Utilizing nursing standards in electronic health records: A descriptive qualitative study.

BACKGROUND: The electronic health record (EHR), including standardized structures and languages, represents an important data source for nurses, to continually update their individual and shared perceptual understanding of clinical situations. Registered nurses' utilization of nursing standards, such as standardized nursing care plans and language in EHRs, has received little attention in the literature. Further research is needed to understand nurses' care planning and documentation practice. AIMS: This study aimed to describe the experiences and perceptions of nurses' EHR documentation practices utilizing standardized nursing care plans including standardized nursing language, in the daily documentation of nursing care for patients living in special dementia-care units in nursing homes in Norway. METHODS: A descriptive qualitative study was conducted between April and November 2021 among registered nurses working in special dementia care units in Norwegian nursing homes. In-depth interviews were conducted, and data was analyzed utilizing reflexive thematic analysis with a deductive orientation. Findings Four themes were generated from the analysis. First, the knowledge, skills, and attitude of system users were perceived to influence daily documentation practice. Second, management and organization of documentation work, internally and externally, influenced motivation and engagement in daily documentation processes. Third, usability issues of the EHR were perceived to limit the daily workflow and the nurses' information-needs. Last, nursing standards in the EHR were perceived to contribute to the development of documentation practices, supporting and stimulating ethical awareness, cognitive processes, and knowledge development. CONCLUSION: Nurses and nursing leaders need to be continuously involved and engaged in EHR documentation to safeguard development and implementation of relevant nursing standards.

The implementation of a multidisciplinary, electronic health record embedded care pathway to improve structured data recording and decrease electronic health record burden.

INTRODUCTION: Theoretically, the added value of electronic health records (EHRs) is extensive. Reusable data capture in EHRs could lead to major improvements in quality measurement, scientific research, and decision support. To achieve these goals, structured and standardized recording of healthcare data is a prerequisite. However, time spent on EHRs by physicians is already high. This study evaluated the effect of implementing an EHR embedded care pathway with structured data recording on the EHR burden of physicians. MATERIALS AND METHODS: Before and six months after implementation, consultations were recorded and analyzed with video-analytic software. Main outcome measures were time spent on specific tasks within the EHR, total consultation duration, and usability indicators such as required mouse clicks and keystrokes. Additionally, a validated questionnaire was completed twice to evaluate changes in physician perception of EHR system factors and documentation process factors. RESULTS: Total EHR time in initial oncology consultations was significantly reduced by 3.7 min, a 27 % decrease. In contrast, although a decrease of 13 % in consultation duration was observed, no significant effect on EHR time was found in follow-up consultations. Additionally, perceptions of physicians regarding the EHR and documentation improved significantly. DISCUSSION: Our results have shown that it is possible to achieve structured data capture while simultaneously reducing the EHR burden, which is a decisive factor in end-user acceptance of documentation systems. Proper alignment of structured documentation with workflows is critical for success. CONCLUSION: Implementing an EHR embedded care pathway with structured documentation led to decreased EHR burden.

Healthcare Resource Utilization and Costs in an At-Risk Population With Diabetic Retinopathy.

Purpose: Several investigators have suggested the cost-effectiveness of earlier screening, management of risk factors, and early treatment for diabetic retinopathy (DR). We aimed to evaluate the extent of health care utilization and cost of delayed care by insurance type in a vulnerable patient population. Methods: A retrospective analysis of patients with DR was conducted using electronic medical record (EMR) data from January 2014 to December 2020 at Denver Health Medical Center, a safety net institution. Patients were classified by disease severity and insurance status. DR-specific costs were assessed via Current Procedural Terminology (CPT) codes over a 24-month follow-up period. Results: Among the 313 patients, a higher proportion of non-English speaking patients were uninsured. Rates of proliferative DR at presentation differed across insurance groups (62% of uninsured, 42% of discount plan, and 33% of Medicare/Medicaid, P = 0.016). There was a significant difference in the total median cost between discount plan patients ($1258, interquartile range [IQR] = $0 - $5901) and both Medicare patients ($751, IQR = $0, $7148, P = 0.037) and Medicaid patients ($593, IQR = $0 - $6299, P = 0.025). Conclusions: There were higher rates of proliferative DR at presentation among the uninsured and discount plan patients and greater total median cost in discount plan patients compared to Medicare or Medicaid. These findings prioritize mitigating gaps in insurance coverage and barriers to preventative care among vulnerable populations. Translational Relevance: Advanced diabetic disease and increased downstream health care utilization and cost vary across insurance type, suggesting improved access to preventative care is needed in these specific at-risk populations.

