Health Service Business Design
Real cases of health services Business Design, based on the foundations presented in the previous chapter are the subject of this section. They illustrate how, having a clear Strategy and Business Model, a Business Pattern that provides a first approximation to a Business Design model can be selected and specialized to make positioning and value to clients operational, following the methodology of Chapter 2.
Service Innovation in a Private Hospital
First, we present the case of a private hospital, one of the largest in Chile and considered among the best in Latin America, summarized in Chapter 1, which has defined the following Strategy and Business Model:1
This hospital wants to be distinguished as the one that provides the best treatments with the best required technology; so they are clearly in the line on best product positioning with an emphasis on differentiation based on continuous innovation on the services they provide.
The value they aspire to offer is to assure patients the right treatment that minimizes health risks for them at a competitive price.
Then the Capabilities this hospital needs are (a) the possibility to evaluate the performance of the several Value Streams that provide services to patients, (b) to identify opportunities for improvement of the medical procedures and introduction of new technology—for example, a new imaging equipment or a robot to perform surgeries—that make a difference for the patient, (c) to be able to formalize all these opportunities as formal investment project and rigorously evaluate them to determine the ones to execute subject to budget limitations, and (d) design, plan, and execute the selected projects that create or modify the corresponding streams, which implement the new ideas. Of the variables defined in the section “Competitive Strategy and Business Model for Health Care Services” of Chapter 2, we concentrate on quality, with the possibility of also introducing the ideas of Porter and Teisberg, and Christensen et al. to gain competitive advantages. This can be done by identifying niches such as chronic diseases—for example, diabetes and hypertension—where models for predicting patient risks are possible to develop for generating preventive actions that increase the value defined by Porter and Teisberg, and generate simpler, lower-cost treatments for less complex diseases as proposed by Christensen et al.; for example, treating patients at their home, as it will be exemplified for a public hospital case in this chapter. In improving quality, as just outlined, also efficiency is to be dealt with to assure costs that make competitive pricing possible. In doing all this the opportunity exists to use formal Analytics to forecast needs, evaluate investment projects and plan them; then the Intelligence Structure II applies. Notice that some of the innovations imply change in the medical practices, which means we are redesigning the service itself and its production processes. All this clearly points to Business Pattern 5 (BP5), “Product innovation,” presented in Chapter 2.
The situation in the hospital before the reported design was that ideas and projects were informally defined and presented in an annual budgetary procedure to the Board, which decided on which projects to execute without any formal evaluation.
The specialized BP5, shown in Figure 3.1, defines a first Business Design, establishing requirements for new business components as follows:
“Service performance and use analysis” implies the need of learning how to evaluate services based on observation and analysis of the use and performance characteristics of the current services, which can be supported by Analytics on well-structured data.
“Design of improved or new service” requires to set processes that take results from (1) and discover opportunities for service innovation, which can go from improving medical practices that are not producing good results or introducing new practices, due to medical or technological advances, to completely new treatments for old or new pathologies, which may generate new Value Streams. This requires the ability to formally perform what we have called “design of the service itself,” which is similar to the product engineering that traditional manufacturing does with well-known practices. The difference here is that services in general and health in particular do not have well-defined processes to do this and service design in the result of experience and tradition. This has the added complexity that health services are always changing because of scientific and technological advances and that, in many cases, health services cannot be designed in advance in terms of the set of specific treatments a patient will need and this has to be determined for the particular situation. So the challenge is to have a process that continuously generates health services that provide innovation and the possibility of dynamic adaptation to the particular patients’ needs.
“Design of improved of new Value Stream” is the design of the service production and it is similar to the production process in manufacturing, but with the complications we identified in (2), in that the service needs adaptation in its production for each patient; this requires well-defined processes that include the design of the detail flow of the service, from the arrival of the patient to conclusion of its treatment, and all the management of the operations of the service, including demand management, scheduling of patients, resource assignment, and flow monitoring.
Figure 3.1 Business Design for the private hospital case
The design that allows making the previous operational requirements will be detailed in the next chapter by defining an architecture and configuration that makes its implementation possible.
