Health Records Research Articles

Osteoarthritis Across Joint Sites in the Million Veteran Program Cohort: Insights From Electronic Health Records and Military Service History.

To characterize the relationship between the frequency of idiopathic osteoarthritis (OA) and characteristics including demographics, comorbidities, military service history, and physical health in a veteran population. We performed a cohort study in the Million Veteran Program (MVP) using International Classification of Diseases, 9th and 10th revision codes to define the frequency of site-specific OA across 3 joints or unspecified OA in veterans with respect to demographics (eg, age, sex, race and ethnicity), military service data, detailed electronic health records, military branch, and war era. We validated previous reports of sex- and age-dependent differences in OA frequency, and we identified that unspecified OA was associated with a higher frequency of 16 Deyo-Charlson comorbidities. These associations generally persisted within each isolated joint site-specific OA. Depending on military branch, prior military engagement was differentially associated with the frequency of OA. Prior United States Army and Navy service were associated with higher and lower risk, respectively, of OA across all joint sites; however, multivariable-adjusted models adjusting for a range of covariates, including age, sex, and ancestry, reversed the apparent protective effect of prior Navy service. These findings highlight the breadth of factors associated with OA in the MVP veteran population and suggest that physical status may be a modifiable risk factor for OA. This work may help in the design of strategies to optimize appropriate detection, intervention, treatment, and even rehabilitation for OA in veterans and the general population.

Integrating Biomarker Testing into EHR Systems: Implications for the Laboratory Based on Findings from a Multistakeholder Summit

Abstract Introduction/Objective Guideline-driven tumor biomarker testing remains standard of care for precision oncology due to the increasing number of treatment decisions that can be made based on tumor-specific alterations. However, most electronic health record (EHR) systems lack bidirectional interfaces with labs that enable computerized order entry and tumor biomarker testing results. Without these integrations, cancer centers may experience delays in test ordering and resulting, manual data entry errors, and operational inefficiencies that impact patient care and survival outcomes. Methods/Case Report To explore how cancer centers, hospitals, oncology practices, and labs integrate EHRs to streamline cancer biomarker testing processes, the Association of Cancer Care Centers (ACCC), in partnership with LUNGevity, convened a multistakeholder summit on Oct. 4, 2023. The summit brought together clinicians, pathologists, genetic counselors, and administrators to discuss practical solutions to issues surrounding interoperability, clinical workflows, and access to clinical data. Results (if a Case Study enter NA) Key findings from the summit include: -EHR-integrated orders and results save time, reduce errors, and streamline clinical workflow. These electronic interfaces enable clear communication between multidisciplinary teams system-wide and ensure that required patient information is readily available at the time of therapy planning. -Standardized workflows that define test ordering, tracking, and resulting protocols for in-house and send-out testing offer important downstream benefits. Staff should clearly understand how specimens are handled for in-house and send-out testing. -Integrations should be planned and built based on the EHR/laboratory information systems (LIS) in place can incorporate solutions to integrate with reference labs using HL7 standards and/or add-on modules to enable discrete genomic data elements. Conclusion Clinicians, pathologists, and administrators should prioritize EHR/LIS integrations to enable more effective cancer biomarker test ordering and resulting. These pre/post-analytic processes have significant implications for patient care. Findings from this summit can enable cancer programs and labs to evaluate current processes, work collaboratively to build integrations, and streamline biomarker testing workflows to enhance the quality and efficiency of delivering precision oncology.

Performance of Machine Learning Suicide Risk Models in an American Indian Population

Few suicide risk identification tools have been developed specifically for American Indian and Alaska Native populations, even though these populations face the starkest suicide-related inequities. To examine the accuracy of existing machine learning models in a majority American Indian population. This prognostic study used secondary data analysis of electronic health record data collected from January 1, 2017, to December 31, 2021. Existing models from the Mental Health Research Network (MHRN) and Vanderbilt University (VU) were fitted. Models were compared with an augmented screening indicator that included any previous attempt, recent suicidal ideation, or a recent positive suicide risk screen result. The comparison was based on the area under the receiver operating characteristic curve (AUROC). The study was performed in partnership with a tribe and local Indian Health Service (IHS) in the Southwest. All patients were 18 years or older with at least 1 encounter with the IHS unit during the study period. Data were analyzed between October 6, 2022, and July 29, 2024. Suicide attempts or deaths within 90 days. Model performance was compared based on the ability to distinguish between those with a suicide attempt or death within 90 days of their last IHS visit with those without this outcome. Of 16 835 patients (mean [SD] age, 40.0 [17.5] years; 8660 [51.4%] female; 14 251 [84.7%] American Indian), 324 patients (1.9%) had at least 1 suicide attempt, and 37 patients (0.2%) died by suicide. The MHRN model had an AUROC value of 0.81 (95% CI, 0.77-0.85) for 90-day suicide attempts, whereas the VU model had an AUROC value of 0.68 (95% CI, 0.64-0.72), and the augmented screening indicator had an AUROC value of 0.66 (95% CI, 0.63-0.70). Calibration was poor for both models but improved after recalibration. This prognostic study found that existing risk identification models for suicide prevention held promise when applied to new contexts and performed better than relying on a combined indictor of a positive suicide risk screen result, history of attempt, and recent suicidal ideation.

