Measuring Patient Engagement Research Articles

Engagement in Healthcare Decision-Making and Associated Factors among Patients with Chronic Non-Communicable Diseases in Southwest Ethiopia, 2023

BackgroundChronic Non-communicable diseases require lifelong care involving patients, families, a team of their care providers, and significant others. Additionally, engaging patients in their healthcare decision-making is crucial for achieving better clinical outcomes. This study aimed to assess patients' engagement in healthcare decision-making and associated factors among adults with chronic non-communicable diseases in Southwest Ethiopia MethodsA cross-sectional study design was used among 422 participants at the public hospital of Jimma town. Study participants were consecutively recruited from May 01 to June 01, 2023. A structured Patient Activation Measure was used to measure patient engagement in healthcare decision-making. Descriptive statistics and binary logistic regression analysis describe the association between dependent and independent variables. ResultA total of 422 patients with chronic diseases participated in the study yielding a response rate of 99.3%. Slightly greater than one-third (35.8% (95% CI: 31.19, 40.41)) of participants in The study area had a high engagement in healthcare decision-making. Residence (Odd ratio 0.27; 95% confidence interval 0.137-0.534), educational level(Odd ratio 0.168; 95% confidence interval 0.064-0.443), access to information materials(Odd ratio 0.226; 95% confidence interval 0.112-0.458), duration(Odd ratio 3.864; 95% confidence interval 2.083-7.169), health literacy(Odd ratio 1.192; 95% confidence interval 1.111-1.28), and preference for autonomy(Odd ratio 1.097; 95% confidence interval 1.058-1.136) were factors statistically associated with patient engagement in healthcare decision-making. ConclusionOne-third of study participants reported high engagement in healthcare decision-making. Thus, healthcare providers should pay attention to patients with low educational levels, who do not have access to information materials, low health literacy levels, and their preference for autonomy to engage them in their healthcare decision-making.

Factors influencing patient engagement in decision making for catheter ablation of atrial fibrillation: a cross-sectional survey.

Patient engagement in decision making could improve healthcare quality and health outcome, which has been emphasized in atrial fibrillation (AF) management guidelines. However, patients report relatively low level of engagement in decision making for catheter ablation (CA). Therefore, this study aims to explore the influencing factors of AF patient engagement in decision making for CA. A cross-sectional study was conducted. A total of 836 patients were recruited from six tertiary hospitals in Shanghai. Adapted version of the Control Preferences Scale, Chinese version of the All Aspects of Health Literacy Scale, Chinese version of the Facilitation of Patient Involvement Scale and the Atrial Fibrillation Knowledge Questionnaire were used to measure patient engagement in decision making, health literacy, perception of physician facilitation and AF knowledge, respectively. Of the 750 patients who returned valid questionnaires, 20.2% of the patients reported active engagement in decision making, 39.5% reported collaborative engagement, and 40.3% reported passive engagement. Compared with patients perceiving passive engagement, those with collaborative or active engagement were more likely to be female, have higher income, moderate EHRA class (II and III), higher perception of physician facilitation, higher health literacy and higher AF knowledge (P＜0.05 for all). The collaborative engagement group exhibited a shorter AF duration. The degree of patient engagement in CA decision making varied, with most perceiving passive engagement. Patient engagement in decision making was influenced by gender, income, duration of AF, EHRA class, perception of physician facilitation, health literacy and AF knowledge.

A shared journey: evaluating a patient-assessed measure of self-management of chronic conditions in an Australian setting.

