Clinician views on how clinical decision support systems can help diagnose asthma in primary care: a qualitative study.

OBJECTIVE: Asthma can be difficult to diagnose in primary care. Clinical decision support systems (CDSS) can assist clinicians when making diagnostic decisions, but the perspectives of intended users need to be incorporated into the software if the CDSS is to be clinically useful. Therefore, we aimed to understand health professional views on the value of an asthma diagnosis CDSS and the barriers and facilitators for use in UK primary care. METHODS: We recruited doctors and nurses working in UK primary care who had experience of assessing respiratory symptoms and diagnosing asthma. Qualitative interviews were used to explore clinicians' experiences of making a diagnosis of asthma and understand views on a CDSS to support asthma diagnosis. Interviews were audio-recorded, transcribed verbatim and analyzed thematically. RESULTS: 16 clinicians (nine doctors, seven nurses) including 13 participants with over 10 years experience, contributed interviews. Participants saw the potential for a CDSS to support asthma diagnosis in primary care by structuring consultations, identifying relevant information from health records, and having visuals to communicate findings to patients. Being evidence based, regularly updated, integrated with software, quick and easy to use were considered important for a CDSS to be successfully implemented. Experienced clinicians were unsure a CDSS would help their routine practice, particularly in straightforward diagnostic scenarios, but thought a CDSS would be useful for trainees or less experienced colleagues. CONCLUSIONS: To be adopted into clinical practice, clinicians were clear that a CDSS must be validated, integrated with existing software, and quick and easy to use.

Patient views on asthma diagnosis and how a clinical decision support system could help: A qualitative study.

INTRODUCTION: Making a diagnosis of asthma can be challenging for clinicians and patients. A clinical decision support system (CDSS) for use in primary care including a patient-facing mode, could change how information is shared between patients and healthcare professionals and improve the diagnostic process. METHODS: Participants diagnosed with asthma within the last 5 years were recruited from general practices across four UK regions. In-depth interviews were used to explore patient experiences relating to their asthma diagnosis and to understand how a CDSS could be used to improve the diagnostic process for patients. Interviews were audio recorded, transcribed verbatim and analysed using a thematic approach. RESULTS: Seventeen participants (12 female) undertook interviews, including 14 individuals and 3 parents of children with asthma. Being diagnosed with asthma was generally considered an uncertain process. Participants felt a lack of consultation time and poor communication affected their understanding of asthma and what to expect. Had the nature of asthma and the steps required to make a diagnosis been explained more clearly, patients felt their understanding and engagement in asthma self-management could have been improved. Participants considered that a CDSS could provide resources to support the diagnostic process, prompt dialogue, aid understanding and support shared decision-making. CONCLUSION: Undergoing an asthma diagnosis was uncertain for patients if their ideas and concerns were not addressed by clinicians and were influenced by a lack of consultation time and limitations in communication. An asthma diagnosis CDSS could provide structure and an interface to prompt dialogue, provide visuals about asthma to aid understanding and encourage patient involvement. PATIENT AND PUBLIC CONTRIBUTION: Prespecified semistructured interview topic guides (young person and adult versions) were developed by the research team and piloted with members of the Asthma UK Centre for Applied Research Patient and Public Involvement (PPI) group. Findings were regularly discussed within the research group and with PPI colleagues to aid the interpretation of data.

Early experience with an opt-in research register - Scottish Health Research Register (SHARE): a multi-method evaluation of participant recruitment performance.

