Care Delivery Research Articles

Protecting Patients And Society In An Era Of Private Equity Provider Ownership: Challenges And Opportunities For Policy.

Private equity (PE) acquisitions in health care delivery nearly tripled from 2010 to 2020. Despite concerns around clinical and economic implications, policy responses have remained limited. We discuss the US policy landscape around PE ownership, using policies in the European Union for comparison. We present four domains in which policy can be strengthened. First, to improve oversight of acquisitions, policy makers should lower reporting thresholds, review sequential acquisitions that together affect market power, automate reviews with potential denials based on market concentration effects, consider new regulatory mechanisms such as attorney general veto, and increase funding for this work. Second, policy makers should increase the longer-run transparency of PE ownership, including the health care prices garnered by acquired entities. Third, policy makers should protect patients and providers by establishing minimum staffing ratios, spending floors for direct patient care, and limits on layoffs and the sale of real estate after acquisition (forms of "asset stripping"). Finally, policy makers should mitigate risky financial behavior by limiting the amount or proportion of debt used to finance PE acquisitions in health care.

Development and validation of a short clinical risk management implementation (Short CRiMI) questionnaire

Clinical Risk Management (CRM) is an important instrument to continuously improve safety of health care delivery. In Germany, hospitals are required by law to implement CRM and incidence reporting systems. Since 2010, nation-wide surveys have been conducted periodically to evaluate implementation of CRM in hospitals. The instrument used in these surveys is constantly being updated to reflect previous experiences, as well as to adapt to ongoing trends and developments in CRM practices. The survey instrument used in 2022 consisted of up to 200 items and took up to an hour to complete. In this study, we aimed to develop a short instrument to measure the level of CRM implementation in hospitals, evaluate its psychometric properties, and to offer benchmarking data for health care facilities of different sizes.We used data collected in 2022 as part of KHaSiMiR study, employing a cross-sectional self-reported online survey. The hospital administrations were invited to designate one CRM manager to participate in the study. Out of 1,411 general hospitals invited, 401 responses were collected (response rate of 28%). After removing the cases with excessive missings, we imputed remaining missing values using multiple imputation, and split the resulting sample (n=362) in two halves (i.e., exploratory and testing subsamples). A principal component analysis was applied on the first subsample. We validated the resulting model using confirmatory factor analysis in the testing subsample. We evaluated internal consistency, and tested external validity of the established instrument using correlation analysis with two single-item measures: subjective evaluation of CRM implementation compared to similar organizations and compared to own ideal level. The principal component analysis included 45 items from the full instrument. The analysis resulted in a three-factor model with 26 items. In the confirmatory factor analysis, the model demonstrated acceptable fit with the data according to the commonly used fit indices: Chi2/df=1.36, CFI=0.941, TLI=0.930, RMSEA=0.045 (90% CI=0.032–0.056), SRMR=0.049. Cronbach’s alpha of all three factors was good (>0.70). All three factors had statistically significant positive correlations with each other (0.359–0.497) and with the two single items (0.282–0.532). None of the correlations were high enough (>0.7) to indicate multicollinearity.The proposed short clinical risk management implementation (Short CRiMI) questionnaire is psychometrically valid and can be used to rapidly evaluate CRM implementation in hospitals. Further research can provide evidence of its external validity and association with quality and safety outcomes. Benchmarking data can be used to compare the results with the data from the most recent Germany-wide survey.

Development of a Collaborative Online International Learning (COIL) Activity.

Global mobility has made global health a priority within nursing curricula and health care organizations. A collaborative online learning activity could promote international perspectives of health care delivery. Including a collaborative online international learning activity in continuing education for practicing nurses is a viable strategy that is consistent with the internationalization at home movement. Use of a qualitative descriptive evaluation approach when teaching prelicen-sure nursing students and educating practicing nurses provides effective international collaboration, promotes a global mindset, and provides an exemplar for professional development specialists to teach practicing nurses. [J Contin Educ Nurs. 2024;55(5):220-223.].

