The impact of electronic health records on diagnosis

Research Trends and Hotspots of Big Data in Ophthalmology: A Bibliometric Analysis and Visualization

PURPOSE

The burst of modern information has significantly promoted the development of global medicine into a new era of big data healthcare. Ophthalmology is one of the most prominent medical specialties driven by big data analytics. This study aimed to describe the development status and research hotspots of big data in ophthalmology.

METHODS

English articles and reviews related to big data in ophthalmology published from January 1, 1999, to April 30, 2024, were retrieved from the Web of Science Core Collection. The relevant information was analyzed and visualized using VOSviewer and CiteSpace software.

RESULTS

A total of 406 qualified documents were included in the analysis. The annual number of publications on big data in ophthalmology reached a rapidly increasing stage since 2019. The United States (n = 147) led in the number of publications, followed by India (n = 77) and China (n = 69). The L.V. Prasad Eye Institute in India was the most productive institution (n = 50), and Anthony Vipin Das was the most influential author with the most relevant literature (n = 45). The electronic medical records were the primary source of ophthalmic big data, and artificial intelligence served as the principal analytics tool. Diabetic retinopathy, glaucoma, and myopia are currently the main topics of interest in this field.

CONCLUSIONS

The application of big data in ophthalmology has experienced rapid growth in recent years. Big data is expected to play an increasingly significant role in shaping the future of research and clinical practice in ophthalmology.

Documentation of the Patient Characteristics Morbid Obesity and Bariatric Surgery in the Hospital Information System and the Influence on the Number of Medication-Related Problems

BACKGROUND

As a result of pharmacokinetic changes, individuals with morbid obesity and/or with bariatric surgery may require dose adjustments, additional monitoring or medication should be avoided. Clinical decision support (CDS) may provide automated alerts enabling correct prescribing but requires documentation of these patient characteristics in the Hospital Information System (HIS) to prevent medication-related problems (MRPs).

OBJECTIVE

The primary objective is to determine the proportion of patients with documentation of the patient characteristics morbid obesity and bariatric surgery in the HIS. The secondary objective is to compare the proportion of patients with an MRP in the group with versus without documentation. Also, the type and severity of MRPs and the medication involved are determined.

METHODS

A prospective cohort study was performed. Patients admitted to the hospital were identified as morbidly obese and/or with bariatric surgery. In the identified patients, the proportion of patients with documentation of the patient characteristics in the HIS was evaluated as primary outcome. Subsequently, patient records were reviewed for MRPs, which were categorized and associated medication was registered. For the primary objective, descriptive statistics was used. For the secondary outcome, the Fisher's exact test was used.

RESULTS

In 43 (21.4%, 95% confidence interval [CI]: 15.7%-27.1%) of 201 included patient (113 morbid obesity, 70 bariatric surgery and 18 both), the patient characteristics were documented. An MRP occurred in 2.3% versus 13.9% (P = 0.032) of patients with and without documentation, respectively. The most common MRP was underdosing in morbid obesity, while in patients with bariatric surgery it was prescription of contra-indicated medication.

CONCLUSION AND RELEVANCE

The proportion of patients with documentation of the patient characteristics bariatric surgery and/or morbid obesity in the HIS is low, which appears to be associated with more MRPs. To improve medication safety, it is important to document these patient characteristics.

Importance of health history analysis in Parkinson's disease

The objective of this research article is to investigate the impact of various health history factors on the risk of developing Parkinson's disease (PD). From the medical history we can identify PD Symptoms and this also help to detect the progression of PD symptoms. By conducting statistical analyses, the study seeks to identify independent risk and protective factors for Parkinson's disease (PD), considering variations in impact across genders and BMI categories.

Introduction

In the diagnosis of PD the analysis of previous health history is very rare in practice while the main diagnosis have been done through the different motor and non-motor symptoms taking in consideration besides the cardinal symptoms of PD for identification and determination the stages of PD. Here we have analyzed the impact of 56 different diseases, symptoms, and surgeries which a subject may have experienced in their life before PD, considered as a health history.

Methods

The behavioral impact for each types of health history have been analyzed statistically with 31,265 subjects including PD, and Control. In this analysis we have calculated the variation of impact for both the Male, and Female, as well as subjects BMI.

Results

98.12 % PD patients, where 97.63 % Male PD, and 98.71 % Female PD were found with at least one health history record. Coronary heart disease odds ratio (OR) 2.15 (1.85-2.51), Colon Cancer OR 2.11 (1.45-3.05), Cranial brain surgery OR 6.21 (5.11-7.56) have the higher risks to PD. Having the history of Asthma OR 0.66 (0.6-0.72), Anemia OR 0.56 (0.51-0.63), Cirrhosis in Liver OR 0.7 (0.57-0.86), Cosmetic surgery OR 0.7 (0.64-0.77), and Gastritis OR 0.78 (0.71-0.87) have been found to be protective to PD. The risk of developing PD varies between male, and female including subjects BMI for each individual health history types. The diseases which reduce the oxygen saturation in blood like, anemia, asthma, and thalassemia act as protective to PD.

Conclusions

In this study we have analyzed fifty six diseases which include surgeries as a health history of PD patients. Study suggests that a thorough health history could greatly aid in understanding the onset and progression of Parkinson's disease (PD).

The validity of hospital diagnostic and procedure codes reflecting morbidity in preterm neonates born <32 weeks gestation

OBJECTIVE

To determine the validity of diagnostic hospital billing codes for complications of prematurity in neonates <32 weeks gestation.

STUDY DESIGN

Retrospective cohort data from discharge summaries and clinical notes (n = 160) were reviewed by trained, blinded abstractors for the presence of intraventricular hemorrhage (IVH) grades 3 or 4, periventricular leukomalacia (PVL), necrotizing enterocolitis (NEC), stage 3 or higher, retinopathy of prematurity (ROP), and surgery for NEC or ROP. Data were compared to diagnostic billing codes from the neonatal electronic health record.

RESULTS

IVH, PVL, ROP and ROP surgery had strong positive predictive values (PPV > 75%) and excellent negative predictive values (NPV > 95%). The PPVs for NEC (66.7%) and NEC surgery (37.1%) were low.

CONCLUSION

Diagnostic hospital billing codes were observed to be a valid metric to evaluate preterm neonatal morbidities and surgeries except in the instance of more ambiguous diagnoses such as NEC and NEC surgery.

Comparative Perspectives on Diagnostic Error Discussions Between Inpatient and Outpatient Pediatric Providers

Diagnostic error remains understudied and underaddressed despite causing significant morbidity and mortality. One barrier to addressing this issue remains provider discomfort. Survey studies have shown significantly more discomfort among providers in discussing diagnostic error compared with other forms of error. Whether the comfort in discussing diagnostic error differs depending on practice setting has not been previously studied. The objective of this study was to assess differences in provider willingness to discuss diagnostic error in the inpatient versus outpatient setting. A multicenter survey was sent out to 3881 providers between May and June 2018. This survey was designed to assess comfort level of discussing diagnostic error and looking at barriers to discussing diagnostic error. Forty-three percent versus 22% of inpatient versus outpatient providers (P = 0.004) were comfortable discussing short-term diagnostic error publicly. Similarly, 76% versus 60% of inpatient versus outpatient providers (P = 0.010) were comfortable discussing short-term diagnostic error privately. A higher percentage of inpatient (64%) compared with outpatient providers (46%) (P = 0.043) were comfortable discussing long-term diagnostic error privately. Forty percent versus 24% of inpatient versus outpatient providers (P = 0.018) were comfortable discussing long-term error publicly. No difference in barriers cited depending on practice setting. Inpatient providers are more comfortable discussing diagnostic error than their outpatient counterparts. More study is needed to determine the etiology of this discrepancy and to develop strategies to increase outpatient provider comfort.

