Colorectal cancer health and care quality indicators in a federated setting using the Personal Health Train.

OBJECTIVE: Hospitals and healthcare providers should assess and compare the quality of care given to patients and based on this improve the care. In the Netherlands, hospitals provide data to national quality registries, which in return provide annual quality indicators. However, this process is time-consuming, resource intensive and risks patient privacy and confidentiality. In this paper, we presented a multicentric 'Proof of Principle' study for federated calculation of quality indicators in patients with colorectal cancer. The findings suggest that the proposed approach is highly time-efficient and consume significantly lesser resources. MATERIALS AND METHODS: Two quality indicators are calculated in an efficient and privacy presevering federated manner, by i) applying the Findable Accessible Interoperable and Reusable (FAIR) data principles and ii) using the Personal Health Train (PHT) infrastructure. Instead of sharing data to a centralized registry, PHT enables analysis by sending algorithms and sharing only insights from the data. RESULTS: ETL process extracted data from the Electronic Health Record systems of the hospitals, converted them to FAIR data and hosted in RDF endpoints within each hospital. Finally, quality indicators from each center are calculated using PHT and the mean result along with the individual results plotted. DISCUSSION AND CONCLUSION: PHT and FAIR data principles can efficiently calculate quality indicators in a privacy-preserving federated approach and the work can be scaled up both nationally and internationally. Despite this, application of the methodology was largely hampered by ELSI issues. However, the lessons learned from this study can provide other hospitals and researchers to adapt to the process easily and take effective measures in building quality of care infrastructures.

The Ability of Primary Care Practices to Measure and Report on Care Quality.

BACKGROUND: Creating useful clinical quality measure (CQM) reports in a busy primary care practice is known to depend on the capability of the electronic health record (EHR). Two other domains may also contribute: supportive leadership to prioritize the work and commit the necessary resources, and individuals with the necessary health information technology (IT) skills to do so. Here we describe the results of an assessment of the above 3 domains and their associations with successful CQM reporting during an initiative to improve smaller primary care practices' cardiovascular disease CQMs. METHODS: The study took place within an AHRQ EvidenceNOW initiative of external support for smaller practices across Washington, Oregon and Idaho. Practice facilitators who provided this support completed an assessment of the 3 domains previously described for each of their assigned practices. Practices submitted 3 CQMs to the study team: appropriate aspirin prescribing, use of statins when indicated, blood pressure control, and tobacco screening/cessation. RESULTS: Practices with advanced EHR reporting capability were more likely to report 2 or more CQMs. Only one-third of practices were "advanced" in this domain, and this domain had the highest proportion of practices (39.1%) assessed as "basic." The presence of advanced leadership or advanced skills did not appreciably increase the proportion of practices that reported 2 or more CQMs. CONCLUSIONS: Our findings support previous reports of limited EHR reporting capabilities within smaller practices but extend these findings by demonstrating that practices with advanced capabilities in this domain are more likely to produce CQM reports.

Confidentiality in the Care of Adolescents: Policy Statement.

Confidentiality is an essential component of high-quality health care for adolescents and young adults and can have an impact on the health care experiences and health outcomes of youth. Federal and state laws, professional guidelines, and ethical standards provide a core framework for guidance in the implementation of confidentiality protections in clinical practice. This policy statement provides recommendations for pediatricians and other pediatric health care professionals, clinics, health systems, payers, and electronic health record developers to optimize confidentiality practices and protections for adolescents and young adults across the spectrum of care.

Using the Electronic Medical Record to Address Code Status Documentation: A Quality Improvement Project.

ABSTRACT: Code status (CS) is often overlooked while admitting patients to the hospital. This is important for patients with end-stage disease. This quality improvement project investigated whether a CS pop-up alert in the electronic medical record, combined with provider education, improved addressing CS. The project consisted of a baseline chart review, implementation of the alert and physician education, and a postintervention chart review. We reviewed 1828 charts at baseline and 1,775 at postintervention. From univariable analysis, there were improvements in addressing CS, being full code, cardiopulmonary resuscitation, intubation, use of vasopressors, and cardioversion technique categories (all p < .001). Documentation of do not resuscitate did not change. From logistic regression, after controlling for age, race, end-stage liver disease, stroke, cancer, hospital unit, and sepsis, patients in the postintervention period were two times more likely to have CS addressed (odds ratio [OR] = 2.04, p < .001). There was a significant improvement in CS documentation from our interventions.

Implementation Status of the Proposal for a Regulation of the European Health Data Space in Portugal: Are We Ready for It?

