Forecast model for the evaluation of economic resources employed in the health care of patients with HIV infection

ClinicoEconomics and Outcomes Research, May 2012

Forecast model for the evaluation of economic resources employed in the health care of patients with HIV infection Paolo Sacchi1, Savino FA Patruno1, Raffaele Bruno1, Serena Maria Benedetta Cima1, Pietro Previtali2, Alessia Franchini2, Luca Nicolini3, Carla Rognoni4, Lucia Sacchi5, Riccardo Bellazzi4, Gaetano Filice11Divisione di Malattie Infettive e Tropicali - Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; 2Università degli Studi di Pavia – Facoltà di Economia, Pavia, Italy; 3Controllo di Gestione Fondazione IRCCS Policlinico San Matteo di Pavia, Pavia, Italy; 4Dipartimento di Informatica e Sistemistica, Universita' degli Studi di Pavia, Pavia, Italy; 5Department of Information Systems and Computing, Brunel University, London, UKBackground and aims: The total health care cost for human immunodeficiency virus (HIV) patients has constantly grown in recent years. To date, there is no information about how this trend will behave over the next few years. The aim of the present study is to define a pharmacoeconomic model for the forecast of the costs of a group of chronically treated patients followed over the period 2004–2009.Methods: A pharmacoeconomics model was built to describe the probability of transition among different health states and to modify the therapy over time. A Markov model was applied to evaluate the temporal evolution of the average cost. The health care resources exploited during hospitalization were analyzed by using an “activity-based costing” method.Results: The Markov model showed that the mean total cost, after an initial increase, tended to remain stable. A total of 20 clinical records were examined. The average daily cost for each patient was EUR 484.42, with a cost for admission of EUR 6781.88.Conclusion: The treatment of HIV infection in compliance with the guidelines is also effective from the payer perspective, as it allows a good health condition to be maintained and reduces the need and the costs of hospitalizations.Keywords: health care cost, HIV, Markov model, activity-based costing

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Forecast model for the evaluation of economic resources employed in the health care of patients with HIV infection

Clinico Economics and Outcomes Research Forecast model for the evaluation of economic resources employed in the health care of patients with HIV infection Savino FA Patruno 2 Raffaele Bruno 2 Serena Maria Benedetta Pietro Previtali 1 Alessia Franchini 1 Luca Nicolini 0 Carla Rognoni 4 Lucia Sacchi 3 Riccardo Bellazzi 4 Gaetano Filice 2 0 Controllo di Gestione Fondazione IRCCS Policlinico San Matteo di Pavia , Pavia , Italy 1 Università degli Studi di Pavia - Facoltà di Economia , Pavia , Italy 2 Divisione di Malattie Infettive e Tropicali - Fondazione IRCCS Policlinico San Matteo , Pavia , Italy 3 Department of Information Systems and Computing, Brunel University , London , UK 4 Dipartimento di Informatica e Sistemistica, Universita' degli Studi di Pavia , Pavia , Italy 8 1 0 2 - l u J - 2 1 n o 7 0 2 . 6 4 . 9 5 . 7 3 y b / m o c . s s e r p e v o d . ww l.y /w no / : tsp sue th la ldedao rpeoF PowerdbyTCPDF(ww.tcpdf.org) Background and aims: The total health care cost for human immunodeficiency virus (HIV) patients has constantly grown in recent years. To date, there is no information about how this trend will behave over the next few years. The aim of the present study is to define a pharmacoeconomic model for the forecast of the costs of a group of chronically treated patients followed Methods: A pharmacoeconomics model was built to describe the probability of transition among different health states and to modify the therapy over time. A Markov model was applied to evaluate the temporal evolution of the average cost. The health care resources exploited during hospitalization were analyzed by using an “activity-based costing” method. Results: The Markov model showed that the mean total cost, after an initial increase, tended to remain stable. A total of 20 clinical records were examined. The average daily cost for each patient was EUR 484.42, with a cost for admission of EUR 6781.88. Conclusion: The treatment of HIV infection in compliance with the guidelines is also effective from the payer perspective, as it allows a good health condition to be maintained and reduces the need and the costs of hospitalizations. health care cost; HIV; Markov model; activity-based costing - n w o d h c r a e s e R s e m o c t u O d n a s c i m o n o c E o c i n il C open access to scientific and medical research Introduction Out of the nearly 150,000 people who live with human immunodeficiency virus (HIV) infection in Italy, about 25,000 have full-blown disease. Although the epidemiologic