Nurses' Attitudes and Factors Affecting Use of Electronic Health Record in Saudi Arabia

(1) Background: Nurses' attitudes toward electronic health records (EHRs) is a very valuable issue that needs to be evaluated, understood, and considered one of the main factors that can lead to its improvement or handicap its implementation. This study aimed to assess nurses' attitudes toward EHRs and associated factors that affect the implementation of EHRs in different hospitals in Saudi Arabia. (2) Methods: A cross-sectional study was utilized to collect data from 297 nurses working in public hospitals and primary healthcare centers in Ha'il Province from January to May 2023. Data were collected using the Nurses' Attitudes Towards Computerization questionnaire and a sociodemographic and work-related characteristics sheet. (3) Results: Most of the participants' attitude scores (81.1%, n = 241) were more than or equal to 60, representing positive attitudes, whereas 18.9% (n = 56) of the nurses' scores were less than 60, which is interpreted as negative attitudes. There was a significant relationship between nurses' attitudes toward EHRs and a participants' sex, where males had a more positive attitude than females (p < 0.001). Particularly, young nurses and those who had previous computer experience had a more positive attitude than older nurses and those who had no computer experience (p = 0.044 and < 0.001, respectively). Saudi nurses holding a master's degree had significantly more positive attitudes toward EHRs than non-Saudi nurses holding a bachelor's or diploma degree (p = 0.007 and 0.048, respectively). Nurses with less experience (less than five years) in the nursing field had a significantly positive attitude. Multiple linear regression showed that sex (p = 0.038), level of education (p = 0.001), and previous computer experience (p < 0.001) were independent factors of nurses' knowledge of EHRs. (4) Conclusion: The majority of nurses had positive overall attitudes toward using EHRs. Nurses who are Saudi nationals, male, younger, have previous computer experience, and have less than five years of experience had a more positive attitude toward EHRs than nurses who are non-Saudi, female, older, have no computer experience, have bachelor's or diploma degree, and have less than five years of experience, respectively. Sex, education level, and previous computer experience were independent factors of nurses' knowledge of EHRs.

Early Ascertainment of Breast Cancer Diagnoses Comparing Self-Reported Questionnaires and Electronic Health Record Data Warehouse: The WISDOM Study

PURPOSE

The goal of this study was to use real-world data sources that may be faster and more complete than self-reported data alone, and timelier than cancer registries, to ascertain breast cancer cases in the ongoing screening trial, the WISDOM Study.

METHODS

We developed a data warehouse procedural process (DWPP) to identify breast cancer cases from a subgroup of WISDOM participants (n = 11,314) who received breast-related care from a University of California Health Center in the period 2012-2021 by searching electronic health records (EHRs) in the University of California Data Warehouse (UCDW). Incident breast cancer diagnoses identified by the DWPP were compared with those identified by self-report via annual follow-up online questionnaires.

RESULTS

Our study identified 172 participants with confirmed breast cancer diagnoses in the period 2016-2021 by the following sources: 129 (75%) by both self-report and DWPP, 23 (13%) by DWPP alone, and 20 (12%) by self-report only. Among those with International Classification of Diseases 10th revision cancer diagnostic codes, no diagnosis was confirmed in 18% of participants.

CONCLUSION

For diagnoses that occurred ≥20 months before the January 1, 2022, UCDW data pull, WISDOM self-reported data via annual questionnaire achieved high accuracy (96%), as confirmed by the cancer registry. More rapid cancer ascertainment can be achieved by combining self-reported data with EHR data from a health system data warehouse registry, particularly to address self-reported questionnaire issues such as timing delays (ie, time lag between participant diagnoses and the submission of their self-reported questionnaire typically ranges from a month to a year) and lack of response. Although cancer registry reporting often is not as timely, it does not require verification as does the DWPP or self-report from annual questionnaires.

Physicians' Perspectives on a Multi-Dimensional Model for the Roles of Electronic Health Records in Approaching a Proper Differential Diagnosis

Many healthcare organizations have adopted Electronic Health Records (EHRs) to improve the quality of care and help physicians make proper clinical decisions. The vital roles of EHRs can support the accuracy of diagnosis, suggest, and rationalize the provided care to patients. This study aims to understand the roles of EHRs in approaching proper differential diagnosis and optimizing patient safety. This study utilized a cross-sectional survey-based descriptive research design to assess physicians' perceptions of the roles of EHRs on diagnosis quality and safety. Physicians working in tertiary hospitals in Saudi Arabia were surveyed. Three hundred and fifty-one participants were included in the study, of which 61% were male. The main participants were family/general practice (22%), medicine, general (14%), and OB/GYN (12%). Overall, 66% of the participants ranked themselves as IT competent, most of the participants underwent IT self-guided learning, and 65% of the participants always used the system. The results generally reveal positive physicians' perceptions toward the roles of the EHR system on diagnosis quality and safety. There was a statistically significant relationship between user characteristics and the roles of the EHR by enhancing access to care, patient-physician encounter, clinical reasoning, diagnostic testing and consultation, follow-up, and diagnostic safety functionality. The study participants demonstrate positive perceptions of physicians toward the roles of the EHR system in approaching differential diagnosis. Yet, areas of improvement in the design and using EHRs are emphasized.

Twelve tips for physicians’ mastering expertise in diagnostic excellence

Diagnostic errors, which account for a large proportion of medical errors, are a global medical challenge. The slogan of reducing diagnostic errors has recently shifted to a new strategy of diagnostic excellence, the core of which is the importance of improving the multidisciplinary diagnostic process. Many of the elements and strategies necessary for diagnostic excellence have been presented. In the context of this diagnostic improvement, some reports have been structured to improve the quality of performance of individual physicians as players. Still, surprisingly, only a few reports have focused on specific day-to-day training strategies for the diagnostic thinking process as expertise. This paper focuses on this point and proposes strategies for refining the diagnostic thinking expertise of frontline physicians in the new era, based on the following four elements: knowledge and experience, diagnostic thinking strategies, information management skills, and calibration and reflection.

Electronic Health Record Use Issues and Diagnostic Error: A Scoping Review and Framework

BACKGROUND

Diagnostic errors are a major source of patient harm, most of which are caused by cognitive errors and biases. Despite research showing the relationship between software systems and cognitive processes, the impact of the electronic health record (EHR) on diagnostic error remains unknown.

METHODS

We conducted a scoping review of the scientific literature to (1) survey the association between aspects of the EHR and diagnostic error, and (2) through a human-systems integration lens, identify the types of EHR issues and their impact on the stages of the diagnostic process.

RESULTS

We analyzed 11 research articles for the relationship between EHR use and diagnostic error. These articles highlight specific technical, usability, and workflow issues with the EHR that pose risks for diagnostic error at every stage of the diagnostic process.

DISCUSSION

Although technical problems such as EHR interoperability and data integrity pose critical issues for the diagnostic process, usability and workflow issues such as poor display design, and inability to track test results also hamper clinicians' ability to track, process, and act in the diagnostic process. Current research methods have limited coverage over clinical settings, are not standardized, and rarely include measures of patient harm.

CONCLUSIONS

The available evidence shows that EHRs pose risks for diagnostic error throughout the diagnostic process, with most issues involving their incompatibility with providers' cognitive processing. A structured and systematic model of collecting and reporting on these errors is needed to understand how the EHR shapes the diagnostic process and improve diagnostic accuracy.