BACKGROUND: Recruiting participants to a clinical study is a resource-intensive process with a high failure rate. The Scottish Health Research Register (SHARE) provides recruitment support service which helps researchers recruit participants by searching patients' Electronic Health Records (EHRs). The current study aims to evaluate the performance of SHARE in participant recruitment. METHODS: Recruitment projects eligible for evaluation were those that were conducted for clinical trials or observational studies and finished before 2020. For analysis of recruitment data, projects with incomplete data were excluded. For each project we calculated, from SHARE records, 1) the fraction of the participants recruited through SHARE as a percentage of the number requested by researchers (percentage fulfilled), 2) the percentage of the potential candidates provided by SHARE to researchers that were actually recruited (percentage provided and recruited), 3) the percentage of the participants recruited through SHARE of all the potentially eligible candidates identified by searching registrants' EHRs (percentage identified and recruited). Research teams of the eligible projects were invited to participate in an anonymised online survey. Two metrics were derived from research teams' responses, including a) the fraction of the recruited over the study target number of participants (percentage fulfilled), and b) the percentage of the participants recruited through SHARE among the candidates received from SHARE (percentage provided and recruited). RESULTS: Forty-four projects were eligible for inclusion. Recruitment data for 24 projects were available (20 excluded because of missingness or incompleteness). Survey invites were sent to all the eligible research teams and received 12 responses. Analysis of recruitment data shows the overall percentage fulfilled was 34.2% (interquartile 13.3-45.1%), the percentage provided and recruited 29.3% (interquartile 20.6-52.4%) and percentage identified and recruited 4.9% (interquartile 2.6-10.2%). Based on the data reported by researchers, percentage fulfilled was 31.7% (interquartile 5.8-59.6%) and percentage provided and recruited was 20.2% (interquartile 8.2-31.0%). CONCLUSIONS: SHARE may be a valuable resource for recruiting participants for some clinical studies. Potential improvements are to expand the registrant base and to incorporate more data generated during patients' different health care encounters into the candidate-searching step.

Examining the effectiveness of telemonitoring with routinely acquired blood pressure data in primary care: challenges in the statistical analysis.

BACKGROUND: Scale-up BP was a quasi-experimental implementation study, following a successful randomised controlled trial of the roll-out of telemonitoring in primary care across Lothian, Scotland. Our primary objective was to assess the effect of telemonitoring on blood pressure (BP) control using routinely collected data. Telemonitored systolic and diastolic BP were compared with surgery BP measurements from patients not using telemonitoring (comparator patients). The statistical analysis and interpretation of findings was challenging due to the broad range of biases potentially influencing the results, including differences in the frequency of readings, 'white coat effect', end digit preference, and missing data. METHODS: Four different statistical methods were employed in order to minimise the impact of these biases on the comparison between telemonitoring and comparator groups. These methods were "standardisation with stratification", "standardisation with matching", "regression adjustment for propensity score" and "random coefficient modelling". The first three methods standardised the groups so that all participants provided exactly two measurements at baseline and 6-12 months follow-up prior to analysis. The fourth analysis used linear mixed modelling based on all available data. RESULTS: The standardisation with stratification analysis showed a significantly lower systolic BP in telemonitoring patients at 6-12 months follow-up (-4.06, 95% CI -6.30 to -1.82, p < 0.001) for patients with systolic BP below 135 at baseline. For the standardisation with matching and regression adjustment for propensity score analyses, systolic BP was significantly lower overall (- 5.96, 95% CI -8.36 to - 3.55 , p < 0.001) and (- 3.73, 95% CI- 5.34 to - 2.13, p < 0.001) respectively, even after assuming that - 5 of the difference was due to 'white coat effect'. For the random coefficient modelling, the improvement in systolic BP was estimated to be -3.37 (95% CI -5.41 to -1.33 , p < 0.001) after 1 year. CONCLUSIONS: The four analyses provide additional evidence for the effectiveness of telemonitoring in controlling BP in routine primary care. The random coefficient analysis is particularly recommended due to its ability to utilise all available data. However, adjusting for the complex array of biases was difficult. Researchers should appreciate the potential for bias in implementation studies and seek to acquire a detailed understanding of the study context in order to design appropriate analytical approaches.

Patients' and Clinicians' Visions of a Future Internet-of-Things System to Support Asthma Self-Management: Mixed Methods Study.

BACKGROUND: Supported self-management for asthma reduces acute attacks and improves control. The internet of things could connect patients to health care providers, community services, and their living environments to provide overarching support for self-management. OBJECTIVE: We aimed to identify patients' and clinicians' preferences for a future internet-of-things system and explore their visions of its potential to support holistic self-management. METHODS: In an exploratory sequential mixed methods study, we recruited patients from volunteer databases and charities' social media. We purposively sampled participants to interview them about their vision of the design and utility of the internet of things as a future strategy for supporting self-management. Respondents who were not invited to participate in the interviews were invited to complete a web-based questionnaire to prioritize the features suggested by the interviewees. Clinicians were recruited from professional networks. Interviews were transcribed and analyzed thematically using PRISMS self-management taxonomy. RESULTS: We interviewed 12 patients and 12 clinicians in the United Kingdom, and 140 patients completed the web-based questionnaires. Patients expressed mostly wanting a system to log their asthma control status automatically; provide real-time advice to help them learn about their asthma, identify and avoid triggers, and adjust their treatment. Peak flow (33/140, 23.6%), environmental (pollen, humidity, air temperature) (33/140, 23.6%), and asthma symptoms (25/140, 17.9%) were the specific data types that patient most wanted. Information about asthma and text or email access to clinical advice provided a feeling of safety for patients. Clinicians wanted automated objective data about the patients' condition that they could access during consultations. The potential reduction in face-to-face consultations was appreciated by clinicians which they perceived could potentially save patients' travel time and health service resources. Lifestyle logs of fitness regimes or weight control were valued by some patients but were of less interest to clinicians. CONCLUSIONS: An automated internet-of-things system that requires minimal input from the user and provides timely advice in line with an asthma action plan agreed by the patient with their clinician was preferred by most respondents. Links to asthma information and the ability to connect with clinicians by text or email were perceived by patients as features that would provide a sense of safety. Further studies are needed to evaluate the usability and effectiveness of internet-of-things systems in routine clinical practice.

