Albert Wong

Standardizing the Inclusion of Indirect Medical Costs in Economic Evaluations

A shortcoming of many economic evaluations is that they do not include all medical costs in life-years gained (also termed indirect medical costs). One of the reasons for this is the practical difficulties in the estimation of these costs. While some methods have been proposed to estimate indirect medical costs in a standardized manner, these methods fail to take into account that not all costs in life-years gained can be estimated in such a way. Costs in lifeyears gained caused by diseases related to the intervention are difficult to estimate in a standardized manner and should always be explicitly modelled. However, costs of all other (unrelated) diseases in life-years gained can be estimated in such a way.We propose a conceptual model of how to estimate costs of unrelated diseases in life-years gained in a standardized manner. Furthermore, we describe how we estimated the parameters of this conceptual model using various data sources and studies conducted in the Netherlands. Results of the estimates are embedded in a software package called ‘Practical Application to Include future Disease costs’ (PAID 1.0). PAID 1.0 is available as a Microsoft® Excel tool (available as Supplemental Digital Content via a link in this article) and enables researchers to ‘switch off’ those disease categories that were already included in their own analysis and to estimate future healthcare costs of all other diseases for incorporation in their economic evaluations.We assumed that total healthcare expenditure can be explained by age, sex and time to death, while the relationship between costs and these three variables differs per disease. To estimate values for age- and sex-specific per capita health expenditure per disease and healthcare provider stratified by time to death we used Dutch cost-of-illness (COI) data for the year 2005 as a backbone. The COI data consisted of age- and sex-specific per capita health expenditure uniquely attributed to 107 disease categories and eight healthcare provider categories. Since the Dutch COI figures do not distinguish between costs of those who die at a certain age (decedents) and those who survive that age (survivors), we decomposed average per capita expenditure into parts that are attributable to decedents and survivors, respectively, using other data sources.

Predictors of Long-Term Care Utilization by Dutch Hospital Patients aged 65+

BackgroundLong-term care is often associated with high health care expenditures. In the Netherlands, an ageing population will likely increase the demand for long-term care within the near future. The development of risk profiles will not only be useful for projecting future demand, but also for providing clues that may prevent or delay long-term care utilization. Here, we report our identification of predictors of long-term care utilization in a cohort of hospital patients aged 65+ following their discharge from hospital discharge and who, prior to hospital admission, were living at home.MethodsThe data were obtained from three national databases in the Netherlands: the national hospital discharge register, the long-term care expenses register and the population register. Multinomial logistic regression was applied to determine which variables were the best predictors of long-term care utilization. The model included demographic characteristics and several medical diagnoses. The outcome variables were discharge to home with no formal care (reference category), discharge to home with home care, admission to a nursing home and admission to a home for the elderly.ResultsThe study cohort consisted of 262,439 hospitalized patients. A higher age, longer stay in the hospital and absence of a spouse were found to be associated with a higher risk of all three types of long-term care. Individuals with a child had a lower risk of requiring residential care. Cerebrovascular diseases [relative risk ratio (RRR) = 11.5] were the strongest disease predictor of nursing home admission, and fractures of the ankle or lower leg (RRR = 6.1) were strong determinants of admission to a home for the elderly. Lung cancer (RRR = 4.9) was the strongest determinant of discharge to the home with home care.ConclusionsThese results emphasize the impact of age, absence/presence of a spouse and disease on long-term care utilization. In an era of demographic and epidemiological changes, not only will hospital use change, but also the need for long-term care following hospital discharge. The results of this study can be used by policy-makers for planning health care utilization services and anticipating future health care needs.

Longitudinal administrative data can be used to examine multimorbidity, provided false discoveries are controlled for

OBJECTIVE This article presents methods for using administrative data to study multimorbidity in hospitalized individuals and indicates how the findings can be used to gain a deeper understanding of hospital multimorbidity. STUDY DESIGN AND SETTING A Dutch nationwide hospital register (n=4,521,856) was used to calculate age- and sex-standardized observed/expected ratios of disease-pairing prevalences with corresponding confidence intervals. RESULTS The strongest association was found for the combination between alcoholic liver and mental disorders due to alcohol abuse (observed/expected=39.2). Septicemia was found to cluster most frequently with other diseases. The consistency of the ratios over time depended on the number of observed cases. Furthermore, the ratios also depend on the length of the time frame considered. CONCLUSION Using observed/expected ratios calculated from the administrative data set, we were able to (1) better quantify known morbidity pairings while also revealing hitherto unnoticed associations, (2) find out which pairings cluster most strongly, and (3) gain insight into which diseases cluster frequently with other diseases. Caveats with this method are finding spurious associations on the basis of too few observed cases and the dependency of the ratio magnitude on the length of the time frame observed.

Persistent mental health disturbances during the 10 years after a disaster: Four-wave longitudinal comparative study

Although some studies have examined the long‐term effects of disasters, very little is known about severe persistent symptoms following disasters. The aim of the present study was to examine persistent mental health problems and to what extent disaster exposure predicts long‐term persistent disturbances.

