Summary of current insurance system shortcomings and expected improvements for future policies.
\r\n\t
",isbn:"978-1-83968-388-6",printIsbn:"978-1-83968-387-9",pdfIsbn:"978-1-83968-389-3",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"61ec2bad4fc3f7060fd64b91fa12e82c",bookSignature:"Ph.D. Vicente Vanaclocha",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10574.jpg",keywords:"Prevalence, Incidence, Worldwide Differences, Red Flags, Moyamoya and School Performance, Medical Treatment, Surgical Treatment, Genetic Markers, Immunologic Factors, Recommended Anesthetic Agents, Source of Intraoperative Complications, Post-Operative ICU Management",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 23rd 2020",dateEndSecondStepPublish:"October 21st 2020",dateEndThirdStepPublish:"December 20th 2020",dateEndFourthStepPublish:"March 10th 2021",dateEndFifthStepPublish:"May 9th 2021",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Vicente Vanaclocha is a Chief of Neurosurgery at the University Hospital of Navarra and head of Neurosurgery Service of San Jaime Hospital in Torrevieja. He has over 25 years of experience in neuro-oncology and minimally invasive surgery techniques. He is a pioneer in many areas in neurosurgery (treatment of brain tumors, Chiari Malformation, and sacroiliac joint disorders).",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"199099",title:"Ph.D.",name:"Vicente",middleName:null,surname:"Vanaclocha",slug:"vicente-vanaclocha",fullName:"Vicente Vanaclocha",profilePictureURL:"https://mts.intechopen.com/storage/users/199099/images/system/199099.jpeg",biography:"Vicente Vanaclocha is Chief of Neurosurgery. Doctor of Medicine from the University of Valencia, he has over 25 years experience in neuro-oncology, minimally invasive and minimally invasive surgery techniques. Specialist in neurosurgery both nationally and internationally (including the General Medical Register of England and stay at the Groote Schuur Hospital in Cape Town, South Africa) has been Chief of Neurosurgery at the University Hospital of Navarra and head of Neurosurgery Service of San Jaime Hospital in Torrevieja. 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"71860",title:"Membrane Applications for Lactose Recovering",doi:"10.5772/intechopen.92135",slug:"membrane-applications-for-lactose-recovering",body:'Dairy industry is one of the major food processing industries in the world, manufacturing a broad range of different products. Therefore, it generates large amounts of by-products during the processing of milk and manufacture of dairy products (e.g., cheese, butter, and yogurts), leading to problems of their management/utilization [1].
Cheese whey is the most abundant co-product in the cheese-making and casein industries. It contains about 65 g L−1 of dry matter, being lactose the main component (70–80%), proteins (9%), corresponding to 20% of all milk proteins, and minerals (8–20%) and, to a much lesser extent, hydrolyzed peptides from casein-k, lipids, and bacteria, which resulted from cheese manufacturing [2, 3]. Generally, for each 100 kg of milk, around 10–20 kg of cheese is manufactured, and 80–90 kg of liquid whey is released [4]. According to Food and Agriculture Organization Corporate Statistical Database (FAOSTAT), more than 114 million tons of whey were produced worldwide in 2013, with Europe producing 63 million tons in that year [5]. Data from the European Whey Products Association (EWPA) indicated that about 6 million tons of whey (dry matter) were produced in the European Union in the year 2015 [6]. In spite of these larger volumes produced, only around 50% of the whey annually produced in the world is valorized into different added-value products. This is because, although cheese whey is an inexpensive and abundant source for developing new added-value products (e.g., foods, pharmaceuticals, and energy), its low solid content makes it difficult for direct utilization [4]. Therefore, for recovering any of its components, such as the lactose, several processes, mainly separation processes, should be used. The intended final use of lactose determines the process that should be used for its separation from cheese whey.
Membrane separation is a filtration process based on the use of membranes for the separation of dissolved or colloidal solids in liquid mixtures, or the separation of small components in gaseous mixtures. A membrane is a permselective barrier between two phases (feed/retentate) and permeate, which preferably allows the permeation of a component (or components) of the feed retaining others, leading to their separation, purification, or concentration. The difference in permeability (membrane transport) between the components of the mixture is due to differences in size (ratio between mean pore radius of membrane and size of solute to be separated) and/or chemical selectivity for membrane material (relationship among chemical characteristics) [4].
These processes differ from frontal filtration in the following characteristics: (1) the particle size they separate; (2) tangential rather than dead-end mode of feed introduction; and (3) use of membranes, in spite of depth filters. Therefore, these processes allow to expand the scope of frontal filtration for separating components of smaller dimensions (less than 1 μm). The parallel flow limits the accumulation of substances retained on the membrane due to shear stress and two different product streams are obtained (Figure 1). When using membranes, the components are retained to the surface in a thin film, called the active layer or skin, and so higher retention rates are possible [4, 7].
Diagram of a membrane separation process [4].
Membrane separation processes can be classified according to the driving force that controls the mass transfer rate of the individual components from one phase to another. These driving forces can be of several natures such as concentration gradients, temperature, pressure, and external force fields. The main processes used at an industrial level are pressure-driven processes, such as microfiltration, ultrafiltration, nanofiltration, and reverse osmosis [8, 9]. In these processes, by applying a pressure, the solvent and some solutes freely permeate the membrane, while others are retained to varying extents, depending on various factors, such as solute, membrane characteristics, operating parameters, or others [8, 9]. The size of the particle or molecule to be separated as well as its chemical properties determines the structure (porous or dense, pore size, and pore size distribution) of the membrane to be used. The nature of the solvent (aqueous or organic), the cleaning method, the applied pressure, and the temperature influence the type of membrane material [10]. When it progresses toward microfiltration, ultrafiltration, nanofiltration, and reverse osmosis, the size or molecular weight of particles or molecules that are retained by the membrane, pore size, and porosity decreases. This means that the hydrodynamic resistance of the membranes to mass transfer is increasing, requiring higher applied pressures to achieve the same permeation fluxes.
Following water and wastewater treatment, the food industry ranks second in applications of those processes. Most applications are in the dairy industry (production of whey protein concentrates; milk protein standardization), followed by the beverage (wine, beer, vinegar, and fruit juice) and egg product industries [8, 11]. In the food industry, the application of membrane separation processes provides several benefits, such as food safety, competitiveness, innovation, and environmental compatibility. Food safety through membrane processes can be achieved, for example, by cold sterilization, using microfiltration. They are competitive with other concentration processes, for example, thermal processes, due to their lower energy consumption. In addition, they can be easily integrated into industrial plants due to ease of implementation, possibility of using compact modules, and good automation. So, these processes are currently present in several industrial plants, namely in the development of new value-added products, for example, from by-products (cheese whey or second cheese whey) and/or residues of the food industry. In addition, since only cleaning agents are used and the processes can be operated under mild conditions (pressure and temperature), they are recognized as green processes [3].
