Business Intelligence Applied to the Economic Feasibility Analysis of Projects in the Orthopedic Implants Sector

Daniella Benevides de Oliveira; Elias Soares De Figueiredo

DOI: 10.22167/2675-6528-202602814

Article derived from a Final Course Work (TCC), with content based on the student’s original work and adapted to the editorial format of the E&S Magazine with the support of the ResumeAI tool, an artificial intelligence solution developed by Instituto Pecege for textual synthesis and organization.

Summary

Project evaluation in the medical device sector requires the integration of market data, analytical methods, and economic-financial assumptions under uncertainty. The study aimed to develop an economic feasibility analysis for hip orthopedic implant projects in Brazil, with an emphasis on Data Science and Business Intelligence. Public data from the Hospital Information System of the SUS (2008-2025) and the Information System of Products of the National Agency for Supplementary Health (2014-2024) were used. After processing, the DATASUS database totaled 72 national annual observations and the ANS database, 11 annual observations. The analytical flow included cleaning, validation, exploratory analysis, linear regression, exponential smoothing, construction of a proxy for the supplementary market, confidential external validation, and modeling of the Free Cash Flow to Firm. The results showed structural growth in primary uncemented total hip arthroplasty and economic viability in the conservative, base, and optimistic scenarios, with an Internal Rate of Return higher than the Minimum Attractive Rate of Return and a positive Net Present Value. The findings were consolidated in a Business Intelligence dashboard. It was concluded that traceable integration between public data, explicit assumptions, and financial evaluation offers consistent support for project prioritization in the orthopedic industry.

Keywords: Business Intelligence; Public health data; Medical devices; Demand projection; Economic feasibility.

1. Introduction

The Brazilian health sector faces growing challenges in planning and evaluating project feasibility. This complexity is multifaceted, stemming from the system’s structure itself, regional inequalities, and the limitations of financial resources available for investment. In a constantly evolving scenario, strategic decision-making becomes a crucial element for the success and sustainability of initiatives in the sector.

In the context of high-complexity surgical procedures, such as hip arthroplasties, these challenges are even more pronounced. The decision regarding the development of new prostheses in this segment is influenced by multiple factors, including population aging, the continuous incorporation of technological innovations, the conditions of the healthcare infrastructure, and the reliance on administrative and regulatory data. Such aspects create an uncertain decision-making environment, requiring structured analyses to support consistent strategic choices (Mendes, 2015; Sharda; Delen; Turban, 2019).

Osteoarticular diseases represent one of the main causes of functional limitation, significantly impacting the population’s quality of life. Globally, musculoskeletal conditions are an important source of disability, especially in contexts of population aging (World Health Organization, 2023). This scenario increases the potential demand for procedures that restore mobility and reduce pain, among which hip arthroplasties stand out.

Hip replacement surgeries encompass various techniques, such as uncemented primary total arthroplasty, cemented, partial, and revision or conversion procedures. These modalities have distinct clinical and technological characteristics and are performed in both the Unified Health System (SUS) and the supplementary sector. SUS hospital production can be consulted in the Hospital Information System (SIH/SUS), while the National Supplementary Health Agency (ANS) provides healthcare data through the Product Information System (Brasil, 2026; ANS, 2026).

Despite the availability of these data sources, there is a gap in integrated quantitative analyses specifically focused on industrial planning and the economic feasibility assessment of orthopedic projects (Vercellis, 2009; Sharda; Delen; Turban, 2019). In this context, the use of analytical approaches based on Business Intelligence (BI) becomes fundamental. BI transforms historical data into structured information that supports strategic decision-making, especially in industrial projects, where early decisions impact future costs and deadlines.

More than a set of technological tools, Business Intelligence is understood as an analytical framework capable of transforming scattered operational data into structured information, supporting market analysis, industrial planning, and investment evaluation (Sharda; Delen; Turban, 2019; Knaflic, 2019). This approach is particularly relevant in regulated sectors, where long-term decisions need to consider uncertainties, economic cycles, and the occurrence of external shocks.

