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2.  Stratification of coronary artery disease patients for revascularization procedure based on estimating adverse effects 
Background
Percutaneous coronary intervention (PCI) is the most commonly performed treatment for coronary atherosclerosis. It is associated with a higher incidence of repeat revascularization procedures compared to coronary artery bypass grafting surgery. Recent results indicate that PCI is only cost-effective for a subset of patients. Estimating risks of treatment options would be an effort toward personalized treatment strategy for coronary atherosclerosis.
Methods
In this paper, we propose to model clinical knowledge about the treatment of coronary atherosclerosis to identify patient-subgroup-specific classifiers to predict the risk of adverse events of different treatment options. We constructed one model for each patient subgroup to account for subgroup-specific interpretation and availability of features and hierarchically aggregated these models to cover the entire data. In addition, we deviated from the current clinical workflow only for patients with high probability of benefiting from an alternative treatment, as suggested by this model. Consequently, we devised a two-stage test with optimized negative and positive predictive values as the main indicators of performance. Our analysis was based on 2,377 patients that underwent PCI. Performance was compared with a conventional classification model and the existing clinical practice by estimating effectiveness, safety, and costs for different endpoints (6 month angiographic restenosis, 12 and 36 month hazardous events).
Results
Compared to the current clinical practice, the proposed method achieved an estimated reduction in adverse effects by 25.0% (95% CI, 17.8 to 30.2) for hazardous events at 36 months and 31.2% (95% CI, 25.4 to 39.0) for hazardous events at 12 months. Estimated total savings per patient amounted to $693 and $794 at 12 and 36 months, respectively. The proposed subgroup-specific method outperformed conventional population wide regression: The median area under the receiver operating characteristic curve increased from 0.57 to 0.61 for prediction of angiographic restenosis and from 0.76 to 0.85 for prediction of hazardous events.
Conclusions
The results of this study demonstrated the efficacy of deployment of bare-metal stents and coronary artery bypass grafting surgery for subsets of patients. This is one effort towards development of personalized treatment strategies for patients with coronary atherosclerosis that could significantly impact associated treatment costs.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-015-0131-0) contains supplementary material, which is available to authorized users.
doi:10.1186/s12911-015-0131-0
PMCID: PMC4336731
Coronary artery disease; Decision making; Decision support systems; Restenosis; Stents; Coronary artery bypass
3.  A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children 
Background
Warfarin is the most widely prescribed anticoagulant for the prevention and treatment of thromboembolic events. Although highly effective, the use of warfarin is limited by a narrow therapeutic range combined with a more than ten-fold difference in the dose required for adequate anticoagulation in adults. An optimal dose that leads to a favourable balance between the wanted antithrombotic effect and the risk of bleeding as measured by the prothrombin time International Normalised Ratio (INR) must be found for each patient. A model describing the time-course of the INR response can be used to aid dose selection before starting therapy (a priori dose prediction) and after therapy has been initiated (a posteriori dose revision).
Results
In this paper we describe a warfarin decision support tool. It was transferred from a population PKPD-model for warfarin developed in NONMEM to a platform independent tool written in Java. The tool proved capable of solving a system of differential equations that represent the pharmacokinetics and pharmacodynamics of warfarin with a performance comparable to NONMEM. To estimate an a priori dose the user enters information on body weight, age, baseline and target INR, and optionally CYP2C9 and VKORC1 genotype. By adding information about previous doses and INR observations, the tool will suggest a new dose a posteriori through Bayesian forecasting. Results are displayed as the predicted dose per day and per week, and graphically as the predicted INR curve. The tool can also be used to predict INR following any given dose regimen, e.g. a fixed or an individualized loading-dose regimen.
Conclusions
We believe that this type of mechanism-based decision support tool could be useful for initiating and maintaining warfarin therapy in the clinic. It will ensure more consistent dose adjustment practices between prescribers, and provide efficient and truly individualized warfarin dosing in both children and adults.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-014-0128-0) contains supplementary material, which is available to authorized users.
doi:10.1186/s12911-014-0128-0
PMCID: PMC4324411
Anticoagulation; Bayesian forecasting; Dose individualization; Population PK/PD-models; Warfarin
4.  Decision coaching using the Ottawa family decision guide with parents and their children: a field testing study 
Background
Although children can benefit from being included in health decisions, little is known about effective interventions to support their involvement. The objective of this study was to evaluate the feasibility and acceptability of decision coaching guided by the Ottawa Family Decision Guide with children and parents considering insulin delivery options for type 1 diabetes (insulin pump, multiple daily injections, or standard insulin injections).
Methods
Pre-/post-test field testing design. Eligible participants were children (≤18 years) with type 1 diabetes and their parents attending an ambulatory diabetes clinic in a tertiary children’s hospital. Parent–child dyads received decision coaching using the Ottawa Family Decision Guide that was pre-populated with evidence on insulin delivery options, benefits, and harms. Primary outcomes were feasibility of recruitment and data collection, and parent and child acceptability of the intervention.
Results
Of 16 families invited to participate, 12 agreed and 7 attended the decision coaching session. For the five missed families, two families were unable to attend the session or the decision coach was not available (N=3). Baseline and immediately post-coaching questionnaires were all completed and follow-up questionnaires two weeks post-coaching were missing from one parent–child dyad. Missing questionnaire items were 5 of 340 items for children (1.5%) and 1 of 429 for parents (0.2%). Decision coaching was rated as acceptable with higher scores from parents and their children who were in earlier stages of decision making.