Assessing the frequency and types of errors involved in the use of a modified intravenous N-acetylcysteine protocol for acetaminophen overdose.

BACKGROUND: Acetaminophen overdose is a leading cause of acute liver failure in developing countries. N-acetylcysteine (NAC) is a highly effective antidote for acetaminophen hepatotoxicity, typically initiated in the emergency department. Due to a known high rate of errors with the standard three-bag IV NAC protocol, in 2019, the Ontario Poison Center changed to a modified 3% IV NAC one-bag protocol. This study was undertaken to determine the frequency and types of errors associated with the use of this protocol. METHODS: Data were gathered via chart review of Ontario Poison Centre electronic medical record cases identified as receiving IV NAC for acetaminophen overdose between August 1 and September 30, 2022. 218 total charts were identified, and 188 were deemed eligible based on inclusion and exclusion criteria. RESULTS: Errors were identified in 25% of charts, consisting of dosing errors in 11.7%, stopping errors in 9.0%, initiation errors in 3.7%, and interruptions in therapy in 3.2%. Dosing errors were the most common type of error (44.4%), with overdoses occurring three times more than underdoses. Errors were identified at 39% of geographic locations in the charts reviewed, with similar frequency in Ontario, Manitoba, and Nunavut. Clinical outcomes were similar in charts with and without errors. INTERPRETATION: The rate of errors identified with this 3% IV NAC one-bag protocol is lower than reported for the standard three-bag protocol, but remains high due to dosing errors. Previously reported issues with prolonged interruptions in therapy with the standard three-bag protocol were low with the current 3% one-bag protocol. Although severe outcomes are rare, IV NAC overdose can be fatal. Identifying local factors in emergency departments that can contribute to administration errors (i.e., dose calculation, pump programming issues) can enhance the safety of this important antidote.

RéSUMé: CONTEXTE: La surdose d'acétaminophène est l'une des principales causes d'insuffisance hépatique aiguë dans les pays en développement. La N-acétylcystéine (NAC) est un antidote très efficace contre l'hépatotoxicité de l'acétaminophène, généralement initiée au service des urgences. En raison d'un taux élevé connu d'erreurs avec le protocole NAC standard à 3 sacs IV, en 2019, le Centre antipoison de l'Ontario a adopté un protocole NAC à 1 sac IV modifié à 3 %. Cette étude a été entreprise pour déterminer la fréquence et les types d'erreurs associées à l'utilisation de ce protocole. MéTHODES: Les données ont été recueillies au moyen d'un examen des dossiers médicaux électroniques du Centre antipoison de l'Ontario qui ont reçu une dose IV de NAC pour une surdose d'acétaminophène entre le 1 août et le 30 septembre 2022. 218 cartes au total ont été identifiées, et 188 ont été jugées admissibles en fonction de critères d'inclusion et d'exclusion. RéSULTATS: Des erreurs ont été relevées dans 25 % des dossiers, soit des erreurs de dosage dans 11,7 %, des erreurs d'arrêt dans 9,0 %, des erreurs d'initiation dans 3,7 % et des interruptions du traitement dans 3,2 %. Les erreurs de dosage étaient le type d'erreur le plus courant (44,4 %), les surdoses étant trois fois plus fréquentes que les sous-doses. Des erreurs ont été relevées à 39 % des emplacements géographiques dans les cartes examinées, avec une fréquence similaire en Ontario, au Manitoba et au Nunavut. Les résultats cliniques étaient similaires dans les tableaux avec et sans erreurs. INTERPRéTATION: Le taux d'erreurs identifiées avec ce protocole à un sac NAC IV à 3 % est inférieur à celui du protocole standard à 3 sacs, mais reste élevé en raison d'erreurs de dosage. Les problèmes précédemment rapportés avec les interruptions prolongées du traitement avec le protocole standard à 3 sacs étaient faibles avec le protocole actuel à 3% à un sac. Bien que les résultats graves soient rares, une surdose de NAC IV peut être fatale. L'identification de facteurs locaux dans les services d'urgence qui peuvent contribuer aux erreurs d'administration (c.-à-d. le calcul de la dose, les problèmes de programmation de la pompe) peut améliorer l'innocuité de cet antidote important.