Cybersecurity lessons from the Vastaamo psychotherapy data breach for psychiatrists and other mental healthcare providers.

The Vastaamo psychotherapy data breach in Finland is perhaps the largest cybersecurity incident in mental healthcare to date, resulting in significant patient harm. There are specific lessons for mental healthcare providers from an analysis of the incident. Case study of this specific electronic health record data breach, based on detailed media reporting. The issues raised include: the importance of governance of the cybersecurity of sensitive personal patient data, such as compliance with legislative requirements on privacy and data security; specific security measures such as de-identification of data, data protection via passwords, multi-factor authentication, firewalls and encryption; and timely and effective communication, and support of those who have been affected. The implications for mental healthcare providers, including psychiatrists and trainees, are that, within their capability, providers need to assess the efficacy and robustness of cybersecurity of electronic health record systems they use, and carefully consider the information that is recorded to minimise exposures such as in the Vastaamo breach.

Are Artificial Intelligence–Generated Replies the Answer to the Electronic Health Record Inbox Problem?

Are Artificial Intelligence–Generated Replies the Answer to the Electronic Health Record Inbox Problem?

Outcomes and Cost-Effectiveness of an EHR-Embedded AI Screener for Identifying Hospitalized Adults at Risk for Opioid Use Disorder.

Hospitalized adults with opioid use disorder (OUD) are at high risk for adverse events and rehospitalizations. This pre-post quasi-experimental study evaluated whether an AI-driven OUD screener embedded in the electronic health record (EHR) was non-inferior to usual care in identifying patients for Addiction Medicine consults, aiming to provide a similarly effective but more scalable alternative to human-led ad hoc consultations. The AI screener analyzed EHR notes in real-time with a convolutional neural network to identify patients at risk and recommend consultation. The primary outcome was the proportion of patients receiving consults, comparing a 16-month pre-intervention period to an 8-month post-intervention period with the AI screener. Consults did not change between periods (1.35% vs 1.51%, p < 0.001 for non-inferiority). The AI screener was associated with a reduction in 30-day readmissions (OR: 0.53, 95% CI: 0.30-0.91, p = 0.02) with an incremental cost of $6,801 per readmission avoided, demonstrating its potential as a scalable, cost-effective solution for OUD care. ClinicalTrials.gov ID : NCT05745480.

A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson's disease.

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments are directed at symptoms and lack ability to slow or prevent disease progression. Large-scale genome-wide association studies (GWAS) have identified numerous genomic loci associated with PD, which may guide the development of disease-modifying treatments. We presented a systems genetics approach to identify potential risk genes and repurposable drugs for PD. First, we leveraged non-coding GWAS loci effects on multiple human brain-specific quantitative trait loci (xQTLs) under the protein-protein interactome (PPI) network. We then prioritized a set of PD likely risk genes (pdRGs) by integrating five types of molecular xQTLs: expression (eQTLs), protein (pQTLs), splicing (sQTLs), methylation (meQTLs), and histone acetylation (haQTLs). We also integrated network proximity-based drug repurposing and patient electronic health record (EHR) data observations to propose potential drug candidates for PD treatments. We identified 175 pdRGs from QTL-regulated GWAS findings, such as SNCA , CTSB , LRRK2, DGKQ , CD38 and CD44 . Multi-omics data validation revealed that the identified pdRGs are likely to be druggable targets, differentially expressed in multiple cell types and impact both the parkin ubiquitin-proteasome and alpha-synuclein (a-syn) pathways. Based on the network proximity-based drug repurposing followed by EHR data validation, we identified usage of simvastatin as being significantly associated with reduced incidence of PD (fall outcome: hazard ratio (HR) = 0.91, 95% confidence interval (CI): 0.87-0.94; for dementia outcome: HR = 0.88, 95% CI: 0.86-0.89), after adjusting for 267 covariates. Our network-based systems genetics framework identifies potential risk genes and repurposable drugs for PD and other neurodegenerative diseases if broadly applied.