The motivation for the development of this study arises from the practical observation of the challenges faced in evaluating industrial projects in the orthopedic sector, especially regarding demand uncertainty and the economic sizing of new products. The absence of structured analyses tends to increase the risk of decisions based on isolated perceptions or poorly founded estimates, which can compromise the financial sustainability of long-term investments (Mendes, 2015; Gitman, 2010). Given this scenario, the general objective was to develop an applied economic feasibility analysis for hip implant projects in Brazil.

2. Material and Methods

The study was conducted as an applied research, with a quantitative approach and descriptive character, configuring itself as a case study. The unit of analysis was the evaluation process of a hip implant project in a medium-sized Brazilian company in the medical device sector, located in the state of São Paulo. The methodology employed secondary data and ensured the confidentiality of the company’s strategic information, presenting it only by indices, percentages, and deadlines, without the use of personal identifiers (Malhotra, 2004; Gil, 2017; Yin, 2015; Bigaton et al., 2024).

Public data sources included Hospital Production from the Hospital Information System of SUS (SIH/SUS), accessed on TABNET, and the semi-annual healthcare data spreadsheets from the National Supplementary Health Agency (ANS), obtained from the Product Information System. From SIH/SUS, data from January 2008 to December 2025 were collected for hip arthroplasties (SIGTAP codes 0408040092, 0408040084, 0408040050, 0408040068, and 0408040076), aggregated by UF, year, and category (Brazil, 2026). From ANS, data on “arthroplasty revision” from 2014 to 2024 were collected, used as a proxy for the supplementary sector due to its aggregated nature (ANS, 2023; ANS, 2026).

The analytical protocol was organized into six sequential steps: collection and understanding of sources; treatment and quality control; exploratory analysis; trend and demand modeling; external validation and economic-financial evaluation; and communication of results in Business Intelligence. Microsoft Excel was the main tool for data wrangling, statistical calculations, projections, and cash flow, while Power BI was used for the organization and communication of results in an executive dashboard.

Data wrangling in Excel involved standardizing dates, grouping SIGTAP codes, unifying federative units, and validating keys. Of the 1,944 possible combinations in the DATASUS matrix, 102 empty cells (5.25%) were converted to zero, as they represented absence of occurrence, without volume interpolation (Kandel et al., 2011; Fávero; Belfiore, 2017). The drops in 2020 and 2021 were maintained as real observations, reflecting the impact of the pandemic.

The demand modeling included a simple linear regression for uncemented primary total hip arthroplasty in the SUS (2008-2025), projecting the central trajectory until 2035 (Kutner et al., 2004). For market sizing, an annual ratio between the ANS review indicator and hip reviews/conversions in the SUS (2014-2022) was calculated, applying it to the volume of primary uncemented hip arthroplasties in the SUS to estimate the private sector. The potential market for devices was expressed by M₁ = 2 × (S₁ + P₁), considering the acetabulum and femoral stem.

The projections of the annual SUS series and the supplementary estimate (2014-2024) were carried out separately by the FORECAST.ETS function of Excel, with the central projections summed and used until 2032, maintaining the volumes of 2033 and 2034 at the 2032 level. Market shares of 2.5%, 5%, and 10% were applied for conservative, base, and optimistic scenarios. An aggregate estimate from an external consultant for 2022 was used for external validation of the order of magnitude, by triangulation of evidence (Yin, 2015).

The economic-financial assessment covered a horizon from 2025 to 2034. The Firm’s Free Cash Flow (FCFF) was calculated considering IRPJ and CSLL of 34% (when EBIT is positive), linear depreciation, working capital requirement of 5% of net revenue, and recovery of this capital in the last period. Prices and costs were maintained in real terms, with a real Minimum Attractiveness Rate (TMA) of 15% per year (Gitman, 2010; Meyer; Paixão, 2018). Simple Payback, Discounted Payback, Net Present Value (NPV), and Internal Rate of Return (IRR) were calculated. The sensitivity of the base scenario was tested by isolated shocks in price, unit cost, demand, and TMA.