The membranes can be manufactured with different types of materials (polymeric or inorganic), may have different structures (symmetrical or asymmetrical), and are usually commercialized in arrangements of membranes, with a high surface area per unit volume, called modules.
The nature of the material used is an important aspect of membrane processes because it can affect the behavior and performance and limits the use of a membrane, for a particular application. Regardless of its nature, that material must have good thermal, mechanical, and chemical stability; hydrophilicity or hydrophobicity; ease of manufacture on a wide variety of dimensions pores; modules; and configurations [4, 7]. In this respect, inorganic membranes made from ceramic materials are the most used, due to its higher thermal, chemical, and mechanical stability than polymeric membranes. These characteristics allow its use in a wider pH region and with different organic solvents. Furthermore, they are easier to clean and disinfect, since more concentrated solutions of strong acids and bases and higher temperatures can be used, keeping their life span. Some disadvantages of these membranes compared to polymeric ones are mainly associated with its higher cost, the need of using higher flow rates (greater energy consumption), and to the fact that, currently, does not exist in the market ceramic nanofiltration membranes with limit of separation less than 250 Da [12].
The classification of membranes according to their structure is shown schematically in Figure 2. Symmetrical membranes include microporous and homogeneous membranes (dense and nonporous). The thickness of the symmetric membranes can vary approximately from 10 to 200 μm, the resistance to mass transfer being determined by the total thickness of the membrane. Thus, the thinner the membrane, the higher the permeation rate [7]. These membranes are applied in microfiltration and can be classified, on an absolute scale, through their maximum equivalent pore diameter. Homogeneous membranes are mainly applied in gas separation. Asymmetric membranes have a structure consisted of a very thin film on their surface with a thickness in the range of 0.1–0.5 μm, called skin or active layer, which is based on a porous support layer, the thickness of which can vary between 100 and 200 μm [4, 7]. The separation occurs only at the surface, in the active layer, retaining components whose molar mass is greater than the molecular weight cut-off (MWCO) of the membrane, which is defined as the molar mass that is 90% rejected by this membrane. The manufacturing process of the membranes still leads to obtaining two different substructures: the integral asymmetric membrane design and nonintegral asymmetric membranes, the latter forming part of the composite membranes. Integral asymmetric membranes are obtained from a single polymer. Composite membranes, also called thin-film, thin, or ultrafine layer composites, are manufactured with a polymer (or other material) different from that used in the layer support and in several stages, which make it possible to optimize each of them, independently. These membranes are used in ultrafiltration, nanofiltration, and reverse osmosis.
Schematic representation of membrane structure.
The design of the modules is based on two types of membrane configurations: flat and tubular. Plate modules and spiral-wound modules involve flat membranes, while tubular, capillary, and hollow fiber modules are based on tubular membrane configurations. In general, an industrial membrane installation consists of the association of several modules, which are selected and configured in parallel or in series, depending on the production/specification of the final product. The selection of the module configuration, as well as the module arrangement, is based on several factors: economic considerations; type of application; ease of cleaning, maintenance, and operation; compactness of the system; and scale and possibility of replacing membranes.
The main parameters used to evaluate the performance of a membrane are the permeate flux that is a measure of its productivity and the apparent rejection coefficient, which allows us to estimate their selectivity. The permeate flux (Jv) is defined as the amount, in volume or mass, that passes through the membrane per unit area and time, that is,
where Jv is the volumetric permeate flux (m s−1); V is the volume of the permeate (m3); A is the membrane surface (m2); and t (s) is the time required to collect the volume of permeate V.
The rejection coefficient is a measure of membrane selectivity for the separation of a given solute, which may be partially or totally retained by it, while the solvent freely permeates the membrane. The apparent (or observed) rejection coefficient, R, is defined as follows:
where Cf is the concentration of a particular solute in the feed, and Cp is the concentration of this solute in the permeate.
The apparent rejection coefficient depends on the experimental conditions, namely transmembrane pressure and feed circulation velocity. This coefficient is a dimensionless quantity, which can take values between 0 and 1, as the solute freely permeates the membrane or is completely retained by it, respectively. The latter situation corresponds to an ideal semi-permeable membrane.
The permeate flux and apparent rejection coefficient are influenced by several factors related to solute characteristics (size and shape, macro and micro solute coexistence), membranes (more hydrophobic/hydrophilic character, surface charge distribution, and surface roughness), operating parameters (transmembrane pressure, feed circulation velocity, and temperature), environmental conditions (pH, ionic strength, and osmotic pressure), and type of module (plane and tubular) [13]. These factors give rise to the resistive phenomena mass transfer across the membrane, referred to as concentration polarization and fouling, which can severely affect the performance of membrane processes. Another factor that can reduce the performance of membrane processes is the effect of osmotic pressure.
Concentration polarization consists in the formation of a concentration gradient in a thin layer near the membrane surface, caused by the accumulation of the retained species and leads to the initial decrease of permeate fluxes, which may also contribute to a reduced selectivity. It mainly affects those processes with larger pore membranes (higher permeate fluxes) such as microfiltration and ultrafiltration and can be minimized through the use of low pressures, high feed circulation rates, and low solute concentrations.
Fouling consists of pore obstruction (on or in the surface), caused by solute-membrane or solute-solute interactions, which mainly depend on the characteristics of the solutes, of the membrane, and of operating conditions and the type of module. This phenomenon can lead to a sharp reduction in permeate flux and can alter membrane selectivity [14]. In order to reduce the effects of fouling, various preventive methods can be used such as (1) use a suitable pre-treatment for the food (pre-filtration, pH adjustment, and adequate heat treatment); (2) select the most suitable membrane (narrow pore size distribution, hydrophobicity characteristics, presence of charged groups, or with certain functional characteristics on the membrane surface); (3) use the modules with spacers and work with high feed circulation rates or even at low permeate fluxes, by reducing the applied transmembrane pressure; and (4) use the rotary (or vibratory) modules, in which the membrane moves on a rotating cylinder, creating greater turbulence close to the membrane, compared with conventional tangential modules, while maintaining low shear rates within the fluid [15].
The effect of osmotic pressure in the decline of permeate fluxes is generally neglected in microfiltration and ultrafiltration since the solutes to be separated in these cases have very high molar masses. However, if the concentration of macromolecular solutes is very high, then this effect will have to be accounted for. The phenomenon is especially important in reverse osmosis and also nanofiltration, since in these processes, the solutes that separate are of low molar mass, so the osmotic pressures can be high, decreasing the effective pressure.
