The purpose of and benefits from conducting program evaluations are described in this section. Accreditation of healthcare services is instrumental to terminate unpopular programs and to open up new and innovative ones. Healthcare policy makers use program evaluations to improve healthcare and social services. The evaluating team focuses on the following issues.

This epilogue recaps the major approaches to healthcare decision-making covered in this book, whether those decisions are reached by patients, insurance agents, government agents including policy makers, or healthcare professionals including hospital administrators.

Any adverse event is detrimental to patient welfare and to the reputations of the hospital/clinic, physicians’ or nurses’ licensing agency, and health insurance providers. All healthcare professionals desire to avoid adverse events. The chance for a recurrence of an adverse event could be lessened if health administrators learn from its first occurrence. For this purpose, health administrators perform what is termed root cause analysis (RCA). More often, RCA is done by interdisciplinary professionals and members of the patient community as an interactive team. There are three types of RCA – divergent, serial, or convergent. Which one among the three is medically or intuitively nontrivial? This chapter provides concepts, tools, and remedial plans to address non-repeatability. This knowledge springs from the collection of pertinent data for the selected adversity, an analytic approach to trace the causes, and setting up plans to ensure its nonoccurrence in the future.

What is a decision? A decision is the process of selecting one option over others for the sake of some advantages. The advantages might be a minimal use of time or human resources, or constrained and/or gained profits. When no alternative appears that is better than the chosen decision in any sense, that decision is called the optimal decision. Attaining the optimum decision is not quite trivial at times due to the complexity of reality. The decision maker is often in need of technical experts called analysts who can simplify, organize, and make the decision easier for the decision maker. Decision-making is a cooperative effort to reach the optimal decision. When these joint efforts succeed, the decision maker and the analyst are appreciated and applauded. When the decision results in failure with a measurable loss, the decision maker is blamed. The decision maker therefore undertakes full responsibility for directing the decision-making process.

First, let us examine the role of uncertainty in scientific inquiries in general and in healthcare decision-making in particular. Weurlander (2020) warns physicians to be careful to deal with uncertainty before making decisions to treat patients. Koffman et al. (2020) discuss reasons for involving uncertainty in healthcare, especially with respect to the COVID-19 pandemic. Uncertainty is not easily defined because of inadequate, incomplete, and ambiguous information.

Many occurrences in personal and professional life exhibit patterns of complete unpredictability – climate, disease outbreaks, financial volatility, natural disasters. Especially in healthcare, a specified outcome might be seen or missing. This vagueness is framed as uncertainty and raises fundamental challenges. Understanding how uncertainties appear is perhaps the beginning of solving this issue. Like an atom can be decomposed to its constituent parts of electrons, neutrons, and protons, the probability of uncertainty can be decomposed to its axioms. Refer to Camio et al. (2019) and Scoones (2019) for more discussion of how uncertainty is identified and illustrated.

First, let us examine why decisions become more authentic and accurate when they are based on evidence. Not all healthcare professionals are convinced data-based decision-making is prudent. To make such decision-making feasible, knowledge of data collection and its analysis is a necessity. Analysts help decision makers handle these complex technicalities. Rarely does a decision maker encounter only one technicality. Consequently, the decision maker may need more than one analyst.

How do we define an analyst? An analyst has the expertise and the knowledge base to study the available information and to understand the choices in front of the decision maker along with the consequences of each.

How do we define the healthcare administrator as a decision maker? The healthcare decision maker has the responsibility to make the best decision in his or her healthcare practices.

In this chapter, methods to collect data from several reliable sources are articulated first. Then the importance of checking the authenticity of the data source is stated. Storing the collected data in Excel spreadsheets is vital. Refer to Hardin and Kotz (2020) for suggestions on improving data collection and amenability. Surging in popularity, mobile health (mHealth) apps foster research, clinical regimens, and individual well-being.

These procedures encourage proactivity and ongoing accountability for healthcare. For the purpose of addressing pertinent healthcare inquiries and quantifying health outcomes, information gathering and assessment on selected variables within a structure coalesce into a process called data collection, which is an essential step in research in all fields, including healthcare. While methods vary across disciplines, the emphasis of all data collection should be accuracy.