3. Results and Discussion

The analysis of the economic viability of projects in the orthopedic implants sector revealed crucial insights into the dynamics of the Brazilian market, the evolution of surgical techniques, and the financial potential of investments. The results obtained, based on public data and strategic premises, allowed for a deep understanding of the trends and factors influencing decision-making in this highly complex segment. The integrated approach of Data Science and Business Intelligence proved effective in transforming raw data into actionable information, in line with the central objective of the study.

Initially, the characterization of the DATASUS and ANS databases was fundamental to establish the robustness of the analysis. The DATASUS database, covering the period from 2008 to 2025, provided 1,944 combinations of federative unit, year, and surgical category, consolidated into 72 annual national totals. The ANS database, in turn, covering from 2014 to 2024, gathered 22 semi-annual observations, consolidated into 11 annual totals. The rigorous treatment of this data, including standardization, grouping of SIGTAP codes, and conversion of empty cells to zero, ensured quality and consistency for the subsequent modeling and projection stages, avoiding volume interpolations that could distort the observed trends (Kandel et al., 2011; Fávero; Belfiore, 2017).

Evolution of primary arthroplasties in the SUS

The evolution of uncemented primary total hip arthroplasty in the Unified Health System (SUS) has shown a consistent growth trajectory throughout the analyzed historical series. Since the early years of the observed period, the volume of procedures has shown gradual expansion, with more evident acceleration in the interval before 2019, indicating the progressive consolidation of this technique in the public system. This growth pattern suggests increasing acceptance of the uncemented technique, possibly driven by technological advancements and better clinical outcomes, making it a strategic focus for new projects.

With the onset of the Covid-19 pandemic, a temporary interruption of this trajectory was observed, characterized by a significant drop in the number of procedures in 2020 and 2021. This behavior was attributed to restrictions imposed on elective surgeries and the reorganization of hospital care capacity. In the subsequent period, between 2022 and 2025, a consistent recovery was observed, with accelerated recovery and volumes that surpassed pre-pandemic levels, reinforcing the presence of a positive structural trend and the resilience of demand for this surgical modality, even in the face of external shocks.

In contrast, the cemented total primary arthroplasty series showed a gradual reduction over the period, noticeable even before the pandemic. The subsequent recovery did not re-establish the initial levels observed, indicating a persistent shift in the composition of procedures performed in the SUS. This decline in the cemented technique, as opposed to the growth of the uncemented one, suggests a growing preference for less invasive or more durable approaches, aligning with global trends in medical device innovation (World Health Organization, 2023).

Partial hip arthroplasty, in turn, remained in a relatively stable range, despite fluctuations and a temporary interruption in 2020. This stability, compared to other techniques, indicates that partial hip arthroplasty occupies a specific niche in the treatment of hip conditions, without the same growth or decline dynamics observed in total hip arthroplasties. Reading these trends together showed that the uncemented technique was the only one to combine a higher recent volume with a sustained growth trajectory, while the cemented technique declined and the partial technique varied within a narrower range.

The comparison between the four categories of arthroplasties analyzed – uncemented, cemented, partial, and revision/conversion – revealed that an aggregated reading of the market would hide distinct trajectories and, therefore, valuable information for investment decisions. Segmentation by surgical technique was decisive in directing the feasibility study to components associated with uncemented fixation. This detailed approach is crucial for industrial planning, as it allows for the identification of segments with the greatest potential for growth and return, optimizing resource allocation and minimizing risks (Mendes, 2015).

Revision surgeries and comparison between the systems

Hip revision or conversion surgeries in the SUS and the aggregated indicator of arthroplasty revision by ANS showed greater volatility compared to the primary series. Both indicators registered a sharp drop in 2020, followed by a subsequent recovery. This simultaneous reduction in both systems is compatible with the postponement of elective procedures during the Covid-19 pandemic, an external shock that profoundly affected healthcare systems globally (Sharda; Delen; Turban, 2019).

