Minder dan excellent is niet gepast

__Abstract__ De prestaties van ziekenhuizen, verpleeghuizen en zelfstandige behandelcentra zijn tegenwoordig vaak onderwerp van gesprek. Doorgaans is dat omdat de zorg die ze leveren als ongepast wordt beschouwd, bijvoorbeeld omdat deze onveilig is. Natuurlijk kan worden getracht met beleidsmaatregelen, oftewel op macroniveau, de organisaties, het mesoniveau, gepast te laten presteren. De factoren die van belang zijn voor de prestaties van organisaties zitten echter voor een belangrijk deel op het mesoniveau zelf. Organisaties kunnen zelf iedere dag beter worden in het leveren van zorg, en minder is niet gepast

The Roadside Healthcare Facility Location Problem

__Abstract__ Providing African truck drivers with adequate access to healthcare is an effective way to reduce the burden and the spread of HIV and other infectious diseases. Therefore, NGO North Star Alliance builds a network of healthcare facilities along major African trucking routes. Choosing the locations of new facilities presents novel and complex optimization problems. This paper considers a general design problem: the Roadside Health Care Facility location Problem (RHFLP). RFHLP entails to select locations for new facilities and to choose for each of these facilities whether or not to add healthcare services for HIV, STIs, Tuberculosis, and/or Malaria to the standard healt

The Roadside Healthcare Facility Location Problem: A Managerial Network Design Challenge

The population of truck drivers plays a key role in the spread of HIV and other infectious diseases in sub-Saharan Africa. Truck drivers thereby affect the health and lives of many, but also suffer from poor health and significantly reduced life expectancy themselves. Due to professional circumstances, their health service needs are generally not well addressed. Therefore, the non-governmental organization North Star Alliance builds a network of healthcare facilities along the largest trucking routes in subSaharan Africa. This paper studies the problem where to place additional facilities, and which health service packages to offer at each facility. The objective combines the maximization of the patient volume at these facilities and the maximization of the effectiveness of the health service delivery to the population served. The latter criterion is modeled through three novel access measures which capture the needs for effective service provisioning. The resulting optimization problem is essentially different from previously studied healthcare facility location problems because of the specific mobile nature of health service demand of truck drivers. Applying our model to the network of major transport corridors in South-East Africa, we investigate several prominent questions managers and decision makers face. We show that the present network expansion strategy, which primarily focuses on patient volumes, may need to be reconsidered: substantial gains in effectiveness can be made when allowing a small reduction in patient volumes. We furthermore show that solutions are rather robust to data impreciseness and that long term network planning can bring substantial benefits, particularly in greenfield situations

The effect of human resource management on performance in hospitals in Sub-Saharan Africa: A systematic literature review

Hospitals in Sub-Saharan Africa (SSA) face major workforce challenges while having to deal with extraordinary high burdens of disease. The effectiveness of human resource management (HRM) is therefore of particular interest for these SSA hospitals. While, in general, the relationship between HRM and hospital performance is extensively investigated, most of the underlying empirical evidence is from western countries and may have limited validity in SSA. Evidence on this relationship for SSA hospitals is scarce and scattered. We present a systematic review of empirical studies investigating the relationship between HRM and performance in SSA hospitals. Following the PRISMA protocol, searching in seven databases (i.e., Embase, MEDLINE, Web of Science, Cochrane, PubMed, CINAHL, Google Scholar) yielded 2252 hits and a total of 111 included studies that represent 19 out of 48 SSA countries. From a HRM perspective, most studies researched HRM bundles that combined practices from motivation-enhancing, skills-enhancing, and empowerment-enhancing domains. Motivation-enhancing practices were most frequently researched, followed by skills-enhancing practices and empowerment-enhancing practices. Few studies focused on single HRM practices (instead of bundles). Training and education were the most researched single practices, followed by task shifting. From a performance perspective, our review reveals that employee outcomes and organizational outcomes are frequently researched, whereas team outcomes and patient outcomes are significantly less researched. Most studies report HRM interventions to have positively impacted performance in one way or another. As researchers have studied a wide variety of (bundled) interventions and outcomes, our analysis does not allow to present a structured set of effective one-to-one relationships between specific HRM interventions and performance measures. Instead, we find that specific outcome improvements can be accomplished by different HRM interventions and conversely that similar HRM interventions are reported to affect different outcome measures. In view of the high burden of disease, our review identified remarkable little evidence on the relationship between HRM and patient outcomes. Moreover, the presented evidence often fails to provide contextual characteristics which are likely to induce variety in the performance effects of HRM interventions. Coordinated resea

Models, algorithms and performance analysis for adaptive operating room scheduling

The complex optimisation problems arising in the scheduling of operating rooms have received considerable attention in recent scientific literature because of their impact on costs, revenues and patient health. For an important part, the complexity stems from the stochastic nature of the problem. In practice, this stochastic nature often leads to schedule adaptations on the day of schedule execution. While operating room performance is thus importantly affected by such adaptations, decision-making on adaptations is hardly addressed in scientific literature. Building on previous literature on adaptive scheduling, we develop adaptive operating room scheduling models and problems, and analyse the performance of corresponding adaptive scheduling policies. As previously proposed (fully) adaptive scheduling models and policies are infeasible in operating room scheduling practice, we extend adaptive scheduling theory by introducing the novel concept of committing. Moreover, the core of the proposed adaptive policies with committing is formed by a new, exact, pseudo-polynomial algorithm to solve a general class of stochastic knapsack problems. Using these theoretica

Modeling Patient Journeys for Demand Segments in Chronic Care, With an Illustration to Type 2 Diabetes

