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 Table of Contents  
ORIGINAL ARTICLE
Year : 2017  |  Volume : 3  |  Issue : 1  |  Page : 25-35

Economic outcomes from telecardiology services


1 Center of Telemedicine and Telephrmacy, School of Pharmacy, University of Camerino, Camerino, Italy
2 Department of Cardiology, “U.Sestili” Hospital, INRCA-IRCCS, Ancona, Italy

Date of Web Publication19-Jun-2017

Correspondence Address:
Milica Kaladjurdjevic
School of Pharmacy, University of Camerino, Camerino
Italy
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/digm.digm_9_17

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  Abstract 

Background and Objectives: Owing to the scarcity of health-care financing and the pressure of aging with the associated increased incidence of chronic heart failure, new models of health-care delivery supported by technology solution require a social economic analysis. We aim to assess improvement of Kansas City Living with Cardiomyopathy Questionnaire (KCCQ) score with telehome monitoring in elderly patients affected with Chronic Heart Failure (CHF) and to estimate a probable cost saving for health-care provider and patient, by calculating a probability to reduce fatal events such as mortality and hospitalization associated with improved health status measured with the KCCQ questionnaire. Materials and Methods: An observational quasi-experimental trial was used. Eight patients affected with chronic heart failure aged 85-90 years of age who have been at least three times hospitalized within the last year were recruited for the study. These patients received an educational module to empower their self-management capacity and a medicine kit necessary for telehome monitoring. The KCCQ questionnaire was employed. The KCCQ questionnaire is an independent predictor of health-care resource utilization. The KCCQ score improvement is associated likely with rehospitalization and mortality reduction according to results from previous clinical trial, where KCCQ score has been demonstrated as a strong statistically independent predictor of mortality and rehospitalization after adjustment for other variables. Results: The KCCQ score improved for 15 points from baseline measurement, after 6 months of telehome monitoring. The improvement of KCCQ score of 15 points represents a reduction of probability of hospitalization and mortality for 18% and 16%, respectively. In addition, an individual's cost savings were calculated, using the individual's willingness to pay to avoid fatal event, individual's productivity gain by avoiding a travel to remote hospital facilities, and an improved probability of positive event with telehome monitoring. Conclusion: Analysis demonstrated a probability for an important economical saving with the use of telehome monitoring for the provider and patient. We can conclude that telehome monitoring represents an innovative service that provides clinical and economical value addition to the patient, health-care system, and society.

Keywords: Chronic heart failure, economic evaluation, elderly, statistical life year, telecardiology, telehome monitoring, willingness to pay


How to cite this article:
Kaladjurdjevic M, Antonicelli R. Economic outcomes from telecardiology services. Digit Med 2017;3:25-35

How to cite this URL:
Kaladjurdjevic M, Antonicelli R. Economic outcomes from telecardiology services. Digit Med [serial online] 2017 [cited 2021 Dec 8];3:25-35. Available from: http://www.digitmedicine.com/text.asp?2017/3/1/25/208452


  Introduction Top


Chronic heart failure represents a syndrome associated with heart's functional weakening, and its incidence increases with age; therefore, it is considered as a syndrome related to aging. Chronic heart failure is associated with patient immobility and physical impairment. According to the level of physical impairment, chronic heart failure syndrome is classified into four functional groups of the New York Heart Association (NYHA I, II, III, IV). On the grounds of functional and organic changes associated with aging, the elderly population are often inclined to hospitalization due to chronic heart failure exacerbation. Chronic heart failure NYHA Class III and IV represent a risk for frequent rehospitalization. Every hospitalization for chronic heart failure carries a risk of mortality. Chronic heart failure represents a major public health problem because of its high mortality and rehospitalization rate. The costs of this syndrome, both in financial and personal terms, are substantial, both for health-care provider and for patient. Direct medical costs of CHF were estimated to be between €3417 and €5576 per year for patients, the largest cost component is related to hospitalizations about 76% of total cost, the costs of rehabilitation and medication are estimated to represent a smaller portion of direct medical cost.[1] Very often, the cause of hospitalization is preventable, as for example, improvement of noncompliance to therapy by frequent patient monitoring. The remote monitoring of patient can prevent hospitalization, mortality, and save cost. In a randomized clinical trial of 230 patients affected with chronic heart failure, telemedicine group demonstrated reduction of rehospitalization for 13% and cost reduction of 35%.[2] Another randomized clinical trial demonstrated that telemedicine has effect on symptoms' frequency reduction and its stabilization, while the number of hospitalization was reduced after 60 days and was statistically significant.[3] Health-care spending for the elderly accounts for one-third of the total governmental health-care spending, therefore an economic evaluation of the different treatment and consultation modalities for chronic disease is necessary to maintain the future sustainability of health-care financing. Studies have demonstrated that telehome monitoring can improve a probability of reduced hospitalization and mortality and produce a cost saving for health-care provider. However, the studies which embody cost-effectiveness analysis of telemedicine only analyzed provider's cost savings and have neglected patient's cost savings.[4]

The health status is an indicator of future outcomes, as, for example, the lower health status indicates a probability of hospitalization or mortality, the health status can be measured with different questionnaires. The Kansas City Living with Cardiomyopathy Questionnaire (KCCQ) score represents a statistically significant outcome measure in patients with chronic heart failure that permits to evaluate the effect of intervention in observational studies, the KCCQ is a 23-item, self-administered instrument that quantifies physical function, symptoms (frequency, severity, and recent change), social function, self-efficacy and knowledge, and quality of life of patients affected with chronic heart failure. Scores range between 0 and 100 points, higher scores reflect better health status.[5] The KCCQ is a validated, noninvasive tool that predicts a future economical and clinical outcome in population affected with CHF.

