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A quantum leap for healthcare

Article-A quantum leap for healthcare

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Optimising patient services by ensuring adequate expertise and resources is an investment in public well-being to enrich societal stability and competitive advantage.

In 2017, the Organization for Economic Cooperation and Development (OECD) estimated that approximately 20 per cent of healthcare spending was effectively wasted in developing nations. Amplifying the issue further, the World Economic Forum Global Coalition for Value in Healthcare puts this number between 30-50 per cent globally. Wasteful spending is identified from three sources:

  • Patients harmed in the course of care delivery requiring further treatment, or provided unnecessary procedures that do not improve their outcomes
  • Care could be provided using fewer resources (via better utilisation of primary healthcare centres, generic pharmaceuticals, etc.)
  • Non-value-adding clinical services and administrative processes, as well as other losses to corruption/fraud

Waste in healthcare is twice the sin. Not only are we misusing resources; we are also adversely affecting the well-being of our population (e.g. harmful procedures, long-waiting times, high costs, and unavailability of services).

Delivering accessible, high-quality healthcare services on a national level in an economically optimal and socially responsible way requires thorough planning and continuous resource management such as specialists, facilities or equipment. This is further compounded by the complexity of resources required in healthcare compared to other industries and the lead-time required to add capacity, such as a decade to prepare a specialist or the years required to build a hospital.

Globally, and especially in the Middle East, despite the rapid professionalisation of the industry, the challenge of optimising patient services remains. Several contextual factors exacerbate it further:

  • Inadequate data healthcare planners often do not have robust and accurate data about current demand, future demand or even current capacity.
  • Misaligned incentive systems many provider organisations do not have the incentives to optimise patient services, especially those that are funded using budgets. Such funding mechanisms strip the providers from the incentive to plan adequately, to optimise demand capture, or to even ensure patient satisfaction.
  • Fragmented regulatory environment in many countries in the region, healthcare is regulated by multiple bodies with often contradicting agendas. This leads to a lack of coordination, inefficient allocation of resources and little accountability to optimise patient services.

This has led to (1) considerable waste through duplication of services; and (2) insufficient access to care in some regions, leading to costly medical transport and poor patient experience.

Clinical economics

Optimising patient services can be simplified as ‘enabling supply to meet the demand for services where and when required’. The fundamental logic of a capacity planning model is relatively simple: measure and compare the supply of resources against the demand, identify the gaps (positives or negatives), and find ways to bridge these gaps, while maintaining the quality of care. In healthcare, bridging gaps and surpluses often requires the intervention of numerous public and private stakeholders.

Healthcare resources are highly specialised and often bespoke in nature. This means the traditional approaches to capacity planning, as in infrastructure or industry, do not translate effectively — making resource definition the first critical step. Diversity of resource categories and granularity of data both dictate the need for a detailed model without it being overly complex. As Jorge Luis Borges famously illustrated via the complexity overkill in his ‘On Exactitude in Science’; “an empire where the science of cartography becomes so exact that only a map on the same scale as the empire itself will suffice”.

Economically clinical

The fundamental tenet of Value Based Health Care (VBHC) is measuring outcomes that patients experience relative to the cost of delivering those outcomes. The VBHC model rewards healthcare providers for providing quality care to patients. Under this approach, providers seek to achieve the triple aim of providing better care for patients and better health for populations at a lower cost.

For the VBHC concept to be successful, defining standardised outcomes is critical. Internationally, there exist several useful repositories (The Decision Institute, ICHOM, NHS, Sweden’s model) of medical outcomes from a rich source of disseminating experiences. Specifically, The International Consortium for Health Outcomes Measurement’s (ICHOM) co-founded by the Harvard Business School, The Boston Consulting Group, and Karolinska Institutet, works to unlock the potential of VBHC by defining global Standard Sets of outcome measures that really matter to patients for the most relevant medical conditions and by driving adoption and reporting of these measures worldwide.

The other aspect of VBHC is cost, which in turn, will be highly correlated to resource optimisation in terms of healthcare infrastructure, beds, clinical and admin teams, and equipment.

This optimisation of resources relies around four key dimensions of understanding your supply, forecasting your demand, governance, and finally developing a model, which is able to generate accurate results to drive change.

