Implementation of a cloud-based electronic medical record for maternal and child health in rural Kenya

Background Complete and timely health information is essential to inform public health decision-making for maternal and child health, but is often lacking in resource-constrained settings. Electronic medical record (EMR) systems are increasingly being adopted to support the delivery of health care, and are particularly amenable to maternal and child health services. An EMR system could enable the mother and child to be tracked and monitored throughout maternity shared care, improve quality and completeness of data collected and enhance sharing of health information between outpatient clinic and the hospital, and between clinical and public health services to inform decision-making. Methods This study implemented a novel cloud-based electronic medical record system in a maternal and child health outpatient setting in Western Kenya between April and June 2013 and evaluated its impact on improving completeness of data collected by clinical and public health services. The impact of the system was assessed using a two-sample test of proportions pre- and post-implementation of EMR-based data verification. Results Significant improvements in completeness of the antenatal record were recorded through implementation of EMR-based data verification. A difference of 42.9% in missing data (including screening for hypertension, tuberculosis, malaria, HIV status or ART status of HIV positive women) was recorded pre- and post- implementation. Despite significant impact of EMR-based data verification on data completeness, overall screening rates in antenatal care were low. Conclusion This study has shown that EMR-based data verification can improve the completeness of data collected in the patient record for maternal and child health. A number of issues, including data management and patient confidentiality, must be considered but significant improvements in data quality are recorded through implementation of this EMR model

Toward a framework for data quality in cloud-based health information system

This Cloud computing is a promising platform for health information systems in order to reduce costs and improve accessibility. Cloud computing represents a shift away from computing being purchased as a product to be a service delivered over the Internet to customers. Cloud computing paradigm is becoming one of the popular IT infrastructures for facilitating Electronic Health Record (EHR) integration and sharing. EHR is defined as a repository of patient data in digital form. This record is stored and exchanged securely and accessible by different levels of authorized users. Its key purpose is to support the continuity of care, and allow the exchange and integration of medical information for a patient. However, this would not be achieved without ensuring the quality of data populated in the healthcare clouds as the data quality can have a great impact on the overall effectiveness of any system. The assurance of the quality of data used in healthcare systems is a pressing need to help the continuity and quality of care. Identification of data quality dimensions in healthcare clouds is a challenging issue as data quality of cloud-based health information systems arise some issues such as the appropriateness of use, and provenance. Some research proposed frameworks of the data quality dimensions without taking into consideration the nature of cloud-based healthcare systems. In this paper, we proposed an initial framework that fits the data quality attributes. This framework reflects the main elements of the cloud-based healthcare systems and the functionality of EHR

Effectiveness of User Centered Design for Optimizing an Electronic Documentation Form

Problem. The electronic form used by lactation consultants to document assessment findings, interventions, plans and recommendations, did not meet user’s requirements. Purpose: The purpose of this project was to evaluate the effect of optimization through a User Centered Design (UCD) process on information quality, use and user satisfaction. Goals. The goals were to provide information technology (IT) support for the organization’s Baby Friendly initiative and to support collaborative, consistent messaging for breastfeeding families which could, in turn, support exclusive breast milk feeding. Exclusive breast milk feeding is a population health initiative that could positively impact the triple aim of better care, lower costs and better health. Objectives. Information quality, use and user satisfaction affect user adoption and acceptance of IT solutions. The objective of this project was to test the effectiveness of UCD on optimization by measuring the increase in information quality, use and user satisfaction after implementation of an optimized electronic lactation assessment. Plan. Stakeholders were identified and the electronic form was optimized through UCD. A pre-test/post-test quasi-experimental design was chosen to measure the effect of optimization. Instruments included a modified version of the System and Use Assessment Survey (AHRQ, n.d.), a chart audit tool and an electronic data warehouse use query. IRB approval was obtained from COMIRB and Regis University. The pre and post data collection periods were each six weeks in length, allowing for a two week chart audit period and four week survey. The intervention was implemented after the close of the pre-test period. Clinical users were educated following the organization’s usual methods for EHR changes. Five months after the intervention, the study timeline was repeated for the post-test period. After the post-test period, a use query was run to collect data for both pre-test and post-test periods. Data were collected, coded, and entered into electronic spreadsheets for storage and analysis. Outcomes and Results. Although the sample as a whole showed no statistically significant increases in any parameter of information quality, use, or user satisfaction, when survey participants were divided by role, nurses and providers, there was a statistically significant increase in the post-test nursing group for two measures of information quality and one measure of information use. A Mann Whitney U test found a significantly higher perception of completeness of the lactation assessment, U = 200, z = -2.11, p = .035, r = .29 and reported frequency of accessing the lactation assessment from the EHR, U= 233, z = -2.01, p = .044, r = 0.26. A Fishers exact test found a statistically significant increase in the presence of lactation assessments in the post-test chart audit [1, N = 39] = 11.8, p =.001, φ= .39). The outcomes may be explained by differences in how each role uses the EHR. Additional education for providers may be necessary to overcome these differences