The KCCQ score is a strong independent predictor of 1-year costs (P < 0.0002), patients with higher KCCQ score (49/80) incurred incremental 1-year cost of $1520 whereas patients with lower KCCQ score incurred cost equal to $4265 and $8999 with scores 25–49 and 0–25, respectively. The each 5-point higher baseline KCCQ score is associated with a 4% decrease in 1-year costs.[6]

The clinical prognostic value of the KCCQ was established in a prospective, international cohort of 1516 patients with heart failure (HF) after a recent acute myocardial infarction. In this study, an analysis of Kaplan–Meier method using the KCCQ-overall summary score (OS) at the 1-, 3-, or 6-month assessment repeatedly demonstrated an increased hazard associated with 1-year cardiovascular mortality and rehospitalization with progressively lower ranges of KCCQ-OS. This association remains even after adjustment for other well-established prognostic variables such as age, left ventricular ejection fraction, revascularization status, and presence of renal dysfunction.[7] Any interventions that yields to KCCQ score improvement may reduce a probability of negative clinical outcomes as mortality and rehospitalization and produce cost savings for health-care provider and patient.

The aim of economic evaluation is to select the best decision about the modality of treatment. Therefore, it is necessary to evaluate the benefits of telehome monitoring to establish whether telehome monitoring is cost benefit for elderly patients affected with HF or not.

Individuals are risk averse and would prefer to avoid fatal events such as rehospitalization, which produce individual's productivity loss and reduce economic wealth of an individual. The productivity loss is defined as reduced time spent on producing income that permits an individual to lead fulfilled professional and private life. Rehospitalization and exacerbation of chronic disease leads to increased household expenditures on health services and goods, while a productivity loss decreases individual's satisfaction, impoverishes household assets, and decreases the quality of life. An individual's willingness to pay (WTP) to avoid hospitalization varies among the studies and countries and are associated with individual's income and education.[8] Individuals are also willing to pay a treatment or intervention that would prolong their lives and prevent early mortality. The value of statistical life (VSL) represents an estimate of the willingness of an individual to trade off his/her wealth for a reduction in the probability of death.[9] The value of a life year (VLY) is estimated to be 100,000 dollars and diminishes with age, but the VLY saved depends on individual's quality of life, therefore it varies across different health statuses.[10] The research demonstrated an inverted U-shaped relationship for the valuation of VSL and age, with maximal peak at 40 years of age, estimation of VSL of an elder person varies across different studies, with unified agreement of its diminished value after 65 years of age.[11] VSL can be used to estimate quality-adjusted life-year (QALY), which reflects the quality of life in terms of morbidity. The morbidity is the quality of the remaining life-years estimated in a scale from 0 to 1 where 0 corresponds to death and 1 corresponds to a state with perfect health.[12],[13]

The early diagnosis of chronic heart failure symptoms' occurrence can be detected by the patient, and therefore a hospitalization can be avoided. To prevent hospitalization for chronic heart failure, it is necessary to educate the patient to recognize the early symptoms of exacerbation and how to manage it. The self-management represents an important tool for primary and secondary prevention and requires patient's education and his/her involvement in the process of care.[14] An effective management of chronic heart failure requires also a frequent and continuous monitoring. The telemedicine can permit higher level of accessibility to health-care service and provision to continuous and frequent monitoring. It was demonstrated that self-management programs that embrace educational modules and telemedicine can reduce health-care utilization and likely produce a monetary benefit for health-care provider and patient.[15],[16] Predicting subsequent costs of HF telemedicine's application helps to identify high-utilization patients who may benefit from targeted telemedicine and educational programs. To have efficient and accessible health-care service, it is necessary to prioritize health care toward patient's need and treatment that will produce the most health gain. With this aim, we evaluated telemedicine home monitoring and educational module's effect after 6 months on KCCQ score and successfully calculate the cost savings for the health-care provider and for the patient.


  Materials and Methods Top


Study population

The patients were recruited from the Cardiology Department of INRCA Hospital during their inpatient stay for chronic heart failure exacerbation.

Inclusion criteria

Patients who had at least three rehospitalization with the primary diagnosis of HF within last year, >80 years of age, II–III class NYHA, HF of different etiology (ischemic, valvular, hypertensive), presence of one or more of the following comorbidities: diabetes, renal insufficiency, hypertension, anemia, assisted by a caregiver (formal or informal) who have basic level of information technology use and who have internet access at home were included in this study.

Exclusion criteria

Patients with age <80 years, recent acute myocardial infarction, severe dementia, severe renal insufficiency (glomerular filtration rate <20), chronic dialysis, cancer with short life expectancy (<1 year), and absence of a caregiver (formal or informal) were excluded from the study.

All patients or their legal representative and caregiver signed an informed consent prior to the study enrollment. They received an educational module [Table 1] with four educational domains, prior to telemedicine monitoring.{Table 1}

Participants were in the age group of 85-90 years, with an average age of 86.7 years [Table 2]. The population over 75 years of age is selected as the target population, as the prevalence of CHF and rehospitalization rate is higher in this subpopulation, therefore this group is expected to benefit more from secondary prevention through telemedicine than younger group of population.{Table 2}

Study measures and intervention

Various clinical measures have been utilized for risk-stratifying HF patients, invasive and noninvasive methods have different degrees of prognostic value and they are often costly and require a specialized person to conduct them.[7] Studies have shown that a simple KCCQ questionnaire that evaluates health status of the patient affected with chronic heart failure can be a powerful predictor of hospitalization and mortality.[17]

Patients' health status was assessed at baseline visit and after 6 months, using the KCCQ questionnaire. The KCCQ questionnaire is a 23-item, self-administered questionnaire that quantifies multiple domains by which chronic heart failure can impact patients' lives, including their physical and social limitations, symptom frequency and severity, and quality of life.