Resource Assignment in the Public Sector
Next, we focus on public health Business Design, where an overall analysis for the public health system in Chile is performed and a design developed to promote a coordinated solution for innovation resource assignment. This case illustrates a situation of a complex multilevel architecture, mentioned before.
Public hospitals have to usually cope with more demand than their capacity allows, generating waiting lists of patients who cannot be attended immediately; hence they need to optimize the use of such capacity and must have means to manage priorities, which means efficiency and fairness. In doing this, one of the best possibilities of improvement is to modify the logic behind the decision on the resources hospitals receive. The idea is assigning resources in a way that promotes efficiency and, at the same time, improves quality.
The state of the health system in Chile in connection with resource allocation oriented to improve efficiency and fairness of the hospital services is as follows:
For the improvement of the efficiency, the current method of resource assignment to hospitals is primarily historical and includes important distortions related to demand. It is based on the idea of “management by commitments,” which are basically goals measured in quantity of medical interventions of different types that the hospital promises to execute to receive a certain amount of resources in any given year. This method fails on several accounts: (a) failure to set goals that consider the true capacity of the hospitals, (b) within a given type of medical interventions the easier cases are selected to formally meet the goals, (c) there is no measure of quality of the intervention, and (d) no incentive to do more than the goal; in fact, there is a disincentive, since more production than the goal means a higher goal for the following year. Obviously, there is no guarantee that a hospital operates at the “right” efficiency level, according to the resources they have. Furthermore, the objectives of fairness and quality are negatively affected because of selection of patients with no priority, but less difficult to treat.
For the improvement of fairness, the processes and practices that currently govern the management of waiting lists should be reformulated; it is necessary to change from attention according to order of arrival to one that ensures the timely delivery of the service, considering formal and objective medical criteria. It is also important to discourage the selection of cost-effective hospital treatments, which implies selection of patients that are easier to treat, by transferring the complex cases to other higher-level hospitals; this increases the count to the goals explained earlier with lower costs, but increases the costs of transportation of patients in complex conditions, owing to nonpayment of the hospital transferring the patients.
We now analyze how hospitals should be managed as a system, particularly in the assignment of resources, to avoid the situations reviewed earlier.
From a strategic point of view, they should follow the positioning of best product and operational effectiveness, as defined by Porter and complemented by Hax and Wilde. This Strategy requires evaluating services provided and improving them to provide better quality as well as use the resources in the best possible way to provide such services at the lowest possible cost (efficiency). As for the Business Model, they should provide value to patients (customers) by executing medical services and management processes in such a way as to guaranty the treatments that patients need with the required quality and at the right time (quality and fairness). Here the ideas of Porter and Teisberg2 and Christensen et al.3 can be considered to provide the right value and adapt practices to disease complexity.
Thus, the Capabilities that hospitals need, according to the preceding Strategy and Business Model, are to be able to measure current efficiency and quality levels to assign resource in such a way that there is an incentive for the hospitals to improve. This means using Analytics of the Data Envelopment Analysis (DEA) type, summarized in Chapter 2, to rigorously measure efficiency and determine what improvements are necessary to increase it. So Intelligence Structure II is needed. This combined with the level i of design we are performing, means that the Business Pattern 3 (BP3), “Internal Learning for Process Improvements” applies. BP3 provides the Capabilities to improve efficiency of health services that produce better quality and fairness to patients. It is also correlated with the proposals by Porter and Teisberg and Christensen et al., since the Capability to innovate on health services provided by this pattern is at the heart of changing medical and management practices that contribute to minimize the cost of the health outcomes and adapting them according to the level of complexity. A specialization of BP3 to this case is shown in Figure 3.2.
Figure 3.2 Specialized BP3 for health system resource assignment
The model in Figure 3.2 defines the new components the health system needs to continuously innovate by assigning resources where the best possibilities are of increasing efficiency, with adequate consideration of quality. Requirements are:
“Value Chain activity and performance analysis” implies the need of learning how to measure health services efficiency based on observation of the performance of the current services, which can be supported by Analytics on well-structured data.
