Real-world Healthcare Systems Research Articles

MedNER: A Service-Oriented Framework for Chinese Medical Named-Entity Recognition with Real-World Application

Named-entity recognition (NER) is a crucial task in natural language processing, especially for extracting meaningful information from unstructured text data. In the healthcare domain, accurate NER can significantly enhance patient care by enabling efficient extraction and analysis of clinical information. This paper presents MedNER, a novel service-oriented framework designed specifically for medical NER in Chinese medical texts. MedNER leverages advanced deep learning techniques and domain-specific linguistic resources to achieve good performance in identifying diabetes-related entities such as symptoms, tests, and drugs. The framework integrates seamlessly with real-world healthcare systems, offering scalable and efficient solutions for processing large volumes of clinical data. This paper provides an in-depth discussion on the architecture and implementation of MedNER, featuring the concept of Deep Learning as a Service (DLaaS). A prototype has encapsulated BiLSTM-CRF and BERT-BiLSTM-CRF models into the core service, demonstrating its flexibility, usability, and effectiveness in addressing the unique challenges of Chinese medical text processing.

External Validation of the eRADAR Risk Score for Detecting Undiagnosed Dementia in Two Real-World Healthcare Systems.

Fifty percent of people living with dementia are undiagnosed. The electronic health record (EHR) Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) was developed to identify older adults at risk of having undiagnosed dementia using routinely collected clinical data. To externally validate eRADAR in two real-world healthcare systems, including examining performance over time and by race/ethnicity. Retrospective cohort study PARTICIPANTS: 129,315 members of Kaiser Permanente Washington (KPWA), an integrated health system providing insurance coverage and medical care, and 13,444 primary care patients at University of California San Francisco Health (UCSF), an academic medical system, aged 65 years or older without prior EHR documentation of dementia diagnosis or medication. Performance of eRADAR scores, calculated annually from EHR data (including vital signs, diagnoses, medications, and utilization in the prior 2 years), for predicting EHR documentation of incident dementia diagnosis within 12 months. A total of 7631 dementia diagnoses were observed at KPWA (11.1 per 1000 person-years) and 216 at UCSF (4.6 per 1000 person-years). The area under the curve was 0.84 (95% confidence interval: 0.84-0.85) at KPWA and 0.79 (0.76-0.82) at UCSF. Using the 90th percentile as the cut point for identifying high-risk patients, sensitivity was 54% (53-56%) at KPWA and 44% (38-51%) at UCSF. Performance was similar over time, including across the transition from International Classification of Diseases, version 9 (ICD-9) to ICD-10 codes, and across racial/ethnic groups (though small samples limited precision in some groups). eRADAR showed strong external validity for detecting undiagnosed dementia in two health systems with different patient populations and differential availability of external healthcare data for risk calculations. In this study, eRADAR demonstrated generalizability from a research sample to real-world clinical populations, transportability across health systems, robustness to temporal changes in healthcare, and similar performance across larger racial/ethnic groups.

Life-cycle health technology assessment for precision oncology.

e18704 Background: Rapid advances in precision oncology challenge timely and sustainable reimbursement decisions. Life-cycle health technology assessment (LC-HTA) can enable conditional patient access to promising precision oncology innovations alongside evidence development. Our objective was to create a life-cycle evaluative framework, called PRecision oncology Evidence Development in Cancer Treatment (PREDiCT). Methods: Through an iterative, health system and stakeholder-informed approach, we designed our LC-HTA framework. Elements supporting data and evidence generation were subsequently implemented within British Columbia, Canada’s provincial cancer control system. Our development, refinement, and pilot implementation process included a structured literature review, multi-disciplinary international expert consultation, a formal gap assessment, and a series of pan-Canadian inter-disciplinary stakeholder workshops to refine framework elements. Results: We engaged n = 15 pan-Canadian and international stakeholders to co-develop the LC-HTA framework. Defining framework components include: (a) managed access that defines the time horizon and pricing conditions of real-world healthcare system trialing; (b) collection of core data elements required to enable economic evaluation of precision oncology using real world data; (c) externally leveraged real world data and evidence generation to determine comparative effectiveness, cost-effectiveness, and the value of conducting additional research; and (d) data interpretation updating decisions, including investment, continued evaluation, or disinvestment from managed access. Key to the success of early framework implementation is the expansion of infrastructure to enable routine collection and linkage of genomic sequencing and cancer treatment data, patient quality of life and clinical outcomes, as well as health resource use spanning the diagnostic, treatment, and follow up trajectory. Conclusions: Sustainable integration of precision oncology requires the design and implementation of learning healthcare systems (LHS) that integrate genomic data with other health information. LC-HTA moves beyond static estimates of clinical and cost-effectiveness to continuously generate evidence that reduces evidentiary uncertainty and supports life-cycle decisions. We are embarking on a PREDiCT pilot to implement the framework in real-time to demonstrate the ability of real-world data to support life cycle evaluation.