Polypharmacy and Potentially Inappropriate Medications in Patients With Advanced Cancer: Prevalence and Associated Factors at the End of Life.

Background: Polypharmacy and potentially inappropriate medications (PIMs) impose a burden on patients with advanced cancer near the end of their lives. However, only a few studies have addressed factors associated with PIMs in such patients. Objective: To examine polypharmacy and factors associated with PIMs in end-of-life patients with advanced cancer. Design: Retrospective chart review. Setting/Subjects: We analyzed 265 patients with advanced cancer who died in a palliative care unit (PCU) or at home in a home medical care (HMC) from April 2018 to December 2022 in Japan. Measurements: Sociodemographic, clinical, and prescription data at the time of PCU admission or HMC initiation were collected from electronic medical records. PIMs were assessed using OncPal Deprescribing Guidelines. Results: Patients with advanced cancer with an average age of 76.3 years and median survival days of 20 were included in the analyses. The average number of medications was 6.4 (standard deviation = 3.4), and PIMs were prescribed to 50.2%. Frequent PIMs included antihypertensive medications, peptic ulcer prophylaxis, and dyslipidemia medications. A multivariate logistic regression analysis revealed that age ≥75 years (adjusted odds ratio [aOR] = 2.30, 95% confidence interval [CI] = 1.30-4.05), referral from an outpatient setting compared with inpatient setting (aOR = 2.06, 95% CI = 1.12-3.80), more than two comorbidities (aOR = 1.88, 95% CI = 1.08-3.29), and more than five medications (aOR = 1.84, 95% CI = 1.03-3.28) were associated with PIMs. Conclusions: Medication reconciliation is recommended at the time of transition to a PCU or HMC, especially for older patients with advanced cancer who were referred from an outpatient setting and present more comorbidities and prescriptions.

Digital Solutions to Optimize Guideline-Directed Medical Therapy Prescriptions in Heart Failure Patients: Current Applications and Future Directions.

PURPOSEOF REVIEW: Guideline-directed medical therapy (GDMT) underuse is common in heart failure (HF) patients. Digital solutions have the potential to support medical professionals to optimize GDMT prescriptions in a growing HF population. We aimed to review current literature on the effectiveness of digital solutions on optimization of GDMT prescriptions in patients with HF. RECENT FINDINGS: We report on the efficacy, characteristics of the study, and population of published digital solutions for GDMT optimization. The following digital solutions are discussed: teleconsultation, telemonitoring, cardiac implantable electronic devices, clinical decision support embedded within electronic health records, and multifaceted interventions. Effect of digital solutions is reported in dedicated studies, retrospective studies, or larger studies with another focus that also commented on GDMT use. Overall, we see more studies on digital solutions that report a significant increase in GDMT use. However, there is a large heterogeneity in study design, outcomes used, and populations studied, which hampers comparison of the different digital solutions. Barriers, facilitators, study designs, and future directions are discussed. There remains a need for well-designed evaluation studies to determine safety and effectiveness of digital solutions for GDMT optimization in patients with HF. Based on this review, measuring and controlling vital signs in telemedicine studies should be encouraged, professionals should be actively alerted about suboptimal GDMT, the researchers should consider employing multifaceted digital solutions to optimize effectiveness, and use study designs that fit the unique sociotechnical aspects of digital solutions. Future directions are expected to include artificial intelligence solutions to handle larger datasets and relieve medical professional's workload.

Virtual quality improvement collaborative with primary care practices during COVID-19: a case study within a clinically integrated network.