Background Patient Assessment of Care in Chronic Conditions (PACIC+), included in some Australian guidelines, has been shown reliable for measuring patient engagement and perception of their care in primary care settings. Various studies have focussed on PACIC+ use in specific conditions. This study aims to expand PACIC+ to measure patient empowerment to self-manage their chronic condition and validate it in the broader Australian primary care population. This study aims to evaluate internal consistency and reliability of PACIC+ and six new supplementary items proposed to assess patient wellbeing and empowerment to self-manage their chronic condition. Methods A repeated-measures correlation design study assessed the expanded PACIC+ over three time-points. Particpants were patients with at least one chronic disease, referred by consultant physician, or recruited by advertisement posters in hospital clinic areas. Results PACIC+ (26-item) had acceptable internal consitency (Cronbach's alpha 0.96). Test-retest reliability (Time-1 and 2, P r (48)=0.43; and New supplementary items: Confidence r (48)=0.54; Understanding r (48)=0.62; Support r (48)=0.43; Overall Health r (48)=0.42; Overall Health Change r (48)=-0.31, P =0.03; and Acute Episodes of Care in 1-month r (48)=0.42, P Conclusions The expanded PACIC+ is an improved psychometric tool providing for the patient's voice in a shared health journey. It is a valid, reliable tool to monitor and measure self-management of chronic conditions in Australian population clinic and primary healthcare settings.

Unpacking patient engagement in remote consultation

PurposeThe purpose of this paper is to examine patient engagement in remote consultation services, an increasingly important issue facing Healthcare Operations Management (HOM) given the significant expansion in this and other forms of telehealth worldwide over the last decade. We use our analysis of the literature to develop a comprehensive framework that incorporates the patient journey, multidimensionality, antecedents and consequences, interventions and improvement options, as well as the cyclic nature of patient engagement. We also propose measures suitable for empirical assessment of different aspects of our framework.Design/methodology/approachWe undertook a comprehensive review of the extant literature using a systematic review approach. We identified and analysed 63 articles published in peer-reviewed scientific journals between 2003 and 2022.FindingsWe conceptualise patient engagement with remote consultation across three key aspects: dimensions, process, and the antecedents and consequences of engagement. We identify nine contextual categories that influence such engagement. We propose several possible metrics for measuring patient engagement during three stages (before service, at/during service and after service) of remote consultation, as well as interventions and possible options for improving patient engagement therein.Originality/valueThe primary contribution of our research is the development of a comprehensive framework for patient engagement in remote consultation that draws on insights from literature in several disciplines. In addition, we have linked the three dimensions of engagement with the clinical process to create a structure for future engagement assessment. Furthermore, we have identified impact factors and outcomes of engagement in remote consultation by understanding which can help to improve levels of adoption, application and satisfaction, and reduce healthcare inequality. Finally, we have adopted a “cyclic” perspective and identified potential interventions that can be combined to further improve patient engagement in remote consultation.

A Scale for Measuring Electronic Patient Engagement Behaviors: Development and Validation.

Advancements in electronic health (eHealth) technology have profoundly impacted patient engagement. This study aimed to develop and validate the Electronic Patient Engagement Behavior (EPEB) scale to measure the conceptual and underlying framework of patient engagement behaviors in an eHealth context. Initial measurement items were generated based on a literature review and qualitative research. Two rounds of surveys, a pilot survey and validation survey, were conducted to evaluate the psychometric properties of the scale. The EPEB scale consists of 15 items in four dimensions: disease information search, physician-patient interaction, social interaction between patients, and disease self-monitoring. In the pilot survey, the exploratory factor analysis revealed a four-factor model, explaining 69.411% of variance. In the validation survey, the Cronbach's α coefficient of each sub-scale was 0.865, 0.904, 0.904, and 0.900 respectively. The Spearman-Brown split coefficient of the scale was 0.963. The results of the cross-sex measurement equivalence test indicate that all fit indices met the measurement criteria. The confirmatory factor analysis indicated second-order 4-factor model fit the data well. The EPEB has a good reliability and validity. The EPEB scale provides a reliable tool for measuring patient engagement behaviors in the eHealth context. The utilization of this scale may yield valuable insights into strategies for enhancing patient engagement and optimizing health outcomes.