The European Health Data Space (EHDS) proposal aims to establish a set of rules and governance frameworks to promote the use of electronic health data for both primary and secondary purposes. This study aims at analysing the implementation status of the EHDS proposal in Portugal, particularly the points concerning the primary use of health data. The proposal was scanned for the points that gave member states a direct responsibility to implement actions, and a literature review and interviews were conducted to assess the implementation status of these policies in Portugal This study found that Portugal is well advanced in the implementation of policies concerning the rights of natural persons in relation to the primary use of their personal health data, but also identified challenges, which include the lack of a common interoperability framework for the exchange of electronic health data.

Accuracy of Electronic Health Record Food Insecurity, Housing Instability, and Financial Strain Screening in Adult Primary Care.

This study assesses the accuracy of electronic health record­based screening questionnaires about social risk factors using external single-domain questionnaires as a comparator.

Enhanced Communication for Interhospital Transfers Increases Preparedness in an Academic Tertiary Care Center.

OBJECTIVES: This quality improvement project sought to enhance clinical information sharing for interhospital transfers to an inpatient hepatology service comprised of internal medicine resident frontline providers (housestaff) with the specific aims of making housestaff aware of 100% of incoming transfers and providing timely access to clinical summaries. INTERVENTIONS: In February 2020, an email notification system to senior medicine residents responsible for patient triage shared planned arrival time for patients pending transfer. In July 2020, a clinical data repository ("Transfer Log") updated daily by accepting providers (attending physicians and subspecialty fellows) became available to senior medicine residents responsible for triage. METHODS: Likert scale surveys were administered to housestaff before email intervention (pre) and after transfer log intervention (post). The time from patient arrival to team assignment (TTA) in the electronic medical record was used as a proxy for time to patient assessment and was measured pre- and postinterventions; >2 hours to TTA was considered an extreme delay. RESULTS: Housestaff reported frequency of access to clinical information as follows: preinterventions 4/31 (13%) sometimes/very often and 27/31 (87%) never/rarely; postinterventions 11/26 (42%) sometimes/very often and 15/26 (58%) never/rarely (p = 0.02). Preinterventions 12/39 (31%) felt "not at all prepared" versus 27/39 (69%) "somewhat" or "adequately"; postinterventions 2/24 (8%) felt "not at all prepared" versus 22/24 (92%) somewhat/adequately prepared (p = 0.06). There was a significant difference in mean TTA between pre- and posttransfer log groups (62 vs. 40 minutes, p = 0.01) and a significant reduction in patients with extreme delays in TTA post-email (18/180 pre-email vs. 7/174 post-email, p = 0.04). CONCLUSION: Early notification and increased access to clinical information were associated with better sense of preparedness for admitting housestaff, reduction in TTA, and reduced frequency of extreme delays in team assignment.

Do Health Technology Safety Issues Vary by Vendor?

There is a need to determine the relative similarity and differences in safety issues across specific types of software and medical devices in order to develop standardized solutions that can be used across these technologies. Over the past several years, health informatics researchers have identified differing types of technology-induced errors or safety issues. This work has led to a literature that has been effective in identifying varying technology-induced errors. Less effort has been made in attempting to understand if there are common types of safety issues and outcomes across vendors for specific types of technology such as electronic health records (EHRs). Our findings demonstrate that some safety issues are common across the same type of software. The findings suggest there is a need to develop standardized approaches to managing technology-induced errors.

Comparison of Medical Cannabis Use Reported on a Confidential Survey vs Documented in the Electronic Health Record Among Primary Care Patients.

Importance: Patients who use cannabis for medical reasons may benefit from discussions with clinicians about health risks of cannabis and evidence-based treatment alternatives. However, little is known about the prevalence of medical cannabis use in primary care and how often it is documented in patient electronic health records (EHR). Objective: To estimate the primary care prevalence of medical cannabis use according to confidential patient survey and to compare the prevalence of medical cannabis use documented in the EHR with patient report. Design, Setting, and Participants: This study is a cross-sectional survey performed in a large health system that conducts routine cannabis screening in Washington state where medical and nonmedical cannabis use are legal. Among 108 950 patients who completed routine cannabis screening (between March 28, 2019, and September 12, 2019), 5000 were randomly selected for a confidential survey about cannabis use, using stratified random sampling for frequency of past-year use and patient race and ethnicity. Data were analyzed from November 2020 to December 2021. Exposures: Survey measures of patient-reported past-year cannabis use, medical cannabis use (ie, explicit medical use), and any health reason(s) for use (ie, implicit medical use). Main Outcomes and Measures: Survey data were linked to EHR data in the year before screening. EHR measures included documentation of explicit and/or implicit medical cannabis use. Analyses estimated the primary care prevalence of cannabis use and compared EHR-documented with patient-reported medical cannabis use, accounting for stratified sampling and nonresponse. Results: Overall, 1688 patients responded to the survey (34% response rate; mean [SD] age, 50.7 [17.5] years; 861 female [56%], 1184 White [74%], 1514 non-Hispanic [97%], and 1059 commercially insured [65%]). The primary care prevalence of any past-year patient-reported cannabis use on the survey was 38.8% (95% CI, 31.9%-46.1%), whereas the prevalence of explicit and implicit medical use were 26.5% (95% CI, 21.6%-31.3%) and 35.1% (95% CI, 29.3%-40.8%), respectively. The prevalence of EHR-documented medical cannabis use was 4.8% (95% CI, 3.45%-6.2%). Compared with patient-reported explicit medical use, the sensitivity and specificity of EHR-documented medical cannabis use were 10.0% (95% CI, 4.4%-15.6%) and 97.1% (95% CI, 94.4%-99.8%), respectively. Conclusions and Relevance: These findings suggest that medical cannabis use is common among primary care patients in a state with legal use, and most use is not documented in the EHR. Patient report of health reasons for cannabis use identifies more medical use compared with explicit questions about medical use.