A Perfect Storm Averted: Flawed Systems, a Dropped Ball, and Cognitive Biases Delay a Critical Diagnosis

This is the first case of Cancer Morbidity, Mortality, and Improvement Rounds, a series of articles intended to explore the unique safety risks experienced by oncology patients through the lens of quality improvement, systems and human factors engineering, and cognitive psychology. This case highlights how multiple overlapping factors contributed to a delay in diagnosing disseminated tuberculosis in a patient with lung cancer. The discussion focuses on the ways that cognitive biases contributed to the delayed diagnosis in a patient who, with the benefit of hindsight, exhibited several signs and symptoms suggesting tuberculosis.Cancer Morbidity, Mortality, and Improvement Rounds is a series of articles intended to explore the unique safety risks experienced by oncology patients through the lens of quality improvement, systems and human factors engineering, and cognitive psychology. For purposes of clarity, each case focuses on a single theme, although, as is true for all medical incidents, there are almost always multiple, overlapping, contributing factors. The quality improvement paradigm used here, which focuses on root cause analyses and opportunities to improve care delivery systems, was previously outlined in this journal.¹.

Autoimmune haemolytic anaemia due to immunodeficiency

Autoimmune disorders are common presenting manifestations of immunodeficiency syndromes. We present a case of a woman in her late teens, with a history of frequent sinopulmonary tract infections during her childhood, who presented to our hospital with anaemia, jaundice and fatigue. She also had significant physical growth retardation for her age and sex. With this case report, we intend to present the diagnostic and therapeutic challenges faced by the patient and our healthcare system and propose a few feasible solutions to tackle these challenges.

Digital health technology-specific risks for medical malpractice liability

Medical professionals are increasingly required to use digital technologies as part of care delivery and this may represent a risk for medical error and subsequent malpractice liability. For example, if there is a medical error, should the error be attributed to the clinician or the artificial intelligence-based clinical decision-making system? In this article, we identify and discuss digital health technology-specific risks for malpractice liability and offer practical advice for the mitigation of malpractice risk.

Understanding barriers to diagnosis in a rare, genetic disease: Delays and errors in diagnosing schwannomatosis

Diagnosis of rare, genetic diseases is challenging, but conceptual frameworks of the diagnostic process can guide quality improvement initiatives. Using the National Academy of Medicine diagnostic framework, we assessed the extent of, and reasons for diagnostic delays and diagnostic errors in schwannomatosis, a neurogenetic syndrome characterized by nerve sheath tumors and chronic pain. We reviewed the medical records of 97 people with confirmed or probable schwannomatosis seen in two US tertiary care clinics. Time-to-event analysis revealed a median time from first symptom to diagnosis of 16.7 years (95% CI, 7.5-26.0 years) and median time from first medical consultation to diagnosis of 9.8 years (95% CI, 3.5-16.2 years). Factors associated with longer times to diagnosis included initial signs/symptoms that were intermittent, non-specific, or occurred at younger ages (p < 0.05). Thirty-six percent of patients were misdiagnosed; misdiagnoses were of underlying genetic condition (18.6%), pain etiology (16.5%), and nerve sheath tumor presence/pathology (11.3%) (non-mutually exclusive categories). One-fifth (19.6%) of patients had a clear missed opportunity for genetics workup that could have led to an earlier schwannomatosis diagnosis. These results suggest that interventions in clinician education, genetic testing availability, expert review of pathology findings, and automatic triggers for genetics referrals may improve diagnosis of schwannomatosis.

Artificial Intelligence, Healthcare, Clinical Genomics, and Pharmacogenomics Approaches in Precision Medicine

Precision medicine has greatly aided in improving health outcomes using earlier diagnosis and better prognosis for chronic diseases. It makes use of clinical data associated with the patient as well as their multi-omics/genomic data to reach a conclusion regarding how a physician should proceed with a specific treatment. Compared to the symptom-driven approach in medicine, precision medicine considers the critical fact that all patients do not react to the same treatment or medication in the same way. When considering the intersection of traditionally distinct arenas of medicine, that is, artificial intelligence, healthcare, clinical genomics, and pharmacogenomics—what ties them together is their impact on the development of precision medicine as a field and how they each contribute to patient-specific, rather than symptom-specific patient outcomes. This study discusses the impact and integration of these different fields in the scope of precision medicine and how they can be used in preventing and predicting acute or chronic diseases. Additionally, this study also discusses the advantages as well as the current challenges associated with artificial intelligence, healthcare, clinical genomics, and pharmacogenomics.

Patients’ willingness and ability to identify and respond to errors in their personal health records: a mixed methods analysis of cross-sectional survey data (Preprint)

Background

Errors in electronic health records are known to contribute to patient safety incidents; however, systems for checking the accuracy of patient records are almost nonexistent. Personal health records (PHRs) enabling patient access to and interaction with the clinical records offer a valuable opportunity for patients to actively participate in error surveillance.

Objective

This study aims to evaluate patients’ willingness and ability to identify and respond to errors in their PHRs.

Methods

A cross-sectional survey was conducted using a web-based questionnaire. Patient sociodemographic data were collected, including age, sex, ethnicity, educational level, health status, geographical location, motivation to self-manage, and digital health literacy (measured using the eHealth Literacy Scale tool). Patients with experience of using the Care Information Exchange (CIE) portal, who specified both age and sex, were included in these analyses. The patients’ responses to 4 relevant survey items (closed-ended questions, some with space for free-text comments) were examined to understand their willingness and ability to identify and respond to errors in their PHRs. Multinomial logistic regression was used to identify patients’ characteristics that predict the ability to understand information in the CIE and willingness to respond to errors in their records. The framework method was used to derive themes from patients’ free-text responses.

Results

Of 445 patients, 181 (40.7%) “definitely” understood the CIE information and approximately half (220/445, 49.4%) understood the CIE information “to some extent.” Patients with high digital health literacy (eHealth Literacy Scale score ≥26) were more confident in their ability to understand their records compared with patients with low digital health literacy (odds ratio [OR] 7.85, 95% CI 3.04-20.29; P<.001). Information-related barriers (medical terminology and lack of medical guidance or contextual information) and system-related barriers (functionality or usability and information communicated or displayed poorly) were described. Of 445 patients, 79 (17.8%) had noticed errors in their PHRs, which were related to patient demographic details, diagnoses, medical history, results, medications, letters or correspondence, and appointments. Most patients (272/445, 61.1%) wanted to be able to flag up errors to their health professionals for correction; 20.4% (91/445) of the patients were willing to correct errors themselves. Native English speakers were more likely to be willing to flag up errors to health professionals (OR 3.45, 95% CI 1.11-10.78; P=.03) or correct errors themselves (OR 5.65, 95% CI 1.33-24.03; P=.02).

Conclusions

A large proportion of patients were able and willing to identify and respond to errors in their PHRs. However, some barriers persist that disproportionately affect the underserved groups. Further development of PHR systems, including incorporating channels for patient feedback on the accuracy of their records, should address the needs of nonnative English speakers and patients with lower digital health literacy.

A Research Agenda for Diagnostic Excellence in Critical Care Medicine

Diagnosing critically ill patients in the intensive care unit is difficult. As a result, diagnostic errors in the intensive care unit are common and have been shown to cause harm. Research to improve diagnosis in critical care medicine has accelerated in past years. However, much work remains to fully elucidate the diagnostic process in critical care. To achieve diagnostic excellence, interdisciplinary research is needed, adopting a balanced strategy of continued biomedical discovery while addressing the complex care delivery systems underpinning the diagnosis of critical illness.