Characteristics of men and women with medically diagnosed cluster headache in a national integrated healthcare system: A Veterans Health Administration cohort study.

Describe the epidemiology of cluster headache (CH) using Veterans Health Administration (VHA) Electronic Health Record (EHR) data. Epidemiologic studies of CH at the population level are difficult because it has a prevalence of ~0.1%. Hospital system-wide studies are an attractive alternative as they have large numbers of patients and broader populations than headache or neurology clinic-based studies. The VHA is an ideal hospital-based system in which to study CH because it is nationwide, predominantly male, has a strong focus on mood disorders and suicidality, and has accessible individual medical records. Here, we report the first headache study based on an ongoing longitudinal cohort of patients with CH using VHA EHR data. The VHA EHR data were accessed from Fiscal Year 2008 to 2019. Patients with CH consisted of all patients with at least one outpatient visit containing a CH diagnosis code from the International Classification of Diseases (ICD)-9 or -10. We extracted data on demographic features, incidence, and prevalence, as well as pain and psychiatric comorbidities. Of the 1,524,960 distinct patients who presented for headache treatment in the VHA between Fiscal Year 2008-2019, 24,131 had at least one visit with a CH diagnosis. The 1-year period prevalence of a CH diagnosis in the VHA ranges from 0.08% to 0.10% for women and 0.10% to 0.18% for men. A larger proportion of women versus men received a diagnosis of unspecified CH (59.6% [1412/2368] vs. 53.6% [11,663/21,763], p < 0.001). Most patients with CH had both comorbid headache and non-headache pain diagnoses. Headache not-otherwise-specified was the most common comorbid headache disorder at 70.0% (16,885/24,131) and was more common in women (76.1%, 1801/2368) compared to men (69.3%, 15,084/21,763). Other common comorbidities included migraine, depression, tobacco use, and obstructive sleep apnea. Rates of suicidal ideation or attempt were almost 50% higher in women (5-year proportion 9.4%, 222/2368) with CH compared to men (6.6%, 1433/21,763). To our knowledge this is the largest hospital system study of CH to date and reinforces several previous studies. Pain, mental health, and sleep disorders comorbidities are particularly prevalent in this group and were often more common in women compared to men with CH. Future work should examine gender and race stratified prevalence estimates within the VHA and other healthcare systems.

Digital supervision in the clinical learning environment: Characterizing teamwork in the electronic health record.

Attending physicians in academic hospitals work in supervisory team structures with medical residents to provide patient care. How attendings utilize the electronic health record (EHR) to support learning through supervision is not well understood. To compare EHR behavior on teaching versus direct care, including evidence of supervisory calibration to learners. Cross-sectional study analysis of EHR metadata from 1721 shifts of hospital medicine faculty at a large, urban academic medical center, January to June 2022. Measures included total EHR time per shift, EHR time outside shift, and time spent on: note-writing, note review/attestation, order entry, and other clinical review. We assessed within physician differences across these service types and used multilevel modeling to determine whether these behaviors varied with resident physicians' experience, accounting for physician-specific signature behavior patterns. Attendings spent substantially less time in the EHR while on teaching service than on direct service (129 vs. 240 min; p < .001) and apportioned their work differently throughout the day. Physicians were less behaviorally consistent and varied more than their peers when on teaching service. Attendings calibrated their supervision to learners. Attendings logged 12.7% less EHR time when paired with more senior residents than postgraduate year 2 (PGY2) residents (137 vs. 120 min, p = .002). PGY1 presence was also associated with reduced EHR time, suggesting some delegation of supervision to senior trainees. EHR behaviors on teaching service are highly variable and differ substantially from direct care; a lack of consistency suggests important opportunities to establish best practices for EHR-based supervision and create an effective clinical learning environment.

Rethinking Measures and Mortality Attribution in Health Care: The ENT Example.