In addition, the performance of the overall membrane process should also take into account economic factors, such as membrane prices and shelf life, cleaning and disinfection reagents, and energy consumption.
In the industrial process that is currently used for lactose production, membrane separation techniques have already been introduced because lactose is currently recovered from the whey ultrafiltration permeate. The whey proteins separated have different and interesting applications (e.g., whey protein concentrates, WPC, or whey protein isolates, WPI), thus contributing to the valorization of cheese whey. The Commonwealth Scientific and Industrial Research Organization (CSIRO) developed a method for the possible commercial production of pharmaceutical quality lactose, which integrates the following operations: ion exchange (for calcium and magnesium removal), nanofiltration/diafiltration (for lactose separation, concentration, and purification), evaporation, crystallization, and chromatography, allowing not only to obtain high purity lactose, as well as mineral salts and calcium from cheese whey. This process has several benefits because through the use of nanofiltration/diafiltration, it is produced by a purified lactose concentrate, minimizing simultaneously the evaporation costs due to the reducing volume. Besides, the nanofiltration permeate can be subjected to reverse osmosis, producing water of good quality (e.g., for cleaning and diafiltration).
The recovery of lactose from cheese whey by membrane processes is mainly carried out by nanofiltration (NF) of the ultrafiltration permeates, due to their physical-chemical composition. Those permeates are composed of small solutes, being lactose the major compound of the dry matter, followed by several ions such as, sodium, potassium, calcium, magnesium, chloride, phosphate, and citrate. Therefore, the specific selectivity of NF to this type of solutes and its lower energy consumption, compared with other processes such as reverse osmosis and evaporation, has boosted their use in dairy [8, 16, 17] and other agroindustrial sectors.
One of the most important uses of nanofiltration is the production of whey-demineralized lactose concentrates in the food industry, or even, if enough purification is achieved, for pharmaceutical purposes. The demineralization of dairy fluids is very important to reduce their high salt content (8–20% of dry matter) [3, 18], which causes several difficulties in processing. A high salt content leads to slow lactose crystallization rate because it reduces lactose solubility in supernatant liquor during crystallization.
The major drawback of the NF process is the fouling caused by mineral precipitation of salts, namely calcium phosphates. Another reason for the decrease of permeate flux is the increase of osmotic pressure and concentration polarization, due to the accumulation of lactose and salts (sodium, potassium, and chloride) near the membrane surface, causing a reduction in the effective pressure [19, 20].
Guu and co-workers [21] found that the application of NF for sweet whey or UF permeates allowed to increase the production of lactose crystals by about 10 and 8%, respectively, for a VRR of 3.0. This behavior was attributed to the partial demineralization of the permeate, especially in terms of the monovalent ions, sodium and potassium. These results raised the interest for the integration of NF membranes in the lactose production plants at the industrial level.
Rice and co-workers [22] carried out nanofiltration of ultrafiltration permeates using polyamide membranes NF270 and observed a severe flux decline during filtration at high temperatures and pH, due to calcium phosphate precipitation, because of its lower solubility in these operating conditions. Those authors suggested that if the pH of the feed was reduced, fouling could be avoided, despite changing the separation properties of the membrane.
Cuartas-Uribe and co-workers [23] studied the concentration of lactose from whey ultrafiltration permeates, combining concentration by nanofiltration with continuous diafiltration modes, and found that the best operating conditions were a transmembrane pressure of 2.0 MPa and a volume dilution factor of around 2.0 because a good removal of chloride was possible with the lowest lactose loss for the permeate. Although these authors claimed that no fouling problems were detected during NF tests, experiments at a larger scale should be performed to evaluate the economic feasibility of the process.
Ferg and co-workers [24] also investigated the recovery of lactose through a combination of membrane processes, namely MF (nominal pore size 0.2 μm), UF (5 kDa MWCO), ion exchange, and RO, and obtained an overall lactose recovery of 74%, with a purity of 99.8%.
Bertoluzzi and co-workers [25] compared the performance of two double-stage membrane processes for treatment of dairy wastewaters: (1) microfiltration (MF) plus NF and (2) MF plus OI. For MF, a hollow fibber module was used, being membranes made of poly(ether sulfonate)/poly(vinyl pyrrolidone) (PES/PVP) mixture with a pore size of 0.20 μm. In the NF and RO experiments, polymeric flat-type membranes were used, being these membranes made of polyamide composites. For the NF experiments, they used two different membranes (NF90 and NF), which are made of the same material but have different rejection properties, since NF90 is a tighter membrane, while the other one is a looser membrane, as can also be confirmed by their hydraulic permeabilities to pure water. Before the experiments, the dairy wastewater was prefiltrated across a filter of 0.25 μm to remove solids and to avoid a quick fouling of membranes. After that, microfiltration was also used as a pretreatment for the next operation (NF or OI) with the objective of improving their performance. The authors found that the sequence of MF followed by RO allowed a better removal of total solids and organic matter. Besides, the composition of the final permeate was compatible with the discharge on receiving waters according to the Brazilian environmental regulations or could be used in cleaning-in-place processes in the dairy factory. Although the results of this study are a good basis for other similar dairy wastewaters, since the variety of manufacturing processes involved in dairy products used is too large, for each type of sample/desired goal, a previous study is always necessary.
Macedo and co-workers [20] used a combination of UF/NF and UF/DF followed by NF/DF of the previous permeates, to recover lactose from the permeates both of sheep cheese whey (PUF-S) and of goat cheese whey (PUF-G) (Figure 3).
Recover of lactose (lactose concentrate) and whey proteins from cheese whey: WPC = whey protein concentrate; DF concentrate = whey protein concentrate of UF/DF; lactose concentrate (obtained after NF/DF) [20].
Both samples were subjected to the following pretreatment: filtration (using traditional cotton cloths), skimming for fat removal, and low pasteurization. NF of both permeates was carried out with NFT50 (NF) membranes until a volume concentration factor (VCF) of about 2.5. It was observed a sharp decrease (around 60%) in the permeate flux in the case of PUF-S and a smaller reduction (about 20%) in PUF-G (Figure 4). The authors attributed this different behavior to the following factors: the higher concentration of lactose and applied pressure used in the case of PUF-S (higher permeate fluxes) led to a greater and faster accumulation of lactose near the membrane surface, causing a higher increase in the osmotic pressure and concentration polarization phenomena. On the other hand, since the pH was 6.06 and the initial concentrations of calcium and phosphate were also higher than those of PUF-G, most probably, mineral fouling occurred due to the formation of insoluble calcium phosphates. In the case of PUF-G, the lower pH (5.43) and calcium and phosphate concentrations, due to the effect of dilution by diafiltration, were less prone to mineral fouling, leading to a more stable permeate flux. In spite of that, the permeate fluxes were lower during all the run, likely because of the highest concentration of chloride ions in goat cheese whey, which caused a greater initial osmotic pressure and therefore a lower effective transmembrane pressure. Beyond this, it is likely that also protein fouling contributed to this behavior since the pH of PUF-G was closest to the isoelectric point of β-lactoglobulin, the most abundant whey protein.