Deep learning predicts postoperative opioids refills in a multi-institutional cohort of surgical patients

BackgroundTo combat the opioid epidemic, several strategies were implemented to limit the unnecessary prescription of opioids in the postoperative period. However, this leaves a subset of patients who genuinely require additional opioids with inadequate pain control. Deep learning models are powerful tools with great potential of optimizing health care delivery through a patient-centered focus. We sought to investigate whether deep learning models can be used to predict patients who would require additional opioid prescription refills in the postoperative period after elective surgery. MethodsThis is a retrospective study of patients who received elective surgical intervention at the Mayo Clinic. Adult English-speaking patients ≥18 years old, who underwent an elective surgical procedure between 2013 and 2019, were eligible for inclusion. Machine learning models, including deep learning, random forest, and eXtreme Gradient Boosting, were designed to predict patients who require opioid refills after discharge from hospital. ResultsA total of 9,731 patients with mean age of 62.1 years (51.4% female) were included in the study. Deep learning and random forest models predicted patients who required opioid refills with high accuracy, 0.79 ± 0.07 and 0.78 ± 0.08, respectively. Procedure performed, highest pain score recorded during hospitalization, and total oral morphine milligram equivalents prescribed at discharge were the top 3 predictors for requiring opioid refills after discharge. ConclusionDeep learning models can be used to predict patients who require postoperative opioid prescription refills with high accuracy. Other machine learning models, such as random forest, can perform equal to deep learning, increasing the applicability of machine learning for combating the opioid epidemic.

Service design for children and young people with common mental health problems: literature review, service mapping and collective case study.

The mental health of children/young people is a growing concern internationally. Numerous reports and reviews have consistently described United Kingdom children's mental health services as fragmented, variable, inaccessible and lacking an evidence base. Little is known about the effectiveness of, and implementation complexities associated with, service models for children/young people experiencing 'common' mental health problems like anxiety, depression, attention deficit hyperactivity disorder and self-harm. To develop a model for high-quality service design for children/young people experiencing common mental health problems by identifying available services, barriers and enablers to access, and the effectiveness, cost effectiveness and acceptability of such services. Evidence syntheses with primary research, using a sequential, mixed-methods design. Inter-related scoping and integrative reviews were conducted alongside a map of relevant services across England and Wales, followed by a collective case study of English and Welsh services. Global (systematic reviews); England and Wales (service map; case study). Literature reviews: relevant bibliographic databases and grey literature. Service map: online survey and offline desk research. Case study: 108 participants (41 children/young people, 26 parents, 41 staff) across nine case study sites. A single literature search informed both reviews. The service map was obtained from an online survey and internet searches. Case study sites were sampled from the service map; because of coronavirus disease 2019, case study data were collected remotely. 'Young co-researchers' assisted with case study data collection. The integrative review and case study data were synthesised using the 'weaving' approach of 'integration through narrative'. A service model typology was derived from the scoping review. The integrative review found effectiveness evidence for collaborative care, outreach approaches, brief intervention services and the 'availability, responsiveness and continuity' framework. There was cost-effectiveness evidence only for collaborative care. No service model appeared to be more acceptable than others. The service map identified 154 English and Welsh services. Three themes emerged from the case study data: 'pathways to support'; 'service engagement'; and 'learning and understanding'. The integrative review and case study data were synthesised into a coproduced model of high-quality service provision for children/young people experiencing common mental health problems. Defining 'service model' was a challenge. Some service initiatives were too new to have filtered through into the literature or service map. Coronavirus disease 2019 brought about a surge in remote/digital services which were under-represented in the literature. A dearth of relevant studies meant few cost-effectiveness conclusions could be drawn. There was no strong evidence to suggest any existing service model was better than another. Instead, we developed a coproduced, evidence-based model that incorporates the fundamental components necessary for high-quality children's mental health services and which has utility for policy, practice and research. Future work should focus on: the potential of our model to assist in designing, delivering and auditing children's mental health services; reasons for non-engagement in services; the cost effectiveness of different approaches in children's mental health; the advantages/disadvantages of digital/remote platforms in delivering services; understanding how and what the statutory sector might learn from the non-statutory sector regarding choice, personalisation and flexibility. This study is registered as PROSPERO CRD42018106219. This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/09/08) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 13. See the NIHR Funding and Awards website for further award information.