“Design of changes in Value Chain” requires to set processes that take results from (1) and discover opportunities for service innovation, which are oriented by the results, since adequate Analytics should indicate which variables explain current efficiency and which changes on them would increase it; for example, patient scheduling practices and resource management that assure its good use. This requires the ability to formally perform what we have called “design of the service itself.” This is particularly difficult in health services that do not have well-defined processes to do this and service design is the result of experience and tradition. This has the added complexity that health services cannot be designed in advance in terms of the set of specific treatments a patient will need and this has to be determined for its particular situation. So the challenge is to have a process that continuously generates health services that provide innovation and the possibility of dynamic adaptation to particular patients’ needs. This must be complemented with the design of the service flow and its management to assure that health care is efficiently delivered and with proper effectiveness.
This design centralizes resource assignment and project definition on the idea of agency theory that this is the only way to assure that principal’s interests are taken care of; also there are economies of scale in defining improvements on the Value Chains of several hospitals by sharing their experiences, formally considered in the comparative efficiency measurements that DEA performs as will be illustrated in Chapter 4. But improvement projects’ execution is decentralized also following agency theory4 in that opportunity costs are reduced, since agents have better knowledge of implementation details. Another theory that supports the decentralization approach is complexity in layered systems, which argues that for such systems, in particular health, there are advantages in such a solution.5
Design in a Public Health Network
As presented in Chapter 2, we consider the case of the Public Chile Health Network and, in particular, the operational management of a geographically defined subnetwork, which is a grouping of hospitals and primary health services that are located in a given region and, in the case of a big city, covers sectors of the same. The key design decision in this case is the degree of management decentralization, since there are three hierarchical levels: overall health system and subnetwork management, and the operating units—primary health and hospitals—that provide the health services. In principle the management of the system is decentralized, since most of the hospitals are defined as self-managed units and primary health services are run by counties. But there are still many coordination issues that need to be centralized, such as referrals among units within a subnetwork and among subnetworks; management of waiting lists; and share of scarce resources such as beds. We will not go into these coordination issues but center on how to make possible that the units’ performance is maximized. The current solution to accomplish this objective is “management by commitments,” where health system central management negotiates with a sub-network and its component units production targets and an associated operating budget; hence a unit commits a given production in accordance with the budget. This practice has two problems: there is no way to calculate the right performance, with optimum use of resources, and no well-founded method to determine the correct budget. We have proposed a structural solution to this problem based on hospitals’ efficiency measurement by means of DEA and budget assignment based on this, which was presented in the previous case and will be detailed in Chapter 4. Here we consider the situation of subnetwork central management, where the short-term operations management is analyzed. The problem is then to design a business structure, assigning roles to the different management levels, such that the idea of decentralization is maintained, but that, as agency theory studies, the principal’s interests expressed by means of commitments are met by the operating units; we also consider a decentralization approach, since as mentioned in previous case, complexity in layered systems supports this idea. Then we focus on what should be the role of sub-network management and, in particular, its responsibility in operations management.
First we define the strategic positioning, which is best product with emphasis on efficiency as discussed in the previous case. As to Business Model, the idea is to provide value to users by executing medical services and management processes in such a way as to guaranty the treatments that patients need with the required quality and at the right time (quality and fairness). Then the Capabilities needed are to be able to generate good information on the performance of the hospitals’ Value Chains; process such information with the proper Analytics, determining opportunities for efficiency improvements; and design improvements in Value Chains according to such opportunities.
Previous analysis implies that the Intelligence Structure II is the one applicable in this case and this, as a consequence, determines that the Business Pattern that should be used is “Internal Learning for Process Improvements,” BP3. This pattern is thus specialized to this case, resulting in the design in Figure 3.3. This design implies requirements as follows:
“Value Chain activity and performance analysis” implies the need of learning how to measure health services and be able to generate good information on the performance of the hospitals’ Value Chains, such as commitments satisfaction, resources available and degree of use, waiting lists, complaints, and the like, which can be supported by Analytics on well-structured data.
