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Wissenschaftlicher Hintergrund POL 6 (1)

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- Angesichts der Neuartigkeit dieses Forschungsbereichs müssen weitere Studien durchgeführt werden, um die Verallgemeinbarkeit des Konzepts sowie seine langfristigen Auswirkungen nachzuweisen.
-legitim ist, sich zu fragen, ob dies das einzig geeignete Studiendesign ist (RCT)

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- PatientInnen erinnern sich nur an eine begrenzte Menge an medizinischen Informationen, die sie erhalten
- bestärkende Faktoren sind
... das medizinische Fachpersonal (Kommunikation, Wissensstand, Vermittlung)
... der/die PatientIn als Person (Alter, Stressoren, Aufnahmefähigkeit, Lernstil)
... Tatsache, dass die meisten PatientInnen nicht in der Lage zu sein scheinen, größere Mengen neuer medizinischer Informationen in kurzer Zeit zu verarbeiten
- wachsende Relevanz von Smartphones und Apps in der
Gesellschaft
- weltweit wurden in den letzten Jahren Studien zur Medical Education zu diversen Fachbereichen der Medizin durchgeführt, welche die Möglichkeiten von Apps in der PatientInnenaufklärung darlegen

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-Welches Design der Informationsbögen bevorzugen die Patient*innen?
-Welche Informationen sind essentiell, welche zu viel?
-Wie wird die Entscheidung bzgl. der OP durch die Informationsbögen beeinflusst?

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Der partielle Gelenkersatz (Schlittenprothese) ist weniger invasiv, ist assoziiert mit einer schnelleren Heilung, geringeren OP-Risiken und einem besseren funktionellen Outcome
aber: höhere Revisions-Rate

Chirurg*innen haben persönliche Präferenzen bezüglich der OP-Verfahren

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- PatientInnenaufklärung ist eine entscheidende Variable bei der gemeinsamen Entscheidungsfindung, einer verbesserten Medikamenten- und Behandlungstreue und einem höheren Maß an Zufriedenheit
- leider hat sich in der Vergangenheit oft gezeigt, dass PatientInnen sich nur an eine begrenzte Menge der medizinischen Informationen erinnern, die sie erhalten
-Apps für Smartphones und Tablets könnten das Potenzial haben, PatientInnen aktiv aufzuklären, indem sie ihnen durch die Verwendung von Push-Benachrichtigungen zeitnahe Informationen zur Verfügung stellen könnten
- darüber hinaus ermöglichen Apps es PatientInnen, medizinische Informationen so oft anzusehen, wie sie möchten, an jedem Ort und zu jeder Zeit

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- im Endstadium der Gonarthrose ist die operative Therapie Mittel der Wahl, wenn konservative Methoden nicht die erwünschte Wirkung zeigen
- weltweit steigt die Zahl der durchgeführten Gelenkersatz-OPs
-sowohl die Totalendoprothese als auch der partielle Gelenkersatz haben Vor- und Nachteile, ein Abwägen ist manchmal schwierig
-die Entscheidung ist oft von der Ärzt*in-Patient*in -Beziehung abhängig
-Patient*innen wünschen sich mehr Informationen, um eine eigene Entscheidung treffen zu können

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- für zukünftige weitere Beschreibung der Entwicklung sind stabile Zeitreihen  und zusätzliche Information entscheidend (z.B. verabreichte Medikamente oder Vorerkrankungen)

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- Arthrose korreliert mit dem Alter,
- Frauen sind häufiger betroffen als Männer
- 17,9% der erwachsenen Gesamtbevölkerung leiden unter dieser Krankheit
-  schmerzhafte Erkrankung der Gelenke + Funktionseinschränkung
- großer Kosten und Aufwandsfaktor für das Gesundheitswesen

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- Arthrose ist eine sehr häufig auftretende Erkrankung, welche Aufgrund des demographischen Wandels in Deutschland zukünftig noch gehäufter auftreten wird
- daraus resultiert eine mögliche Überlastung des Gesundheitswesens und ein hoher Leidensdruck für große Teile der Bevölkerung

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Eure Stichpunkte dazu:

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Review

¹ IQ healthcare, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, Netherlands

² Interactive Studios, Rosmalen, Netherlands

³ Máxima Medical Center, Veldhoven, Netherlands

Corresponding Author:

Thomas Timmers, MSc

IQ healthcare

Radboud Institute for Health Sciences

Radboud University Medical Center

Geert Grooteplein Zuid 10

Nijmegen, 6525 GA

Netherlands

Phone: 31 73 644 6069

Email: thomas.timmers@radboudumc.nl

Background: Patient education is a crucial element within health care. It is a known predictor for increased engagement in shared decision making, improved medication and treatment adherence, higher levels of satisfaction, and even better treatment outcomes. Unfortunately, often patients only remember a very limited amount of medical information. An important reason is that most patients are simply not capable of processing large amounts of new medical information in a short time. Apps for smartphones and tablets have the potential to actively educate patients by providing them with timely information through the use of push notifications.

Objective: The objective of this systematic review is to provide an overview of the effects of using smartphone and tablet apps to educate patients with timely education. Within this review, we focused on patients that receive their care in a hospital setting. We assessed the effects of the interventions on outcomes, such as patients' knowledge about their illness and treatment, adherence to treatment instructions and to medication usage, and satisfaction with the care they received.

Methods: A comprehensive search of MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and Web of Science was conducted. Randomized controlled trials (RCTs) published between January 2015 and November 2019 were eligible for inclusion. Two reviewers independently searched and screened articles, assessed study quality and risk of bias, and extracted the data. Due to the heterogeneity of populations, interventions, and outcomes, a meta-analysis was not deemed appropriate. Instead, a narrative synthesis is presented.

Results: A total of 21 RCTs with 4106 participants were included. Compared to usual care, overall effectiveness of the interventions was demonstrated in 69% of the outcomes. Effectiveness increased to 82% when the intervention had a duration shorter than one month and increased to 78% when the intervention provided at least one push notification per week. The interventions showed the highest effects on satisfaction with information, adherence to treatment instructions and to medication usage, clinical outcomes, and knowledge.

Conclusions: This review demonstrates that educating patients with timely medical information through their smartphones or tablets improves their levels of knowledge, medication or treatment adherence, satisfaction, and clinical outcomes, as well as having a positive effect on health care economics. These effects are most pronounced in interventions with a short duration (ie, less than a month) and with a high frequency of messages to patients (ie, once per week or more). With the knowledge that patient education is a predictor for improved outcomes and the fact that patients have obvious difficulties processing large amounts of new medical information, we suggest incorporating the delivery of timely information through smartphone and tablet apps within current medical practices.

J Med Internet Res 2020;22(4):e17342

doi:10.2196/17342

Keywords

Patient education is a crucial element within health care. Health care professionals provide patients with information about the origins of complaints, treatment options, prognosis, how to prepare for treatment, or how to manage one's health during the recovery phase. Health care professionals educate their patients because knowledge is a known predictor for increased engagement in shared decision making, improved medication and treatment adherence, higher levels of satisfaction, and better outcomes [,].

Unfortunately, patients often only remember a limited amount of the medical information they receive. Many different factors contribute to this. Some of these factors are related to the health care professional, such as using jargon or communicating in a passive way. Other factors are related to the patient, such as age, learning style, and stress []. Another important reason is the fact that most patients are simply not capable of processing large amounts of new medical information in a short amount of time [].

During the last decade, smartphones, tablets, and apps have become commonplace in our society. These innovations offer many new opportunities within health care, such as optimizing the process of patient education. Apps, for example, allow patients to look at medical information as often as they like, at any place, and at any time. The information is comprehensive and different modes of information delivery and interaction are available. Furthermore, push notifications allow health care providers to actively educate patients with timely information, which, in this review, is defined as providing patients with small pieces of information at the time that these are actually relevant to them.

Although interventions like these appear to have much potential in allowing patients to better understand and to remember medical information, an overview of all available evidence on the effectiveness of these technologies has thus far not been published. The objective of this systematic review is to provide an overview of the effectiveness of educating patients by providing timely information using smartphone and tablet apps. With this systematic review, we focused on patients that receive care in a hospital setting rather than in primary care. We have chosen to do so since projects in primary care have already demonstrated effectiveness of electronic health (eHealth) apps, but these primarily focused on chronically ill patients from a population perspective and on telemonitoring services from an intervention perspective.

In this paper, we assess the effects that these interventions have on outcomes, such as patients' knowledge about their illness and treatment options, adherence to medication or instructions, and satisfaction with the information or the care they received.

Search Strategy and Data Sources

To identify relevant studies, we used a two-step strategy. First, we conducted a preliminary search in PubMed to identify key articles, relevant keywords, and Medical Subject Headings (MeSH) terms. The second step was to have the search strategy be peer reviewed by an information specialist from the Radboud academic medical center's medical library. shows the search strategy for the final search. We comprehensively searched the following databases: MEDLINE (Medical Literature Analysis and Retrieval System Online) (Ovid); Embase (Elsevier); CINAHL (Cumulative Index to Nursing and Allied Health Literature) (EBSCO); and Web of Science. Relevant systematic reviews were also assessed for eligible articles. In order to compare the effectiveness of interventions, we preferred to only include randomized controlled trials (RCTs). Since we were unsure about the number and quality of RCTs, our primary search also included cohort and quasi-experimental studies. After assessing the number and quality of RCTs, we decided to only include these in the review. Reporting was done in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [].

Based on the results of our preliminary search, we deliberately limited our search to articles published between January 1, 2015, and November 1, 2019, as the interventions described before this period did not meet the eligibility criteria or could no longer be repeated since the technique was outdated or no longer available. We searched for papers in English and looked at reference lists of included studies to optimize our search.

Eligibility Criteria

RCTs were included if they met a number of eligibility criteria: (1) interventions had a focus on patient education through a smartphone or tablet app, used in a hospital setting; (2) interventions had to use push notifications to actively notify patients about newly available information in the app; and (3) the intervention had to be available for multiple days.