Lessons learned in measuring patient engagement in a Canada-wide childhood disability network

BackgroundThe CHILD-BRIGHT Network, a pan-Canadian childhood disability research Network, is dedicated to patient-oriented research, where numerous stakeholders, including patient-partners, researchers, and clinicians are involved at different levels. The Network is committed to continuously improving the level of engagement and partnerships’ impact. Measuring patient engagement is therefore important in reflecting on our practices and enhancing our approaches. We aimed to measure patient engagement longitudinally and explore in greater depth the perceived benefits, barriers and facilitators, and overall satisfaction with patient engagement, from the perspectives of the different stakeholders.MethodsPatient engagement was measured using online surveys. In a longitudinal study design over a 3-years period (2018–2020) the Community-Based Participatory Research (CBPR) questionnaire was used. To enrich our understanding of patient engagement in Year 3, we employed the Public and Patient Engagement Evaluation Tool (PPEET) in a cross-sectional, convergent parallel mixed-method study design. Descriptive statistics and a thematic-based approach were used for data analysis.ResultsThe CBPR questionnaire was completed by n = 167 (61.4% response rate), n = 92 (30.2% response rate), and n = 62 (14.2% response rate) Network members in Years 1, 2, and 3, respectively. Ninety-five (n = 95, 21.8% response rate) members completed the PPEET in Year 3. CBPR findings demonstrate a stable and high satisfaction level with patient engagement over time, where 94%, 86%, and 94% of stakeholders indicated that the project is a “true partnership” in Years 1, 2, and 3, respectively. In Years 2 and 3, we noted an improvement in patient-partners’ comfort level in sharing their views and perspectives (92% and 91% vs. 74%). An increase in critical reflective trust (i.e., allowing for discussing and resolving mistakes) from Year 1 to 3 was found, both from the perspectives of patient-partners (51–65%) and researchers (48–75%). Using the PPEET, patient engagement factors (i.e., communications and supports for participation, ability to share views and perspectives) and impact were highly rated by most (80–100%) respondents. PPEET’s qualitative responses revealed several patient engagement advantages (e.g., increased projects’ relevance, enhanced knowledge translation), barriers (e.g., group homogeneity), facilitators (e.g., optimal communication strategies), and solutions to further improve patient engagement (e.g., provide clarity on goals).ConclusionOur 3-years patient engagement evaluation journey demonstrated a consistent and high level of satisfaction with patient engagement within the Network and identified advantages, barriers, facilitators, and potential solutions. Improvements were observed in members’ comfort in sharing their views and perspectives, along with an increase in critical reflective trust. These findings underscore the Network's commitment to enhancing patient engagement and provide valuable insights for continued improvement and optimization of collaborative efforts.

Patient engagement in multimorbidity: a systematic review of patient-reported outcome measures.

People with multimorbidity are increasingly engaged, enabled, and empowered to take responsibility for managing their health status. The purpose of the study was to systematically review and appraise the psychometric properties of tools measuring patient engagement in adults with multimorbidity and their applicability for use within engagement programs. PubMed, Scopus, Web of Science, and PsycInfo were searched from inception to 1 July 2021. Gray literature was searched using EBSCO host-database "Open dissertation". The reference lists of studies meeting the inclusion criteria were searched to identify additional eligible studies. The screening of the search results and the data extraction were performed independently by two reviewers. The methodological quality of the included studies was evaluated with the COSMIN checklist. Relevant data from all included articles were extracted and summarized in evidence synthesis tables. Twenty articles on eight tools were included. We included tools that measure all four dimensions of patient engagement (i.e., engagement, empowerment, activation, and participation). Their psychometric properties were analyzed separately. Most tools were developed in the last 10 years in Europe or the USA. The comparison of the estimated psychometric properties of the retrieved tools highlighted a significant lack of reliable patient engagement measures for people with multimorbidity. Available measures capture a diversity of constructs and have very limited evidence of psychometric properties that are vital for patient-reported measures, such as invariance, reliability, and responsiveness. This review clarifies how patient engagement, as operationalized in measures purporting to capture this concept, overlaps with, and differs from other related constructs in adults with multimorbidity. The methodological quality of psychometric tools measuring patient engagement in adults with multimorbidity could be improved. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=259968, identifier CRD42021259968.

Assessing the Impact of Primary Care-Led Optimisation Clinics in the Management of Type 2 Diabetes: A Service Redesign Pilot Study.