An OS based on contributions from each domain quantifies the multiple domains of the KCCQ into a single summary score. The KCCQ values for all domains range from 0 to 100, with higher scores representing lower symptom burden and better quality of life. Scores are divided into ranges of 0–25, 26–50, 51–75, and 76–100, and correspond to severe, moderate, fair, and little to no disability, respectively.[18]

The intervention consisted of an educational module given to the patient and his/her caregiver before the study and telemedicine monitoring for 6 months of the study. Educational module comprises four thematic modules which are shown in [Table 1]. A structured brochure containing all major information regarding CHF and how to place electrocardiogram (ECG) leads and electronic stethoscope was given to every patient and caregiver. Telemedicine kit is given to the patient free of charge, which consisted of tablet and devices for measuring vital parameters. A telemedicine platform supporting multispecialty teleconsultations and telehome care was used. The software was developed to be used by people without medical skills such as patients and caregivers. The technical system platform has to be configured at the moment of deployment to the user. The user interface has been developed to take into account the simplicity of using the mandatory characteristics. The software allows storage and sending data in real time without data loss, also in the case of lack of connectivity. It integrates different types of medical devices tailored for the patient with chronic heart failure. Every kit contains medical device (blood pressure device, oxygen saturation device, weight control device, ECG – 12 leads, and electronic stethoscope) [Figure 1] and tablet with software. Every physician was allowed to access the data on a daily basis to control the list of patients enrolled in the trial. Using a secure protected system, all the study physicians could also consult transmitted data of each patient regarding vitals, as well as visualize all data over time graphically using a telemedicine platform [Figure 1]. The patient or caregiver, once a week, was required to perform vital sign measurements. All data measured with medical devices were transmitted to a software program installed on tablet using a Bluetooth connection. All data measured would be received by a central computer at the cardiology department, the cardiologist once a day will perform control and, if necessary, will contact patient. Telehome monitoring service consisted of remote monitoring, therapy optimization, early symptom detection, and consultation with cardiologist.{Figure 1}

The primary objective was to assess a change of KCCQ score after 6 months of telemonitoring and to estimate a change in probability of a fatal event such as hospitalizations and mortality associated with change in KCCQ score after 6 months. The second objective was to evaluate a possible patient cost savings by applying a WTP model to change probability for a fatal event after 6 months.

Measuring clinical outcomes and follow-up: Measuring outcomes

Social economic analysis represents a systemic approach to determine the optimum use of scarce resources. It involves comparison of two or more alternatives under given assumptions and constraints. It is measured in monetary terms of the private and social benefit of the intervention to the health-care provider and to the patient. To do that, we needed to establish a probability of hospitalization and mortality with usual care of population aged 85-90 years, who live in Marche region. Based on the study of Politi et al.,[19] our study population have an hospitalization rate of 40%. Different estimations have been published about 1 year mortality of population between 75 and 85 years, the results from the studied group of 66,547 patients who were admitted for the first time with HF diagnosis estimated a mortality of 44% for 1 year, the study population had an median age of 72 years for men and 78 for women, the other study estimated a mortality rate of 34% for women and 46% for men per 100,000 residents, for population aged 75–85 years.[20],[21] Every rehospitalization after the first hospitalization increases the probability of death. Our study population were older than 80 years of age; as age increases to 84 years, 1-year case fatality rate increases to 58.1%. The factors that influence the mortality rate are variation in heart pathophysiology, presence of more comorbidities, and medication noncompliance.[22] The cost of CHF per hospitalization event is reimbursed according to disease-related group (DRG), for CHF (congestive heart failure), it is represented by code 127. The cost for DRG 127 (defined as heart insufficiency and shock) is 3052 euros.[23] The report of the Italian Ministry of Health demonstrates minimum and maximum length of stay for CHF of 5 and 14 days and average length of stay of 9, with cost of every day hospital stay of 143 euros.[24]

Cost of average length of hospitalization of patient with CHF is estimated to 4339 euros. Cost of drugs and specialist ambulatory service has been retrieved from the SIMG (Italian Association of General Physician) document [25] and corresponds to next costs: laboratory, diagnostic procedure, therapy, cardiologist visits, and general practitioner visit. As the objective of the study was to estimate a probability of cost saving from reduced number of hospitalization and mortality, these costs are only presented in [Table 3], but were not used in analysis.{Table 3}

