To (1) examine the burden of multiple chronic conditions (MCC) in an urban health system, and (2) propose a methodology to identify subpopulations of interest based on diagnosis groups and costs.
Retrospective cross-sectional study.
Mount Sinai Health System, set in all five boroughs of New York City, USA.
192 085 adult (18+) plan members of capitated Medicaid contracts between the Healthfirst managed care organisation and the Mount Sinai Health System in the years 2012 to 2014.
We classified adults as having 0, 1, 2, 3, 4 or 5+ chronic conditions from a list of 69 chronic conditions. After summarising the demographics, geography and prevalence of MCC within this population, we then described groups of patients (segments) using a novel methodology: we combinatorially defined 18 768 potential segments of patients by a pair of chronic conditions, a sex and an age group, and then ranked segments by (1) frequency, (2) cost and (3) ratios of observed to expected frequencies of co-occurring chronic conditions. We then compiled pairs of conditions that occur more frequently together than otherwise expected.
61.5% of the study population suffers from two or more chronic conditions. The most frequent dyad was hypertension and hyperlipidaemia (19%) and the most frequent triad was diabetes, hypertension and hyperlipidaemia (10%). Women aged 50 to 65 with hypertension and hyperlipidaemia were the leading cost segment in the study population. Costs and prevalence of MCC increase with number of conditions and age. The disease dyads associated with the largest observed/expected ratios were pulmonary disease and myocardial infarction. Inter-borough range MCC prevalence was 16%.
In this low-income, urban population, MCC is more prevalent (61%) than nationally (42%), motivating further research and intervention in this population. By identifying potential target populations in an interpretable manner, this segmenting methodology has utility for health services analysts.
Omissions and delays in delivering nursing care are widely reported consequences of staffing shortages, with potentially serious impacts on patients. However, studies so far have relied almost exclusively on nurse self-reporting. Monitoring vital signs is a key part of nursing work and electronic recording provides an opportunity to objectively measure delays in care. This study aimed to determine the association between registered nurse (RN) and nursing assistant (NA) staffing levels and adherence to a vital signs monitoring protocol.
Retrospective observational study.
32 medical and surgical wards in an acute general hospital in England.
538 238 nursing shifts taken over 30 982 ward days.
Vital signs observations were scheduled according to a protocol based on the National Early Warning Score (NEWS). The primary outcome was the daily rate of missed vital signs (overdue by ≥67% of the expected time to next observation). The secondary outcome was the daily rate of late vital signs observations (overdue by ≥33%). We undertook subgroup analysis by stratifying observations into low, medium and high acuity using NEWS.
Late and missed observations were frequent, particularly in high acuity patients (median=44%). Higher levels of RN staffing, measured in hours per patient per day (HPPD), were associated with a lower rate of missed observations in all (IRR 0.983, 95% CI 0.979 to 0.987) and high acuity patients (0.982, 95% CI 0.972 to 0.992). However, levels of NA staffing were only associated with the daily rate (0.954, CI 0.949 to 0.958) of all missed observations.
Adherence to vital signs monitoring protocols is sensitive to levels of nurse and NA staffing, although high acuity observations appeared unaffected by levels of NAs. We demonstrate that objectively measured omissions in care are related to nurse staffing levels, although the absolute effects are small.
The data and analyses presented here were part of the larger Missed Care study (ISRCTN registration: 17930973).
This systematic literature review aims to identify important design features of the electronic personal health record (PHR) that may improve medication adherence in the adult population with long-term conditions.
PubMed (including MEDLINE), CINAHL, Science Direct (including EMBASE), BioMed Central, ACM digital, Emerald Insight, Google Scholar and Research Gate.
Studies that were published between 1 January 2002 and 31 May 2018 in English were included if the participants were adults, with at least one long-term condition, were able to self-administer their medication and were treated in primary care settings. The quality of evidence was assessed with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system and the risk of bias was appraised using the Cochrane risk of bias tool.