Background Many individuals diagnosed with type 2 diabetes (T2D) in the London Borough of Waltham Forest, treated solely with oral hypoglycaemic medications (OHAs), exhibit increased levels of glycated haemoglobin (HbA1c). While specialised community and secondary care clinics are at full capacity, a gap exists for dedicated diabetes optimisation services at the primary care level. This study aimed to launch a remote Primary Care Network (PCN)-based clinic during the coronavirus disease 2019 (COVID-19) pandemic to enhance the management of OHAs, introduce motivational interviewing, and incorporate patient empowerment strategies in tandem with a secondary care endocrinologist. The primary objective was to evaluate the impact on HbA1c levels and other metabolic parameters. Concurrently, the "behaviour change model" served to measure patient engagement. Methodology We recruited 43 patients in this study, each undergoing a 30-minute consultation focused on diabetes management. A dedicated administrator ensured patient engagement and a three-month follow-up with repeat metabolic profile testing. Sustained, high-quality care was upheld through bimonthly remote consultations, receiving expertise from an endocrinology consultant. Results Of the pilot's 38 patients managed solely with OHAs, 31 achieved an HbA1c reduction of more than 11 mmol/mol. The overall median reduction for the entire cohort was significant (initially 88 mmol/mol versus 70 mmol/mol, p < 0.0001). Triglyceride levels also saw a notable median decline (1.56 mmol/L down to 1.20 mmol/L, p = 0.0247). Of the 38 completing the pilot, 14 had behavioural stages recorded both initially and at follow-up. Employing motivational interviewing led to significant diabetes-related behavioural changes in 11 of the 14 patients. Conclusions A PCN-based optimisation clinic, augmented with active recall strategies, was a cost-effective method to boost awareness, self-management, and glycaemic control among individuals with T2D. These PCN-led clinics orchestrated by primary care clinicians offer a streamlined solution for achieving treatment benchmarks even amid the challenges of the COVID-19 pandemic.

Conceptualizing and redefining successful patient engagement in patient advisory councils in learning health networks.

Patient engagement has historically referenced engagement in one's healthcare, with more recent definitions expanding patient engagement to encompass patient advocacy work in Learning Health Networks (LHNs). Efforts to conceptualize and define what patient engagement means-and what successful patient engagement means-are, however, lacking and a barrier to meaningful and sustainable patient engagement via patient advisory councils (PACs) across LHNs. Several co-authors (Madeleine Huwe, Becky Woolf, Jennie David) are former ImproveCareNow (ICN) PAC members, and we integrate a narrative review of the extant literature and a case study of our lived experiences as former ICN PAC members. We present nuanced themes of successful patient engagement from our lived experiences on ICN's PAC, with illustrative quotes from other PAC members, and then propose themes and metrics to consider in patient engagement across LHNs. Successful patient engagement in our experiences with ICN's PAC reaches beyond the "levels of engagement" previously described in the literature. We posit that our successful patient/PAC engagement experiences with ICN represent key mechanisms that could be applied across LHNs, including (1) personal growth for PAC members, (2) PAC internal engagement/community, (3) PAC engagement and presence within the LHN, (4) local institutional engagement for those who participate in the LHN, and (5) tangible resources/products from PAC members. Patient engagement in LHNs, like ICN, holds significant power to meaningfully shape and co-produce healthcare systems, and engagement is undervalued and conceptualized dichotomously (eg, engaged or not engaged). Reconceptualizing successful patient/PAC engagement is critical in ongoing efforts to study, support, and understand mechanisms of sustainable and successful patient engagement. Having a modern, multidimensional definition for successful patient engagement in LHNs can support efforts to increase underrepresented voices in PACs, measure and track successful multidimensional patient engagement, and study how successful patient engagement may impact outcomes for patients and LHNs.

Shared decision making among hypertensive clients in public hospitals of West Shoa, central Ethiopia, 2020: Institution based cross sectional study