Assessing the Implementation and Effectiveness of the Electronic Patient-Reported Outcome Tool for Older Adults With Complex Care Needs: Mixed Methods Study.

BACKGROUND: Goal-oriented care is being adopted to deliver person-centered primary care to older adults with multimorbidity and complex care needs. Although this model holds promise, its implementation remains a challenge. Digital health solutions may enable processes to improve adoption; however, they require evaluation to determine feasibility and impact. OBJECTIVE: This study aims to evaluate the implementation and effectiveness of the electronic Patient-Reported Outcome (ePRO) mobile app and portal system, designed to enable goal-oriented care delivery in interprofessional primary care practices. The research questions driving this study are as follows: Does ePRO improve quality of life and self-management in older adults with complex needs? What mechanisms are likely driving observed outcomes? METHODS: A multimethod, pragmatic randomized controlled trial using a stepped-wedge design and ethnographic case studies was conducted over a 15-month period in 6 comprehensive primary care practices across Ontario with a target enrollment of 176 patients. The 6 practices were randomized into either early (3-month control period; 12-month intervention) or late (6-month control period; 9-month intervention) groups. The primary outcome measure of interest was the Assessment of Quality of Life-4D (AQoL-4D). Data were collected at baseline and at 3 monthly intervals for the duration of the trial. Ethnographic data included observations and interviews with patients and providers at the midpoint and end of the intervention. Outcome data were analyzed using linear models conducted at the individual level, accounting for cluster effects at the practice level, and ethnographic data were analyzed using qualitative description and framework analysis methods. RESULTS: Recruitment challenges resulted in fewer sites and participants than expected; of the 176 target, only 142 (80.6%) patients were identified as eligible to participate because of lower-than-expected provider participation and fewer-than-expected patients willing to participate or perceived as ready to engage in goal-setting. Of the 142 patients approached, 45 (32%) participated. Patients set a variety of goals related to self-management, mental health, social health, and overall well-being. Owing to underpowering, the impact of ePRO on quality of life could not be definitively assessed; however, the intervention group, ePRO plus usual care (mean 15.28, SD 18.60) demonstrated a nonsignificant decrease in quality of life (t24=-1.20; P=.24) when compared with usual care only (mean 21.76, SD 2.17). The ethnographic data reveal a complex implementation process in which the meaningfulness (or coherence) of the technology to individuals' lives and work acted as a key driver of adoption and tool appraisal. CONCLUSIONS: This trial experienced many unexpected and significant implementation challenges related to recruitment and engagement. Future studies could be improved through better alignment of the research methods and intervention to the complex and diverse clinical settings, dynamic goal-oriented care process, and readiness of provider and patient participants. TRIAL REGISTRATION: ClinicalTrials.gov NCT02917954; https://clinicaltrials.gov/ct2/show/NCT02917954.

Exploring the perspectives of primary care providers on use of the electronic Patient Reported Outcomes tool to support goal-oriented care: a qualitative study.