Remote Monitoring of Patient- and Family-Generated Health Data in Pediatrics.

In this article, we provide an overview of remote monitoring of pediatric PGHD and family-generated health data, including its current uses, future opportunities, and implementation resources.

Perceived Security Risk Based on Moderating Factors for Blockchain Technology Applications in Cloud Storage to Achieve Secure Healthcare Systems.

Due to the high amount of electronic health records, hospitals have prioritized data protection. Because it uses parallel computing and is distributed, the security of the cloud cannot be guaranteed. Because of the large number of e-health records, hospitals have made data security a major concern. The cloud's security cannot be guaranteed because it uses parallel processing and is distributed. The blockchain (BC) has been deployed in the cloud to preserve and secure medical data because it is particularly prone to security breaches and attacks such as forgery, manipulation, and privacy leaks. An overview of blockchain (BC) technology in cloud storage to improve healthcare system security can be obtained by reading this paper. First, we will look at the benefits and drawbacks of using a basic cloud storage system. After that, a brief overview of blockchain cloud storage technology will be offered. Many researches have focused on using blockchain technology in healthcare systems as a possible solution to the security concerns in healthcare, resulting in tighter and more advanced security requirements being provided. This survey could lead to a blockchain-based solution for the protection of cloud-outsourced healthcare data. Evaluation and comparison of the simulation tests of the offered blockchain technology-focused studies can demonstrate integrity verification with cloud storage and medical data, data interchange with reduced computational complexity, security, and privacy protection. Because of blockchain and IT, business warfare has emerged, and governments in the Middle East have embraced it. Thus, this research focused on the qualities that influence customers' interest in and approval of blockchain technology in cloud storage for healthcare system security and the aspects that increase people's knowledge of blockchain. One way to better understand how people feel about learning how to use blockchain technology in healthcare is through the United Theory of Acceptance and Use of Technology (UTAUT). A snowball sampling method was used to select respondents in an online poll to gather data about blockchain technology in Middle Eastern poor countries. A total of 443 randomly selected responses were tested using SPSS. Blockchain adoption has been shown to be influenced by anticipation, effort expectancy, social influence (SI), facilitation factors, personal innovativeness (PInn), and a perception of security risk (PSR). Blockchain adoption and acceptance were found to be influenced by anticipation, effort expectancy, social influence (SI), facilitating conditions, personal innovativeness (PInn), and perceived security risk (PSR) during the COVID-19 pandemic, as well as providing an overview of current trends in the field and issues pertaining to significance and compatibility.

Evaluating Completeness of Discrete Data on Physical Functioning for Children With Cerebral Palsy in a Pediatric Rehabilitation Learning Health System.

OBJECTIVE: The purpose of this study was to determine the extent that physical function discrete data elements (DDE) documented in electronic health records (EHR) are complete within pediatric rehabilitation settings. METHODS: A descriptive analysis on completeness of EHR-based DDEs detailing physical functioning for children with cerebral palsy was conducted. Data from an existing pediatric rehabilitation research learning health system data network, consisting of EHR data from 20 care sites in a pediatric specialty health care system, were leveraged. Completeness was calculated for unique data elements, unique outpatient visits, and unique outpatient records. RESULTS: Completeness of physical function DDEs was low across 5766 outpatient records (10.5%, approximately 2 DDEs documented). The DDE for Gross Motor Function Classification System level was available for 21% (n = 3746) outpatient visits and 38% of patient records. Ambulation level was the most frequently documented DDE. Intercept only mixed effects models demonstrated that 21.4% and 45% of the variance in completeness for DDEs and the Gross Motor Function Classification System, respectively, across unique patient records could be attributed to factors at the individual care site level. CONCLUSION: Values of physical function DDEs are missing in designated fields of the EHR infrastructure for pediatric rehabilitation providers. Although completeness appears limited for these DDEs, our observations indicate that data are not missing at random and may be influenced by system-level standards in clinical documentation practices between providers and factors specific to individual care sites. The extent of missing data has significant implications for pediatric rehabilitation quality measurement. More research is needed to understand why discrete data are missing in EHRs and to further elucidate the professional and system-level factors that influence completeness and missingness. IMPACT: Completeness of DDEs reported in this study is limited and presents a significant opportunity to improve documentation and standards to optimize EHR data for learning health system research and quality measurement in pediatric rehabilitation settings.