The Contribution of Pharmacogenetic Drug Interactions to 90-Day Hospital Readmissions: Preliminary Results from a Real-World Healthcare System.

Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines exist for many medications commonly prescribed prior to hospital discharge, yet there are limited data regarding the contribution of gene-x-drug interactions to hospital readmissions. The present study evaluated the relationship between prescription of CPIC medications prescribed within 30 days of hospital admission and 90-day hospital readmission from 2010 to 2020 in a study population (N = 10,104) who underwent sequencing with a 14-gene pharmacogenetic panel. The presence of at least one pharmacogenetic indicator for a medication prescribed within 30 days of hospital admission was considered a gene-x-drug interaction. Multivariable logistic regression analyzed the association between one or more gene-x-drug interactions with 90-day readmission. There were 2211/2354 (93.9%) admitted patients who were prescribed at least one CPIC medication. Univariate analyses indicated that the presence of at least one identified gene-x-drug interaction increased the risk of 90-day readmission by more than 40% (OR = 1.42, 95% confidence interval (CI) 1.09–1.84) (p = 0.01). A multivariable model adjusting for age, race, sex, employment status, body mass index, and medical conditions slightly attenuated the effect (OR = 1.32, 95% CI 1.02–1.73) (p = 0.04). Our results suggest that the presence of one or more CPIC gene-x-drug interactions increases the risk of 90-day hospital readmission, even after adjustment for demographic and clinical risk factors.

Prophylactic Treatment in People with Severe Hemophilia B in the US: An Analysis of Real-World Healthcare System Costs and Clinical Outcomes