Variation of average (three replicates) permeate fluxes with the volume concentration factor (VCF) for the concentration by nanofiltration of PUF-S (∆P = 3.0 × 106 Pa; <v> = 1.42 m s−1) and PUF-G (∆P = 2.0 × 106 Pa; <v> = 0.94 m s−1), at T = 25°C [20].
These results suggest that, in order to reach a better NF performance for recovering lactose, the following procedures should be applied: (1) precipitate calcium or use ionic exchange resins with the objective to reduce calcium concentration in the permeates, avoiding the decline of permeate fluxes during NF, due to the formation of calcium phosphates and (2) optimize NF/DF process to improve the performance of recovery process of lactose.
Membrane processes, for example, nanofiltration, also play a role in the recovery of mother liquor (or delactosed permeate) resulting from the crystallization process. This co-product was investigated after fractionation by membrane processes (NF and reverse osmosis) for salt substitute in soup formulations [26, 27]. By NF, the residual lactose was recovered and recycled to the crystallization tank, enhancing the yield of this process. On the other hand, the permeate was subjected to reverse osmosis producing a retentate enriched in salt, which will be used in the food industry. A detailed review about the possible valorization of the mother liquor is described by Oliveira and co-workers [28].
Several processes for lactose production involving advanced technologies are commercially available. Most of them include membrane processes, namely nanofiltration and reverse osmosis for the production of edible lactose, crystalline lactose, and lactose syrup, which can be used for the production of galactooligosaccharides.
The integration of membrane processes for recovering bioactive compounds from cheese whey, in small and medium dairies, in spite of the initial cost of the equipment, must be investigated in each case. The economic viability of these plants will depend on the valuation to be given to the different separated fractions. Cheese producer’s associations may play a decisive role in the concentration of all the cheese whey released in a given region, in a single plant for processing/recovery of value-added compounds.
The recovery of lactose from cheese whey allows not only the valorization of this co-product in the cheese industry, but also to mitigate the environmental damage caused by it. This work is focused on the use of membrane processes for lactose recovery. The selection of the most suitable process depends on several factors such as composition of the initial cheese whey (quite varied, especially in the case of those resulting from artisanal cheese production), volume produced, and final intended application for lactose. Progress in these processes will lead to an overall improvement in the process of recovering lactose from cheese whey. In the case of membrane separation, its implementation at the industrial level is increasing. Hitherto, its use in small and medium scales is conditioned by the initial economic investment, depending rather on the synergy of the various producers, which in turn should be driven by their associations.
The author Antónia Macedo acknowledges to the project LACTIES (Innovation and eco-efficiency in the dairy sector), PDR2020-1.0.1.-FEADER-030773, and the research group LEAF (Linking Landscape, Environment, Agriculture and Food) for funding this work.
The authors declare no conflict of interest.
In 1998, the State Council of China issued a decision on establishing the basic medical insurance system for urban employees [1].
As a consequence, a universal medical insurance system (UMIS) was designed to improve access to medical services and reduce out-of-pocket (OOP) costs for all Chinese citizens [2]. By 2014, 97.5% of the population had some form of insurance coverage. The key options are the urban employee basic medical insurance (UEBMI), the new rural cooperative medical scheme (NRCMS), or the urban resident basic medical insurance (URBMI). The differences are in the type of population covered (e.g., in 2014, 283.3 million urban employees, 736 million rural citizens, or 314.5 million urban residents), in the annual premium per capita (in 2014, 2841 RMB for UEBMI, 411 RMB for NRCMS, or 409 RMB for URBMI) and consequently, the scope of available funds and coverage [2].
All employing units (employers) and their employees in cities and towns are intended to participate in the UEBMI. The expenses of basic medical insurance shall be shared by employers and employees. The basic system includes the combination of social coordination funds and individual medical saving accounts (MSAs).
The basic medical insurance premiums are paid by individual employees with a 2% payroll tax and by employers with 6% payroll tax. About 30% of the contributions of employers are paid into the personal MSAs, while the remaining 70% of the basic medical insurance premiums are collected as coordination funds. Individual MSAs are used for outpatient payment, the coordination funds are used for hospitalization and to provide for coverage of some special diseases with high medical costs in outpatient departments [3]. The maximum ceiling payment is limited at four to six times the average annual wage of local employees. The excess cost can be insured by commercial medical insurance or government medical assistance. In 2010, these basic medical insurance principles were included in the Social Insurance Law of the People’s Republic of China [4].
Although all provinces have implemented provincial solutions for the basic medical insurance for employees, a few shortcomings have been observed over the years. These include the risk that the funds in the MSAs are not always used efficiently and may not suffice to cover a comprehensive outpatient care. In consequence, patients may prefer to use inpatient care facilities, which however, lead to higher overall costs [3, 5]. Simply put, individual choices on use of health-care funds are done with the short-term individual or family advantage in mind, whereas with pooled HC funds, decisions can be made based on overall health outcome of the population, and supply cost can be negotiated or managed accordingly. Not every individual owner of an MSA has the capability to invest in that HC service, which maximizes health outcomes with the available funds, and there is a risk that individual choices favor delayed treatments at more advanced stages of disease and to worse outcomes. An international study on the efficiency of MSA across different countries (China, Singapore, South Africa, and the United States of America) concluded that “the available evidence suggests that MSA schemes have generally been inefficient and inequitable and have not provided adequate financial protection” [6].
In addition, many healthy people or high-income employees do not use the savings in the personal accounts and therefore, they accumulate over time in the personal MSAs and are not available for the financing of current health-care services [7]. For example, in the Liaoning Province, the recent average proportion of health-care funds accumulated in individual accounts reached 40%, resulting in almost half of medical insurance funds being accumulated as surplus held in the MSAs. The same situation as was observed in Shanghai in 2015, with 40.3% of premium surplus accumulated in medical savings accounts [8]. In a model with a pooled fund administered across the whole membership, the entire budget could be allocated for health-care services across the members as needed. Thus, at any time, the money which is not spent by healthy people can be used for the treatment of sick people.
In terms of equity, a high variation in scope of coverage is also observed [9]. For access to medicines, distorted funding mechanisms create financial barriers for access to medicine in China [10, 11]. Research in 2014 on the impact of the UEBMI on equity revealed improved equity for inpatient services, but inequity growth for outpatient services [12].
