Hospital-acquired infections in Belgian acute-care hospitals: financial burden of disease and potential cost savings.

INTRODUCTION: Hospital Acquired Infections (HAIs) are considered to be one of the most serious patient safety issues in healthcare today. It has been shown that HAIs contribute significantly not only to morbidity and mortality, but also to excessive costs for the health care system and for hospitalized patients. Since possibilities of prevention and control exist, hospital quality can be improved while simultaneously the cost of care is reduced. The objectives of this study were to examine the prevalence and the excess costs associated with HAIs. METHODS: A retrospective observational study was performed to estimate costs associated with hospital-acquired infections in Belgian hospitals, both in procedural admissions and in medical admissions. Hospital, diagnosis-related group, age and gender were used as matching factors to compare stays associated with HAIs and stays without HAIs. Data were obtained from the Minimum Basic Data Set 2008 used by Belgian hospitals to register case-mix data for each admission to obtain reimbursement from the authorities. Data included information from 45 hospitals representing 16,141 beds and 2,467,698 patient stays. Using the 2008 national feedback programme of the Belgian government, cost data were collected (prolonged length of stay, additional pharmaceuticals and procedures) and subsequently linked to the data set. By means of a sensitivity analysis we estimated potential monetary savings when a reduction in the incidence of HAIs in hospitals having a higher rate of hospital-acquired infections in comparison to other hospitals would be realized. RESULTS: In our sample 5.9% of the hospital stays were associated with a hospital-acquired infection. In the procedural admission subset this was the case for 4.7% of the hospital stays. The additional mean cost of the hospital-acquired infection was Euro 2,576 for all stays (P < 0.001) and Euro 3,776 for procedural stays (P < 0.001). The total burden of disease in Belgium is estimated at Euro 533,076,110 for all admissions and Euro 235,667,880 for the subset of procedural admissions. The excess length of stay varied between hospitals from 2.52 up to 8.06 days (Md 4.58, SD 1.01), representing an associated cost of Euro 355,060,174 (66.61% of the total cost). The cost of additional medical procedures and additional pharmaceutical products was estimated at Euro 62,864,544 (11.97%) and Euro 115,151,939 (21.60%) respectively. Overall, our results showed that considerable variability between hospitals regarding the incidence of HAIs (3.77-9.78%) for all hospital stays is present, indicating a potential for improvement. We provide a full overview of the potential monetary savings when reductions in HAIs are realized by applying different thresholds. For instance, if all Belgian hospitals having a higher rate of hospital-acquired infections improve their rate to the level of the hospital corresponding to percentile 75 (= 7.5% HAL) savings would be Euro 17,799,326. CONCLUSION: HALs are associated with important additional healthcare costs. Although not all hospital-acquired infections can be prevented, an opportunity to increase cost-effectiveness of hospital care delivery presents itself. This study is the first to estimate the annual economic burden of HALs for Belgium at a national level, incorporating all associated hospital costs. Apart from the fact that the cost of prolonged length of stay is of major importance, we have also shown that the cost of additional procedures and pharmaceutical products cannot be neglected when estimating the financial burden of HAIs.

Costs associated with readmissions in Belgian acute-care hospitals.