INTRODUCTION: Quality improvement collaboratives (QICs) are a common approach to facilitate practice change and improve care delivery. Attention to QIC implementation processes and outcomes can inform best practices for designing and delivering collaborative content. In partnership with a clinically integrated network, we evaluated implementation outcomes for a virtual QIC with independent primary care practices delivered during COVID-19. METHODS: We conducted a longitudinal case study evaluation of a virtual QIC in which practices participated in bimonthly online meetings and monthly tailored QI coaching sessions from July 2020 to June 2021. Implementation outcomes included: (1) level of engagement (meeting attendance and poll questions), (2) QI capacity (assessments completed by QI coaches), (3) use of QI tools (plan-do-check-act (PDCA) cycles started and completed) and (4) participant perceptions of acceptability (interviews and surveys). RESULTS: Seven clinics from five primary care practices participated in the virtual QIC. Of the seven sites, five were community health centres, three were in rural counties and clinic size ranged from 1 to 7 physicians. For engagement, all practices had at least one member attend all online QIC meetings and most (9/11 (82%)) poll respondents reported meeting with their QI coach at least once per month. For QI capacity, practice-level scores showed improvements in foundational, intermediate and advanced QI work. For QI tools used, 26 PDCA cycles were initiated with 9 completed. Most (10/11 (91%)) survey respondents were satisfied with their virtual QIC experience. Twelve interviews revealed additional themes such as challenges in obtaining real-time data and working with multiple electronic medical record systems. DISCUSSION: A virtual QIC conducted with independent primary care practices during COVID-19 resulted in high participation and satisfaction. QI capacity and use of QI tools increased over 1 year. These implementation outcomes suggest that virtual QICs may be an attractive alternative to engage independent practices in QI work.

Use of Noisy Labels as Weak Learners to Identify Incompletely Ascertainable Outcomes: A Feasibility Study with Opioid-Induced Respiratory Depression.

Objective: Assigning outcome labels to large observational data sets in a timely and accurate manner, particularly when outcomes are rare or not directly ascertainable, remains a significant challenge within biomedical informatics. We examined whether noisy labels generated from subject matter experts' heuristics using heterogenous data types within a data programming paradigm could provide outcomes labels to a large, observational data set. We chose the clinical condition of opioid-induced respiratory depression for our use case because it is rare, has no administrative codes to easily identify the condition, and typically requires at least some unstructured text to ascertain its presence. Materials and Methods: Using de-identified electronic health records of 52,861 post-operative encounters, we applied a data programming paradigm (implemented in the Snorkel software) for the development of a machine learning classifier for opioid-induced respiratory depression. Our approach included subject matter experts creating 14 labeling functions that served as noisy labels for developing a probabilistic Generative model. We used probabilistic labels from the Generative model as outcome labels for training a Discriminative model on the source data. We evaluated performance of the Discriminative model with a hold-out test set of 599 independently-reviewed patient records. Results: The final Discriminative classification model achieved an accuracy of 0.977, an F1 score of 0.417, a sensitivity of 1.0, and an AUC of 0.988 in the hold-out test set with a prevalence of 0.83% (5/599). Discussion: All of the confirmed Cases were identified by the classifier. For rare outcomes, this finding is encouraging because it reduces the number of manual reviews needed by excluding visits/patients with low probabilities. Conclusion: Application of a data programming paradigm with expert-informed labeling functions might have utility for phenotyping clinical phenomena that are not easily ascertainable from highly-structured data.

Safety of direct-acting oral anticoagulant (DOAC) prescribing: OpenSAFELY-TPP analysis of 20.5 million adults' electronic health records.

BACKGROUND: During the COVID-19 pandemic many patients were switched from warfarin to DOACs which require the creatinine clearance calculated to ensure the correct dose is prescribed to avoid bleeding or reduced efficacy. AIM: To identify the study population proportion prescribed a DOAC. Of these, the proportion with recorded: weight, estimated Glomerular Filtration Rate (eGFR), creatinine, creatinine clearance (CrCl) and atrial fibrillation (AF). To analyse the proportion of patients with recorded AF and CrCl prescribed a recommended DOAC dose. DESIGN & SETTING: A retrospective cohort study of 20.5 million adult NHS patients' electronic health records (EHRs) in England in the OpenSAFELY-TPP platform (January 2018 to February 2023). METHOD: Patients on DOACs were analysed for age, sex, recorded weight, eGFR, creatinine, CrCl and AF. Prescribed DOAC doses in patients with recorded AF were compared to recommended doses for recorded CrCl and determined as either recommended, underdose or overdose. RESULTS: In February 2023, weight, eGFR, creatinine, CrCl, AF and, AF and CrCl were recorded in 72.8%; 92.4%; 94.3%; 73.5%; 73.9% of study population respectively. Both AF and CrCl were recorded for 56.7% of patients. Of these, 86.2% received the recommended and 13.8% non-recommended DOAC doses. CONCLUSIONS: CrCl is not recorded for a substantial number of patients on DOACs. We recommend that national organisations tasked with safety, collectively update guidance on the appropriate weight to use in the Cockcroft-Gault equation, clarify that CrCl is not equivalent to eGFR and work with GP clinical system suppliers to standardise the calculation of CrCl in the EHR.