BACKGROUND: Digital health technologies can support primary care delivery, but clinical uptake in primary care is limited. This study explores enablers and barriers experienced by primary care providers when adopting new digital health technologies, using the example of the electronic Patient Reported Outcome (ePRO) tool; a mobile application and web portal designed to support goal-oriented care. To better understand implementation drivers and barriers primary care providers' usage behaviours are compared to their perspectives on ePRO utility and fit to support care for patients with complex care needs. METHODS: This qualitative sub-analysis was part of a larger trial evaluating the use of the ePRO tool in primary care. Qualitative interviews were conducted with providers at the midpoint (i.e. 4.5-6 months after ePRO implementation) and end-point (i.e. 9-12 months after ePRO implementation) of the trial. Interviews explored providers' experiences and perceptions of integrating the tool within their clinical practice. Interview data were analyzed using a hybrid thematic analysis and guided by the Technology Acceptance Model. Data from thirteen providers from three distinct primary care sites were included in the presented study. RESULTS: Three core themes were identified: (1) Perceived usefulness: perceptions of the tool's alignment with providers' typical approach to care, impact and value and fit with existing workflows influenced providers' intention to use the tool and usage behaviour; (2) Behavioural intention: providers had a high or low behavioural intention, and for some, it changed over time; and (3) Improving usage behaviour: enabling external factors and enhancing the tool's perceived ease of use may improve usage behaviour. CONCLUSIONS: Multiple refinements/iterations of the ePRO tool (e.g. enhancing the tool's alignment with provider workflows and functions) may be needed to enhance providers' usage behaviour, perceived usefulness and behavioural intention. Enabling external factors, such as organizational and IT support, are also necessary to increase providers' usage behaviour. Lessons from this study advance knowledge of technology implementation in primary care. TRIAL REGISTRATION: Clinicaltrials.gov Identified NCT02917954. Registered September 2016, https://www.clinicaltrials.gov/ct2/show/study/NCT02917954.

Telemonitoring at scale for hypertension in primary care: An implementation study.

BACKGROUND: While evidence from randomised controlled trials shows that telemonitoring for hypertension is associated with improved blood pressure (BP) control, healthcare systems have been slow to implement it, partly because of inadequate integration with existing clinical practices and electronic records. Neither is it clear if trial findings will be replicated in routine clinical practice at scale. We aimed to explore the feasibility and impact of implementing an integrated telemonitoring system for hypertension into routine primary care. METHODS AND FINDINGS: This was a quasi-experimental implementation study with embedded qualitative process evaluation set in primary care in Lothian, Scotland. We described the overall uptake of telemonitoring and uptake in a subgroup of representative practices, used routinely acquired data for a records-based controlled before-and-after study, and collected qualitative data from staff and patient interviews and practice observation. The main outcome measures were intervention uptake, change in BP, change in clinician appointment use, and participants' views on features that facilitated or impeded uptake of the intervention. Seventy-five primary care practices enrolled 3,200 patients with established hypertension. In an evaluation subgroup of 8 practices (905 patients of whom 427 [47%] were female and with median age of 64 years [IQR 56-70, range 22-89] and median Scottish Index of Multiple Deprivation 2012 decile of 8 [IQR 6-10]), mean systolic BP fell by 6.55 mm Hg (SD 15.17), and mean diastolic BP by 4.23 mm Hg (SD 8.68). Compared with the previous year, participating patients made 19% fewer face-to-face appointments, compared with 11% fewer in patients with hypertension who were not telemonitoring. Total consultation time for participants fell by 15.4 minutes (SD 68.4), compared with 5.5 minutes (SD 84.4) in non-telemonitored patients. The convenience of remote collection of BP readings and integration of these readings into routine clinical care was crucial to the success of the implementation. Limitations include the fact that practices and patient participants were self-selected, and younger and more affluent than non-participating patients, and the possibility that regression to the mean may have contributed to the reduction in BP. Routinely acquired data are limited in terms of completeness and accuracy. CONCLUSIONS: Telemonitoring for hypertension can be implemented into routine primary care at scale with little impact on clinician workload and results in reductions in BP similar to those in large UK trials. Integrating the telemonitoring readings into routine data handling was crucial to the success of this initiative.

Promoting healthy teenage behaviour across three European countries through the use of a novel smartphone technology platform, PEGASO fit for future: study protocol of a quasi-experimental, controlled, multi-Centre trial.

