Brief review: Adoption of electronic medical records to enhance acute pain management

Dashboard of Short-Term Postoperative Patient Outcomes for Anesthesiologists: Development and Preliminary Evaluation

BACKGROUND

Anesthesiologists require an understanding of their patients' outcomes to evaluate their performance and improve their practice. Traditionally, anesthesiologists had limited information about their surgical outpatients' outcomes due to minimal contact post discharge. Leveraging digital health innovations for analyzing personal and population outcomes may improve perioperative care. BC Children's Hospital's postoperative follow-up registry for outpatient surgeries collects short-term outcomes such as pain, nausea, and vomiting. Yet, these data were previously not available to anesthesiologists.

OBJECTIVE

This quality improvement study aimed to visualize postoperative outcome data to allow anesthesiologists to reflect on their care and compare their performance with their peers.

METHODS

The postoperative follow-up registry contains nurse-reported postoperative outcomes, including opioid and antiemetic administration in the postanesthetic care unit (PACU), and family-reported outcomes, including pain, nausea, and vomiting, within 24 hours post discharge. Dashboards were iteratively co-designed with 5 anesthesiologists, and a department-wide usability survey gathered anesthesiologists' feedback on the dashboards, allowing further design improvements. A final dashboard version has been deployed, with data updated weekly.

RESULTS

The dashboard contains three sections: (1) 24-hour outcomes, (2) PACU outcomes, and (3) a practice profile containing individual anesthesiologist's case mix, grouped by age groups, sex, and surgical service. At the time of evaluation, the dashboard included 24-hour data from 7877 cases collected from September 2020 to February 2023 and PACU data from 8716 cases collected from April 2021 to February 2023. The co-design process and usability evaluation indicated that anesthesiologists preferred simpler designs for data summaries but also required the ability to explore details of specific outcomes and cases if needed. Anesthesiologists considered security and confidentiality to be key features of the design and most deemed the dashboard information useful and potentially beneficial for their practice.

CONCLUSIONS

We designed and deployed a dynamic, personalized dashboard for anesthesiologists to review their outpatients' short-term postoperative outcomes. This dashboard facilitates personal reflection on individual practice in the context of peer and departmental performance and, hence, the opportunity to evaluate iterative practice changes. Further work is required to establish their effect on improving individual and department performance and patient outcomes.

Factors associated with the perceptions of eHealth technology of Chinese nurses and nursing students

AIM

The current study sought to assess the perceptions of eHealth technology of nurses and nursing students in China and to examine the association between these perceptions and demographic factors.

BACKGROUND

Despite the increasing use of eHealth technologies in China and across the globe, the perceptions of practicing and student nurses remain minimally explored. Findings from such an inquiry can potentially inform actions and policies to improve the uptake of eHealth technologies among Chinese nurses.

DESIGN

This was a cross-sectional study with a real-time online survey.

METHODS

A convenience sample of 1338 nurses and nursing students from Mainland China participated in the study. Their perceptions of eHealth technology were collected using the Chinese version of the Perceptions of eHealth Technology Scale. The Kruskal-Wallis test and multiple linear regression analysis were used to examine the relationship between demographic variables (age group, gender, occupation, education level, position and clinical experience) and perceptions of eHealth technology. All study procedures adhered to the STROBE guidelines.

RESULTS

Most participants were aged between 20 and 29 (55.8%). Nearly half (42.5%) were frontline clinical nursing staff, some were nursing students (36.2%), academic nursing staff (12.3%) and clinical nursing management staff (9.0%). Regardless of the differences in their demographic characteristics, the participants had higher mean scores in "Perception of eHealth applications" and lower mean scores in "Knowledge of eHealth technology". Participants with doctoral degree had a higher mean total score and higher sub-scale scores in knowledge of eHealth technology, perception of the advantages of eHealth technology and perception of eHealth applications; and the lowest scores in perception of the disadvantages of eHealth technology and perception of eHealth applications. Occupation, position and clinical experience were found to be the demographic characteristics associated with eHealth perceptions, before adjusting for age and gender. Education level was associated with eHealth perceptions regardless of adjustment.

CONCLUSION

Overall, participants had higher scores on perceptions of eHealth applications but lower scores on knowledge of eHealth technology. Considering the association between education and all subscales and overall scores, it may be essential to implement continuing professional education for nurses to improve their knowledge of eHealth applications. Encouragement to use available eHealth digital technologies may also be helpful to improve perceptions of eHealth.

How physicians can empower patients with digital tools

Background

While there is broad consensus that the use of digital tools would significantly improve patient empowerment, to date, an improvement in health outcomes has been elusive.