Exploring work-life integration in vascular surgery and surgery

ObjectiveThere is a growing emphasis on achieving work-life balance, defined as the balance between work and personal life. However, this concept is gradually shifting towards work-life integration (WLI), which is relevant in the health care sector, particularly surgery. We performed a literature review to evaluate factors that contribute to WLI in the field of surgery, with a particular focus on vascular surgery. MethodsA literature review of WLI in surgery, specifically vascular surgery, was performed from inception to February 2024. PubMed was searched for papers written in the English and French languages using the MeSH terms “work-life balance” or “work-life integration” in “vascular surgery” or “surgery.” Findings were categorized in a tiered framework focused on faculty or staff, trainees (including medical students, residents, or fellows), and people identifying as underrepresented in medicine (URIM). ResultsTwenty-four articles were identified as relevant for this review. Previous reports have identified a high prevalence of burnout and suicide among the vascular surgery workforce. Collegial support and institutional culture were identified as pivotal in enhancing WLI. Inefficiencies in health care delivery, administrative burdens, and a lack of autonomy were recognized as barriers for WLI. Factors specific to gender and parenthood lead to unequal challenges in achieving WLI. Medical trainees’ WLI perceptions influenced their specialty choices and risk of burnout. Also, URIM trainees encountered additional obstacles like discrimination and attrition, though some reports indicated a resilience advantage among minority physicians. ConclusionsThis review has highlighted differences in challenges related to WLI across faculty and staff, trainees, and individuals identifying as URIM and emphasizes the need for systemic and cultural reforms, flexible work arrangements, and greater support for underrepresented groups to foster a healthier work-life ecosystem in health care.

Primary palliative care in low- and middle-income countries: A systematic review and thematic synthesis of the evidence for models and outcomes.

Serious health-related suffering is predicted to double in low- and middle-income countries by 2060. Primary care offers the best opportunity to meet Universal Health Coverage in an equitable way. Primary palliative care growth should be evidence-based to ensure provision is feasible, acceptable and culturally congruent. To identify the current evidence related to primary palliative care and to describe how primary palliative is defined in this setting, dominant typologies of care and meaningful outcome measures in LMICs. A systematic review and thematic synthesis was conducted. We described the nature, extent and distribution of published literature on primary palliative care in low- and middle-income countries, use thematic synthesis to characterize typologies of primary palliative care and design a process model for care delivery in low- and middle-income countries. Medline, Psychinfo, Global Health, Embase and CINAHL. Thirty-five publications were included. Nearly half took place in Asia (n = 16, 45.7%). We identified five dominant typologies of primary palliative care, including delivery in primary care clinics by multidisciplinary healthcare teams and palliative care specialists, in people's homes by healthcare professionals and volunteers and in tertiary healthcare facilities by generalists. We designed a process model for how these models operate within larger health systems and identified barriers and facilitators to implementing primary palliative care in this context. Evidence supporting primary palliative care in low- and middle-income countries is limited, and much of the published literature comes from Asia and southern Africa. Health systems in low- and middle-income countries have unique strengths and needs that affect primary palliative care services that should guide how services evolve to meet future need.

Drivers of Variation in Opioid Prescribing after Common Surgical Procedures in a Large Multihospital Healthcare System.

Misuse of prescription opioids is a well-established contributor to the United States opioid epidemic. The primary objective of this study was to identify which level of care delivery (i.e. patient, prescriber, or hospital) produced the most unwarranted variation in opioid prescribing after common surgical procedures. Electronic health record (EHR) data from a large multihospital healthcare system was used in conjunction with random-effect models to examine variation in opioid prescribing practices following similar inpatient and outpatient surgical procedures between October 2019 and September 2021. Unwarranted variation was conceptualized as variation resulting from prescriber behavior unsupported by evidence. Covariates identified as drivers of warranted variation included characteristics known to influence pain levels or patient safety. All other model variables, including prescriber specialty and patient race, ethnicity, and insurance status were characterized as potential drivers of unwarranted variation. Among 25,188 procedures with an opioid prescription at hospital discharge, 53.5% exceeded guideline recommendations, corresponding to 13,228 patients receiving the equivalent of >140,000 excess 5mg oxycodone tablets following surgical procedures. Prescribing variation was primarily driven by prescriber-level factors, with approximately half of the total variation in morphine milligram equivalents (MMEs) prescribed observed at the prescriber level and not explained by any measured variables. Unwarranted covariates associated with higher prescribed opioid quantity included non-Hispanic black race, Medicare insurance, smoking history, later hospital discharge times, and prescription by a surgeon rather than a hospitalist or primary care provider. Given the large proportion of unexplained variation observed at the provider level, targeting prescribers through education and training may be an effective strategy for reducing postoperative opioid prescribing.

Linkage of routinely collected NHS data to evaluate liaison mental health services: challenges and lessons learned.