The patient cost generated during the physician visit with usual care is estimated to evaluate the benefit of telemedicine application versus usual care. INRCA Hospital is located in Marche region and treat population in the area of Ancona municipalities. It is estimated that patients need to travel at least 25 km to be visited by cardiologist located at INRCA Hospital. Hence, the estimated cost of travel (considering the current price of gasoline of 1.50 euros and amortization cost of 20%) was 1.2 euros for every 10 km. The total 2-way travel is estimated at an average of 50 km necessary to be traveled to be visited by cardiologist at INRCA Hospital (5 × 1.2 euros estimation of 6 euros for the travel). Every visit and travel to the hospital consumes time, which represents productivity loss. The productivity loss evaluates a person's productivity capacity that would be a benefit for the individual and for the rest of the society or an ability to engage in leisure time or to work, but is lost due to necessity to visit a medical doctor and is spent for that purpose. The productivity loss in studies reviewed is evaluated differently. The most common monetary estimation of productivity loss is as loss of wages. In literature, average wage is estimated differently.[26] In our study, the study population was retired population, and therefore the monetary value of productivity loss was not so easy to estimate. To evaluate loss of leisure time was a possibility. However, after published materials were reviewed, the monetary value of leisure time resulted in a wide range of estimation from 20 euros to 10,000 per hour (defined as individual's estimation) and was influenced by many factors. Hence, we used a part-time engagement in work force of retired population, as part-time worker, the wage per hour is estimated as 20 euros per hour.[27] The elderly people usually do not visit doctor alone, very often they are accompanied by family members or a caregiver. Therefore, the productivity loss for caregiver or family member was necessary to be estimated. The cost of per hour for caregiver is estimated to be 12 euros per hour.[27] The productivity loss of family member differs according to family member's wages, the average hourly labor cost is estimated at 25 euros in the European-28 state members.[28]

The usual time that a patient would spend for a cardiologist visit which includes, travel, physician examination, and waiting in physician waiting room is estimated to be 6 h. It represents a productivity or leisure time loss sustained by every physician visit [Table 4].{Table 4}

Every new intervention generates additional cost to standard procedures. The cost of telemedicine equipment given to every patient was of 2448 euros and it included the following: telemedicine kit cost of 2000 euros, cost of maintenance of 384 euros for a period of 6 months, and the cost of telemedicine training of 64 euros, given once, before the study. As well, it is necessary to mention that according to literature review about economic evaluation of telemedicine,[29] certain categories of costs, among which fixed cost represented with the depreciation cost and facility costs and variable cost, represented by training cost, maintenance and repairs, telecommunication cost (connection), administrative support and supplies were excluded from the analysis due to their expected modest size and the unavailability of reasonable estimates. An additional indicator of efficiency of health-care service provision is utility.

The primary and secondary care visits have an objective to prevent hospitalization, patient's health worsening, and maintain patients' quality of life. The utility of usual care is presented as 70%, the most common reason for lower interest of patients to visit a specialist in the moment of follow-up visit for an existing condition was the necessity to travel to the hospital. The patients would have seen a specialist only in 70% of cases, if telemedicine was not available and were willing to spend $25 and an hour of their time to see the specialist, but they were not willing to take a day off work and drive 300 miles round trip for the same care.[30] In case of telemedicine, these inconveniences of traveling were avoided. But, opinion of the physician about diagnostic capability of telemedicine versus usual care was needed to be taken into account. Although telemedicine offers a better accessibility to health-care services, physician's opinion about telemedicine has shown that 10% of physicians indicated that a definitive diagnosis could not be achieved through telemedicine.[30] Therefore, according to 10% of physicians, a face-to face consult would have been better than a telemedicine consultation. The utility of telemedicine was estimated as 90% [Table 5].{Table 5}


  Results Top


Data about patient diagnosis, current therapy, and comorbidities were extracted from medical records located at the Cardiology Department of INRCA Hospital. After the interview with patient and his/her family members, for purpose of the study, an interview with caregiver was also conducted. During the interview, the study was presented, with explanation of patient's benefit, responsibility, and adverse effect of the study. For the purpose of Care SEK study, the caregiver was also obliged to sign an informed consent.

The KCCQ is a 23-item, self-administered instrument that was collected at baseline and after 6 months of telehome monitoring [Table 6].
Table  6: Kansas City Cardiomyopathy Questionnaire score

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Limited by a small sample size, to estimate the effect of telemedicine intervention on hospitalization and mortality, we used change of KCCQ score before and after telemedicine trial as a predictor of economical ad clinical outcomes of telemedicine. From collected KCCQ questionnaire before and after the trial, the health status of patients affected with CHF was assessed. The change in health status assessed after 6 months were used to estimate a change in the probability of hospitalization and mortality after 6 months of telehome monitoring. The KCCQ is a strong independent predictor of hospitalization and mortality, as well as an indicator of quality of life.[6], 7, [31],[32],[33] The cost of HF is associated with different KCCQ scores, a score of below 25 was considered as worst health status, 25/49, 50/75, and above 75 were considered poor, fair, and good, respectively, and corresponds to 8415, 3988, and 1421 euros, respectively.[6] In our study, improvement of KCCQ score from 35 to 50 points with telemedicine has saved 2567 euros annually.

The KCCQ score below 49 corresponds to 40% probability to be hospitalized in 1 year.[31] For each 10-point score of KCCQ increase, the hospitalization rate decreases by 11%.[31] A 16% of decrease in hospitalization is related to 15-point KCCQ score improvement (35–50 points) in telemedicine study [Table 6].

The mortality rate within 1 year of elderly aged 72–85 years, affected with CHF with standard care, is between 44% and 58%,[20],[21] and for the purpose of further calculation, we will hypothesize a mortality rate of 50% for an elderly aged 85 years affected with CHF, user of standard health-care services. Every 10 points of KCCQ score improvement correlate with a probability of 12% decrease for death and hospitalization,[31] which predicts a decrease of probability of death in our telemedicine study up to 18% related to 15-point KCCQ score improvement (35–50 points) in telemedicine study [Table 6].

The cost of travel and productivity loss with usual care is estimated to be 270 euros [Table 4]. These losses refer to travel cost and productivity loss generated by every standard visit. With telehome monitoring, patients can avoid cost of travel and productivity loss of five hours and save a productivity gain of 250 euros. Telemedicine visit requires the time necessary for telemedicine consultation estimated to be 1 h and equals to productivity loss of 20 euros.