trend of HIV infection shows a significant decrease, a small but constant number of new cases is diagnosed every year.1 Since 1996, highly active antiretroviral therapy (HAART) has changed the clinical course of HIV infection, reducing the rate of disease progression, incidence of opportunistic infections, and mortality. This prolonged survival has turned HIV infection into a chronic disease. This change has caused a constant shift of the economic resources needed to treat HIV infection from the hospital to outpatient management. The economic impact of HIV infection is well acknowledged, and it mainly includes the use of health care services for the treatment of HIV infection, the treatment of acquired immunodeficiency syndrome (AIDS)-associated symptoms and opportunistic infections, and the indirect costs associated with morbidity and premature death of working-age patients.2,3 In Italy, inpatient and outpatient specialist services are funded according to a prospective per case payment system based on a regional fee plan. The reimbursement provided for outpatient activities is based on national price lists. Each region can Clinico Economics and Outcomes Research 2012:4 117–126 choose whether to adopt the national rate of reimbursement or determine its own rate, as in the case of the Lombardy Regional Healthcare System (RHS). This is calculated taking into account the production costs (time and resources) and the strategic priorities of the Regional Social Services and 0281 HeaTlthheCamaroeuPnltatno, bwehpiacihdabryetuhpedRaHteSdfyoerahrolys.p4ital admissions l--Ju is determined using the diagnosis-related group (DRG) 21n system (International Classification of Diseases, Ninth o7 Revision, Clinical Modification), introduced in Italy in 1995. .620 A specific weight, which takes into account the composition ..945 of the procedures delivered by the providers, is assigned to /y37b teoacchalrceugliaotne athned ruepgdiaotneadl edvieargynoyseiasr-.reSluactehdwgerioguhpt irsatueseodf .com reimbursement. rsse The Lombardy region is the most populated of the vpeo 20 Italian regions, with more than 15% of the whole Italian .dww l.y population, and has the highest prevalence of AIDS cases /w no in Italy, which has a strong impact on the regional health / : tsp sue care budget. thom lsaon From 200 1 to 2008 , there have been more than 3500 new fr r HIV cases diagnosed in Lombardy, with a high prevalence ldedao rpeoF (70%) within males. The majority of patients were diagnosed nw with an advanced phase of the disease.4 Recently, the health odh authorities of the Lombardy region organized a survey aimed rcae at the characterization of the epidemiological features of seR new HIV cases. A total of 472 new HIV subjects have been se identified showing a high prevalence of heterosexual exposure tcom as a risk factor. These epidemiological data confirm that udO facing HIV remains a priority for health care organizations san and that a specific strategy needs to be implemented.2 icm In Lombardy, HAART therapies can be delivered only cono inside the hospitals. The provider is refunded with the same iilcnoEC admruogu. nAtsthaelsRoHreSppoartieddatinthientmeronmateinotnoafl tshtuedpiuersc,hthaisseaomfeoaucnht is generally lower than the market value.4 Up to now, the Regional Healthcare Service has spent more than EUR 150,000,000 to provide HIV therapy, and this amount increases by about 10% every year. In Lombardy, the total number of treated patients increased by 32.1% between 2004 and 2009. The total expenditure for the management of these subjects increased from EUR 224,902,421 to EUR 255,946,864, mostly due to the cost of the drugs, which grew from EUR 107,185,600 to EUR 137,215,086 (data from the Regional Data Base: banca Dati assistito Regione Lombardia). Previous studies have investigated the determinants of costs, consistently finding a relationship between CD4 cell count and health care expenditures.5 submit your manuscript | www.dovepress.com Dovepress As a matter of fact, other clinical features such as HIV viral load and hepatitis C virus coinfection may be related to costs. Moreover, although it has been shown that the total health care cost for these patients has constantly grown, there is still no information about how this trend will behave in the upcoming years, in particular with regards to chronically treated patients, who are the majority in the treated population.4 Since the expenditure for the care of patients with HIV AIDS has a relevant impact on the total health budget in Italy, and its trend is currently unknown, the present study was designed to define a pharmacoeconomic model to forecast the costs of a group of chronically treated patients followed over the period 2004–2009 at the Division of Infectious and Tropical Diseases of the IRCCS Policlinico San Matteo Foundation. Because the estimate of the real cost of hospital