However, the recovery occurred at different intensities between the SUS and the supplementary sector, indicating distinct dynamics of access and healthcare capacity. In 2024, both indicators remained above 2020 levels, but the supplementary series continued to be higher in absolute values. This comparison should be interpreted as evidence of relative behavior between the systems, and not as clinical equivalence, since the ANS indicator aggregates arthroplasty revisions without discriminating the specific joint, which constitutes an important limitation for direct inferences about the hip market.

Projection of primary uncemented total hip arthroplasty

The demand projection for primary uncemented total hip arthroplasty in the SUS was performed using a simple linear regression, which estimated an average growth of 810 procedures per year. The model presented a coefficient of determination (R²) of 0.720, a mean absolute error of 1,688 procedures, a root mean squared error of 2,624, and a mean absolute percentage error of 18.1%. The regression slope was statistically different from zero, with p < 0.001, indicating a significant relationship between time and the volume of procedures.

The model fit was considered moderate, an expected outcome given the disruption observed in 2020 due to the pandemic and the acceleration of recovery from 2022 onwards. Retaining the pandemic years in the historical series, although it reduced the fit compared to a smoothed series, was a prudent choice to represent the effectively observed variability and incorporate the risk inherent in external shocks. Anchored to the last observed point, the central projection trajectory remained increasing until 2035, providing a basis for long-term planning.

The operational bands of uncertainty, which widened with the projection horizon, were used solely to communicate potential demand variability, not as formal statistical intervals. This distinction is crucial, as these bands do not support probabilistic tests and, therefore, were not used as direct input in the financial assessment. This approach reflects the need to balance statistical precision with managerial prudence in an environment of uncertainty, as advocated by authors such as Kutner et al. (2004).

Construction of the market sizing hypothesis

The construction of the market sizing hypothesis involved the integration of data from the SUS and the supplementary sector. In the common window up to 2022, the ANS review indicator remained consistently above SUS hip reviews or conversions in most years. Both indicators registered a drop in 2020 and a subsequent recovery, providing the empirical basis for constructing a proxy for the supplementary sector. This relationship allowed for the estimation of private sector demand in a traceable manner and consistent with available public data.

The application of the annual ratio between the ANS indicator and SUS reviews to the series of uncemented SUS arthroplasties resulted in an estimate for the supplementary sector that proved superior to the public count throughout the analyzed window. The drop observed in 2020 was preserved in the proxy, avoiding the creation of an artificially continuous trajectory and ensuring that the estimate reflected real market conditions. This methodology allowed for a more faithful representation of total demand, considering the particularities of each healthcare system.

To convert the volume of surgeries into potential demand for components, it was considered that each hip arthroplasty procedure requires two main components: acetabulum and femoral stem. This unit of analysis approximates the clinical market to the industrial object being evaluated, avoiding treating a surgery as equivalent to a single part and providing a more precise basis for production sizing. The potential market for devices was then expressed as double the sum of the number of uncemented surgeries in the SUS and the estimate from the supplementary sector.

To bring the combined market to the financial horizon, the annual series of SUS and the supplementary estimate between 2014 and 2024 were projected separately using Excel’s FORECAST.ETS function. This function, with automatic seasonality detection and enabled missing point imputation, operated without an intra-annual cycle and without effective imputation, given the annual periodicity and the absence of gaps. The central projections were summed, multiplied by two components, and used until 2032, with the volumes for 2033 and 2034 maintained at the 2032 level out of prudence. On this total market, shares of 2.5%, 5%, and 10% were applied, denominated as conservative, base, and optimistic scenarios, respectively.

The estimate obtained for the year 2022 showed the same order of magnitude as the sectoral benchmark provided by an external consultant specializing in the Brazilian orthopedic implants market. This convergence was interpreted as external validation of the estimate’s plausibility, rather than proof of accuracy, given that the sources and methods used by the consultant and the study were distinct. The consultant’s estimate, which was confidential, was not incorporated into the cash flow but served as an important point of evidence triangulation (Yin, 2015).