BackgroundPatient involvement in health care empowers patients to choose treatment and improves the quality of care and treatment outcomes. Despite its purpose, shared decision-making in clinical encounters was not given attention. So, this study aims to assess the level of shared decision-making among hypertensive patients. ObjectiveTo study the level of shared decision-making among hypertensive patients. MethodThe institution-based cross-sectional study method was used to collect data in three randomly selected public hospitals in the West Shoa Zone. A simple random sampling method was used for the selection of study participants. A pretested and structured shared decision-making questionnaire was used to measure patient engagement in decision-making. A descriptive analysis was done to determine the individual patient's level of involvement in shared decision-making. A 95% confidence interval (95% CI) was used to determine the level of shared decision-making. ResultsA total of 406 patients with hypertension participated in the study, yielding a response rate of 96.2%. Totally, 45.3% [CI (43.28–46.75)] of the participants have actively participated in shared decision-making. On the other hand, 53.6% [CI (49.42–56.7)] of participants reported they have been understood by their caregivers, and 52.9% [CI (46.2–58.9)] of the participants reported their caregiver helped them understand all the treatment options. On the other hand, only 121 patients, i.e., 34.7% [CI [28.86–37.8]] of the participants, have jointly chosen one type of treatment with their care provider. ConclusionThe level of involvement in shared decision-making among hypertensive patients is low in the study area compared to the expected standard of shared decision-making. So enhanced patient involvement in health care decisions is important.

Dosage and outcomes in a complex care intervention.

The purpose of our study was to assess the relationship between intervention dosage and hospital utilization outcomes among patients with complex health and social needs enrolled in a care management program. We highlight the importance of measuring patient engagement and intervention dosage in program evaluation. We performed a secondary analysis of data collected between 2014 and 2018 as part of a randomized controlled trial of the Camden Coalition's signature care management intervention. Our analytical sample consisted of 393 patients. We calculated a time-invariant cumulative dosage rank based on the number of hours spent by care teams working with or on behalf of patients and then divided patients into low- and high-dosage groups. We applied propensity score reweighting to compare hospital utilization outcomes between patients in these 2 groups. Compared with patients in the low-dosage group, those in the high-dosage group had a lower readmission rate at 30 (21.6% vs 36.6%; P < .001) and 90 (41.7% vs 55.2%; P = .003) days post enrollment. The difference between the 2 groups at 180 days post enrollment was not statistically significant (57.5% vs 64.9%; P = .150). Our study elucidates a gap in how care management programs for patients with complex health and social needs are evaluated. Although the study shows an association between intervention dosage and care management outcomes, patients' medical complexity and social circumstances are among the factors that can attenuate the dose-response relationship over time.

Patient engagement in decision making and associated factors among outpatients with selected non-communicable chronic diseases in public hospitals of West Shoa, Ethiopia.

Despite the importance of patient engagement in health care decision-making in the care of patients with chronic diseases, there is limited information about it and the factors affecting it in Ethiopia and in the Public Hospitals of West Shoa in particular. Thus, this study was designed to assess the engagement of patients with selected chronic non-communicable diseases in health care decision-making and associated factors in public hospitals of West Shoa Zone, Oromia, Ethiopia. We used an institution -based cross-sectional study design. We used systematic sampling for the selection of study participants from June 7-July 26, 2020. Standardized, pretested, and structured Patient Activation Measure was used to measure patient engagement in healthcare decision-making. We did descriptive analysis to determine the magnitude of patient engagement in health care decision-making. Multivariate logistic regression analysis was used to determine factors associated with patients' engagement in the health care decision-making process. Adjusted odds ratio with a 95% confidence interval was calculated to measure the strength of association. We declared statistical significance at p<0.05. we presented the results in tables and graphs. 406 patients with chronic diseases took part in the study, yielding a response rate of 96.2%. Less than a fifth [19.5% (95% CI: 15.5, 23.6)] of participants in the study area had a high engagement in their health care decision-making. Educational level (college or above) [AOR = 5.2, 95% CI (1.76-15.46)], duration of diagnosis >5 years [AOR = 1.8, 95% CI (1.03-3.2)], health literacy [AOR = 1.15, 95% CI (1.06-1.24)], autonomy preference in decision making [AOR = 1.35, 95% CI (1.03-1.96)] were factors significantly associated with participants' engagement in health care decision making among patients with chronic diseases. A high number of respondents had a low engagement in their health care decision-making. Preference for autonomy in decision making, educational level, health literacy, duration of diagnosis with the disease were factors associated with patient engagement in health care decision making among patients with chronic diseases in the study area. Thus, patients should be empowered to be involved in decision making to increase their engagement in the care.

Measuring patient engagement with HIV care in sub-Saharan Africa: a scoping study.

