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Health providers' readiness for electronic health records adoption: A cross-sectional study of two hospitals in northern Ghana.

ABSTRACT: INTRODUCTION:Electronic Health Records are receiving considerable attention as a valuable tool for managing clinical information. Despite the prospects of Electronic Health Records in developing countries, many pre-implementation assessments target organizational, managerial, and infrastructural readiness, but barely include a detailed examination of health provider readiness. Meanwhile, health provider readiness is a critical success factor for electronic health records in settings where the majority of the workforce is less likely to have basic computer skills. We sought to assess the readiness of health providers for electronic health records in Ghana. MATERIALS AND METHOD:An institutional-based cross-sectional study was conducted among 350 health providers in northern Ghana from June-September 2019. Data were collected using a modified questionnaire on provider readiness. The mean overall readiness was calculated for each respondent. Providers with readiness score below the overall mean score were categorized as not being ready while those at or above the mean score were considered ready. Multiple linear regression was conducted to determine the factors that determine provider readiness. RESULTS:Two hundred and nine health providers responded to the questionnaire (59.7 response rate). The mean overall readiness was 3.61 (SD = .76), mean core readiness was 3.74 (SD = .80), and mean engagement readiness was 3.47 (SD = .67). Using the average overall readiness score as the cut-off for determining being ready and not ready for electronic health records, overall readiness was 54.9%, core readiness was 67.2%, while engagement readiness was 43.1%. Age, sex, old employees compared to new employees, computer literacy, and knowledge of electronic health records were significant determinants of health providers' readiness to adopt electronic health records. CONCLUSION:We observed that health providers were marginally ready for electronic health records adoption. While participants might have expressed dissatisfaction with paper-based records and expressed a desire for electronic health records, they expressed fear of the potential impact of computerized records. We proposed a robust informatics curriculum and capacity building workshops for improving provider readiness for electronic health records.

SUBMITTER: Abdulai AF

PROVIDER: S-EPMC7271985 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Health providers' readiness for electronic health records adoption: A cross-sectional study of two hospitals in northern Ghana.

Abdulai Abdul-Fatawu AF Adam Fuseini F

PloS one 20200604 6

<h4>Introduction</h4>Electronic Health Records are receiving considerable attention as a valuable tool for managing clinical information. Despite the prospects of Electronic Health Records in developing countries, many pre-implementation assessments target organizational, managerial, and infrastructural readiness, but barely include a detailed examination of health provider readiness. Meanwhile, health provider readiness is a critical success factor for electronic health records in settings wher ...[more]

PMID: 32497074

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Project description:BackgroundThe adoption of an electronic health record (EHR) in the healthcare system has the potential to make healthcare service delivery effective and efficient by providing accurate, up-to-date, and complete information. Despite its great importance, the adoptions of EHR in low-income country settings, like Ethiopia, were lagging and increasingly failed. Assessing the readiness of stakeholders before the actual adoption of EHR is considered the prominent solution to tackle the problem. However, little is known about healthcare providers' EHR readiness in this study setting. Accordingly, this research was conducted aiming at examining healthcare providers' readiness for EHR adoption and associated factors in southwestern Ethiopia.MethodsAn institutional-based cross-sectional study was conducted from September 1 to October 30, 2021. A total of 423 healthcare providers working in public hospitals were selected using a simple random sampling technique. Multivariable logistic regression was fitted to identify determinant factors of overall healthcare providers' readiness after the other covariates were controlled.ResultIn this study, the overall good readiness level of EHR adoption was 52.8% (n = 204) [95% CI of 47.9% to 56.6%]. Age, computer literacy, computer access at health facilities, attitude towards EHRs, awareness about EHRs, perceived benefit, and perceived technology self-efficacy were significantly associated with the overall health care providers' readiness for the adoption of EHR using a cut point of P-value less than 0.05.ConclusionAround half of the respondents had a good level of overall healthcare providers' readiness for the adoption of EHR which was considered inadequate. This finding implied that a huge effort is required to improve readiness before the actual implementation of EHRs. The finding implied that younger-aged groups were more ready for such technology which in turn implied; the older one needs more concern. Enhancing computer literacy, confidence building to raise self-efficacy of such technology, addressing the issue of computer availability at health facilities, building a positive attitude, awareness campaign of EHR, and recognizing the usefulness of such systems were the necessary measures to improve EHR readiness in this setting. Additionally, further studies are recommended to encompass all types of EHR readiness such as organizational readiness, technology readiness, societal readiness, and so on. Additionally, exploring the healthcare provider opinion with qualitative study and extending the proposed study to other implementation settings are recommended to be addressed by future works.

