METHODS: We used data spanning 2010-2018 from children aged 2-12 years within the Chicago Area Patient-Centered Outcomes Research Network-an electronic health record network. Four clinical systems comprised the derivation sample and a fifth the validation sample. Body mass index, blood pressure, cholesterol, and blood glucose were categorized as ideal, intermediate, and poor using clinical measurements, laboratory readings, and International Classification of Diseases diagnosis codes and summed for an overall CVH score. Group-based trajectory modeling was used to create CVH score trajectories which were assessed for classification accuracy in the validation sample.
RESULTS: Using data from 122,363 children (47% female, 47% non-Hispanic White) three trajectories were identified: 59.5% maintained high levels of clinical CVH, 23.4% had high levels of CVH that declined, and 17.1% had intermediate levels of CVH that further declined with age. A similar classification emerged when the trajectories were fitted in the validation sample.
CONCLUSIONS: Stratification of CVH was present by age 2, implicating the need for early life and preconception prevention strategies.
RESULTS: Quality Implementation Framework (QIF) was adopted to develop the breast cancer module as part of the in-house EMR system used at UMMC, called i-Pesakit©. The completion of the i-Pesakit© Breast Cancer Module requires management of clinical data electronically, integration of clinical data from multiple internal clinical departments towards setting up of a research focused patient data governance model. The 14 QIF steps were performed in four main phases involved in this study which are (i) initial considerations regarding host setting, (ii) creating structure for implementation, (iii) ongoing structure once implementation begins, and (iv) improving future applications. The architectural framework of the module incorporates both clinical and research needs that comply to the Personal Data Protection Act.
CONCLUSION: The completion of the UMMC i-Pesakit© Breast Cancer Module required populating EMR including management of clinical data access, establishing information technology and research focused governance model and integrating clinical data from multiple internal clinical departments. This multidisciplinary collaboration has enhanced the quality of data capture in clinical service, benefited hospital data monitoring, quality assurance, audit reporting and research data management, as well as a framework for implementing a responsive EMR for a clinical and research organization in a typical middle-income country setting. Future applications include establishing integration with external organization such as the National Registration Department for mortality data, reporting of institutional data for national cancer registry as well as data mining for clinical research. We believe that integration of multiple clinical visit data sources provides a more comprehensive, accurate and real-time update of clinical data to be used for epidemiological studies and audits.
METHODS: Convenience sampling was employed for data collection in three government hospitals for 7 months. A standardized effectiveness survey for EHR systems was administered to primary health care providers (specialists, medical officers, and nurses) as they participated in medical education programs. Empirical data were assessed by employing partial least squares-structural equation modeling for hypothesis testing.
RESULTS: The results demonstrated that knowledge quality had the highest score for predicting performance and had a large effect size, whereas system compatibility was the most substantial system quality component. The findings indicated that EHR systems supported the clinical tasks and workflows of care providers, which increased system quality, whereas the increased quality of knowledge improved user performance.
CONCLUSION: Given these findings, knowledge quality and effective use should be incorporated into evaluating EHR system effectiveness in health institutions. Data mining features can be integrated into current systems for efficiently and systematically generating health populations and disease trend analysis, improving clinical knowledge of care providers, and increasing their productivity. The validated survey instrument can be further tested with empirical surveys in other public and private hospitals with different interoperable EHR systems.
METHODS: Currently available indicators from both household and facility surveys were collated through publicly available global databases and respective survey instruments. We then developed a suite of potential indicators and associated data points for the 45 WHO Essential Interventions spanning preconception to newborn care. Four types of performance indicators were identified (where applicable): process (i.e. coverage) and outcome (i.e. impact) indicators for both screening and treatment/prevention. Indicators were evaluated by an international expert panel against the eRegistries indicator evaluation criteria and further refined based on feedback by the eRegistries technical team.
RESULTS: Of the 45 WHO Essential Interventions, only 16 were addressed in any of the household survey data available. A set of 216 potential indicators was developed. These indicators were generally evaluated favourably by the panel, but difficulties in data ascertainment, including for outcome measures of cause-specific morbidity and mortality, were frequently reported as barriers to the feasibility of indicators. Indicators were refined based on feedback, culminating in the final list of 193 total unique indicators: 93 for preconception and antenatal care; 53 for childbirth and postpartum care; and 47 for newborn and small and ill baby care.
CONCLUSIONS: Large gaps exist in the availability of information currently collected to support the implementation of the WHO Essential Interventions. The development of this suite of indicators can be used to support the implementation of eRegistries and other data platforms, to ensure that data are utilised to support evidence-based practice, facilitate measurement and accountability, and improve maternal and child health outcomes.
AREAS COVERED: We searched multiple databases, including PubMed, Web of Knowledge, Scopus, ACM, Embase, IEEE and Ingenta. We explored various evaluation aspects of MD and EMR to gain a better understanding of their complex integration. We reviewed numerous risk management and assessment frameworks related to MD and EMR security aspects and mitigation controls and then identified their common evaluation aspects. Our review indicated that previous evaluation frameworks assessed MD and EMR independently. To address this gap, we proposed an evaluation framework based on the sociotechnical dimensions of health information systems and risk assessment approaches for MDs to evaluate MDI-EMR integratively.