Introduction The treatment paradigm for people with severe hemophilia B in the US typically involves prophylaxis with factor IX (FIX) replacement therapy, the primary aim of which is to provide sufficient FIX levels to reduce the frequency of bleeding events. The clinical benefits of FIX prophylaxis are well understood, however the cost of FIX products as well as costs associated with healthcare resource utilization present a significant burden to the healthcare system. Substantive costs may also accrue in patients who continue to bleed while on prophylaxis, due to the impact on both short and long-term joint-related outcomes. In the absence of existing data in the US, the 'Cost of Hemophilia Across the USA: a Socioeconomic Survey' (CHESS US) study was conducted to establish a population-based estimate of the real-world US healthcare system burden associated with severe hemophilia. Using data drawn from the CHESS US study, this analysis examines the real-world healthcare system costs and clinical outcomes of people with severe hemophilia B on FIX prophylaxis. Methods CHESS US, a retrospective, cross-sectional dataset of adults with severe hemophilia in the USA, gathered information on patient cost via a patient record form. Data on the following parameters are included in this analysis: FIX consumption, annualized bleeding rate (ABR), the presence of one or more chronically damaged joints ("problem joint"), as well as costs associated with annual (prophylactic) factor consumption and hospitalizations (i.e., number of admissions, number of day cases, total inpatient days, and total intensive care unit [ICU] days). All variables report retrospective data of the 12 months prior to enrolment in the study. Results are presented as mean (± standard deviation) or N (%). Results In total, 132 of 576 patients profiled in the CHESS US study had severe hemophilia B. Among them, 77 patients were on FIX prophylaxis, of whom 44 patients reported FIX dosing regimen and were included in the current analyses. Among them, 20 patients were treated with conventional FIX and 24 patients with extended half-life (EHL) FIX products. The cohort has a mean age of 27.64 (± 11.05) and mean weight (kg) of 75.71 (± 13.41). In the last 12 months, the mean number of international units (IU) prescribed for FIX prophylaxis across the full cohort was 257,216 IU (± 213,591), with an associated annual cost of $610,966 (± $495,869). Among patients treated with conventional FIX, mean prescribed FIX was 287,141 IU (± 264,906) at an annual cost of $397,491 (± $359,788), while patients treated with EHL FIX reported a mean prescribed FIX of 232,278 IU (± 160,914) at an annual cost of $788,861 (± $529,258). The cohort reported a mean ABR of 1.73 (± 1.39); 8 (18%) were reported to have a target joint meeting the International Society on Thrombosis and Haemostasis (ISTH) definition; and 11% were reported to have had at least one chronically damaged joint (i.e., problem joint). Healthcare resource utilization associated with bleed events were reported as follows: hospital admissions days [0.18 (± 0.62)]; inpatient days [0.34 (± 1.22)]; and ICU days [0.23 (± 0.86)]. The direct medical cost to the healthcare system was $2,885 (± $7,857; excluding FIX cost) and $614,886 (± $498,839; including FIX cost). Discussion Data from the CHESS US study showed substantial costs and resource utilization among patients with severe hemophilia B receiving FIX prophylaxis, of which the cost of FIX replacement therapy constituted most of the total cost to healthcare system. Although the ABR observed in the analysis population was low, bleed-related hospitalizations comprised a significant non-drug cost to the healthcare system. A proportion of patients also still experienced joint arthropathy. Such substantial clinical and economic burden highlights that unmet needs remain in patients with severe hemophilia B on FIX prophylaxis in the US. Disclosures Noone: HCD Economics: Employment. Pedra:HCD Economics: Employment. Asghar:HCD Economics: Employment. O'Hara:HCD Economics: Employment, Equity Ownership. Sawyer:uniQure Inc.: Employment. Li:uniQure Inc.: Employment.

An optimal sensor placement algorithm (O-SPA) for improving tracking precision of human activity in real-world healthcare systems

In this article, an Optimal Sensor Placement Algorithm (O-SPA) is designed for improving the precision of human activity. This placement algorithm is designed based on the fact of improving the Rate of Observation (RO) and sensing in the day-to-day activities of human. SPA for RO and sensing improves the analysis precision by accumulating and classifying useful sensor information. Useful sensor information is achieved by approximating the sensor data mitigating positioning errors. The analysis process differentiates useful and less preference information from the placed sensors to reduce complications in classification. This device positioning algorithm is more specific for the precision of data accumulation and manipulation by reducing sensing errors to improve the efficiency of healthcare systems The efficiency of healthcare systems with optimal sensor deployment is measured in terms of accuracy (98.9%), classification time (0.079s), replications (4.12), recall (96.29%), and error factor (0.000021). The efficiency results are the best compared to Hybrid sensing aided human activity recognition (HHAR), Multi-sensor fusion with ensemble pruning system (MSF-EP) and Activities of daily living Compressive sensing (ADL).

Gender Differences in the Prevalence of Fibromyalgia and in Concomitant Medical and Psychiatric Disorders: A National Veterans Health Administration Study.

Fibromyalgia is a poorly understood, chronically disabling pain syndrome. While research has focused on its clinical presentation and treatment, less is known about fibromyalgia's clinical epidemiology in real-world healthcare systems. Gender differences have been difficult to study because relatively few males are diagnosed with fibromyalgia. Veterans Health Administration (VHA) patients diagnosed with fibromyalgia nationwide in FY 2012 were compared to Veterans with other pain diagnoses on sociodemographic characteristics, medical and psychiatric diagnoses, health service use, and opioid and psychotropic prescription fills. Additional analyses compared characteristics of men and women diagnosed with fibromyalgia. Risk ratios and Cohen's d were used for bivariate comparisons, followed by logistic regression analyses to identify independent factors associated with a diagnosis of fibromyalgia in the VHA. Altogether, 77,087 of 2,216,621 Veterans with pain diagnoses (3.48%) were diagnosed with fibromyalgia. They were more likely to be female, younger than patients with other pain conditions, more likely to have multiple psychiatric comorbidities and other types of pain, and used more medical outpatient services. Women diagnosed with fibromyalgia were younger and more likely to have headaches, connective tissue diseases (CTD), and psychiatric comorbidities, while men had more comorbid medical conditions. In this large, predominantly older male sample of Veterans with pain diagnoses, those with fibromyalgia were far more likely to be women. Gender comparisons showed women with fibromyalgia were more likely to be diagnosed with psychiatric disorders and CTD, while males were more likely to be diagnosed with medical conditions. Fibromyalgia shows a striking, gender-dependent picture of multimorbidity, which should be considered in treatment.