Therefore telemedicine can produce productivity gain of 250 euros per visit. Additionally probable improvement of NYHA classes from NYHA III to NYHA II, by improving health status, would improve QALY from 0,61 to 0,68. Different classes NYHA of CHF corresponds following to QALY, NYHA Class I–IV correspond to QALY of 0.77, 0.68, 0.61 and 0.50 respectively.[34]

[Table 7] contains the results obtained with telehome monitoring according to the KCCQ score change after 6 months with telemedicine home monitoring.{Table 7}

Statistical value of life and willingness to pay (WTP)

The telemedicine intervention represents financial investment, and we needed to estimate if the benefit of telemedicine can overcome the cost of telemedicine investment. To assess the value of nonhospitalization from the patients' side, we analyze literature based on evidence that show WTP of an individual in regard of avoidance of hospitalization. WTP represents how much an individual is willing to pay for new treatment or medical intervention that will prevent or decrease the probability of hospitalization. The willingness of an individual to avoid hospitalization varies from 490,[11] 1500,[35] to 7870[36] euros and is influenced by individual's wealth, education, and income.[37] An individual with higher income will be more willing to pay any intervention as he/she will sustain higher productivity loss in case of hospitalization.

To define a benefit of avoiding premature death, it is necessary to assess monetary VLY (value of life year) loss due to chronic heart failure. An individual can be willing to pay some amount of money to reduce a probability of death in the next year. For the willingness of people to trade off their wealth to avoid the probability of death, a common term similar to the value of a statistical life is used.[12]

The common estimation of the VSL (value of statistical life) is based on the life of someone who is 40 years old, in perfect health, at the average life expectancy of 80 years of age. At 40 years of age, a probability to achieve 80 years of age corresponds to roughly 40 life-years and is estimated as VSL of $4 million, where a VLY is $100,000.[12] The VLY of an individual with 40 years and an individual with 75 years is different. With aging, the risk factors that can cause mortality increase, and therefore the VLY diminishes. [Table 8] represents the estimation of different discount rates related to aging.{Table 8}

However, aging is not the only factor which discounts VLY, the poor quality of life associated with different commorbidities and disabilities also discounts VLY. If we improve KCCQ score from 35 to 50, we obtain improvement of quality of life and better health status.

To obtain VLY of an individual aged 85/90 years affected with CHF, we have to apply discount rate for aging and for the commorbidity as CHF. [Table 9] represents a VLY of our target population before and after telehome monitoring study.{Table 9}

The VSL year is higher with telemedicine as the health status of elderly aged 85 is better off with telemedicine application, which has been demonstrated with KCCQ improvement after 6 months.

How much an individual is willing to pay an intervention or treatment to live an extra year of life, after 75 years of age? The WTP for an extra year of life of an individual who has reached his/her life expectancy of 75 years is estimated to be 1505 euros according to a random sample of adult Swedes, who expressed their current WTP for a new technology which would prolong the expected remaining duration of their lives, conditional on having survived until the age of 75.[42]

Applying a probability of an event (hospitalization and mortality) to old and new KCCQ score, and adding the cost of hospitalization from [Table 3] and VLY from [Table 9], we obtained a probable cost savings with telehome monitoring. Additional cost of telemedicine equipment is added to telemedicine arm. The cost of CHF management [6] according to old and new KCCQ score obtained with telehome monitoring was calculated too. [Figure 2] shows a total probable cost saving for health-care providers with telehome monitoring which is estimated to be 7632 euros per patient.{Figure 2}

Evaluating patients' productivity loss with standard care and productivity gain with telehome monitoring, and deducting the cost of telemedicine solution, we estimated a probable cost saving for patients. To the probability, to avoid a fatal event such as hospitalization and mortality with usual care and telehome monitoring, the WTP of an individual to avoid fatal event is added. With telemedicine, we have a higher probability to avoid a hospitalization and mortality and to improve quality of life. [Figure 3] shows the probable cost savings with telehome monitoring per patient which is 5428 euros.{Figure 3}


  Discussion Top


Almost 30% of hospital readmissions are avoidable.[43] Frequent and continuous monitoring can improve patients' compliance to the therapy, the self-management can improve patient's responsibility and their health behavior. Chronic heart failure requires a patient involvement in disease management and continuous monitoring of patient's vital parameters.

The telemedicine intervention theoretically should provide essential savings for health-care system. The cost of travel avoided, prevention of hospitalization through early detection and frequent monitoring represent cost containment for both sides, for patient and health-care system theoretically and empirically. Nevertheless, the high cost of telemedicine equipment, lack of professional's human skills for telemedicine use, as well as lack of willingness to change are obstacles for wider use of telemedicine.

The most common economic analysis is cost analysis, and it neglects a broad range of economic benefits of telemedicine from a variety perspectives, as benefits associated with transportation, leisure time, productivity, and quality of life.[29]

The KCCQ questionnaire quantifies the severity of HF from patient's perspective and its impact on physical and social function and quality of life, 5-point change in the KCCQ score corresponds to changes in the measures of functional capacity, that is estimated as clinically meaningful.[44]

The aim in our study was to establish the benefits and cost saving with telehome monitoring application in relation to improved health status measured with KCCQ questionnaire. As previously mentioned, chronic heart failure represents a major public health-care problem, because the disability, rehospitalization, and mortality are associated with it. This problem shows an increasing trend associated with an increase in the prevalence and incidence of CHF among elderly population.