BACKGROUND: Behaviour change interventions targeting physical activity, diet, sleep and sedentary behaviour of teenagers show promise when delivered through smartphones. However, to date there is no evidence of effectiveness of multicomponent smartphone-based interventions. Utilising a user-centred design approach, we developed a theory-based, multi-dimensional system, PEGASO Fit For Future (PEGASO F4F), which exploits sophisticated game mechanics involving smartphone applications, a smartphone game and activity sensors to motivate teenagers to take an active role in adopting and maintaining a healthy lifestyle. This paper describes the study protocol to assess the feasibility, usability and effectiveness (knowledge/awareness and behavioural change in lifestyle) of the PEGASO system. METHODS: We are conducting a quasi-experimental controlled cluster trial in 4 sites in Spain, Italy, and UK (England, Scotland) over 6 months. We plan to recruit 525, in a 2:1 basis, teenagers aged 13-16 years from secondary schools. The intervention group is provided with the PEGASO system whereas the comparison group continues their usual educational routine. Outcomes include feasibility, acceptance, and usability of the PEGASO system as well as between and within group changes in motivation, self-reported diet, physical activity, sedentary and sleeping behaviour, anthropometric measures and knowledge about a healthy lifestyle. DISCUSSION: PEGASO F4F will provide evidence into the cross-cultural similarities and differences in the feasibility, acceptability and usability of a multi-dimensional smartphone based behaviour change intervention for teenagers. The study will explore facilitating factors, challenges and barriers of engaging teenagers to adapt and maintain a healthy lifestyle when using smartphone technology. Positive results from this ICT based multi component intervention may have significant implications both at clinical level, improving teenagers health and at public health level since it can present an influential tool against the development of chronic disease during adulthood. TRIAL REGISTRATION: https://clinicaltrials.gov Registration number: NCT02930148, registered 4 October 2016.

Implementing telemonitoring in primary care: learning from a large qualitative dataset gathered during a series of studies.

BACKGROUND: Telemonitoring for long term conditions such as hypertension and diabetes has not been widely adopted despite evidence of efficacy in trials and policy support. The Telescot programme comprised a series of seven trials and observational studies of telemonitoring for long term conditions in primary care, all with an explanatory qualitative component which had been analysed and published separately. There were changes to the models of care within and between studies and combining datasets would provide a longitudinal view of the evolution of primary care based telemonitoring services that was not available in the individual studies, as well as allowing comparison across the different conditions monitored. We aimed to explore what drove changes to the way telemonitoring was implemented, compare experience of telemonitoring across the range of long term conditions, and identify what issues, in the experience of the participants, need to be considered in implementing new telemonitoring systems. METHOD: Synthesis and thematic reanalysis of transcribed qualitative interview and focus group data from the Telescot programme adopting an interpretive description approach. All transcribed and coded text was re-read and data relating to the experience of the telemonitoring services, perceptions of future use and strategies for implementation were recoded into one consistent system. This was analysed thematically. RESULTS: The combined dataset contained transcribed qualitative interview and focus group data from 181 patients and 109 professionals. Four major themes were identified, using data, empowering patients, adjusting the model of care and system design. CONCLUSION: Telemonitoring was valued by patients who found it empowering and convenient. This, combined with initial professional concern that increased surveillance may create dependency led to the development of a more patient led service. However, despite a number of initial concerns being addressed as the service evolved, primary care professionals identified a number of barriers to widespread routine adoption of telemonitoring, many of which could be addressed by improved system design.

Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data.

BACKGROUND: Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of chronic obstructive pulmonary disease (COPD) exacerbations, with a view to instituting timely treatment. However, algorithms to identify exacerbations result in frequent false-positive results and increased workload. Machine learning, when applied to predictive modelling, can determine patterns of risk factors useful for improving prediction quality. OBJECTIVE: Our objectives were to (1) establish whether machine learning techniques applied to telemonitoring datasets improve prediction of hospital admissions and decisions to start corticosteroids, and (2) determine whether the addition of weather data further improves such predictions. METHODS: We used daily symptoms, physiological measures, and medication data, with baseline demography, COPD severity, quality of life, and hospital admissions from a pilot and large randomized controlled trial of telemonitoring in COPD. We linked weather data from the United Kingdom meteorological service. We used feature selection and extraction techniques for time series to construct up to 153 predictive patterns (features) from symptom, medication, and physiological measurements. We used the resulting variables to construct predictive models fitted to training sets of patients and compared them with common symptom-counting algorithms. RESULTS: We had a mean 363 days of telemonitoring data from 135 patients. The two most practical traditional score-counting algorithms, restricted to cases with complete data, resulted in area under the receiver operating characteristic curve (AUC) estimates of 0.60 (95% CI 0.51-0.69) and 0.58 (95% CI 0.50-0.67) for predicting admissions based on a single day's readings. However, in a real-world scenario allowing for missing data, with greater numbers of patient daily data and hospitalizations (N=57,150, N+=55, respectively), the performance of all the traditional algorithms fell, including those based on 2 days' data. One of the most frequently used algorithms performed no better than chance. All considered machine learning models demonstrated significant improvements; the best machine learning algorithm based on 57,150 episodes resulted in an aggregated AUC of 0.74 (95% CI 0.67-0.80). Adding weather data measurements did not improve the predictive performance of the best model (AUC 0.74, 95% CI 0.69-0.79). To achieve an 80% true-positive rate (sensitivity), the traditional algorithms were associated with an 80% false-positive rate: our algorithm halved this rate to approximately 40% (specificity approximately 60%). The machine learning algorithm was moderately superior to the best symptom-counting algorithm (AUC 0.77, 95% CI 0.74-0.79 vs AUC 0.66, 95% CI 0.63-0.68) at predicting the need for corticosteroids. CONCLUSIONS: Early detection and management of COPD remains an important goal given its huge personal and economic costs. Machine learning approaches, which can be tailored to an individual's baseline profile and can learn from experience of the individual patient, are superior to existing predictive algorithms and show promise in achieving this goal. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number ISRCTN96634935; http://www.isrctn.com/ISRCTN96634935 (Archived by WebCite at http://www.webcitation.org/722YkuhAz).