Affordability of medicines, a major part of outpatient care, is also still of concern [13]. There is a high regional variability in the scope of coverage and reimbursement methods [13]. For example, in some cities, the coverage for pharmaceuticals lies within the general outpatient coverage scheme; in others a range of “regulated diseases” are defined for coverage, whereas in other cities, a secondary drug reimbursement lists exist.
Due to these challenges and shortcomings, provincial insurance authorities want to improve their insurance policies for UEBMI by raising reimbursement for outpatient care services and products. This will in turn improve utilization of all available funds to increase the overall efficiency of healthcare.
In China, the responsibility for transferring nationally formulated policy objectives into the provinces is decentralized and lies with the provincial administration. There are many options on how the provincial policies can be formulated and applied. Alignment of the overall central policy is important to ensure consistency and equity in health-care access for the Chinese population. However, new policies are in the responsibility of the provincial insurance authorities, and therefore, the policy decision has to be made in each province under consideration of the national policy priorities and the provincial political and health-care context. In such complex situations, decision support tools may help the provincial authorities to prioritize possible insurance options.
Among the plethora of decision support tools, multiple criteria decision analysis (MCDA) was chosen because this method can help to assess multiple, and sometimes conflicting, criteria to evaluate alternatives [14, 15, 16]. It originates from operational research supporting single decision-makers [17] but is increasingly also used to structure decision alternatives, to prognose their consequences, and to facilitate dialog on the benefits and harms of decisions in a multistakeholder context in order to enhance procedural quality in the decision-making process [18]. MCDA methods are used across many branches of science and policy-making including environmental, infrastructural, and health-care policies, prioritization, and planning [15, 19, 20].
Next to MCDA, other methods are existing to inform strategic decisions between alternative option and much can be learned from the world of business management [21]. Some of these lead to increasing complexity such as strategic options development and analysis (SODA), a comprehensive cognitive mapping of individual stakeholder views. Others, such as a “strengths, weakness, opportunity, and threat” (SWOT) analysis, structure the thinking and accumulate facts and data, but the interpretation and weighing is left to the decision-makers. Pure deliberation of the alternatives in the discussion among decision-makers and experts often lead to decisions of low transparency and may lack consistency. Simulating the impact of a new policy in a health economic models or trade-off models would limit the factors to be considered.
MCDA is an umbrella term for decision support tools which can be used in situations like presented here for the Chinese insurance policies, where (1) there are one or several clearly stated objectives that stakeholders groups and/or decision-makers value differently [20], (2) there are several alternative options how to fully or partially reach these objectives, and (3) there multiple criteria, which can be integrated into a calculable composite measure of the benefit or worth of the various alternatives [21]. Among the MCDA methods are the analytic hierarchy process, weighed sum and weighed product models, or ranking and simple multiattribute rating techniques (SMART) as described below [22, 23].
A taskforce of the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) has described the MCDA process for the use in health-care decisions [24, 25]. Generally, the process includes six steps, and is adapted based on the specific decision problem, objective, and context. The definition of the decision problem is the first step. Subsequently, agreement needs to be reached among the stakeholders to determine which criteria are useful to determine the alternative option that will best solve the decision problem. If the importance of these defined criteria differs, the stakeholders also should agree on the weight (relative importance) of each criterion in the assessment of the alternative options.
Finally, in the assessment of the alternatives, each criterion is scored separately and contributes with the predetermined weight, to the composite score that reflects the overall performance of each alternative. As decisions in healthcare often impact a wide range of stakeholders, the criteria may also be chosen to accommodate different stakeholder perspectives [26]. MCDA is being used widely across health-care systems to inform decision-making in healthcare, including benefit-risk assessment of medicines, formulary listings, purchasing, or reimbursement decisions [25, 27, 28, 29]. MCDA has specifically been suggested as an evidence-based health technology assessment (HTA) tool for evaluating off-patent pharmaceuticals in developing countries [30]. Examples for using MCDA in decision-making for off-patent medicines in developing countries are emerging in several countries such as China, Thailand, Indonesia, or Egypt [31, 32, 33, 34].
A short explanation of MCDA in lay language (English) can be viewed in the online material to this book and via the Internet (
The objective of this initiative was to collaborate among provincial insurance policy leaders in China to create an MCDA tool to evaluate insurance policy options across China. This collaborative process was intended to provide a transparent prioritization of insurance models to guide provinces in the decision process. A secondary objective was to adapt a globally validated MCDA in a local environment to address a specific decision problem.
MCDA is a method to support decision-making, while allowing for adaptation to a specific decision problem. The methodology, framework, and process applied in the workshop followed a previously developed and validated model (Figure 1) [30, 33] for adaptation to a new decision problem and context. Each of the phases will be described in detail below.
Process applied for adapting a previously developed MCDA tool and framework to the decision problem of developing new insurance policies in China.
To achieve broad buy-in and acceptance for the tool, many of the important stakeholders should be included. Through participation in an interactive workshop, individual stakeholders will be able to see exactly how the tool was developed and can contribute their perspective to shape the new tool. In order to limit the workshop to less than 1-day preparation prior to the workshop is important. Ideally, the definition of the decision problem should occur prior to the workshop. For the initiative described here, decision problem was the assessment of health-care policy options across China (see Section 1.4).
One of the core principles of designing and implementing change is that the key stakeholders are considered throughout the process according to their respective position in the context of the change. The design and implementation of the new insurance policies will be the responsibility of the provincial insurance authorities under the conditions outlined by the national policy framework. They will not only have to be convinced by the new insurance model and its feasibility, but they will also have to defend any new design versus the outside stakeholders such as provincial policy-makers, provincial urban employers, and provincial urban employees, and toward the inside stakeholders who will be charged with the implementation.
In this initiative, the analysis started by listing all impacted stakeholders who hold influence over the proposed change in program. Each of the stakeholders was rated by their level of interest in the insurance policy and the level of influence (power) they have in relation to the new policies.
For the development of the decision tool, these medical insurance representatives were invited to participate in the workshop. In addition, academic policy influencers and public health experts participated in the presentations and discussions.
In the subsequent steps of piloting, validation, and full implantation (beyond the described workshop), a broader range of stakeholders has to be involved or managed to ensure that their interests are represented, and the decision principles are accepted by expanded stakeholders.
As outlined in the introduction (see Sections 1.1 and 1.2), the national policies could benefit by improvements in the insurance coverage scheme for urban employees. To accommodate the comparison of alternative insurance policies a multicriteria decision tool was created to test how well each insurance option addressed national and provincial requirements.
For this, a set of requirements was identified through desk research and discussion with policy-makers and academic health policy experts before the workshop by the core team, which led to the base set of evaluation criteria.