IntroductionEngagement with HIV care is a multi‐dimensional, dynamic process, critical to maintaining successful treatment outcomes. However, measures of engagement are not standardized nor comprehensive. This undermines our understanding of the scope of challenges with engagement and whether interventions have an impact, complicating patient and programme‐level decision‐making. This study identified and characterized measures of engagement to support more consistent and comprehensive evaluation.MethodsWe conducted a scoping study to systematically categorize measures the health system could use to evaluate engagement with HIV care for those on antiretroviral treatment. Key terms were used to search literature databases (Embase, PsychINFO, Ovid Global‐Health, PubMed, Scopus, CINAHL, Cochrane and the World Health Organization Index Medicus), Google Scholar and stakeholder‐identified manuscripts, ultimately including English evidence published from sub‐Saharan Africa from 2014 to 2021. Measures were extracted, organized, then reviewed with key stakeholders.Results and discussionWe screened 14,885 titles/abstracts, included 118 full‐texts and identified 110 measures of engagement, categorized into three engagement dimensions (“retention,” “adherence” and “active self‐management”), a combination category (“multi‐dimensional engagement”) and “treatment outcomes” category (e.g. viral load as an end‐result reflecting that engagement occurred). Retention reflected status in care, continuity of attendance and visit timing. Adherence was assessed by a variety of measures categorized into primary (prescription not filled) and secondary measures (medication not taken as directed). Active self‐management reflected involvement in care and self‐management. Three overarching use cases were identified: research to make recommendations, routine monitoring for quality improvement and strategic decision‐making and assessment of individual patients.ConclusionsHeterogeneity in conceptualizing engagement with HIV care is reflected by the broad range of measures identified and the lack of consensus on “gold‐standard” indicators. This review organized metrics into five categories based on the dimensions of engagement; further work could identify a standardized, minimum set of measures useful for comprehensive evaluation of engagement for different use cases. In the interim, measurement of engagement could be advanced through the assessment of multiple categories for a more thorough evaluation, conducting sensitivity analyses with commonly used measures for more comparable outputs and using longitudinal measures to evaluate engagement patterns. This could improve research, programme evaluation and nuanced assessment of individual patient engagement in HIV care.

A novel opt-in vs opt-out approach to referral-based treatment of tobacco use in Veterans Affairs (VA) primary care clinics: A provider-level randomized controlled trial protocol

To determine whether an opt-out approach is effective for referral to treatment for tobacco use, we designed a clinical reminder for nurses in a primary care setting that provides a referral for patients who smoke cigarettes. We will use a two-arm, cluster-randomized design to assign nurses at the VA New York Harbor Healthcare System to test which mode of referral (opt-in vs opt-out) is more effective. All patients will be referred to evidence-based treatment for tobacco cessation including counseling from the New York State Quitline, and VetsQuit, a text messaging-based system for tobacco cessation counseling. We will measure patient engagement with the referral both in the short and long term to determine if referral modality had an impact on tobacco cessation treatment. We will also measure nurse engagement with the referral before, during, and after the implementation of the reminder to determine whether an opt-out approach is cost effective at the health system level. At the conclusion of this project, we expect to have developed and tested an opt-out system for increasing tobacco cessation treatment for Veterans in VA primary care and to have a thorough understanding of factors associated with implementation.Trial Registration:Clinicaltrials.govIdentifierNCT03477435

A Novel User Utility Score for Diabetes Management Using Tailored Mobile Coaching: Secondary Analysis of a Randomized Controlled Trial.

