Dataset Information

Assessing Ghana's eHealth workforce: implications for planning and training.

ABSTRACT:

Background

eHealth-the proficient application of information and communication technology to support healthcare delivery-has been touted as one of the best solutions to address quality and accessibility challenges in healthcare. Although eHealth could be of more value to health systems in low- and middle-income countries (LMICs) where resources are limited, identification of a competent workforce which can develop and maintain eHealth systems is a key barrier to adoption. Very little is known about the actual or optimal states of the eHealth workforce needs of LMICs. The objective of this study was to develop a framework to characterize and assess the eHealth workforce of hospitals in LMICs.

Methods

To characterize and assess the sufficiency of the workforce, we designed this study in twofold. First, we developed a general framework to categorize the eHealth workforce at any LMIC setting. Second, we combined qualitative data, using semi-structured interviews and the Workload Indicator of Staffing Needs (WISN) to assess the sufficiency of the eHealth workforce in selected hospitals in a LMIC setting like Ghana.

Results

We surveyed 76 (60%) of the eHealth staff from three hospitals in Ghana-La General Hospital, University of Ghana Hospital, and Greater Accra Regional Hospital. We identified two main eHealth cadres, technical support/information technology (IT) and health information management (HIM). While the HIM cadre presented diversity in expertise, the IT group was dominated by training in Science (42%) and Engineering (55%), and the majority (87%) had at least a bachelor's degree. Health information clerk (32%), health information officer (25%), help desk specialist (20%), and network administrator (11%) were the most dominant roles. Based on the WISN assessment, the eHealth workforce at all the surveyed sites was insufficient. La General and University of Ghana were operating at 10% of required IT staff capacity, while Ridge was short by 42%.

Conclusions

We have developed a framework to characterize and assess the eHealth workforce in LMICs. Applying it to a case study in Ghana has given us a better understanding of potential eHealth staffing needs in LMICs, while providing the quantitative basis for building the requisite human capital to drive eHealth initiatives. Educators can also use our results to explore competency gaps and refine curricula for burgeoning training programs. The findings of this study can serve as a springboard for other LMICs to assess the effects of a well-trained eHealth workforce on the return on eHealth investments.

SUBMITTER: Ogoe HA

PROVIDER: S-EPMC6260724 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Assessing Ghana's eHealth workforce: implications for planning and training.

Ogoe Henry A HA Asamani James A JA Hochheiser Harry H Douglas Gerald P GP

Human resources for health 20181127 1

<h4>Background</h4>eHealth-the proficient application of information and communication technology to support healthcare delivery-has been touted as one of the best solutions to address quality and accessibility challenges in healthcare. Although eHealth could be of more value to health systems in low- and middle-income countries (LMICs) where resources are limited, identification of a competent workforce which can develop and maintain eHealth systems is a key barrier to adoption. Very little is ...[more]

PMID: 30482223

Similar Datasets

Project description:BackgroundeHealth is the use of information and communication technologies to enable and improve health and health care services. It is crucial that medical students receive adequate training in eHealth as they will work in clinical environments that are increasingly being enabled by technology. This trend is especially accelerated by the COVID-19 pandemic as it complicates traditional face-to-face medical consultations and highlights the need for innovative approaches in health care.ObjectiveThis review aims to evaluate the extent and nature of the existing literature on medical student training in eHealth. In detail, it aims to examine what this education consists of, the barriers, enhancing factors, and propositions for improving the medical curriculum. This review focuses primarily on some key technologies such as mobile health (mHealth), the internet of things (IoT), telehealth, and artificial intelligence (AI).MethodsSearches were performed on 4 databases, and articles were selected based on the eligibility criteria. Studies had to be related to the training of medical students in eHealth. The eligibility criteria were studies published since 2014, from a peer-reviewed journal, and written in either English or French. A grid was used to extract and chart data.ResultsThe search resulted in 25 articles. The most studied aspect was mHealth. eHealth as a broad concept, the IoT, AI, and programming were least covered. A total of 52% (13/25) of all studies contained an intervention, mostly regarding mHealth, electronic health records, web-based medical resources, and programming. The findings included various barriers, enhancing factors, and propositions for improving the medical curriculum.ConclusionsTrends have emerged regarding the suboptimal present state of eHealth training and barriers, enhancing factors, and propositions for optimal training. We recommend that additional studies be conducted on the following themes: barriers, enhancing factors, propositions for optimal training, competencies that medical students should acquire, learning outcomes from eHealth training, and patient care outcomes from this training. Additional studies should be conducted on eHealth and each of its aspects, especially on the IoT, AI, programming, and eHealth as a broad concept. Training in eHealth is critical to medical practice in clinical environments that are increasingly being enabled by technology. The need for innovative approaches in health care during the COVID-19 pandemic further highlights the relevance of this training.