Healthcare administrators working in hospitals, clinics, government agencies, and financial and insurance institutions must probe whether the healthcare services they provide are effective, efficient, and optimal. Health economists and data analysts invest time and effort to project the future performance of the healthcare services their institutions provide. These and related concerns could be answered by time series data analysis and forecasting. Hospital/clinic administrators, healthcare professionals, insurance agents, and patients all desire high-quality healthcare services utilizing a minimal amount of resources.

Developed and developing nations alike notice a percentage of their populations has inadequate health insurance coverage. Resources providers encounter restrictions that forbid financial support to underserved populations, including those with no health insurance coverage. Attempts have frequently been made to raise efficiency and cost-effectiveness in healthcare services. However, to achieve these goals, background knowledge and skill are essential and good understanding of forecasting methods can help healthcare administrators learn, apply, and utilize data to attain their goals. Every constituency involved in healthcare is aware of the necessity to improve the quality of healthcare services on a daily or a periodical basis.

The decision tree is a hierarchical approach to select one among many alternatives and then observing the outcome. The outcome has a different value and a different probability of occurrence. What is a value? A value is a priority. The value can be negative (in dollars) in the case of loss or positive in the case of gain/profit. What is probability? Probability is a numerical speculation of an occurrence in a closed interval [0, 1]. When the probability is zero, the uncertain outcome is unlikely. When the probability is one, the outcome is almost certain.

The expected value is the weighted average of the possible values. Each value is weighted according to its probability of occurrence. The expected value is a guide. Because of the realities of professional and personal life, decision-making is not a one-time action but is repeated.

Six Sigma methods and lean management principles yield high-quality healthcare services to patients in hospitals, clinical, and health agencies. Hence, it is worthwhile to learn, apply, and appreciate them. Six Sigma comprises a rigorous, well-focused, and scientific approach to improve the quality of healthcare operations. Healthcare professionals and patients are equally fond of the Six Sigma methods and lean management principles. The basic Six Sigma concept provides effective incorporation of statistical properties. The approach originated from the so-called Gaussian (normal) frequency pattern. Analysts who desire to apply the Six Sigma methods or lean management principles ought to confirm whether the collected data have Gaussian frequency patterns under their original scale or in a transformed scale.

The variables emerge from a quantitatively measurable attribute of the quality of the sample units. The sample units in this context are patients who receive treatment for an illness or medical professionals who deliver healthcare services to patients. The Six Sigma methods are based on the statistical properties of Gaussian data. Recall from your statistics courses that 99.974% of the standardized Z-values of a measurable attribute/variable fall between −3.0 and 3.0 in their frequency pattern.

Economic value and cost-effectiveness are integral parts of a sound healthcare operation. Cost-effectiveness focuses on quality-adjusted life years (QALY). A cost-effectiveness analysis (CEA) aims to attain maximum health benefits with limited consumption of resources. The cost is, of course, a value gained from the use of resources elsewhere.

The benefits that exist in one program if money is shifted to it from another program are the opportunity cost. The cost of drugs, medicines, staff salaries, equipment, and patients’ out-of-pocket expense are direct costs. Productivity costs include losses due to time. Indirect costs include pain, suffering, adverse outcomes, and so forth.

This chapter examines three software programs that assist users to compute the necessary quantities, make summaries, construct graphical displays – including charts – from data, and create two- and three-dimensional pictures from expressions or numbers.

Microsoft Excel is a module of the Microsoft Office suite of software programs (www.microsoft.com/en-us/download). Excel is composed of several subroutines, Excel commands, through which users can perform calculations. JASP, now in the public domain (https://jasp-stats.org), was created and is supported by the University of Amsterdam in the Netherlands. Input data for analysis by JASP need to be entered in an Excel spreadsheet, saved as a comma-delimited (.CSV) file, and fed to JASP software. Microsoft Math Solver, developed and maintained by the Microsoft Corporation, is free to download. It allows users to solve math and science problems. It was developed and maintained by the Microsoft Corporation.