Economic-financial evaluation and Business Intelligence panel

The economic-financial evaluation of the project covered a horizon from 2025 to 2034, with two years dedicated to development and eight years to commercial operation. The Free Cash Flow to Firm (FCFF) was calculated considering Earnings Before Interest and Taxes (EBIT), income taxes, depreciation, Capital Expenditure (CAPEX) investments, and Net Working Capital Change (ANCG). IRPJ and CSLL of 34% were considered only when EBIT was positive, linear depreciation of identifiable assets, working capital requirement equivalent to 5% of net revenue, and recovery of this capital in the last period. Prices and costs were kept in real terms, and a real and single Minimum Attractiveness Rate (TMA) of 15% per year was adopted (Gitman, 2010; Meyer; Paixão, 2018).

The three market share scenarios (conservative, base, and optimistic) produced positive operational flows after the start of commercialization. The expansion of market share resulted in greater cash generation and a reduction in the investment recovery period. The application of taxation, depreciation, and working capital ensured that the comparison between scenarios was carried out on a common and consistent basis, reflecting the real financial and fiscal conditions of the project. FCFF became positive in the first year of commercial operation in all scenarios and grew in line with projected demand, with flows indexed by the initial investment, equal to 100, and working capital recovery incorporated in the last period.

The simple Payback and discounted Payback indicators were calculated for each scenario. In the conservative scenario, the simple Payback was estimated at 4.27 years and the discounted at 6.54 years. In the base scenario, the periods were 2.82 years for the simple Payback and 3.58 years for the discounted. In the optimistic scenario, the periods were 2.04 years for the simple Payback and 2.34 years for the discounted. In all cases, the discounted Payback was higher than the simple one, which is expected when future cash flows are brought to present value by the WACC of 15%, reflecting the opportunity cost of capital.

The Net Present Value (NPV) remained positive in all three scenarios and demonstrated an increase proportional to market share. To preserve the confidentiality of the company’s strategic information, the NPV was presented as a ratio between the NPV and the initial investment, without disclosing the absolute amounts. This positive result in all scenarios reinforces the project’s viability, even under more restrictive conditions, and indicates that the value generated by the project exceeds the cost of the invested capital.

The estimated Internal Rates of Return (IRRs) were 21.6% in the conservative scenario, 41.2% in the base scenario, and 68.4% in the optimistic scenario. All these IRRs were higher than the real Minimum Attractiveness Rate (MAR) of 15% per year, confirming the financial attractiveness of the project. Although the conservative scenario presented the smallest safety margin, it still preserved the financial acceptance criterion, indicating that the project is capable of generating returns above the cost of capital in all considered projections.

Sensitivity analysis indicated that the selling price and unit cost exerted the greatest influence on the NPV, followed by demand and the MARR. Within the isolated ranges of variation of ±20% in the base-case assumptions, the NPV remained positive. This result does not equate to the probability of joint occurrence of all shocks, but it highlights which assumptions require priority monitoring for project management. The ability to identify and quantify sensitivity to different variables is fundamental for risk management and strategic decision-making (Mendes, 2015).

The results were consolidated in a Business Intelligence (BI) dashboard, which brought together market evolution, participation scenarios, accumulated flows, and viability indicators. The dashboard acted as a communication and exploration layer for the results, allowing navigation by scenario and comparison of findings without exposing the internal monetary values of the work, which remained confidential. The financial calculations were kept in Excel to preserve traceability between assumptions, formulas, and checks, ensuring the transparency and auditability of the analytical process (Sharda; Delen; Turban, 2019; Knaflic, 2019).

Synthesis of the economic-financial evaluation

In an integrated manner, the results demonstrated that the selection of the primary uncemented arthroplasty segment was supported by public evidence of growth, by an explicit proxy of the supplementary market, and by a robust financial assessment, subject to scenarios and sensitivity analysis. The value of Business Intelligence resided in the traceable connection between all stages of the analysis, from data collection to final visualization, and not just in the presentation of results. This traceability is essential for the credibility and reviewability of the model.