INTRODUCTION: Internationally, hospital readmissions have a great appeal as an indicator of hospital quality. Since possibilities in prevention and control exist, reducing rates of hospital readmission has attracted attention of policymakers as a way to improve quality of care while simultaneously reducing costs. Therefore reducing the number of readmissions is considered to be a pillar of more cost-effective hospital care. The goal of this study was to estimate the cost of hospital readmissions at a national level, describe differences in readmission rates between hospitals and to calculate the potential monetary savings of reducing excess readmissions. METHODS: Stays data were obtained from the Minimum Basic Data Set 2008 in a sample of 45 hospitals representing 16,141 beds. Readmissions were identified as a second admission for the same patient with the same APR-DRG code within 1 month or 3 months after discharge. Hospital type, diagnosis-related group, age and gender were used as matching factors in comparing readmission rates. Specific types of readmissions that occur naturally in each other's proximity due to the repeating nature of the therapy were excluded from the analysis. The costs per readmission were then calculated by linking the stays data with the cost data per APR-DRG and per severity index using the 2008 national feedback. The results of our sample were then extrapolated to all Belgian hospitals in order to calculate the total cost of readmissions. By means of a sensitivity analysis we estimated potential monetary savings when a reduction in the incidence of readmissions in hospitals having a higher readmission rate in comparison to other hospitals would be realized. RESULTS: In our sample 1.5% readmissions within 1 month after discharge and 2.1% within 3 months after discharge were identified. The additional weighted mean cost of these readmissions was Euro 3,495.58 within 1 month and Euro 3,572.20 within 3 months. The total financial burden, as extrapolated to the Belgian setting, is estimated at Euro 280,091,471.The wide variability between hospitals in incidence of readmissions (1.17-6.40%) indicates a potential for improvement. For instance, if all Belgian hospitals having a higher readmission rate improve their rate to the level of the hospital corresponding to percentile 75 (= 2.4% readmissions) savings would amount to Euro 14,118,509. CONCLUSION: The observed incidence of readmissions is associated with important additional healthcare costs. Although not all readmissions can be prevented, there is clearly a potential to increase cost-effectiveness of hosp tal care delivery.

Health economic consequences related to the diagnosis of fibromyalgia syndrome.

OBJECTIVE: To evaluate the use and costs of medical resources before and after a diagnosis of fibromyalgia syndrome (FMS) in a large primary care population in the UK. METHODS: We applied an existing data set for medical resource use among patients with a coded diagnosis of FMS. The observed quantities of 157 types of medical resource use before and after the diagnosis of FMS were multiplied by unit costs in order to calculate the cost of care (general practitioner [GP] visits, drugs, referrals, and diagnostics) within the National Health Service, excluding hospital costs. Costs before diagnosis were used in a trend analysis to predict later costs, assuming the diagnosis had never been made, and these predicted costs were compared with the observed costs after diagnosis. RESULTS: Following a diagnosis of FMS, a decrease in costs as compared with the predicted trend was observed. In the 4 years after diagnosis, the average difference between the predicted and observed cost was pound66.21 per 6 months per patient. This suggests that making the diagnosis leads to savings and a decrease in resource use. The main effect was observed for tests and imaging ( pound24.02 per 6 months), followed by pharmaceuticals ( pound22.27), referrals ( pound15.56), and GP visits ( pound4.36). CONCLUSION: Failure to diagnose a true case of FMS has its own costs, largely in excess GP visits, investigations, and prescriptions.

Gout in the UK and Germany: prevalence, comorbidities and management in general practice 2000-2005.

OBJECTIVE: To investigate and compare the prevalence, comorbidities and management of gout in practice in the UK and Germany. METHODS: A retrospective analysis of patients with gout, identified through the records of 2.5 million patients in UK general practices and 2.4 million patients attending GPs or internists in Germany, using the IMS Disease Analyzer. RESULTS: The prevalence of gout was 1.4% in the UK and Germany. Obesity was the most common comorbidity in the UK (27.7%), but in Germany the most common comorbidity was diabetes (25.9%). The prevalence of comorbidities tended to increase with serum uric acid (sUA) levels. There was a positive correlation between sUA level and the frequency of gout flares. Compared with those in whom sUA was <360 micromol/l (<6 mg/dl), odds ratios for a gout flare were 1.33 and 1.37 at sUA 360-420 micromol/l (6-7 mg/dl), and 2.15 and 2.48 at sUA >530 micromol/l ( >9 mg/dl) in the UK and Germany, respectively (p<0.01). CONCLUSIONS: The prevalence of gout in practice in the UK and Germany in the years 2000-5 was 1.4%, consistent with previous UK data for 1990-9. Chronic comorbidities were common among patients with gout and included conditions associated with an increased risk for cardiovascular disease, such as obesity, diabetes and hypertension. The importance of regular monitoring of sUA in order to tailor gout treatment was highlighted by data from this study showing that patients with sUA levels >or=360 micromol/l (>or=6 mg/dl) had an increased risk of gout flares.