The burden of Lyme borreliosis expressed in disability-adjusted life years

BACKGROUND Lyme borreliosis (LB) is the most commonly reported tick-borne infection in Europe and North America. In the last 15 years a 3-fold increase was observed in general practitioner consultations for LB in the Netherlands. To support prioritization of prevention and control efforts for LB, we estimated its burden expressed in Disability-Adjusted Life Years (DALYs). METHODS We used available incidence estimates for three LB outcomes: (i) erythema migrans (EM), (ii) disseminated LB and (iii) Lyme-related persisting symptoms. To generate DALYs, disability weights and duration per outcome were derived using a patient questionnaire including health-related quality of life as measured by the EQ-5D. RESULTS We estimated the total LB burden for the Netherlands in 2010 at 10.55 DALYs per 100,000 population (95% CI: 8.80-12.43); i.e. 0.60 DALYs for EM, 0.86 DALYs for disseminated LB and 9.09 DALYs for Lyme-related persisting symptoms. Per patient this was 0.005 DALYs for EM, 0.113 for disseminated LB and 1.661 DALYs for a patient with Lyme-related persisting symptoms. In a sensitivity analysis the total LB burden ranged from 7.58 to 16.93 DALYs per 100,000 population. CONCLUSIONS LB causes a substantial disease burden in the Netherlands. The vast majority of this burden is caused by patients with Lyme-related persisting symptoms. EM and disseminated Lyme have a more modest impact. Further research should focus on the mechanisms that trigger development of these persisting symptoms that patients and their physicians attribute to LB.

Medical innovation and age-specific trends in health care utilization : Findings and implications

Health care utilization is expected to rise in the coming decades. Not only will the aggregate need for health care grow by changing demographics, so too will per capita utilization. It has been suggested that trends in health care utilization may be age-specific. In this paper, age-specific trends in health care utilization are presented for different health care sectors in the Netherlands, for the period 1981-2009. For the hospital sector we also explore the link between these trends and the state of medical technology. Using aggregated data from a Dutch health survey and a nationwide hospital register, regression analysis was used to examine age-specific trends in the probability of utilizing health care. To determine the influence of medical technology, the growth in age-specific probabilities of hospital care was regressed on the number of medical patents while adjusting for confounders related to demographics, health status, supply and institutional factors. The findings suggest that for most health care sectors, the trend in the probability of health care utilization is highest for ages 65 and up. Larger advances in medical technology are found to be significantly associated with a higher growth of hospitalization probability, particularly for the higher ages. Age-specific trends will raise questions on the sustainability of intergenerational solidarity in health care, as solidarity will not only be strained by the ageing population, but also might find itself under additional pressure as the gap in health care utilization between elderly and non-elderly grows over time. For hospital care utilization, this process might well be accelerated by advances in medical technology.

Disaster exposure as a risk factor for mental health problems, eighteen months, four and ten years post-disaster--a longitudinal study.

BackgroundDisaster experiences have been associated with higher prevalence rates of (mental) health problems. The objective of this study was to examine the independent relation between a series of single disaster experiences versus the independent predictive value of a accumulation of disaster experiences, i.e. a sum score of experiences and symptoms of distress and post-traumatic stress disorder (PTSD).MethodsSurvivors of a fireworks disaster participated in a longitudinal study and completed a questionnaire three weeks (wave 1), eighteen months (wave 2) and four years post-disaster (wave 3). Ten years post-disaster (wave 4) the respondents consisted of native Dutch survivors only. Main outcome measures were general distress and symptoms of PTSD.ResultsDegree of disaster exposure (sum score) and some disaster-related experiences (such as house destroyed, injured, confusion) were related to distress at waves 2 and 3. This relation was mediated by distress at an earlier point in time. None of the individual disaster-related experiences was independently related to symptoms of distress. The association between the degree of disaster exposure and symptoms of PTSD at waves 2 and 3 was still statistically significant after controlling for symptoms of distress and PTSD at earlier point in time. The variable ‘house destroyed’ was the only factor that was independently related to symptoms of PTSD at wave 2. Ten years after the disaster, disaster exposure was mediated by symptoms of PTSD at waves 2 and 3. Disaster exposure was not independently related to symptoms of PTSD ten years post-disaster.ConclusionsUntil 4 years after the disaster, degree of exposure (a sum score) was a risk factor for PTSD symptoms while none of the individual disaster experiences could be identified as an independent risk factor. Ten years post-disaster, disaster exposure was no longer an independent risk factor for symptoms of PTSD. Since symptoms of PTSD and distress at earlier waves perpetuate the symptoms at later waves, health care workers should aim their resources at those who still have symptoms after one and a half year post-disaster, to prevent health problems at medium and long-term.

The cost of Lyme borreliosis

Background Lyme borreliosis (LB) is the most frequently reported tick-borne infection in Europe and North America. The aim of this study was to estimate the cost-of-illness of LB in the Netherlands. We used available incidence estimates from 2010 for tick bite consultations and three symptomatic LB outcomes: erythema migrans (EM), disseminated LB and Lyme-related persisting symptoms. The cost was estimated using these incidences and the average cost per patient as derived from a patient questionnaire. We estimated the cost from a societal perspective, including healthcare cost, patient cost and production loss, using the friction cost method and a 4% annual discount rate. Tick bites and LB in 2010 led to a societal cost of €19.3 million (95% CI 15.6-23.4; 16.6 million population) for the Netherlands. Healthcare cost and production loss each constituted 48% of the total cost (€9.3 and €9.2 million/year), and patient cost 4% (€0.8 million/year). Of the total cost, 37% was related to disseminated LB, followed by 27% for persisting symptoms, 22% for tick bites and 14% for EM. Per outcome, for an individual case the mean cost of disseminated LB and Lyme-related persisting symptoms was both around €5700; for EM and GP consultations for tick bites this was €122 and €53. As an alternative to the friction cost method, the human capital method resulted in a total cost of €23.5 million/year. LB leads to a substantial societal cost. Further research should therefore focus on additional preventive interventions.