From a total of 27 studies that matched the inclusion criteria, 12 were excluded due to low quality of evidence, 10 were rated moderate and 5 were rated high quality. All the included studies had low sample size and limited follow-up duration. Thirteen of the included studies found that the use of a PHR has increased medication adherence. The identified design features are reminders, education, personalisation and tailoring, feedback and alerts, gamification, medication management, medical appointment management, diary and self-monitoring, health condition management, set goals, patient’s blog and tethered. It was impossible to draw conclusions as to which feature is important to what group of patients and why. The most frequently identified conditions were HIV and diabetes. This review did not identify any papers with negative results. It was not possible to numerically aggregate the PHR effect due to high heterogeneity of the medication adherence measurement, study type, participants and PHRs used.
Although we found recurrent evidence that PHRs can improve medication adherence, there is little evidence to date to indicate which design features facilitate this process.
The National Early Warning Score is used as standard clinical practice in the UK as a track and trigger system to monitor hospitalised patients. Currently, nurses are tasked to take routine vital signs measurements and manually record these on a clinical chart. Wearable devices could provide an easier, reliable, more convenient and cost-effective method of monitoring. Our aim is to evaluate the clinical validity of Polso (ChroniSense Medical, Yokneam Illit, Israel), a wrist-based device, to provide National Early Warning Scores.
We will compare Polso National Early Warning Score measurements to the currently used manual measurements in a UK Teaching District General Hospital. Patients aged 18 years or above who require recordings of observations of vital signs at least every 6 hours will be enrolled after consenting. The sample size for the study was calculated to be 300 participants based on the assumption that the final dataset will include four pairs of measurements per-patient and per-vital sign, resulting in a total of 1200 pairs of data points per vital sign. The primary outcome is the agreement on the individual parameter scores and values of the National Early Warning Score: (1) respiratory rate, (2) oxygen saturation, (3) body temperature, (4) systolic blood pressure and (5) heart rate. Secondary outcomes are the agreement on the aggregate National Early Warning Score. The incidence of adverse events will be recorded. The measurements by the device will not be used for the clinical decision-making in this study.
We obtained ethical approval, reference number 18/LO/0123 from London—Hampstead Research Ethics Committee, through the Integrated Research Application System, (reference number: 235 034. The study received no objection from the Medicine and Health Regulatory Authority, reference number: CI/20018/005 and has National Institute for Health Research portfolio adoption status CPMS number: 32 532.
To examine the oral health conditions and oral health behaviour of high-cost patients and evaluate oral health measures as predictors of future high-cost patients.
A retrospective, population-based cohort study using administrative healthcare records.
The National Health Insurance Service (NHIS) medical check-up database (a.k.a. NHIS—national health screening cohort database) in South Korea.
131 549 individuals who received biennial health check-ups including dental check-ups in 2011 or 2012, aged 49–88.
Current and subsequent year high-cost patient status.
High-cost patients, on average, incur higher dental costs, suffer more from periodontal disease, brush their teeth less and use secondary oral hygiene products less. Some of the self-reported oral health behaviours and oral symptom variables show statistically significant associations with subsequent year high-cost patient indicators, even after adjusting for demographic, socioeconomic, medical conditions, and prior healthcare cost and utilisation.
We demonstrate that oral health measures are associated with an increased risk of becoming a high-cost patient.
This study aimed to investigate the challenges in implementing a Zambian electronic health records (EHR) system labelled ‘SmartCare’ from diverse stakeholder perspectives in order to improve prevention of mother-to-child transmission (PMTCT) data collection so that SmartCare can be used for clinic performance strengthening and programme monitoring.
This is a qualitative retrospective study.
SmartCare is a Zambian Ministry of Health (MoH)-led project funded by the US Centre for Disease Control and Prevention. Data were collected using in-depth interviews, observations and focus group discussions (FGDs) between September and November 2016. Seventeen in-depth interviews were held with a range of key informants from the MoH and local and international organisations implementing SmartCare. Four data entry observations and three FGDs with 22 pregnant and lactating women seeking PMTCT services were conducted. Data were analysed using a thematic content approach.