Liaison mental health services provide mental health care to patients in acute hospital settings. Evaluation of liaison services is challenging due to their heterogeneous organisation and delivery, high case throughput and varied patient case mix. We aimed to link routinely collected National Health Service data from secondary care settings, chosen for their service characteristics, to data from primary care to evaluate hospital-based liaison mental health services in England. We planned to compare patients referred to hospital-based liaison services with comparable patients in the same hospital not referred to liaison services and comparable patients in hospitals without any liaison services. We designed and enacted a methodology to link data from: (1) Hospital Episode Statistics, a database controlled by the National Health Service Digital and (2) ResearchOne, a primary care database controlled by The Phoenix Partnership. Obtaining approvals for the steps prespecified in the methodological protocol took 907 days. Enactment following approvals took 385 days. Data supplied from Hospital Episode Statistics contained 181,063 patients from 6 hospitals (mean=30,177, standard deviation=28,875.86) who matched the inclusion and exclusion criteria. Data supplied from ResearchOne contained 33,666 (18.6%) of these patients from the 6 hospitals (mean=5611, standard deviation=5206.59). Time required for approvals and enactment was attributable to slowness of data handling processes within each data holder and to resolution of technical and organisational queries between them. Variation in number of patients for which data was supplied between databases and between hospitals was attributable to coding inconsistencies and to the limited intersection of patient populations between databases and variation in recording practices between hospitals. Although it is technically feasible to link primary and secondary care data, the current system is challenging, complicated, unnecessarily bureaucratic, time consuming and costly. This limits the number of studies that could be conducted with these rich data sources. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number 13/58/08.

Stakeholder Perspectives of PATH (Plan for Appropriate Tailored Healthcare in Pregnancy) Telemedicine Recommendations [ID 2683565

INTRODUCTION: The COVID-19 pandemic has propelled innovation in prenatal care delivery including use of telemedicine for routine prenatal visits. The Plan for Appropriate Tailored Healthcare in Pregnancy (PATH), a consensus-based prenatal care recommendation developed by a multidisciplinary panel of prenatal care experts, includes two recommendations regarding telemedicine: 1) telemedicine should be an option for all visits aside from four key in-person contacts requiring in-person visits; and 2) home monitoring is an appropriate option for most routine parameters during pregnancy. A national listening tour was conducted to elicit stakeholder feedback for incorporating telemedicine recommendations into practice. METHODS: We conducted nine, 120-minute virtual focus groups with more than 25 organizations including professional (8), patient advocacy (8), public health (5), and payer groups (4). Focus groups were transcribed, coded by recommendation. Data were next analyzed with matrix coding across positive attitudes, negative attitudes, and implementation considerations. RESULTS: Focus groups included 110 participants. Most participants supported telemedicine use as a care modality for routine prenatal care. Positive attitudes included the belief that telemedicine increased care flexibility, care access, and patients' health agency. Negative attitudes included concerns that poor digital literacy, insufficient access to devices, and high cost could perpetuate existing health disparities. Implementation considerations included the importance of relationship building with patients, technical support staff use, home monitoring device validation, and patient education on telehealth best practices. Participants also emphasized needed improvements to telehealth infrastructure and funding. CONCLUSION: Interprofessional stakeholders broadly support telemedicine use in routine prenatal care. Improvements in existing advocacy efforts, research, and infrastructure in underserved communities are needed to facilitate increased access to telemedicine.

Opportunities to Improve Palliative Care Delivery in High-Grade Glioma

Opportunities to Improve Palliative Care Delivery in High-Grade Glioma

Improving routine use of clinical pathway decision support through integration of an EHR with a clinical library resource designed to provide evidence-based guidance within oncology workflows

BackgroundThe rapid evolution, complexity, and specialization of oncology treatment makes it challenging for physicians to provide care based on the latest and best evidence. We hypothesized that physicians would use evidence-based trusted care pathways if they were easy to use and integrated into clinical workflow at the point of care.MethodsWithin a large integrated care delivery system, we assembled clinical experts to define and update drug treatment pathways, encoded them as flowcharts in an online library integrated with the electronic medical record, communicated expectations that clinicians would use these pathways for every eligible patient, and combined data from multiple sources to understand usage over time.ResultsWe were able to achieve > 75% utilization of eligible protocols ordered through these pathways within two years, with > 90% of individual oncologists having consulted the pathway at least once, despite no requirements or external incentives associated with pathway usage. Feedback from users contributed to improvements and updates to the guidance.ConclusionsBy making our clinical decision support easily accessible and actionable, we find that we have made considerable progress toward our goal of having physicians consult the latest evidence in their treatment decisions.