Conclusion
Decision coaching with children and their parents considering insulin options was feasible implement and evaluate in our diabetes clinic and was acceptable to participants. Recruitment was difficult due to scheduling restrictions related to the timing of the study. Coaching should target participants earlier in the decision making process and be scheduled at times that are convenient for families and coaches. Findings were used to inform a full-scale evaluation that is currently underway.
doi:10.1186/s12911-014-0126-2
PMCID: PMC4326318
Children; Parents; Decision-coaching; Patient decision aid; Diabetes
5.  Development of a computerised decision aid for thrombolysis in acute stroke care 
Background
Thrombolytic treatment for acute ischaemic stroke improves prognosis, although there is a risk of bleeding complications leading to early death/severe disability. Benefit from thrombolysis is time dependent and treatment must be administered within 4.5 hours from onset of symptoms, which presents unique challenges for development of tools to support decision making and patient understanding about treatment. Our aim was to develop a decision aid to support patient-specific clinical decision-making about thrombolysis for acute ischaemic stroke, and clinical communication of personalised information on benefits/risks of thrombolysis by clinicians to patients/relatives.
Methods
Using mixed methods we developed a COMPuterised decision Aid for Stroke thrombolysiS (COMPASS) in an iterative staged process (review of available tools; a decision analytic model; interactive group workshops with clinicians and patients/relatives; and prototype usability testing). We then tested the tool in simulated situations with final testing in real life stroke thrombolysis decisions in hospitals. Clinicians used COMPASS pragmatically in managing acute stroke patients potentially eligible for thrombolysis; their experience was assessed using self-completion forms and interviews. Computer logged data assessed time in use, and utilisation of graphical risk presentations and additional features. Patients’/relatives’ experiences of discussions supported by COMPASS were explored using interviews.
Results
COMPASS expresses predicted outcomes (bleeding complications, death, and extent of disability) with and without thrombolysis, presented numerically (percentages and natural frequencies) and graphically (pictographs, bar graphs and flowcharts). COMPASS was used for 25 patients and no adverse effects of use were reported. Median time in use was 2.8 minutes. Graphical risk presentations were shared with 14 patients/relatives. Clinicians (n = 10) valued the patient-specific predictions of benefit from thrombolysis, and the support of better risk communication with patients/relatives. Patients (n = 2) and relatives (n = 6) reported that graphical risk presentations facilitated understanding of benefits/risks of thrombolysis. Additional features (e.g. dosage calculator) were suggested and subsequently embedded within COMPASS to enhance usability.
Conclusions
Our structured development process led to the development of a gamma prototype computerised decision aid. Initial evaluation has demonstrated reasonable acceptability of COMPASS amongst patients, relatives and clinicians. The impact of COMPASS on clinical outcomes requires wider prospective evaluation in clinical settings.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-014-0127-1) contains supplementary material, which is available to authorized users.
doi:10.1186/s12911-014-0127-1
PMCID: PMC4326413
Decision support; Decision aid; Patient information; Shared decision making; Risk communication; Thrombolysis; Acute stroke
6.  Using an electronic medical record (EMR) to conduct clinical trials: Salford Lung Study feasibility 
Background
Real-world data on the benefit/risk profile of medicines is needed, particularly in patients who are ineligible for randomised controlled trials conducted for registration purposes. This paper describes the methodology and source data verification which enables the conduct of pre-licensing clinical trials of COPD and asthma in the community using the electronic medical record (EMR), NorthWest EHealth linked database (NWEH-LDB) and alert systems.
Methods
Dual verification of extracts into NWEH-LDB was performed using two independent data sources (Salford Integrated Record [SIR] and Apollo database) from one primary care practice in Salford (N = 3504). A feasibility study was conducted to test the reliability of the NWEH-LDB to support longitudinal data analysis and pragmatic clinical trials in asthma and COPD. This involved a retrospective extraction of data from all registered practices in Salford to identify a cohort of patients with a diagnosis of asthma (aged ≥18) and/or COPD (aged ≥40) and ≥2 prescriptions for inhaled bronchodilators during 2008. Health care resource utilisation (HRU) outcomes during 2009 were assessed. Exacerbations were defined as: prescription for oral corticosteroids (OCS) in asthma and prescription of OCS or antibiotics in COPD; and/or hospitalisation for a respiratory cause.
Results
Dual verification demonstrated consistency between SIR and Apollo data sources: 3453 (98.6%) patients were common to both systems; 99.9% of prescription records were matched and of 29,830 diagnosis records, one record was missing from Apollo and 272 (0.9%) from SIR. Identified COPD patients were also highly concordant (Kappa coefficient = 0.98).
A total of 7981 asthma patients and 4478 COPD patients were identified within the NWEH-LDB. Cohort analyses enumerated the most commonly prescribed respiratory medication classes to be: inhaled corticosteroids (ICS) (42%) and ICS plus long-acting β2-agonist (LABA) (40%) in asthma; ICS plus LABA (55%) and long-acting muscarinic antagonists (36%) in COPD. During 2009 HRU was greater in the COPD versus asthma cohorts, and exacerbation rates in 2009 were higher in patients who had ≥2 exacerbations versus ≤1 exacerbation in 2008 for both asthma (137.5 vs. 20.3 per 100 person-years, respectively) and COPD (144.6 vs. 41.0, respectively).
Conclusion
Apollo and SIR data extracts into NWEH-LDB showed a high level of concordance for asthma and COPD patients. Longitudinal data analysis characterized the COPD and asthma populations in Salford including medications prescribed and health care utilisation outcomes suitable for clinical trial planning.
doi:10.1186/s12911-015-0132-z
PMCID: PMC4331140
Asthma; COPD; Electronic medical record; EMR; Real-world data; Primary and secondary healthcare; Dual verification
7.  Exploring critical factors influencing physicians’ acceptance of mobile electronic medical records based on the dual-factor model: a validation in Taiwan 
Background
With respect to information management, most of the previous studies on the acceptance of healthcare information technologies were analyzed from “positive” perspectives. However, such acceptance is always influenced by both positive and negative factors and it is necessary to validate both in order to get a complete understanding. This study aims to explore physicians’ acceptance of mobile electronic medical records based on the dual-factor model, which is comprised of inhibitors and enablers, to explain an individual’s technology usage. Following an earlier healthcare study in the USA, the researchers conducted a similar survey for an Eastern country (Taiwan) to validate whether perceived threat to professional autonomy acts as a critical inhibitor. In addition, perceived mobility, which is regarded as a critical feature of mobile services, was also evaluated as a common antecedent variable in the model.