National performance metrics ultimately enhance patient decision-making and promote meaningful improvements in health care delivery, which makes having valid and reliable measures essential. This study examined US News and World Report metrics from 2019 to 2012 and used electronic health record data, combined with detailed chart review across 3 in-system hospitals, to assess the provision of care compared to the attribution of patients assigned to the ear, nose, and throat (ENT) mortality group. Of the initial 47 ENT-attributed deaths, 23 of those were verified, dimensioning the mortality rate from 1.7% to just 0.8%. These results underscore the necessity of rethinking measures and mortality attribution methodologies to be more accurate. Current methods use Medicare Severity Diagnosis Related Group billing coding to map the attribution. We suggest transitioning away from specialty ranking approaches and towards a procedure and condition "rating" approach to ensure that these ranking types capture data about the provision of care within a given encounter.

The role of patient reported symptom data in co-producing meaning in rheumatoid arthritis.

Patients with rheumatoid arthritis (RA) experience a range of symptoms including joint pain and inflammation, stiffness, fatigue, anxiety, and low mood. Similar to patients with other long-term conditions, they may have periods of time when their disease is under control, and times when their condition is less stable, requiring treatment adjustments. The REMORA2 feasibility study explored the implementation of an integrated symptom-tracking system using a smartphone application (app), enabling patients to track day-to-day symptoms. The data was available in the electronic health record to be viewed at subsequent consultations. This paper explores patients' comments on living with RA, and how patient-reported symptom data supports informed interactions as patients and clinicians work together to coproduce meaning from the data. Individual semi-structured interviews were conducted with 21 patients and 7 clinicians, supplemented by nonparticipant observations of 5 clinical appointments. Thematic analysis was used to analyse data from the interviews, with an ethnographic approach used to analyse the observational data. Both clinicians and patients reported the benefits of reviewing the data in the clinic together. This helped inform decisions about pain management and identified patients who might otherwise have dismissed symptoms such as pain, because of their natural inclination to be stoical. Improved insights on the care of RA were generated as patients and clinicians discuss symptom tracking data. This can assist the patient-clinician dyad in the process of two-way learning and shared decision-making on the management of a long-term condition.

Development and implementation of autoverification standardization in the adult and pediatric emergency department.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. This project utilized the guidance of the American Society of Health-System Pharmacists (ASHP) autoverification toolkit to refine our health system's approach to autoverification and contribute to the literature regarding appropriate use of autoverification technology in a pediatric and adult emergency department (ED). This single-center quality improvement study was conducted in an academic medical center ED that has 33 pediatric beds and 77 adult beds. A team consisting of clinical pharmacy specialists in emergency medicine, medication safety and informatics personnel, operational managers, and pharmacy leadership was identified to develop and implement autoverification best practices in the ED utilizing practices outlined within the ASHP autoverification toolkit. Before implementation of best practices, defined as the "preoptimization" state, autoverification took place for most medications available in the automated dispensing cabinets (ADCs). By anchoring the autoverification rule on ADC inventory, it was challenging to optimize both inventory practices and autoverification best practices. This project focused on redesigning the autoverification rules in the electronic health record, defined as the "postoptimization" state. In the postoptimization state, autoverification in the ED was updated to better align with regulatory standards. Autoverification metrics and the percentage of orders that autoverified vs required pharmacist verification were analyzed in the preoptimization and postoptimization states. This project utilized the guidance from ASHP's autoverification toolkit to refine our health system's approach to autoverification. High-alert medications (eg, insulin, extended-release opioids, digoxin) were taken off autoverification following implementation. Optimization of autoverification rules allows more orders for high-alert medications to be reviewed by a pharmacist.

Time-Driven, Activity-Based Cost Analysis of Pars Plana Vitrectomy in Rhegmatogenous Retinal Detachment at a Large Academic Center

Purpose: To perform a time-driven, activity-based cost analysis of retinal detachment (RD) surgery and compare it with reimbursement rates. Methods: This economic analysis at a single academic institution used time-driven, activity-based costing methodology to determine the cost of rhegmatogenous RD repair with primary pars plana vitrectomy. A process flow map was created to highlight each surgical case’s operative episodes, including clinical follow-ups. Time logs were obtained from the electronic health record for each operative phase and clinical follow-up. The overhead and anesthesia costs were collected from the institution’s cost accounting system. The direct material and personnel costs were obtained from internal financial data. Results: Seventy-six cases that met the inclusion criteria were included in the cost analysis study. The time-driven, activity-based cost of RD was $6247.17, and the reimbursement was $5442.91. Therefore, each procedure had a net negative loss of $804.26. To break even, the average operation time would need to be reduced from the determined average of 90.49 minutes to 64.90 minutes. Conclusions: This study found that Medicare underestimates the true cost of RD surgery. Changes in referral patterns may be motivated by reimbursement rates lower than the cost of the procedure, which could ultimately affect patient access to care.