The SmartCare system has evolved from various patient tracking systems into a multifunctional system. There is a burden of information required so that sometimes not all is collected and entered into the database, resulting in poor data quality. Funding challenges impede data collection due to manpower constraints and shortages of supplies. Challenges associated with data collection depend on whether a paper-based or computer-based system is used. There is no uniformity in the data quality verification and submission strategies employed by various IPs. There is little feedback from the EHR system at health facility level, which has led to disengagement as stakeholders do not see the importance of the system.
SmartCare has structural challenges which can be traced from its development. Funding gaps have resulted in staffing and data collection disparities within IPs. The lack of feedback from the system has also led to complacency at the operational level, which has resulted in poor data quality in later years.
To identify how social return on investment (SROI) analysis—traditionally used by business consultants—has been interpreted, used and innovated by academics in the health and social care sector and to assess the quality of peer-reviewed SROI studies in this sector.
Community and residential settings.
A wide range of demographic groups and age groups.
The following databases were searched: Web of Science, Scopus, CINAHL, Econlit, Medline, PsychINFO, Embase, Emerald, Social Care Online and the National Institute for Health and Care Excellence. Limited uptake of SROI methodology by academics was found in the health and social care sector. From 868 papers screened, 8 studies met the criteria for inclusion in this systematic review. Study quality was found to be highly variable, ranging from 38% to 90% based on scores from a purpose-designed quality assessment tool. In general, relatively high consistency and clarity was observed in the reporting of the research question, reasons for using this methodology and justifying the need for the study. However, weaknesses were observed in other areas including justifying stakeholders, reporting sample sizes, undertaking sensitivity analysis and reporting unexpected or negative outcomes. Most papers cited links to additional materials to aid in reporting. There was little evidence that academics had innovated or advanced the methodology beyond that outlined in a much-cited SROI guide.
Academics have thus far been slow to adopt SROI methodology in the evaluation of health and social care interventions, and there is little evidence of innovation and development of the methodology. The word count requirements of peer-reviewed journals may make it difficult for authors to be fully transparent about the details of their studies, potentially impacting the quality of reporting in those studies published in these journals.
Examination of the prevalence and patterns of multimorbidity among the elderly in China.
More than 10 000 households in 28 of the 34 provinces of mainland China.
11 707 Chinese adults aged 60 and over.
Prevalence and patterns of multimorbidity among the participants. Relative risks were calculated to estimate the probability of up to 14 chronic conditions coexisting with each other. Observed-to-expected (O/E) ratios were used to analyse the patterns of multimorbidity.
Multimorbidity was present in 43.6% of respondents from the sample population, with women having the greater prevalence compared with men. There were 804 different comorbidity combinations identified, including 76 dyad combinations and 169 triad combinations. The top 10 morbidity dyads and triads accounted for 69.01% and 47.05% of the total dyad and triad combinations observed, respectively. Among the 14 chronic conditions included in the study, asthma, stroke, heart attack and six other chronic conditions were the main components of multimorbidity due to their high relative risk ratios. The most frequently occurring clusters with higher O/E ratios were stroke along with emotional, nervous, or psychiatric problems; memory-related diseases together emotional, nervous, or psychiatric problems; and memory-related diseases and asthma accompanied by chronic lung diseases and asthma.
The results of this study highlight the high prevalence of multimorbidity in the elderly population in China. Further studies are required to understand the aetiology of multimorbidity, and future primary healthcare policies should be made while taking multimorbidity into consideration.
Drug–drug interaction (DDI) alerts in hospital electronic medication management (EMM) systems are generated at the point of prescribing to warn doctors about potential interactions in their patients’ medication orders. This project aims to determine the impact of DDI alerts on DDI rates and on patient harm in the inpatient setting. It also aims to identify barriers and facilitators to optimal use of alerts, quantify the alert burden posed to prescribers with implementation of DDI alerts and to develop algorithms to improve the specificity of DDI alerting systems.