PBRNs or RBPNs or Both?

In this issue, two reports by Kelly and colleagues describe the development of the Recovery-Oriented Care Collaborative, a practice-based research network (PBRN) focused on improving services for people with serious mental illness. In the Research & Services Partnerships column, these authors detail the stepwise process of developing infrastructure, clarifying priorities, and executing an initial researchproject. In a related letter to the editor, the authors report project findings regarding the impact of integrating mental health and general medical care. As Kelly and colleagues describe, developing an effective PBRN requires attention to both infrastructure and culture. They note that the necessary infrastructure to support research includes administrative processes to facilitate communication, as well as technical tools or processes to collect and organize data. But establishing that infrastructure requires a cultural foundation of transparency and trust. Although the interests of clinical practice and research are often closely aligned, they are rarely identical. Serving those varying interests usually requires some compromise and sacrifice, which can be purchased only with trust. As Kelly and colleagues describe, developing transparency and trust is an iterative process. Trust facilitates successful collaboration, which further strengthens trust. Repeated successfully, this process expands beyond individual relationships to change the cultures of both clinical and research organizations. This process of mutual engagement characterizes community-based participatory research or what Van de Ven has called “engaged scholarship.” This iterative process of collaboration enables another important cultural shift: the establishment of continuous measurement as a core function of effective health care. Although measurement-based care in mental health has lagged behind many areas of general medicine, use of standard depression outcome measures is being rapidly implemented in community practice. The spread of electronicmedical records systems allows those measurement data to be organized in support of both care for individual patients and populationbased research. As always, the most important barriers to this transformation are cultural rather than technical. Patients, providers, and health systems must have confidence that systematic measurement of care processes, care experience, and patient-centered outcomes will support improvement for all rather than punish those already disadvantaged. A culture of continuous measurement can then enable a culture of continuous inquiry. As Kelly and colleagues describe, a learning health care system depends on engaging patients, clinicians, and health system leaders in a collaborative process of identifying and answering research questions. Behavioral scientists understand the power of immediate reinforcement. If the objective is to reinforce the behavior of asking questions, then a learning health care system should aim to provide timely answers to questions that arise from practice. Disagreements about best practices are healthy. In a culture of continuous inquiry, however, a disagreement leads to the questions: “What informationwould we need to actually know the answer?How can we find that information in our practice?” It must be admitted, however, that a culture of continuous inquiry and rapid-cycle learningwould create challenges for traditional researchers and traditional journals such as this one. Our current practice of disseminating research findings through journal publicationmay serve the career interests of researchers and the business interests of publishers. But delayed reporting of answers until publication does not always serve the interests of patients, clinicians, and leaders of health care systems. Notably, legislation establishing the Patient-CenteredOutcomes Research Institute (PCORI) required that findings of PCORIfunded research be made public within 90 days. Significant changes to our research traditions may be in the works. We can certainly lament the limited reach of research into community practice and the resulting delay in dissemination of evidence-based practices. Butwe can point to some advances on the national scene. PCORI’s National Patient-Centered Clinical Research Network (PCORnet) is developing infrastructure to “liberate” data from large health care systems and engage patients and patient-led organizations in the research process. NIH’s Health Care Systems Research Collaboratory is supporting a series of large pragmatic clinical trials based in real-world health care systems. The NIMH-funded Mental Health Research Network supports an infrastructure for clinical trials andobservational research in 13 large health care systems across theUnited States. The ultimate goal is the seamless integration of research and practice. In such a learning health care system, collaboration between patients, clinicians, health system leaders, and researchers would not be a special event. A culture of continuous measurement and continuous inquiry would extend to every placewherepeople livingwithpsychiatric disorders receive care, including rural practices and those serving traditionally disadvantaged groups. If this goal were realized, an observer might ask, “Is this a practice-based research network or a researchbased practice network?” And the answer would be “Yes!”