BackgroundMobile health applications have been developed to support diabetes self-management, but their effectiveness could depend on patient engagement. Therefore, patient engagement must be examined through multifactorial tailored behavioral interventions from an individual perspective.ObjectiveThis study aims to evaluate the usefulness of a novel user utility score (UUS) as a tool to measure patient engagement by using a mobile health application for diabetes management.MethodsWe conducted a subanalysis of results from a 12-month randomized controlled trial of a tailored mobile coaching (TMC) system among insurance policyholders with type 2 diabetes. UUS was calculated as the sum of the scores for 4 major core components (range 0-8): frequency of self-monitoring blood glucose testing, dietary and exercise records, and message reading rate. We explored the association between UUS for the first 3 months and glycemic control over 12 months. In addition, we investigated the relationship of UUS with blood pressure, lipid profile, and self-report scales assessing diabetes self-management.ResultsWe divided 72 participants into 2 groups based on UUS for the first 3 months: UUS:0-4 (n=38) and UUS:5-8 (n=34). There was a significant between-group difference in glycated hemoglobin test (HbA1c) levels for the 12-months study period (P=.011). The HbA1c decrement at 12 months in the UUS:5-8 group was greater than that of the UUS:0-4 group [–0.92 (SD 1.24%) vs –0.33 (SD 0.80%); P=.049]. After adjusting for confounding factors, UUS was significantly associated with changes in HbA1c at 3, 6, and 12 months; the regression coefficients were –0.113 (SD 0.040; P=.006), –0.143 (SD 0.045; P=.002), and –0.136 (SD 0.052; P=.011), respectively. Change differences in other health outcomes between the 2 groups were not observed throughout a 12-month follow-up.ConclusionsUUS as a measure of patient engagement was associated with changes in HbA1c over the study period of the TMC system and could be used to predict improved glycemic control in diabetes self-management through mobile health interventions.Trial RegistrationClinicalTrial.gov NCT03033407; https://clinicaltrials.gov/ct2/show/NCT03033407

The Malay Version of Patient Activation Measure: An Instrument for Measuring Patient Engagement in Healthcare

Effective diabetes management depends on both pharmacological treatment and patients’ engagement in their own care. PAM is an instrument that measures patients’ ability to self-manage their chronic illnesses and determines patients’ level of activation. The purpose of this study was to develop a translated Malay version of the PAM instrument and subsequently, to conduct a reliability and validity assessment. A cross-sectional study among patients with type 2 diabetes was performed in a teaching public primary care clinic. Forward and backward translation was conducted, followed by pre-testing and cognitive interviewing. Data from 130 patients were analysed using SPSS software to assess the internal consistency and the psychometric properties of the Malay version of PAM instrument. Cronbach’s alpha for all items was 0.87, indicating good internal consistency. Exploratory Factor Analysis (EFA) showed a possibility of a three-factor model, which were labelled as a) confidence in performing preventive behaviors b) feel responsible and in charge of own health, and c) knowledge, ability to communicate and adherence to treatment. All items have a factor loading of higher than 0.4. The Cronbach’s alpha value was 0.85, 0.7 and 0.58 for the first, second and third subscales, respectively. The Malay version of PAM instrument showed a good reliability index and might have multiple subscales. Assessing these subscales are useful for the healthcare team in the evaluation of ‘patient activation’ among patients with diabetes. Efforts will thus be easier when responding to the patients’ needs and facilitating them to become active health managers.

Development and validation of an instrument to measure patient engagement in Hong Kong Special Administrative Region, China.

ObjectiveThe objective of this study was to develop, pilot test, and psychometrically validate a patient engagement questionnaire, called Patient Engagement Index (PEI), in Hong Kong, China.MethodThe method employed was based on a patient engagement framework and literature review and expert panel discussion. A new measure named PEI with 20 items divided into five factors was developed. A pilot study of 40 patients was used to confirm the clarity of PEI. Explored factor analysis was used to confirm the construct validity. Cronbach’s alpha, intercorrelation coefficients (ICCs), and weighted kappa were used to assess the internal consistency reliability and test–retest reliability separately. Rasch model and differential item functioning were also used to further confirm the fit of the instrument.ResultsIn all, 324 participants successfully completed the survey. Based on the evaluation of exploratory factor analysis and theoretically considerations, a four-factor structure comprising 20 items was identified. Rasch analysis also confirmed that the model has a good fit (ranging from 0.662 to 1.294). All domains were considered internally consistent (alpha >0.7). Test–retest showed both ICC (>0.6) and weighted kappa (>0.4) meeting the minimum recommended standard. No ceiling or floor effect was found. Furthermore, Spearman’s correlation coefficient confirmed that PEI had good internal validity.ConclusionPEI was shown to have good reliability and validity. This is a short, quick, and appropriate tool to assess the extent of patient engagement in both clinical and research settings.

Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: a study protocol

BackgroundSmoking is one of the most avoidable health risk factors, and yet the quitting success rates are low. The usage of tailored health messages to support quitting has been proved to increase quitting success rates. Technology can provide convenient means to deliver tailored health messages. Health recommender systems are information-filtering algorithms that can choose the most relevant health-related items—for instance, motivational messages aimed at smoking cessation—for each user based on his or her profile. The goals of this study are to analyze the perceived quality of an mHealth recommender system aimed at smoking cessation, and to assess the level of engagement with the messages delivered to users via this medium.MethodsPatients participating in a smoking cessation program will be provided with a mobile app to receive tailored motivational health messages selected by a health recommender system, based on their profile retrieved from an electronic health record as the initial knowledge source. Patients’ feedback on the messages and their interactions with the app will be analyzed and evaluated following an observational prospective methodology to a) assess the perceived quality of the mobile-based health recommender system and the messages, using the precision and time-to-read metrics and an 18-item questionnaire delivered to all patients who complete the program, and b) measure patient engagement with the mobile-based health recommender system using aggregated data analytic metrics like session frequency and, to determine the individual-level engagement, the rate of read messages for each user. This paper details the implementation and evaluation protocol that will be followed.DiscussionThis study will explore whether a health recommender system algorithm integrated with an electronic health record can predict which tailored motivational health messages patients would prefer and consider to be of a good quality, encouraging them to engage with the system. The outcomes of this study will help future researchers design better tailored motivational message-sending recommender systems for smoking cessation to increase patient engagement, reduce attrition, and, as a result, increase the rates of smoking cessation.Trial registrationThe trial was registered at clinicaltrials.org under the ClinicalTrials.gov identifier NCT03206619 on July 2nd 2017. Retrospectively registered.

Neurocognitive Engagement Therapy

Background and Purpose: Physical rehabilitation therapists are recognizing increasing numbers of older clients presenting with cognitive impairment in the post–acute setting. Therapists working with these patients often feel ill-prepared to address the special challenges of this population and often experience difficulty fully engaging the client in therapy. Decreased engagement in a therapy plan of care may lead to worse functional outcomes and increased debility. The purpose of this study was to examine the efficacy of neurocognitive engagement therapy (NET), a new model for rehabilitation, through a randomized clinical trial. Neurocognitive engagement therapy utilizes evidence-based best practices in dementia care as well as task-specific practice to increase engagement and therapeutic gains among individuals with cognitive impairment in the post–acute setting. Methods: Eighty-five subacute rehabilitation patients participated in the study, with 43 in the active group who received care based on the NET model and 42 in the control group who received traditional post–acute rehabilitation services. The groups were randomly assigned by location of the post–acute admission. The Pittsburgh Rehabilitation Participation Scale was used to measure patient engagement in physical, occupational, and speech therapy. The Modified Barthel Index was used to assess change in overall function. Results and Discussion: Results revealed that Active group participants demonstrated higher mean engagement ratings across all 3 NET therapy types (Ps ≤ .05), with the same mean number of sessions. A Group-by-Time ANOVA revealed a significant interaction effect (P = .05) for pre-/postfunctional gains on the Barthel, indicating more functional gains in the Active group. After accounting for individual differences in engagement, hierarchical multiple linear regression modeling demonstrated that engagement mediated the effects on functional improvement. That is, active patients appeared to have greater functional gains because they had higher engagement. Conclusion: The results suggest that NET is efficacious for cognitively impaired patients. Patients who received NET were more engaged in the process of therapy and had greater functional gains than those who were cognitively impaired and received traditional rehabilitation.

More than just Measurement.

I have reviewed with pleasure the article by Kuluski et al. (2017) who posit that measures of patient experience are required to more effectively guide healthcare reform. While I am generally in support of the original paper, I argue in this commentary that: (1) measuring patient engagement experience should not be done in isolation from broader change management processes; (2) care must be taken to ensure that measures of patient experience are developed with rigor and do not further complicate the already vast performance metrics literature and, (3) any revised set of performance metrics requires ongoing evaluation, to help ensure its optimal value.