We excluded trials that focused solely on the acceptance or feasibility of technology, content or design of the intervention, availability in app stores, telemedicine (ie, remote care), websites or online platforms, or trials that only described the usage of an SMS. Furthermore, articles focusing on data collection, security, behavior or characteristics of patients, and health care professionals were excluded, as were study protocols. Studies were not excluded on the basis of sociodemographic characteristics of patients, such as age, gender, ethnicity, or any other related characteristic.

Data Selection, Extraction, and Management

The search results from different electronic databases were combined within a single Endnote library, version 8.2 (Clarivate Analytics), and duplicates were removed. Two reviewers (TT and LJ) independently screened titles and abstracts to identify studies that potentially met the inclusion criteria. The full text of these articles was retrieved and read. Two review authors (TT and LJ) independently assessed these articles against the eligibility criteria and extracted the data from the included studies using a structured data extraction form. Disagreements were resolved through discussion and, if necessary, a third reviewer (RBK) was consulted. We extracted information about the patient population, outcomes, interventions, controls, results, and outcome measures.

Assessment of Risk of Bias

Two reviewers (TT and LJ) independently assessed the risk of bias of included RCTs using the Cochrane Collaboration's risk of bias tool []. Judgements concerning the risk of bias for each study were classified as high, some concerns, or low.

Data Synthesis

Included studies were insufficiently homogenous in terms of patient population, outcomes, and type of intervention. The decision not to perform a meta-analysis was made as a consensus by all authors. For any outcome that was investigated in three or more studies, we present a narrative synthesis of results. In order to compare the effects of the different interventions over the different studies, a standardized mean difference (SMD) is reported, including the 95% CI for the effect. SMD is reported only when results are normally distributed and mean and SD are available. The magnitude of the effect is interpreted according to Cohen's guidelines: small (SMD is 0.2 or lower), medium (SMD is between 0.2 and 0.8), or large (SMD is 0.8 or higher) [].

Furthermore, we created a narrative synthesis of overall results per outcome in relation to the duration of the intervention or the frequency with which messages were sent to the patient. Therefore, the duration of the intervention was subdivided into short (<1 month) and long (≥1 month). The frequency of messaging was subdivided into high (>1 message per week) or low (≤1 message per week). The relative effectiveness was calculated by dividing the total number of participants in studies that demonstrated an effect for the outcome by the total number of participants in studies linked to the outcome. Finally, a weighted overall effect was calculated summarizing all outcomes, specified for the duration of the intervention and the frequency of messages.

Overview

Our searches yielded a total of 5497 articles from which 2041 unique articles were derived. After screening titles and abstracts, 1970 records were excluded. A total of 71 articles were assessed for eligibility by full-text screening. A total of 50 articles were excluded after full-text reading because of study type (ie, cohort, quasi-experimental, or other) or because the intervention used did not actually deliver timely education. In total, 21 RCTs were included in the review, including 4106 participants (see ). Sample sizes ranged from 34 participants [] to 650 participants [].

‎
Figure 1. PRISMA (Preferred Reported Items for Systematic Reviews and Meta-Analyses) flowchart. RCT: randomized controlled trial.
View this figure

Included Studies: Study Designs and Populations

Details of the population, type of intervention, outcomes, and mean age of participants are presented in . The details of the interventions used, their duration, phase of the treatment, and frequency of notifying patients are presented in . An overview of all the measurement instruments used per study to assess these outcomes can be found in .

Table 1. Details of the publications, interventions, outcomes, and populations.

Study

Year

Country

Department

Population (n)

Age (years), mean

Outcomes

Timmers []

2019

Netherlands

Orthopedics

Knee replacement (212)

65

Pain, QoL a, physical functioning, satisfaction, and health care consumption

Li []

2019

China

Surgery

Pediatric day-care surgery (127)

4 b

Quality of recovery, satisfaction, and time consumption during follow-up

Alanzi []

2018

Saudi Arabia

Internal medicine

Diabetes mellitus (92)

41 c

Knowledge and self-efficacy

a QoL: quality of life.

b Age of the children who underwent surgery. In the study, their parents (age not mentioned) used the app and provided the data.

c Study only reports that 75% of the participants were 41 years or older.

Table 2. Details and duration of the interventions used, frequency of notifying patients, and treatment phase.

Study

Year

Country

Intervention and control

Duration

Notification frequency

Treatment phase a

Van der Meij []

2018

Netherlands

Personalized eHealth b program through an app for patients undergoing abdominal surgery
Control: Placebo website with standard recovery advice

3 months

Weekly

Post

a Pre: before the start of the treatment; post: after the start of the treatment.

b eHealth: electronic health.

Risk of Bias of Included Studies

All 21 included studies were assessed for risk of bias in the following domains: selection of the reported result, measurement of the outcome, missing outcome data, deviations from intended interventions, and randomization process. The levels of risk-low, some concerns, or high-per study, per domain are presented in . An overview of the percentage of studies related to the level of risk and domain of bias is presented in .

‎
Figure 2. Level of risk of bias, per study, per domain.
View this figure

‎
Figure 3. Risk of bias presented as the percentage of studies with low risk, some concerns, or high risk, scored for the different domains of bias.
View this figure

Outcomes

Overview

Characteristics of the included studies are presented per outcome. Per study, the effect of the intervention on the outcome is described as in favor of the intervention group, in favor of the control group, or no effect.

Satisfaction

Table 3. Details about patients' satisfaction.

Satisfaction with information provided

Satisfaction with care received

a All items were patient reported versus clinician reported.

b Effects were in favor of the intervention group (+) or there were no effects (=). No study had effects in favor of the control group (-).

c SMD: standardized mean difference.

d Outcome only measured in intervention group.

eNo SD available (only average and P value).

f Nonnormal distributed data.

Adherence

Regarding patients' adherence to their medication usage, an effect in favor of the intervention group was demonstrated in all three studies addressing this theme. These studies focused on drug adherence in Parkinson disease [], anticoagulation adherence in patients who suffered from atrial fibrillation [], or myocardial infarction []. With regard to the latter, patients in the intervention group reported lower missed medication doses. However, the same study also reported that there were no differences between groups in results related to the medication adherence questionnaire that was assessed. SMD ranged from small to medium in two studies [,] and could not be calculated for the other study.

Table 4. Details about patients' adherence.

Adherence to instructions

Adherence to medication

a Items were either clinician reported (CR) or patient reported (PR).

b Effects were in favor of the intervention group (+) or there were no effects (=). No study had effects in favor of the control group (-).

c SMD: standardized mean difference.

dNo SD available (only average and P value).

e Nonnormal distributed data.

Quality of Life

Table 5. Details about patients' quality of life.

Van der Meij []

Abdominal surgery (344)

After abdominal surgery

=

SMD could not be calculated d

Guo []

Atrial fibrillation (209)

After starting atrial fibrillation management program

+

SMD could not be calculated d

a All items were patient reported versus clinician reported.

b Effects were in favor of the intervention group (+) or there were no effects (=). No study had effects in favor of the control group (-).

c SMD: standardized mean difference.

dNo SD available (only average and P value).

Clinical Outcomes

Regarding symptoms, an effect in favor of the intervention group was demonstrated in one out of three studies. These results were related to a decrease in symptom severity after using an intervention to train pelvic floor muscles in women who suffer from stress-related urinary incontinence []. No differences between groups were reported in nonmotor symptoms related to Parkinson disease [] and asthma []. SMD ranged from small to large within one study [] and could not be calculated for the other studies.

Table 6. Details about clinical parameters.

Clinical parameters and study, population, and description a

Effect b

SMD c (95% CI)

Physical functioning and pain

Clinical values

Exercise capacity (VO ₂ peak) (CR)

=

0.22 (-0.24 to 0.69)

Symptoms

a Items were either patient reported (PR) or clinician reported (CR).

b Effects were in favor of the intervention group (+) or there were no effects (=). No study had effects in favor of the control group (-).

c SMD: standardized mean difference.

dNo SD available (only average and P value).

e Nonnormal distributed data.

Health Care Economics

Table 7. Details of health care economics of studies.

Study, Population (n), Description a

Effect b

SMD c (95% CI)

Abdominal surgery (344)

Cardiac rehabilitation (80)

Colorectal surgery (97)

Length of stay (CR)

=

0.19 (-0.21 to 0.59)

Knee replacement (212)

Surgery (127)

Time consumed during follow-up (CR)

+

3.58 (3.02 to 4.14)

a Items were either clinician reported (CR) or patient reported (PR).

b Effects were in favor of the intervention group (+), in favor of the control group (-), or there were no effects (=).

c SMD: standardized mean difference.

d Nonnormal distributed data.

Knowledge

Table 8. Details about disease-specific knowledge acquisition.

Guo []

Atrial fibrillation (209)

Knowledge about atrial fibrillation

+

SMD could not be calculated d

a All items were patient reported versus clinician reported.

b Effects were in favor of the intervention group (+) for all studies, versus effects in favor of the control group (-) or no effects (=).

c SMD: standardized mean difference.

d Nonnormal distributed data.

Narrative Synthesis of Overall Results

Overall results demonstrate an average effectiveness of the intervention of 69% (see ). Satisfaction with information, adherence to instructions and medication, clinical outcomes (eg, weight loss or adenoma detection), and knowledge acquisition showed the highest effects (>70%). When taking into account the duration of the intervention, a clear advantage in terms of effect is demonstrated by the interventions that have a duration of less than one month, compared to the interventions that take more than one month: 82% effectiveness versus 69%. A clear difference is noted in the comparison between the frequencies of messaging patients with information as well: an average effectiveness of 78% in the high-frequency group (more than once per week, on average) versus 64% in the low-frequency group (once per week, on average).

Table 9. Synthesis of results: average effectiveness per outcome.

Outcome

Dimension

Number of studies/ population members

Average effectiveness a, %

Duration, %

Frequency, %

Short
(<1 month)

Long
(≥1 month)

High b

Low c

Adherence

Instructions

8/2032

75

72

100

75

N/A d

a Average effectiveness is the weighted average of the population linked to an outcome and the part of the population with a positive effect on the outcome.

b High frequency is >1 message per week, on average.

c Low frequency is ≤1 message per week, on average.

d N/A: not applicable.