Implementation of an electronic identification system in the setting of perioperative autologous cell salvage transfusion: Experience at a university hospital.

Perioperative autologous cell salvage (PACS) is one of the effective strategies in patient blood management (PBM). However, mistransfusion, in which the wrong blood is transfused to the wrong patient, of PACS units has been reported. In this study, we implemented a bar code-based electronic identification system (EIS) for blood transfusion in the setting of PACS transfusion. Between February 2009 and December 2020, a total of 12341 surgical patients (9% of whom received surgical interventions) received blood transfusion, among whom 6595 (54 %) received autologous blood transfusion alone, 2877 (23 %) both autologous and allogeneic blood transfusions, and 2869 (23 %) allogeneic blood transfusion alone. Among autologous blood conservation techniques, PACS units were transfused to 7873 patients (83 %) without a single mistransfusion. Rates of overall compliance with the electronic pre-transfusion check at the bedside for all autologous units and PACS units were 98.8 and 98.5 %, respectively. Our observations suggest that a bar code-based EIS can be successfully applied to PACS transfusion, as well as allogeneic blood transfusion in operating rooms.

Spinal pain and major depression in a military cohort: bias analysis of dependent misclassification in electronic medical records.

BACKGROUND: Spinal pain and major depression are prevalent conditions in adult populations and are particularly impactful in the military. However, the temporal relationship between these two conditions remains poorly understood. METHODS: Using data extracted from electronic medical records, we assessed the association between incident diagnoses of spinal pain and major depression in a cohort of 48,007 Canadian Armed Forces personnel followed from January 2017 to August 2018. We used multivariate Poisson regression to measure the association between the period prevalence of these two conditions. We used probabilistic bias modelling to correct our estimates for misclassification of spinal pain and major depression. RESULTS: After correcting for misclassification with probabilistic bias modelling, subjects newly diagnosed with spinal pain during the study period were 1.41 times (95% interval 1.25, 1.59) more likely also to be diagnosed with incident major depression, and personnel newly diagnosed with major depression were 1.28 times (95% interval 1.17, 1.39) more likely also to be diagnosed with spinal pain, compared to undiagnosed counterparts of the same age and sex. Without bias corrections, we would have overestimated the magnitude of the association between major depression and spinal pain by a factor of approximately 2.0. CONCLUSION: Our results highlight a moderate and bi-directional association between two of the most prevalent disorders in military populations. Our results also highlight the importance of correcting for misclassification in electronic medical record data research.

Comparison of paper and electronic documentation for trauma activations in a pediatric trauma center.

BACKGROUND: There are limited data on the accuracy of documentation of trauma activations in the electronic medical record (EMR) compared with a paper chart. Our primary objective was to compare the accuracy of documentation between a paper chart and EMR in pediatric trauma. METHODS: We studied video recordings of trauma activations at a level 1 pediatric trauma center. These videos were reviewed, and data points collected were used to compare accuracy of documentation in the paper chart and EMR. RESULTS: We reviewed 106 videos with 1614 data points collected. Of those, 805 data points were compared with their corresponding paper chart with 710 data points correctly documented (88.2%). The remaining 809 data points were compared with their corresponding electronic documentation after implementation of the EMR with 681 data points being correctly documented (84.2%). Overall, we found that paper documentation was significantly more accurate than the EMR (p = 0.019). When analyzed in subcategories of pre-arrival information, primary and secondary survey, and interventions, paper documentation was found to be significantly more accurate than the EMR for components of the primary and secondary survey (87.3% vs. 80.4%, p = 0.001). There was no significant difference in accuracy of documentation between paper and EMR for pre-arrival information (88.1% vs. 89.4%) or interventions (90.3% vs. 92%). CONCLUSION: Documentation of trauma activations is overall more accurate using a paper chart than EMR. Although documentation was accurate for most categories using both a paper chart and EMR, we found significantly less accuracy in documentation of the primary and secondary survey in the EMR.