Adoption of Electronic Dental Records: Examining the Influence of Practice Characteristics on Adoption in One State

Barriers and facilitators for the implementation of electronic dental record systems: Perspectives from a developing country

INTRODUCTION

The need for dental data in healthcare services and the inadequacy of paper records due to their inherent limitations have led to a shift towards electronic dental record systems (EDR). Implementing EDR comes with numerous barriers and challenges. Therefore, this research was conducted to identify the implementation barriers and facilitators for EDRs.

METHODS

This descriptive-analytical cross-sectional study was conducted on dentists working in public and private clinics in Tehran, Iran. A questionnaire consisting of three sections was designed to collect data on the demographic information of dentists, the barriers in five categories including financial barriers (6 questions), organizational barriers (11 questions), technical barriers (5 questions), personal barriers (3 questions), and ethical and legal barriers (6 questions), as well as facilitators for the implementation of EDR (15 questions) based on the literature, using a five-point Likert scale. 130 dentists from 60 dental clinics participated in the study. The data were analyzed using descriptive statistics (calculating frequency distribution, mean, and standard deviation). The mean scores were classified into four categories based on quartiles from very low importance to very high importance including very low importance (mean ≤ 1.25), low importance (1.25 ≥ mean < 2.5), important (2.5 ≥ mean < 3.75), and very high importance (mean ≥ 3.75). Finally, each of the barriers and facilitators among user dentists and non-user dentists was compared using the Mann-Whitney U test. The data were analyzed using SPSS software.

RESULTS

The findings indicate that dentists consider all barriers and challenges in implementing EDR to be important, and all the proposed facilitators for addressing these challenges to be very important. Among these important barriers are the rapid turnover of managers and policymakers at higher levels (3.69 out of 5) as a personal barrier, legal issues related to electronic records (3.65 out of 5) as an ethical-legal barrier, the lack of necessary standards for data exchange between different systems (3.64 out of 5) as a technical barrier, dentists' limited awareness of the benefits of this system (3.63 out of 5) as a personal barrier, and the lack of suitable legal infrastructure for EDR implementation (3.62 out of 5) as an ethical-legal barrier. Additionally, among the very important facilitators, training dentists and staff on EDR (4.31 out of 5) is noteworthy.

CONCLUSION

To address the important barriers to EDR implementation, including legal-ethical barriers, legal institutions, and regulators must establish relevant laws and regulations to overcome these obstacles. Furthermore, if system users learn about the features, goals, benefits, and positive impact of EDR on their work and gain the necessary awareness, their resistance to changes will decrease, and their interest and readiness to accept EDR will increase.

Influence of Practice Characteristics on the Adoption of Electronic Dental Records in Jeddah, Saudi Arabia

OBJECTIVES

The adoption of electronic dental records (EDRs) is less extensively studied than electronic medical records (EMRs) in Saudi Arabia. Therefore, a multivariate analysis was conducted to calculate the adoption of EDRs and determine the practice characteristics that influence adoption.

METHODS

An online survey was conducted with 220 dental practices in Jeddah from August to December 2021. The questionnaire contained 10 items that measured the adoption of EDRs and identified the region, district, practice characteristics, and practice size. A regression analysis was used to ascertain the relationships between EDR adoption and the predictor variables.

RESULTS

About 93% of the dental practices, we surveyed in Jeddah had adopted EDRs. Public dental practices and large practices were associated with higher rates of adoption (respectively, 97.0%, p = 0.016; 97.8%, p = 0.009). The logistic regression model showed statistically significant results regarding practice characteristics, practice size, and the acceptance of insurance patients. EDR adoption was 89% less likely for private dental practices, 99% less likely for smaller dental practices (≥2 dentists), and 98% less likely in dental practices that did not treat patients with insurance.

CONCLUSIONS

Our study sample showed a high rate of EDR adoption. Among the participants, public practices, large practices, and practices that treat patients with insurance were the most positively inclined toward EDR adoption.

Informational Needs for Dental-Oriented Electronic Health Records from Dentists' Perspectives

INTRODUCTION

Information technology is vital to support dental care services and is yet to be thoroughly investigated. This study aims to assess the dentists' needs and requirements for health records from dental care providers' perspectives.

METHODS

In-depth interviews were conducted with dentists during clinic practices. This qualitative research method involves exploring the information and functions dentists use to obtain information from EHR. The target population is the dental staff interacting with the patients and accessing the electronic health records in the government and private sectors.