Principal Findings

The objective of this systematic review was to evaluate the effectiveness of educating patients by providing timely information using smartphone and tablet apps. In particular, we focused on patients that had undergone treatment in a hospital. A total of 21 studies were identified, most with some concerns in terms of risk of bias. Included studies showed low levels of homogeneity in terms of populations and outcomes. Overall results demonstrate an average effectiveness of the interventions in 69% of the studies. Satisfaction with information, adherence to instructions and medication, improved clinical values (eg, weight loss or adenoma detection), and knowledge acquisition showed the highest effects (>70%). An overall effect of 82% was observed in studies that lasted less than one month. Studies with a higher frequency of messaging (ie, more than once per week) were associated with an average effect of 78%. These results should not only be considered effective from a single outcome point-of-view, but should be, from a more holistic perspective, considered as important components required for effective patient self-management support as well [].

Our results are in line with earlier reviews that focus on the effect of eHealth interventions on multiple outcomes in chronic health conditions [,]. A review by Schoeppe et al reported a positive effect in terms of prevention by focusing on lifestyle changes, such as diet, exercise, and sedentary behavior []. The average duration of the interventions in the Schoeppe et al review was 8 weeks, which is longer than the average duration of interventions in our review. However, this is probably due to the fact that the interventions in the Schoeppe et al review focused on behavioral changes related to lifestyle, whereas studies in our review sometimes lasted only 3 or 4 days, in which the aim is not to change one's lifestyle, but to optimize one's preparation for a one-time event such as a colonoscopy. The usage of frequent notifications has been recognized to encourage greater exposure to the intervention's content without deterring engagement [].

Even though results seem to indicate that interventions of a short duration with a high frequency of notifications are beneficial to the patient, the low level of homogeneity across these studies makes it impossible to extract an optimal structure, duration, or frequency for messaging patients. Such a challenge has also been reported in a 2018 review on education via strategies and structures []. Unfortunately, only a few studies reported detailed information about the content that was provided to patients, its format (eg, text, photo, or video), and the actual timing of the content delivery. This information could have provided additional insights on what makes interventions successful or not.

Our results demonstrate the emerging character of this field of research: the 21 included studies were conducted in 10 different medical departments, covering 15 different types of treatments. Four medical specialties-cardiology, orthopedics, surgery, and gastroenterology-have had more than three studies included. Only interventions related to colonoscopy and knee replacement were studied more than once. The results regarding the number of studies that we excluded from this review also demonstrate that many studies still focus on feasibility, acceptance of technology, and the design and content of apps, rather than on the actual effect of this type of intervention.

Strengths and Limitations

To our knowledge, this review is the first to assess the effectiveness of educating patients in preparation of, during, or after their treatment in the hospital using an app for smartphones or tablets. This review adopted a detailed and comprehensive search strategy, followed by robust screening, data extraction, and risk-of-bias assessment, adhering to the PRISMA guidelines. A total of 21 studies were found eligible for inclusion, seven of them having a low risk level of bias and 14 of them having a level of bias with some concerns according to Cochrane's risk of bias assessment. The relatively large sample sizes allowed us to calculate SMDs and therewith enabled us to compare study outcomes. The observed high level of heterogeneity in terms of outcomes, population, and intervention characteristics, such as interaction models, commercial and noncommercial products, or social media platforms, made it inappropriate to perform a meta-analysis for any outcome.

In this review, we focused on the timely delivery of educational information to overcome patient-perceived information overload. The duration of the interventions within these studies ranged from 3 days to 6 months. In our opinion, this range is another indicator that this type of research is still at an early stage, in which the focus of the trial is really on the intervention itself instead of its long-term effects.

Implications for Practice

The results of our review demonstrate the effective application of smartphone and tablet apps to educate patients with timely information. The effects are visible within various outcomes and across various medical specialties. Medical practices could benefit from these effects by combining two already-existing resources: patient education materials and smartphones and tablets. Patient education is already available on hospital websites, brochures, and through the oral advice of health care professionals. Additionally, more and more patients, as well as their surrounding caretakers, possess a smartphone or tablet. By adding the concept of timing to existing educational materials, one could improve the likelihood that patients receive the right information at the right time. By using the push notification mechanism on smart devices, patients can also be actively made aware of newly available information related to their treatment. Medical practices may choose to either build an app themselves or use already-available commercial products or platforms, social media or otherwise. After the initial development of an app, little or no further adjustments to existing workflows are needed for successful implementation, which is regarded as a crucial factor for successful eHealth implementation []. Of course, some patients may require support during the initial downloading or configuring of the app, but when this effort is compared to the possible benefits in terms of improved outcomes, satisfaction, and health care consumption as described in this review, these efforts appear worthwhile.

Future Research

Delivering timely education to patients through an app for smartphones or tablets has the potential to contribute to the emerging field of patient education research, which may lead to a positive effect on numerous outcomes. Given the novelty of this area of research, more studies need to be performed in order to demonstrate the generalizability of the concept, as well as its long-term effects. In this review, we chose to include only RCTs, since this study design is currently considered to be the gold standard research design to assess the effectiveness of interventions. Yet, we believe it is legitimate to question whether this is the only appropriate study design, as eHealth innovations and research projects could be characterized by what we would like to refer to as "moving objects" and "moving targets." By moving objects, we refer to the interventions themselves, as these may easily be adapted to the real-time needs of patients and health care providers by their inventors. By moving targets, we refer to outcomes that might not have been defined in the original research protocol but arose from the data and insights that were gathered during the study. Changing the intervention itself or adding outcomes during the course of a study is, however, often considered not done, as it could quickly lead to a high risk of bias and a lower overall quality of the research. As a consequence, many interventions might not be studied at all, because from a supplier's or producer's perspective, it feels unnatural not to be able to respond to these real-world demands "just because a study design won't allow you to." This challenge was also reported by two recent studies focusing on eHealth interventions in general [] and, more specifically, in the field of psychiatry [].

We suggest that other study designs, such as pragmatic RCTs, action research, or even real-world data, are considered to be eligible to demonstrate the effectiveness of these interventions. These designs more closely mimic a routine clinical setting from a health care provider's perspective (ie, no double blinding or placebo-controlled setting) and allow the interventions to be altered by the supplier during the course of the study if needed. This could lower some of the existing barriers and may convince more stakeholders to participate in eHealth research.

Conclusions

This review demonstrates that educating patients with timely medical information through their smartphones or tablets improves their levels of knowledge, medication or treatment adherence, satisfaction, and clinical outcomes, as well as having a positive effect on health care economics. These effects are most pronounced in interventions with a short duration (ie, less than a month) and with a high frequency of messaging patients (ie, once per week or more). With the knowledge that patient education is a predictor for improved outcomes and the fact that patients have obvious difficulties processing large amounts of new medical information, we suggest incorporating the delivery of timely information through smartphone and tablet apps within current medical practices.

Acknowledgments

The authors would like to thank Elmie Peters, medical librarian at Radboud University Medical Center (Radboudumc), for her input in shaping and optimizing the search strategy. Furthermore, the authors would like to thank Samuel Credgington for language editing.

Authors' Contributions

All authors were involved in the design of the protocol, development of the search strategy, and selection of data sources. TT and LJ independently screened articles and assessed the risk of bias of the included studies. TT drafted the manuscript. LJ, RBK, and JAMK critically revised the manuscript. All authors read and approved the final manuscript.

Conflicts of Interest

None declared.
‎ ‎
‎

CINAHL: Cumulative Index to Nursing and Allied Health Literature

eHealth: electronic health

MEDLINE: Medical Literature Analysis and Retrieval System Online

MeSH: Medical Subject Headings

PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Radboudumc: Radboud University Medical Center

RCT: randomized controlled trial

SMD: standardized mean difference

Edited by G Eysenbach; submitted 08.12.19; peer-reviewed by L Whitehead, D Reukers, MC Chang, G Dermody, C Mullens; comments to author 15.01.20; revised version received 21.02.20; accepted 22.03.20; published 13.04.20

©Thomas Timmers, Loes Janssen, Rudolf B Kool, Jan AM Kremer. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.04.2020.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

Background: Patient education is a crucial element within health care. It is a known predictor for increased engagement in shared decision making, improved medication and treatment adherence, higher levels of satisfaction, and even better treatment outcomes. Unfortunately, often patients only remember a very limited amount of medical information. An important reason is that most patients are simply not capable of processing large amounts of new medical information in a short time. Apps for smartphones and tablets have the potential to actively educate patients by providing them with timely information through the use of push notifications.

Objective: The objective of this systematic review is to provide an overview of the effects of using smartphone and tablet apps to educate patients with timely education. Within this review, we focused on patients that receive their care in a hospital setting. We assessed the effects of the interventions on outcomes, such as patients' knowledge about their illness and treatment, adherence to treatment instructions and to medication usage, and satisfaction with the care they received.

Methods: A comprehensive search of MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and Web of Science was conducted. Randomized controlled trials (RCTs) published between January 2015 and November 2019 were eligible for inclusion. Two reviewers independently searched and screened articles, assessed study quality and risk of bias, and extracted the data. Due to the heterogeneity of populations, interventions, and outcomes, a meta-analysis was not deemed appropriate. Instead, a narrative synthesis is presented.

Results: A total of 21 RCTs with 4106 participants were included. Compared to usual care, overall effectiveness of the interventions was demonstrated in 69% of the outcomes. Effectiveness increased to 82% when the intervention had a duration shorter than one month and increased to 78% when the intervention provided at least one push notification per week. The interventions showed the highest effects on satisfaction with information, adherence to treatment instructions and to medication usage, clinical outcomes, and knowledge.

Conclusions: This review demonstrates that educating patients with timely medical information through their smartphones or tablets improves their levels of knowledge, medication or treatment adherence, satisfaction, and clinical outcomes, as well as having a positive effect on health care economics. These effects are most pronounced in interventions with a short duration (ie, less than a month) and with a high frequency of messages to patients (ie, once per week or more). With the knowledge that patient education is a predictor for improved outcomes and the fact that patients have obvious difficulties processing large amounts of new medical information, we suggest incorporating the delivery of timely information through smartphone and tablet apps within current medical practices.