Chronic care is an important area for cost-effective and efficient health service delivery. Matching demand and services for chronic care is not easy as patients may have different needs in different stages of the disease. More insight is needed into the complete patient journey to do justice to the services required in each stage of the disease, to the different experiences of patients in each part of the journey, and to outcomes in each stage. With patient journey we refer to the “journey” of the patient along the services received within a demand segment of chronic care. We developed a generic framework for describing patient journeys and provider networks, based on an extension of the well-known model of Donabedian, to relate demand, services, resources, behavior, and outcomes. We also developed a generic operational model for the detailed modeling of services and resources, allowing for insight into costs. The generic operational model can be tailored to the specific characteristics of patient groups. We applied this modeling approach to type 2 diabetes (T2D) patients. Diabetes care is a form of chronic care for patients suffering diabetes mellitus. We studied the performance of T2D networks, using a descriptive model template. To identify and describe demand we made use of the following demand segments within the diabetes type 2 population: patients targeted for prevention; patients with stage 1 diabetes treated by their GP with lifestyle advice; patients with diabetes stage 2 treated by their GP with lifestyle advice and oral medication; patients with stage 3 diabetes treated by their GP with lifestyle advice, oral medication, and insulin injections; patients with stage 4 diabetes with complications (treated by internal medicine specialists). We used a Markov model to describe the transitions between the different health states. The model enables the patient journey through the health care system for cohorts of newly diagnosed T2D patients to be described, and to make a projection of the resource requirements of the different demand segments over the years. We illustrate our approach with a case study on a T2D care network in The Netherlands and reflect on the role of demand segmentation to analyse the case study results, with the objective of improving the T2D service delivery

Toward Elimination of Infectious Diseases with Mobile Screening Teams

I n pursuit of Sustainable Development Goal 3 “Ensure healthy lives and promote well-being for all at all ages,” considerable global effort is directed toward elimination of infectious diseases in general and Neglected Tropical Diseases in particular. For various such diseases, the deployment of mobile screening teams forms an important instrument to reduce prevalence toward elimination targets. There is considerable variety in planning methods for the deployment of these mobile teams in practice, but little understanding of their effectiveness. Moreover, there appears to be little understanding of the relationship between the number of mobile teams and progress toward the goals. This research considers capacity planning and deployment of mobile screening teams for one such neglected tropical disease: Human African trypanosomiasis (HAT, or sleeping sickness). We prove that the deployment problem is strongly NP-Hard and propose three approaches to find (near) optimal screening plans. For the purpose of practical implementation in remote rural areas, we also develop four simple policies. The performance of these methods and their robustness is benchmarked for a HAT region in the Democratic Republic of Congo (DRC). Two of the four simple practical policies yield near optimal solutions, one of which also appears robust against parameter impreciseness. We also present a simple approximation of prevalence as a function of screening capacity, which appears rather accurate for the case study. While the results may serve to more effectively allocate funding and deploy mobile screening capacity, they also indicate that mobile screening may not suffice to achieve HAT eliminatio

Intention to use Medical Apps Among Older Adults in the Netherlands: Cross-Sectional Study

BACKGROUND: The increasing health service demand driven by the aging of the global population calls for the development of modes of health service delivery that are less human resource-intensive. Electronic health (eHealth) and medical apps are expected to play an important role in this development. Although evidence shows mobile medical apps might be effective in improving the care, self-management, self-efficacy, health-related behavior, and medication adherence of older adults, little is known about older adults' intention to use these technologies when needed, or the factors influencing this intention. OBJECTIVE: The objective of this study was to investigate the relationship of technology acceptance factors and intention to use mobile medical apps among community-dwelling older adults. METHODS: Data was collected using questionnaires. The factors selected from the literature have been validated using Cronbach α and tested for significance using logistic regressions. RESULTS: Almost half (49.7%) of the included older adults reported no intention to use medical apps. Adjusted logistic regression analysis per factor showed that the factors Attitude toward use (odds ratio [OR] 8.50), Perceived usefulness (OR 5.25), Perceived ease of use (OR 4.22), Service availability (OR 3.46), Sense of control (OR 3.40), Self-perceived effectiveness (OR 2.69), Facilities (OR 2.45), Personal innovativeness (OR 2.08), Social relationships (OR 1.79), Subjective norm (OR 1.48), and Feelings of anxiety (OR 0.62) significantly influenced the intention to use mobile medical apps among older adults, whereas the factor Finance (OR 0.98) did not. When considered together, a controlled multivariate logistic regression yielded high explained variances of 0.542 (Cox-Snell R2) and 0.728 (Nagelkerke R2). CONCLUSIONS: The high odds ratios and explained variance indicate that the factors associated with the intention to use medical apps are largely understood and the most important factors have been identified. To advance the evidence base, experimental controlled research should investigate the causality between the factors, intention to use, and actual use. For this purpose, our evidence suggests that policies designed to improve Attitude toward use appear most effective, followed by policies addressing Perceived usefulness, Perceived ease of use, Service availability, and Sense of control

Characteristics of patient portals developed in the context of health information exchanges: Early policy effects of incentives in the meaningful use program in the United States

__Background:__ In 2014, the Centers for Medicare & Medicaid Services in the United States launched the second stage of its Electronic Health Record (EHR) Incentive Program, providing financial incentives to providers to meaningfully use their electronic health records to engage patients online. Patient port

Productivity and quality of Dutch hospitals during system reform

This study addresses the productivity of Dutch hospitals since the start of the health systems reform in 2005. We consider DEA based measures, which include efficiency and quality for the complete set of Dutch hospitals and present cross-sectional and longitudinal analysis. In particular, we consider how hospital efficiency has developed. As the reform created an environment of regulated competition, we pay special attention to relative efficiency. Our results suggest that the differences in efficiency among hospitals have become larger. In the years 2009–2010, the number of hospitals identified as (close to) efficient by DEA analysis decreased