Project description:BackgroundFederal initiatives are underway that provide physicians with financial incentives for meaningful use (MU) of electronic health records (EHRs) and assistance to purchase and implement EHRs.ObjectiveWe sought to examine readiness and interest in MU among primary care physicians and specialists, and identify factors that may affect their readiness to obtain MU incentives.Design/participantsWe analyzed 4 years of data (2008-2011) from the National Ambulatory Medical Care Survey (NAMCS) Electronic Medical Record (EMR) Supplement, an annual cross-sectional nationally representative survey of non-federally employed office-based physicians.Main measuresSurvey-weighted EHR adoption rates, potential to meet selected MU criteria, and self-reported intention to apply for MU incentives. We also examined the association between physician and practice characteristics and readiness for MU.Key resultsThe overall sample consisted of 10,889 respondents, with weighted response rates of 62 % (2008); 74 % (2009); 66 % (2010); and 61 % (2011). Primary care physicians' adoption of EHRs with the potential to meet MU nearly doubled from 2009 to 2011 (18 % to 38 %, p<0.01), and was significantly higher than specialists (19 %) in 2011 (p<0.01). In 2011, half of physicians (52 %) expressed their intention to apply for MU incentives; this did not vary by specialty. Multivariate analyses report that EHR adoption was significantly higher in both 2010 and 2011 compared to 2009, and primary care physicians and physicians working in larger or multi-specialty practices or for HMOs were more likely to adopt EHRs with the potential to meet MU.ConclusionsPhysician EHR adoption rates increased in advance of MU incentive payments. Although interest in MU incentives did not vary by specialty, primary care physicians had significantly higher rates of adopting EHRs with the potential to meet MU. Addressing barriers to EHR adoption, which may vary by specialty, will be important to enhancing coordination of care.

Project description:BackgroundIn England, almost all general practices (GPs) have implemented GP online services such as electronic personal health records (ePHRs) that allow people to schedule appointments, request repeat prescriptions, and access parts of their medical records. The overall adoption rate of GP online services has been low, reaching just 28% in October 2019. In a previous study, Abd-Alrazaq et al adopted a model to assess the factors that influence patients' use of GP online services in England. According to the previous literature, the predictive power of the Abd-Alrazaq model could be improved by proposing new associations between the existing variables in the model.ObjectiveThis study aims to improve the predictive power of the Abd-Alrazaq model by proposing new relationships between the existing variables in the model.MethodsThe Abd-Alrazaq model was amended by proposing new direct, mediating, moderating, and moderated mediating effects. The amended model was examined using data from a previous study, which were collected by a cross-sectional survey of a convenience sample of 4 GPs in West Yorkshire, England. Structural equation modeling was used to examine the theoretical model and hypotheses.ResultsThe new model accounted for 53% of the variance in performance expectancy (PE), 76% of the variance in behavioral intention (BI), and 49% of the variance in use behavior (UB). In addition to the significant associations found in the previous study, this study found that social influence (SI) and facilitating conditions (FCs) are associated with PE directly and BI indirectly through PE. The association between BI and UB was stronger for younger women with higher levels of education, income, and internet access. The indirect effects of effort expectancy (EE), perceived privacy and security (PPS), and SI on BI were statistically stronger for women without internet access, patients with internet access, and patients without internet access, respectively. The indirect effect of PPS on BI was stronger for patients with college education or diploma than for those with secondary school education and lower, whereas the indirect effect of EE on BI was stronger for patients with secondary school education or lower than for those with college education or a diploma.ConclusionsThe predictive power of the Abd-Alrazaq model improved by virtue of new significant associations that were not examined before in the context of ePHRs. Further studies are required to validate the new model in different contexts and to improve its predictive power by proposing new variables. The influential factors found in this study should be considered to improve patients' use of ePHRs.

Project description:BackgroundThe last few decades have witnessed significant advances in the development of digital tools and applications for mental health care. Despite growing evidence for their effectiveness, acceptance and use of these tools in clinical practice remain low. Hence, a validated and easy-to-use instrument for assessing professionals' readiness to adopt eMental health (EMH) is necessary to gain further insights into the process of EMH adoption and facilitate future research on this topic.ObjectiveThe aim of this study is to develop and validate an instrument for assessing mental health care professionals' readiness to adopt EMH.MethodsItem generation was guided by literature and inputs from mental health care professionals and experts in survey development. Exploratory factor analyses were conducted on an initial set of 29 items completed by a sample of mental health care professionals (N=432); thereafter, the scale was reduced to 15 items in an iterative process. The factor structure thus obtained was subsequently tested using a confirmatory factor analysis with a second sample of mental health care professionals (N=363). The internal consistency, convergent validity, and predictive validity of the eMental Health Adoption Readiness (eMHAR) Scale were assessed.ResultsExploratory factor analysis resulted in a 3-factor solution with 15 items. The factors were analyzed and labeled as perceived benefits and applicability of EMH, EMH proactive innovation, and EMH self-efficacy. These factors were confirmed through a confirmatory factor analysis. The total scale and subscales showed a good internal consistency (Cronbach α=.73-.88) along with acceptable convergent and predictive relationships with related constructs.ConclusionsThe constructed eMHAR Scale showed a conceptually interpretable 3-factor structure having satisfactory characteristics and relationships with relevant concepts. Its ease of use allows for quick acquisition of data that can contribute to understanding and facilitating the process of adoption of EMH by clinical professionals.