J Med Internet Res 2020;22(4):e17342

doi:10.2196/17342

Keywords

Patient education is a crucial element within health care. Health care professionals provide patients with information about the origins of complaints, treatment options, prognosis, how to prepare for treatment, or how to manage one's health during the recovery phase. Health care professionals educate their patients because knowledge is a known predictor for increased engagement in shared decision making, improved medication and treatment adherence, higher levels of satisfaction, and better outcomes [,].

Unfortunately, patients often only remember a limited amount of the medical information they receive. Many different factors contribute to this. Some of these factors are related to the health care professional, such as using jargon or communicating in a passive way. Other factors are related to the patient, such as age, learning style, and stress []. Another important reason is the fact that most patients are simply not capable of processing large amounts of new medical information in a short amount of time [].

During the last decade, smartphones, tablets, and apps have become commonplace in our society. These innovations offer many new opportunities within health care, such as optimizing the process of patient education. Apps, for example, allow patients to look at medical information as often as they like, at any place, and at any time. The information is comprehensive and different modes of information delivery and interaction are available. Furthermore, push notifications allow health care providers to actively educate patients with timely information, which, in this review, is defined as providing patients with small pieces of information at the time that these are actually relevant to them.

Although interventions like these appear to have much potential in allowing patients to better understand and to remember medical information, an overview of all available evidence on the effectiveness of these technologies has thus far not been published. The objective of this systematic review is to provide an overview of the effectiveness of educating patients by providing timely information using smartphone and tablet apps. With this systematic review, we focused on patients that receive care in a hospital setting rather than in primary care. We have chosen to do so since projects in primary care have already demonstrated effectiveness of electronic health (eHealth) apps, but these primarily focused on chronically ill patients from a population perspective and on telemonitoring services from an intervention perspective.

In this paper, we assess the effects that these interventions have on outcomes, such as patients' knowledge about their illness and treatment options, adherence to medication or instructions, and satisfaction with the information or the care they received.

Search Strategy and Data Sources

To identify relevant studies, we used a two-step strategy. First, we conducted a preliminary search in PubMed to identify key articles, relevant keywords, and Medical Subject Headings (MeSH) terms. The second step was to have the search strategy be peer reviewed by an information specialist from the Radboud academic medical center's medical library. shows the search strategy for the final search. We comprehensively searched the following databases: MEDLINE (Medical Literature Analysis and Retrieval System Online) (Ovid); Embase (Elsevier); CINAHL (Cumulative Index to Nursing and Allied Health Literature) (EBSCO); and Web of Science. Relevant systematic reviews were also assessed for eligible articles. In order to compare the effectiveness of interventions, we preferred to only include randomized controlled trials (RCTs). Since we were unsure about the number and quality of RCTs, our primary search also included cohort and quasi-experimental studies. After assessing the number and quality of RCTs, we decided to only include these in the review. Reporting was done in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [].

Based on the results of our preliminary search, we deliberately limited our search to articles published between January 1, 2015, and November 1, 2019, as the interventions described before this period did not meet the eligibility criteria or could no longer be repeated since the technique was outdated or no longer available. We searched for papers in English and looked at reference lists of included studies to optimize our search.

Eligibility Criteria

RCTs were included if they met a number of eligibility criteria: (1) interventions had a focus on patient education through a smartphone or tablet app, used in a hospital setting; (2) interventions had to use push notifications to actively notify patients about newly available information in the app; and (3) the intervention had to be available for multiple days.

We excluded trials that focused solely on the acceptance or feasibility of technology, content or design of the intervention, availability in app stores, telemedicine (ie, remote care), websites or online platforms, or trials that only described the usage of an SMS. Furthermore, articles focusing on data collection, security, behavior or characteristics of patients, and health care professionals were excluded, as were study protocols. Studies were not excluded on the basis of sociodemographic characteristics of patients, such as age, gender, ethnicity, or any other related characteristic.

Data Selection, Extraction, and Management

The search results from different electronic databases were combined within a single Endnote library, version 8.2 (Clarivate Analytics), and duplicates were removed. Two reviewers (TT and LJ) independently screened titles and abstracts to identify studies that potentially met the inclusion criteria. The full text of these articles was retrieved and read. Two review authors (TT and LJ) independently assessed these articles against the eligibility criteria and extracted the data from the included studies using a structured data extraction form. Disagreements were resolved through discussion and, if necessary, a third reviewer (RBK) was consulted. We extracted information about the patient population, outcomes, interventions, controls, results, and outcome measures.

Assessment of Risk of Bias

Two reviewers (TT and LJ) independently assessed the risk of bias of included RCTs using the Cochrane Collaboration's risk of bias tool []. Judgements concerning the risk of bias for each study were classified as high, some concerns, or low.

Data Synthesis

Included studies were insufficiently homogenous in terms of patient population, outcomes, and type of intervention. The decision not to perform a meta-analysis was made as a consensus by all authors. For any outcome that was investigated in three or more studies, we present a narrative synthesis of results. In order to compare the effects of the different interventions over the different studies, a standardized mean difference (SMD) is reported, including the 95% CI for the effect. SMD is reported only when results are normally distributed and mean and SD are available. The magnitude of the effect is interpreted according to Cohen's guidelines: small (SMD is 0.2 or lower), medium (SMD is between 0.2 and 0.8), or large (SMD is 0.8 or higher) [].

Furthermore, we created a narrative synthesis of overall results per outcome in relation to the duration of the intervention or the frequency with which messages were sent to the patient. Therefore, the duration of the intervention was subdivided into short (<1 month) and long (≥1 month). The frequency of messaging was subdivided into high (>1 message per week) or low (≤1 message per week). The relative effectiveness was calculated by dividing the total number of participants in studies that demonstrated an effect for the outcome by the total number of participants in studies linked to the outcome. Finally, a weighted overall effect was calculated summarizing all outcomes, specified for the duration of the intervention and the frequency of messages.

Overview

Our searches yielded a total of 5497 articles from which 2041 unique articles were derived. After screening titles and abstracts, 1970 records were excluded. A total of 71 articles were assessed for eligibility by full-text screening. A total of 50 articles were excluded after full-text reading because of study type (ie, cohort, quasi-experimental, or other) or because the intervention used did not actually deliver timely education. In total, 21 RCTs were included in the review, including 4106 participants (see ). Sample sizes ranged from 34 participants [] to 650 participants [].

‎
Figure 1. PRISMA (Preferred Reported Items for Systematic Reviews and Meta-Analyses) flowchart. RCT: randomized controlled trial.
View this figure

Included Studies: Study Designs and Populations

Details of the population, type of intervention, outcomes, and mean age of participants are presented in . The details of the interventions used, their duration, phase of the treatment, and frequency of notifying patients are presented in . An overview of all the measurement instruments used per study to assess these outcomes can be found in .

Table 1. Details of the publications, interventions, outcomes, and populations.

Study

Year

Country

Department

Population (n)

Age (years), mean

Outcomes

Timmers []

2019

Netherlands

Orthopedics

Knee replacement (212)

65

Pain, QoL a, physical functioning, satisfaction, and health care consumption

Li []

2019

China

Surgery

Pediatric day-care surgery (127)

4 b

Quality of recovery, satisfaction, and time consumption during follow-up

Alanzi []

2018

Saudi Arabia

Internal medicine

Diabetes mellitus (92)

41 c

Knowledge and self-efficacy

a QoL: quality of life.

b Age of the children who underwent surgery. In the study, their parents (age not mentioned) used the app and provided the data.

c Study only reports that 75% of the participants were 41 years or older.

Table 2. Details and duration of the interventions used, frequency of notifying patients, and treatment phase.

Study

Year

Country

Intervention and control

Duration

Notification frequency

Treatment phase a

Van der Meij []

2018

Netherlands

Personalized eHealth b program through an app for patients undergoing abdominal surgery
Control: Placebo website with standard recovery advice

3 months

Weekly

Post

a Pre: before the start of the treatment; post: after the start of the treatment.

b eHealth: electronic health.

Risk of Bias of Included Studies

All 21 included studies were assessed for risk of bias in the following domains: selection of the reported result, measurement of the outcome, missing outcome data, deviations from intended interventions, and randomization process. The levels of risk-low, some concerns, or high-per study, per domain are presented in . An overview of the percentage of studies related to the level of risk and domain of bias is presented in .

‎
Figure 2. Level of risk of bias, per study, per domain.
View this figure

‎
Figure 3. Risk of bias presented as the percentage of studies with low risk, some concerns, or high risk, scored for the different domains of bias.
View this figure

Outcomes

Overview

Characteristics of the included studies are presented per outcome. Per study, the effect of the intervention on the outcome is described as in favor of the intervention group, in favor of the control group, or no effect.

Satisfaction

Table 3. Details about patients' satisfaction.

Satisfaction with information provided

Satisfaction with care received

a All items were patient reported versus clinician reported.

b Effects were in favor of the intervention group (+) or there were no effects (=). No study had effects in favor of the control group (-).

c SMD: standardized mean difference.

d Outcome only measured in intervention group.

eNo SD available (only average and P value).

f Nonnormal distributed data.

Adherence

Regarding patients' adherence to their medication usage, an effect in favor of the intervention group was demonstrated in all three studies addressing this theme. These studies focused on drug adherence in Parkinson disease [], anticoagulation adherence in patients who suffered from atrial fibrillation [], or myocardial infarction []. With regard to the latter, patients in the intervention group reported lower missed medication doses. However, the same study also reported that there were no differences between groups in results related to the medication adherence questionnaire that was assessed. SMD ranged from small to medium in two studies [,] and could not be calculated for the other study.

Table 4. Details about patients' adherence.

Adherence to instructions

Adherence to medication

a Items were either clinician reported (CR) or patient reported (PR).

b Effects were in favor of the intervention group (+) or there were no effects (=). No study had effects in favor of the control group (-).

c SMD: standardized mean difference.

dNo SD available (only average and P value).

e Nonnormal distributed data.

