Case-studies of displacement effects in Dutch hospital care.

BACKGROUND: Under a constrained health care budget, cost-increasing technologies may displace funds from existing health services. However, it is unknown what services are displaced and how such displacement takes place in practice. The aim of our study was to investigate how the Dutch hospital sector has dealt with the introduction of cost-increasing health technologies, and to present evidence of the relative importance of three main options to deal with cost-increases in health care: increased spending, increased efficiency, or displacement of other services. METHODS: We conducted six case-studies and interviewed 84 professionals with various roles and responsibilities (practitioners, heads of clinical department, board of directors, insurers, and others) to investigate how they experienced decision making in response to the cost pressure of cost-increasing health technologies. Transcripts were analyzed thematically in Atlas.ti on the basis of an item list. RESULTS: Direct displacement of high-value care due to the introduction of new technologies was not observed; respondents primarily pointed to increased spending and efficiency measures to accommodate the introduction of the cost-increasing technologies. Respondents found it difficult to identify the opportunity costs; partly due to limited transparency in the internal allocation of funds within a hospital. Furthermore, respondents experienced the entry of new technologies and cost-containment as two parallel processes that are generally not causally linked: cost containment was experienced as a permanent issue to level costs and revenues, independent from entry of new technologies. Furthermore, the way of financing was found important in displacement in the Netherlands, especially as there is a separate budget for expensive drugs. This budget pressure was found to be reallocated horizontally across departments, whereas the budget pressure of other services is primarily reallocated vertically within departments or divisions. Respondents noted that hospitals have reacted to budget pressures primarily through a narrowing in the portfolio of their services, and a range of (other) efficiency measures. The board of directors is central in these processes, insurers are involved only to a limited extent. CONCLUSIONS: Our findings indicate that new technologies were generally accommodated by greater efficiency and increased spending, and that hospitals sought savings or efficiency measures in response to cumulative cost pressures rather than in response to single cost-increasing technologies.

Identifying and prioritizing lower value services from Dutch specialist guidelines and a comparison with the UK do-not-do list.

BACKGROUND: The term 'lower value services' concerns healthcare that is of little or no value to the patient and consequently should not be provided routinely, or not be provided at all. De-adoption of lower value care may occur through explicit recommendations in clinical guidelines. The present study aimed to generate a comprehensive list of lower value services for the Netherlands that assesses the type of care and associated medical conditions. The list was compared with the NICE do-not-do list (United Kingdom). Finally, the feasibility of prioritizing the list was studied to identify conditions where de-adoption is warranted. METHODS: Dutch clinical guidelines (published from 2010 to 2015) were searched for lower value services. The lower value services identified were categorized by type of care (diagnostics, treatment with and without medication), type of lower value service (not routinely provided or not provided at all), and ICD10 codes (international classification of diseases). The list was prioritized per ICD10 code, based on the number of lower value services per ICD10 code, prevalence, and burden of disease. RESULTS: A total of 1366 lower value services were found in the 193 Dutch guidelines included in our study. Of the lower value services, 30% covered diagnostics, 29% related to surgical and medical treatment without drugs primarily, and 39% related to drug treatment. The majority (77%) of all lower value services was on care that should not be offered at all, whereas the other 23% recommended on care that should not be offered routinely. ICD10 chapters that included most lower value services were neoplasms and diseases of the nervous system. Dutch guidelines appear to contain more lower value services than UK guidelines. The prioritization processes revealed several conditions, including back pain, chronic obstructive pulmonary disease, and ischemic heart diseases, where lower value services most likely occur and de-adoption is warranted. CONCLUSIONS: In this study, a comprehensive list of lower value services for Dutch hospital care was developed. A feasible method for prioritizing lower value services was established. Identifying and prioritizing lower value services is the first of several necessary steps in reducing them.

Is the role as gatekeeper still feasible? A survey among Dutch general practitioners.