Objective

The objective of this study was to assess how to improve the ability of physicians to empower patients with digital tools.

Methods

We conducted a web-based survey using SurveyMonkey over nearly 6 months. A questionnaire was sent with an email, explaining the aims of the survey and providing a link to complete the web-based questionnaire, to the heads of each of the 37 medical national societies adhering to the EFIM (European Federation of Internal Medicine), inviting them to disseminate the questionnaire among their members.

Results

Two hundred and eighteen responses were received. They suggest that the main success factors in increasing and improving patient empowerment with digital tools and realizing health goals are clinical evidence, followed by patient/physician involvement in the design, tools designed around the real needs of the patient, and reimbursement. Most of the respondents who have already prescribed digital tools for patient empowerment are just enough satisfied with the results achieved by their patients. Interestingly, 18% of the respondents had spent more than 30 min on the visit of patient to doctor. However, the majority devoted only 5–9 min to illustrating the suggested digital tools.

Conclusions

According to the respondents, clinical evidence, motivation, physician and patient’s involvement in design, and reimbursement, as well as organizations’ appropriate business models and support, are the main determinants of the diffusion and effective adoption of digital tools for successful patient empowerment in internal medicine.

Implementation of Electronic Medical Records in Mental Health Settings: Scoping Review

BACKGROUND

The success of electronic medical records (EMRs) is dependent on implementation features, such as usability and fit with clinical processes. The use of EMRs in mental health settings brings additional and specific challenges owing to the personal, detailed, narrative, and exploratory nature of the assessment, diagnosis, and treatment in this field. Understanding the determinants of successful EMR implementation is imperative to guide the future design, implementation, and investment of EMRs in the mental health field.

OBJECTIVE

We intended to explore evidence on effective EMR implementation for mental health settings and provide recommendations to support the design, adoption, usability, and outcomes.

METHODS

The scoping review combined two search strategies that focused on clinician-facing EMRs, one for primary studies in mental health settings and one for reviews of peer-reviewed literature in any health setting. Three databases (Medline, EMBASE, and PsycINFO) were searched from January 2010 to June 2020 using keywords to describe EMRs, settings, and impacts. The Proctor framework for implementation outcomes was used to guide data extraction and synthesis. Constructs in this framework include adoption, acceptability, appropriateness, feasibility, fidelity, cost, penetration, and sustainability. Quality assessment was conducted using a modified Hawker appraisal tool and the Joanna Briggs Institute Critical Appraisal Checklist for Systematic Reviews and Research Syntheses.

RESULTS

This review included 23 studies, namely 12 primary studies in mental health settings and 11 reviews. Overall, the results suggested that adoption of EMRs was impacted by financial, technical, and organizational factors, as well as clinician perceptions of appropriateness and acceptability. EMRs were perceived as acceptable and appropriate by clinicians if the system did not interrupt workflow and improved documentation completeness and accuracy. Clinicians were more likely to value EMRs if they supported quality of care, were fit for purpose, did not interfere with the clinician-patient relationship, and were operated with readily available technical support. Evidence on the feasibility of the implemented EMRs was mixed; the primary studies and reviews found mixed impacts on documentation quality and time; one primary study found downward trends in adverse events, whereas a review found improvements in care quality. Five papers provided information on implementation outcomes such as cost and fidelity, and none reported on the penetration and sustainability of EMRs.

CONCLUSIONS

The body of evidence relating to EMR implementation in mental health settings is limited. Implementation of EMRs could benefit from methods used in general health settings such as co-designing the software and tailoring EMRs to clinical needs and workflows to improve usability and acceptance. Studies in mental health and general health settings rarely focused on long-term implementation outcomes such as penetration and sustainability. Future evaluations of EMRs in all settings should consider long-term impacts to address current knowledge gaps.

Redeveloping the JBI Model of Evidence Based Healthcare

BACKGROUND

In 2005, Pearson et al. presented a developmental framework of evidence-based practice that sought to situate healthcare evidence and its role and use within the complexity of practice settings globally. A decade later, it was deemed timely to re-examine the Model and its component parts to determine whether they remain relevant and a true and accurate reflection of where the evidence-based movement is today.

METHODS

A two-phase process was employed for this project. Phase 1 involved a citation analysis, conducted using the index citation of the original source article on the Joanna Briggs Institute (JBI) Model by Pearson et al. The databases searched were Web of Science and Google Scholar from year of publication (2005) to July 2015. Duplicates and articles in languages other than English were removed, and all results were imported and combined in an Excel spreadsheet for review, coding and interpretation. Phase 2 (model revision) occurred in two parts. Part 1 involved revision of the Model by an internal working group. This revised version of the Model was then subjected to a process of focus group discussion (Part 2) that engaged staff of the Joanna Briggs Collaboration during the 2015 annual general meeting. These data were recorded then transcribed for review and consideration.