“Design of improvements in Value Chain” requires to set processes that take results from (1) and discover opportunities for service improvements, which are oriented by the results, since adequate Analytics should indicate which parts of the Value Chains need better practices to assure good resource use or provide better service; for example, best practices for demand prediction and capacity planning, using simulation, for surgeries to reduce excessive waiting lists; analyses of users’ formal complaints to identify opportunities for process improvements leading to eliminate such complains; and human-resource planning for emergency services according to forecasted demand to improve service. So the challenge is to have a process that continuously generates process improvements on the hospitals’ Value Chains that provide innovation and the possibility of dynamic adaptation to the particular patients’ needs. Also there is the need to create processes that implement the changes in such chains.
Figure 3.3 Business Design for subnetwork improvement management
We worked on this design with one subnetwork in Chile and found many opportunities for improvement that were discovered, designed, and implemented by the subnetwork management, in collaboration with the hospitals. We found that this is the right place to do this since analyses can be made with data from several hospitals, comparing situations and developing solutions that can be used in several of them; practices that have worked well in one hospital can be disseminated to others; and hospitals do not have the resources to rigorously do this innovation by design. This is also supported by the agency and complexity theory in layered systems analysis in the same way as in the previous case. So the architecture design shown in Figure 2.12 of Chapter 2 is justified as well by the analysis we have just performed.
Design of Emergency Service
This case corresponds to the emergency service of a University hospital. It was motivated by a serious quality of service problem, whose worst effect was service denial to patients because of extreme congestion, including closing the doors of emergency facilities. The positioning strategy must then be best product with emphasis on quality differentiation or improvement, but efficiency should also be considered due to the high costs and large deficit the hospital has. So the Business Model should be to generate value for patients with on-time services, according to the severity of their condition, without loss of quality in the health service itself, and making a good use of resources.
The Capabilities this hospital needs, for the aforementioned purposes, are to be able to predict emergency demand; transform this demand on requirements of different resources, such as nurses, doctors, boxes, beds, and others; and continuously adapt resource capacity to provide a response time to patients according to their needs. So Intelligence Structure II is the relevant to model demand and assign resources optimally; hence the Business Pattern that applies is BP3, “Internal Learning for Process Improvements.” This pattern is thus specialized to this case, resulting in the design in Figure 3.4. This design implies requirements as follows:
“Emergency Value Stream activity analysis” implies the need of learning how to predict emergency services demand and be able to generate good information, which can be supported by Analytics on well-structured activity history; also resource use should be analyzed to determine how to convert demand on resource requirements; and information on delays processed to determine where in the Value Stream are the most acute problems.
“Design of improvements in Value Stream” requires to set processes that take results from (1) and design service improvements, which are oriented by the results, since adequate Analytics should indicate which parts of the Value Stream need better practices to assure good resource use or provide better service; for example, emergency extreme congestion prediction to prevent closing; best practices for capacity planning based on demand models, using simulation, to reduce excessive waiting time; and continuous monitoring of service flow to detects congestion problems in advance to improve service and also detect unnecessary delays, for example, on medical exams, to speed up patients and make a better use of facilities. So the challenge is to have a process that generates improvements on the hospitals’ emergency Value Stream. Also there is the need of to create processes that implement the changes in such chain.
Work was successfully done by implementing innovation processes that redesigned the Value Stream and continuously monitors online its performance to discover problems that need to be dealt with, producing immediate improvements in service, including avoiding closing.
Figure 3.4 Business Design for emergency service improvement
Design of Services for Patients at Home in a Public Children Hospital
Now we present the case of a children’s hospital which has chronic patients with respiratory problems that need permanent monitoring, spending most of their time at the hospital using beads, which is a very scarce resource. So the challenge was to perform a Business Design that provides a solution for keeping the children at their homes with the proper attention that assures their well-being. So this hospital wanted to evolve to personalized added valued services according to the following Strategy and Business Model.