Quality of Life

Table 5. Details about patients' quality of life.

Van der Meij []

Abdominal surgery (344)

After abdominal surgery

=

SMD could not be calculated d

Guo []

Atrial fibrillation (209)

After starting atrial fibrillation management program

+

SMD could not be calculated d

a All items were patient reported versus clinician reported.

b Effects were in favor of the intervention group (+) or there were no effects (=). No study had effects in favor of the control group (-).

c SMD: standardized mean difference.

dNo SD available (only average and P value).

Clinical Outcomes

Regarding symptoms, an effect in favor of the intervention group was demonstrated in one out of three studies. These results were related to a decrease in symptom severity after using an intervention to train pelvic floor muscles in women who suffer from stress-related urinary incontinence []. No differences between groups were reported in nonmotor symptoms related to Parkinson disease [] and asthma []. SMD ranged from small to large within one study [] and could not be calculated for the other studies.

Table 6. Details about clinical parameters.

Clinical parameters and study, population, and description a

Effect b

SMD c (95% CI)

Physical functioning and pain

Clinical values

Exercise capacity (VO ₂ peak) (CR)

=

0.22 (-0.24 to 0.69)

Symptoms

a Items were either patient reported (PR) or clinician reported (CR).

b Effects were in favor of the intervention group (+) or there were no effects (=). No study had effects in favor of the control group (-).

c SMD: standardized mean difference.

dNo SD available (only average and P value).

e Nonnormal distributed data.

Health Care Economics

Table 7. Details of health care economics of studies.

Study, Population (n), Description a

Effect b

SMD c (95% CI)

Abdominal surgery (344)

Cardiac rehabilitation (80)

Colorectal surgery (97)

Length of stay (CR)

=

0.19 (-0.21 to 0.59)

Knee replacement (212)

Surgery (127)

Time consumed during follow-up (CR)

+

3.58 (3.02 to 4.14)

a Items were either clinician reported (CR) or patient reported (PR).

b Effects were in favor of the intervention group (+), in favor of the control group (-), or there were no effects (=).

c SMD: standardized mean difference.

d Nonnormal distributed data.

Knowledge

Table 8. Details about disease-specific knowledge acquisition.

Guo []

Atrial fibrillation (209)

Knowledge about atrial fibrillation

+

SMD could not be calculated d

a All items were patient reported versus clinician reported.

b Effects were in favor of the intervention group (+) for all studies, versus effects in favor of the control group (-) or no effects (=).

c SMD: standardized mean difference.

d Nonnormal distributed data.

Narrative Synthesis of Overall Results

Overall results demonstrate an average effectiveness of the intervention of 69% (see ). Satisfaction with information, adherence to instructions and medication, clinical outcomes (eg, weight loss or adenoma detection), and knowledge acquisition showed the highest effects (>70%). When taking into account the duration of the intervention, a clear advantage in terms of effect is demonstrated by the interventions that have a duration of less than one month, compared to the interventions that take more than one month: 82% effectiveness versus 69%. A clear difference is noted in the comparison between the frequencies of messaging patients with information as well: an average effectiveness of 78% in the high-frequency group (more than once per week, on average) versus 64% in the low-frequency group (once per week, on average).

Table 9. Synthesis of results: average effectiveness per outcome.

Outcome

Dimension

Number of studies/ population members

Average effectiveness a, %

Duration, %

Frequency, %

Short
(<1 month)

Long
(≥1 month)

High b

Low c

Adherence

Instructions

8/2032

75

72

100

75

N/A d

a Average effectiveness is the weighted average of the population linked to an outcome and the part of the population with a positive effect on the outcome.

b High frequency is >1 message per week, on average.

c Low frequency is ≤1 message per week, on average.

d N/A: not applicable.

Principal Findings

The objective of this systematic review was to evaluate the effectiveness of educating patients by providing timely information using smartphone and tablet apps. In particular, we focused on patients that had undergone treatment in a hospital. A total of 21 studies were identified, most with some concerns in terms of risk of bias. Included studies showed low levels of homogeneity in terms of populations and outcomes. Overall results demonstrate an average effectiveness of the interventions in 69% of the studies. Satisfaction with information, adherence to instructions and medication, improved clinical values (eg, weight loss or adenoma detection), and knowledge acquisition showed the highest effects (>70%). An overall effect of 82% was observed in studies that lasted less than one month. Studies with a higher frequency of messaging (ie, more than once per week) were associated with an average effect of 78%. These results should not only be considered effective from a single outcome point-of-view, but should be, from a more holistic perspective, considered as important components required for effective patient self-management support as well [].

Our results are in line with earlier reviews that focus on the effect of eHealth interventions on multiple outcomes in chronic health conditions [,]. A review by Schoeppe et al reported a positive effect in terms of prevention by focusing on lifestyle changes, such as diet, exercise, and sedentary behavior []. The average duration of the interventions in the Schoeppe et al review was 8 weeks, which is longer than the average duration of interventions in our review. However, this is probably due to the fact that the interventions in the Schoeppe et al review focused on behavioral changes related to lifestyle, whereas studies in our review sometimes lasted only 3 or 4 days, in which the aim is not to change one's lifestyle, but to optimize one's preparation for a one-time event such as a colonoscopy. The usage of frequent notifications has been recognized to encourage greater exposure to the intervention's content without deterring engagement [].

Even though results seem to indicate that interventions of a short duration with a high frequency of notifications are beneficial to the patient, the low level of homogeneity across these studies makes it impossible to extract an optimal structure, duration, or frequency for messaging patients. Such a challenge has also been reported in a 2018 review on education via strategies and structures []. Unfortunately, only a few studies reported detailed information about the content that was provided to patients, its format (eg, text, photo, or video), and the actual timing of the content delivery. This information could have provided additional insights on what makes interventions successful or not.

Our results demonstrate the emerging character of this field of research: the 21 included studies were conducted in 10 different medical departments, covering 15 different types of treatments. Four medical specialties-cardiology, orthopedics, surgery, and gastroenterology-have had more than three studies included. Only interventions related to colonoscopy and knee replacement were studied more than once. The results regarding the number of studies that we excluded from this review also demonstrate that many studies still focus on feasibility, acceptance of technology, and the design and content of apps, rather than on the actual effect of this type of intervention.

Strengths and Limitations

To our knowledge, this review is the first to assess the effectiveness of educating patients in preparation of, during, or after their treatment in the hospital using an app for smartphones or tablets. This review adopted a detailed and comprehensive search strategy, followed by robust screening, data extraction, and risk-of-bias assessment, adhering to the PRISMA guidelines. A total of 21 studies were found eligible for inclusion, seven of them having a low risk level of bias and 14 of them having a level of bias with some concerns according to Cochrane's risk of bias assessment. The relatively large sample sizes allowed us to calculate SMDs and therewith enabled us to compare study outcomes. The observed high level of heterogeneity in terms of outcomes, population, and intervention characteristics, such as interaction models, commercial and noncommercial products, or social media platforms, made it inappropriate to perform a meta-analysis for any outcome.

In this review, we focused on the timely delivery of educational information to overcome patient-perceived information overload. The duration of the interventions within these studies ranged from 3 days to 6 months. In our opinion, this range is another indicator that this type of research is still at an early stage, in which the focus of the trial is really on the intervention itself instead of its long-term effects.

Implications for Practice

The results of our review demonstrate the effective application of smartphone and tablet apps to educate patients with timely information. The effects are visible within various outcomes and across various medical specialties. Medical practices could benefit from these effects by combining two already-existing resources: patient education materials and smartphones and tablets. Patient education is already available on hospital websites, brochures, and through the oral advice of health care professionals. Additionally, more and more patients, as well as their surrounding caretakers, possess a smartphone or tablet. By adding the concept of timing to existing educational materials, one could improve the likelihood that patients receive the right information at the right time. By using the push notification mechanism on smart devices, patients can also be actively made aware of newly available information related to their treatment. Medical practices may choose to either build an app themselves or use already-available commercial products or platforms, social media or otherwise. After the initial development of an app, little or no further adjustments to existing workflows are needed for successful implementation, which is regarded as a crucial factor for successful eHealth implementation []. Of course, some patients may require support during the initial downloading or configuring of the app, but when this effort is compared to the possible benefits in terms of improved outcomes, satisfaction, and health care consumption as described in this review, these efforts appear worthwhile.

Future Research

Delivering timely education to patients through an app for smartphones or tablets has the potential to contribute to the emerging field of patient education research, which may lead to a positive effect on numerous outcomes. Given the novelty of this area of research, more studies need to be performed in order to demonstrate the generalizability of the concept, as well as its long-term effects. In this review, we chose to include only RCTs, since this study design is currently considered to be the gold standard research design to assess the effectiveness of interventions. Yet, we believe it is legitimate to question whether this is the only appropriate study design, as eHealth innovations and research projects could be characterized by what we would like to refer to as "moving objects" and "moving targets." By moving objects, we refer to the interventions themselves, as these may easily be adapted to the real-time needs of patients and health care providers by their inventors. By moving targets, we refer to outcomes that might not have been defined in the original research protocol but arose from the data and insights that were gathered during the study. Changing the intervention itself or adding outcomes during the course of a study is, however, often considered not done, as it could quickly lead to a high risk of bias and a lower overall quality of the research. As a consequence, many interventions might not be studied at all, because from a supplier's or producer's perspective, it feels unnatural not to be able to respond to these real-world demands "just because a study design won't allow you to." This challenge was also reported by two recent studies focusing on eHealth interventions in general [] and, more specifically, in the field of psychiatry [].

We suggest that other study designs, such as pragmatic RCTs, action research, or even real-world data, are considered to be eligible to demonstrate the effectiveness of these interventions. These designs more closely mimic a routine clinical setting from a health care provider's perspective (ie, no double blinding or placebo-controlled setting) and allow the interventions to be altered by the supplier during the course of the study if needed. This could lower some of the existing barriers and may convince more stakeholders to participate in eHealth research.