A controlled pre-post design will be used. Study sites include six major referral hospitals in two Australian states, New South Wales and Queensland. Three hospitals will act as control sites and will implement an EMM system without DDI alerts, and three as intervention sites with DDI alerts. The medical records of 280 patients admitted in the 6 months prior to and 6 months following implementation of the EMM system at each site (total 3360 patients) will be retrospectively reviewed by study pharmacists to identify potential DDIs, clinically relevant DDIs and associated patient harm. To identify barriers and facilitators to optimal use of alerts, 10–15 doctors working at each intervention hospital will take part in observations and interviews. Non-identifiable DDI alert data will be extracted from EMM systems 6–12 months after system implementation in order to quantify alert burden on prescribers. Finally, data collected from chart review and EMM systems will be linked with clinically relevant DDIs to inform the development of algorithms to trigger only clinically relevant DDI alerts in EMM systems.
This research was approved by the Hunter New England Human Research Ethics Committee (18/02/21/4.07). Study results will be published in peer-reviewed journals and presented at local and international conferences and workshops.
The aim of this study was to examine long-term trends in the receipt of medicines information (MI) among adult medicine users from 1999 to 2014.
Repeated cross-sectional postal survey from the years 1999, 2002, 2005 and 2008–2014.
Each study year, a new nationally representative sample of 5000 Finns aged 15–64 years was drawn from the Population Register Centre of Finland.
The range of annual respondents varied from 2545 to 3371 and response rates from 53% to 67%. Of the total responses (n=29 465), 64% were from medicine users (n=18 862, ranging by year from 58% to 68%).
Receipt of information on medicines in use within 12 months prior to the survey from a given list of consumer MI sources available in Finland.
Physicians, community pharmacists and package leaflets were the most common MI sources throughout the study period. Receipt of MI increased most from the Internet (from 1% in 1999 to 16% in 2014), while decreased most from physicians (62% to 47%) and package leaflets (44% to 34%), and remained stable from community pharmacists (46% to 45%) and nurses (14% to 14%). In 1999, of the medicine users 4% did not report receipt of MI from any of the sources listed in the survey, while this proportion had remarkably increased to 28% in 2014.
Healthcare professionals and package leaflets had still a dominating importance in 2014 despite the growing number of MI sources over time, but still a minority of adult medicine users reported receiving MI via the Internet in 2014. Worrying is that the proportion of adult medicine users who did not receive MI from any of the sources became seven fold during the study period.
The ‘learning healthcare system’ (LHS) has been proposed to deliver better outcomes for patients and communities by analysing routinely captured health information and feeding back results to clinical staff. This approach is being piloted in the Connected Health Cities (CHC) programme in four regions in the north of England. This article describes the protocol of the evaluation of this programme.
In designing this evaluation, we had to take a pragmatic approach to ensure the feasibility of completing the work within 1 year. Furthermore, we have designed the evaluation in such a way as to be able to capture differences in how each of the CHC regions uses a variety of methods to create their own LHS. A mixed methods approach has been adopted for this evaluation due the scale and complexities of the pilot study. A documentary review will identify how CHC pilot study deliverables were operationalised. To gain a broad understanding of CHC staff experiences, an online survey will be offered to all staff to complete. Semi-structured interviews with key programme staff will be used to gain a deeper understanding of key achievements, as well as how challenges have been overcome or managed. Our data analysis will triangulate the documentary review, survey and interview data. A thematic analysis using our logic model as a framework will also be used to assess progress against the CHC programme deliverables and to identify recommendations to support future programme decision-making.
Ethical approval was granted by The University of Manchester Ethics Committee on 24 May 2018. The results will be actively disseminated through peer-reviewed journals, conference presentations, social media, the internet and various stakeholder/patient and public engagement activities.
