A plague on health systems

A plague on health systems

Significant technical and structural inefficiencies plague the world’s health systems, but by enabling policies that ease digital health innovation and encourage investment, we can create space for integrated digital strategies that deliver better health care

The major health system challenges are a mix of technical problems, leading to fragmented non-interoperable data silos and structural problems, with different goals and mandates among the various actors.

Effective health care requires an effective flow of people, services and associated information through a streamlined sequence of processes. The digital transformation in health care promises to enhance our ability to generate, manage and use such information through information technology and big data analytics. Using the analogy of an information highway, the health informatics challenge extends beyond admitting and collecting tolls from individual vehicles to innovatively measuring traffic flow and other performance indicators. It is entirely possible for those managing the highway to share data on performance, bottlenecks, inefficiencies, design issues and the efficacy of interventions without compromising the privacy of vehicle owners. Similarly, although health data itself is private, such that unrestricted public access is not advisable, there should be no such restrictions on data about the efficiency and costs of healthcare processes. Yet there is tremendous resistance to transparency in healthcare system processes, despite the common knowledge that healthcare errors are a leading cause of adverse patient outcomes. Given the burgeoning costs and declining patient satisfaction globally, there is an urgent need to integrate, analyse and make available such information, without hiding behind the shield of health data privacy.

An ideal system

An ideal digital health data system should operate at a national scale, mapped to other relevant data such that there can be seamless cross-indexing and inferencing. For example, one could map geo-tagged environmental data such as air or water pollution with population-level health patterns to understand environmental health risks. We have seen important examples of globally important health insights from countries with highly connected national health systems, such as the United Kingdom or Israel. During the initial rollout of Covid-19 vaccines in Israel, the availability of digital data covering most of the population allowed rapid estimates for vaccine efficacy in preventing infections or hospitalisation. In the UK, national health data coupled with SARS-CoV2 genomic surveillance data led to precise estimates of infectivity, virulence and vaccine evasion properties of variants.

Unfortunately, in most instances, data comes in non-interoperable formats, whether in high-income or low- or middle-income countries. This is often by design, either to maintain data hegemony or to increase the dependence of existing clients on solution providers and vendors. This well-known problem needs to be regulated at the national policy level by specifying essential interoperable standards for all important data. Once such standards are in place, it is relatively easy to develop open-source common data model tools that permit federated learning across multiple data. The CDM movement is more difficult in some first-mover countries such as the United States, where health data is already large and heavily fragmented. Second movers, such as India, which underwent a digital transformation in the social and financial spheres before addressing health, have the advantage of being able to create a common national digital strategy that brings together national identification, universal payment interfaces, health insurance, health services, data standards and regulations.

Additional efforts will be needed to overcome structural challenges within a mixed healthcare delivery system. Health is an unalienable right, and a strong public system must exist to meet health needs. However, there must also be encouragement for private investments in health systems to promote innovation and technological advance. From the digital and data perspectives, this demands balancing the needs of individuals, society, entrepreneurs and investors. An ideal ecosystem would integrate both the public and private sectors, with optimisation of public spending in a sector-agnostic fashion with the goal of maximising societal benefit. This requires trust – and the best way to engender such trust is probably a verifiable digital data flow, with adequate safeguards against tampering or misuse.

Overcoming fragmentation

The digital transformation of India is expected to transform health care through such a trusted digital data flow. Its national digital strategy contains an insurance component (Ayushman Bharat) that supports in-patient care at participating private health organisations for all poor and vulnerable families. A verifiable end-to-end digital framework is expected to transparently integrate previously fragmented aspects, ranging from eligibility assessment of beneficiaries to reimbursements to health service providers. Public support for private health care will supplement the limited capacity of public institutions, while also creating viability for private investment in advanced health care. Digital workflows and data informatics are expected to increase efficiency and insights, especially after integration of expanded wellness and preventive care services under the national digital health mission. The use of associated data for the common good, with minimal individual risk, is the subject of forthcoming digital privacy legislation. Planning well is half the battle and this is a good start.

Major technical and structural inefficiencies plague health systems, limiting the benefits of digital transformation. Enabling policies that ease digital health innovation and promote investments, without compromising on fundamental public values, are needed to ensure desired health futures.