Methods
Physicians from three branch hospitals of a medical group were invited to participate and complete questionnaires. Partial least squares, a structural equation modeling technique, was used to evaluate the proposed model for explanatory power and hypotheses testing.
Results
158 valid questionnaires were collected, yielding a response rate of 33.40%. As expected, the inhibitor of perceived threat has a significant impact on the physicians’ perceptions of usefulness as well as their intention to use. The enablers of perceived ease of use and perceived usefulness were also significant. In addition, as expected, perceived mobility was confirmed to have a significant impact on perceived ease of use, perceived usefulness and perceived threat.
Conclusions
It was confirmed that the dual-factor model is a comprehensive method for exploring the acceptance of healthcare information technologies, both in Western and Eastern countries. Furthermore, perceived mobility was proven to be an effective antecedent variable in the model. The researchers believe that the results of this study will contribute to the research on the acceptance of healthcare information technologies, particularly with regards to mobile electronic medical records, based on the dual-factor viewpoints of academia and practice.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-014-0125-3) contains supplementary material, which is available to authorized users.
doi:10.1186/s12911-014-0125-3
PMCID: PMC4333263
Dual-factor model; Perceived threat; Perceived mobility; Mobile electronic medical records; Physicians
8.  Early telemedicine training and counselling after hospitalization in patients with severe chronic obstructive pulmonary disease: a feasibility study 
Background
An essential element in the treatment of patients with chronic obstructive pulmonary disease (COPD) is rehabilitation, of which supervised training is an important part. However, not all individuals with severe COPD can participate in the rehabilitation provided by hospitals and municipal training centres due to distance to the training venues and transportation difficulties. The aim of the study was to assess the feasibility of an individualized home-based training and counselling programme via video conference to patients with severe COPD after hospitalization including assessment of safety, clinical outcomes, patients’ perceptions, organisational aspects and economic aspects.
Methods
The design was a pre- and post-test intervention study. Fifty patients with severe COPD were included. The telemedicine training and counselling included three weekly supervised exercise sessions by a physiotherapist and up to two supervised counselling and training sessions in energy conservation techniques by an occupational therapist. The telemedicine videoconferencing equipment was a computer containing a screen, a microphone, an on/off switch and a volume control.
Results
Thirty seven (74%) participants completed the programme, with improvements in health status assessed by the Clinical COPD Questionnaire and physical performance assessed by a sit-to-stand test and a timed-up-and-go test. There were no cases of patient fall or emergency contact with a general practitioner during the telemedicine training sessions. The study participants believed the telemedicine training and counselling was essential for getting started with being physically active in a secure manner. The business case showed that under the current financing system, the reimbursement to the hospital was slightly higher than the hospital expenditures. Thus, the business case for the hospital was positive. The organizational analysis indicated that the perceptions of the staff were that the telemedicine service had improved the continuity of the rehabilitation programme for the patients and enabled the patients’ everyday lives to be included in the treatment.
Conclusions
This study showed that home-based supervised training and counselling via video conference is safe and feasible and that telemedicine can help to ensure more equitable access to supervised training in patients with severe COPD.
Trial registration
Clinical Trials NCT02085187 (Date of registration 10.03.2014).
doi:10.1186/s12911-014-0124-4
PMCID: PMC4336686
Pulmonary rehabilitation; Training; Counselling; Telemedicine; Videoconference; COPD; Chronic disease; Internet
9.  Cultural adaptation of a shared decision making tool with Aboriginal women: a qualitative study 
Background
Shared decision making (SDM) may narrow health equity gaps experienced by Aboriginal women. SDM tools such as patient decision aids can facilitate SDM between the client and health care providers; SDM tools for use in Western health care settings have not yet been developed for and with Aboriginal populations. This study describes the adaptation and usability testing of a SDM tool, the Ottawa Personal Decision Guide (OPDG), to support decision making by Aboriginal women.
Methods
An interpretive descriptive qualitative study was structured by the Ottawa Decision Support Framework and used a postcolonial theoretical lens. An advisory group was established with representation from the Aboriginal community and used a mutually agreed-upon ethical framework. Eligible participants were Aboriginal women at Minwaashin Lodge. First, the OPDG was discussed in focus groups using a semi-structured interview guide. Then, individual usability interviews were conducted using a semi-structured interview guide with decision coaching. Iterative adaptations to the OPDG were made during focus groups and usability interviews until saturation was reached. Transcripts were coded using thematic analysis and themes confirmed in collaboration with an advisory group.
Results
Aboriginal women 20 to 60 years of age and self-identifying as First Nations, Métis, or Inuit participated in two focus groups (n = 13) or usability interviews (n = 6). Seven themes were developed that either reflected or affirmed OPDG adaptions: 1) “This paper makes it hard for me to show that I am capable of making decisions”; 2) “I am responsible for my decisions”; 3) “My past and current experiences affect the way I make decisions”; 4) “People need to talk with people”; 5) “I need to fully participate in making my decisions”; 6) “I need to explore my decision in a meaningful way”; 7) “I need respect for my traditional learning and communication style”.