A history of traumatic brain injury is associated with poorer cognition and imaging evidence of altered white matter tract integrity in UK Biobank (n = 50 376)

Abstract Traumatic brain injury (TBI) is a risk factor for neurodegenerative disease. We currently have no means to identify patients most at risk of neurodegenerative disease following injury and, resultantly, no means to target risk mitigation interventions. To address this, we explored the association between history of traumatic brain injury with cognitive performance and imaging measures of white matter integrity. From the UK Biobank imaging sub-study (n = 50 376), participants were identified with either self-reported (n = 177) or health record coded broad- (injury codes; n = 1096) or narrow-band (TBI specific codes; n = 274) TBI, or as controls with no such documented history (n = 49 280). Cognitive scores and imaging measures of corpus callosum white matter integrity were compared between injury participants (versus no injury), corrected for age, sex, socioeconomic status and medications. TBI was associated with poorer cognitive and imaging phenotypes. The strongest deleterious associations were for narrow-band injury (β difference 0.2–0.3; P &amp;lt; 0.01). All cognitive and imaging phenotypes were strongly inter-correlated (P &amp;lt; 0.001). This study provides insight into possible early biomarkers predating neurodegenerative disease following brain injury. Measures of cognition and white matter following injury may provide means to identify individuals most at risk of neurodegenerative disease, to which mitigation strategies might be targeted.

Predicting buprenorphine adherence among patients with opioid use disorder in primary care settings

BackgroundMedications for opioid use disorder (MOUD), including buprenorphine, are effective treatments for opioid use disorder (OUD) and reduce risk for overdose and death. Buprenorphine can be prescribed in outpatient primary care settings to treat OUD; however, prior research suggests adherence to buprenorphine in these settings can be low. The purpose of this study was to identify the rates of and factors associated with buprenorphine adherence among patients with OUD in the first six months after a new start of buprenorphine.MethodsData were extracted from the electronic health record (EHR) from a large integrated health system in the upper Midwest. Patients with OUD (N = 345; Mean age = 37.6 years, SD 13.2; 61.7% male; 78% White) with a new start of buprenorphine between March 2019 and July 2021 were included in the analysis. Buprenorphine adherence in the first six months was defined using medication orders; the proportion of days covered (PDC) with a standard cut-point of 80% was used to classify patients as adherent or non-adherent. Demographic (e.g., age, sex, race and ethnicity, geographic location), service (e.g., encounters, buprenorphine formulations and dosage) and clinical (e.g., diagnoses, urine toxicology screens) characteristics were examined as factors that could be related to adherence. Analyses included logistic regression with adherence group as a binary outcome.ResultsLess than half of patients were classified as adherent to buprenorphine (44%). Adjusting for other factors, male sex (OR = 0.34, 95% CI = 0.20, 0.57, p < .001) and having an unexpected positive for opioids on urine toxicology (OR = 0.42, 95% CI = 0.21, 0.83, p < .014) were associated with lower likelihood of adherence to buprenorphine, whereas being a former smoker (compared to a current smoker; OR = 1.82, 95% CI = 1.02, 3.27, p = .014) was associated with greater likelihood of being adherent to buprenorphine.ConclusionsThese results suggest that buprenorphine adherence in primary care settings may be low, yet male sex and smoking status are associated with adherence rates. Future research is needed to identify the mechanisms through which these factors are associated with adherence.

High caregiver adverse childhood experiences are associated with increased pediatric infection-related healthcare utilization and antibiotic use

