A conceptual framework is used to present the linkage between variables; thus, it requires diagrams that clearly illustrate cause-and-effect relationships. It promotes use of relevant research objectives and selection of an effective research approach that improves the validity, reliability and usability of findings. Researchers therefore consider it important to construct a conceptual framework before gathering data for both qualitative and quantitative studies (Rahmani et al, 2021).

In this section, the author examines some key impediments to the conceptualization and operationalization of care management and health innovation, specifically the setbacks to integrating digital health (DH) at the PHC level. The analysis requires an understanding of the concept of fit—both horizontal and vertical fit—in order to properly explore the health innovation ecosystem in developing economies like Nigeria as well as assess the existing health management strategies that have been the focal points of this paper. More than 95% of health workers agree that healthcare management determines the performance of healthcare organizations and the future of global health systems. But the key to achieving efficiency under value-based care models lies in moderate and critical use of strategic approach to risk stratification (Eggli and Halfon, 2003; Zaadoud et al, 2020).

Every health care model—including the Beveridge, Bismarck, national health insurance (NHI), and out-of-pocket models—is presumably linked to some type of value-based care (VBC) payment structure established to provide cost control and positive health outcomes. Innovation-driven healthcare management thus takes different forms such as drug therapies, surgical procedures, devices and tests, including some proven effective models for training health workers, sensitizing patients, empowering health administrators, and enhancing care delivery. But while ‘health innovation’ is widely perceived as a positive concept with favourable outcomes for both patients and health organizations, the term ‘innovative management’ usually attracts resentment from a large number of care users, especially in Nigeria due to low performance in service quality dimensions—e.g. (a) empathy (b) culture (c) priority (d) affordability (e) accessibility (f) communication etc. These variables with high impact on patient satisfaction are not common in Nigeria’s PHC system.

Rather, stakeholders in the health innovation ecosystem—mainly healthcare organizations, doctors and nurses—are addressing operational and concept-related issues arising from modern-day healthcare management theories and strategies. For example, the relevance of innovation in healthcare is widely argued because some new practices gain rapid uptake and diffusion in the global health system even when they have unproven efficacy and limited benefits as well as pose unnecessary risks to patients. On the contrary, some high-impact innovations capable of improving health outcomes for patients are hardly approved by government agencies for use in hospitals and care homes (Gupta et al, 2015). Thus, the three major areas in healthcare management are:

• Policies and Programs
• Health factors, and
• Health outcomes.

Figure A: Conceptual Framework for the Study

Source: The Author (2022)

Theoretical Outline:

The key areas of healthcare management stated under strategies in Figure A are further categorized as follows: (a) Span health behaviours (e.g., smoking, diet and exercise, alcohol and drug addiction etc) (b)     Clinical Care (e.g., access to healthcare services and improved quality of care) (c) Social and economic factors (e.g., education, income, and family and social support) (d)     Physical environment (e.g., air and water quality and housing and transportation).

Further, the Attribution, Utilitarian and Evidence-based Management theories in healthcare as well as the models of care (Beveridge, Bismarck, NHI and Out-of-Pocket) emphasize improvement in the quality of life and extension of people’s life span as the core objective of health management. Based on the HM concept, the key health management strategies are as follows:

Figure B: Health Management Strategies

Source: The Author (2022)

Evidence-based research indicates that rapid diffusion of innovation in healthcare is largely buoyed by profit-seeking behaviour. Some health organizations have been commercialized—with support from governments—to the point of repackaging cheap treatments as expensive ones for new markets and inventing ‘diseases’ such as ‘social anxiety disorder.’ An example is the use of Avastin (a cheap drug for treating colon cancer) as an expensive cure for macular degeneration. There have been arguments on the introduction of new and expensive health technologies that provide insignificant advantages when compared to existing treatments. Therefore, digital health technologies should do more than comply with basic safety standards by adding value to clinical practice, and more importantly, improving the quality of care (Vrontis et al, 2022).

The theoretical outline shown in Figure B highlights the linkage between key variables in the health innovation ecosystem as well as the relationship between them. Every health system has social, political, cultural and economic factors that influence healthcare leadership, diffusion of innovation, choice of care models and access to health care solutions. Thus, an ideal intervention to improve care delivery starts with technology diffusion for better diagnosis, treatment and control of diseases/illnesses.

Figure C: Theoretical Framework for the Study

Source: The Author (2022)

The scope and conceptual framework indicate that preventive measures taken to reduce morbidity and mortality arising from exposure to behavioural risk factors are more likely to fall among the cost-effective interventions. In other words, innovation-driven health solutions have proven potentials to relieve governments and health systems of the ill-health and economic burden created by non-communicable diseases (NCDs) (Gupta et al, 2015).

From the perspective (conceptualization) of health innovation, Figure C shows that inefficiencies in the health innovation ecosystem eventually result in consistently fewer chronic illnesses being diagnosed, treated and controlled—thereby lowering health outcomes and economic output. The cyclic relationship can create health-related poverty in the sense that ‘poor health causes poverty and access to quality health care is dependent on an individual’s purchasing power.’ On the other hand, the bi-directional linkage between socioeconomic factors and diagnosis, treatment and control of chronic illness show there are underlying socioeconomic factors that limit access to health care in every system, especially in countries implementing the out-of-pocket model.  According to Li and Garnsey (2014), some models of care are formulated to support the status quo and further impoverish individuals and households who are supposed to be the main beneficiaries.

Evidence-based research indicates that data transformation, analytic transformation, payment transformation and care transformation cannot be achieved without strategic management. But digital health technologies provide massive opportunities for every health system to improve outcomes for laboratories, health organizations, GPs, and most importantly, patients. When compared with other sectors in the global economy, findings show that transformation in healthcare management, particularly diagnostics, has recently taken a new dimension notwithstanding the fact that health providers are yet to maximize the full potentials of analytics, machine learning, and other DH technologies (Ziadlou, 2021).

Figure D: Innovation in Health Services

Source: The Author (2022)

Health care delivery in Nigeria is facing serious challenges, and health administrators do not have a fail-proof blueprint for transforming health care services beyond the need to remove financial barriers and make health care easily accessible. Inadequate funding of the health sector as well as rapid technological change have also constrained the system’s ability to respond effectively (Patricio et al, 2020). Further, technology adoption in health care has increased specialization among health professionals thereby increasing demand for health-related professionals and paraprofessional groups. Transformation in the areas of data, analytics, payment and care has thus increased differentiation and specialization of health facilities—a laudable achievement that makes coordination of health services somewhat cumbersome. On this premise, innovation-driven health care is fast becoming more fragmented, expensive and still inaccessible in rural areas (Kozlowska et al, 2020).

These concerns about healthcare management at the PHC level have rapidly increased interest in innovation within the health care system, particularly the multifaceted challenges associated with acquisition and use of new DH technologies to improve health care delivery. However, all innovative health management strategies provided in this study, especially their applicability in health systems in operational terms, are implicit and sourced from a wide range of publications.

References

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