Multimorbidity refers to the presence of two or more chronic health conditions within one person, where no one condition is primary. Research suggests that multimorbidity is highly correlated with chronic pain, which is pain lasting longer than 3 months. Psychotherapeutic interventions for people living with chronic illness have resulted in reduced symptom reporting and improved psychological well-being. There is a dearth of research, however, using online psychotherapy for people living with multimorbidity where chronic pain is a central condition. This study will compare the effectiveness of an online acceptance and commitment therapy (ACT) intervention with a waiting list control condition in terms of improving health-related quality of life (HRQoL) and reducing levels of pain interference in people with chronic pain and at least one other condition.
192 adult participants with non-malignant pain that persists for at least 3 months and at least one other medically diagnosed condition will be randomised to one of two study conditions. The experimental group will undergo an eight-session internet-delivered ACT programme over an 8-week period. A waiting list group will be offered the ACT intervention after the 3-month follow-up period. HRQoL and pain interference will act as the primary outcomes. Data will be analysed using a linear mixed model and adjusted to account for demographic and clinical variables as necessary. A Study Within a Trial will be incorporated to examine the effect on recruitment and retention of showing participants an animated educational video.
Ethical approval has been granted by the Research Ethics Committee of the National University of Ireland, Galway. Dissemination of results will be via peer reviewed journal articles and conference presentations.
To determine the prevalence, degree of trust and usefulness of the online health information seeking source and identify associated factors in the adult population from the rural region of China.
A cross-sectional population-based study.
A self-designed questionnaire study was conducted between May and June 2015 in four districts of Zhejiang Province.
652 adults aged ≥18 years (response rate: 82.8%).
The prevalence, degree of trust and usefulness of online health information was the primary outcome. The associated factors were investigated by 2 test.
Only 34.8% of participants had faith in online health information; they still tended to select and trust a doctor which is the first choice for sources of health information. 36.7% of participants, being called ‘Internet users’, indicated that they had ever used the internet during the last 1 year. Among 239 internet users, 40.6% of them reported having sought health information via the internet. And 103 internet users responded that online health information was useful. Inferential analysis demonstrated that younger adults, individuals with higher education, people with a service-based tertiary industry career and excellent health status used online health information more often and had more faith in it (p
Using the internet to access health information is uncommon in the rural residential adult population in Zhejiang, China. They still tend to seek and trust health information from a doctor. Internet as a source of health information should be encouraged.
Health systems in North America and Europe have been criticised for their lack of safety, efficiency and effectiveness despite rising healthcare costs. In response, healthcare leaders and researchers have articulated the need to transform current health systems into continuously and rapidly learning health systems (LHSs). While digital technology has been envisioned as providing the transformational power for LHSs by generating timely evidence and supporting best care practices, it remains to be ascertained if it is indeed playing this role in current LHS initiatives. This paper presents a protocol for a scoping review that aims at providing a comprehensive understanding of how and to what extent digital technology is used within LHSs. Results will help to identify gaps in the literature as a means to guide future research on this topic.
Multiple databases and grey literature will be searched with terms related to learning health systems. Records selection will be done in duplicate by two reviewers applying pre-defined inclusion and exclusion criteria. Data extraction from selected records will be done by two reviewers using a piloted data charting form. Results will be synthesised through a descriptive numerical summary and a mapping of digital technology use onto types of LHSs and phases of learning within LHSs.
Ethical approval is not required for this scoping review. Preliminary results will be shared with stakeholders to account for their perspectives when drawing conclusions. Final results will be disseminated through presentations at relevant conferences and publications in peer-reviewed journals.