Abstract Background Higher caregiver adverse childhood experiences (ACEs) have been associated with a range of pediatric outcomes, including hospitalizations. We recently found that higher caregiver ACEs are associated with higher rates of influenza vaccine uptake. However, to our knowledge, no studies have examined links between caregiver ACEs and specific infections or infection-related outcomes, such as antibiotics prescribed. We sought to evaluate associations between caregiver ACEs and pediatric infection-related outcomes. Methods We conducted a retrospective cohort study of two pediatric primary care sites, each serving a predominantly non-Hispanic Black, publicly insured population. At one primary care site (Clinic A), routine screenings for caregiver ACEs began in 2019 at the 1-month well-child check and were retrieved from the electronic health record. For the other primary care site (Clinic B), a prior research study surveyed caregiver ACEs of 283 children. Focusing on children 0-4 years of age in both primary care sites, we retrieved data from the electronic health record, including patient infection-related outcomes, demographic characteristics, and social risk screen results for those who had caregiver ACEs systematically recorded. The number of reported caregiver ACEs was our exposure variable, dichotomized as high (≥4) or low (≤3). Patient demographic characteristics, results of the overall social risk and maternal depression screen, and area deprivation index scores linked to patients’ geocoded home addresses were also collected. Bivariate analyses were pursued using chi square test statistics. Results A total of 1,442 children 0-4 years of age were included in the study, and 50.0% were female, 74.7% Black, and 2.6% Hispanic. Fifteen percent of caregivers had high (≥4) ACEs. Differences in infection-related outcomes, and relevant covariates, based on high and low caregiver ACEs are depicted in Table 1. Children of caregivers with high ACEs had more outpatient infection-related visits (80% versus 72.6%, p = 0.03), including more diagnoses of streptococcal pharyngitis (10.1% versus 4.1%, p = 0.0004). They also had more prescriptions for any oral antibiotic (30.9% versus 23.2%, p = 0.02). In bivariate analyses, high caregiver ACEs (31.3% versus 23.7%, p = 0.03), lower area deprivation index score (mean (SD) of 0.47 (0.16) versus 0.50 (0.16), p &amp;lt; 0.01), older patient age (mean (SD) of 2.73 (1.10) versus 1.73 (1.00) years, p &amp;lt; 0.0001), and any outpatient (35.9% versus 2.2%, p &amp;lt; 0.0001), emergent (40.0% versus 10.9%, p &amp;lt; 0.0001), or inpatient visit (42.7% versus 23.0%, p &amp;lt; 0.0001) were each associated with the presence of antibiotic use. Race, ethnicity, a positive social risk screen, and positive depression screen were not associated with antibiotic use. Conclusion High caregiver ACEs appear to be associated with some types of pediatric infectious diagnoses, antibiotic use and increased infection-related outpatient healthcare utilization. Future adjusted analyses assessing for potential links between ACEs and infection-related outcomes, independent of variables like insurance status, social risk, and area-level deprivation, are warranted and planned.

Application of a digital quality measure for cancer diagnosis in Epic Cosmos.

Missed and delayed cancer diagnoses are common, harmful, and often preventable. We previously validated a digital quality measure (dQM) of emergency presentation (EP) of lung cancer in 2 US health systems. This study aimed to apply the dQM to a new national electronic health record (EHR) database and examine demographic associations. We applied the dQM (emergency encounter followed by new lung cancer diagnosis within 30 days) to Epic Cosmos, a deidentified database covering 184 million US patients. We examined dQM associations with sociodemographic factors. The overall EP rate was 19.6%. EP rate was higher in Black vs White patients (24% vs 19%, P < .001) and patients with younger age, higher social vulnerability, lower-income ZIP code, and self-reported transport difficulties. We successfully applied a dQM based on cancer EP to the largest US EHR database. This dQM could be a marker for sociodemographic vulnerabilities in cancer diagnosis.

Physician-reported barriers and facilitators to thyroid hormone deprescribing in older adults.

Thyroid hormone is one of the most commonly prescribed medications in the United States. Misuse of and overtreatment with thyroid hormone is common in older adults and can lead to cardiovascular and skeletal adverse events. Even though deprescribing can reduce inappropriate care, no studies have yet explored specific barriers and facilitators to guide thyroid hormone deprescribing in older adults (defined as discontinuation of thyroid hormone when initiated without an appropriate indication or dose reduction in those overtreated). We conducted semi-structured interviews with 19 endocrinologists, geriatricians, and primary care physicians who prescribe thyroid hormone. Interviews were completed between July 2020 and December 2021 via two-way video conferencing. We used both an inductive and deductive content analysis guided by the Theoretical Domains Framework to evaluate transcribed and coded participant responses. Thematic analysis characterized themes related to barriers and facilitators to thyroid hormone deprescribing practices in older adults. The most commonly reported barriers to thyroid hormone deprescribing were related to patient-level factors, followed by physician- and system-level factors. Patient factors included patients' perceived need for thyroid hormone use and patient anxiety/concerns about potential side effects related to thyroid hormone dose reduction, patient lack of knowledge, and misinformation regarding deprescribing. Physician- and system-level barriers included clinic visit time constraints, physician inertia, physician lack of knowledge about deprescribing, perceived lack of sufficient patient follow-up, and electronic health record limitations. The most prominent physician-reported facilitators to thyroid hormone deprescribing were effective physician-to-patient communication, and positive physician-patient relationship, including patients' trust in their treating physician. Barriers and facilitators to thyroid hormone deprescribing in older adults were reported at multiple levels including patient-, physician-, and system-level factors. Interventions to improve thyroid hormone deprescribing in older adults should aim to improve patient education and expectations, increase multidisciplinary physician awareness, and overcome physician inertia.