Implementation of chronic kidney disease guidelines for sodium-glucose co-transporter-2 inhibitor use in primary care in the UK: a cross-sectional study.

Background: The cardiovascular and kidney benefits of sodium-glucose co-transporter-2 (SGLT2) inhibitors in people with chronic kidney disease (CKD) are well established. The implementation of updated SGLT2 inhibitor guidelines and prescribing in the real-world CKD population remains largely unknown. Methods: A cross-sectional study of adults with CKD registered with UK primary care practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre network on the 31st December 2022 was undertaken. Pseudonymised data from electronic health records held securely within the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub (ORCHID) were extracted. An update to a previously described ontological approach was used to identify the study population, using a combination of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) indicating a diagnosis of CKD and laboratory confirmed CKD based on Kidney Disease: Improving Global Outcomes (KDIGO) diagnostic criteria. We examined the extent to which SGLT2 inhibitor guidelines apply to and are then implemented in adults with CKD. A logistic regression model was used to identify factors associated with SGLT2 inhibitor prescribing, reported as odds ratios (ORs) with 95% confidence intervals (CI). The four guidelines under investigation were the United Kingdom Kidney Association (UKKA) Clinical Practice Guideline SGLT2 Inhibition in Adults with Kidney Disease (October 2021), American Diabetes Association (ADA) and KDIGO Consensus Report on Diabetes Management in CKD (October 2022), National Institute for Health and Care Excellence (NICE) Guideline Type 2 Diabetes in Adults: Management (June 2022), and NICE Technology Appraisal Dapagliflozin for Treating CKD (March 2022). Findings: Of 6,670,829 adults, we identified 516,491 (7.7%) with CKD, including 32.8% (n = 169,443) who had co-existing type 2 diabetes (T2D). 26.8% (n = 138,183) of the overall CKD population had a guideline directed indication for SGLT2 inhibitor treatment. A higher proportion of people with CKD and co-existing T2D were indicated for treatment, compared to those without T2D (62.8% [n = 106,468] vs. 9.1% [n = 31,715]). SGLT2 inhibitors were prescribed to 17.0% (n = 23,466) of those with an indication for treatment, and prescriptions were predominantly in those with co-existing T2D; 22.0% (n = 23,464) in those with T2D, and <0.1% (n = 2) in those without T2D. In adjusted multivariable analysis of people with CKD and T2D, females (OR 0.69, 95% CI 0.67-0.72, p <0.0001), individuals of Black ethnicity (OR 0.84, 95% CI 0.77-0.91, p <0.0001) and those of lower socio-economic status (OR 0.72, 95% CI 0.68-0.76, p <0.0001) were less likely to be prescribed an SGLT2 inhibitor. Those with an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 had a lower likelihood of receiving an SGLT2 inhibitor, compared to those with an eGFR ≥60 mL/min/1.73 m2 (eGFR 45-60 mL/min/1.73 m2 OR 0.65, 95% CI 0.62-0.68, p <0.0001, eGFR 30-45 mL/min/1.73 m2 OR 0.73, 95% CI 0.69-0.78, p <0.0001, eGFR 15-30 mL/min/1.73 m2 OR 0.52, 95% CI 0.46-0.60, p <0.0001, eGFR <15 mL/min/1.73 m2 OR 0.03, 95% CI 0.00-0.23, p = 0.0037, respectively). Those with albuminuria (urine albumin-to-creatinine ratio 3-30 mg/mmol) were less likely to be prescribed an SGLT2 inhibitor, compared to those without albuminuria (OR 0.78, 95% CI 0.75-0.82, p <0.0001). Interpretation: SGLT2 inhibitor guidelines in CKD have not yet been successfully implemented into clinical practice, most notably in those without co-existing T2D. Individuals at higher risk of adverse outcomes are paradoxically less likely to receive SGLT2 inhibitor treatment. The timeframe between the publication of guidelines and data extraction may have been too short to observe changes in clinical practice. Enhanced efforts to embed SGLT2 inhibitors equitably into routine care for people with CKD are urgently needed, particularly in those at highest risk of adverse outcomes and in the absence of T2D. Funding: None.