RESULTS

Thirty-five dentists were interviewed directly after the treatment session and asked four pre-defined questions, the dentists' needs were collected, and the met and unmet needs were presented. The interview results revealed 42 needs (15 were met and 27 were unmet), with an average of 1.17 needs per session. The information needs were categorized into foreground and background information needs and reported in nine main themes.

DISCUSSION

The interviews were analyzed, and as a result, nine themes were generated: chief complaints and symptoms, medical and health history, medications, visual representations of the problem, treatment procedures, X-ray services, needs related to advanced features, needs related to insurance coverage, and finally, information needs related to the treatment environment. The required information and functions mentioned by dentists in the study emphasize the need for integrated modules for oral and medical care services. Generally, it is evident that dentists have substantial unmet needs, and the desired EHR should have functions that cover all dentists' needs.

CONCLUSION

The study's findings demonstrate gaps between current and desired EHR to serve dentists' needs. Dentists need better access to patient history and medical information, progress notes, and X-rays to provide visualization tools for problems and patient charts. Moreover, essential needs were related to messaging capability, educational tools, availability of tutorial videos, and accessing external resources. Information needs were described and should be considered when designing EHR to meet all dentists' needs.

Accuracy of parent-reported health history in a dental setting

BACKGROUND

Obtaining thorough documentation of a patient's medical history is important for dental care professionals, as oral health is connected intricately to systemic health. The purpose of this study was to assess the accuracy of parent-reported health history for pediatric patients in a dental setting.

METHODS

A retrospective chart review was conducted on 863 patients 17 years and younger. Parent-reported health history was compared with subsequent physician-to-dentist consultations. The most common diagnoses were grouped on the basis of International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, categories.

RESULTS

The sensitivity of parent report of health conditions was highest for reporting mental and behavioral disorders (75.1%; 95% CI, 69.6% to 80.0%), followed by nervous system diseases (63.0%; 95% CI, 47.5% to 76.8%), respiratory conditions (47.9%; 95% CI, 37.6% to 58.4%), congenital conditions (46.3%; 95% CI, 30.7% to 62.6%), and cardiovascular conditions (25.0%; 95% CI, 11.4% to 43.4%) and was lowest for hematologic conditions (12.2%; 95% CI, 4.1% to 26.2%). Parents of children 6 years and older and those with private insurance had higher sensitivity for reporting mental and behavioral conditions than those with children younger than 6 years or having Medicaid (P < .0001). The specificity of parent-reported health conditions ranged from 96.0% for mental and behavioral disorders to 99.8% for hematologic conditions.

CONCLUSIONS

Sensitivity varied widely, showing that parents may be unreliable in their report of children's health histories and that dentists cannot rely solely on parents when obtaining health history.

PRACTICAL IMPLICATIONS

In advocating for patient safety, especially for those with special needs and complex medical conditions, this study supports the use of medical evaluation before dental treatment and for the integration of dental and electronic health records.

Current state of dental informatics in the field of health information systems: a scoping review

Background

Over the past 50 years, dental informatics has developed significantly in the field of health information systems. Accordingly, several studies have been conducted on standardized clinical coding systems, data capture, and clinical data reuse in dentistry.

Methods

Based on the definition of health information systems, the literature search was divided into three specific sub-searches: “standardized clinical coding systems,” “data capture,” and “reuse of routine patient care data.” PubMed and Web of Science were searched for peer-reviewed articles. The review was conducted following the PRISMA-ScR protocol.

Results

A total of 44 articles were identified for inclusion in the review. Of these, 15 were related to “standardized clinical coding systems,” 15 to “data capture,” and 14 to “reuse of routine patient care data.” Articles related to standardized clinical coding systems focused on the design and/or development of proposed systems, on their evaluation and validation, on their adoption in academic settings, and on user perception. Articles related to data capture addressed the issue of data completeness, evaluated user interfaces and workflow integration, and proposed technical solutions. Finally, articles related to reuse of routine patient care data focused on clinical decision support systems centered on patient care, institutional or population-based health monitoring support systems, and clinical research.

Conclusions

While the development of health information systems, and especially standardized clinical coding systems, has led to significant progress in research and quality measures, most reviewed articles were published in the US. Clinical decision support systems that reuse EDR data have been little studied. Likewise, few studies have examined the working environment of dental practitioners or the pedagogical value of using health information systems in dentistry.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-022-02163-9.

Investigation of patients' access to EHR data via smart apps in Chinese Hospitals

Background

Given that China has encouraged EHR usage in hospitals for more than a decade, patients’ access to their own EHR data is still not as widely utilized as expected.

Methods

We cultivated a survey with four categories and field interviews of measures to identify whether hospitals have already released EHR data to patients, inpatients or outpatients, the top EHR release contents and the most popular release software.

