Dutch healthcare reform: did it result in better patient experiences in hospitals? a comparison of the consumer quality index over time

<p>Abstract</p> <p>Background</p> <p>In 2006, the Dutch hospital market was reformed to create a more efficient delivery system through managed competition. To allow competition on quality, patient experiences were measured using the Consumer Quality index (CQI). We study whether public reporting and competition had an effect on the CQI between 2006 and 2009.</p> <p>Methods</p> <p>We analyzed 8,311 respondents covering 31 hospitals in 2006, 22,333 respondents covering 78 hospitals in 2007 and 24,246 respondents covering 94 hospitals in 2009. We describe CQI trends over the period 2006-2009. In addition we compare hospitals that varied in the level of competition they faced and hospitals that were forced to publish CQI results publicly and those that were not. We corrected for observable covariates between hospital respondents using a multi level linear regression. We used the Herfindahl Hirschman Index to indicate the level of competition.</p> <p>Results</p> <p>Between 2006 and 2009 hospitals showed a CQI improvement of 0.034 (p < 0.05) to 0.060 (p < 0.01) points on a scale between one and four. Hospitals that were forced to publish their scores showed a further improvement of 0.027 (p < 0.01) to 0.030 (p < 0.05). Furthermore, hospitals that faced more competition from geographically close competitors showed a more pronounced improvement of CQI-scores 0.004 to 0.05 than other hospitals (p < 0.001).</p> <p>Conclusion</p> <p>Our results show that patients reported improved experiences measured by the CQI between 2006 and 2009. CQI levels improve at a faster rate in areas with higher levels of competition. Hospitals confronted with forced public publication of their CQI responded by enhancing the experiences of their patients.</p

Outpatient costs in pharmaceutically treated diabetes patients with and without a diagnosis of depression in a Dutch primary care setting

<p>Abstract</p> <p>Background</p> <p>To assess differences in outpatient costs among pharmaceutically treated diabetes patients with and without a diagnosis of depression in a Dutch primary care setting.</p> <p>Methods</p> <p>A retrospective case control study over 3 years (2002-2004). Data on 7128 depressed patients and 23772 non-depressed matched controls were available from the electronic medical record system of 20 general practices organized in one large primary care organization in the Netherlands. A total of 393 depressed patients with diabetes and 494 non-depressed patients with diabetes were identified in these records. The data that were extracted from the medical record system concerned only outpatient costs, which included GP care, referrals, and medication.</p> <p>Results</p> <p>Mean total outpatient costs per year in depressed diabetes patients were €1039 (SD 743) in the period 2002-2004, which was more than two times as high as in non-depressed diabetes patients (€492, SD 434). After correction for age, sex, type of insurance, diabetes treatment, and comorbidity, the difference in total annual costs between depressed and non-depressed diabetes patients changed from €408 (uncorrected) to €463 (corrected) in multilevel analyses. Correction for comorbidity had the largest impact on the difference in costs between both groups.</p> <p>Conclusions</p> <p>Outpatient costs in depressed patients with diabetes are substantially higher than in non-depressed patients with diabetes even after adjusting for confounders. Future research should investigate whether effective treatment of depression among diabetes patients can reduce health care costs in the long term.</p

The cost-effectiveness of a new disease management model for frail elderly living in homes for the elderly, design of a cluster randomized controlled clinical trial

<p>Abstract</p> <p>Background</p> <p>The objective of this article is to describe the design of a study to evaluate the clinical and economic effects of a Disease Management model on functional health, quality of care and quality of life of persons living in homes for the elderly.</p> <p>Methods</p> <p>This study concerns a cluster randomized controlled clinical trial among five intervention homes and five usual care homes in the North-West of the Netherlands with a total of over 500 residents. All persons who are not terminally ill, are able to be interviewed and sign informed consent are included. For cognitively impaired persons family proxies will be approached to provide outcome information. The Disease Management Model consists of several elements: (1) Trained staff carries out a multidimensional assessment of the patients functional health and care needs with the interRAI Long Term Care Facilities instrument (LTCF). Computerization of the LTCF produces immediate identification of problem areas and thereby guides individualized care planning. (2) The assessment outcomes are discussed in a Multidisciplinary Meeting (MM) with the nurse, primary care physician, nursing home physician and Psychotherapist and if necessary other members of the care team. The MM presents individualized care plans to manage or treat modifiable disabilities and risk factors. (3) Consultation by an nursing home physician and psychotherapist is offered to the frailest residents at risk for nursing home admission (according to the interRAI LTCF). Outcome measures are Quality of Care indicators (LTCF based), Quality Adjusted Life Years (Euroqol), Functional health (SF12, COOP-WONCA), Disability (GARS), Patients care satisfaction (QUOTE), hospital and nursing home days and mortality, health care utilization and costs.</p> <p>Discussion</p> <p>This design is unique because no earlier studies were performed to evaluate the effects and costs of this Disease Management Model for disabled persons in homes for the elderly on functional health and quality of care.</p> <p>Trail registration number</p> <p>ISRCTN11076857</p