RESULTS

The citation analysis revealed that the Model was primarily utilized to conceptualize evidence and evidence-based healthcare, but that language used in relation to concepts within the Model was variable. Equally, the working group and focus group feedback confirmed that there was a need to ensure the language utilized in the Model was internationally appropriate and in line with current international trends. This feedback and analysis informed the revised version of the JBI Model.

CONCLUSION

Based on the citation analysis, working group and focus group feedback the new JBI Model for Evidence Based Healthcare attempts to utilize more internationally appropriate language to detail the intricacies of the relationships between systems and individuals across different settings and the need for contextual localization to enable policy makers and practitioners to make evidence-based decisions at the point of care.

Barriers and Facilitators When Implementing Web-Based Disease Monitoring and Management as a Substitution for Regular Outpatient Care in Pediatric Asthma: Qualitative Survey Study

Background

Despite their potential benefits, many electronic health (eHealth) innovations evaluated in major studies fail to integrate into organizational routines, and the implementation of these innovations remains problematic.

Objective

The purpose of this study was to describe health care professionals’ self-identified perceived barriers and facilitators for the implementation of a Web-based portal to monitor asthmatic children as a substitution for routine outpatient care. Also, we assessed patients’ (or their parents) satisfaction with this eHealth innovation.

Methods

Between April and November 2015, we recruited 76 health care professionals (from 14 hospitals). During a period of 6 months, participants received 3 questionnaires to identify factors that facilitated or impeded the use of this eHealth innovation. Questionnaires for patients (or parents) were completed after the 6-month virtual asthma clinic (VAC) implementation period.

Results

Major perceived barriers included concerns about the lack of structural financial reimbursement for Web-based monitoring, lack of integration of this eHealth innovation with electronic medical records, the burden of Web-based portal use on clinician workload, and altered patient-professional relationship (due to fewer face-to-face contacts). Major perceived facilitators included enthusiastic and active initiators, a positive attitude of professionals toward eHealth, the possibility to tailor care to individual patients (“personalized eHealth”), easily deliverable care according to current guidelines using the VAC, and long-term profit and efficiency.

Conclusions

The implementation of Web-based disease monitoring and management in children is complex and dynamic and is influenced by multiple factors at the levels of the innovation itself, individual professionals, patients, social context, organizational context, and economic and political context. Understanding and defining the barriers and facilitators that influence the context is crucial for the successful implementation and sustainability of eHealth innovations.

Modeling and Predicting Outcomes of eHealth Usage by European Physicians: Multidimensional Approach from a Survey of 9196 General Practitioners

Background

The literature has noted the need to use more advanced methods and models to evaluate physicians’ outcomes in the shared health care model that electronic health (eHealth) proposes.

Objective

The goal of our study was to design and evaluate a predictive multidimensional model of the outcomes of eHealth usage by European physicians.

Methods

We used 2012-2013 survey data from a sample of 9196 European physicians (general practitioners). We proposed and tested two composite indicators of eHealth usage outcomes (internal practices and practices with patients) through 2-stage structural equation modeling. Logistic regression (odds ratios, ORs) to model the predictors of eHealth usage outcomes indicators were also calculated.

Results

European general practitioners who were female (internal practices OR 1.15, 95% CI 1.10-1.20; practices with patients OR 1.19, 95% CI 1.14-1.24) and younger—aged <35 years (internal practices OR 1.14, 95% CI 1.02-1.26; practices with patients OR 1.32, 95% CI 1.13-1.54) and aged 36-45 years (internal practices OR 1.16, 95% CI 1.06-1.28; practices with patients OR 1.21, 95% CI 1.10-1.33)—had a greater propensity toward favorable eHealth usage outcomes in internal practices and practices with patients. European general practitioners who positively valued information and communication technology (ICT) impact on their personal working processes (internal practices OR 5.30, 95% CI 4.73-5.93; practices with patients OR 4.83, 95% CI 4.32-5.40), teamwork processes (internal practices OR 4.19, 95% CI 3.78-4.65; practices with patients OR 3.38, 95% CI 3.05-3.74), and the doctor-patient relationship (internal practices OR 3.97, 95% CI 3.60-4.37; practices with patients OR 6.02, 95% CI 5.43-6.67) had a high propensity toward favorable effects of eHealth usage on internal practices and practices with patients. More favorable eHealth outcomes were also observed for self-employed European general practitioners (internal practices OR 1.33, 95% CI 1.22-1.45; practices with patients OR 1.10, 95% CI 1.03-1.28). Finally, general practitioners who reported that the number of patients treated in the last 2 years had remained constant (internal practices OR 1.08, 95% CI 1.01-1.17) or increased (practices with patients OR 1.12, 95% CI 1.03-1.22) had a higher propensity toward favorable eHealth usage outcomes.