Improving Palivizumab Administration to High-Risk Infants with Heart Disease via a Communication-Based Quality Improvement Initiative.

To improve palivizumab administration in high-risk infants with congenital heart disease to 80% over 2 years at an academic children's heart center. A multidisciplinary team at our institution implemented a series of interventions over a 2-year prior. Pediatric cardiac patients were identified for palivizumab eligibility, and a baseline rate of administration was obtained. A series of communication and documentation-based interventions were implemented over the course of the next 2 years. Palivizumab eligible infants (n = 114) were determined based on guidelines after review of diagnosis code, oxygen saturation, and medications. Doses of palivizumab were tracked via the electronic health record. The primary outcome measures were the rate of monthly palivizumab doses administered per the number of eligible months and the percentage of infants who received at least 80% of eligible doses during the respiratory syncytial virus season. The rate of monthly palivizumab doses increased from 57.6% during the baseline period to 78.4% during the final year of the project (p = 0.02). The percentage of infants who received 80% of eligible doses increased from 42.1 to 60% but was not statistically significant (p = 0.20). Interventions focused on properly identifying and tracking infants eligible for palivizumab treatment significantly increased the rates of administration.

Patterns of multimorbidity in primary care electronic health records: A systematic review.

Background: Multimorbidity, the coexistence of multiple chronic conditions in an individual, is a complex phenomenon that is highly prevalent in primary care settings, particularly in older individuals. This systematic review summarises the current evidence on multimorbidity patterns identified in primary care electronic health record (EHR) data. Methods: Three databases were searched from inception to April 2022 to identify studies that derived original multimorbidity patterns from primary care EHR data. The quality of the included studies was assessed using a modified version of the Newcastle-Ottawa Quality Assessment Scale. Results: Sixteen studies were included in this systematic review, none of which was of low quality. Most studies were conducted in Spain, and only one study was conducted outside of Europe. The prevalence of multimorbidity (i.e. two or more conditions) ranged from 14.0% to 93.9%. The most common stratification variable in disease clustering models was sex, followed by age and calendar year. Despite significant heterogeneity in clustering methods and disease classification tools, consistent patterns of multimorbidity emerged. Mental health and cardiovascular patterns were identified in all studies, often in combination with diseases of other organ systems (e.g. neurological, endocrine). Discussion: These findings emphasise the frequent coexistence of physical and mental health conditions in primary care, and provide useful information for the development of targeted preventive and management strategies. Future research should explore mechanisms underlying multimorbidity patterns, prioritise methodological harmonisation to facilitate the comparability of findings, and promote the use of EHR data globally to enhance our understanding of multimorbidity in more diverse populations.

Implementation and evaluation of Exercise is Medicine in primary care clinics within a large academic health system.

OBJECTIVE: Exercise is Medicine (EIM) is a global initiative encouraging healthcare providers to routinely assess and promote physical activity (PA) among patients. The objective of this study was to evaluate the feasibility, adoption, implementation and effectiveness of EIM from patient, clinician and healthcare staff perspectives using a combination of electronic health record (EHR), survey and interview data. DESIGN: This study used a combination of the Practical Robust Implementation and Sustainability Model (PRISM) and the Learning Evaluation model to implement EIM. Data captured from the EHR, including Physical Activity Vital Sign (PAVS) scores, and data collected from qualitative surveys and interviews were used to evaluate the programme's Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM, which is embedded within PRISM) from provider, staff and patient perspectives. SETTING: Five primary care clinics within a large academic health system. PARTICIPANTS: A total of 24 443 patients from all participating clinics had at least one PAVS score during the study period. A total of 17 clinicians completed surveys, and 4 clinicians, 8 medical assistants and 9 patients completed interviews. RESULTS: Implementation fidelity metrics varied widely between components and across clinics but were generally consistent over time, indicating a high degree of programme maintenance. Fidelity was highest during the first 6 months of the COVID-19 pandemic when most visits were virtual. Mean PAVS scores increased from 57.7 (95% CI: 56 to 59.4) to 95.2 (95% CI: 91.6 to 98.8) min per week at 6 months for patients not meeting PA guidelines at baseline and decreased from 253.84 (95% CI: 252 to 255.7) to 208.3 (95% CI: 204.2 to 212.4) min per week at 6 months for patients meeting PA guidelines at baseline. After EIM implementation, clinician-estimated time spent discussing PA with patients increased for 35% of providers and stayed the same for 53%. CONCLUSION: Overall, this study established EIM's feasibility, adoption, implementation and maintenance in routine primary care practice within a large academic health system. From a population health perspective, EIM is a model to emulate to help primary care providers efficiently address healthy lifestyle behaviours in routine primary care visits.