INTRODUCTION: In the 2012 International Health Policy Survey by the Commonwealth Fund, 57% of Dutch GPs indicated that Dutch patients receive too much health care. This is an unexpected finding, given the clear gatekeeper role of Dutch GPs and recent efforts strengthening this role. OBJECTIVES: The study aims to explore where perceived overuse of care prevails and to identify factors associated with too much care at the entry point of Dutch health care. METHOD: An American survey exploring perceptions of the amount of care among primary care providers was modified for relevance to the Dutch health system. We further included additional factors possibly related to overuse based on 12 interviews with Dutch GPs. The survey was sent to a random sample of 600 GPs. RESULTS: Dutch GPs (N = 157; response rate 26.2%) indicated that patients receive (much) too much care in general hospitals, primary care, GP cooperatives as well as private clinics. The Dutch responding GPs showed a relatively demand-satisfying attitude, which contributed to the delivery of too much care, often leading to deviation from guidelines and professional norms. The increasing availability of diagnostic facilities was identified as an additional factor contributing to the provision of unnecessary care. Finally, funding gaps between primary care and hospitals impede cooperation and coordination, provoking unnecessary care. CONCLUSION: Our results--most notably regarding the demand-satisfying attitude of responding GPs--call into question the classical view of the guidance and gatekeeper role of GPs in the Dutch health care system.

Organisational targets of patient safety improvement programs in primary care; an international web-based survey.

BACKGROUND: Organisational problems contribute to many errors in healthcare delivery. Our objective was to identify the most important organisational items in primary care which could be targeted by programs to improve patient safety. METHODS: A web-based survey was undertaken in an international panel of 65 experts on patient safety from 20 countries. They were asked to rate 52 patient safety items on a five-point Likert scale which regards importance of each item for use for educational interventions to improve patient safety. RESULTS: The following 7 organizational items were regarded 'extremely important' by more than 50% of the experts: the use of sterile equipment with small surgical procedures (63%), the availability of adequate emergency drugs in stock (60%), regular cleaning of facilities (59%), the use of sterile surgical gloves when recommended (57%), the availability of at least one adequately trained staff member to deal with collapse and need for resuscitation (56%), adequate information handover when a patient is discharged from the hospital (56%) and periodically training of GPs in basic life support and other medical emergencies (53%). CONCLUSION: Seven organisational items were consistently prioritized; other items may be relevant in specific countries only. The logical next step is to develop and evaluate interventions targeted at these items.

Characteristics and health care utilization among patients with chronic heart failure: a longitudinal claim database analysis.

AIMS: This study aimed to determine the characteristics of patients with heart failure and high costs (top 1% and top 2-5% highest costs in perspective of the general population) and to explore the longitudinal health care utilization and persistency of high costs. METHODS AND RESULTS: Longitudinal observational study using claims data from 2006 to 2014 in the Netherlands. We identified all patients that received a hospital treatment for chronic heart failure between 1 January 2008 and 31 December 2010. Of each selected patient, all claims from the Dutch curative health system and with a starting date between 1 January 2006 and 31 December 2014 were extracted. Pharmaceutical and hospital claims were used to establish characteristics and indicators for health care utilization. Descriptive analyses and generalized estimating equation models were used to analyse characteristics, longitudinal health care utilization and to identify factors associated with high costs. Our findings revealed that the difference in costs between top 1%, top 2-5%, and bottom 95% patients with heart failure was mainly driven by hospital costs; and the top 1% group experienced a remarkable increase of mental health costs. Top 1% and top 2-5% patients with heart failure differed from lower cost patients in their higher rate of chronic conditions, excessive polypharmacy, hospital admissions, and heart-related surgeries. Heart-related surgeries contributed to the incidental high costs in 54% of top 1% patients, and the costs of the remaining top 1% patients were driven by mental health and pharmaceuticals use and rates of chronic conditions and multimorbidity. Top 1% patients were relatively young. Anaemia, dementia, diseases of arteries, veins and lymphatic vessels, influenza, and kidney failure were significantly associated with high costs. The end-of-life period was predictive of top 1% and top 5% costs. More than 90% of the population incurred at least one top 5% year during follow-up, and 31.8% incurred at least one top 1% year. Fifty-seven per cent incurred multiple top 5% years whereas only 8.6% incurred multiple top 1% years. Top 5% years were more frequently consecutive than top 1% years. CONCLUSIONS: Top 1% utilization occurs predominantly incidentally and among less than a third of patients with heart failure, whereas almost all patients with heart failure experience at least one top 5% year, and more than half experience two or more top 5% years. Both medical and psychiatric/psychosocial needs contribute to high costs in heart failure patients. Comprehensive and integrated efforts are needed to further improve quality of care and reduce unnecessary costs.