Conclusions
Adaptations resulted in a culturally adapted version of the OPDG that better met the needs of Aboriginal women participants and was more accessible with respect to health literacy assumptions. Decision coaching was identified as required to enhance engagement in the decision making process and using the adapted OPDG as a talking guide.
doi:10.1186/s12911-015-0129-7
PMCID: PMC4320550
Equity; Aboriginal; Indigenous; Women; Shared decision making; Cultural adaptation; Usability testing; Health literacy
10.  Need to know: the need for cognitive closure impacts the clinical practice of obstetrician/gynecologists 
Background
Need for cognitive closure (NFCC) has been shown to be a consistent and measurable trait. It has effects on decision making and has been associated with more rapid decision making, higher reliance on heuristics or biases for decision making, reduced tolerance for ambiguity, and reduced interest in searching for alternatives. In medical practice, these tendencies may lead to lower quality of decision making.
Methods
This study measured NFCC in 312 obstetrician/gynecologists using a survey-style approach. Physicians were administered a short NFCC scale and asked questions about their clinical practice.
Results
Obstetrician/gynecologists with high NFCC were found to be less likely to address a number of clinical questions during well-woman exams, and were more likely to consult a greater number of sources when prescribing new medications.
Conclusions
NFCC of physicians may have an important impact on practice. It is possible that increased training during residency or medical school could counteract the detrimental effects of NFCC, and steps can be taken through increased use of electronic reminder systems could orient physicians to the appropriate questions to ask patients.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-014-0122-6) contains supplementary material, which is available to authorized users.
doi:10.1186/s12911-014-0122-6
PMCID: PMC4297425
Need for Cognitive Closure; Obstetricians/gynecologists; Medical decision making; Uncertainty
11.  E-Health, another mechanism to recruit and retain healthcare professionals in remote areas: lessons learned from EQUI-ResHuS project in Mali 
Background
The aim of this study was to evaluate the perceived influence of telehealth on recruitment and retention of healthcare professionals in remote areas in Mali.
Methods
After 15 months of diagnosis imaging training and telehealth activities at four project sites in remote Mali, between May 2011 and August 2012, a 75-item questionnaire was administered to healthcare professionals to assess the various factors related to Information and Communication Technologies (ICT), especially telehealth, and their influence on health personnel recruitment and retention. Questions assessing perceived impact of telehealth on recruitment and retention of healthcare professionals were rated on a five-point Likert scale. Dependent variables were perceived influence of ICT on recruitment and retention and independent variables were access to ICT, ICT training, ICT use, perceived benefits and drawbacks of telehealth, and perceived barriers to recruitment and retention. A multiple linear regression was performed to identify variables explaining the respondents’ perceptions regarding telehealth influence on recruitment and retention.
Results
Data analysis showed that professionals in remote areas have very positive perceptions of telehealth in general. Many benefits of telehealth for recruitment and retention were highlighted, with perceived benefits of ICT (p = 0.0478), perceived effects of telehealth on recruitment (p = 0.0018), telehealth training (0.0338) and information on telehealth (0.0073) being the strongest motivators for recruitment, while the perceived effects of telehealth on retention (p = 0.0018) was the only factor significantly associated with retention.
Conclusions
Based on our study results, telehealth could represent a mechanism for recruiting and retaining health professionals in remote areas and could reduce the isolation of these professionals through networking opportunities.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-014-0120-8) contains supplementary material, which is available to authorized users.
doi:10.1186/s12911-014-0120-8
PMCID: PMC4305223  PMID: 25539841
12.  A comparison of smartphones to paper-based questionnaires for routine influenza sentinel surveillance, Kenya, 2011–2012 
Background
For disease surveillance, manual data collection using paper-based questionnaires can be time consuming and prone to errors. We introduced smartphone data collection to replace paper-based data collection for an influenza sentinel surveillance system in four hospitals in Kenya. We compared the quality, cost and timeliness of data collection between the smartphone data collection system and the paper-based system.
Methods
Since 2006, the Kenya Ministry of Health (MoH) with technical support from the Kenya Medical Research Institute/Centers for Disease Control and Prevention (KEMRI/CDC) conducted hospital-based sentinel surveillance for influenza in Kenya. In May 2011, the MOH replaced paper-based collection with an electronic data collection system using Field Adapted Survey Toolkit (FAST) on HTC Touch Pro2 smartphones at four sentinel sites. We compared 880 paper-based questionnaires dated Jan 2010-Jun 2011 and 880 smartphone questionnaires dated May 2011-Jun 2012 from the four surveillance sites. For each site, we compared the quality, cost and timeliness of each data collection system.
Results
Incomplete records were more likely seen in data collected using pen-and-paper compared to data collected using smartphones (adjusted incidence rate ratio (aIRR) 7, 95% CI: 4.4-10.3). Errors and inconsistent answers were also more likely to be seen in data collected using pen-and-paper compared to data collected using smartphones (aIRR: 25, 95% CI: 12.5-51.8). Smartphone data was uploaded into the database in a median time of 7 days while paper-based data took a median of 21 days to be entered (p < 0.01). It cost USD 1,501 (9.4%) more to establish the smartphone data collection system ($17,500) than the pen-and-paper system (USD $15,999). During two years, however, the smartphone data collection system was $3,801 (7%) less expensive to operate ($50,200) when compared to pen-and-paper system ($54,001).
Conclusions
Compared to paper-based data collection, an electronic data collection system produced fewer incomplete data, fewer errors and inconsistent responses and delivered data faster. Although start-up costs were higher, the overall costs of establishing and running the electronic data collection system were lower compared to paper-based data collection system. Electronic data collection using smartphones has potential to improve timeliness, data integrity and reduce costs.
doi:10.1186/s12911-014-0107-5
PMCID: PMC4305246  PMID: 25539745
Data collection; Electronic; Pen-and-paper; Smartphone; Quality; Cost; Timeliness
13.  Scoping review of toolkits as a knowledge translation strategy in health 
Background
Significant resources are invested in the production of research knowledge with the ultimate objective of integrating research evidence into practice. Toolkits are becoming increasingly popular as a knowledge translation (KT) strategy for disseminating health information, to build awareness, inform, and change public and healthcare provider behavior. Toolkits communicate messages aimed at improving health and changing practice to diverse audiences, including healthcare practitioners, patients, community and health organizations, and policy makers. This scoping review explores the use of toolkits in health and healthcare.