Evaluating Electronic Health Record Limitations and Time Expenditure in a German Medical Center

OBJECTIVES

This study set out to obtain a general profile of physician time expenditure and electronic health record (EHR) limitations in a large university medical center in Germany. We also aim to illustrate the merit of a tool allowing for easier capture and prioritization of specific clinical needs at the point of care for which the current study will inform development in subsequent work.

METHODS

Nineteen physicians across six different departments participated in this study. Direct clinical observations were conducted with 13 out of 19 physicians for a total of 2,205 minutes, and semistructured interviews were conducted with all participants. During observations, time was measured for larger activity categories (searching information, reading information, documenting information, patient interaction, calling, and others). Semistructured interviews focused on perceived limitations, frustrations, and desired improvements regarding the EHR environment.

RESULTS

Of the observed time, 37.1% was spent interacting with the health records (9.0% searching, 7.7% reading, and 20.5% writing), 28.0% was spent interacting with patients corrected for EHR use (26.9% of time in a patient's presence), 6.8% was spent calling, and 28.1% was spent on other activities. Major themes of discontent were a spread of patient information, high and often repeated documentation burden, poor integration of (new) information into workflow, limits in information exchange, and the impact of such problems on patient interaction. Physicians stated limited means to address such issues at the point of care.

CONCLUSION

In the study hospital, over one-third of physicians' time was spent interacting with the EHR, environment, with many aspects of used systems far from optimal and no convenient way for physicians to address issues as they occur at the point of care. A tool facilitating easier identification and registration of issues, as they occur, may aid in generating a more complete overview of limitations in the EHR environment.

Preliminary Exploration of Main Elements for Systematic Classification Development: Case Study of Patient Safety Incidents (Preprint)

Background

Currently, there is no holistic theoretical approach available for guiding classification development. On the basis of our recent classification development research in the area of patient safety in health information technology, this focus area would benefit from a more systematic approach. Although some valuable theoretical and methodological approaches have been presented, classification development literature typically is limited to methodological development in a specific domain or is practically oriented.

Objective

The main purposes of this study are to fill the methodological gap in classification development research by exploring possible elements of systematic development based on previous literature and to promote sustainable and well-grounded classification outcomes by identifying a set of recommended elements. Specifically, the aim is to answer the following question: what are the main elements for systematic classification development based on research evidence and our use case?

Methods

This study applied a qualitative research approach. On the basis of previous literature, preliminary elements for classification development were specified, as follows: defining a concept model, documenting the development process, incorporating multidisciplinary expertise, validating results, and maintaining the classification. The elements were compiled as guiding principles for the research process and tested in the case of patient safety incidents (n=501).

Results

The results illustrate classification development based on the chosen elements, with 4 examples of technology-induced errors. Examples from the use case regard usability, system downtime, clinical workflow, and medication section problems. The study results confirm and thus suggest that a more comprehensive and theory-based systematic approach promotes well-grounded classification work by enhancing transparency and possibilities for assessing the development process.

Conclusions

We recommend further testing the preliminary main elements presented in this study. The research presented herein could serve as a basis for future work. Our recently developed classification and the use case presented here serve as examples. Data retrieved from, for example, other type of electronic health records and use contexts could refine and validate the suggested methodological approach.

Locked the Car, Why Not the Computer: A Qualitative and Quantitative Study on Data Safety Compliance

Information technology has become an integral part of health care in the United Kingdom National Health Service (NHS). All health care professionals are required to have a certain level of cyber ethics and knowledge of computers. This is assured by regular mandatory training. The government of the United Kingdom has charted out a course to strengthen cyber security and prevent any crises like Wannacry. Simple things like leaving a computer unlocked can pose a potential threat to the cyber security of the whole NHS. These cannot be addressed with money alone, as they involve complex interactions of human factors. Such seemingly simple non-compliance results often in harm to the patient or breach of confidentiality. We tried to find out the compliance among junior doctors to the Trust Information Technology (IT) Safe Usage Policy. We made interventions and interviewed junior doctors to find out the reasons for non-compliance. We re-audited in order to see if our interventions helped. We also audited compliance in another Trust independently, which showed that this problem is not specific to a particular trust. Here we suggest the changes that all Trusts can make and follow our model to audit their compliance.

Advancing Diagnostic Safety Research: Results of a Systematic Research Priority Setting Exercise

BACKGROUND

Diagnostic errors are a major source of preventable harm but the science of reducing them remains underdeveloped.

OBJECTIVE

To identify and prioritize research questions to advance the field of diagnostic safety in the next 5 years.

PARTICIPANTS

Ninety-seven researchers and 42 stakeholders were involved in the identification of the research priorities.

DESIGN

We used systematic prioritization methods based on the Child Health and Nutrition Research Initiative (CHNRI) methodology. We first invited a large international group of expert researchers in various disciplines to submit research questions while considering five prioritization criteria: (1) usefulness, (2) answerability, (3) effectiveness, (4) potential for translation, and (5) maximal potential for effect on diagnostic safety. After consolidation, these questions were prioritized at an in-person expert meeting in April 2019. Top-ranked questions were subsequently reprioritized through scoring on the five prioritization criteria using an online questionnaire. We also invited non-research stakeholders to assign weights to the five criteria and then used these weights to adjust the final prioritization score for each question.

KEY RESULTS

Of the 207 invited researchers, 97 researchers responded and 78 submitted 333 research questions which were then consolidated. Expert meeting participants (n = 21) discussed questions in different breakout sessions and prioritized 50, which were subsequently reduced to the top 20 using the online questionnaire. The top 20 questions addressed mostly system factors (e.g., implementation and evaluation of information technologies), teamwork factors (e.g., role of nurses and other health professionals in the diagnostic process), and strategies to engage patients in the diagnostic process.

CONCLUSIONS

Top research priorities for advancing diagnostic safety in the short-term include strengthening systems and teams and engaging patients to support diagnosis. High-priority areas identified using these systematic methods can inform an actionable research agenda for reducing preventable diagnostic harm.

A survey of outpatient Internal Medicine clinician perceptions of diagnostic error

Background Little is known about how practicing Internal Medicine (IM) clinicians perceive diagnostic error, and whether perceptions are in agreement with the published literature. Methods A 16-question survey was administered across two IM practices: one a referral practice providing care for patients traveling for a second opinion and the other a traditional community-based primary care practice. Our aim was to identify individual- and system-level factors contributing to diagnostic error (primary outcome) and conditions at greatest risk of diagnostic error (secondary outcome). Results Sixty-five of 125 clinicians surveyed (51%) responded. The most commonly perceived individual factors contributing to diagnostic error included atypical patient presentations (83%), failure to consider other diagnoses (63%) and inadequate follow-up of test results (53%). The most commonly cited system-level factors included cognitive burden created by the volume of data in the electronic health record (EHR) (68%), lack of time to think (64%) and systems that do not support collaboration (40%). Conditions felt to be at greatest risk of diagnostic error included cancer (46%), pulmonary embolism (43%) and infection (37%). Conclusions Inadequate clinician time and sub-optimal patient and test follow-up are perceived by IM clinicians to be persistent contributors to diagnostic error. Clinician perceptions of conditions at greatest risk of diagnostic error may differ from the published literature.