Overview and Summary: Care Coordination: Benefits of Interprofessional Collaboration

Care transitions are recognized as a time of significant vulnerability for children and adults with multiple chronic illnesses and complex health and social needs. Moving between settings or between providers requires comprehensive preparation and education of patients and families and accurate and timely flow of essential information. Lack of effective coordination on both sides of the transition leaves patients at risk for serious adverse outcomes influencing quality of life and function and substantial cost.This OJIN topic captures several important steps in the evolution of knowledge and practice of transitional care and care coordination. Together, the articles included in this topic reflect where we have been and where we still need to go to assure that patients and their families have safe and effective transitional care experiences. The articles range from a summary of over two decades of research on the nurse-led Transitional Care Model (TCM) to recent pilot studies developing new models and tools to expand transitional care and care coordination interventions to new settings and populations.In Continuity of Care: The Transitional Care Model, Hirschman and members of the multiprofessional Transitional Care Model (TCM) team at the University of Pennsylvania detail the evidence supporting the impact of their nurse-led transitional care model on quality and cost outcomes for older adults with multiple chronic illnesses. The TCM has undergone rigorous testing over the past two decades and has consistently demonstrated reductions in hospitalizations and costs for Medicare beneficiaries at high risk for adverse outcomes. This well-recognized model has been implemented in hospitals and health systems including patientcentered medical homes across the United States. The nine core TCM interventions and tools developed to measure them are described in the paper. This latest summary of the body of TCM research and its translation into real-world health care systems is a testament to the importance of rigorous and continuous programs of research for defining and improving care coordination for vulnerable populations with complex care needs.DelBoccio and colleagues describe one hospital's experience in becoming a top performer in transitional care in Successes and Challenges in Patient Care Transition Programming. Spurred to improve transitional care by changes in the Affordable Care Act, Indiana University Health North Hospital launched new programs to enhance patient activation and health team performance in medication management and communication with post-acute providers. Their experience reinforces the importance of effective teamwork and continuous quality improvement in making meaningful improvements in the care transition experience and subsequent performance outcomes.Nurses across academic and clinical settings in Minnesota describe the implementation of two models of care coordination for children with medical complexity (CMC) in their article Pediatric Care Coordination: Lessons Learned and Future Priorities. Cady and colleagues designed the TeleFamilies Model and PRoSPer models of pediatric care coordination to overcome current challenges of integrating complex care for children in healthcare homes (HCH) and to address key components of their state's healthcare reform legislation. Examining the implementation of new care coordination models within the context of unfolding state healthcare reform is a critical aspect of this article. Both the TeleFamilies and PRoSPer models incorporate nurses as drivers of care coordination processes in concert with members of interprofessional teams. They involve different team members and the use of different technologies according to the needs of children and families in rural and urban HCHs. The results of initial model tests show improved family perceptions of their health care experience and provider communication. The authors suggest several opportunities for further evaluation of In their article Registered Nurse Care Coordination: Creating a Preferred Future for Older Adults with Muitimorbiditv. …

Abstract W P352: Integration of Acute Stroke Care Process Measures with Health Care Delivery System Characteristics Enhances the Understanding of Stroke Team Effectiveness

Introduction: Effective therapy of acute ischemic stroke (AIS) is time dependent, and outcomes are influenced by the organizational capacity of each healthcare delivery system to successfully implement stroke treatment protocols that include time targets. Objective: Analyses of both workflow process and individual stroke care team structure and function will identify critical system characteristics associated with the delivery of thrombolytic therapy according to treatment guidelines in a real-world health care system. Methods: We performed a mixed method analysis (integration of medical outcomes, workflow process analysis and team personnel structure/function mapping) in 11 acute stroke care sites within a single health care system. Individual facility characteristics, variation of treatment delivery, and acute stroke care critical paths were evaluated at each care site. Formal and informal stroke care teams were mapped using network analytic software. Results: Based on these data, a benchmark hospital was identified. This site had 422 admissions for ischemic stroke in 2012, with the following median transition times for thrombolysis candidates: door to radiology (13.4 minutes), turnaround time for reporting lab results (40 minutes), time from order to scan result (20 minutes), and time from order to infusion (22 minutes). Network analysis of the team members revealed a robust, integrated team with high scores for centrality and density. The structure of the network was strongest in the workflow areas with the best performance. Conclusion: Health care delivery systems can access basic data on stroke management and health outcomes; however, these data sources are incomplete with respect to the complex interactions of personnel and processes associated with effective acute stroke care. A mixed method model of real-world stroke care teams provides new insights into the key system-level solutions for the rapid delivery of thrombolytic therapy.