Methods
Using Arksey and O’Malley’s scoping review framework, health-based toolkits were identified through a search of electronic databases and grey literature for relevant articles and toolkits published between 2004 and 2011. Two reviewers independently extracted data on toolkit topic, format, target audience, content, evidence underlying toolkit content, and evaluation of the toolkit as a KT strategy.
Results
Among the 253 sources identified, 139 met initial inclusion criteria and 83 toolkits were included in the final sample. Fewer than half of the sources fully described the toolkit content and about 70% made some mention of the evidence underlying the content. Of 83 toolkits, only 31 (37%) had been evaluated at any level (27 toolkits were evaluated overall relative to their purpose or KT goal, and 4 toolkits evaluated the effectiveness of certain elements contained within them).
Conclusions
Toolkits used to disseminate health knowledge or support practice change often do not specify the evidence base from which they draw, and their effectiveness as a knowledge translation strategy is rarely assessed. To truly inform health and healthcare, toolkits should include comprehensive descriptions of their content, be explicit regarding content that is evidence-based, and include an evaluation of the their effectiveness as a KT strategy, addressing both clinical and implementation outcomes.
doi:10.1186/s12911-014-0121-7
PMCID: PMC4308831  PMID: 25539950
Toolkit; Knowledge translation; Practice change; Evaluation; Health
14.  Extension of the primary care research object model (PCROM) as clinical research information model (CRIM) for the “learning healthcare system” 
Background
Patient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials. The EU funded project TRANSFoRm aims to create a “Learning Healthcare System” at a European level that is able to support all types of research using primary care data, to recruit patients and follow patients in clinical studies and to improve diagnosis and therapy. The implementation of such a Learning Healthcare System needs an information model for clinical research (CRIM), as an informational backbone to integrate aspects of primary care with clinical trials and database searches.
Methods
Workflow descriptions and corresponding data objects of two clinical use cases (Gastro-Oesophageal Reflux Disease and Type 2 Diabetes) were described in UML activity diagrams. The components of activity diagrams were mapped to information objects of PCROM (Primary Care Research Object Model) and BRIDG (Biomedical Research Integrated Domain Group) and evaluated. The class diagram of PCROM was adapted to comply with workflow descriptions.
Results
The suitability of PCROM, a primary care information model already used for clinical trials, to act as an information model for TRANSFoRm was evaluated and resulted in its extension with 14 new information object types, two extensions of existing objects and the introduction of two new high-ranking concepts (CARE area and ENTRY area). No PCROM component was redundant. Our result illustrates that in primary care based research an important but underestimated portion of research activity takes place in the area of care (e.g. patient consultation, screening, recruitment and response to adverse events). The newly introduced CARE area for care-related research activities accounts for this shift and includes Episode of Care and Encounter as two new basic elements. In the ENTRY area different aspects of data collection were combined, including data semantics for observations, assessment activities, intervention activities and patient reporting to enable case report form (CRF) based data collection combined with decision support.
Conclusions
Research with primary care data needs an extended information model that covers research activities at the care site which are characteristic for primary care based research and the requirements of the complicated data collection processes.
doi:10.1186/s12911-014-0118-2
PMCID: PMC4276023  PMID: 25519481
15.  A web-based intervention to support self-management of patients with type 2 diabetes mellitus: effect on self-efficacy, self-care and diabetes distress 
Background
Management of diabetes mellitus is complex and involves controlling multiple risk factors that may lead to complications. Given that patients provide most of their own diabetes care, patient self-management training is an important strategy for improving quality of care. Web-based interventions have the potential to bridge gaps in diabetes self-care and self-management. The objective of this study was to determine the effect of a web-based patient self-management intervention on psychological (self-efficacy, quality of life, self-care) and clinical (blood pressure, cholesterol, glycemic control, weight) outcomes.
Methods
For this cohort study we used repeated-measures modelling and qualitative individual interviews. We invited patients with type 2 diabetes to use a self-management website and asked them to complete questionnaires assessing self-efficacy (primary outcome) every three weeks for nine months before and nine months after they received access to the website. We collected clinical outcomes at three-month intervals over the same period. We conducted in-depth interviews at study conclusion to explore acceptability, strengths and weaknesses, and mediators of use of the website. We analyzed the data using a qualitative descriptive approach and inductive thematic analysis.
Results
Eighty-one participants (mean age 57.2 years, standard deviation 12) were included in the analysis. The self-efficacy score did not improve significantly more than expected after nine months (absolute change 0.12; 95% confidence interval −0.028, 0.263; p = 0.11), nor did clinical outcomes. Website usage was limited (average 0.7 logins/month). Analysis of the interviews (n = 21) revealed four themes: 1) mediators of website use; 2) patterns of website use, including role of the blog in driving site traffic; 3) feedback on website; and 4) potential mechanisms for website effect.
Conclusions
A self-management website for patients with type 2 diabetes did not improve self-efficacy. Website use was limited. Although its perceived reliability, availability of a blog and emailed reminders drew people to the website, participants’ struggles with type 2 diabetes, competing priorities in their lives, and website accessibility were barriers to its use. Future interventions should aim to integrate the intervention seamlessly into the daily routine of end users such that it is not seen as yet another chore.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-014-0117-3) contains supplementary material, which is available to authorized users.
doi:10.1186/s12911-014-0117-3
PMCID: PMC4272538  PMID: 25495847
Diabetes mellitus; Online systems; Patient self-management; Self-efficacy; Repeated measures modelling; Qualitative methods
16.  Stage 1 of the meaningful use incentive program for electronic health records: a study of readiness for change in ambulatory practice settings in one integrated delivery system 
Background
Meaningful Use (MU) provides financial incentives for electronic health record (EHR) implementation. EHR implementation holds promise for improving healthcare delivery, but also requires substantial changes for providers and staff. Establishing readiness for these changes may be important for realizing potential EHR benefits. Our study assesses whether provider/staff perceptions about the appropriateness of MU and their departments’ ability to support MU-related changes are associated with their reported readiness for MU-related changes.