Healthcare and Fitness Data Management Using the IoT-Based Blockchain Platform

Because of the availability of more than an actor and a wireless component among e-health applications, providing more security and safety is expected. Moreover, ensuring data confidentiality within different services becomes a key requirement. In this paper, we propose to collect data from health and fitness smart devices deployed in connection with the proposed IoT blockchain platform. The use of these devices helps us in extracting an amount of highly valuable heath data that are filtered, analyzed, and stored in electronic health records (EHRs). Different actors of the platform, coaches, patients, and doctors, collaborate to provide an on-time diagnosis and treatment for various diseases in an easy and cost-effective way. Our main purpose is to provide a distributed, secure, and authorized access to these sensitive data using the Ethereum blockchain technology. We have designed an integrated low-powered IoT blockchain platform for a healthcare application to store and review EHRs. This architecture, based on the blockchain Ethereum, includes a web and mobile application allowing the patient as well as the medical and paramedical staff to have a secure access to health information. The Ethereum node is implemented on an embedded platform, which should provide an efficient, flexible, and secure system despite the limited resources and low power consumption of the multiprocessor platform.

Leveraging electronic health records to improve management of noncommunicable diseases at primary healthcare centres in Saudi Arabia: a qualitative study

Background

Electronic Health Records (EHRs) can contribute to the earlier detection and better treatment of chronic diseases by improving accuracy and accessibility of patient data. The Saudi Ministry of Health (MOH) implemented an EHR system in all primary health care clinics (PHCs) as part of measures to improve their performance in managing chronic disease. This study examined the perspective of physicians on the current scope and content of NCDs management at PHCs including the contribution of the EHR system.

Methods

Semi-structured interviews were conducted with 22 physicians working in chronic disease clinics at PHCs covering a range of locations and clinic sizes. The participants were selected based on their expertise using a combination of purposive and convenience sampling. The interviews were transcribed, analyzed and coded into the key themes.

Results

Physicians indicated that the availability of the EHR helped organise their work and positively influenced NCDs patient encounters in their PHCs. They emphasised the multiple benefits of EHR in terms of efficiency, including the accuracy of patient documentation and the availability of patient information. Shortcomings identified included the lack of a patient portal to allow patients to access information about their health and lack of capacity to facilitate multi-disciplinary care for example through referral to allied health services. Access to the EHR was limited to MOH primary healthcare centres and clinicians noted that patients also received care in private clinics and hospitals.

Conclusion

While well regarded by clinicians, the EHR system impact on patient care at chronic disease clinics is not being fully realised. Enabling patient access to their EHR would be help promote self-management, a core attribute of effective NCD management. Co-ordination of care is another core attribute and in the Saudi health system with multiple public and private providers, this may be substantially improved if the patients EHR was accessible wherever care was provided. There is also a need for enhanced capacity to support improving patient’s nutrition and physical activity.

Small sleepers, big data: leveraging big data to explore sleep-disordered breathing in infants and young children

STUDY OBJECTIVES

Infants represent an understudied minority in sleep-disordered breathing (SDB) research and yet the disease can have a significant impact on health over the formative years of neurocognitive development that follow. Herein we report data on SDB in this population using a big data approach.

METHODS

Data were abstracted using the Cerner Health Facts database. Demographics, sleep diagnoses, comorbid medication conditions, healthcare utilization, and economic outcomes are reported.

RESULTS

In a cohort of 68.7 million unique patients, over a 9-year period, there were 9,773 infants and young children with a diagnosis of SDB (obstructive sleep apnea [OSA], nonobstructive sleep apnea, and "other" sleep apnea) who met inclusion criteria, encompassing 17,574 encounters, and a total of 27,290 diagnoses across 62 U.S. health systems, 172 facilities, and 3 patient encounter types (inpatient, clinic, and outpatient). Thirty-nine percent were female. Thirty-nine percent were ≤1 year of age (6,429 infants), 50% were 1-2 years of age, and 11% were 2 years of age. The most common comorbid diagnoses were micrognathia, congenital airway abnormalities, gastroesophageal reflux, chronic tonsillitis/adenoiditis, and anomalies of the respiratory system. Payor mix was dominated by government-funded entities.

CONCLUSIONS

We have used a novel resource, large-scale aggregate, de-identified EHR data, to examine SDB. In this population, SDB is multifactorial, closely linked to comorbid medical conditions and may contribute to a significant burden of healthcare costs. Further research focusing on infants at highest risk for SDB can help target resources and facilitate personalized management.

A new approach to medical diagnostic decision support

Data mining is a powerful tool to reduce costs and mitigate errors in the diagnostic analysis and repair of complex engineered system, but it has yet to be applied systematically to the most complex and socially expensive system - the human body. The currently available approaches of knowledge-based and pattern-based artificial intelligence are unsuited to the iterative and often subjective nature of clinician-patient interactions. Furthermore, current electronic health records generally have poor design and low quality for such data mining. Bayesian methods have been developed to suggest multiple possible diagnoses given a set of clinical findings, but the larger problem is advising the physician on useful next steps. A new approach based on inverting Bayesian inference allows identification of the diagnostic actions that are most likely to disambiguate a differential diagnosis at each point in a patient's work-up. This can be combined with personalized cost information to suggest a cost-effective path to the clinician. Because the software is tracking the clinician's decision-making process, it can provide salient suggestions for both diagnoses and diagnostic tests in standard, coded formats that need only to be selected. This would reduce the need to type in free text, which is prone to ambiguities, omissions and errors. As the database of high-quality records grows, the scope, utility and acceptance of the system should also grow automatically, without requiring expert updating or correction.

A theoretical model of health management using data-driven decision-making: the future of precision medicine and health

BACKGROUND

The burden of chronic and societal diseases is affected by many risk factors that can change over time. The minimalisation of disease-associated risk factors may contribute to long-term health. Therefore, new data-driven health management should be used in clinical decision-making in order to minimise future individual risks of disease and adverse health effects.

METHODS

We aimed to develop a health trajectories (HT) management methodology based on electronic health records (EHR) and analysing overlapping groups of patients who share a similar risk of developing a particular disease or experiencing specific adverse health effects. Formal concept analysis (FCA) was applied to identify and visualise overlapping patient groups, as well as for decision-making. To demonstrate its capabilities, the theoretical model presented uses genuine data from a local total knee arthroplasty (TKA) register (a total of 1885 patients) and shows the influence of step by step changes in five lifestyle factors (BMI, smoking, activity, sports and long-distance walking) on the risk of early reoperation after TKA.

RESULTS

The theoretical model of HT management demonstrates the potential of using EHR data to make data-driven recommendations to support both patients' and physicians' decision-making. The model example developed from the TKA register acts as a clinical decision-making tool, built to show surgeons and patients the likelihood of early reoperation after TKA and how the likelihood changes when factors are modified. The presented data-driven tool suits an individualised approach to health management because it quantifies the impact of various combinations of factors on the early reoperation rate after TKA and shows alternative combinations of factors that may change the reoperation risk.

CONCLUSION

This theoretical model introduces future HT management as an understandable way of conceiving patients' futures with a view to positively (or negatively) changing their behaviour. The model's ability to influence beneficial health care decision-making to improve patient outcomes should be proved using various real-world data from EHR datasets.