From a supply and demand perspective, key resources of a healthcare system must be accounted for, such as manpower, beds, equipment and operating rooms. Experience has shown that international benchmarking for supply and demand parameters of developed nations could be misleading for developing economies. Additionally, hospitals and primary healthcare centres serving specific population catchment areas, in particular for extended periods, often adapt to their communities’ specific needs. After a sufficient amount of time, a given hospital will have naturally tailored its services to the population it serves, or the population would have found alternate services (including reducing demand, which is detrimental). This means that when it comes to identifying the resources needed, individual hospitals are a preferable source of information, versus international benchmarks. On the other hand, for the model components that are concerned with efficient operation of a hospital, and the healthcare system as a whole, best-practice benchmarks can be more appropriate. For example, the number of biomedical technicians required with a specific skillset can be factored based on the number of machines installed, which in turn is determined by the actual utilisation of the machines based on actual admission numbers rather than on benchmarks.

Key stakeholder engagement through a robust governance mechanism is essential to ensure that model recommendations for capacity planning can be actioned. The welfare of the healthcare system as a whole must come before individual healthcare personnel needs.

Finally, there needs to be a capacity-planning model that is data-driven, accurate, yet easy to use. Such a model must inform decision makers on the existing healthcare situation as well as a reasonably precise future projection of demand, supply and gaps therein. Hence, the model has to be dynamic, with ability to show real time changes. The model should allow for scenario analysis, which will enable decision makers to plan for future healthcare scenarios such as changes to model of care, medical and technological innovations, changes in disease prevalence and incidence rates, and demographic shifts. Ultimately, the model should have the capability to support decision making on investments and strategic initiatives.

Ecosystem-level impact: National optimisation

A European country’s national hospital system is lagging behind its counterparts in terms of several key metrics, including higher hospitalisation rates, longer average lengths of stay, lower bed occupancy, poorer accessibility, etc. The national regulator decided to restructure the national hospital system to improve results. A dedicated team started with modelling and projecting the supply and demand of healthcare at the micro-regional level, benchmarked selected KPIs, and set targets to improve the system.

Based on the results of the capacity-planning model, the regulator started licensing hospitals for specialisations aligned with their population’s forecasted needs. An incentive structure was also introduced to promote investment in underserved areas and specialisations. Finally, for select specialisations, cooperation between providers was encouraged to optimise the overall network efficiency.

Ecosystem-level impact: Provider optimisation

A hospital located alongside a busy highway was originally conceived as a general hospital to serve the local community. Its proximity to the highway led it to receive an inordinate number of trauma patients involved in road-traffic accidents (RTAs). This has resulted in a diminished quality for other non-emergency patients such as long waiting times, high referral rates to other facilities, and crowded wards. All of this is driven by a noticeable “shortage” of beds, OR time, and anaesthesiologists.

The cost of adding capacity is prohibitive as there is little space for expansion. The hospital considered adapting its mission and its service portfolio — focusing on being a trauma centre. In addition to the capital costs associated with such a change, some of the local community needs will have to be offered by distant hospitals.

Before pursuing this plan, the hospital leadership wanted to explore if it would be possible to reduce RTAs (i.e. reduce supply rather than to increase capacity). An integrated capacity planning model allowed them to simulate a reduction in RTA admissions over a multi-year horizon and the impact on capacity as well as service levels to the community.

The previously perceived gaps requiring investment could be mitigated by a multi-government agency initiative to tackle RTAs. Armed with this analysis, the hospital leadership was able to change direction and engage with relevant stakeholders.

Fine-tuning the engine

Healthcare should be planned and managed like any public utility; it begins with accurate capacity planning and, more specifically, shifting the focus from adding capacity to optimising capacity and finally preventing waste. Our experience has shown estimated savings amount up to 16 per cent of annual budget across an entire healthcare system. Savings realised are through optimisation of resource allocation and trimming of surplus. These are savings that can be redirected to focus on a coordinated prevention effort. 

A healthcare capacity-planning model is critical in enabling leadership to make informed investment decisions in a dynamic market facing new technologies, shifting demographics, and changing disease patterns. It drives efficient operations and strategy execution by offering a differentiated view of the workforce and facilities. It supports the long-term management of public health by providing a platform for testing future scenarios. And perhaps most significantly, as an investment in public well-being it is an investment in a society’s stability and competitive advantage. 

References available on request.

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