Temporary Financial Assistance Reduced The Probability Of Unstable Housing Among Veterans For More Than 1 Year.

The Department of Veterans Affairs (VA) aims to reduce homelessness among veterans through programs such as Supportive Services for Veteran Families (SSVF). An important component of SSVF is temporary financial assistance. Previous research has demonstrated the effectiveness of temporary financial assistance in reducing short-term housing instability, but studies have not examined its long-term effect on housing outcomes. Using data from the VA's electronic health record system, we analyzed the effect of temporary financial assistance on veterans' housing instability for three years after entry into SSVF. We extracted housing outcomes from clinical notes, using natural language processing, and compared the probability of unstable housing among veterans who did and did not receive temporary financial assistance. We found that temporary financial assistance rapidly reduced the probability of unstable housing, but the effect attenuated after forty-five days. Our findings suggest that to maintain long-term housing stability for veterans who have exited SSVF, additional interventions may be needed.

The validity of electronic health data for measuring smoking status: a systematic review and meta-analysis.

BACKGROUND: Smoking is a risk factor for many chronic diseases. Multiple smoking status ascertainment algorithms have been developed for population-based electronic health databases such as administrative databases and electronic medical records (EMRs). Evidence syntheses of algorithm validation studies have often focused on chronic diseases rather than risk factors. We conducted a systematic review and meta-analysis of smoking status ascertainment algorithms to describe the characteristics and validity of these algorithms. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. We searched articles published from 1990 to 2022 in EMBASE, MEDLINE, Scopus, and Web of Science with key terms such as validity, administrative data, electronic health records, smoking, and tobacco use. The extracted information, including article characteristics, algorithm characteristics, and validity measures, was descriptively analyzed. Sources of heterogeneity in validity measures were estimated using a meta-regression model. Risk of bias (ROB) in the reviewed articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. RESULTS: The initial search yielded 2086 articles; 57 were selected for review and 116 algorithms were identified. Almost three-quarters (71.6%) of algorithms were based on EMR data. The algorithms were primarily constructed using diagnosis codes for smoking-related conditions, although prescription medication codes for smoking treatments were also adopted. About half of the algorithms were developed using machine-learning models. The pooled estimates of positive predictive value, sensitivity, and specificity were 0.843, 0.672, and 0.918 respectively. Algorithm sensitivity and specificity were highly variable and ranged from 3 to 100% and 36 to 100%, respectively. Model-based algorithms had significantly greater sensitivity (p = 0.006) than rule-based algorithms. Algorithms for EMR data had higher sensitivity than algorithms for administrative data (p = 0.001). The ROB was low in most of the articles (76.3%) that underwent the assessment. CONCLUSIONS: Multiple algorithms using different data sources and methods have been proposed to ascertain smoking status in electronic health data. Many algorithms had low sensitivity and positive predictive value, but the data source influenced their validity. Algorithms based on machine-learning models for multiple linked data sources have improved validity.

Bolstering Advance Care Planning Measurement Using Natural Language Processing.

Despite its growth as a clinical activity and research topic, the complex dynamic nature of advance care planning (ACP) has posed serious challenges for researchers hoping to quantitatively measure it. Methods for measurement have traditionally depended on lengthy manual chart abstractions or static documents (e.g., advance directive forms) even though completion of such documents is only one aspect of ACP. Natural language processing (NLP), in the form of an assisted electronic health record (EHR) review, is a technological advancement that may help researchers better measure ACP activity. In this article, we aim to show how NLP-assisted EHR review supports more accurate and robust measurement of ACP. We do so by presenting three example applications that illustrate how using NLP for this purpose supports (1) measurement in research, (2) detailed insights into ACP in quality improvement, and (3) identification of current limitations of ACP in clinical settings.

Stressful life events in electronic health records: a scoping review.