Presentation and formatting of laboratory results: a narrative review on behalf of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group "postanalytical phase" (WG-POST)

In laboratory medicine, much effort has been put into analytical quality in the past decades, making this medical profession one of the most standardized with the lowest rates of error. However, even the best analytical quality cannot compensate for errors or low quality in the pre or postanalytical phase of the total testing process. Guidelines for data reporting focus solely on defined data elements, which have to be provided alongside the analytical test results. No guidelines on how to format laboratory reports exist. The habit of reporting as much diagnostic data as possible, including supplemental information, may lead to an information overload. Considering the multiple tasks physicians have to do simultaneously, unfiltered data presentation may contribute to patient risk, as important information may be overlooked, or juxtaposition errors may occur. As laboratories should aim to answer clinical questions, rather than providing sole analytical results, optimizing formatting options may help improve the effectiveness and efficiency of medical decision-making. In this narrative review, we focus on the underappreciated topic of laboratory result reporting. We present published literature, focusing on the impact of laboratory result report formatting on medical decisions as well as approaches, potential benefits, and limitations for alternative report formats. We discuss influencing variables such as, for example, the type of patient (e.g. acute versus chronic), the medical specialty of the recipient of the report, the display of reference intervals, the medium or platform on which the laboratory report is presented (printed paper, within electronic health record systems, on handheld devices, etc.), the context in which the report is viewed in, and difficulties in formatting single versus cumulative reports. Evidence on this topic, especially experimental studies, is scarce. When considering the medical impact, it is of utmost importance that laboratories focus not only on the analytical aspects but on the total testing process. The achievement of high analytical quality may be of minor value if essential results get lost in overload or scattering of information by using a non-formatted tabular design. More experimental studies to define guidelines and to standardize effective and efficient reporting are most definitely needed.

A novel tool for patient data management in the ICU-Ensuring timely and accurate vital data exchange among ICU team members

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COVID-19 displaced many healthcare providers to intensive care units to meet the demand of incoming COVID-19 patients.

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The infrastructure and IT support costs needed to establish EMRs are barriers to underserved regions adopting EMR technology.

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Inexpensive implementation of this tool may allow for better patient care and data collection in certain regions.

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Users can manage patient information electronically with less data overload and a more intuitive user experience.

Objective

The coronavirus pandemic has highlighted the need to simplify data collection for critically-ill patients, particularly for physicians relocated to the ICU setting. Herein we present a simple, reproducible, and highly-customizable manual-entry tool to track ICU patients using new HIPAA-compliant Google Big Query technology for parsing large datasets. This innovative flow chart is useful and could be modified to serve the particular needs of different sub-specialists, particularly those that either rely heavily on hand-written notes or experience poor electronic medical record (EMR) penetration.

Methods

The tool was developed using a combination of three Google Enterprise features: Google Forms for data input, Google Sheets for data output, and Google Big Query for data parsing. Code was written in SQL. Sheets functions were used to transpose and filter parsed data. White and black box tests were performed to examine functionality.

Results

Our tool was successfully able to collect and output fictional patient data across all 57 data points specified by the intensivists and surgeons of Cardiovascular Department of Mt. Sinai Morningside Hospital.

Conclusion

The functional tests performed demonstrate use of the tool. Though originally conceived to simplify patient data collection for newly relocated physicians to the ICU, our tool also overcomes financial and technological barriers previously described in low-income countries that could dramatically improve patient care and provide data to power future studies in these regions. With the original code provided, implementers may adapt our tool to best meet the requirements of their clinical setting and protocols during this very challenging time.

Psychosocial Factors Are Associated with Electronic Portal Registration

BACKGROUND

Electronic health records often include a portal for secure patient-clinician communication. There is evidence that use of electronic portals increases satisfaction, treatment adherence, safety, and clinical outcomes. We want everyone to enjoy these benefits and we noticed low and uneven portal use. We studied factors that we can address to improve portal use.

QUESTIONS/PURPOSES

After controlling for differences in patient characteristics, what psychological and demographic factors are associated with an increased likelihood of registering for an electronic health record portal among people seeking musculoskeletal specialty care?

METHODS

We reviewed data on 5672 adult English or Spanish-speaking patients seen in a musculoskeletal specialty office between October 2017 and December 2019. Eighteen percent (996 patients) had missing measures of symptoms of depression and anxiety due to intermittent problems with survey technology, leaving 4676 for analysis, 42% (1970 of 4676) men and 58% (2706 of 4676) women with a mean age of 51±15, 76% (3569 of 4676) of patients were English speaking, 22% (1015 of 4676) were Spanish speaking, and 2% (92 of 4676) spoke another language. Seventy-seven percent (3620 of 4676) of patients were residents of Austin, Texas, USA, 4% (159) were from Pflugerville, Texas, USA, 3% (143) were from Del Valle, Texas, USA, and 16% (754 of 4676) were from other areas of Texas. Ninety nine percent of patients were residents of Texas (4645 of 4676). Twenty-three percent of patients visited the upper extremity team (1077 of 4676), 37% the lower extremity team (1721 of 4676), 21% the back and neck team (1002 of 4676), and 19% the sport medicine team (876 of 4676). Seventy eight percent of patients (3654 of 4676) registered in portal and 22% (1022 of 4676) did not. The omitted population were not different from our study population in terms of age, gender, language, residence, and region of symptoms. We used a two-question measure of symptoms of depression (Patient Health Quality-2 [PHQ-2]) and a two-question measure of symptoms of anxiety (General Anxiety Disorder-2 [GAD-2]). The primary outcome was portal registration. To account for potential confounding, a multivariable logistic regressions model was used to determine the influence of age, spoken language, city and state of residence, care team, number of completed visits and GAD and PHQ scores on portal registration.

RESULTS

After controlling for potentially confounding variables such as state of residence, we found younger age (odds ratio 0.98 [95% CI 0.97 to 0.99]; p < 0.01), speaking English (OR 1.85 [95% CI 1.14 to 3.02]; p = 0.01) rather than Spanish (OR 0.27 [95% CI 0.17 to 0.45]; p < 0.01), seeking care for back or neck symptoms, (OR 3.84 [95% CI 2.60 to 5.66]; p < 0.01) and higher number of completed visits (OR 1.03 [95% CI 1.01 to 1.05]; p < 0.01) were associated with an increased likelihood of portal registration while living in Austin, Texas, USA (OR 0.68 [95% CI 0.53 to 0.87]; p < 0.01) and Del Valle, Texas, USA (OR 0.47 [95% CI 0.30 to 0.74]; p < 0.01) compared with Pflugerville, Texas, USA, or other cities, seeking care for upper extremity (OR 0.74 [95% CI 0.58 to 0.94]; p = 0.01) or lower extremity symptoms (OR 0.68 [95% CI 0.53 to 0.86]; p < 0.01), and greater symptoms of anxiety (GAD score) (OR 0.97 [95% CI 0.95 to 0.99]; p < 0.01) or depression (PHQ score) (OR 0.97 [95% CI 0.95 to 0.98]; p < 0.01) were associated with lower likelihood of registering for the portal. English language, city of residence, and seeking care for back or neck symptoms (due to insurance contracts) were all associated with higher socioeconomic status in our setting.

CONCLUSIONS

The association of better mental and social health (financial, employment, housing and food security; connectedness) with registration in a communication portal directs us to be more intentional about efforts to specifically welcome disadvantaged people to participate in the portal and to study the impact and effectiveness of such efforts.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Assessment of Health Information Technology-Related Outpatient Diagnostic Delays in the US Veterans Affairs Health Care System: A Qualitative Study of Aggregated Root Cause Analysis Data

IMPORTANCE

Diagnostic delay in the outpatient setting is an emerging safety priority that health information technology (HIT) should help address. However, diagnostic delays have persisted, and new safety concerns associated with the use of HIT have emerged.

OBJECTIVE

To analyze HIT-related outpatient diagnostic delays within a large, integrated health care system.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study involved qualitative content analysis of safety concerns identified in aggregated root cause analysis (RCA) data related to HIT and outpatient diagnostic delays. The setting was the US Department of Veterans Affairs using all RCAs submitted to the Veterans Affairs (VA) National Center for Patient Safety from January 1, 2013, to July 31, 2018.