Systematic review of high-cost patients' characteristics and healthcare utilisation.

OBJECTIVES: To investigate the characteristics and healthcare utilisation of high-cost patients and to compare high-cost patients across payers and countries. DESIGN: Systematic review. DATA SOURCES: PubMed and Embase databases were searched until 30 October 2017. ELIGIBILITY CRITERIA AND OUTCOMES: Our final search was built on three themes: 'high-cost', 'patients', and 'cost' and 'cost analysis'. We included articles that reported characteristics and utilisation of the top-X% (eg, top-5% and top-10%) patients of costs of a given population. Analyses were limited to studies that covered a broad range of services, across the continuum of care. Andersen's behavioural model was used to categorise characteristics and determinants into predisposing, enabling and need characteristics. RESULTS: The studies pointed to a high prevalence of multiple (chronic) conditions to explain high-cost patients' utilisation. Besides, we found a high prevalence of mental illness across all studies and a prevalence higher than 30% in US Medicaid and total population studies. Furthermore, we found that high costs were associated with increasing age but that still more than halve of high-cost patients were younger than 65 years. High costs were associated with higher incomes in the USA but with lower incomes elsewhere. Preventable spending was estimated at maximally 10% of spending. The top-10%, top-5% and top-1% high-cost patients accounted for respectively 68%, 55% and 24% of costs within a given year. Spending persistency varied between 24% and 48%. Finally, we found that no more than 30% of high-cost patients are in their last year of life. CONCLUSIONS: High-cost patients make up the sickest and most complex populations, and their high utilisation is primarily explained by high levels of chronic and mental illness. High-cost patients are diverse populations and vary across payer types and countries. Tailored interventions are needed to meet the needs of high-cost patients and to avoid waste of scarce resources.

Characteristics and healthcare utilisation patterns of high-cost beneficiaries in the Netherlands: a cross-sectional claims database study.

OBJECTIVE: To determine medical needs, demographic characteristics and healthcare utilisation patterns of the top 1% and top 2%-5% high-cost beneficiaries in the Netherlands. DESIGN: Cross-sectional study using 1 year claims data. We broke down high-cost beneficiaries by demographics, the most cost-incurring condition per beneficiary and expensive treatment use. SETTING: Dutch curative health system, a health system with universal coverage. PARTICIPANTS: 4.5 million beneficiaries of one health insurer. MEASURES: Annual total costs through hospital, intensive care unit use, expensive drugs, other pharmaceuticals, mental care and others; demographics; most cost-incurring and secondary conditions; inpatient stay; number of morbidities; costs per ICD10-chapter (International Statistical Classification of Diseases, 10th revision); and expensive treatment use (including dialysis, transplant surgery, expensive drugs, intensive care unit and diagnosis-related groups >€30 000). RESULTS: The top 1% and top 2%-5% beneficiaries accounted for 23% and 26% of total expenditures, respectively. Among top 1% beneficiaries, hospital care represented 76% of spending, of which, respectively, 9.0% and 9.1% were spent on expensive drugs and ICU care. We found that 54% of top 1% beneficiaries were aged 65 years or younger and that average costs sharply decreased with higher age within the top 1% group. Expensive treatments contributed to high costs in one-third of top 1% beneficiaries and in less than 10% of top 2%-5% beneficiaries. The average number of conditions was 5.5 and 4.0 for top 1% and top 2%-5% beneficiaries, respectively. 53% of top 1% beneficiaries were treated for circulatory disorders but for only 22% of top 1% beneficiaries this was their most cost-incurring condition. CONCLUSIONS: Expensive treatments, most cost-incurring condition and age proved to be informative variables for studying this heterogeneous population. Expensive treatments play a substantial role in high-costs beneficiaries. Interventions need to be aimed at beneficiaries of all ages; a sole focus on the elderly would leave many high-cost beneficiaries unaddressed. Tailored interventions are needed to meet the needs of high-cost beneficiaries and to avoid waste of scarce resources.