Economic evaluation alongside a single RCT of an integrative psychotherapeutic nursing home programme

__Abstract__ There is an 80% prevalence of two or more psychiatric symptoms in psychogeriatric patients. Multiple psychiatric symptoms (MPS) have many negative effects on quality of life of the patient as well as on caregiver burden and competence. Irrespective of the effectiveness of an intervention programme, it is important to take into account its economic aspects

An architecture for observational learning and decision making based on internal models

We present a cognitive architecture whose main constituents are allowed to grow through a situated experience in the world. Such an architectural growth is bootstrapped from a minimal initial knowledge and the architecture itself is built around the biologically-inspired notion of internal models. The key idea, supported by findings in cognitive neuroscience, is that the same internal models used in overt goal-directed action execution can be covertly re-enacted in simulation to provide a unifying explanation to a number of apparently unrelated individual and social phenomena, such as state estimation, action and intention understanding, imitation learning and mindreading. Thus, rather than reasoning over abstract symbols, we rely on the biologically plausible processes firmly grounded in the actual sensorimotor experience of the agent. The article describes how such internal models are learned in the first place, either through individual experience or by observing and imitating other skilled agents, and how they are used in action planning and execution. Furthermore, we explain how the architecture continuously adapts its internal agency and how increasingly complex cognitive phenomena, such as continuous learning, prediction and anticipation, result from an interplay of simpler principles. We describe an early evaluation of our approach in a classical AI problem-solving domain: the Sokoban puzzle

Autocatalytic endogenous reflective architecture

The document describes the architecture of the system being developed in the project. The principal contribution of this work is to the engineering of autonomous systems in a general fashion, i.e. independently of the target domain. This work is not “biologically inspired” and contributing to modeling natural intelligences is not an objective of the project. The main challenge set for the system is to adapt in dynamic open-ended environments with insufficient knowledge and limited resources. The system is to perform in real-time and extract knowledge from the domain it operates in. In particular, this means discovering meaningful states in the environment and learning skills by observing intentional agents in the domain. No system facing the complexity of the real world is able to learn effectively and efficiently from scratch. For each domain our system is plunged in, we hand craft a bootstrap code (called the Masterplan) that consists of the necessary initial and minimal knowledge to observe and act in the domain. The system is model-based and model-driven, meaning that its architecture is unified and consists essentially of dynamic hierarchies of models that capture knowledge in an executable form. The system is thus composed of executable models. From this perspective, learning translates into building models, integrating them into the existing hierarchies and revising them continuously. This perpetual rearranging of the internal agency of the system addresses the first objective of the HUMANOBS project: to design an auto-reconfigurable architecture. Learning is based on model building, which in turn is driven by goals and predictions, i.e. the evaluation by the system of the observed phenomenology of the domain. In other words, the system infers what it shall do (specification) and observes ways to reach these goals (implementation). In that regard, this addresses the second objective of the project: to build a system that can auto-generate specifications for skills and behaviors based on their observation. Learned specifications and implementations are highly context-dependent, which raises the challenge of identifying when to reuse (or refrain from reusing) learned models. Specifications and implementations are built hierarchically, which means that the system is able to reuse previously learned skills, however said skills are by design executable in parallel: this raises the challenge of coordinating (or sequentializing) the operation of the models that implement said skills. The architecture has been designed from the onset to solve these issues, and this addresses the last objective of the project: to build behavior generation and coordination mechanisms for the reproduction and reuse of observed skills. The architecture has been designed in a principled way (each part of the architecture is based on the same architectural template), and organizes the cooperation of four continuous processes: Model Acquisition, Model Revision, Compaction (or model compression) and Reaction (reactive behavior in the domain). It is the interplay of said processes that not only ensure the viability of the whole system but also improves its performance. For example, acquiring models only requires a few examples, performs in real-time and is fast, but this process requires another process that revises models also rapidly and in real-time, and this in turn is supported by the reactive behavior of the system that pays attention only to meaningful entities and phenomena – which it has learned previously, the whole cycle having been bootstrapped by the Masterplan. This is in sharp contrast with traditional Machine Learning approaches which ignore the other cognitive processes of a system and thus, left on their own, require enormous quantities of training examples and cannot perform in real-time. A functional prototype has been developed as a proof of concept of the architecture, and the preliminary results reported in this deliverable strongly indicate that the architecture is sound and that our approach towards the engineering of autonomous systems is tractable and promising. 5/80 This prototype has been expanded, generalized and optimized furthermore into the final state of the architecture (with respect to the time frame of the project). The implemented final system satisfies the requirements of the project (although the evaluation results are presented in a separate deliverable) and, in particular, is completely domain-independent. Future developments and related research avenues have been identified and will bring the architecture beyond the requirements of this project. In the main, these developments are aimed at addressing the issues of (a) adding curiosity and imagination to the system's capabilities and, (b) controlling the autonomous bottom-up growth by means of top-down allonomic constraints