Preliminary criteria were identified in the five domains presented in Figure 2: (1) funding and finance, (2) access, (3) policy priority (access), (4) equity, and (5) likelihood of change. Each of the domains contained two or three criteria as defined below with a total number of 11 criteria. Of the five domains, two ((2) access and (3) policy priority) were related to access. While more criteria had been considered, it was important to manage the number of criteria. The relevance and feasibility of the proposed criteria was further challenged in the workshop by the participating stakeholders.
Five domains for assessing the impact of insurance policy options on the intended outcomes of the policy changes.
Under the domain of “funding and finance,” two criteria were proposed. The criterion “financial impact for insurance” should help to roughly estimate the financial risk of a potential future health policy on health-care expenditure to be covered by the insurance scheme in comparison to the current insurance expenditure. To estimate the impact of a future insurance model on overall extent of insurance expenditure would be available as funding for healthcare, a criterion “mobilization of funding for outpatient healthcare (HC)” was proposed.
To assess the impact of a future policy on overall “access” for patients to healthcare, three criteria were predefined. With the criterion “access to pharmaceuticals,” the impact of a new insurance model on patient access to ambulatory pharmaceutical therapies as compared to the current system should be assessed. As most of the ambulatory care is made up by pharmaceuticals, which currently are to a large extent paid by the patients out-of-pocket, improvement in this area would be a major achievement. To compare the expected impact of the new model on overall coverage for healthcare in the outpatient setting, the second criterion “outpatient coverage” was suggested. The third criterion “economic burden for patients” was introduced to assess the impact of the potential future health policy on the patients’ finances in comparison to the current system.
A separate domain named “access/policy priority” was put forward for discussion in the workshop to emphasize the need of meeting the policy priorities set by the national government policy. The first priority to be addressed is “timely interventions” (care when it is needed) to assess the impact of the future model on time to care (initiated by patient, family member, or insurance model). The intent here is to decrease the hurdles or improve the motivation for searching for healthcare early in the disease process instead of waiting until reaching more severe disease states before seeking care. The second criterion in this domain, “primary care utilization” is meant to help determine the impact of the future policy on the use of primary care in comparison to the current system. The policy objective emphasized by this criterion is to shift care more toward the primary care level with much lower hurdles for patients as opposed to the current practice of accessing care mostly through specialized hospital services.
Two criteria were attributed to the domain of “equity.” “Solidarity for outpatient HC” appeared an important criterion to compare the impact of the new policy system on the solidarity principle. Full solidarity would mean equal health-care cost to everybody independent from personal health status. Furthermore, the impact of the future insurance model on health-care equity as compared to the current situation should be captured under the criterion of “equity.” This could potentially also imply higher contributions for people with higher income.
An important aspect to look at is the feasibility of introducing a new insurance policy model. This was to be addressed by the domain of “likelihood of change.” The criterion “ease of transition,” required an estimate of the smoothness of transitioning from the current to the future model. A specific criterion “acceptability to stakeholders” was proposed to account for the resistance of key stakeholders toward changing from the current to the potential future system. The final domains and their related criteria are presented in Table 2.
Gaps in current health-care coverage and insurance systems | Expected improvements with a future insurance policy |
---|---|
Equity
| Equity
|
Summary of current insurance system shortcomings and expected improvements for future policies.
Domain | Criterion | Definition |
---|---|---|
Funding and finance | Financial impact and funding for insurance | To estimate the financial impact of a potential future health policy on health-care expenditure to be covered by the insurance scheme in comparison to the current expenditure |
Access | Access to pharmaceuticals | To estimate the impact of a new insurance model on patient access to ambulatory pharmaceutical therapies as compared to the current system |
Coverage for outpatient HC | To compare the expected impact of the new model on overall coverage for ambulatory care | |
Affordability: economic burden for patients | To assess the financial impact on out-of-pocket cost for the patients or family | |
Policy priority | Timely interventions | To assess the impact of the future model on time to care (initiated by patient, family member, or insurance model) |
Primary care utilization | To estimate the impact of the future policy on the use of primary care in comparison to the current system | |
Equity | Solidarity for outpatient HC | To compare the impact of the new policy system on the solidarity principle. Full solidarity = equal HC cost to everybody independent from personal health status |
Equity | To estimate the impact of the future insurance model on health-care (HC) equity as compared to the current situation | |
Likelihood of change | Ease of transition | To estimate the smoothness of transitioning from the current to the future model |
Acceptability to stakeholders | To estimate the resistance of key stakeholders toward changing from the current to the potential future system |
Domains and criteria with definitions as determined in the workshop.
For each of the proposed criteria, a scoring scale was developed. The scoring definitions were mostly qualitative assessments and nonlinear. For example, the possible outcomes and related scores for “financial risk for insurance” were high risk of nonmanageable cost increase (exclusion), increased but manageable cost increase (25%), minimal cost increase expected (50%), same cost as current (75%), decreased cost to insurance expected (100%). In this example, exclusion means that an insurance option would be immediately excluded which can, with reasonable certainty, be expected to lead to massive financial impact to a degree which may bankrupt the insurance. Another example of a proposed scoring is the criterion of “equity” with the possible outcomes of “high degree of HC differences within population” (0%), “limited improvement of HC equity” (25%), “(limited) improvement of HC equity” (50%), “HC equity is mostly satisfied” (75%), “HC is the same for everybody” (100%).
Except for the score “exclusion,” all scores are expressed in percentages. This method provides for a normalization within the scoring system even if each score does not have the same number of scoring levels. This also allows for differentiation between the importance of the possible outcomes. The final score for each criterion will be calculated from the score (in percentage) and the maximum score achievable by this criterion (described in Section 2.3).
The interactive stakeholder workshop took place in Beijing, China, on September 14, 2018 under the leadership of Professor Shanlian Hu (Fudan University). The agenda started with introductory presentations on the policy changes which triggered the initiative. The view on the initiative from different perspectives (e.g., academic, policy, industry) was presented through a moderated discussion of participants’ expectations and viewpoints on upcoming changes and the expected improvements in health insurance schemes. This was followed by an interactive component to develop a common general decision model following a validated MCDA calculation model and process for local adaptation [30, 35]. This portion of the workshop was moderated by two international health-policy advisors.
Because the workshop facilitators spoke English, the entire workshop was supported by simultaneous translation to ensure involvement, understanding, and contribution of all participants. All materials were made available in the both languages.
The flow of the interactive part of the workshop is depicted in Figure 3.
Six-step process for developing the MCDA tool in a workshop with key decision-makers for prioritizing insurance policy options in China.
Each insurance representative had the opportunity to address shortcomings of the current system and their expectations for an improved insurance scheme. The key statements resulting from this discussion are summarized in Table 1. These shortcomings and expectations were well aligned with those proposed by the core team during the workshop preparation. Overall, there was high concordance among the participants.