Self-monitoring of blood pressure in hypertension: A systematic review and individual patient data meta-analysis.

BACKGROUND: Self-monitoring of blood pressure (BP) appears to reduce BP in hypertension but important questions remain regarding effective implementation and which groups may benefit most. This individual patient data (IPD) meta-analysis was performed to better understand the effectiveness of BP self-monitoring to lower BP and control hypertension. METHODS AND FINDINGS: Medline, Embase, and the Cochrane Library were searched for randomised trials comparing self-monitoring to no self-monitoring in hypertensive patients (June 2016). Two reviewers independently assessed articles for eligibility and the authors of eligible trials were approached requesting IPD. Of 2,846 articles in the initial search, 36 were eligible. IPD were provided from 25 trials, including 1 unpublished study. Data for the primary outcomes-change in mean clinic or ambulatory BP and proportion controlled below target at 12 months-were available from 15/19 possible studies (7,138/8,292 [86%] of randomised participants). Overall, self-monitoring was associated with reduced clinic systolic blood pressure (sBP) compared to usual care at 12 months (-3.2 mmHg, [95% CI -4.9, -1.6 mmHg]). However, this effect was strongly influenced by the intensity of co-intervention ranging from no effect with self-monitoring alone (-1.0 mmHg [-3.3, 1.2]), to a 6.1 mmHg (-9.0, -3.2) reduction when monitoring was combined with intensive support. Self-monitoring was most effective in those with fewer antihypertensive medications and higher baseline sBP up to 170 mmHg. No differences in efficacy were seen by sex or by most comorbidities. Ambulatory BP data at 12 months were available from 4 trials (1,478 patients), which assessed self-monitoring with little or no co-intervention. There was no association between self-monitoring and either lower clinic or ambulatory sBP in this group (clinic -0.2 mmHg [-2.2, 1.8]; ambulatory 1.1 mmHg [-0.3, 2.5]). Results for diastolic blood pressure (dBP) were similar. The main limitation of this work was that significant heterogeneity remained. This was at least in part due to different inclusion criteria, self-monitoring regimes, and target BPs in included studies. CONCLUSIONS: Self-monitoring alone is not associated with lower BP or better control, but in conjunction with co-interventions (including systematic medication titration by doctors, pharmacists, or patients; education; or lifestyle counselling) leads to clinically significant BP reduction which persists for at least 12 months. The implementation of self-monitoring in hypertension should be accompanied by such co-interventions.

Telehealth Interventions to Support Self-Management of Long-Term Conditions: A Systematic Metareview of Diabetes, Heart Failure, Asthma, Chronic Obstructive Pulmonary Disease, and Cancer.