MAIN OUTCOMES AND MEASURES

Common themes associated with the role of HIT-related safety concerns were identified and categorized according to the Health IT Safety framework for measuring, monitoring, and improving HIT safety. This framework includes 3 related domains (ie, safe HIT, safe use of HIT, and using HIT to improve safety) situated within an 8-dimensional sociotechnical model accounting for interacting technical and nontechnical variables associated with safety. Hence, themes identified enhanced understanding of the sociotechnical context and domain of HIT safety involved.

RESULTS

Of 214 RCAs categorized by the terms delay and outpatient submitted during the study period, 88 were identified as involving diagnostic delays and HIT, from which 172 unique HIT-related safety concerns were extracted (mean [SD], 1.97 [1.53] per RCA). Most safety concerns (82.6% [142 of 172]) involved problems with safe use of HIT, predominantly sociotechnical factors associated with people, workflow and communication, and a poorly designed human-computer interface. Fewer safety concerns involved problems with safe HIT (14.5% [25 of 172]) or using HIT to improve safety (0.3% [5 of 172]). The following 5 key high-risk areas for diagnostic delays emerged: managing electronic health record inbox notifications and communication, clinicians gathering key diagnostic information, technical problems, data entry problems, and failure of a system to track test results.

CONCLUSIONS AND RELEVANCE

This qualitative study of a national RCA data set suggests that interventions to reduce outpatient diagnostic delays could aim to improve test result management, interoperability, data visualization, and order entry, as well as to decrease information overload.

Frequency and Types of Patient-Reported Errors in Electronic Health Record Ambulatory Care Notes

Importance

As health information transparency increases, patients more often seek their health data. More than 44 million patients in the US can now readily access their ambulatory visit notes online, and the practice is increasing abroad. Few studies have assessed documentation errors that patients identify in their notes and how these may inform patient engagement and safety strategies.

Objective

To assess the frequency and types of errors identified by patients who read open ambulatory visit notes.

Design, Setting, and Participants

In this survey study, a total of 136 815 patients at 3 US health care organizations with open notes, including 79 academic and community ambulatory care practices, received invitations to an online survey from June 5 to October 20, 2017. Patients who had at least 1 ambulatory note and had logged onto the portal at least once in the past 12 months were included. Data analysis was performed from July 3, 2018, to April 27, 2020.

Exposures

Access to ambulatory care open notes through patient portals for up to 7 years (2010-2017).

Main Outcomes and Measures

Proportion of patients reporting a mistake and how serious they perceived the mistake to be, factors associated with finding errors characterized by patients as serious, and categories of patient-reported errors.

Results

Of 136 815 patients who received survey invitations, 29 656 (21.7%) responded and 22 889 patients (mean [SD] age, 55.16 [15.96] years; 14 447 [63.1%] female; 18 301 [80.0%] white) read 1 or more notes in the past 12 months and completed error questions. Of these patients, 4830 (21.1%) reported a perceived mistake and 2043 (42.3%) reported that the mistake was serious (somewhat serious: 1563 [32.4%]; very serious: 480 [9.9%]). In multivariable analysis, female patients (relative risk [RR], 1.79; 95% CI, 1.72-1.85), more educated patients (RR, 1.38; 95% CI, 1.29-1.48), sicker patients (RR, 1.89; 95% CI, 1.84-1.94), those aged 45 to 64 years (RR, 2.23; 95% CI, 2.06-2.42), those 65 years or older (RR, 2.00; 95% CI, 1.73-2.32), and those who read more than 1 note (2-3 notes: RR, 1.82; 95% CI, 1.34-2.47; ≥4 notes: RR, 3.09; 95% CI, 2.02-4.73) were more likely to report a mistake that they found to be serious compared with their reference groups. After categorization of patient-reported very serious mistakes, those specifically mentioning the word diagnosis or describing a specific error in current or past diagnoses were most common (98 of 356 [27.5%]), followed by inaccurate medical history (85 of 356 [23.9%]), medications or allergies (50 of 356 [14.0%]), and tests, procedures, or results (30 of 356 [8.4%]). A total of 23 (6.5%) reflected notes reportedly written on the wrong patient. Of 433 very serious errors, 255 (58.9%) included at least 1 perceived error potentially associated with the diagnostic process (eg, history, physical examination, tests, referrals, and communication).

Conclusions and Relevance

In this study, patients who read ambulatory notes online perceived mistakes, a substantial proportion of which they found to be serious. Older and sicker patients were twice as likely to report a serious error compared with younger and healthier patients, indicating important safety and quality implications. Sharing notes with patients may help engage them to improve record accuracy and health care safety together with practitioners.

Patient Safety Culture, Health Information Technology Implementation, and Medical Office Problems That Could Lead to Diagnostic Error

BACKGROUND

Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment or by leading to unnecessary or harmful treatment.

OBJECTIVES

The aim of the study was to investigate the relationship between patient safety culture, health information technology (IT) implementation, and the frequency of problems that could lead to diagnostic errors in the medical office setting, such as unavailable test results, unavailable medical records, or unpursued abnormal results.

METHODS

We used survey data from 925 medical offices nationwide that voluntarily submitted results to the 2012 Agency for Healthcare Research and Quality Medical Office Surveys on Patient Safety Culture database. At the office level, we ran a multivariate regression model to estimate the effect of culture on problem frequency while controlling for office-reported implementation levels of health IT, office characteristics such as the number of locations, and survey characteristics such as the percent of respondents that were physicians.

RESULTS

The most frequent problem was "results from a lab or imaging test were not available when needed"; across 925 offices, the average was 15% reporting that it happened daily or weekly. Higher overall culture scores were significantly associated with fewer occurrences of each problem assessed. Compared with offices with completed health IT implementation, offices in the process of health IT implementation had higher frequency of problems.

CONCLUSIONS

This study offers insight into how patient safety culture and health IT implementation in medical offices can influence the frequency of breakdowns in processes of care, thereby identifying potential vulnerabilities that can increase diagnostic errors.

How well is the electronic health record supporting the clinical tasks of hospital physicians? A survey of physicians at three Norwegian hospitals

Background

The electronic health record is expected to improve the quality and efficiency of health care. Many novel functionalities have been introduced in order to improve medical decision making and communication between health care personnel. There is however limited evidence on whether these new functionalities are useful. The aim of our study was to investigate how well the electronic health record system supports physicians in performing basic clinical tasks.

Methods

Physicians of three prominent Norwegian hospitals participated in the survey. They were asked, in an online questionnaire, how well the hospital’s electronic health record system DIPS supported 49 clinical tasks as well as how satisfied they were with the system in general, including the technical performance. Two hundred and eight of 402 physicians (52%) submitted a completely answered questionnaire.

Results

Seventy-two percent of the physicians had their work interrupted or delayed because the electronic health record hangs or crashes at least once a week, while 22% had experienced this problem daily. Fifty-three percent of the physicians indicated that the electronic health record is cumbersome to use and adds to their workload. The majority of physicians were satisfied with managing tests, e.g., requesting laboratory tests, reading test results and managing radiological investigations and electrocardiograms. Physicians were less satisfied with managing referrals. There was high satisfaction with some of the decision support functionalities available for prescribing drugs. This includes drug interaction alerts and drug allergy warnings, which are displayed automatically. However, physicians were less satisfied with other aspects of prescribing drugs, including getting an overview of the ongoing drug therapy.