OBJECTIVES: Stressful life events, such as going through divorce, can have an important impact on human health. However, there are challenges in capturing these events in electronic health records (EHR). We conducted a scoping review aimed to answer 2 major questions: how stressful life events are documented in EHR and how they are utilized in research and clinical care. MATERIALS AND METHODS: Three online databases (EBSCOhost platform, PubMed, and Scopus) were searched to identify papers that included information on stressful life events in EHR; paper titles and abstracts were reviewed for relevance by 2 independent reviewers. RESULTS: Five hundred fifty-seven unique papers were retrieved, and of these 70 were eligible for data extraction. Most articles (n = 36, 51.4%) were focused on the statistical association between one or several stressful life events and health outcomes, followed by clinical utility (n = 15, 21.4%), extraction of events from free-text notes (n = 12, 17.1%), discussing privacy and other issues of storing life events (n = 5, 7.1%), and new EHR features related to life events (n = 4, 5.7%). The most frequently mentioned stressful life events in the publications were child abuse/neglect, arrest/legal issues, and divorce/relationship breakup. Almost half of the papers (n = 7, 46.7%) that analyzed clinical utility of stressful events were focused on decision support systems for child abuse, while others (n = 7, 46.7%) were discussing interventions related to social determinants of health in general. DISCUSSION AND CONCLUSIONS: Few citations are available on the prevalence and use of stressful life events in EHR reflecting challenges in screening and storing of stressful life events.

Optimizing Outpatient Radiation Oncology Consult Workflow by Using Time-Driven Activity-Based Costing: Efficiency and Financial Impacts.

PURPOSE: Clinical efficiency is a key component of value-based health care. Our objective here was to identify workflow inefficiencies by using time-driven activity-based costing (TDABC) and evaluate the implementation of a new clinical workflow in high-volume outpatient radiation oncology clinics. METHODS: Our quality improvement study was conducted with the Departments of GI, Genitourinary (GU), and Thoracic Radiation Oncology at a large academic cancer center and four community network sites. TDABC was used to create process maps and optimize workflow for outpatient consults. Patient encounter metrics were captured with a real-time status function in the electronic medical record. Time metrics were compared using Mann-Whitney U tests. RESULTS: Individual patient encounter data for 1,328 consults before the intervention and 1,234 afterward across all sections were included. The median overall cycle time was reduced by 21% in GI (19 minutes), 18% in GU (16 minutes), and 12% at the community sites (9 minutes). The median financial savings per consult were $52 in US dollars (USD) for the GI, $33 USD for GU, $30 USD for thoracic, and $42 USD for the community sites. Patient satisfaction surveys (from 127 of 228 patients) showed that 99% of patients reported that their providers spent adequate time with them and 91% reported being seen by a care provider in a timely manner. CONCLUSION: TDABC can effectively identify opportunities to improve clinical efficiency. Implementing workflow changes on the basis of our findings led to substantial reductions in overall encounter cycle times across several departments, as well as high patient satisfaction and significant financial savings.

A Mixed Methods Analysis of Standardized Documentation of Serious Illness Conversations Within an Electronic Health Record Module During Hospitalization.

BACKGROUND: Analysis of documented Serious Illness Conversations (SICs) in the inpatient setting can help clinicians align management to address patient and caregiver needs. METHODS: We conducted a mixed methods analysis of the first instance of standardized documentation of a SIC within a structured module among hospitalized general medicine patients from 2018 to 2019. Percentage of documentations that included a description of patient or family understanding of the patient's medical condition and use of radio buttons to answer the "prognostic information shared," "hopes," and "worries" modules are reported. Using grounded theory approach, physicians analyzed free text entries to: "What is important to the patient/family?" and "Recommendations or next steps planned." RESULTS: Out of 5142 patients, 59 patients had a documented SIC. Patient or family understanding of the medical condition(s) was reported in 56 (95%). For "prognostic information shared," the most frequently selected radio buttons were: 49 (83%) incurable disease and 28 (48%) prognosis of weeks to months while those for "hopes" were: 52 (88%) be comfortable and 27 (46%) be at home and for "worries" were: 49 (83%) other physical suffering and 36 (61%) pain. Themes generated from entries to "What's important to patient/family?" included being with loved ones; comfort; mentally and physically present; and reliable care while those for "Recommendations" were coordinating support services; symptom management; and support and communication. CONCLUSIONS: SIC content indicated concern about pain and reliable care suggesting the complex, intensive nature of caring for seriously ill patients and the need to consider SICs earlier in the life course of patients.