Methods
We surveyed providers and staff representing 47 ambulatory practices within an integrated delivery system. We assessed whether respondent’s role and practice-setting type (primary versus specialty care) were associated with reported readiness for MU (i.e., willingness to change practice behavior and ability to document actions for MU) and hypothesized predictors of readiness (i.e., perceived appropriateness of MU and department support for MU). We then assessed associations between reported readiness and the hypothesized predictors of readiness.
Results
In total, 400 providers/staff responded (response rate approximately 25%). Individuals working in specialty settings were more likely to report that MU will divert attention from other patient-care priorities (12.6% vs. 4.4%, p = 0.019), as compared to those in primary-care settings. As compared to advanced-practice providers and nursing staff, physicians were less likely to have strong confidence in their department’s ability to solve MU implementation problems (28.4% vs. 47.1% vs. 42.6%, p = 0.023) and to report strong willingness to change their work practices for MU (57.9% vs. 83.3% vs. 82.0%, p < 0.001). Finally, provider/staff perceptions about whether MU aligns with departmental goals (OR = 3.99, 95% confidence interval (CI) = 2.13 to 7.48); MU will divert attention from other patient-care priorities (OR = 2.26, 95% CI = 1.26 to 4.06); their department will support MU-related change efforts (OR = 3.99, 95% CI = 2.13 to 7.48); and their department will be able to solve MU implementation problems (OR = 2.26, 95% CI = 1.26 to 4.06) were associated with their willingness to change practice behavior for MU.
Conclusions
Organizational leaders should gauge provider/staff perceptions about appropriateness and management support of MU-related change, as these perceptions might be related to subsequent implementation.
doi:10.1186/s12911-014-0119-1
PMCID: PMC4272806  PMID: 25495926
17.  Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform 
Background
Over 100 trials show that patient decision aids effectively improve patients’ information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions.
Methods
An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care.
Results
This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p < 0.01).
Conclusions
Combining decision science and health informatics approaches facilitated rapid development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web-based decision aid component performed comparably with the videobooklet decision aid used in clinical practice. Future studies may use this interactive research platform to study patients’ decision making processes in real-time, explore interdisciplinary approaches to designing web-based decision aids, and test strategies for tailoring decision support to meet patients’ needs and preferences.
doi:10.1186/s12911-014-0112-8
PMCID: PMC4275953
Decision support; Patient decision aid; Web-based; Informed patient choice; Shared decision making; Consumer health informatics; Patient-centered; User-centered; Decision technology; Osteoarthritis; Development
18.  Is pathology necessary to predict mortality among men with prostate-cancer? 
Background
Statistical models developed using administrative databases are powerful and inexpensive tools for predicting survival. Conversely, data abstraction from chart review is time-consuming and costly. Our aim was to determine the incremental value of pathological data obtained from chart abstraction in addition to information acquired from administrative databases in predicting all-cause and prostate cancer (PC)-specific mortality.
Methods
We identified a cohort of men with diabetes and PC utilizing population-based data from Ontario. We used the c-statistic and net-reclassification improvement (NRI) to compare two Cox- proportional hazard models to predict all-cause and PC-specific mortality. The first model consisted of covariates from administrative databases: age, co-morbidity, year of cohort entry, socioeconomic status and rural residence. The second model included Gleason grade and cancer volume in addition to all aforementioned variables.
Results
The cohort consisted of 4001 patients. The accuracy of the admin-data only model (c-statistic) to predict 5-year all-cause mortality was 0.7 (95% CI 0.69-0.71). For the extended model (including pathology information) it was 0.74 (95% CI 0.73-0.75). This corresponded to a change in category of predicted probability of survival among 14.8% in the NRI analysis.
The accuracy of the admin-data model to predict 5-year PC specific mortality was 0.76 (95% CI 0.74-0.78). The accuracy of the extended model was 0.85 (95% CI 0.83-0.87). Corresponding to a 28% change in the NRI analysis.
Conclusions
Pathology chart abstraction, improved the accuracy in predicting all-cause and PC-specific mortality. The benefit is smaller for all-cause mortality, and larger for PC-specific mortality.
doi:10.1186/s12911-014-0114-6
PMCID: PMC4275978
Prostate cancer; Survival; Prediction models; Population-based study
19.  Health Professionals’ readiness to implement electronic medical record system at three hospitals in Ethiopia: a cross sectional study 
Background
Electronic medical record systems are being implemented in many countries to support healthcare services. However, its adoption rate remains low, especially in developing countries due to technological, financial, and organizational factors. There is lack of solid evidence and empirical research regarding the pre implementation readiness of healthcare providers. The aim of this study is to assess health professionals’ readiness and to identify factors that affect the acceptance and use of electronic medical recording system in the pre implementation phase at hospitals of North Gondar Zone, Ethiopia.
Methods
An institution based cross-sectional quantitative study was conducted on 606 study participants from January to July 2013 at 3 hospitals in northwest Ethiopia. A pretested self-administered questionnaire was used to collect the required data. The data were entered using the Epi-Info version 3.5.1 software and analyzed using SPSS version 16 software. Descriptive statistics, bi-variate, and multi-variate logistic regression analyses were used to describe the study objectives and assess the determinants of health professionals’ readiness for the system. Odds ratio at 95% CI was used to describe the association between the study and the outcome variables.