Project description:BackgroundFor health care services to address the health care needs of populations and respond to changes in needs over time, workforces must be planned. This requires quantitative models to estimate future workforce requirements that take account of population size, oral health needs, evidence-based approaches to addressing needs, and methods of service provision that maximize productivity. The aim of this scoping review was to assess whether and how these 4 elements contribute to existing models of oral health workforce planning.MethodsA scoping review was conducted. MEDLINE, Embase, HMIC, and EconLit were searched, all via OVID. Additionally, gray literature databases were searched and key bodies and policy makers contacted. Workforce planning models were included if they projected workforce numbers and were specific to oral health. No limits were placed on country. A single reviewer completed initial screening of abstracts; 2 independent reviewers completed secondary screening and data extraction. A narrative synthesis was conducted.ResultsA total of 4,009 records were screened, resulting in 42 included articles detailing 47 models. The workforce planning models varied significantly in their use of data on oral health needs, evidence-based services, and provider productivity, with most models relying on observed levels of service utilization and demand.ConclusionsThis review has identified quantitative workforce planning models that aim to estimate future workforce requirements. Approaches to planning the oral health workforce are not always based on deriving workforce requirements from population oral health needs. In many cases, requirements are not linked to population needs, while in models where needs are included, they are constrained by the existence and availability of the required data. It is critical that information systems be developed to effectively capture data necessary to plan future oral health care workforces in ways that relate directly to the needs of the populations being served.Knowledge transfer statementPolicy makers can use the results of this study when making decisions about the planning of oral health care workforces and about the data to routinely collect within health services. Collection of suitable data will allow for the continual improvement of workforce planning, leading to a responsive health service and likely future cost savings.

Project description:ObjectiveResearch suggests recently graduated urology residents do not feel ready for independent practice. We conducted a study to determine if Accreditation Council for Graduate Medical Education (ACGME) minimum case requirements, resident case logs, and graduating resident perceived readiness for practice are aligned with the procedural demand and needs of the current urology workforce.DesignCorrelative study comparing the association between (1) workforce demand and ACGME case requirements, and (2) workforce demand and perceived resident competency. Three distinct datasets were used; (1) the 2017 Medicare Part B National Summary Data File; (2) the 2017 National Data Report published by the ACGME; and (3) a graduating resident survey from Okhunov et al. SETTING: N/A.ParticipantsN/A.ResultsIn 2017, there were a total of 6,784,696 urologic cases performed through Medicare. We found nonsignificant positive associations between resident case logs (rho = 0.16, p = 0.5784), ACGME minimum procedure requirements (rho = 0.42, p = 0.1255), and Medicare procedural demand. Our 15 index procedures accounted for 21.1% (n = 1,431,775) of all Medicare cases, with a median number of 7706 procedures. Endopyelotomy was the least common procedure (n = 98), while cystoscopy was the most common (n = 980,623). Medicare case volume was positively correlated with graduating residents' procedural confidence (r = 0.86, p < 0.0001). We identified four categories with varied alignment of training and demand: (1) high volume and high confidence, (2) high volume and low confidence, (3) low volume and high confidence, and (4) low volume and low confidence.ConclusionsOptimizing urology residency training is time-sensitive and important. Using national Medicare data coupled with recently graduated urology resident survey results, we provide a guiding framework for improving the alignment of training with workforce demand. Informed by these results, we recommend altering training requirements to reflect these needs.

Dataset Information

Assessing Ghana's eHealth workforce: implications for planning and training.

Background

Methods

Results

Conclusions

Publications

Assessing Ghana's eHealth workforce: implications for planning and training.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets