Abstract
Improving quality of care is one of the priorities of policymakers in the U.S. While the spending on quality of care in the U.S. is the highest among all the developed nations, the desired health outcomes achieved have been below many of them. The largest portion of personal health care spending in 2019 went toward hospital care (37.2%), which was followed by physician and clinical services (24.1%). In this chapter, the authors focus on these direct care services, specifically explaining how hospitals and clinics can improve health and financial outcomes using data analytics. Specifically, building on CRISP-DM, a data mining process model, the authors explain the healthcare data analytics processes for hospitals and clinics to improve quality and financial performance.
Top1. Introduction
The World Health Organization defines quality of care as the “degree to which health services for individuals and populations increase the likelihood of desired health outcomes.” Improving quality of care is one of the priorities of policymakers in the U.S. While the spending on quality of care in the U.S. is the highest among all the developed nations, the U.S was ranked poorly in several measures of wellbeing or desired health outcomes (cms.gov, 2023). For example, health spending accounted for 18.3 percent of the nation's Gross Domestic Product, while life expectancy is 77 (85 in Japan, the highest) and obesity hits an all-time high (40% in adults) (cms.gov, 2023). To address these public concerns, the U.S. healthcare system extensively supports initiatives and policies to reduce the cost and improve the quality of care, such as population health and prevention, value-based care, patient-centered care, electronic health records and price transparency (Kocher et al., 2010; Afrizal et al., 2019; Hajian et al., 2023).
In this chapter, we focus on direct care services, specifically how hospitals and clinics can improve health and financial outcomes using data analytics. Two main groups of institutions contribute to the quality of care in the U.S.: those that provide direct care to patients (such as hospitals, clinics, and treatment centers), and those that support the care of individuals through products and services (such as pharmaceuticals, insurance, and population health organizations). The largest portion of personal health care spending in 2019 went toward hospital care (37.2%), which was followed by physician and clinical services (24.1%) (cdc.gov, 2023). The main function of hospitals is to provide medical treatment and care to patients with illnesses, injuries, or other health conditions. Hospitals also offer emergency care, diagnostic testing, surgery, rehabilitation, and inpatient and outpatient care. Some large size hospitals serve as a center for research and education, providing opportunities for medical professionals to advance their knowledge and skills. Additionally, hospitals play a crucial role in public health, providing vaccinations and disease control measures, and serving as a resource for health information and education for the community.
While hospitals and clinics account for a significant portion of the healthcare spending, their profit margins are narrow. Some hospitals, particularly large academic medical centers, may operate at a loss or with very thin margins due to the high cost of providing complex medical services, conducting research, and training medical professionals. On the other hand, smaller, community hospitals or specialized facilities may be more profitable due to their lower overhead costs and more favorable payer mix. Large or small, all hospitals and clinics are price-takers, meaning they do not have the power to influence the market price of their services. In other words, hospitals accept the prevailing market price often set by the government and insurers and cannot negotiate a higher or lower price for their services.
Since hospitals cannot control prices, they aim to minimize their cost as well as maximize their revenue from insurers. Particularly, in recent years, the hospitals have faced financial pressures, including increasing competition, declining reimbursement rates, and rising costs for labor, supplies, and technology. Many hospitals have sought to reduce costs and improve efficiency, while also exploring new revenue streams, such as outpatient services, telemedicine, and partnerships with other healthcare providers. Ultimately, the profitability of hospitals is a complex and dynamic issue that is influenced by a range of economic, regulatory, and demographic factors. With the Affordable Care Act, hospital reimbursements from insurers are closely tied to their quality performance. Hospitals are financially penalized due to their relatively low-quality performance (Barnes et al., 2018).
Key Terms in this Chapter
Direct care services: Direct care services refer to health care services that are provided directly to patients or clients by a health care professional or caregiver. These services are typically provided in a clinical or home care setting and involve direct interaction between the patient and the health care provider (e.g., hospitals, clinics, and treatment centers).
Affordable Care Act: The Affordable Care Act (ACA), also known as Obamacare, is a law passed in the United States in 2010 with the aim of increasing access to health insurance and improving the quality and affordability of health care.
Co-creation in healthcare: Co-creation in healthcare refers to a collaborative approach in which patients, caregivers, and healthcare providers work together to design and deliver health care services. Co-creation recognizes that patients and their caregivers have valuable insights and expertise that can contribute to improving the quality and effectiveness of healthcare services.
Service Delivery: Service delivery is simply the execution of service designs to achieve the desired outcomes.
Business Intelligence (BI): Generally located within the larger concept of Business Analytics, Business Intelligence refers to gathering, filtering, and presenting data from various sources such as internal and external databases, and data warehouses to support business decision-making.
Quality of Care: The World Health Organization (WHO) defines quality of care as “the extent to which health care services provided to individuals and patient populations improve desired health outcomes.” This definition emphasizes the importance of focusing on the outcomes that matter most to patients and populations, and on the effectiveness of health care services in achieving those outcomes.
Exploratory Data Analysis (EDA): Exploratory Data Analysis (EDA) is a data analysis approach involving an initial, critical examination of the data to identify patterns and anomalies typically conducted using summary statistics and basic visualizations.
Healthcare Quality: Healthcare quality refers to the degree to which health services meet the needs, expectations, and preferences of patients, and are consistent with current medical knowledge and best practices. Healthcare quality is essential for ensuring that patients receive safe, effective, timely, patient-centered, and equitable care.
Key Performance Indicators (KPIs): Key Performance Indicators (KPIs) are metrics used to monitor the performance of an organization or a business process. Managers can use KPIs to determine whether the organization is achieving its desired outcomes, presented on a dashboard in a website or a mobile device app. Examples of KPIs include revenues, employee turnover rate, number of products assembled on the factory floor, or number of patients discharged.
Data Visualization: Data Visualization refers to presenting the data in a chart with visual elements like different colors, shapes, and sizes to understand and communicate patterns, trends, and relationships that may be hidden in the raw data.
Indirect care services (Support services): Indirect care services refer to health care services that support or facilitate the delivery of direct care services, but are not provided directly to patients (e.g., pharmaceuticals, insurance, and population health organizations).
Plan-Do-Check-Act (PDCA) Cycle: The Plan-Do-Check-Act (PDCA) cycle is a continuous improvement model used in many industries, including health care, to improve processes and achieve better outcomes. It is an iterative data-driven problem-solving technique that was first developed by American physicist Walter Shewhart in the 1920s. In the 1950s, Edwards Deming popularized the technique and named the cycle the “Shewhart” Cycle.
Service Design: Service design is the activity of planning people, infrastructure, communication, and material components of a service in order to achieve the desired outcomes.
Business Analytics: Business analytics refers to the use of statistical, computational and data mining techniques in functional areas of business such as marketing, finance, and operations to extract insights from data that can be used to make data driven business decisions.
Data Mining: Data mining refers to the process of discovering patterns, trends, and relationships within datasets using the techniques and algorithms in Supervised and Unsupervised Learning.
Unsupervised Machine Learning: Unlike supervised machine learning where the input data includes a target variable, unsupervised machine learning algorithms are not provided with any target variable. Instead, Unsupervised Machine Learning refers to methods to discover patterns, relationships, and structures in the data set without any prior knowledge or guidance. Association and cluster analysis are examples of Unsupervised Machine Learning.
Supervised Machine Learning: This is a type of machine learning approach where the objective is to build a model that can learn the relationship between the input variables (predictors) and the target variable (predicted) so that the model can make accurate predictions on new, unseen data. Predictive analytics (e.g. linear regression and decision tree techniques) is part of Supervised Machine Learning.