The improvement of KCCQ score from baseline of 15 points [Table 6] permits to calculate probable reduction of hospitalization, mortality, and probable cost reduction associated with new (after trial) health status. The cost of hospitalization and outpatient care generated by patients is paid by provider, while mortality represents a cost for society; any improvement in these outcomes represents a cost saving for the health-care provider and society. Even when cost of singular telemedicine equipment and associated maintenance and training cost were deducted, telehome monitoring application was more cost-effective than standard care [Figure 2]. This has been demonstrated with reduction of hospitalization of 16% and mortality rate of 18% that correspond to cost savings of 694 euros and 6293 euros, respectively. The yearly outpatient cost was decreased after the trial with saving of 2567 euros per patient, with a total cost saving for provider side of 7632 euros [Figure 2].

The KCCQ score improvement also improved a probability to avoid hospitalization and to extend additional year of life, after the level of life expectancy of 75 years of age is reached. Even when the high cost of telemedicine was deducted, benefits for the patient in terms of monetary value were higher for telemedicine [Figure 3]. On patient's side, we obtained cost savings of 5428 euros with telemedicine [Figure 3].

A meta-analysis of randomized clinical trial which assessed the cost-effectiveness and the cost utility of remote patient monitoring versus the usual care demonstrated cost saving from 300 euros to 1000 euros, in favor of remote patient monitoring. The cost savings demonstrated a (QALYs) gain of 0.06.[45] In our study improvement of KCCQ score of 15 points demonstrated improvement of QALY gain of 0,07 [Table 7].

The other studies conducted on elderly population affected with CHF, with a mean age from 66 to 79 years, demonstrated similar results of cost savings with telemedicine solution. Reduction of hospitalization between usual care and remote monitoring was 40% in telemedicine group, and important cost saving was obtained.[46],[47] In our study, hospitalization rate is reduced for 16%. In addition, the studies from literature demonstrated a reduction in mortality rate of 56% with telemedicine.[48] In our study, reduction of mortality associated with KCCQ score improvement was 18%.

The reviewed studies were randomized clinical trials, with a strong internal validity. Furthermore, the number of patients in those studies was higher from 24 to 230 in telemedicine group or in total from 48 to 460 patients in both arms, than in our study.[46],[47],[48]

The results from the meta-analysis and randomized clinical trial are in correlation with our results, although we achieved minor rate of hospitalization and mortality than the mentioned studies. Our study has limitation such as small sample size (eight patients), older population (average age of 86.7 years), design (observational study), and duration of study (6 months), which can be the reason for minor improvement of clinical outcomes in our study.

Although the highest burden of CHF cost is carried by health-care provider, the benefit of telemedicine at patient side is also very important and has influence on patient motivation toward telemedicine. Based on the results demonstrated in our studies, represented as cost savings of 5428 euros per patient with telemedicine, it may have significance of probable increase of telemedicine wider use and patient's acceptance of telemedicine.

Our study had included important innovation not present in other studies such as educational module, which has the aim to increase knowledge and self-efficacy of an individual in the management of chronic heart failure, preparing patient for self-management. The KCCQ as well showed a positive effect of educational model with improvement of KCCQ self-efficacy score from 34 to 53, stability score from 55 to 62.5, system frequency score from 36.3 to 47.5, and social limitations from 10 to 23 [Table 7]. The clinical improvement was observed as patient felt better with frequent monitoring, which prevented disease exacerbation and hospitalization, that usually makes patient weak and limits his/her capacity to socialize. The patient's subjective and clinically objective assessment of quality-of-life improvement correlated with higher score of KCCQ with telemedicine use from 28.3 to 38. Quality of life is observed as reduction of symptoms' occurrence, better mobility of patient, lower depression occurrence, and reduction of hospitalization.


  Conclusion Top


Telecardiology is a cost-effective intervention for the elderly population affected with HF. In our study, when cost of telemedicine is deducted, benefit for either provider or patient was significant. The sustainability of health-care system financing is under the pressure with growing aging population. Quality-of-care indicators such as effectiveness, responsiveness, patient centeredness, and accessibility can be improved with telemedicine. Health-care service for the elderly affected with chronic disease can be provided in a more effective way through telehome monitoring, allowing aging in place. The ultimate goal and effect of any health-care system is to provide good health of the population.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Biermann J, Neumann T, Angermann CE, Erbel R, Maisch B, Pittrow D, et al. Economic burden of patients with various etiologies of chronic systolic heart failure analyzed by resource use and costs. Int J Cardiol 2012;156:323-5.  Back to cited text no. 1
[PUBMED]    
2.
Giordano A, Scalvini S, Zanelli E, Corrà  U, Longobardi GL, Ricci VA, et al. Multicenter randomised trial on home-based telemanagement to prevent hospital readmission of patients with chronic heart failure. Int J Cardiol 2009;131:192-9.  Back to cited text no. 2
    
3.
Dansky KH, Vasey J, Bowles K. Impact of telehealth on clinical outcomes in patients with heart failure. Clin Nurs Res 2008;17:182-99.  Back to cited text no. 3
[PUBMED]    
4.
Dang S, Dimmick S, Kelkar G. Evaluating the evidence base for the use of home telehealth remote monitoring in elderly with heart failure. Telemed J E Health 2009;15:783-96.  Back to cited text no. 4
    
5.
Spertus J, Peterson E, Conard MW, Heidenreich PA, Krumholz HM, Jones P, et al. Monitoring clinical changes in patients with heart failure: A comparison of methods. Am Heart J 2005;150:707-15.  Back to cited text no. 5
    