Results
Out of 606 study participants only 328 (54.1%) were found ready to use the electronic medical recording system according to our criteria assessment. The majority of the study participants, 432 (71.3%) and 331(54.6%) had good knowledge and attitude for EMR system, respectively. Gender (AOR = 1.87, 95% CI: [1.26, 2.78]), attitude (AOR = 1.56, 95% CI: [1.03, 2.49]), knowledge (AOR = 2.12, 95% CI: [1.32, 3.56]), and computer literacy (AOR =1.64, 95% CI: [0.99, 2.68]) were significantly associated with the readiness for EMR system.
Conclusions
In this study, the overall health professionals’ readiness for electronic medical record system and utilization was 54.1% and 46.5%, respectively. Gender, knowledge, attitude, and computer related skills were the determinants of the presence of a relatively low readiness and utilization of the system. Increasing awareness, knowledge, and skills of healthcare professionals on EMR system before system implementation is necessary to increase its adoption.
doi:10.1186/s12911-014-0115-5
PMCID: PMC4276073
Electronic medical record system (EMR); EMR system; EMR implementation; EMR readiness; EMR utilization; Associated factors of EMR; EMR adoption; Ethiopia
20.  Communicating cancer treatment information using the Web: utilizing the patient’s perspective in website development 
Background
Online cancer information can support patients in making treatment decisions. However, such information may not be adequately tailored to the patient’s perspective, particularly if healthcare professionals do not sufficiently engage patient groups when developing online information. We applied qualitative user testing during the development of a patient information website on stereotactic ablative radiotherapy (SABR), a new guideline-recommended curative treatment for early-stage lung cancer.
Methods
We recruited 27 participants who included patients referred for SABR and their relatives. A qualitative user test of the website was performed in 18 subjects, followed by an additional evaluation by users after website redesign (N = 9). We primarily used the ‘thinking aloud’ approach and semi-structured interviewing. Qualitative data analysis was performed to assess the main findings reported by the participants.
Results
Study participants preferred receiving different information that had been provided initially. Problems identified with the online information related to comprehending medical terminology, understanding the scientific evidence regarding SABR, and appreciating the side-effects associated with SABR. Following redesign of the website, participants reported fewer problems with understanding content, and some additional recommendations for better online information were identified.
Conclusions
Our findings indicate that input from patients and their relatives allows for a more comprehensive and usable website for providing treatment information. Such a website can facilitate improved patient participation in treatment decision-making for cancer.
doi:10.1186/s12911-014-0116-4
PMCID: PMC4271466  PMID: 25481306
Lung cancer; Patient information; Internet; Treatment decisions
21.  Learning to improve medical decision making from imbalanced data without a priori cost 
Background
In a medical data set, data are commonly composed of a minority (positive or abnormal) group and a majority (negative or normal) group and the cost of misclassifying a minority sample as a majority sample is highly expensive. This is the so-called imbalanced classification problem. The traditional classification functions can be seriously affected by the skewed class distribution in the data. To deal with this problem, people often use a priori cost to adjust the learning process in the pursuit of optimal classification function. However, this priori cost is often unknown and hard to estimate in medical decision making.
Methods
In this paper, we propose a new learning method, named RankCost, to classify imbalanced medical data without using a priori cost. Instead of focusing on improving the class-prediction accuracy, RankCost is to maximize the difference between the minority class and the majority class by using a scoring function, which translates the imbalanced classification problem into a partial ranking problem. The scoring function is learned via a non-parametric boosting algorithm.
Results
We compare RankCost to several representative approaches on four medical data sets varying in size, imbalanced ratio, and dimension. The experimental results demonstrate that unlike the currently available methods that often perform unevenly with different priori costs, RankCost shows comparable performance in a consistent manner.
Conclusions
It is a challenging task to learn an effective classification model based on imbalanced data in medical data analysis. The traditional approaches often use a priori cost to adjust the learning of the classification function. This work presents a novel approach, namely RankCost, for learning from medical imbalanced data sets without using a priori cost. The experimental results indicate that RankCost performs very well in imbalanced data classification and can be a useful method in real-world applications of medical decision making.
doi:10.1186/s12911-014-0111-9
PMCID: PMC4261533  PMID: 25480146
Medical decision making; Imbalanced data; Classification; Partial ranking
22.  Diagnostic accuracy of a screening electronic alert tool for severe sepsis and septic shock in the emergency department 
Background
Early recognition of severe sepsis and septic shock is challenging. The aim of this study was to determine the diagnostic accuracy of an electronic alert system in detecting severe sepsis or septic shock among emergency department (ED) patients.
Methods
An electronic sepsis alert system was developed as a part of a quality-improvement project for severe sepsis and septic shock. The system screened all adult ED patients for a combination of systemic inflammatory response syndrome and organ dysfunction criteria (hypotension, hypoxemia or lactic acidosis). This study included all patients older than 14 years who presented to the ED of a tertiary care academic medical center from Oct. 1, 2012 to Jan. 31, 2013. As a comparator, emergency medicine physicians or the critical care physician identified the patients with severe sepsis or septic shock.
In the ED, vital signs were manually entered into the hospital electronic heath record every hour in the critical care area and every two hours in other areas. We also calculated the time from the alert to the intensive care unit (ICU) referral.
Results
Of the 49,838 patients who presented to the ED, 222 (0.4%) were identified to have severe sepsis or septic shock. The electronic sepsis alert had a sensitivity of 93.18% (95% CI, 88.78% - 96.00%), specificity of 98.44 (95% CI, 98.33% – 98.55%), positive predictive value of 20.98% (95% CI, 18.50% – 23.70%) and negative predictive value of 99.97% (95% CI, 99.95% – 99.98%) for severe sepsis and septic shock. The alert preceded ICU referral by a median of 4.02 hours (Q1 - Q3: 1.25–8.55).