Conclusions

We provide new evidence of predictors (sociodemographic issues, attitudes toward ICT impacts, and working conditions) that explain favorable eHealth usage outcomes. The results highlight the need to develop more specific policies for eHealth usage to address different realities.

What is Important in E-health Interventions for Stroke Rehabilitation? A Survey Study among Patients, Informal Caregivers and Health Professionals

Incorporating user requirements in the design of e-rehabilitation interventions facilitates their implementation. However, insight into requirements for e-rehabilitation after stroke is lacking. This study investigated which user requirements for stroke e-rehabilitation are important to stroke patients, informal caregivers, and health professionals. The methodology consisted of a survey study amongst stroke patients, informal caregivers, and health professionals (physicians, physical therapists and occupational therapists). The survey consisted of statements about requirements regarding accessibility, usability and content of a comprehensive stroke e-health intervention (4-point Likert scale, 1=unimportant/4=important). The mean with standard deviation was the metric used to determine the importance of requirements. Patients (N=125), informal caregivers (N=43), and health professionals (N=105) completed the survey. The mean score of user requirements regarding accessibility, usability and content for stroke e-rehabilitation was 3.1 for patients, 3.4 for informal caregivers and 3.4 for health professionals. Data showed that a large number of user requirements are important and should be incorporated into the design of stroke e-rehabilitation to facilitate their implementation.

Is there an optimum number needed to retrieve to justify inclusion of a database in a systematic review search?

OBJECTIVE

To determine whether calculation of a 'Number Needed to Retrieve' (NNTR) is possible and desirable as a means of evaluating the utility of a database for systematic review.

METHODS

To determine an overall NNTR, eight systematic reviews were tracked to determine how many abstracts were retrieved compared to the number of articles meeting the inclusion criteria. An NNTR was calculated for each database searched to measure the utility of including it in systematic review searches.

RESULTS

Across eight systematic reviews, 17 378 abstracts were reviewed. Of these, 122 met the inclusion criteria for their reviews resulting in an overall NNTR of 142. Individual reviews had an NNTR range of 28-310. Three databases delivered unique results (medline, cinahl and globalhealth). The majority of the included studies appeared in multiple databases. Only five articles were found in a single database.

CONCLUSIONS

This research offers a proof of concept of 'NNTR'. While the eight review NNTRs varied widely, all were consistent with the range initially reported by Booth. Included articles consistently appeared in multiple databases, suggesting that duplicate abstracts should be screened first as these are likely to include highly relevant, high-quality results.

Time to Onset of Sustained Postoperative Pain Relief (SuPPR): Evaluation of a New Systems-level Metric for Acute Pain Management

OBJECTIVES

Prior work on postoperative pain trajectories has examined pain score changes over time using daily averages of pain scores. However, little is known about the time required until patients consistently report minimal postoperative pain.

MATERIALS AND METHODS

We conducted a retrospective cohort study of surgical case data from 7293 adult patients to examine the impact of age, sex, and the type of surgery on the time to sustained postoperative pain relief (SuPPR). We defined SuPPR as the time required until a patient reports the first of multiple (2, 3, 4, or 5 sequential measurements; eg, SuPPR-2, SuPPR-3), uninterrupted, mild pain scores (≤4/10).

RESULTS

Overall, SuPPR times ranged from 3 minutes for SuPPR-2 and 9 minutes for SuPPR-5 to 160.1 hours for SuPPR-2 and 183.1 hours for SuPPR-5. For the SuPPR-2 outcome, the median time to event was 10.9 hours (interquartile range, 3 to 26.1 h) after surgery. For the SuPPR-5 outcomes, the median time to event was 31.5 hours (interquartile range, 17.8 to 54.2 h) after surgery. The peak median difference between 2 sequential SuPPR definitions was between SuPPR-3 and SuPPR-2 at 9 hours, with subsequent decreases to 6.5 hours between SuPPR-4 and SuPPR-3, and 5.2 hours between SuPPR-5 and SuPPR-4. There were statistically different differences across SuPPR-2 through SuPPR-5 definitions by age, sex, and type of surgery.

DISCUSSION

Although additional analyses are necessary, SuPPR may represent a novel method for evaluating acute pain service performance.

Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update)

Background

There is a significant potential for e-health to deliver cost-effective, quality health care, and spending on e-health systems by governments and healthcare systems is increasing worldwide. However, there remains a tension between the use of e-health in this way and implementation. Furthermore, the large body of reviews in the e-health implementation field, often based on one particular technology, setting or health condition make it difficult to access a comprehensive and comprehensible summary of available evidence to help plan and undertake implementation. This review provides an update and re-analysis of a systematic review of the e-health implementation literature culminating in a set of accessible and usable recommendations for anyone involved or interested in the implementation of e-health.

Methods

MEDLINE, EMBASE, CINAHL, PsycINFO and The Cochrane Library were searched for studies published between 2009 and 2014. Studies were included if they were systematic reviews of the implementation of e-health. Data from included studies were synthesised using the principles of meta-ethnography, and categorisation of the data was informed by the Consolidated Framework for Implementation Research (CFIR).

Results

Forty-four reviews mainly from North America and Europe were included. A range of e-health technologies including electronic medical records and clinical decision support systems were represented. Healthcare settings included primary care, secondary care and home care. Factors important for implementation were identified at the levels of the following: the individual e-health technology, the outer setting, the inner setting and the individual health professionals as well as the process of implementation.

Conclusion

This systematic review of reviews provides a synthesis of the literature that both acknowledges the multi-level complexity of e-health implementation and provides an accessible and useful guide for those planning implementation. New interpretations of a large amount of data across e-health systems and healthcare settings have been generated and synthesised into a set of useable recommendations for practice. This review provides a further empirical test of the CFIR and identifies areas where additional research is necessary.

Trial registration

PROSPERO, CRD42015017661

Electronic supplementary material

The online version of this article (doi:10.1186/s13012-016-0510-7) contains supplementary material, which is available to authorized users.

Adoption of e-health technology by physicians: a scoping review

OBJECTIVE

The goal of this scoping review was to summarize the current literature identifying barriers and opportunities that facilitate adoption of e-health technology by physicians.

DESIGN

Scoping review.

SETTING

MEDLINE, EMBASE, and PsycINFO databases as provided by Ovid were searched from their inception to July 2015. Studies captured by the search strategy were screened by two reviewers and included if the focus was on barriers and facilitators of e-health technology adoption by physicians.

RESULTS

Full-text screening yielded 74 studies to be included in the scoping review. Within those studies, eleven themes were identified, including cost and liability issues, unwillingness to use e-health technology, and training and support.

CONCLUSION

Cost and liability issues, unwillingness to use e-health technology, and training and support were the most frequently mentioned barriers and facilitators to the adoption of e-health technology. Government-level payment incentives and privacy laws to protect health information may be the key to overcome cost and liability issues. The adoption of e-health technology may be facilitated by tailoring to the individual physician's knowledge of the e-health technology and the use of follow-up sessions for physicians and on-site experts to support their use of the e-health technology. To ensure the effective uptake of e-health technologies, physician perspectives need to be considered in creating an environment that enables the adoption of e-health strategies.

The preferences of users of electronic medical records in hospitals: quantifying the relative importance of barriers and facilitators of an innovation

Background

Currently electronic medical records (EMRs) are implemented in hospitals, because of expected benefits for quality and safety of care. However the implementation processes are not unproblematic and are slower than needed. Many of the barriers and facilitators of the adoption of EMRs are identified, but the relative importance of these factors is still undetermined. This paper quantifies the relative importance of known barriers and facilitators of EMR, experienced by the users (i.e., nurses and physicians in hospitals).

Methods

A discrete choice experiment (DCE) was conducted among physicians and nurses. Participants answered ten choice sets containing two scenarios. Each scenario included attributes that were based on previously identified barriers in the literature: data entry hardware, technical support, attitude head of department, performance feedback, flexibility of interface, and decision support. Mixed Multinomial Logit analysis was used to determine the relative importance of the attributes.

Results

Data on 148 nurses and 150 physicians showed that high flexibility of the interface was the factor with highest relative importance in their preference to use an EMR. For nurses this attribute was followed by support from the head of department, presence of performance feedback from the EMR and presence of decisions support. While for physicians this ordering was different: presence of decision support was relatively more important than performance feedback and support from the head of department.

Conclusion

Considering the prominent wish of all the intended users for a flexible interface, currently used EMRs only partially comply with the needs of the users, indicating the need for closer incorporation of user needs during development stages of EMRs. The differences in priorities amongst nurses and physicians show that different users have different needs during the implementation of innovations. Hospital management may use this information to design implementation trajectories to fit the needs of various user groups.