6.
Chan PS, Soto G, Jones PG, Nallamothu BK, Zhang Z, Weintraub WS, et al. Patient health status and costs in heart failure: Insights from the eplerenone post-acute myocardial infarction heart failure efficacy and survival study (EPHESUS). Circulation 2009;119:398-407.  Back to cited text no. 6
[PUBMED]    
7.
Soto GE, Jones P, Weintraub WS, Krumholz HM, Spertus JA. Prognostic value of health status in patients with heart failure after acute myocardial infarction. Circulation 2004;110:546-51.  Back to cited text no. 7
[PUBMED]    
8.
Pearce D. Valuing Risks to Life and Health, Paper Prepared for the European Commission (DGXI) Workshop on Valuing Mortality and Valuing Morbidity, Brussels, November, Revised December; 2000.  Back to cited text no. 8
    
9.
Orley A. Measuring the Value of a Statistical Life: Problems and Prospects, Discussion Paper Series, Forschungsinstitut Zur Zukunft Der Arbeit Institute for the Study of Laboratory; January, 2006.  Back to cited text no. 9
    
10.
Boardman A, Greenberg D, Vining A, Weimer D. Cost-Benefit Analysis: Concepts and Practice. 4th ed. United Kingdom: Pearson Education Limited; 2014.  Back to cited text no. 10
    
11.
EuroVaQ, European Value of a Quality Adjusted Life Year: Instrument Specific Targeted Research Project, Final Publishable Report; 2010.  Back to cited text no. 11
    
12.
Burström K, Sun S, Gerdtham UG, Henriksson M, Johannesson M, Levin LÅ, et al. Swedish experience-based value sets for EQ-5D health states. Qual Life Res 2014;23:431-42.  Back to cited text no. 12
    
13.
Hultkrantz L, Svensson M. The value of a statistical life in Sweden: A review of the empirical literature. Health Policy 2012;108:302-10.  Back to cited text no. 13
    
14.
Dickstein K, Cohen-Solal A, Filippatos G, McMurray JJ, Ponikowski P, Poole-Wilson PA, et al. ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2008: The Task Force for the diagnosis and treatment of acute and chronic heart failure 2008 of the European Society of Cardiology. Developed in collaboration with the Heart Failure Association of the ESC (HFA) and endorsed by the European Society of Intensive Care Medicine (ESICM). Eur J Heart Fail 2008;10:933-89.  Back to cited text no. 14
    
15.
Koehler F, Winkler S, Schieber M, Sechtem U, Stangl K, Böhm M, et al. Telemedical Interventional Monitoring in Heart Failure (TIM-HF), a randomized, controlled intervention trial investigating the impact of telemedicine on mortality in ambulatory patients with heart failure: Study design. Eur J Heart Fail 2010;12:1354-62.  Back to cited text no. 15
    
16.
Jovicic A, Holroyd-Leduc JM, Straus SE. Effects of self-management intervention on health outcomes of patients with heart failure: A systematic review of randomized controlled trials. BMC Cardiovasc Disord 2006;6:43.  Back to cited text no. 16
    
17.
Heidenreich PA, Spertus JA, Jones PG, Weintraub WS, Rumsfeld JS, Rathore SS, et al. Health status identifies heart failure outpatients at risk for hospitalization or death. J Am Coll Cardiol 2006;47:752-6.  Back to cited text no. 17
    
18.
Sullivan MD, Levy WC, Russo JE, Crane B, Spertus JA. Summary health status measures in advanced heart failure: Relationship to clinical variables and outcome. J Card Fail 2007;13:560-8.  Back to cited text no. 18
    
19.
Politi C, Deales A, Cicchitelli F, Marcobelli A, Barbadoro P, Zorzan R, et al. Health care costs for heart failure in Marche region Pharmacoeconomics-Ital-Res-Articles 2005;7:165.  Back to cited text no. 19
    
20.
MacIntyre K, Capewell S, Stewart S, Chalmers JW, Boyd J, Finlayson A, et al. Evidence of improving prognosis in heart failure: Trends in case fatality in 66 547 patients hospitalized between 1986 and 1995. Circulation 2000;102:1126-31.  Back to cited text no. 20
    
21.
Shahar E, Lee S, Kim J, Duval S, Barber C, Luepker RV. Hospitalized heart failure: Rates and long-term mortality. J Card Fail 2004;10:374-9.  Back to cited text no. 21
    
22.
Konstam MA. Progress in heart failure management? Lessons from the real world. Circulation 2000;102:1076-8.  Back to cited text no. 22
    
23.
Ministry of Health, DECREE 18 October 2012. Remuneration for acute hospital care, hospital rehabilitation and after-care rehabilitation and specialist outpatient care. Gazzetta Ufficiale Della Republica Italiana; 28 January, 2013.  Back to cited text no. 23
    
24.
Cacciatore P, Ceccolini C, Granella P, Lispi L, Boldrini R, Di Cesare M, et al. Analisi Dei Ricoveri Per Insufficienza Cardiaca in Italia Anni 2001-2003: Rome: Departimento Della Qualita, Ministero Della Salute; 2007.  Back to cited text no. 24
    
25.
Final Report, Framework Agreement between Umbria and S.I.M.G. Analysis of Costs of Diabetes Mellitus and Cardiac Insufficiency. Firenze: General Directorate of Health and Social Cohesion; 2014.  Back to cited text no. 25
    
26.
Agha Z, Schapira RM, Maker AH. Cost effectiveness of telemedicine for the delivery of outpatient pulmonary care to a rural population. Telemed J E Health 2002;8:281-91.  Back to cited text no. 26
    
27.
Sahlen KG, Löfgren C, Brodin H, Dahlgren L, Lindholm L. Measuring the value of older people's production: A diary study. BMC Health Serv Res 2012;12:4.  Back to cited text no. 27
    