admission is currently not evaluated, an “activity-based costing” model was used to provide a trusted measure of resources employed in this setting. The combination of these data will supply a better resource allocation to the policymaker. Methods A pharmacoeconomic model, and in particular a Markov model (MM),6 was implemented to forecast the total expenditure trend over the next 4 years. MMs are stochastic models, where the study of a system is based on the assessment of the state of the system at a specific time stamp and of the probability of transition to a new state in the future, such transition being dependent only on the values of the current state and not on the previous history of the system up to that point (Markov property). The six health care states of the MM were defined based on CD4 count and HIV viral load, as detailed in Table 1. Such a model takes into account the probability of: • transition among different health states over time; • modification of the therapy due to virological failure or side effects; and • use of new generation and expensive drugs. This model will enable the number of people who will be in a specific health status at a particular time to be determined. As the total health care costs increase with the progression of the disease, the probability for a patient to change his/her health status will influence the total cost of the patient group he/she belongs to, and consequently will be related to the definition of the total resources to be employed for the management of the patients. This model has been implemented using TreeAge Pro Suite software (TreeAge Software, Inc, Williamstown, MA). To build the model, an evaluation of the clinical records of the patients treated at the Division of Infectious and Tropical Diseases between 2004 and 2009 was carried out. For each patient, the following data were collected: • demographics, clinical events, antiretroviral therapy; • the total cost, calculated as a sum of: ○ antiretroviral drugs cost (number of boxes per month of treatment), ○ visits cost, ○ laboratory and instrumental examinations cost (according to the price list of RHS for Lombardy), ○ nonantiretroviral therapy cost (all the drugs prescribed to the patient and collected at any provider within the Lombardy region, such as hospitals and pharmacies), ○ hospital admissions cost (DRGs reimbursement). Costs were discounted at 2009, considering the Italian inflation rates related to the average consumer prices. Cost analyses were performed considering both the evolution of the total costs and of each cost category between 2004 and 2009. The clinical data were then analyzed to identify patient characteristics which may be related to the costs in each year. The cohort of HIV patients followed at the outpatients division of the Divisione di Malattie Infettive e Tropicali - Fondazione IRCCS Policlinico San Matteo, Pavia was analyzed separately. Activity-based cost of HIV-related DRGs The analysis of the resources exploited for the assistance of patients during hospitalization (eg, the actual amount of direct costs and the estimate of indirect costs) was carried out by a retrospective analysis of the clinical records of 20 cases. The “activity-based costing” method was used, which is an accounting method that analyzes the performance process by breaking it down into multiple activities and computing the final cost as the sum of the cost of each activity. The cost of health performances can be divided into all the components cooperating in the production process. The methodology used in this case was as follows: 1. Modeling of the process of care, taking into account the sequence of diagnosis, therapy, and assistance given to the hospitalized patient t s o c t c e r i d n I t s o c t c e r i D e r a c g n i s r u N Indirect cost General cost: Internal logistic Management of nonhealth material Sanitation Maintenance cost of equipment Administrative check in/out Daily hospitalization Patient cost Medical care Laundry Health material, drug, etc Meal Medical laboratory instrumental tests/procedures submit your manuscript | www.dovepress.com Dovepress 119 Total turnover cost Total cost Cost for day hospitalized 2. Identification of the matrix of performed activities, including the knowledge on the professional figures involved. The following activities were identified: • hospital admission (administrative, medical, and nursing) • hospital stay (medical and nursing activity during hospital stay, meal and laundry costs, diagnostic procedures – both laboratory and instrumental, healthand nonhealth-related equipment costs, external consultants) • hospital discharge (administrative, medical, and nursing) A scheme of the root used is shown in Figure 1. To quantify the cost of each activity, the following guidelines were used: 1. Medical and nursing assistance (whole staff cost per day of stay) 2. Direct