Conclusions

This review demonstrates that educating patients with timely medical information through their smartphones or tablets improves their levels of knowledge, medication or treatment adherence, satisfaction, and clinical outcomes, as well as having a positive effect on health care economics. These effects are most pronounced in interventions with a short duration (ie, less than a month) and with a high frequency of messaging patients (ie, once per week or more). With the knowledge that patient education is a predictor for improved outcomes and the fact that patients have obvious difficulties processing large amounts of new medical information, we suggest incorporating the delivery of timely information through smartphone and tablet apps within current medical practices.

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Educating Patients by Providing Timely Information Using Smartphone and Tablet Apps: Systematic Review

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Abstract

Purpose

For patients with end-stage knee osteoarthritis, joint replacement is a widely used and successful operation to help improve quality-of-life when non-operative measures have failed. For a significant proportion of patients there is a choice between a partial or total knee replacement. Decision aids can help people weigh up the need for and benefits of treatment against possible risks and side-effects. This study explored patients' experiences of deciding to undergo knee replacement surgery to identify information priorities, to inform a knee replacement decision aid.

Methods

Four focus groups were held with 31 patients who were candidates for both partial and total knee replacement surgery. Two focus groups included patients with no prior knee replacement surgery (pre-surgery); two with patients with one knee already replaced and who were candidates for a second surgery on their other knee (post-surgery). Data were analysed using Framework Analysis.

Results

Participants described a process of arriving at 'readiness for surgery' a turning point where the need for treatment outweighed their concerns. Referral and personal factors influenced their decision-making and expectations of surgery in the hope to return to a former self. Those with previous knee surgery offered insights into whether their expectations were met. 'Information for decisions' details the practicality and the optimal timing for the delivery of a knee replacement decision aid. In particular, participants would have valued hearing about the experiences of other patients and seeing detailed pictures of both surgical options. Information priorities were identified to include in a decision aid for knee replacement surgery.

Conclusions

Patients' experiences of surgical decision-making have much in common with the Necessity-Concerns Framework. Whilst originally developed to understand drug treatment decisions and adherence, it provides a useful lens to understand decision-making about surgery. The use of a decision aid could enhance decision-making on knee replacement surgery. Ultimately, patients' understanding of the risks and benefits of both surgical options could be improved and in turn, help informed decision-making. The knee replacement decision aid is perceived as a useful tool to be associated with other detailed information resources as recommended.

Introduction

Osteoarthritis is the most common form of knee arthritis in older people aged between 60 and 80 [ 1]. It is a degenerative condition that can cause joint pain, stiffness, decreased function [ 2] and can impact both the healthcare system and patients quality-of-life [ 3, 4]. At the end-stages of knee osteoarthritis, surgery may be recommended when non-surgical treatments are ineffective. Undergoing knee replacement surgery can relieve pain and improve function [ 5]. In the UK, approximately 100,000 patients per annum undergo knee replacement [ 6] and globally the numbers performed are steadily increasing.

When patients decide to undergo joint replacement, they may face a choice about the type of joint replacement to be used. Patients are eligible for partial (only the damaged half of the knee is replaced) or total knee replacement when the osteoarthritic disease is localised to one compartment of the knee and the anterior cruciate ligament is intact [ 7, 8]. Both interventions are standard care. In the UK, approximately 8% of knee replacements preformed are partial [ 9], although evidence indicates that up to 50% of patients may be eligible [ 10, 11]. This suggests up to 50,000 patients a year in the UK potentially face a decision between partial or total knee replacement.

Compared to total knee replacement, the partial procedure is less invasive and is associated with a faster recovery, reduced risk of blood transfusion, fewer medical complications and lower mortality [ 10, 12, 13]. Both procedures significantly reduce pain and improve function for the majority of patients, but comparative evidence suggests that partial replacement is associated with better functional outcome [ 14, 15]. Yet, long-term studies and registry data show that the revision rate is higher following partial than total knee replacement [ 12, 13, 16, 17].

Close patient involvement in medical decision-making is now strongly recommended in Europe and the US [ 3, 18]. Shared decision-making (SDM) is a collaborative process where clinicians and patients share the best available evidence when facing a decision [ 19, 20], and where patients are supported to consider options, to achieve informed preferences [ 20]. Whilst being ethically desirable, the wider benefits include better health outcomes and improved patient satisfaction by choosing more appropriate options [ 21].

Implementing SDM into routine care is difficult despite health policy interest [ 18]. Mismatches between patients and healthcare professionals have been found in the decision-making process. One study on support needs of patients' choosing between partial and total knee replacement found patients' wanted more information on the risks and benefits [ 22]. However, surgeons were concerned with confusing and overloading patients with information [ 22]. McHugh and Luker [ 23] highlighted the need for standardised evidence-based information on knee replacement options. They found many were not provided with treatment options resulting in people searching independently for information and some receiving conflicting advice. Evidence also suggests that some surgeons may not be in equipoise between the two procedures [ 24]. Considering the different perioperative and post-operative outcomes of partial and total knee replacement, it is likely that these factors will impact patient preference [ 3].

One way to support SDM is through decision aids, such as Option Grids, providing accurate and accessible information [ 25]. Option Grids are one-page evidence-based summaries of available options presented in a table format with frequently asked questions (FAQs) listed as the rows derived from common concerns allowing horizontal comparison between options [ 18]. FAQ answers under each option are based on the latest research evidence [ 18] and have been developed from patient surveys [e.g. 26] and team decisions (e.g. including clinicians, researchers and patient representatives) based on evidence from patient preference literature [e.g. 27]. They are designed to be read in a few minutes [ 18] and used in consultations to prompt dialogue [ 28]. Most importantly, they are developed collaboratively with multi-disciplinary clinical teams and patients [ 28]. Recent research suggests both patients and clinicians find them acceptable and practical and should be considered within routine consultations [ 25, 29, 30]. This study consulted the Option Grid guidelines on developing a decision aid.

Greater depth of understanding patients' concerns/issues may be obtained through qualitative research. The aims of this study were to: (1) explore patients' experiences before surgery including how they came to decide to have knee replacement surgery, and (2) seek their views on a knee replacement surgery decision aid based on the Option Grid format, including their preferences for content and style of the potential decision aid. Overall, we aimed to uncover information needs/priorities patients need to know to share decisions with clinicians to inform a decision aid comparing partial and total knee replacement.

Method

Approval was obtained from the London-Surrey Borders Research Ethics Committee and the NHS Research and Development Department in Oxford.

Participants

Four focus groups were held; two with patients with no prior knee replacement surgery (pre-surgery) and two with patients with one knee already replaced and candidates for knee replacement surgery on their other knee (post-surgery). The number of groups was based on feasibility and gaining insight into pre- and post-surgery experiences. We included pre and post-surgery groups as both groups face the same decision of knee replacement surgery. In particular, the post-surgery groups enabled us to explore their surgery outcomes and review information required post-surgery. All were attending outpatient or pre-operative assessment knee clinics in Oxford. 92 patients were invited: 33 declined, reasons included living a distance away to attend and/or relying on others to bring them, and not feeling comfortable in a group setting; 7 were no longer eligible; 7 were uncontactable; 14 could not attend on the day. 31 patients participated. Table 1 outlines the demographic characteristics.

Recruitment

Purposive sampling was used to recruit participants based on the following criteria: willing and able to give informed consent; aged 18 and above; diagnosed with end-stage knee osteoarthritis; a candidate for either partial or total knee replacement. Participants were excluded if they were a candidate for only total knee replacement or too frail to participate.

Orthopaedic surgeons identified eligible participants by reviewing medical records and introduced SS who explained the study. Interested participants were given the patient information sheet, and contact details exchanged. Focus groups are typically comprised of 5-8 people [ 31]. To allow for drop-out, we over-recruited [ 32, 33] and stopped once 10 participants were in each group.

Focus groups

Focus groups were chosen because they allow for the production of data and insights that may be less accessible without group interaction [ 34] and are used to explore views on interventions [ 35]. They are also a platform to inform participants on topics by including experts as co-facilitators, which may lead to better data quality in more complex research contexts [ 36]. This parallels the growing recognition of integrating researchers, practitioners and patients/consumers in collaborative approaches.

Each focus group lasted up to 2 h, was digitally audio-recorded and held at a research centre. SS, a qualitative researcher and chartered and registered health psychologist was the facilitator. Two orthopaedic surgeons (AA, LB) experienced in both surgical options were the expert co-facilitators and attended two groups each. The surgeons were involved in the presentation of options and when factual information was required or to address queries/concerns. The roles and responsibilities of all group members were outlined at the start of each group and managed by SS who is experienced in conducting focus groups. Consideration of managing the groups was also taken into account in the focus group design. For example, we included background questions to explore the participants understanding of the options before the presentations. We also incorporated an activity-oriented question [ 33, 37] to discuss around the content to include in the decision aid. This encourages deeper elaboration of ideas and focuses attention [ 33]. Table 2 outlines the group members characteristics for each focus group.

An independent review of the questioning routes from an orthopaedic patient liaison group (PLG), including patient representatives and multi-disciplinary healthcare professionals, ensured relevance of the questions from a patient perspective. Appendix 1 provides the pre-surgery questioning route and Appendix 2 the post-surgery questioning route.

Focus group structure: Informed consent was obtained followed by a short welcome which included an explanation of anonymity and confidentiality. There were three parts: 1. General introductions; a brainstorming session on what matters most when deciding to have surgery and what is known about knee surgery. 2. Presentation of the options, use of decision aids in the clinical encounter and discussion. The Option Grid on 'self-management of knee pain, due to arthritis of the knee' [ 38] was recommended by the PLG to use as an example. 3. Group work on FAQ's/information to be included. Participants were split into groups of 2-3 people to discuss the questions and information required for a new decision aid for knee replacement surgery.

Analysis

Framework Analysis [ 39] was used to structure and explore the data. This systematic approach addresses specific applied questions for informing policy and practice [ 39]. NVivo 11 was used to manage the data [ 40].