The Strategy is to deliver integral services for children at home and use the hospital only for emergencies. The Business Model is to provide value through new services that allow to diagnosis the children at home and then provide adequate care that can be given there; also to detect crisis that require treatment by hospital professionals; all this to be executed by a new service line under design. This means that hospital has to generate the following Capabilities:
Be able to structure a solution to collect patient data at his or her home and discover, by means of Analytics, predictive models for children that alert the hospital of health problems.
From behavior results, go on to determine the right actions when crisis are forecasted and carry on with such actions.
Finally, create and maintain the necessary Value Stream to put into practice the attention at home, which today does not exist.
To provide these Capabilities the Intelligent Structure IV is needed, since not only the normal patient data is relevant, but continuous data coming from instruments at the patients’ home, in the idea of Internet of Things (IoT), are needed, which is big data. By combining the design level i, the Intelligent Structure IV, and the emphasis of this case in a new business line that necessarily will need a new Value Stream, the right Business Pattern is BP2, “Creation of new streams of service”; hence, this pattern can be specialized to this case as shown in Figure 3.5.
Figure 3.5 Service design for patients attended at home
The specialized BP2 requires the following components to be designed in detail:
“Build transaction Data mart and develop models,” which determine the variables to be monitored, transfer it to a Data mart to build predictive models for patients’ crisis, and make data available for model operation.
“Design criteria for at home services” uses predictive models to define criteria for advising medical professionals on actions to be taken, who decide on and execute such actions.
“Design of improved or new Value Stream” including design and development of new evaluation processes, software support, human resources provision, and other resources needed—to put into practice the attention at home, which today do not exist.
“Definition of patients with access to service,” which determines the chronic patients in the hospital that are subjects for service at home.
These processes were developed including online monitoring of medical variables—such as temperature, cardiac frequency, and respiratory frequency—and a diagnosis data-based analytical model to determine when a patient is in crisis and needs medical attention. More detail for this case will be given in Chapter 6.
Design of Medical School Service Improvement
From a strategic point of view, this medical school should follow the positioning of best product and operational effectiveness, as defined by Porter and complemented by Hax and Wilde. This Strategy requires evaluating services offered and improving them to provide better quality as well as use of the resources in the best possible way, generating such services at the lowest possible cost (efficiency); this is particularly relevant for this school due to the large operational deficit it carries. As for the Business Model, they should provide value to students by providing a state of the art curriculum that gives them the right preparation for successful career; to society, medical research that advances the medical standards of the country and gives the proper foundation for teaching; and to client population the best services through an associated clinical hospital.
Thus, the Capabilities the school needs, according to the aforementioned Strategy and Business Model, are to be able to measure current efficiency and quality levels of its about 50 departments to determine which ones are not providing good academic services or do not properly use resources, or both, to take corrective actions. This means using Analytics of the DEA type to rigorously measure efficiency and quality and to determine what improvements are necessary to increase them. So Intelligence Structure II is needed.
This, combined with the level i of design we are performing, means that the BP3, “Internal Learning for Process Improvements,” applies, which provides the Capabilities to improve efficiency and quality of academic services. Then it can be specialized to this case as shown in Figure 3.6.
The model in Figure 3.6 defines the new components the medical school needs to continuously innovate where the best possibilities are of increasing efficiency, with adequate consideration of quality. Requirements are:
“School Value Streams efficiency analysis” implies the need of learning how to measure the efficiency and quality of the academic services that are provided through various Value Streams—medical undergraduate and graduate formation, research, and extension—based on observation of the performance of the current services, which can be supported by Analytics on well-structured data.
“Design of improvements in Value Chain” requires to set processes that take results from (1) and discover opportunities for service innovation, which are oriented by the results, since adequate Analytics should indicate which variables explain current efficiency and quality and which changes on them would increase it; for example, increase the faculty academic qualifications or provide better research support.
The processes necessary to satisfy the previous requirement have been designed and successfully tested in practice, showing that DEA models correctly measure efficiency and gives hard support for taking specific actions to improve departments’ performance; they are currently under implementation at the medical school.
Figure 3.6 Specialized BP3 for medical school service improvement