Finally, participants shared a common voice that the workshop would yield a tool to choose the most rational insurance system to meet the needs of their provincial environments, while still maintaining national consistency.
Each domain and their related preliminary criteria were presented and discussed with workshop participants. The participants confirmed the relevance of all proposed domains and criteria except under the domain funding and finance. The criterion “mobilization of funding for outpatient HC” was dropped as participants stated that concept was covered by the “financial impact for insurance” criterion. Thus, these 2 criteria were merged into one and that resulted in 10 criteria across 5 domains as listed in Table 2.
The proposed scoring for all criteria was reviewed and general agreement was reached that the scoring should systematically apply the same number, levels, and results of possible scores. A consistent five-level scoring for each criterion was developed, whereby the first criterion would always result in exclusion of that insurance option. The scoring is defined in Table 3.
Outcomes definitions and scoring for each decision criterion.
A multicriteria decision analysis was demonstrated in Excel (Microsoft™). Although the model was programmed before the workshop based on the predefined domains, criteria, and scoring, there was continuous adaptation throughout the workshop to reflect the input of the participants. The final model integrated all results from the workshop.
Once agreement had been reached on the domains, criteria, and scoring functions, the participants were guided through the process of ranking the criteria and subsequently weighing them for their relative importance.
This involved an anonymous voting with an audience response system (Ombea® with OMBEA ResponsePad™) for defining the decision priorities among the list of 10 criteria (step 4 in Figure 3) and the relative importance of each of the criteria in the overall decision (step 5 in Figure 3) following the modified simple multiattribute rating technique (SMART) method for ranking and swing weighing of the criteria [29]. For each vote, the result was computed as a median value. The resulting model was tested and reviewed using two test cases (step 6).
The first step in validating a decision model is testing the model with either known or extreme alternatives. During the workshop, there was limited time for testing; therefore, we will present two high-level insurance policy options to compare using the resulting model from the workshop.
A concern raised during the introduction was that the insurance funds allocated to medical savings accounts (MSAs) are not used efficiently. Therefore, a key component of health-care reform should include a more effective use of MSA funding.
The goals of a future reform would be to (1) increase the population solidarity and foster a more rational use of medical insurance premiums both from the perspective of the employee and the employer and thus (2) increase the efficiency of how the funds are utilized. In addition, the new policies should support key government (national) health-care policy priorities such as (3) a shift health-care utilization from tertiary to primary care services, and thus (4) incentivize earlier use of health-care services instead of delaying until more expensive inpatient services are required (timely interventions).
The scope of payment for personal MSAs would be expanded to include additional services such as deductible (user fees) of hospitalization medical expenses, or for the medical expenses of other family members, paying the premiums of commercial medical insurance participation. Thus, insured employees would have more options for MSA spending and would still make individual decisions on when and how the money would be spent. This option would not provide an incentive to increase the use of outpatient care.
A pooled outpatient funding system for the urban employees’ medical insurance would be established, similar to how current inpatient service is funded. This would create a gradual transition of payments into the coordinated population fund instead of the MSA and ultimately absorb the remaining funds in current MSAs. In this option, the decision on funding allocation would be made by the insurance authority or government across the entire insured population for both outpatient and inpatient care. Proactive funding of outpatient care would be intended to decrease inpatient care down the road.
Four members of the project team and two additional Chinese health-care experts used the MCDA model to independently rate the two insurance policy options. Their answers were evaluated using the following rules:
If three or four of the raters answered identically, this was taken as the result for that attribute;
If the answers were distributed, the median result was used;
If the median was between two scores, the answers from the Chinese respondents were given a higher weight;
If the result was between two scores, the more conservative response was chosen.
Following this approach, insurance option 2 was rated with a total of 78.0 points as the superior policy as compared to insurance option 1 with a total of 53.95 points. The detailed results are shown in Table 4. Insurance option 1 scored better for the attributes relating to “financial impact and funding for the insurance,” “access to pharmaceuticals,” coverage for outpatient healthcare, “affordability/economic burden to patients,” “timely interventions,” “primary care utilization,” “solidarity,” and “equity.” In the final two attributes “ease of transition” and “acceptability to stakeholders,” insurance option 1 was rated higher.
Scoring of option 1 and option 2 in the MCDA model for the comparison of insurance models in China as rated by six test persons (four Chinese, two international).
This example shows that there is a trade-off in any decision-making process—in this case between the domain “likelihood of change” where option 1 scored higher and for the other four domains, where option 2 scored higher. The model highlighted these trade-offs and made them more transparent. Once policy-makers agree on their final decisions, they are also more aware of what resistance may be expected and therefore may be better prepared to consider preventive measures to minimize such resistance.
The intention of model testing was to understand (A) ease of use of the model for those using the model and (B) to see how consistent the answers are between different users.
To answer the first question, the users were specifically asked about their experience. The model was rated to be very easy (1) or easy (2) and neutral by two raters.
The interrater consistency varied depending on both the attributes and the insurance option. For most questions, there was a clear preference for one score. The highest response variability was observed for option 1 in relation to “financial impact and funding for insurance,” “primary care utilization,” “ease of transition,” and “acceptability to stakeholders.” The responses for option 2 had less variability.
In order to improve the interrater variability, two improvements were suggested: (1) provide the raters with a more detailed description of the meaning of an attribute and a score and (2) provide more a more detailed description of the two insurance models. An additional step of deliberation where a discussion could be led between the raters could give the rational for their individual ratings and consensus could be developed in the process. The latter approach would help to improve the cross-rater understanding as a part of the implementation and training process and enhance the consistent use of the model over time.
Two raters proposed to reduce the numbers of criteria for some of the options, because it may be difficult to determine the exact response if the gradual differences between the possible answers become too small.
We would propose when applying this model to a decision problem the interrater variability should be monitored throughout the introduction phases. The results of these evaluations will help to improve the model over time.
Before releasing the model to provincial insurers, further pilot testing would be recommended. Ideally, a selected group of insurance experts would be asked to use the model in the assessment of their own insurance options and, in parallel, the two “standard” options as described above.
After the evaluation, the pilot users should be interviewed for their experience in the process and suggestions for improvement. This feedback could be used for building a next version tool, which could then be presented to the State Medical Insurance Bureau and released to a broader user group. In addition, guidance and training material should be developed to support interrater consistency in the application of the model. Dissemination could happen via various channels such as the State Medical Insurance Bureau or presentations and workshops at provincial or national conferences where insurance policy experts come together.
As mentioned above, the use of the model should be accompanied by an ongoing collection for user feedback (e.g., in an online survey format) and regular revision of the tool for further adaptation to new application requirements.
At the end of the first workshop, participants found high value in the MCDA approach toward building a criteria-based decision tool. In particular, they appreciated the experience with the MCDA methodological approach which can be applied to decisions in technology assessment based on predefined requirements.