A Learning Health Sciences Approach to Understanding Clinical Documentation in Pediatric Rehabilitation Settings

The work presented in this dissertation provides an analysis of clinical documentation that challenges the concepts and thinking surrounding missingness of data from clinical settings and the factors that influence why data are missing. It also foregrounds the critical role of clinical documentation as infrastructure for creating learning health systems (LHS) for pediatric rehabilitation settings. Although completeness of discrete data is limited, the results presented do not reflect the quality of care or the extent of unstructured data that providers document in other locations of the electronic health record (EHR) interface. While some may view imputation and natural language processing as means to address missingness of clinical data, these practices carry biases in their interpretations and issues of validity in results. The factors that influence missingness of discrete clinical data are rooted not just in technical structures, but larger professional, system level and unobservable phenomena that shape provider practices of clinical documentation. This work has implications for how we view clinical documentation as critical infrastructure for LHS, future studies of data quality and health outcomes research, and EHR design and implementation. The overall research questions for this dissertation are: 1) To what extent can data networks be leveraged to build classifiers of patient functional performance and physical disability? 2) How can discrete clinical data on gross motor function be used to draw conclusions about clinical documentation practices in the EHR for cerebral palsy? 3) Why does missingness of discrete data in the EHR occur? To address these questions, a three-pronged approach is used to examine data completeness and the factors that influence missingness of discrete clinical data in an exemplar pediatric data learning network will be used. As a use-case, evaluation of EHR data completeness of gross motor function related data, populated by providers from 2015-2019 for children with cerebral palsy (CP), will be completed. Mixed methods research strategies will be used to achieve the dissertation objectives, including developing an expert-informed and standards-based phenotype model of gross motor function data as a task-based mechanism, conducting quantitative descriptive analyses of completeness of discrete data in the EHR, and performing qualitative thematic analyses to elicit and interpret the latent concepts that contribute to missingness of discrete data in the EHR. The clinical data for this dissertation are sourced from the Shriners Hospitals for Children (SHC) Health Outcomes Network (SHOnet), while qualitative data were collected through interviews and field observations of clinical providers across three care sites in the SHC system.PHDHlth Infrastr & Lrng Systs PhDUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162994/1/njkoscie_1.pd

Master of Science

thesisThere is a high risk for communication failures at the hospital discharge. Discharge summaries (DCS) can mitigate these risks by describing not only the hospital course but also follow-up plans. Improvement in the DCS may play a crucial role to improve communication at this transition of care. This research identifies gaps between the local standard of practice and best practices reported in the literature. It also identifies specific components of the DCS that could be improved through enhanced use of health information technology. A manual chart review of 188 DCS was performed. The medication reconciliations were analyzed for completeness and for medical reasoning. The pending results reported in the DCS were compared to those identified in the enterprise data warehouse (EDW). Documentation of follow-up arrangements was analyzed. Report of patient preferences, patient goals, lessons learned, and the overall handover tone were also noted. Patients were discharged on an average of 9.8 medications. Only 3% of the medication reconciliations were complete regarding which medications were continued, changed, new, and discontinued; 94% were incomplete and medical reasoning was frequently absent. There were 358 pending results in 188 hospital discharges. 14% of those results were in the DCS while 86% were only found in the EDW. Less than 50% iv of patients had clear documentation of scheduled follow-up. Patient preferences, patient goals, and lessons learned were rarely (6%, 1%, and 3% respectively) included. There was a handover tone in only 17% of the DCS. The quality gaps in the DCS are consistent with the literature. Medication reconciliations were frequently incomplete, pending results were rarely available, and documentation of follow-up care occurred less than half of the time. Evaluating the DCS primarily as a clinical handover is novel. Information necessary for safe handovers and to promote continuity of care is frequently missing. Future improvements should reshape the DCS to improve continuity of care

Physicians Perception of The Impact of E-health Reform on The Saudi Arabian Health System

