and patients have been exposed to and may enable

future research to further identify the independent and interactive effects of intervention characteristics. 4.3. Practice implications We argue that the implementation of SDM in clinical practice should still be encouraged. After all, involvement of patients in the decision making process is the right thing to do from an ethical point of view. However, to successfully implement SDM outside the research setting, we have to demonstrate its value to both clinicians and patients. Therefore, an important first step is to increase awareness and understanding of SDM. This may be achieved by making SDM part of health education curricula and by providing clinicians with ample opportunities for accessible and pragmatic communication skills training to foster SDM in their consultations (e.g. e-learning modules) [54]. Recent initiatives, such as the Ask 3 questions campaign, may help target patients along with the implementation of other SDM interventions [55]. As shown by this systematic review, patients may be best served with electronically delivered SDM interventions that not only comprise education, but also exercises that help them clarify their treatment-related values. Furthermore, organizational efforts are required. Organizations should provide clinicians and patients with the infrastructure and support necessary to make SDM an everyday reality. Role of funding This research did not receive any specific grant from funding agencies in the public, commercial, or non-for-profit sectors. Author contributions Elke G.E. Mathijssen: conception and design of the study, acquisition of data, analysis and interpretation of data, drafting and critical revision of the manuscript. Bart J.F. van den Bemt: conception and design of the study, acquisition of data, analysis and interpretation of data, critical revision of the manuscript. Frank H.J. van den Hoogen: analysis and interpretation of data, critical revision of the manuscript. Calin D. Popa: analysis and interpretation of data, critical revision of the manuscript. Johanna E. Vriezekolk: conception and design of the study, acquisition of data, analysis and interpretation of data, critical revision of the manuscript. All authors read and approved the final version of the manuscript. Declaration of Competing Interest The authors declare that there is no conflict of interest. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.pec.2019.08. 034. References [1] C. Charles, A.F. Gafni, T. Whelan, Shared decision-making in the medical encounter: what does it mean? (or it takes at least two to tango), Soc. Sci. Med. 44 (1997) 681–692. [2] G. Elwyn, D. Frosch, R. Thomson, N. Joseph-Williams, A. Lloyd, P. Kinnersley, E. Cording, D. Tomson, C. Dodd, S. Rollnick, A. Edwards, M. Barry, Shared decision making: a model for clinical practice, J. Gen. Intern. Med. 27 (2012) 1361–1367.

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Please cite this article in press as: E.G.E. Mathijssen, et al., Interventions to support shared decision making for medication therapy in long term conditions: A systematic review, Patient Educ Couns (2019), https://doi.org/10.1016/j.pec.2019.08.034