Results

Of the 1344 responding hospitals from 30 provinces nationwide, 41.37% of hospitals have already released their EHR data to patients, of which 97.12% are through smart apps. More than 91% of hospitals use WeChat, and 32.37% of hospitals developed their own standalone apps or use vendors’ apps. A total of 54.63% were released to both outpatients and inpatients, and the top release contents were all objective. A rough estimation is made that releasing EHR data to patients via smart apps may save the hospital 15.9 million RMB per year and patients 9.4 million RMB altogether.

Conclusions

EHR data release is believed to bring both patient and hospital cost savings and efficiency gains but is still considered spontaneous and requires legal support and government regulation.

Machine Learning-Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study

Background

With the prevalence of cardiovascular diseases increasing worldwide, early prediction and accurate assessment of heart failure (HF) risk are crucial to meet the clinical demand.

Objective

Our study objective was to develop machine learning (ML) models based on real-world electronic health records to predict 1-year in-hospital mortality, use of positive inotropic agents, and 1-year all-cause readmission rate.

Methods

For this single-center study, we recruited patients with newly diagnosed HF hospitalized between December 2010 and August 2018 at the First Affiliated Hospital of Dalian Medical University (Liaoning Province, China). The models were constructed for a population set (90:10 split of data set into training and test sets) using 79 variables during the first hospitalization. Logistic regression, support vector machine, artificial neural network, random forest, and extreme gradient boosting models were investigated for outcome predictions.

Results

Of the 13,602 patients with HF enrolled in the study, 537 (3.95%) died within 1 year and 2779 patients (20.43%) had a history of use of positive inotropic agents. ML algorithms improved the performance of predictive models for 1-year in-hospital mortality (areas under the curve [AUCs] 0.92-1.00), use of positive inotropic medication (AUCs 0.85-0.96), and 1-year readmission rates (AUCs 0.63-0.96). A decision tree of mortality risk was created and stratified by single variables at levels of high-sensitivity cardiac troponin I (<0.068 μg/L), followed by percentage of lymphocytes (<14.688%) and neutrophil count (4.870×10⁹/L).

Conclusions

ML techniques based on a large scale of clinical variables can improve outcome predictions for patients with HF. The mortality decision tree may contribute to guiding better clinical risk assessment and decision making.

Improving Oral-Systemic Healthcare through the Interoperability of Electronic Medical and Dental Records: An Exploratory Study

OBJECTIVES

Electronic health records (EHRs) are rarely shared among medical and dental providers. The purpose of this study was to assess current information sharing and the value of improved electronic information sharing among physicians and dentists in Germany and the United States.

MATERIALS AND METHODS

A survey was validated and distributed electronically to physicians and dentists at four academic medical centers. Respondents were asked anonymously about EHR use and the medical and dental information most valuable to their practice.

RESULTS

There were 118 responses, a response rate of 23.2%. The majority (63.9%) of respondents were dentists and the remainder were physicians. Most respondents (66.3%) rated the importance of sharing information an 8 or above on a 1-to-10 Likert scale. Dentists rated the importance of sharing clinical information significantly higher than physicians (p = 0.0033). Most (68.5%) providers could recall an instance when access to medical or dental information would have improved patient care. Dentists were significantly more likely to report this than physicians (p = 0.008).

CONCLUSION

Physicians would value a standardized measure of "oral health" in their EHR. Dentists were less likely to find specific medical diagnostic test results of value. Both dentists and physicians agreed that oral-systemic health was important; interoperable EHRs could facilitate information transfer between providers and enhance research on oral-systemic health connections. Both dentists and physicians believed that an interoperable EHR would be useful to practice, but desired information was different between these groups. Refinement of the information needed for shared practice is required.

Impact of big data on oral health outcomes

Biomedical big data amasses from different sources such as electronic health records, health research, wearable devices and social media. Recent advances in data capturing, storage and analysis techniques have facilitated conversion of a wealth of knowledge in biomedical big data into evidence-based actionable plans to enhance population health and well-being. The delay in reaping the benefits of biomedical big data in dentistry is mainly due to the slow adoption of electronic health record systems, unstructured clinical records, tattered communication between data silos and perceiving oral health as a separate entity from general health. Recent recognition of the complex interplay between oral and general health has acknowledged the power of oral health big data to glean new insights on disease prevention and management. This review paper summarizes recent advances, limitations and challenges in biomedical big data in health care with emphasis on oral health and discusses the potential future applications of oral health big data to improve the quality and efficiency of personalized health care.