The audio-recordings were transcribed verbatim and anonymised. SS led the analysis following the analytical process of the five stages: familiarisation, identifying a thematic framework, indexing, charting, mapping and interpretation. JS was involved in reading and initial coding and differences in interpretation were resolved by discussion. The initial analytical framework was based on the questioning route and aims of the study. The final stage can be a visual presentation of the findings [ 41]. The coded nodes from NVivo were added to one sheet of paper to review connections [ 42]. The framework and integration of findings were reviewed by LL and JS. Emerging analysis was also presented regularly to health experience researchers including SR. Final themes were reviewed by all the authors.

Results

Key and related sub-themes are outlined in Table 3. Throughout this section, we refer to boxes that provide further illustrative quotations from the qualitative data, attached in Supplementary material.

Readiness for surgery

Marking time

Participants often detailed lengthy and complicated journeys to deciding to undergo surgery. Visiting the GP was typically the first step and differences in referral to secondary care were experienced. Difficulties 'getting to see the surgeon' as Samuel described, and going through a series of non-surgical interventions including pain medication, physiotherapy and steroid injections before considering surgery were common (Box 1 in Supplementary material). Many became frustrated with their GPs, and other avenues of care were now perceived as what Floyd called 'a delaying tactic' for surgery.

For some, personal circumstances including family ill health prevented them from proceeding with surgery (Box 2 in Supplementary material). Knee osteoarthritis is not life threatening and personal delays experienced suggests timing of surgery was viewed as flexible.

Judging the time-from managing to seeking surgery

Initially, for some, adapting their movement (e.g. using devices to pick-up items) prevented knee symptoms dictating their life. Some found creative ways to accommodate knee problems rather than accept surgery, Ellen described: 'I've been coming downstairs backwards for years.' However, others like Molly feared delaying surgery: 'I want to go ahead...before I kind of get to that point.' There could be an urgency for those with knee replacements to get the second done for concerns of putting 'pressure' (Grace) on the replaced knee and damaging the prosthesis.

Many described becoming housebound, stopping activities, relying on pain medication and feeling unsafe. The frustration of not being able to continue with activities affected their identity. A common concern was feeling 'old before my time' (Doug) and missing out socially was another concern. Surgery provided an opportunity to resume a former self and 'get back to normal' (Rose).

A turning point was often described, 'I was in such pain that really I didn't care about what the implications were' (Lloyd). Risk factors were outweighed by the hope of removing pain, stiffness, swelling, and improving posture, mobility, control and quality-of-life. Surgery offered an opportunity to gain their life and control back (Box 3 in Supplementary material).

For some, judging the time for surgery was assisted by routine questionnaires at surgical appointments. Questionnaires such as the Oxford Knee Score (OKS) [ 43] that rates pain and function were found to be 'incredibly helpful' (Olivia) and prompted participants to proceed with surgery (Box 4 in Supplementary material). However, many queried the OKS noting the score appeared on their post-appointment letter. Once explained, many would have found this information beneficial in assessing their decision and outcome.

Time to reflect-expectations and reality

The post-operative group largely discussed quick and satisfied outcomes from surgery, with some dissatisfaction when participants were unable to return to activities or experienced long recoveries. Most were pleased they were eventually pain free with improved mobility and wanted to move forward with the next surgery on their other knee (Box 5 in Supplementary material).

Post-operatively, most experienced what Tim described as 'a sense of abandonment.' Information was needed on exercises they should be doing post-operatively (and pre-operatively, this was also mentioned by the pre-surgery group) to aid fitness and recovery. Kneeling was a frequent concern (this was also a concern for the pre-surgery group) and what could and should not be done to prevent harming the prosthesis. They also wanted more information on pain management and dealing with medication side-effects such as constipation.

Information for decisions

Benefits, choice and recommendations

The decision aid was received as a useful tool. Participants talked about how it could make them feel 'forearmed' (William) and provide them with a 'starting point' (Celia) for further research, and some reflected how it would help the consultation and act as an information resource (Box 6 in Supplementary material). One participant did not like the proposed tool: 'I'm not the sort that bothers about things like that...but...I can see that it's good for a lot of people' (Stewart).

The presentation and discussion of surgical options made some realise they had not fully understood the options (Box 7 in Supplementary material) and having a decision aid would have made them better informed.

However, whether patients had a choice on which knee replacement caused some debate. Some argued the decision should be down to the surgeon and wanted to know the surgeon's preference. Others felt involved and given a choice, with some reporting that the decision was a surgical one (Box 8 in Supplementary material). However, despite the clinical aspect, some argued they still had a choice by presenting their 'preference' (Eric), and the tool would prepare them on the possible outcomes.

Participants discussed recommendations to the tool. Information presented concisely was essential and 'bullet points' (Tim) were suggested for clarity. Other recommendations included a space for notes.

Several people suggested quantifying the information-'putting a number on it' (Dean)-would help them understand and weigh up the pros and cons of the options.

Others wanted more qualitative information about patient's experiences (Box 9 in Supplementary material). Including quotations from people's stories on one side of paper was recognised to be difficult due to space. Instead, it was suggested that the tool should be part of a wider information resource.

Information timing and needs

The appropriate timing to present the decision aid which would determine the FAQ's and information needs was discussed. Participants imagined themselves in various scenarios and the effect of receiving the tool before seeing the surgeon:

won't you send that out to people who have knee pain...that's not due to arthritis...they may say, "Oh but in there it says I can have a partial knee replacement, and actually you're telling me no" (Gayle)

It was recommended that the tool should be presented at the patient's appointment and the surgeon was best placed for the conversation on surgery options rather than a GP or physiotherapist:

when I first came in, I knew about knee replacements, but I had no idea or no knowledge of what the procedures were (Patrick)

The information needs will now be discussed under the following subheadings. Table 4 provides a summary of the information priorities.

Background to the options

A key aspect to the new decision aid was knowing what surgery involves:

I'd want to know is what is the difference between the two [options]...so I need a definition of what one is as opposed to the other (Eric)

Detailed diagrams/pictures of both options were recommended to be provided on the reverse of the tool.

Outcomes

Information on outcomes included needing to know about the improvements knee replacement could provide:

The first one was outcomes in terms of long-term pain relief...improved mobility (Gayle)

Having information on the prosthesis outcomes was also important (Box 10 in Supplementary material).

Further treatment post-surgery was also questioned:

Do you need...extensive physio post-op? (Anna)

Many stated the importance of having the 'medical complications that can happen' (Patrick) during the operations. They drilled down further highlighting specific risks such as blood clots, nerve damage and infection.

Cosmetic

Cosmetic improvements to their knee were queried. Tim described:

I used to be comfortably over six feet, but I'm not any more...your legs go like a jockey's...you walk around in your best suit...people say, "What's happened to your leg sort of sticking out at a funny angle?"

Many enquired about the length of the scars and their visibility. Katie had a good outcome, but she reflected on meeting others which had caused her worry:

a chap...had two partial knees...one scar was quite okay...white and the other one was zigzag and red...he said "This one was infected."

Having 'less scar tissue' (Doug) made some consider their choice.

Time

Time was a factor in terms of age, length of procedure and recovery. Particularly, older patients questioned their age and undergoing surgery.

Many were surprised that the duration of both procedures was shorter than expected. Some remarked that the length of the procedure would not impact their decision, however for Karl it did: 'The less time you're going to be out the better.'

What is meant by recovery also needs to be clarified:

recovery to do what?...have a shower...drive cars...walk a mile...ride a bike five miles. (Gayle)

For the majority, recovery meant time in hospital and getting back to physical activities.

Discussion

Participants arrived at 'readiness for surgery', a turning point where accommodating their condition gave way to a perceived need for surgery and hopes of improved function as a result. 'Information for decisions' included the tool to be presented by the surgeon, suggested benefits and recommendations, views on choice and important information priorities identified.

In the current study, many experienced difficulties being referred to secondary care and became frustrated with their GP, perceiving other treatments as hindering surgery. McHugh et al. [ 44] found those with worse pain and physical functioning were more likely to have knee replacement surgery. They suggested improvements are required to GP referral processes and guidance on who should have surgery. The ACHE (Arthroplasty Candidacy Help Engine) Tool is a new referral guide using the OKS to identify candidacy for joint replacement [ 4]. User evaluation revealed the tool was viewed positively by patients and GPs to support referral but low response rates are noted [ 4]. In this study, there was support for the ACHE Tool to guide referral decisions and improve patients experience of the referral process.

Readiness for surgery was based on a number of factors including pain with a desire to stop pain medication, improve activity levels, financial concerns and psychosocial improvements. The Necessity-Concerns Framework (NCF) provides a useful lens through which to interpret our findings and its theoretical implications has been suggested to extend to surgery [ 45]. The NCF was developed to understand attitudes to medication and helps explain the relationship between common-sense evaluation and extent of treatment adherence [ 46, 47, 48]. Adherence is influenced by perceptions of the need of treatment (necessity beliefs) and concerns about the adverse effects of that treatment (concern beliefs) [ 47].

In the current study, perceptions of personal need were often masked by normalising and adapting movements (a finding also noted by Hudak et al. [ 49]) preventing a need for treatment. Andersen et al. [ 50] refer to this as 'appraisal delay' when delays are encountered due to symptom interpretations.

Participants traded-off costs and benefits of surgery. Concerns consisted of kneeling issues post-surgery and surgery complications (e.g. infection/recovery). A threshold was hit when other alternatives were exhausted, a finding noted by Suarez-Almazor et al. [ 51] in their study on total knee replacement surgery decision-making. Often experienced was an interaction of biopsychosocial factors [ 52]. Biologically, the knee was becoming uncontrollable/unpredictable and painful. Psychologically, identity was impacted (e.g. feeling old) with a need to gain control back (e.g. regaining mobility) (see also [ 23, 51]). Many participants were missing out on social activities. Smith et al. [ 53] found social isolation through reduced participation and functional capability. In the current study, surgery was eventually associated with stronger perceptions of necessity for treatment and fewer concerns about adverse consequences in the hope of returning to a former self.