Even with two initial years without revenue, the inclusion of incremental working capital, taxation on profit, and the adoption of a real WACC of 15%, the project maintained a positive NPV and an IRR higher than the benchmark rate in all three scenarios. The feasibility conclusion, however, depends on the realization of market share, price, cost, and demand assumptions, and should be re-evaluated as new data becomes available. This caveat highlights the dynamic nature of project evaluation and the need for continuous monitoring of assumptions.

Strategic direction of the study

The strategic direction of the study for the development of uncemented acetabular and femoral stems stemmed from the combination of the historical growth trend of this technique, its technological complexity, and its economic potential. The decision to preserve the pandemic series in the data and to maintain the final two years of the market at the 2032 level was a deliberate choice to reduce the risk of overestimating demand. This prudent approach ensures that the projections reflect a more realistic and conservative scenario, aligned with best practices for project management in uncertain environments.

In summary, the research demonstrated that primary uncemented total arthroplasty presents the most favorable trajectory among the analyzed techniques, justifying the project’s focus on this segment. The integration of public data, demand projections, and a rigorous economic-financial evaluation, consolidated in a Business Intelligence panel, offers consistent and traceable support for prioritizing projects in the orthopedic industry. The findings confirm the project’s economic viability in the conservative, base, and optimistic scenarios, with financial indicators that exceed acceptance criteria, providing a solid basis for strategic decision-making.

4. Conclusion

The study sought to develop an economic feasibility analysis for hip orthopedic implant projects in Brazil, focusing on the application of Data Science and Business Intelligence. A structural growth in uncemented primary total hip arthroplasty was observed in the Unified Health System, even after the temporary interruption caused by the pandemic. In contrast, the cemented technique showed a decline, while partial hip arthroplasty remained stable. Segmentation by surgical technique proved crucial for the project’s strategic direction. Demand was projected by integrating public SUS data with a proxy built for the supplementary sector, resulting in an estimate of the potential market for acetabular components and femoral stems. The economic-financial evaluation indicated feasibility in the conservative, base, and optimistic scenarios, with a positive Net Present Value and an Internal Rate of Return higher than the Minimum Attractive Rate of 15% per year. The main contribution lies in demonstrating how traceable integration between public data, explicit assumptions, and rigorous financial evaluation, consolidated in a Business Intelligence dashboard, offers consistent support for project prioritization in the orthopedic industry.

However, limitations were identified stemming from the administrative nature of the databases, the absence of disaggregation by articulation in the National Supplementary Health Agency’s review indicator, and the use of operational bands, rather than formal intervals, in linear projection. Business confidentiality also restricted the disclosure of absolute monetary values, which were presented only by indices and percentages. For future studies, annual updating of the series, testing of alternative predictive models through out-of-sample validation, obtaining supplementary specific data by articulation, and incorporating regional analyses are recommended. The developed methodology can be adapted to other orthopedic segments, such as spine, knee, and trauma, provided that the premises and proxies are revalidated for each specific market. The project’s feasibility, therefore, depends on the realization of market share, price, cost, and demand premises, requiring continuous monitoring and reassessment as new information becomes available.

Bibliographic References

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Brasil. Ministério da Saúde. Departamento de Informática do SUS [DATASUS]. 2026. Produção Hospitalar (SIH/SUS): dados consolidados de AIH, por local de internação, a partir de 2008. Disponível em: <https://datasus.saude.gov.br/acesso-a-informacao/producao-hospitalar-sih-sus/>. Acesso em: 31 jul. 2026.

Mendes, G. H. S. 2015. Administração estratégica. Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil.

Sharda, R.; Delen, D.; Turban, E. 2019. Business intelligence e análise de dados para gestão do negócio. 4. ed. Bookman, Porto Alegre, RS, Brasil.

Vercellis, C. 2009. Business intelligence: data mining and optimization for decision

World Health Organization [WHO]. 2023. Musculoskeletal conditions. WHO, Geneva, Switzerland.

Article originating from the Final Course Work of the Specialization in Data Science and Analytics of the MBA USP/Esalq

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