28.
Eurostat. The Greying of the Baby Boomers: A Century-Long View of Ageing in European Populations. Luxembourg: Statistics in Focus, Eurostat the Statistical Office of the European Union; 2011.  Back to cited text no. 28
    
29.
Dávalos ME, French MT, Burdick AE, Simmons SC. Economic evaluation of telemedicine: Review of the literature and research guidelines for benefit-cost analysis. Telemed J E Health 2009;15:933-48.  Back to cited text no. 29
    
30.
Stensland J, Speedie SM, Ideker M, House J, Thompson T. The relative cost of outpatient telemedicine services. Telemed J 1999;5:245-56.  Back to cited text no. 30
    
31.
Joseph SM, Novak E, Arnold SV, Jones PG, Khattak H, Platts AE, et al. Comparable performance of the Kansas City Cardiomyopathy Questionnaire in patients with heart failure with preserved and reduced ejection fraction. Circ Heart Fail 2013;6:1139-46.  Back to cited text no. 31
    
32.
Kosiborod M, Soto GE, Jones PG, Krumholz HM, Weintraub WS, Deedwania P, et al. Identifying heart failure patients at high risk for near-term cardiovascular events with serial health status assessments. Circulation 2007;115:1975-81.  Back to cited text no. 32
    
33.
Dai S, Manoucheri M, Gui J, Zhu X, Malhotra D, Li S, et al. Kansas City Cardiomyopathy Questionnaire utility in prediction of 30-day readmission rate in patients with chronic heart failure. Cardiol Res Pract 2016;2016:4571201.  Back to cited text no. 33
    
34.
Alehagen U, Rahmqvist M, Paulsson T, Levin LA. Quality-adjusted life year weights among elderly patients with heart failure. Eur J Heart Fail 2008;10:1033-9.  Back to cited text no. 34
    
35.
Srinivasan  T.   Cost  of  Excess  Hospitalizations  and  Emergency  Department  Visits  for  the  2006-2008.   Environmental  Health Perspectives. Available from: http://www.ehponline.org/docs/2008/11594/abstract.html. [Last retrieved on 2017 Jan 20].  Back to cited text no. 35
    
36.
Extern E, Maddison D. The Plausibility of the ExternE Estimates of the External Effects of Electricity Production, Paper GEC 99-04, Centre for Social and Economic Research on the Global Environment, University College London, London; 1999.  Back to cited text no. 36
    
37.
Pavel MS, Chakrabarty S, Gow J. Assessing willingness to pay for health care quality improvements. BMC Health Serv Res 2015;15:43.  Back to cited text no. 37
    
38.
Jones-Lee M. The Economics of Safety and Physical Risk. Oxford: Blackwell; 1989.  Back to cited text no. 38
    
39.
Jones-Lee M, Loomes G, O'Reilly D, Philips P. The Value of Preventing Non-fatal Road Injuries: Findings of a Willingness to Pay National Sample Survey, Working Paper WP/SRC/2, Transport Research Laboratory, Crowthorne; 1993.  Back to cited text no. 39
    
40.
Jones-Lee MW, Loomes G, Jones S, Rowlatt P, Spackman M, Jones S. Valuationof Deaths from Air Pollution, NERA and CASPAR, Report Prepared for the Department of Environment, Transport and the Regions and the Department of Trade and Industry, London; 1998.  Back to cited text no. 40
    
41.
Krupnick A, Alberini A, Cropper M, Simon N, O'Brien B, Goeree R, Heintzelman M. Age, Health and Willingness of Pay for Mortality Risk Reduction: A Contingent Valuation of Ontario Residents, Discussion Paper 0-0-37, Resources for the Future, Washington DC; 2000.  Back to cited text no. 41
    
42.
Johannesson M, Johansson PO. To be, or not to be, that is the question: An empirical study of the WTP for an increased life expectancy at an advanced age. J Risk Uncertain 1996;13:163-74. [1996 Kluwer Academic Publisher].  Back to cited text no. 42
    
43.
van Walraven C, Bennett C, Jennings A, Austin PC, Forster AJ. Proportion of hospital readmissions deemed avoidable: A systematic review. CMAJ 2011;183:E391-402.  Back to cited text no. 43
    
44.
Flynn KE, Lin L, Moe GW, Howlett JG, Fine LJ, Spertus JA, et al. Relationships between changes in patient-reported health status and functional capacity in outpatients with heart failure. Am Heart J 2012;163:88-94.e3.  Back to cited text no. 44
    
45.
Klersy C, De Silvestri A, Gabutti G, Raisaro A, Curti M, Regoli F, et al. Economic impact of remote patient monitoring: An integrated economic model derived from a meta-analysis of randomized controlled trials in heart failure. Eur J Heart Fail 2011;13:450-9.  Back to cited text no. 45
    
46.
Jerant AF, von Friederichs-Fitzwater MM, Moore M. Patients' perceived barriers to active self-management of chronic conditions. Patient Educ Couns 2005;57:300-7.  Back to cited text no. 46
    
47.
Benatar D, Bondmass M, Ghitelman J, Avitall B. Outcomes of chronic heart failure. Arch Intern Med 2003;163:347-52.  Back to cited text no. 47
    
48.
Goldberg LR, Piette JD, Walsh MN, Frank TA, Jaski BE, Smith AL, et al. Randomized trial of a daily electronic home monitoring system in patients with advanced heart failure: The Weight Monitoring in Heart Failure (WHARF) trial. Am Heart J 2003;146:705-12.  Back to cited text no. 48
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]



 

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