BACKGROUND: Self-management support is one mechanism by which telehealth interventions have been proposed to facilitate management of long-term conditions. OBJECTIVE: The objectives of this metareview were to (1) assess the impact of telehealth interventions to support self-management on disease control and health care utilization, and (2) identify components of telehealth support and their impact on disease control and the process of self-management. Our goal was to synthesise evidence for telehealth-supported self-management of diabetes (types 1 and 2), heart failure, asthma, chronic obstructive pulmonary disease (COPD) and cancer to identify components of effective self-management support. METHODS: We performed a metareview (a systematic review of systematic reviews) of randomized controlled trials (RCTs) of telehealth interventions to support self-management in 6 exemplar long-term conditions. We searched 7 databases for reviews published from January 2000 to May 2016 and screened identified studies against eligibility criteria. We weighted reviews by quality (revised A Measurement Tool to Assess Systematic Reviews), size, and relevance. We then combined our results in a narrative synthesis and using harvest plots. RESULTS: We included 53 systematic reviews, comprising 232 unique RCTs. Reviews concerned diabetes (type 1: n=6; type 2, n=11; mixed, n=19), heart failure (n=9), asthma (n=8), COPD (n=8), and cancer (n=3). Findings varied between and within disease areas. The highest-weighted reviews showed that blood glucose telemonitoring with feedback and some educational and lifestyle interventions improved glycemic control in type 2, but not type 1, diabetes, and that telemonitoring and telephone interventions reduced mortality and hospital admissions in heart failure, but these findings were not consistent in all reviews. Results for the other conditions were mixed, although no reviews showed evidence of harm. Analysis of the mediating role of self-management, and of components of successful interventions, was limited and inconclusive. More intensive and multifaceted interventions were associated with greater improvements in diabetes, heart failure, and asthma. CONCLUSIONS: While telehealth-mediated self-management was not consistently superior to usual care, none of the reviews reported any negative effects, suggesting that telehealth is a safe option for delivery of self-management support, particularly in conditions such as heart failure and type 2 diabetes, where the evidence base is more developed. Larger-scale trials of telehealth-supported self-management, based on explicit self-management theory, are needed before the extent to which telehealth technologies may be harnessed to support self-management can be established.

Correction: Supported Telemonitoring and Glycemic Control in People with Type 2 Diabetes: The Telescot Diabetes Pragmatic Multicenter Randomized Controlled Trial.

[This corrects the article DOI: 10.1371/journal.pmed.1002098.].

Supported Telemonitoring and Glycemic Control in People with Type 2 Diabetes: The Telescot Diabetes Pragmatic Multicenter Randomized Controlled Trial.

BACKGROUND: Self-monitoring of blood glucose among people with type 2 diabetes not treated with insulin does not appear to be effective in improving glycemic control. We investigated whether health professional review of telemetrically transmitted self-monitored glucose results in improved glycemic control in people with poorly controlled type 2 diabetes. METHODS AND FINDINGS: We performed a randomized, parallel, investigator-blind controlled trial with centralized randomization in family practices in four regions of the United Kingdom among 321 people with type 2 diabetes and glycated hemoglobin (HbA1c) >58 mmol/mol. The supported telemonitoring intervention involved self-measurement and transmission to a secure website of twice-weekly morning and evening glucose for review by family practice clinicians who were not blinded to allocation group. The control group received usual care, with at least annual review and more frequent reviews for people with poor glycemic or blood pressure control. HbA1c assessed at 9 mo was the primary outcome. Intention-to-treat analyses were performed. 160 people were randomized to the intervention group and 161 to the usual care group between June 6, 2011, and July 19, 2013. HbA1c data at follow-up were available for 146 people in the intervention group and 139 people in the control group. The mean (SD) HbA1c at follow-up was 63.0 (15.5) mmol/mol in the intervention group and 67.8 (14.7) mmol/mol in the usual care group. For primary analysis, adjusted mean HbA1c was 5.60 mmol/mol / 0.51% lower (95% CI 2.38 to 8.81 mmol/mol/ 95% CI 0.22% to 0.81%, p = 0·0007). For secondary analyses, adjusted mean ambulatory systolic blood pressure was 3.06 mmHg lower (95% CI 0.56-5.56 mmHg, p = 0.017) and mean ambulatory diastolic blood pressure was 2.17 mmHg lower (95% CI 0.62-3.72, p = 0.006) among people in the intervention group when compared with usual care after adjustment for baseline differences and minimization strata. No significant differences were identified between groups in weight, treatment pattern, adherence to medication, or quality of life in secondary analyses. There were few adverse events and these were equally distributed between the intervention and control groups. In secondary analysis, there was a greater number of telephone calls between practice nurses and patients in the intervention compared with control group (rate ratio 7.50 (95% CI 4.45-12.65, p < 0.0001) but no other significant differences between groups in use of health services were identified between groups. Key limitations include potential lack of representativeness of trial participants, inability to blind participants and health professionals, and uncertainty about the mechanism, the duration of the effect, and the optimal length of the intervention. CONCLUSIONS: Supported telemonitoring resulted in clinically important improvements in control of glycaemia in patients with type 2 diabetes in family practice. Current Controlled Trials, registration number ISRCTN71674628. TRIAL REGISTRATION: Current Controlled Trials ISRCTN 71674628.