Using Administrative Data to Better Treat Chronic Limb Threatening Ischemia

Chronic limb threatening ischemia (CLTI) is the most severe manifestation of peripheral arterial disease represents a particularly high-risk subgroup of patients. As such, efforts to better understand this complex patient population through well-designed clinical research studies are critical to improving CLTI care. Prospective randomized clinical trials (RCTs) remain the gold standard in clinical research, but these trials are resource-intensive and have highly selective patient populations, which limit their feasibility and generalizability. Alternatively, retrospective studies are less expensive than RCTs, have a larger sample size, and are more generalizable owing to a broader patient population. Health care administrative data provide rich sources of information that may be used for research purposes and are increasingly being used for the study of vascular surgery conditions, including CLTI. Although administrative data are collected for billing purposes, they may be leveraged to study a broad range of topics in vascular surgery including those related to health care delivery, epidemiology, health disparities, and outcomes. This review provides an overview of administrative data available for CLTI research, the strengths and limitations of these data sources, current areas of investigation, and future opportunities for further study with the goal of improving outcomes in this high-risk population.

A service-user digital intervention to collect real-time safety information on acute, adult mental health wards: the WardSonar mixed-methods study.

Acute inpatient mental health services report high levels of safety incidents. The application of patient safety theory has been sparse, particularly concerning interventions that proactively seek patient perspectives. Develop and evaluate a theoretically based, digital monitoring tool to collect real-time information from patients on acute adult mental health wards about their perceptions of ward safety. Theory-informed mixed-methods study. A prototype digital monitoring tool was developed from a co-design approach, implemented in hospital settings, and subjected to qualitative and quantitative evaluation. Phase 1: scoping review of the literature on patient involvement in safety interventions in acute mental health care; evidence scan of digital technology in mental health contexts; qualitative interviews with mental health patients and staff about perspectives on ward safety. This, alongside stakeholder engagement with advisory groups, service users and health professionals, informed the development processes. Most data collection was virtual. Phase 1 resulted in the technical development of a theoretically based digital monitoring tool that collected patient feedback for proactive safety monitoring. Phase 2: implementation of the tool in six adult acute mental health wards across two UK NHS trusts; evaluation via focused ethnography and qualitative interviews. Statistical analysis of WardSonar data and routine ward data involving construction of an hour-by-hour data set per ward, permitting detailed analysis of the use of the WardSonar tool. A total of 8 patients and 13 mental health professionals participated in Phase 1 interviews; 33 staff and 34 patients participated in Phase 2 interviews. Patients could use a web application (the WardSonar tool) to record real-time perceptions of ward safety. Staff could access aggregated, anonymous data to inform timely interventions. Coronavirus disease 2019 restrictions greatly impacted the study. Stakeholder engagement permeated the project. Phase 1 delivered a theory-based, collaboratively designed digital tool for proactive patient safety monitoring. Phase 2 showed that the tool was user friendly and broadly acceptable to patients and staff. The aggregated safety data were infrequently used by staff. Feasibility depended on engaged staff and embedding use of the tool in ward routines. There is strong evidence that an incident leads to increased probability of further incidents within the next 4hours. This puts a measure on the extent to which social/behavioural contagion persists. There is weak evidence to suggest that an incident leads to a greater use of the WardSonar tool in the following hour, but none to suggest that ward atmosphere predicts future incidents. Therefore, how often patients use the tool seems to send a stronger signal about potential incidents than patients' real-time reports about ward atmosphere. Implementation was limited to two NHS trusts. Coronavirus disease 2019 impacted design processes including stakeholder engagement; implementation; and evaluation of the monitoring tool in routine clinical practice. Higher uptake could enhance validity of the results. WardSonar has the potential to provide a valuable route for patients to communicate safety concerns. The WardSonar monitoring tool has a strong patient perspective and uses proactive real-time safety monitoring rather than traditional retrospective data review. The WardSonar tool can be refined and tested further in a post Coronavirus disease 2019 context. This study is registered as ISRCTN14470430. This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR128070) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 14. See the NIHR Funding and Awards website for further award information.

An Electronic Health Record-Integrated Application for Standardizing Care and Monitoring Patients With Autosomal Dominant Polycystic Kidney Disease Enrolled in a Tolvaptan Clinic: Design and Implementation Study.