cost of material and diagnostic procedures (cost/day or cost/activity – price list of RHS for Lombardy) 3. Indirect costs (calculated according to hospital cost driver, as summarized in Figure 2). Results Cost of antiretroviral therapy in the period 2004–2009 This analysis was carried out on the total cohort of patients followed at the authors’ department. During the monitored period, the total drug cost constantly increased both as a whole cost and as percentage trend. Figure 3 shows how the yearly incremental cost is about 17% for years 2005–2006, decreases to 5% for 2007–2008, and goes back to previous levels for 2008–2010. This trend is motivated by the increase in the number of treated patients (from 840 to 913 during the observation period) and by the use of more expensive drugs as suggested by the simultaneous growth of the average cost per patient (Figure 4). Analysis of a cohort of 200 patients Demographics A total of 200 subjects consecutively starting the follow-up period between 2004 and 2009 were considered for the analysis. Table 2 summarizes the demographic features of the analyzed population. All patients received antiretroviral treatment during their follow-up. Costs according to health state Table 3 shows the distribution of the patients according to their health status. At the beginning of the observation period, the percentage of patients in state 1 was 37%, while in 2009 it dropped to 9%. At the same time, the percentage of patients in state 6 rose from 8% in 2004 to 27% in 2009, with an increase of 5% every year. Table 4 reports the detailed costs related to the different considered categories, such as drugs, visits, and laboratory and instrumental tests. The total cost of each status and the average cost per patient are also reported. The transition of patients towards a better health status affects the overall cost distribution, while the average yearly cost per patient remains quite stable. The total cost of patients in health status along the period of observation (Figure 7), while the average total cost, after an initial increase, tends to show a stable behavior (Figure 8). This observation is confirmed also by a Monte Carlo simulation (Figure 9) showing that in a hypothetical cohort of 10,000 patients, the average cost per patient for the period 2004–2013 would range between EUR 72,000 and EUR 76,000, with a probability of more than 50% (Figure 10) (95% uncertainty limits, calculated by taking the 2.5th and 97.5th percentiles of the 10000 Monte Carlo simulations: [53568.17, 83865.63]). ldedao rpeoF n w o d h c r a e s e R s e m o c t u O d n a s c i m o n o c E o c iil n C 400000 350000 300000 Health state 1:Trend 2004–2009 2004 2005 2006 2007 2008 2009 Total cost Mean cost Total cost 122 Activity-based cost of HIV-related DRGs Twenty clinical records of patients admitted to hospital in the first 6 months of 2009 , among those of the group analyzed by MM, have been examined, each one referring to a single hospital stay. The computation of the costs for every admission showed that the indirect costs and those related to hospital staff total EUR 391.70. Figure 2 shows the strategy used to evaluate the costs. Into this amount, the cost of administrative and general activities that account for the 7.5% of the total direct cost were also considered. The direct cost for each patient is computed as the sum of the costs for drugs, laboratory tests, and procedures. The cost of the drugs was assessed by multiplying the number of dispensed units (pills or vials) for each day of stay by the length of stay. The mean length of stay was 14 days. The average daily cost for each patient was EUR 485.12 (EUR 391.70 indirect cost + EUR 93.42 direct cost), with an average cost per admission of EUR 6792.88 (Figures 10 and 11). Health state 6:Trend 2004–2009 500000 450000 400000 350000 )300000 ( o250000 r u200000 E150000 100000 50000 0 500000 450000 400000 )350000 (300000 ro250000 u E200000 150000 100000 50000 2004 2005 2006 2007 2008 2009 Health state 6:Trend 2004–2009 2004 2005 2006 2007 2008 2009 Total cost Mean cost Total cost 2009 Year 2005 2006 2007 2008 2010 2011 2012 2013 2014 Predicted average annual cost per patient Total predicted cost per patient distribution (Monte Carlo simulation on the period 2004−2013) 0.6 0.5 64000 68000 72000 76000 80000 84000 88000 Total predicted cost per patient 18.22 1.92 Discussion This retrospective study was designed to evaluate the temporal evolution of the resources used in HIV patient care. Since it is trivial that the increase in the number of treated patients should lead to an increase in the health care related costs, the authors herein tried to assess the costs of a cohort of chronically treated patients to forecast the amount of resources needed over the next few years to carry on their health assistance. This is particularly useful in a setting where the public