Physical Restraint Use in Hospitalized Patients: A Study of Routinely Collected Health Records Data.

The use of restraints in hospitalized patients is associated with physical and psychological adversity for patients and staff. The minimization of restraint use is a key goal in the hospital setting. Reaching this goal requires an accurate assessment of existing patterns of use across clinical settings. This study reports the rate of physical restraints among patients hospitalized within a multi-entity healthcare network along with stratification by care context, diagnostic, and demographic factors, and examines the sensitivity and specificity of ICD-10 code Z78.1 "physical restraint status" for defining physical restraints relative to electronic health record (EHR) documentation. The EHR was used for a retrospective analysis of all adults hospitalized between 2017 and 2022. Hospitalized adults. Patient demographics, structured diagnostic information, care area, length of stay, and in-hospital mortality, Z78.1 coding for physical restraints, restraint documentation in orders and flowsheets. Among 742,607 hospitalizations, 6.3% (n=47,041) involved the use of physical restraint based on coding or EHR documentation. Treatment in the intensive care unit (ICU) included restraint in 39% of encounters whereas treatment outside the ICU included restraint use in 1.3% of encounters. Besides critical illness, demographic factors including increasing age (adjusted odds ratio (aOR)=1.21 [1.19-1.23]), male gender (aOR=1.56, [1.52-1.60]), unknown race (aOR=1.27 [1.19-1.35]), and preferred language other than English (aOR=1.24, [1.18-1.29]) were associated with higher odds of restraint utilization. As compared to EHR orders or documentation of restraint, the ICD-10 code for physical restraint had a sensitivity of 1.5% and a specificity of 99.99%. Among adults admitted to acute care hospitals, clinical, demographic, and operational factors were associated with increased odds of restraint, with care in the ICU associated with greatly increased odds of restraint. Research into restraint utilization using coded administrative claims data is likely limited by the sensitivity of physical restraint coding.

Cost Drivers of Pars Plana Vitrectomy for Retinal Detachment: Time-Driven Activity-Based Costing Analysis

Introduction: To determine drivers of day-of-surgery costs for pars plana vitrectomy (PPV) in the management of retinal detachment (RD) repair, the mainstay treatment, based on surgical complexity and intraoperative factors. Methods: Economic analysis was performed using time-driven activity-based costing methodology for patients who had standard (Current Procedural Terminology [CPT] code 67108) or complex (CPT 67113) RD repair with PPV at the University of Michigan in 2021. Data were obtained via the electronic health record and previous literature. PPV expenses were determined with time-driven activity-based costing, a cost calculation that incorporates time and key resource costs, and were analyzed using univariate and multivariate regression. Results: The analysis included 412 PPVs (270 standard and 142 complex based on CPT code). The operating room time was significantly increased in complex cases ( P &lt; .01). Univariate analysis found that complex PPV, cryopexy, staining agent use, retinectomy, simultaneous scleral buckling, perfluoro-N-octane (PFO) use, silicone oil tamponade, and perfluoropropane tamponade were associated with a statistically significant difference in costs ( P &lt; .01); use of laser retinopexy was not significantly associated ( P = .7190). Multivariate analysis found that standard PPV cost an average $5132.33 and significant incremental costs were found for complex PPV (+$1185.55; P &lt; .001), cryopexy (+$465.02; P = .032), staining (+$525.16; P = .04), PFO use (+$1089.54; P &lt; .0001), retinectomy (+$2031.17; P &lt; .0001), and simultaneous scleral buckling (+$916.34; P = .006). Conclusions: The intraoperative factors that increase operating room time and ultimately the incurred cost of complex PPV cases vs standard PPV were identified and economically defined. These findings can improve practice patterns by optimizing costs for effective surgical planning in the management of RD repair.