Yu et al. warned in a recent publication that “if supply-induced demand is not effectively controlled, a universal and uniform social health insurance may be more harmful than beneficial in China” [36]. By substituting the existing fee-for-service design with bundled provider payment policies, there can be more integrated approaches for smaller population groups that exist in China [37]. However, this is only possible, if allocation of funds for outpatient services is made by health-care decision-makers, guided by considerations of equity, access, and efficiency in public healthcare. Tools such as MCDA will improve transparency and consistency in health-care decision-making. Although the decision on the future UEBMI policy will be made on a provincial level, the evaluation tool will assist the decision-makers to go through a set of rational decision considerations (criteria) before selecting the most appropriate option. A consensus process, validated through a pilot testing phase, will provide a high level of legitimacy to the decision-making process.
UEBMI is the insurance system for urban employees. The other insurance options for urban residents (URBMI) or for rural citizens (NRCMS) could use similar tools for further developing their insurance options or to design a merged insurance policy [38]. However, it should be noted that the three systems vary in terms of financing mechanisms, funding extent, and coverage policies and would require a full adaptation of the model. In addition, the stakeholders involved in the process might differ. For example, consumers or patients could be included as important stakeholders, because URBMI and NRCMS are voluntary systems and not mandatory by employment.
The described methodology could also be transferable to other types of decisions in China, such as which products should be listed or reimbursed, or which of the available alternatives should be purchased [30]. Such an application is presented in another chapter of this book at the example of purchasing off-patent pharmaceuticals in hospitals in Thailand [39]. However, successful adaptation of the methodology for each new type of application requires a thorough process described in Figure 1 of this report, including preparation, involvement of the decision stakeholders, and phased implementation [33].
Many countries moving toward Universal Healthcare Coverage are building up their health-care systems and coverage policies. They will face similar decisions throughout this process. Although the instrument described here has been developed for the needs of the Chinese stakeholders in the context of the current insurance policies, the process and the principles can be transferred to other countries. This structured and transparent approach for planning and implementation can provide learnings for improvement of health-care insurance policies.
By using a structured and previously validated process for developing a decision support tool [33], we were able to work with key stakeholders from several provinces in China during a 1-day workshop to apply the tool to a decision problem. The resulting MCDA spreadsheet model can be used by UEBMI insurance policy-makers in the provinces of China to compare new options of insurance policies.
A few key components in the process are essential for successful implementation. The most important is the engagement of the stakeholders impacted by the decision. Through the engagement of all stakeholders, a variety of factors can be considered and an open exchange is possible through a workshop format to incorporate all perspectives [40]. In addition, stakeholders, who are part of the “inner circle,” or the guiding coalition, can further to convey the momentum for change. This becomes of utmost importance once full implementation is realized [37, 40, 41]. In our example, the decision to limit the stakeholders to insurance experts and academic health policy leaders was purposeful to reflect the current decision-makers. However, a broader range of stakeholders may be involved in the testing phase of individuals’ provinces or countries.
Another key success factor is to clearly define the decision problem at the outset of the stakeholder collaboration. If there is a general agreement on the objective of the new policy, and on the criteria, which help to measure whether the objectives can be achieved, the MCDA tool offers an opportunity for increasing transparency of the decision process. Increased transparency may also contribute to a higher trust in the policies by the public in China [42].
The participants in the workshop cautioned that it may be necessary to adapt such a model in their respective provinces to address provincial health-care priorities, which may differ from province to province. A practical implication was use of the domains and criteria as a checklist for the design of new insurance policy options.
Finally, for the long-term success of any future policy change, measurement of outcomes is important. The criteria used in the selection process could become key performance indicators around population health and economics as used in other evaluations [2, 5, 43].
Some limitations or pitfalls of using MCDA as a decision support tool need to be considered. First, there is a risk of bias in the MCDA when the criteria overlap and therefore overemphasize certain aspects of the evaluation. In our example, the participants felt this to be the case with the two finance-related criteria which were originally proposed. They, therefore, decided to merge the two criteria into one. Second, the ranking and weighing methodologies can have a high impact on the “resolution” capability of the decision support tool. In this chapter, we have used a modified SMART approach to MCDA which has been recognized broadly as practicable [23, 39]. It should also be emphasized that decision-makers may be tempted to use the summary score as “the decision argument.” Instead, decision-makers should deliberate and compare the entire rating profile to confirm, that the instrument and the summary score have validity in the specific comparison. This will allow a more differentiated argumentation and documentation why a specific decision has been taken and which preventive measures should be taken to overcome the areas of weaknesses of the chosen option, which are those criteria, where it scored low.
There are also a few limitations to our proposed process. In our workshop, only a limited number of stakeholders were represented. Future programs should aim to achieve a good balance between all relevant stakeholders to maintain an active dialog during the workshop and manage the number of participants to avoid limitation of discussion. Preparation through stakeholder research, including mapping and assessment of appointments, is important to strike this balance.
Another limitation was the need to work with translators during the entire process, which was due to the international composition of the project management and moderating team. To minimize the risk for misunderstanding, the workshop was simultaneously translated and all materials, including the model, were available in both English and Chinese language.
In this report, we have demonstrated how an internationally developed and validated process based on MCDA methods was adapted to decide which funding model should be selected for the future UEBMI insurance policy in the provinces of China. The processes included extensive stakeholder analysis and engagement as well as an interactive workshop for building consensus on objectives of the reforms, the criteria for success, and the measures for scoring such criteria.
The advantage of combining stakeholder driven cocreation with the principles of multicriteria decision analysis was to build a model with the input and final consensus of key stakeholders that still allows for local adaptation of criteria, weighing, and scoring. Using such a structured decision model fosters consistency and transparency across all decisions and allows for documentation of the decision process and evaluation of the impact.
We would like to end this report with a specific concluding comment of one of the workshop participants: “It is hard to predict the future; but using a rational method to approximate the future needs for insurance models will help me to convince my constituents.”
This initiative has been funded by Abbott Products Operations AG in Switzerland: DB received funding for moderating the workshop and for the travel expenses; APH received funding for planning and facilitating the workshop and for writing the manuscript. The open access fees for the book chapter were also paid by the company.
HC | healthcare |
HTA | health technology assessment |
ISPOR | International Society of Pharmacoeconomics and Outcomes Research |
MCDA | multicriteria decision analysis |
MSA | medical saving accounts |
NRCMS | new rural cooperative medical scheme |
OPP | out-of-pocket costs |
RMB | Renminbi, Yuán (currency of the People’s Republic of China) |
UEBMI | urban employee basic medical insurance |
UMIS | universal medical insurance system |
URBMI | urban resident basic medical insurance |
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