Our study supports previous findings that decision aids are acceptable tools [ 25]. Despite variation on surgery choice, most wanted an active role in SDM and the surgeon's recommendation. Similar findings in orthopaedics and cancer care have been found [ 54, 55]. Woolhead et al. [ 56] found participants struggled to make sense of their outcome of knee surgery and often described it in contradictory terms. In the current study, participants felt the decision aid would prepare them for all possible outcomes.

Recommendations included using the back of the page for images and notes. Previous research has supported the use of images on decision aids and has often been used to bridge literacy barriers [ 48, 57]. We recommend visual information should not be limited to literacy level.

Further recommendations to the tool included using bullet points for clarity and a quantitative format which falls into the traditional didactic approach of health information presented by facts and statistics [ 58, 59]. However, the benefits of hearing others experiences were noted in the current study. Patient narratives have been increasingly used to provide health information to patients [ 58, 59, 60]. Narratives are easily processed [ 59, 61] and may also provide important emotional and social information often lacking in health resources [ 59]. We recommend that the knee replacement surgery decision aid will be a useful adjunct to the clinical discussion and needs to be part of a whole that includes patient experience and pre/post-operative information to better support patients in their decision-making. In support, Bennett et al.'s [ 59] study found a combination of supplementing factual information with patient narratives was useful and likely provided better understanding of cancer screening.

The findings support existing literature around the importance on outcomes (e.g. pain reduction/function/flexibility/kneeling/mobility [e.g. 5, 14, 15]), risks (e.g. blood clots/nerve damage/infection/survival of prosthesis/rates of revision [e.g. 12, 13, 14, 15, 16, 17, 62, 63, 64]) and time factors (e.g. age/length of procedure/recovery/time in hospital [e.g. 13, 14, 49, 65, 66, 67, 68, 69, 70]). It further identifies original priorities, such as cosmetic concerns including the appearance of the knee and scar concerns. Research has found satisfaction with limb alignment appears to influence outcome after total knee replacement and is often excluded in outcome measures [ 71] and that high concerns about scarring following elective surgery are irrespective of age, gender, ethnic background or geographic location [ 72]. Expectations need to be addressed between patients and clinicians [ 71, 72] which we envision with the implementation of this decision aid.

Study limitations

Participants were recruited from one hospital and were white and English speaking, which may limit the applicability of the findings. It is important to conduct research with a demographically diverse sample. Having orthopaedic surgeons involved in the focus groups may have deterred some participants. The post-surgery group had more partial than total knee replacement participants. However, the post-surgery group were in the same situation as the pre-surgery group faced with options which many did not experience with their first knee replacement.

Study outcomes and future directions

Our findings highlighted the need for a decision aid focused on partial and total knee replacement. A reference group was initiated, the study findings consulted on, FAQ's determined and information prioritised to include in the decision aid. A systematic review has been completed comparing partial versus total knee replacement to help inform the FAQs [ 73]. The tool will be user-tested and evaluated in the clinical setting.

Conclusions

Patient decision-making for knee replacement surgery could be improved by the use of a decision aid to help people weigh up their concerns against their need for surgery and potential benefits. This would improve patient understanding of the risks and benefits of both surgical options and help patients make an informed decision. It is recommended that information on patient narratives and pre- and post-operative information (e.g. exercises to aid recovery) would supplement the decision-making.

Acknowledgements

We would like to thank all the participants who generously shared their experiences and gave their time to take part in the study. We would also like to thank the Nuffield Orthopaedic Patient Liaison Group for consulting on the study and Professor Glyn Elwyn, Arianna Blaine and Margaret Allyn. We also acknowledge with thanks Consultant Orthopaedic Surgeons Mr William Jackson and Mr Nicholas Bottomley, and the knee surgical teams in Oxford for supporting the study in the recruitment process. Special thanks also to Dr Jenny Hislop from the Health Experiences Research Group, University of Oxford for her expertise and guidance on the qualitative aspects of the study from the initial proposal to review of the analysis.

Funding

The funding has been made available through the Academic Knee Surgery Research Programme that is run by Professor Andrew Price. This group is based at the Botnar Research Centre is part funded by the Oxford NIHR Biomedical Research Centre.

Author information

Affiliations

1. Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Oxford, UK

Stephanie Smith, Abtin Alvand, James Smith, Lee Bayliss, Hannah Wilson & Andrew Price

2. Health Services Research Unit, University of Aberdeen, Aberdeen, UK

Louise Locock

3. Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Louise Locock & Sara Ryan

4. Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia

James Smith

Corresponding author

Correspondence to Stephanie Smith.

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Appendices

Appendix 1: Pre-surgery questioning route plus prompts

Part 1

Opening question

1. Let's start by introducing ourselves. Could you inform the group of your name, a little bit about yourself and fill in the blank with any word that comes to mind, 'My knee is ____________'

Brainstorming session

2. What matters most to you when deciding whether to have knee replacement surgery?
Prompts: Issues or concerns/recovery/activities (e.g. housework, exercise)
Facilitator/co-facilitator to write comments on the board/flip chart

Background questions

3. What do you know about your surgery so far?
Prompts: Information given/risks/benefits/options provided?
4. Imagine yourself one year after surgery. What would have to be different about your life for you to say it was worth it?
Prompt: What are you hoping for?

Part 2

Presentation

* Presentation on the two options
* Show an example of an Option Grid-highlight 6-8 FAQs, evidence-based answers
* How Option Grids are recommended to be used in the medical encounter

Key questions

5. You have all been invited today because you are all possible candidates for either a partial or total knee replacement. What are your thoughts on these two options?
Prompt: Have any of you discussed the two options with your surgeons? [Link in with question 3].
6. What are your thoughts on Option Grids?
Prompts: Do you think they are useful?/likes/dislikes of the Option Grid/level of information required in the Option Grid/how the Option Grid is suggested to be used.
7. How do you feel about being actively involved in the decision of which knee replacement to have?
Prompts: Issues/concerns/empowering?
8. Do you think the surgeon should tell you if they have a preference on which surgery (partial or total) you should have?

Part 3

Group work

9. What information/questions do you think needs to be included in the new Option Grid on partial and total knee replacement surgery options to treat knee osteoarthritis?
Prompts: What are the most important questions that need to be listed?/What information is required to aid decision-making between partial and total knee replacements?
* Comments from brainstorming session to refer to
* Flip chart paper and pens available to participants.
* Groups will come together as a whole to review lists/comments.

Ending questions

10. Of all the things we've discussed today, has anything come up that has surprised you?
11. Is there anything else we haven't discussed yet that you think is important to know about before we develop the Option Grid?
Prompt: Is there anything that you wanted to say but didn't have the chance to?

Appendix 2: Post-surgery questioning route plus prompts

Part 1

Opening Question

1. Let's start by introducing ourselves. Could you inform the group of your name and fill in the blank with any word that comes to mind, 'My knee is ____________'
This could be on your current knee or the knee to be operated on, or both.

Brainstorming session

2. Thinking back to before you had knee replacement surgery, what mattered most to you when deciding whether to have knee replacement surgery?
Prompts: Issues or concerns/recovery/activities (e.g. housework, exercise)
Facilitator/co-facilitator to write comments on the board/flip chart
3. Thinking back is there any information you'd wished you'd know about before your knee replacement surgery?
4. Some of you are shortly undergoing knee replacement surgery on your other knee or this is planned for the near future, have your views changed on what matters to you since having knee replacement surgery?

Background questions

5. What information were you or have you been told about your surgery so far?
Prompts: Information given/risks/benefits/options provided?
6. Thinking back to before you had knee replacement surgery, what were your expectations?
Prompts: What are you hoping for?/Did the reality meet your expectations?
7. What are you hoping for with your upcoming knee replacement surgery or would you be hoping for with future knee replacement surgery?

Part 2

Presentation

* Presentation on the two options
* Show an example of an Option Grid-highlight 6-8 FAQs, evidence-based answers
* How Option Grids are recommended to be used in the medical encounter

Key questions

8. You have all experienced one of these options (partial or total) and some of you may shortly be having knee replacement or in the near future on your other knee, what are your thoughts on these two options?
Prompt: Have any of you discussed the two options with your surgeons? [Link in with question 5].
9. What are your thoughts on Option Grids?
Prompts: Do you think they are useful?/likes/dislikes of the Option Grid/level of information required in the Option Grid/how the Option Grid is suggested to be used.
10. How do you feel about being actively involved in the decision of which knee replacement to have?
Prompts: Issues/concerns/empowering?
11. Do you think the surgeon should tell you if they have a preference on which surgery (partial or total) you should have?

Part 3

Group work

12. What information/questions do you think needs to be included in the new Option Grid on partial and total knee replacement surgery options to treat knee osteoarthritis?
Prompts: What are the most important questions that need to be listed?/What information is required to aid decision-making between partial and total knee replacements?
* Comments from brainstorming session to refer to
* Flip chart paper and pens available to participants.
* Groups will come together as a whole to review lists/comments.

Ending questions

13. Of all the things we've discussed today, has anything come up that has surprised you?
14. Is there anything else we haven't discussed yet that you think is important to know about before we develop the Option Grid?
Prompt: Is there anything that you wanted to say but didn't have the chance to?

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Smith, S., Alvand, A., Locock, L. et al. Partial or total knee replacement? Identifying patients' information needs on knee replacement surgery: a qualitative study to inform a decision aid. Qual Life Res 29, 999-1011 (2020). https://doi.org/10.1007/s11136-019-02381-9
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DOI: https://doi.org/10.1007/s11136-019-02381-9

Keywords

Knee arthroplasty

Partial knee replacement

Total knee replacement

Information needs

Shared decision-making

Decision aid

Option Grid

Framework analysis

Qualitative

# data[].attributes.attachment_link.title
Partial or total knee replacement? Identifying patients' information needs on knee replacement surgery: a qualitative study to inform a decision aid - Quality of Life Research

# data[].attributes.attachment_link.description
Purpose For patients with end-stage knee osteoarthritis, joint replacement is a widely used and successful operation to help improve quality-of-life when non-operative measures have failed. For a significant proportion of patients there is a choice between a partial or total knee replacement.