The Ministry of Health (MOH) in the Kingdom of Saudi Arabia introduced E-health system reform in 2011. The national E-health plan has already been in action; the MOH expects to implement the system throughout the country by 2021. The MOH manages about 60% of the hospitals in Saudi Arabia. In 2016, the government of Saudi Arabia introduced vision 2030. One of the main objectives of the reform is to accelerate the implementation of primary and digital infrastructure projects. This research aims to evaluate the effectiveness of the E-health system reform in Saudi Arabia. This research utilized a questionnaire to collect data from physicians who work at the Ministry of Health in Saudi Arabia to evaluate the outcome of the E-health system reform. The total responses used for the study were 188. An Ordinary Least Squares (OLS) regression was used to measure physicians\u27 perception of E-health effect on MOH, patient referrals, and cost of care. The analysis included services provided by MOH to measure the effect of E-health. Collectively these measures affect the patient\u27s experience. Quality and consistency, efficiencies, speed of patient\u27s admission and examination, accuracy, and completeness of filling out reports were significantly impacted by electronic services. The analysis outcomes suggest that E-health improved patients\u27 services and helped create a better environment for their visits and treatment. The analysis investigated the effect of E-health on physician perceptions of patient referrals and waiting time. The outcomes indicate a significant enhancement in inpatient referrals in speed, accuracy and completeness, bed availability, viewing patient\u27s medical history, and remote diagnosis. The E-health reform in Saudi Arabia has significantly enhanced patient referrals between the MOH primary care centers and hospitals, reduced the waiting time, and increased the number of referrals. Physician perceptions on the cost of care were also included in the analysis. The analysis included accuracy, viewing patient\u27s history, electronic services cost reduction, overall cost, and electronic training. The outcomes indicate no significant impact on the cost of care after introducing the E-health reform in Saudi Arabia except for remote training. The analysis shows that online training is affected significantly with E-health, which led to a cost reduction. the cost of care in Saudi Arabia has not been significantly impacted by the introduction of the E-health reform in Saudi Arabia. However, training can be effective for accuracy to contribute to cost reduction, and electronic services affect remote training, and E-health can reduce the cost of training

Using Informatics to Improve Autism Screening in a Pediatric Primary Care Practice

Background: According to the most recent report from the CDC (2018), autism spectrum disorder (ASD) affects approximately one in 59 children in the United States (U.S.). In 2007, the American Academy of Pediatrics (AAP) issued a strong recommendation for all primary care providers to screen children for autism, using a validated tool, at the 18 and 24-month well-child visits, in order to begin the referral process for more formal testing, and intervention, promptly. Despite the strong stance of the AAP and evidence supporting the importance of early intervention for children with ASD, not all primary care providers are screening for ASD or developmental delay. Purpose: To improve the percentage of eligible children, presenting for 18 and 24 month wellchild visits in a pediatric primary care office, who are screened for ASD, by integrating the Modified Checklist for Autism in Toddlers (M-CHAT) screening tool into the electronic medical record with tablets. The specific aims were to increase the percentage of children screened and improve the documentation of the screens performed. Methods: This quality improvement project utilized a before-after quantitative design to support the improvement. Reports were obtained for three months prior to the implementation of the tablets and process change, and again for three months following the implementation. Manual chart reviews were also performed to verify the data from the reports. The definition used for complete screening for this project included 1) presence of the completed screen in the medical record, 2) provider documentation of the result, interpretation, and plan if indicated, and 3) CPT code entry for charge capture completed in the electronic medical record. Results: The results of the project revealed improvements in overall percentages of eligible children screened for autism at D-H Nashua Pediatrics. The percentage of complete screening increased from 64.7% to 73.9% following the implementation of the project, a change which is statistically significant (t=31.6105, df=16,p=0.05). Each individual element was also tracked and those results showed that 1) the completeness of provider documentation related to the screening increased from 93.6% to 96% (t=41.3321, df=16, p=0.05) and 2) the M-CHAT screen was present in the electronic health record (EHR) 98.9% of the time, which was an increase from 84.6% (t=295.4084, df=16, p=0.05). The charge capture completion rate remained statistically unchanged at 76.5% (t=0.4664, df=16, p=0.05). Additionally, only one screening was noted to be missed altogether, out of 280 eligible children. Prior to the project, there were four missed screenings (out of 156 eligible children) captured by the chart reviews conducted over three months prior to the implementation of the project. Overall, the results show that the project resulted in an increase the percentage of M-CHAT screening, an increase in the presence of source documentation in the electronic health record (EHR), and more complete provider documentation related to the screening

Supporting Clinical Decision Making in Cancer Care Delivery

Background: Cancer treatment and management require complicated clinical decision making to provide the highest quality of care for an individual patient. This is facilitated in part with ever-increasing availability of medications and treatments but hindered due to barriers such as access to care, cost of medications, clinician knowledge, and patient preferences or clinical factors. Although guidelines for cancer treatment and many symptoms have been developed to inform clinical practice, implementation of these guidelines into practice is often delayed or does not occur. Informatics-based approaches, such as clinical decision support, may be an effective tool to improve guideline implementation by delivering patient-specific and evidence-based knowledge to the clinician at the point of care to allow shared decision making with a patient and their family. The large amount of data in the electronic health record can be utilized to develop, evaluate, and implement automated approaches; however, the quality of the data must first be examined and evaluated. Methods: This dissertation addresses gaps the literature about clinical decision making for cancer care delivery. Specifically, following an introduction and review of the literature for relevant topics to this dissertation, the researcher presents three studies. In Study One, the researcher explores the use of clinical decision support in cancer therapeutic decision making by conducting a systematic review of the literature. In Study Two, the researcher conducts a quantitative study to describe the rate of guideline concordant care provided for prevention of acute chemotherapy-induced nausea and vomiting (CINV) and to identify predictors of receiving guideline concordant care. In Study Three, the researcher conducts a mixed-methods study to evaluate the completeness, concordance, and heterogeneity of clinician documentation of CINV. The final chapter of this dissertation is comprised of key findings of each study, the strengths and limitations, clinical and research implications, and future research. Results: In Study One, the systematic review, the researcher identified ten studies that prospectively studied clinical decision support systems or tools in a cancer setting to guide therapeutic decision making. There was variability in these studies, including study design, outcomes measured, and results. There was a trend toward benefit, both in process and patient-specific outcomes. Importantly, few studies were integrated into the electronic health record. In Study Two, of 180 patients age 26 years or less, 36% received guideline concordant care as defined by pediatric or adult guidelines, as appropriate. Factors associated with receiving guideline concordant care included receiving a cisplatin-based regimen, being treated in adult oncology compared to pediatric oncology, and solid tumor diagnosis. In Study Three, of the 127 patient records reviewed for the documentation of chemotherapy-induced nausea and vomiting, 75% had prescriber assessment documented and 58% had nursing assessment documented. Of those who had documented assessments by both prescriber and nurse, 72% were in agreement of the presence/absence of chemotherapy-induced nausea and vomiting. After mapping the concept through the United Medical Language System and developing a post-coordinated expression to identify chemotherapy-induced nausea and vomiting in the text, 85% of prescriber documentation and 100% of nurse documentation could be correctly categorized as present/absent. Further descriptors of the symptoms, such as severity or temporality, however, were infrequently reported. Conclusion: In summary, this dissertation provides new knowledge about decision making in cancer care delivery. Specifically, in Study One the researcher describes that clinical decision support, one potential implementation strategy to improve guideline concordant care, is understudied or under published but a promising potential intervention. In Study Two, I identified factors that were associated with receipt of guideline concordant care for CINV, and these should be further explored to develop interventions. Finally, in Study Three, I report on the limitations of the data quality of CINV documentation in the electronic health record. Future work should focus on validating these results on a multi-institutional level

Data gaps in electronic health record (EHR) systems: An audit of problem list completeness during the COVID-19 pandemic

OBJECTIVE: To evaluate the completeness of diagnosis recording in problem lists in a hospital electronic health record (EHR) system during the COVID-19 pandemic. DESIGN: Retrospective chart review with manual review of free text electronic case notes. SETTING: Major teaching hospital trust in London, one year after the launch of a comprehensive EHR system (Epic), during the first peak of the COVID-19 pandemic in the UK. PARTICIPANTS: 516 patients with suspected or confirmed COVID-19. MAIN OUTCOME MEASURES: Percentage of diagnoses already included in the structured problem list. RESULTS: Prior to review, these patients had a combined total of 2841 diagnoses recorded in their EHR problem lists. 1722 additional diagnoses were identified, increasing the mean number of recorded problems per patient from 5.51 to 8.84. The overall percentage of diagnoses originally included in the problem list was 62.3% (2841 / 4563, 95% confidence interval 60.8%, 63.7%). CONCLUSIONS: Diagnoses and other clinical information stored in a structured way in electronic health records is extremely useful for supporting clinical decisions, improving patient care and enabling better research. However, recording of medical diagnoses on the structured problem list for inpatients is incomplete, with almost 40% of important diagnoses mentioned only in the free text notes