RHS has to make a regular plan of the amount of future costs. It was found that the costs relating to the cohort of patients treated at the authors’ institution increased constantly over time. This is due to an increase in the number of treated patients and to the use of new and more expensive drugs. Focusing on a group of chronic patients treated for a long period of time, it was found that the costs remain substantially stable and will not show a significant growth in the future. Moreover, the patients are likely to show a transition toward a better health status. The advantages of the antiretroviral treatment are confirmed by the reduction of the hospitalization rate, shown by the decrease in the costs relating to the reimbursements for hospital admission. Also, it was also found that each day at the hospital costs about EUR 500. This amount exceeds the DRG reimbursement fee if the stay is longer than 13 days. Thus, hospitalization causes a resource use corresponding to that of a year of antiretroviral therapy. Clinico Economics and Outcomes Research 2012:4 ldedao rpeoF are very interesting, since they are related to an economic organization also constitute important areas of coverage. The manuscript management system is completely online and includes a very quick and fair peer-review system, which is all easy to use. Visit http://www.dovepress.com/testimonials.php to read real quotes from published authors. The present study has some limitations. First, it is a single-center study, and the results may be affected by local patient management and by the use of considered cost driver. Moreover, the number of patients is limited and cannot be considered representative of a wider sample. Finally, the different reimbursement systems within the National Health Service make the results of this study not directly comparable to those of other international studies. Our findings should however address some indication to the payer. First, the treatment of patients in a stable clinical condition doesn’t show a trend leading to a signif icant increase. Second, also treating patients in an early stage of the disease allows them to be maintained in a good condition, reducing the need of hospitalization. Third, the hospital stay requires the use of massive economic resources, which increase with the length of hospitalization and exceed the reimbursement fee. Finally, the tendency to an improvement of the patients’ condition opens the way to a reduction of the nontangible costs related to HIV disease, such as productivity loss and the worsening of quality of life. In conclusion, it can be stated that the treatment of HIV infection in compliance to the guidelines is effective also from ClinicoEconomics and Outcomes Research Publish your work in this journal Disclosure The authors report no conflicts of interest in this work. 1. Suligoi B , Boros S , Camoni L , Lepore D . Available at: www.iss.it/binary/ pres/cont/Rapporto_31_dicembre_ 2008 .pdf. 2. Casari S , Suligoi B , Camoni L . Caratteristiche comportamentali dei pazienti HIV+ di recente riscontro (Studio Nu . Di.H.) Simit 9° Congresso Nazionale; November 24-27 , 2010 ; Rome, Italy. 3. Sendi P , Palmer AJ , Gafni A , Battegay M. Highly active antiretroviral therapy: pharmacoeconomic issues in the management of HIV infection . Pharmacoeconomics . 2001 ; 19 ( 7 ): 709 - 713 . 4. Regione Lombardia [homepage on the Internet] . ALEE-AO - Atlante Lombardo Epidemiologico ed Economico dell'Attività Ospedaliera. Feb 2012 [cited February 11 , 2012 ]. Available from: http://www.aleeao.it/. Accessed February 11 , 2012 . 5. Moore RD . Cost effectiveness of combination HIV therapy: 3 years later . Pharmacoeconomics . 2000 ; 17 ( 4 ): 325 - 330 . 6. Simpson KN , Strassburger A , Jones WJ , Dietz B , Rajagopalan R . Comparison of Markov model and discrete-event simulation techniques for HIV . Pharmacoeconomics . 2009 ; 27 ( 2 ): 159 - 165 . 7. Schackman BR , Gebo KA , Walensky RP , et al. The lifetime cost of current human immunodeficiency virus care in the United States . Med Care . 2006 ; 44 : 990 - 997 . 8. Fleishman JA , Gebo KA , Reilly ED , et al. Hospital and outpatient health services utilization among HIV infected adults in care 2000-2002 . Med Care. 2005 ; 43 ( Suppl 9 ): 11140 - 11152 . 9. Rizzardini G , Restelli U , Bonfanti P. The cost of HIV disease in Northern Italy: the payer's perspective . J Acquir Immune Defic Syndr . 2011 ; 57 : 211 - 217 .


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Paolo Sacchi, Savino FA Patruno, Raffaele Bruno, Serena Maria Benedetta Cima, Pietro Previtali, Alessia Franchini, Luca Nicolini, Carla Rognoni, Lucia Sacchi, Riccardo Bellazzi, Gaetano Filice. Forecast model for the evaluation of economic resources employed in the health care of patients with HIV infection, ClinicoEconomics and Outcomes Research, 2012, 117-126, DOI: 10.2147/CEOR.S24845