Tolvaptan is the only US Food and Drug Administration-approved drug to slow the progression of autosomal dominant polycystic kidney disease (ADPKD), but it requires strict clinical monitoring due to potential serious adverse events. We aimed to share our experience in developing and implementing an electronic health record (EHR)-based application to monitor patients with ADPKD who were initiated on tolvaptan. The application was developed in collaboration with clinical informatics professionals based on our clinical protocol with frequent laboratory test monitoring to detect early drug-related toxicity. The application streamlined the clinical workflow and enabled our nursing team to take appropriate actions in real time to prevent drug-related serious adverse events. We retrospectively analyzed the characteristics of the enrolled patients. As of September 2022, a total of 214 patients were enrolled in the tolvaptan program across all Mayo Clinic sites. Of these, 126 were enrolled in the Tolvaptan Monitoring Registry application and 88 in the Past Tolvaptan Patients application. The mean age at enrollment was 43.1 (SD 9.9) years. A total of 20 (9.3%) patients developed liver toxicity, but only 5 (2.3%) had to discontinue the drug. The 2 EHR-based applications allowed consolidation of all necessary patient information and real-time data management at the individual or population level. This approach facilitated efficient staff workflow, monitoring of drug-related adverse events, and timely prescription renewal. Our study highlights the feasibility of integrating digital applications into the EHR workflow to facilitate efficient and safe care delivery for patients enrolled in a tolvaptan program. This workflow needs further validation but could be extended to other health care systems managing chronic diseases requiring drug monitoring.

2024 Alzheimer's disease facts and figures.

This article describes the public health impact of Alzheimer's disease (AD), including prevalence and incidence, mortality and morbidity, use and costs of care and the ramifications of AD for family caregivers, the dementia workforce and society. The Special Report discusses the larger health care system for older adults with cognitive issues, focusing on the role of caregivers and non-physician health care professionals. An estimated 6.9 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060, barring the development of medical breakthroughs to prevent or cure AD. Official AD death certificates recorded 119,399 deaths from AD in 2021. In 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh-leading cause of death in the United States. Official counts for more recent years are still being compiled. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2021, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 140%. More than 11 million family members and other unpaid caregivers provided an estimated 18.4 billion hours of care to people with Alzheimer's or other dementias in 2023. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $346.6 billion in 2023. Its costs, however, extend to unpaid caregivers' increased risk for emotional distress and negative mental and physical health outcomes. Members of the paid health care and broader community-based workforce are involved in diagnosing, treating and caring for people with dementia. However, the United States faces growing shortages across different segments of the dementia care workforce due to a combination of factors, includingthe absolute increase in the number of people living with dementia. Therefore, targeted programs and care delivery models will be needed to attract, better train and effectively deploy health care and community-based workers to provide dementia care. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2024 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $360 billion. The Special Report investigates how caregivers of older adults with cognitive issues interact with the health care system and examines the role non-physician health care professionals play in facilitating clinical care and access to community-based services and supports. It includes surveys of caregivers and health care workers, focusing on their experiences, challenges, awareness and perceptions of dementia care navigation.

A Thematic Analysis: Disparities of Palliative Care Delivery to Native American and Rural Family Caregivers

A Thematic Analysis: Disparities of Palliative Care Delivery to Native American and Rural Family Caregivers