Project description:BACKGROUND: Previous studies regarding the use of information technologies (IT) specifically among pediatricians and other physicians who treat children are lacking. As such, the objective of this study is to examine the use of electronic health record (EHR) systems and other IT applications among pediatricians and other child health providers (CHPs) in Florida. METHODS: We focus on pediatricians and other CHPs who responded to a state-wide physician survey of IT use. CHPs included general pediatricians, pediatric sub-specialists, and family physicians who self-reported a practice composition of at least 20% children. We compared general pediatricians to other CHPs and all CHPs (including pediatricians) to other physicians with respect to computer and internet availability, and to the use of personal digital assistants and EHRs. Those with an EHR were also compared regarding the availability of key functions available in their system. Statistical analyses included chi-square analysis and logistic regression models which controlled for numerous factors. RESULTS: A total of 4,203 surveys (28.2% response) including 1,021 CHPs, were returned. General pediatricians (13.7%) were significantly less likely to be using an EHR than both CHP family physicians (26.1%) and pediatric sub-specialists (29.6%; p < .001). In multivariate analysis, only general pediatricians were significantly less likely than other physicians to indicate the use of an EHR system (OR = .43; 95% C.I. = .29 - .64). Overall, CHPs were less likely to have key functions available in their EHR system including electronic prescribing (53.3% vs. 61.9%; p = .028), and electronic order entry (47.7% vs. 57.2%; p = .017) among others. General pediatricians and pediatric sub-specialists frequently lagged behind CHP family physicians with respect to key EHR functions. In contrast, CHPs had growth charts (51.3% vs. 24.0%; p < .001) and weight-based dosing functions (35.5% vs.22.7%; p < .001) more frequently than others. CONCLUSION: Physicians caring for children, and especially pediatricians, in Florida, are significantly slower than other doctors to adopt EHRs, and important electronic patient safety functionalities, into their office practices.

Project description:ObjectivesTo evaluate the implementation and adoption of the NHS detailed care records service in "early adopter" hospitals in England.DesignTheoretically informed, longitudinal qualitative evaluation based on case studies.Setting12 "early adopter" NHS acute hospitals and specialist care settings studied over two and a half years.Data sourcesData were collected through in depth interviews, observations, and relevant documents relating directly to case study sites and to wider national developments that were perceived to impact on the implementation strategy. Data were thematically analysed, initially within and then across cases. The dataset consisted of 431 semistructured interviews with key stakeholders, including hospital staff, developers, and governmental stakeholders; 590 hours of observations of strategic meetings and use of the software in context; 334 sets of notes from observations, researchers' field notes, and notes from national conferences; 809 NHS documents; and 58 regional and national documents.ResultsImplementation has proceeded more slowly, with a narrower scope and substantially less clinical functionality than was originally planned. The national strategy had considerable local consequences (summarised under five key themes), and wider national developments impacted heavily on implementation and adoption. More specifically, delays related to unrealistic expectations about the capabilities of systems; the time needed to build, configure, and customise the software; the work needed to ensure that systems were supporting provision of care; and the needs of end users for training and support. Other factors hampering progress included the changing milieu of NHS policy and priorities; repeatedly renegotiated national contracts; different stages of development of diverse NHS care records service systems; and a complex communication process between different stakeholders, along with contractual arrangements that largely excluded NHS providers. There was early evidence that deploying systems resulted in important learning within and between organisations and the development of relevant competencies within NHS hospitals.ConclusionsImplementation of the NHS Care Records Service in "early adopter" sites proved time consuming and challenging, with as yet limited discernible benefits for clinicians and no clear advantages for patients. Although our results might not be directly transferable to later adopting sites because the functionalities we evaluated were new and untried in the English context, they shed light on the processes involved in implementing major new systems. The move to increased local decision making that we advocated based on our interim analysis has been pursued and welcomed by the NHS, but it is important that policymakers do not lose sight of the overall goal of an integrated interoperable solution.

Dataset Information

Health providers' readiness for electronic health records adoption: A cross-sectional study of two hospitals in northern Ghana.

Publications

Health providers' readiness for electronic health records adoption: A cross-sectional study of two hospitals in northern Ghana.

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