Conclusions

In the survey physicians asked for improvements of certain electronic health record functionalities like medication, clinical workflow support including planning and better overviews. In addition, there is apparently a need to focus on system stability, number of logins, reliability and better instructions on available electronic health record features. Considerable development is needed in current electronic health record systems to improve usefulness and satisfaction.

Electronic health records, communication, and data sharing: challenges and opportunities for improving the diagnostic process

Background Diagnosis requires that clinicians communicate and share patient information in an efficient manner. Advances in electronic health records (EHRs) and health information technologies have created both challenges and opportunities for such communication. Methods We conducted a multi-method, focused ethnographic study of physicians on general medicine inpatient units in two teaching hospitals. Physician teams were observed during and after morning rounds to understand workflow, data sharing and communication during diagnosis. To validate findings, interviews and focus groups were conducted with physicians. Field notes and interview/focus group transcripts were reviewed and themes identified using content analysis. Results Existing communication technologies and EHR-based data sharing processes were perceived as barriers to diagnosis. In particular, reliance on paging systems and lack of face-to-face communication among clinicians created obstacles to sustained thinking and discussion of diagnostic decision-making. Further, the EHR created data overload and data fragmentation, making integration for diagnosis difficult. To improve diagnosis, physicians recommended replacing pagers with two-way communication devices, restructuring the EHR to facilitate access to key information and improving training on EHR systems. Conclusions As advances in health information technology evolve, challenges in the way clinicians share information during the diagnostic process will rise. To improve diagnosis, changes to both the technology and the way in which we use it may be necessary.

Payment Innovations To Improve Diagnostic Accuracy And Reduce Diagnostic Error

Diagnostic accuracy is essential for treatment decisions but is largely unaccounted for by payers, including in fee-for-service Medicare and proposed Alternative Payment Models (APMs). We discuss three payment-related approaches to reducing diagnostic error. First, coding changes in the Medicare Physician Fee Schedule could facilitate the more effective use of teamwork and information technology in the diagnostic process and better support the cognitive work and time commitment that physicians make in the quest for diagnostic accuracy, especially in difficult or uncertain cases. Second, new APMs could be developed to focus on improving diagnostic accuracy in challenging cases and make available support resources for diagnosis, including condition-specific centers of diagnostic expertise or general diagnostic centers of excellence that provide second (or even third) opinions. Performing quality improvement activities that promote safer diagnosis should be a part of the accountability of APM recipients. Third, the accuracy of diagnoses that trigger APM payments and establish payment amounts should be confirmed by APM recipients. Implementation of these multipronged approaches can make current payment models more accountable for addressing diagnostic error and position diagnostic performance as a critical component of quality-based payment.

Safeuristics! Do Heuristic Evaluation Violation Severity Ratings Correlate with Patient Safety Severity Ratings for a Native Electronic Health Record Mobile Application?

OBJECTIVE

Usability of electronic health records (EHRs) remains challenging, and poor EHR design has patient safety implications. Heuristic evaluation detects usability issues that can be classified by severity. The National Institute of Standards and Technology provides a safety scale for EHR usability. Our objectives were to investigate the relationship between heuristic severity ratings and safety scale ratings in an effort to analyze EHR safety.

MATERIALS AND METHODS

Heuristic evaluation was conducted on seven common mobile EHR tasks, revealing 58 heuristic violations and 28 unique usability issues. Each usability issue was independently scored for severity by trained hospitalists and a Human Factors researcher and for safety severity by two physician informaticists and two clinical safety professionals.

RESULTS

Results demonstrated a positive correlation between heuristic severity and safety severity ratings. Regression analysis demonstrated that 49% of safety risk variability by clinical safety professionals (r = 0.70; n = 28) and 42% of safety risk variability by clinical informatics specialists (r = 0.65; n = 28) was explained by usability severity scoring of problems outlined by heuristic evaluation. Higher severity ratings of the usability issues were associated with increased perceptions of patient safety risk.

DISCUSSION

This study demonstrated the use of heuristic evaluation as a technique to quickly identify usability problems in an EHR that could lead to safety issues. Detection of higher severity ratings could help prioritize failures in EHR design that more urgently require design changes. This approach is a cost-effective technique for improving usability while impacting patient safety.

CONCLUSION

Results from this study demonstrate the efficacy of the heuristic evaluation technique to identify usability problems that impact safety of the EHR. Also, the use of interdisciplinary teams for evaluation should be considered for severity assessment.

Primary care physicians' attitudes to the adoption of electronic medical records: a systematic review and evidence synthesis using the clinical adoption framework

BACKGROUND

Recent decades have seen rapid growth in the implementation of Electronic Medical Records (EMRs) in healthcare settings in both developed regions as well as low and middle income countries. Yet despite substantial investment, the implementation of EMRs in some primary care systems has lagged behind other settings, with piecemeal adoption of EMR functionality by primary care physicians (PCPs) themselves. We aimed to review and synthesise international literature on the attitudes of PCPs to EMR adoption using the Clinical Adoption (CA) Framework.

METHODS

MEDLINE, PsycINFO, and EMBASE were searched from 1st January 1996 to 1st August 2017 for studies investigating PCP attitudes towards EMR adoption. Papers were screened by two independent reviewers, and eligible studies selected for further assessment. Findings were categorised against the CA Framework and the quality of studies assessed against one of three appropriate tools.

RESULTS

Out of 2263 potential articles, 33 were included, based in North and South America, Europe, Middle East and Hong Kong. Concerns about the accessibility, reliability and EMR utility exerted an adverse influence on PCPs' attitudes to adoption. However many were positive about their potential to improve clinical productivity, patient safety and care quality. Younger, computer-literate PCPs, based in large/multi-group practices, were more likely to be positively inclined to EMR use than older physicians, less-skilled in technology use, based in solo practices. Adequate training, policies and procedures favourably impacted on PCPs' views on EMR implementation. Financial factors were common system level influencers shaping EMR adoption, from start-up costs to the resources required by ongoing use.

CONCLUSIONS

By using the CA Framework to synthesise the evidence, we identified a linked series of factors influencing PCPs attitudes to EMR adoption. Findings underline the need to involve end-users in future implementation programmes from the outset, to avoid the development of an EMR which is neither feasible nor acceptable for use in practice.

TRIAL REGISTRATION

PROSPERO CRD42016038790 .

Diagnostic accuracy in Family Medicine residents using a clinical decision support system (DXplain): a randomized-controlled trial

BACKGROUND

Clinical reasoning is an essential skill in physicians, required to address the challenges of accurate patient diagnoses. The goal of the study was to compare the diagnostic accuracy in Family Medicine residents, with and without the use of a clinical decision support tool (DXplain http://www.mghlcs.org/projects/dxplain).

METHODS

A total of 87 first-year Family Medicine residents, training at the National Autonomous University of Mexico (UNAM) Postgraduate Studies Division in Mexico City, participated voluntarily in the study. They were randomized to a control group and an intervention group that used DXplain. Both groups solved 30 clinical diagnosis cases (internal medicine, pediatrics, gynecology and emergency medicine) in a multiple-choice question test that had validity evidence.

RESULTS

The percent-correct score in the Diagnosis Test in the control group (44 residents) was 74.1±9.4 (mean±standard deviation) whereas the DXplain intervention group (43 residents) had a score of 82.4±8.5 (p<0.001). There were significant differences in the four knowledge content areas of the test.

CONCLUSIONS

Family Medicine residents have appropriate diagnostic accuracy that can improve with the use of DXplain. This could help decrease diagnostic errors, improve patient safety and the quality of medical practice. The use of clinical decision support systems could be useful in educational interventions and medical practice.