Digital Transformation in Healthcare Challenges and Prospects

The following are presented, by the global community, as the main fields of Digital Transformation (DT) in Healthcare: Telemedicine Telemedicine is the remote delivery of healthcare services through Information and Communication Technologies (ICTs). It could be particularly beneficial in a range of services such as medical consultation, diagnosis remote monitoring of patients’ status and educational purposes. Patients could con- nect with healthcare providers at a distance using video calls, messaging platforms, or other communication tools. Telemedicine enhances accessibility to healthcare by overcoming geographical barriers while at the same time provides a transformative approach to healthcare services. Big Data Big data represents vast and diverse health information sets collected from several sources like Electronic Health Records (EHRs), wearable devices and social media. Big data can extract valuable insights and patterns, assisting clinical decision-making, public health management, personalised medicine and disease forecasting. Internet of Things (IoT) The Internet of Things (IoT) in healthcare refers to the interconnected network of medical devices, sensors and sys- tems that collect and exchange health data through the Inter- net. These devices offer real-time exchange of various data monitoring like patient's vital signs, and remote patient’s care, which could eventually result in the improvement of operational efficiency within healthcare systems, and patients' monitoring and care delivery. Virtual Reality (VR) in Health Virtual Reality (VR) employs immersive computer-generated environments into realistic experiences to transform medical training and education, rehabilitation, surgical planning and pain management. Employing VR tools such as headsets, users engage with three-dimensional simulation scenarios for training and skill practice in a safe environment without risking personal and patient safety. In addition, VR offers opportunities to improve outcomes, provide safer experiences to patients, while promoting the evolution of healthcare systems and care delivery. Artificial Intelligence (AI) in Health AI in healthcare is an umbrella term for the applications of Machine Learning (ML) algorithms used in medical contexts. AI algorithms analyse medical data, aiding in diagnostics, drug discovery, personalised medicine, and patient management. Virtual (personal) Assistants in Health Virtual Health Assistants (VHAs) are tools designed to engage patients, provide personalised health information and assist in various aspects of health services administration. Using Natural language Processing (NLP) and ML algorithms, VHAs offer support to remote communication between patients and healthcare providers, understand patients’ inquiries and healthcare-related issues. Also, VHAs could facil- itate appointment scheduling, symptom assessment, medication management, and health coaching, resulting at the enhancement of accessibility in healthcare and the empower- ment of the patient. Blockchain in Health Blockchain is an emerging technology, which utilises decentralised systems to record and manage healthcare information and patient data. By linking data blocks, blockchain can enhance security, interoperability and traceability, and address significant challenges such as data breaches, interoperability issues, and inefficiencies in data sharing, thus providing a stan- dardised and secure platform for data exchange across health- care systems and stakeholders. Medical Wearables Wearables emerge positive outcomes on continuing monitoring, tracking and early detecting of health issues. Wearables are devices wore on the body or putted on clothing allowing constant monitoring of health data and behaviour. They enable individuals to engage a proactive approach to their health and well-being, by empowering them to take control of their health. In addition, wearables have the potential to enhance telemedicine and population health management, while reducing healthcare costs.

Shared Decision-Making at the Intersection of Disability, Culture, and Language Accessibility: An Educational Session for Medical Students.

People with disabilities and those with non-English language preferences have worse health outcomes than their counterparts due to barriers to communication and poor continuity of care. As members of both groups, people who are Deaf users of American Sign Language have compounded health disparities. Provider discomfort with these specific demographics is a contributing factor, often stemming from insufficient training in medical programs. To help address these health disparities, we created a session on disability, language, and communication for undergraduate medical students. This 2-hour session was developed as a part of a 2020 curriculum shift for a total of 404 second-year medical student participants. We utilized a retrospective postsession survey to analyze learning objective achievement through a comparison of medians using the Wilcoxon signed rank test (α = .05) for the first 2 years of course implementation. When assessing 158 students' self-perceived abilities to perform each of the learning objectives, students reported significantly higher confidence after the session compared to their retrospective presession confidence for all four learning objectives (ps < .001, respectively). Responses signifying learning objective achievement (scores of 4, probably yes, or 5, definitely yes), when averaged across the first 2 years of implementation, increased from 73% before the session to 98% after the session. Our evaluation suggests medical students could benefit from increased educational initiatives on disability culture and health disparities caused by barriers to communication, to strengthen cultural humility, the delivery of health care, and, ultimately, health equity.

Decision support framework for home health caregiver allocation using optimally tuned spectral clustering and genetic algorithm

Population aging is a global challenge, leading to increased demand for health care and social services for the elderly. Home Health Care (HHC) is a vital solution to serve this segment of the population. Given the increasing demand for HHC, it is essential to coordinate and regulate caregiver allocation efficiently. This is crucial for both budget-optimized planning and ensuring the delivery of high-quality care. This research addresses a fundamental question in home health agencies (HHAs): “How can caregiver allocation be optimized, especially when caregivers prefer flexibility in their visit sequences?”. While earlier studies proposed rigid visiting sequences, our study introduces a decision support framework that allocates caregivers through a hybrid method that considers the flexibility in visiting sequences and aims to reduce travel mileage, increase the number of visits per planning period, and maintain the continuity of care – a critical metric for patient satisfaction. Utilizing data from an HHA in Tennessee, United States, our approach led to an impressive reduction in average travel mileage (up to 42%, depending on discipline) without imposing restrictions on caregivers. Furthermore, the proposed framework is used for caregivers’ supply analysis to provide valuable insights into caregiver resource management.