Spatial accessibility in suboptimally configured health care systems: A modified two-step floating catchment area (M2SFCA) metric

The floating catchment area (FCA) family of metrics employ principles from gravity-based models to incorporate supply, demand, and distance in their characterization of the spatial accessibility of health care resources. Unlike traditional gravity models, the FCA metrics provide an output in highly interpretable container-like units (e.g., physicians per person). This work explores two significant issues related to FCA metrics. First, the Three Step Floating Catchment Area is critically examined. Next, the research shows that all FCA metrics contain an underlying assumption that supply locations are optimally configured to meet the needs of the population within the system. Because truly optimal configurations are highly unlikely in real-world health care systems, a modified two-step floating catchment area (M2SFCA) metric is offered to address this issue. The M2SFCA is built upon previous FCA metrics, but allows for spatial accessibility to be discounted as a result of the suboptimal configuration of health care facilities within the system. The utility of the new metric is demonstrated through simulated data examples and a case study exploring acute care hospitals in Michigan.

Can CER be an effective tool for change in the development and assessment of new drugs and technologies?

Comparative effectiveness research (CER) has been proposed in the United States as a way to compare new drugs and technologies with established alternatives and determine not just whether a therapy works, but how well it works compared to other options. To define the current use of CER in the development of new drugs and technologies and explore what is needed for this research approach to reduce or stabilize health care costs in the United States. In 2010, the Patient-Centered Outcomes Research Institute (PCORI) was established by the Patient Protection and Affordable Care Act (PPACA) to coordinate federally funded CER and recommend research priorities. Hochman and McCormick's (2010) evaluation of 328 randomized trials, observational studies, and meta-analyses involving medications published between June 2008 and September 2009 in 6 key journals showed that most published research did not fulfill the criteria of CER (defined as comparison to active treatment) and that most study design is driven by FDA requirements rather than the need to develop evidence to facilitates election of the most effective therapy. Since PPACA provides alternative funding for CER, it could encourage funding more studies to help determine which treatment delivers the best value per unit of investment from clinical, humanistic, and economic perspectives. Manufacturers may avoid CER because it increases product development costs, but a drug proven more effective is more likely to be accepted by formulary committees, increasing the drug's market share, whereas payers may reject or limit use of a new drug that performs less effectively in comparative studies. CER may not directly reduce expenditures for drugs and medical technologies. The results may vary widely from case to case; however, despite often significantly higher prices for new drugs, it is important to look beyond product costs to the overall impact on health care costs, including medical cost offsets that may occur through improved health or decreased morbidity. To truly decrease cost and improve quality, cost-effectiveness will have to be integrated into CER with the objective of prioritizing efficient therapies in the real-world health care system. If the methods and output of CER improve, the resulting cost-effectiveness ratios will also be more useful to the payer. CER should ultimately, therefore, be a useful tool to help patients, providers, and decision makers provide the most effective and most cost-effective interventions.

“This Drug May Work, But Is It Worth the Cost?” Can Comparative Effectiveness Research Help Tame Rising Health Care Costs?

“This Drug May Work, But Is It Worth the Cost?” Can Comparative Effectiveness Research Help Tame Rising Health Care Costs?