EXPERT OPINION: The emergence of MDI-EMR cyber threats requires appropriate evaluation tools to ensure the safe development and application of MDI-EMR. Consequently, our proposed framework will continue to evolve through subsequent validations and refinements. This process aims to establish its applicability in informing stakeholders of the safety level and assessing its effectiveness in mitigating risks for future improvements.
OBJECTIVE: To measure factors associated with mHealth adoption among primary care physicians (PCPs) in Malaysia.
METHODS: A cross-sectional study using a self-administered questionnaire was conducted among PCPs. The usage of mHealth apps by the PCPs has divided into the use of mHealth apps to support PCPs' clinical work and recommendation of mHealth apps for patient's use. Factors associated with mHealth adoption were analysed using multivariable logistic regression.
RESULTS: Among 217 PCPs in the study, 77.0% used mHealth apps frequently for medical references, 78.3% medical calculation and 30.9% interacting with electronic health records (EHRs). Only 22.1% of PCPs frequently recommended mHealth apps to patients for tracking health information, 22.1% patient education and 14.3% use as a medical device. Performance expectancy and facilitating conditions were associated with mHealth use for medical references. Family medicine trainees, working in a government practice and performance expectancy were the facilitators for the use of mHealth apps for medical calculation. Internet connectivity, performance expectancy and use by colleagues were associated with the use of mHealth with EHR. Performance expectancy was associated with mHealth apps' recommendation to patients to track health information and provide patient education.
CONCLUSIONS: PCPs often used mHealth apps to support their clinical work but seldom recommended mHealth apps to their patients. Training for PCPs is needed on the appraisal and knowledge of the mHealth apps for patient use.
METHODS: We used a mixed-method design to evaluate how participants used the smartphone diary tool and their perspectives on usability. Participants were high cardiovascular-risk patients recruited from a primary care clinic and used the tool for a week. We measured usability with the System Usability Scale (SUS) questionnaire and interviewed participants to explore utility and usability issues.
RESULTS: The information diary was available in three languages and tested with 24 participants. The mean SUS score was 69.8 ± 12.9. Five themes related to utility were: IDP functions as a health information diary; supporting discussion of health information with doctors; wanting a feedback function about credible information; increasing awareness of the need to appraise information; and wanting to compare levels of trust with other participants or experts. Four themes related to usability were: ease of learning and use; confusion about selecting the category of information source; capturing offline information by uploading photos; and recording their level of trust.
CONCLUSION: We found that the smartphone diary can be used as a research instrument to record relevant examples of information exposure. It potentially modifies how people seek and appraise topic-specific health information.
Materials and Methods: A total of thirty patients among all gynecology inpatients who were planned for TLH with or without BSO with controlled medical diseases, normal preoperative investigations, and uncomplicated surgery were recruited from January 2014 to December 2016. Data were collected from electronic medical records. Postoperatively, patients who fulfilled the selection criteria were discharged within 24 h and were followed up at 6 weeks and 3 months postsurgery. The results were presented as frequency with percentage and mean standard deviation.
Results: All patients who had uncomplicated surgery and blood loss <1 l with no early postoperative complications were discharged within 24 h. They had a pain score of < 3 and were able to ambulate and tolerated orally well. None of these patients who were discharged 24 h postsurgery required readmissions. During follow-up, there were no reported complications such as persistent pain, wound infection, or herniation.
Conclusion: Twenty-four hours' discharge post-TLH with or without BSO is feasible and safe if the selection process is adhered to.
METHODS: In 14 Central England general practices, a novel case-finding tool (Familial Hypercholetserolaemia Case Ascertainment Tool, FAMCAT1) was applied to the electronic health records of 86 219 patients with cholesterol readings (44.5% of total practices' population), identifying 3375 at increased risk of FH. Of these, a cohort of 336 consenting to completing Family History Questionnaire and detailed review of their clinical data, were offered FH genetic testing in primary care.
RESULTS: Genetic testing was completed by 283 patients, newly identifying 16 with genetically confirmed FH and 10 with variants of unknown significance. All 26 (9%) were recommended for referral and 19 attended specialist assessment. In a further 153 (54%) patients, the test suggested polygenic hypercholesterolaemia who were managed in primary care. Total cholesterol and low-density lipoprotein-cholesterol levels were higher in those patients with FH-causing variants than those with other genetic test results (p=0.010 and p=0.002).
CONCLUSION: Electronic case-finding and genetic testing in primary care could improve identification of FH; and the better targeting of patients for specialist assessment. A significant proportion of patients identified at risk of FH are likely to have polygenic hypercholesterolaemia. There needs to be a clearer management plan for these individuals in primary care.
TRIAL REGISTRATION NUMBER: NCT03934320.