Digital data generated in the course of clinical care are increasingly being leveraged for a wide range of secondary purposes. Researchers need to develop governance policies that can assure the public that their information is being used responsibly. Our aim was to develop a generalisable model for governance of research emanating from health data repositories that will invoke the trust of the patients and the healthcare professionals whose data are being accessed for health research. We developed our governance principles and processes through literature review and iterative consultation with key actors in the research network including: a data governance working group, the lead investigators and patient advisors. We then recruited persons to participate in the governing and advisory bodies. Our governance process is informed by eight principles: (1) transparency; (2) accountability; (3) follow rule of law; (4) integrity; (5) participation and inclusiveness; (6) impartiality and independence; (7) effectiveness, efficiency and responsiveness and (8) reflexivity and continuous quality improvement. We describe the rationale for these principles, as well as their connections to the subsequent policies and procedures we developed. We then describe the function of the Research Governing Committee, the majority of whom are either persons living with diabetes or physicians whose data are being used, and the patient and data provider advisory groups with whom they consult and communicate. In conclusion, we have developed a values-based information governance framework and process for Diabetes Action Canada that adds value over-and-above existing scientific and ethics review processes by adding a strong patient perspective and contextual integrity. This model is adaptable to other secure data repositories.
Asthma and chronic obstructive pulmonary disease (COPD) are common respiratory conditions, which result in significant morbidity worldwide. These conditions are associated with a range of non-specific symptoms, which in themselves are a target for health research. Such research is increasingly being conducted using electronic health records (EHRs), but computable phenotype definitions, in the form of code sets or code lists, are required to extract structured data from these large routine databases in a systematic and reproducible way. The aim of this protocol is to specify a systematic review to identify code sets for respiratory symptoms in EHRs research.
MEDLINE and Embase databases will be searched using terms relating to EHRs, respiratory symptoms and use of code sets. The search will cover all English-language studies in these databases between January 1990 and December 2017. Two reviewers will independently screen identified studies for inclusion, and key data will be extracted into a uniform table, facilitating cross-comparison of codes used. Disagreements between the reviewers will be adjudicated by a third reviewer. This protocol has been produced in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol guidelines.
As a review of previously published studies, no ethical approval is required. The results of this review will be submitted to a peer-reviewed journal for publication and can be used in future research into respiratory symptoms that uses electronic healthcare databases.
To introduce serialised medicines into an operational hospital dispensary and assess the technical effectiveness of digital medicine authentication (MA) technology under European Union Falsified Medicines Directive (EU FMD) conditions.
Thirty medicine lines were serialised using 2D data matrix labels and introduced into an operational UK National Health Service (NHS) hospital dispensary. Staff were asked to check medicines for two-dimensional (2D) data matrices and scan those products, in addition to their usual medicine preparation and checking processes. Four per cent of the study medicines were labelled with a 2D barcode which generated a pop-up, identifying the medicine as either authenticated elsewhere (falsified), authenticated here, expired or recalled.
An NHS teaching hospital based in the UK, the same site as the Naughton et al 2016 study.
General Pharmaceutical Council registered, accredited accuracy checking technicians and pharmacists.
Average response times, offline issues, instances of incorrect quarantine and workarounds. The EU FMD maximum response time is 300 milliseconds (ms).
During the checking stage of medicine preparation, the average response time for MA in this study was 131 ms. However, 4.67% of attempted authentications experienced offline issues, an increase of 4.23% from the previous study. An increase in offline instances existed alongside an increase in incorrect quarantine.
Digital drug screening has the capability of operating with average response times which are below the maximum EU FMD limit of 300 ms. However, there was an increased incidence of offline errors and cases of incorrect quarantine. The practical and legal implications of supplying a substandard or falsified medicine during offline periods without prior authentication or withholding supply until online status resumes are not yet fully understood.
Patient records are often fragmented across organisations and departments in UK health and care services, often due to substandard information technology. However, although government policy in the UK and internationally is strongly pushing ‘digital transformation’, the evidence for the positive impact of electronic information systems on cost, quality and safety of healthcare is far from clear. In particular, the mechanisms by which information availability is translated into better decision-making are not well understood. We do not know when a full interorganisational record is more useful than a key information summary or an institutional record. In this paper, we describe our scoping review of how interorganisational electronic health records affect decision-making by hospital physicians and pharmacists.