Effectiveness and Cost of a Transitional Care Program for Heart Failure

Randomized controlled trials have demonstrated the efficacy of nurse-led transitional care programs to reduce readmission rates for patients with heart failure; the effectiveness of these programs in real-world health care systems is less well understood. We performed a prospective study with concurrent controls to test an advanced practice nurse-led transitional care program for patients with heart failure who were 65 years or older and were discharged from Baylor Medical Center Garland (BMCG) from August 24, 2009, through April 30, 2010. We compared the effect of the program on 30-day (from discharge) all-cause readmission rate, length of stay, and 60-day (from admission) direct cost for BMCG with that of other hospitals within the Baylor Health Care System. We also performed a budget impact analysis using costs and reimbursement experience from the intervention. The intervention significantly reduced adjusted 30-day readmission rates to BMCG by 48% during the postintervention period, which was better than the secular reductions seen at all other facilities in the system. The intervention had little effect on length of stay or total 60-day direct costs for BMCG. Under the current payment system, the intervention reduced the hospital financial contribution margin on average $227 for each Medicare patient with heart failure. Preliminary results suggest that transitional care programs reduce 30-day readmission rates for patients with heart failure. This underscores the potential of the intervention to be effective in a real-world setting, but payment reform may be required for the intervention to be financially sustainable by hospitals.

Social Work and Health Care Practice and Policy: A Psychosocial Research Agenda

It has been almost 15 years since social work researcher Rosalie Kane (1982) accurately predicted many of the changes occurring in health care today. Observing that social work had no monopoly on concern for the whole person and for the psychosocial well-being and quality of life of the individual, Kane also predicted that psychosocial research would influence health care decision making, that researchers from other professions and disciplines would conduct basic and applied psychosocial research, and that social workers would have to live with the results. Cautioning that research by others might fail to address problems and services of particular concern to social workers, Kane called on social work to empirically examine its practice by specifying the interventions and outcomes of social work services. In recent years, research on social and psychological factors and health has matured into a broad and increasingly respected science. Striking advances have been made in methodologies, and hybrid disciplines (for example, psychoneuroimmunology) have emerged that reflect critical linkages among biological, social, and psychological factors. Barriers to conducting large-scale controlled studies of psychosocial interventions are being surmounted. For example, the National Heart, Lung, and Blood Institute is currently conducting a four-year, multisite clinical trial of a psychosocial intervention among 3,000 post-heart attack patients. At the same time, policymakers' concerns about the cost, quality, and outcomes of health care have spawned the area of health services research, including effectiveness research and the RAND Medical Outcomes Study (Roper, Winkenwerder, Hackbarth, & Krakauer, 1988; Stewart et al., 1989; Wells, Burnam, & Camp., 1995). As a result, increasingly sophisticated services research methodologies and outcome measurement (Ware & Sherbourne, 1992) are being developed that can be applied to studies of the delivery of psychosocial services in real-world health care systems (Narrow, Regier, Rae, Manderscheid, & Locke, 1993; Regier et al., 1993; Sharfstein, Stoline, & Goldman, 1993; Taube, Mechanic, & Hohmann, 1989). Since Kane's (1982) call for increased social work research, social work contributions to the growing body of health-related psychosocial and services research have increased significantly. Indeed, social work researchers have produced two of the leading studies in mental health research (Hogarty et al., 1986; Test & Stein, 1980). Social workers are also increasing research on behavioral and supportive group interventions for patients with life-threatening physical illness (Evans & Connis, 1995; Subramanian, 1990; Toseland, Blanchard, & McCallion, 1995). However, the majority of studies have been conducted by researchers from other professions and disciplines. This article addresses the question, What are the implications of extant psychosocial health-related research for a future social work research agenda? In focusing on next steps for social work research, emphasis is given to gaps in the existing research on basic psychosocial research, psychosocial treatment and intervention research, and health services research (including managed care, outcome and quality of care, and intervention effectiveness research). The examples cited have been brought to the attention of the Institute for the Advancement of Social Work Research (IASWR) and are among the current priorities of national research funding organizations. The article concludes with recommended actions to increase social work's use of and contributions to the development of empirically based knowledge for health care practice and policy. Basic Psychosocial Research An extensive body of research documents the profound effects of behavioral and social factors on the etiology, course, and management of illness (Anderson & Armstead, 1995; Berkman, 1995; Kaplan, 1995; Kiecolt-Glaser & Glaser, 1995; Manuck, Marsland, Kaplan, & Williams, 1995; Scheier & Bridges, 1995). …