Conclusions
Our study shows that electronic sepsis alert tool has high sensitivity and specificity in recognizing severe sepsis and septic shock, which may improve early recognition and management.
doi:10.1186/s12911-014-0105-7
PMCID: PMC4261595  PMID: 25476738
Clinical decision support; Sepsis; Sensitivity and specificity; Septic shock; Emergency department; Electronic alert
23.  Practicing evidence based medicine at the bedside: a randomized controlled pilot study in undergraduate medical students assessing the practicality of tablets, smartphones, and computers in clinical life 
Background
Practicing evidence-based medicine is an important aspect of providing good medical care. Accessing external information through literature searches on computer-based systems can effectively achieve integration in clinical care. We conducted a pilot study using smartphones, tablets, and stationary computers as search devices at the bedside. The objective was to determine possible differences between the various devices and assess students’ internet use habits.
Methods
In a randomized controlled pilot study, 120 students were divided in three groups. One control group solved clinical problems on a computer and two intervention groups used mobile devices at the bedside. In a questionnaire, students were asked to report their internet use habits as well as their satisfaction with their respective search tool using a 5-point Likert scale.
Results
Of 120 surveys, 94 (78.3%) complete data sets were analyzed. The mobility of the tablet (3.90) and the smartphone (4.39) was seen as a significant advantage over the computer (2.38, p < .001). However, for performing an effective literature search at the bedside, the computer (3.22) was rated superior to both tablet computers (2.13) and smartphones (1.68). No significant differences were detected between tablets and smartphones except satisfaction with screen size (tablet 4.10, smartphone 2.00, p < .001).
Conclusions
Using a mobile device at the bedside to perform an extensive search is not suitable for students who prefer using computers. However, mobility is regarded as a substantial advantage, and therefore future applications might facilitate quick and simple searches at the bedside.
Electronic supplementary material
The online version of this article (doi:10.1186/s12911-014-0113-7) contains supplementary material, which is available to authorized users.
doi:10.1186/s12911-014-0113-7
PMCID: PMC4262131  PMID: 25477073
Usability; Mobile device; Smartphone; Tablet computer; Evidence based medicine
24.  A Bayesian spatio‐temporal approach for real‐time detection of disease outbreaks: a case study 
Background
For researchers and public health agencies, the complexity of high‐dimensional spatio‐temporal data in surveillance for large reporting networks presents numerous challenges, which include low signal‐to‐noise ratios, spatial and temporal dependencies, and the need to characterize uncertainties. Central to the problem in the context of disease outbreaks is a decision structure that requires trading off false positives for delayed detections.
Methods
In this paper we apply a previously developed Bayesian hierarchical model to a data set from the Indiana Public Health Emergency Surveillance System (PHESS) containing three years of emergency department visits for influenza‐like illness and respiratory illness. Among issues requiring attention were selection of the underlying network (Too few nodes attenuate important structure, while too many nodes impose barriers to both modeling and computation.); ensuring that confidentiality protections in the data do not impede important modeling day of week effects; and evaluating the performance of the model.
Results
Our results show that the model captures salient spatio‐temporal dynamics that are present in public health surveillance data sets, and that it appears to detect both “annual” and “atypical” outbreaks in a timely, accurate manner. We present maps that help make model output accessible and comprehensible to public health authorities. We use an illustrative family of decision rules to show how output from the model can be used to inform false positive–delayed detection tradeoffs.
Conclusions
The advantages of our methodology for addressing the complicated issues of real world surveillance data applications are three‐fold. We can easily incorporate additional covariate information and spatio‐temporal dynamics in the data. Second, we furnish a unified framework to provide uncertainties associated with each parameter. Third, we are able to handle multiplicity issues by using a Bayesian approach. The urgent need to quickly and effectively monitor the health of the public makes our methodology a potentially plausible and useful surveillance approach for health professionals.
doi:10.1186/s12911-014-0108-4
PMCID: PMC4267748  PMID: 25476843
Conditional autoregressive process; Influenza; Gaussian Markov random field; Spatial statistics; Spatio‐temporal; Syndromic surveillance
25.  Development and psychometric properties of a brief measure of subjective decision quality for breast cancer treatment 
Background
Breast cancer patients face several preference-sensitive treatment decisions. Feelings such as regret or having had inadequate information about these decisions can significantly alter patient perceptions of recovery and recurrence. Numerous objective measures of decision quality (e.g., knowledge assessments, values concordance measures) have been developed; there are far fewer measures of subjective decision quality and little consensus regarding how the construct should be assessed. The current study explores the psychometric properties of a new subjective quality decision measure for breast cancer treatment that could be used for other preference sensitive decisions.
Methods
320 women aged 20–79 diagnosed with AJCC stage 0 – III breast cancer were surveyed at two cancer specialty centers. Decision quality was assessed with single items representing six dimensions: regret, satisfaction, and fit as well as perceived adequacy of information, time, and involvement. Women rated decision quality for their overall treatment experience and surgery, chemotherapy, and radiation decisions separately. Principle components was used to explore factor structure. After scales were formed, internal consistency was computed using Cronbach’s alpha. The association of each of the four final scales with patient characteristics scores was examined by Pearson correlation.
Results
For overall breast cancer treatment as well as surgery, chemotherapy, and radiation decisions, the six items yielded a single factor solution. Factor loadings of the six decision items were all above .45 across the overall and treatment-specific scales, with the exception of “Right for You” for chemotherapy and radiation. Internal consistency was 0.77, 0.85, 0.82, and 0.78 for the overall, surgery, chemotherapy, and radiation decision quality scales, respectively.
Conclusions
Our measure of subjective appraisal of breast cancer treatment decisions includes 5 related elements; regret and satisfaction as well as perceived adequacy of information, time, and involvement. Future research is needed to establish norms for the measure as is further psychometric testing, particularly to examine how it is associated with outcomes such as quality of life, psychological coping and objective decision quality.
doi:10.1186/s12911-014-0110-x
PMCID: PMC4272518  PMID: 25476986
Breast cancer; Oncology; Decision making; Decision quality; Decision satisfaction; Scale development; Psychometric testing

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