Interventions to modify physical activity in patients with COPD: a systematic review.

The broad range of interventions to increase physical activity (PA) in patients with chronic obstructive pulmonary disease (COPD) has not been systematically assessed. We aimed to perform a systematic review of the interventional studies that have assessed PA as an outcome in patients with COPD.A systematic search in five different databases (Medline, Embase, PsycINFO, CINAHL and Web of Science) was performed in March 2015. Two independent reviewers analysed the studies against the inclusion criteria (COPD defined by spirometry; prospective, randomised/nonrandomised studies, cohort and experimental studies with interventions using PA as an outcome), extracted the data and assessed the quality of evidence.60 studies were included. Seven intervention groups were identified. PA counselling increased PA levels in COPD, especially when combined with coaching. 13 studies showed positive effects of pulmonary rehabilitation (PR) on PA, while seven studies showed no changes. All three PR programmes >12 weeks in duration increased PA. Overall, the quality of evidence was graded as very low.Interventions focusing specifically on increasing PA, and longer PR programmes, may have greater impacts on PA in COPD. Well-designed clinical trials with objective assessment of PA in COPD patients are needed.

The epidemiology, healthcare and societal burden and costs of asthma in the UK and its member nations: analyses of standalone and linked national databases.

BACKGROUND: There are a lack of reliable data on the epidemiology and associated burden and costs of asthma. We sought to provide the first UK-wide estimates of the epidemiology, healthcare utilisation and costs of asthma. METHODS: We obtained and analysed asthma-relevant data from 27 datasets: these comprised national health surveys for 2010-11, and routine administrative, health and social care datasets for 2011-12; 2011-12 costs were estimated in pounds sterling using economic modelling. RESULTS: The prevalence of asthma depended on the definition and data source used. The UK lifetime prevalence of patient-reported symptoms suggestive of asthma was 29.5 % (95 % CI, 27.7-31.3; n = 18.5 million (m) people) and 15.6 % (14.3-16.9, n = 9.8 m) for patient-reported clinician-diagnosed asthma. The annual prevalence of patient-reported clinician-diagnosed-and-treated asthma was 9.6 % (8.9-10.3, n = 6.0 m) and of clinician-reported, diagnosed-and-treated asthma 5.7 % (5.7-5.7; n = 3.6 m). Asthma resulted in at least 6.3 m primary care consultations, 93,000 hospital in-patient episodes, 1800 intensive-care unit episodes and 36,800 disability living allowance claims. The costs of asthma were estimated at least £1.1 billion: 74 % of these costs were for provision of primary care services (60 % prescribing, 14 % consultations), 13 % for disability claims, and 12 % for hospital care. There were 1160 asthma deaths. CONCLUSIONS: Asthma is very common and is responsible for considerable morbidity, healthcare utilisation and financial costs to the UK public sector. Greater policy focus on primary care provision is needed to reduce the risk of asthma exacerbations, hospitalisations and deaths, and reduce costs.

Involving patients in clinical research: the Telescot Patient Panel.

BACKGROUND: To date, patient involvement in the development of clinical research work has been limited. In 2011, the Telescot research team commenced work on a feasibility trial to investigate home telemonitoring of blood pressure for people who have experienced stroke or transient ischaemic attack (TIA). The team decided to involve patients in the development of the research. OBJECTIVES: To improve research design through patient involvement. METHOD OF PATIENT INVOLVEMENT: A modified form of the 'Scrutiny Panel' approach was used to involve people who had stroke in the research project. RESULTS: The Patient Panel supported the research in three key ways: it informed patient communication; it presented patient perspectives on the applicability and usability of the intervention; and it guided the development of the qualitative study. DISCUSSION: The initiative was considered a positive experience for all. However, challenges were identified in terms of the time and cost implications of undertaking patient involvement. IMPLICATION FOR RESEARCH PRACTICE: Importance is attached to adequate project planning and development, partnership working with community-based organizations and the necessity for clear role delineation between patients and professionals to enable effective collaborative working. CONCLUSIONS: The Telescot Patient Panel was beneficial in supporting the development of the feasibility trial. The Panel approach was considered transferable to other clinical research contexts.