This scoping review will follow the Arksey and O’Malley (2005) methodology. The review has adopted sociotechnical systems thinking and the notion of distributed cognition as its guiding conceptual models. The UK National Institute for Health and Care Excellence Healthcare Databases Advanced Search will be used, as it incorporates key sources including PubMed, Medline, Embase, HMIC and Health Business Elite. A hand search will be conducted using the reference lists of included studies to identify additional relevant articles. A two-part study selection process will be used: (1) a title and abstract review and (2) full text review. During the first step, two researchers separately will review the citations yielded from the search to determine eligibility based on the defined inclusion and exclusion criteria. Related articles will be included if they are empirical studies that address how interorganisational records affect decision-making by hospital physicians and pharmacists.
The results will be disseminated through stakeholder meetings, conference presentations and peer-reviewed publication. The data used are from publicly available secondary sources, so this study does not require ethical review.
The Centers for Disease Control and Prevention (CDC) spend significant time and resources to track influenza vaccination coverage each influenza season using national surveys. Emerging data from social media provide an alternative solution to surveillance at both national and local levels of influenza vaccination coverage in near real time.
This study aimed to characterise and analyse the vaccinated population from temporal, demographical and geographical perspectives using automatic classification of vaccination-related Twitter data.
In this cross-sectional study, we continuously collected tweets containing both influenza-related terms and vaccine-related terms covering four consecutive influenza seasons from 2013 to 2017. We created a machine learning classifier to identify relevant tweets, then evaluated the approach by comparing to data from the CDC’s FluVaxView. We limited our analysis to tweets geolocated within the USA.
We assessed 1 124 839 tweets. We found strong correlations of 0.799 between monthly Twitter estimates and CDC, with correlations as high as 0.950 in individual influenza seasons. We also found that our approach obtained geographical correlations of 0.387 at the US state level and 0.467 at the regional level. Finally, we found a higher level of influenza vaccine tweets among female users than male users, also consistent with the results of CDC surveys on vaccine uptake.
Significant correlations between Twitter data and CDC data show the potential of using social media for vaccination surveillance. Temporal variability is captured better than geographical and demographical variability. We discuss potential paths forward for leveraging this approach.
To explore the scope of the published literature on computer-tailoring, considering both the development and the evaluation aspects, with the aim of identifying and categorising main approaches and detecting research gaps, tendencies and trends.
Original researches from any country and healthcare setting.
Patients or health consumers with any health condition regardless of their specific characteristics.
A systematic scoping review was undertaken based on the York’s five-stage framework outlined by Arksey and O’Malley. Five leading databases were searched: PubMed, Scopus, Science Direct, EBSCO and IEEE for articles published between 1990 and 2017. Tailoring concept was investigated for three aspects: system design, information delivery and evaluation. Both quantitative (ie, frequencies) and qualitative (ie, theme analysis) methods have been used to synthesis the data.
After reviewing 1320 studies, 360 articles were identified for inclusion. Two main routes were identified in tailoring literature including public health research (64%) and computer science research (17%). The most common facets used for tailoring were sociodemographic (73 %), target behaviour status (59%) and psycho-behavioural determinants (56%), respectively. The analysis showed that only 13% of the studies described the tailoring algorithm they used, from which two approaches revealed: information retrieval (12%) and natural language generation (1%). The systematic mapping of the delivery channel indicated that nearly half of the articles used the web (57%) to deliver the tailored information; printout (19%) and email (10%) came next. Analysis of the evaluation approaches showed that nearly half of the articles (53%) used an outcome-based approach, 44% used process evaluation and 3% assessed cost-effectiveness.
This scoping review can inform researchers to identify the methodological approaches of computer tailoring. Improvements in reporting and conduct are imperative. Further research on tailoring methodology is warranted, and in particular, there is a need for a guideline to standardise reporting.